From 4881c2bfb474b36034ca6614e8a3ce465a2f4231 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 09:08:03 -0700 Subject: [PATCH 01/36] chore(deps): upgrade to langgraph-checkpoint 3.0 and redisvl 0.11 - Upgrade langgraph-checkpoint from >=2.0.21,<3.0.0 to >=3.0.0,<4.0.0 - Upgrade redisvl from >=0.5.1,<1.0.0 to >=0.11.0,<1.0.0 - Update Python requirement from >=3.9,<3.14 to >=3.10,<3.14 (Python 3.9 EOL) - Remove Python 3.9 from classifiers - Update Black target-version to remove py39 BREAKING CHANGE: Drops Python 3.9 support, now requires Python 3.10+ Addresses security vulnerability CVE-2025-64439 in langgraph-checkpoint --- poetry.lock | 173 ++++++++++++++++++++++++++++++++----------------- pyproject.toml | 9 ++- 2 files changed, 117 insertions(+), 65 deletions(-) diff --git a/poetry.lock b/poetry.lock index 9d6c1ab..b3fcaea 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,5 @@ # This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. [[package]] name = "aioconsole" @@ -14,6 +15,7 @@ files = [ [package.extras] dev = ["pytest", "pytest-asyncio", "pytest-cov", "pytest-repeat", "uvloop"] +dev = ["pytest", "pytest-asyncio", "pytest-cov", "pytest-repeat", "uvloop"] [[package]] name = "aiofiles" @@ -221,7 +223,7 @@ files = [ {file = "cffi-1.17.1-cp39-cp39-win_amd64.whl", hash = "sha256:d016c76bdd850f3c626af19b0542c9677ba156e4ee4fccfdd7848803533ef662"}, {file = "cffi-1.17.1.tar.gz", hash = "sha256:1c39c6016c32bc48dd54561950ebd6836e1670f2ae46128f67cf49e789c52824"}, ] -markers = {main = "platform_python_implementation == \"PyPy\"", dev = "python_version > \"3.9.1\" or platform_python_implementation == \"PyPy\""} +markers = {main = "platform_python_implementation == \"PyPy\""} [package.dependencies] pycparser = "*" @@ -359,6 +361,7 @@ files = [ dev = ["Pygments", "build", "chardet", "pre-commit", "pytest", "pytest-cov", "pytest-dependency", "ruff", "tomli", "twine"] hard-encoding-detection = ["chardet"] toml = ["tomli"] +toml 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+target-version = ['py310', 'py311', 'py312', 'py313'] exclude = ''' ( | \.egg From a189a92197be99cdab9b400af1857402abd1c5de Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 10:28:04 -0700 Subject: [PATCH 02/36] fix(serializer): update JsonPlusRedisSerializer for checkpoint 3.0 API - Update dumps_typed signature to return tuple[str, bytes] (was tuple[str, str]) - Update loads_typed signature to accept tuple[str, bytes] - Remove dumps() and loads() methods (not in SerializerProtocol anymore) - Use orjson with custom _default_handler for LangChain object serialization - Leverage parent's _encode_constructor_args for LC format encoding - Use parent's _reviver for security-checked deserialization - Maintain Interrupt object handling from Issue #113 fix - Add msgpack backward compatibility for old checkpoints BREAKING CHANGE: dumps_typed/loads_typed signatures changed for checkpoint 3.0 The SerializerProtocol interface changed in checkpoint 3.0 to use only dumps_typed and loads_typed (dumps/loads removed), and the signatures now use bytes instead of strings. Addresses CVE-2025-64439 security fix in parent class. --- langgraph/checkpoint/redis/jsonplus_redis.py | 138 ++++++++------ tests/test_jsonplus_redis_serializer_v3.py | 190 +++++++++++++++++++ 2 files changed, 269 insertions(+), 59 deletions(-) create mode 100644 tests/test_jsonplus_redis_serializer_v3.py diff --git a/langgraph/checkpoint/redis/jsonplus_redis.py b/langgraph/checkpoint/redis/jsonplus_redis.py index bb84ced..8b2c274 100644 --- a/langgraph/checkpoint/redis/jsonplus_redis.py +++ b/langgraph/checkpoint/redis/jsonplus_redis.py @@ -1,6 +1,5 @@ -import base64 import logging -from typing import Any, Union +from typing import Any import orjson from langgraph.checkpoint.serde.jsonplus import JsonPlusSerializer @@ -9,26 +8,16 @@ class JsonPlusRedisSerializer(JsonPlusSerializer): - """Redis-optimized serializer using orjson for faster JSON processing. - - This serializer handles the conversion of LangChain objects (including messages) - to and from their serialized format. It specifically addresses the MESSAGE_COERCION_FAILURE - issue by ensuring that LangChain message objects stored in their serialized format - (with 'lc', 'type', 'constructor' fields) are properly reconstructed as message objects - rather than being left as raw dictionaries. - - The serialized format for LangChain objects looks like: - { - 'lc': 1, # LangChain version marker - 'type': 'constructor', - 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], - 'kwargs': {'content': '...', 'type': 'human', 'id': '...'} - } - - This serializer ensures such objects are properly deserialized back to their - original message object form (e.g., HumanMessage, AIMessage) to prevent - downstream errors when the application expects message objects with specific - attributes and methods. + """Redis-optimized serializer using orjson for JSON processing. + + Redis requires JSON-serializable data (not msgpack), so this serializer: + 1. Uses orjson for fast JSON serialization + 2. Handles LangChain objects by encoding them in the LC constructor format + 3. Handles Interrupt objects with custom serialization/deserialization + 4. Applies parent's _reviver for security-checked object reconstruction + + In checkpoint 3.0, the serializer API uses only dumps_typed/loads_typed + with tuple[str, bytes] signatures (changed from tuple[str, str] in 2.x). """ SENTINEL_FIELDS = [ @@ -38,28 +27,77 @@ class JsonPlusRedisSerializer(JsonPlusSerializer): "parent_checkpoint_id", ] - def dumps(self, obj: Any) -> bytes: - """Use orjson for serialization with LangChain object support via default handler.""" - # Use orjson with default handler for LangChain objects - # The _default method from parent class handles LangChain serialization - return orjson.dumps(obj, default=self._default) + def _default_handler(self, obj: Any) -> Any: + """Custom JSON encoder for objects that orjson can't serialize. - def loads(self, data: bytes) -> Any: - """Use orjson for JSON parsing with reviver support, fallback to parent for msgpack data.""" + This handles LangChain objects by delegating to the parent's + _encode_constructor_args method which creates the LC format. + """ + # Try to encode using parent's constructor args encoder + # This creates the {"lc": 2, "type": "constructor", ...} format try: - # Fast path: Use orjson for JSON data - parsed = orjson.loads(data) - # Apply reviver for LangChain objects (lc format) + # _encode_constructor_args needs the CLASS, not the instance + # For LangChain objects with to_json(), use that data for kwargs + if hasattr(obj, "to_json"): + json_dict = obj.to_json() + if isinstance(json_dict, dict) and "lc" in json_dict: + # Already in LC format, return as-is + return json_dict + + # For other objects, encode with constructor args + # Pass the class and the instance's __dict__ as kwargs + return self._encode_constructor_args( + type(obj), + kwargs=obj.__dict__ if hasattr(obj, "__dict__") else {} + ) + except Exception: + # For types we can't handle, raise TypeError + raise TypeError(f"Object of type {type(obj)} is not JSON serializable") + + def dumps_typed(self, obj: Any) -> tuple[str, bytes]: + """Serialize using orjson for JSON. + + Returns: + tuple[str, bytes]: Type identifier and serialized bytes + """ + if isinstance(obj, bytes): + return "bytes", obj + elif isinstance(obj, bytearray): + return "bytearray", bytes(obj) + elif obj is None: + return "null", b"" + else: + # Use orjson for JSON serialization with custom default handler + json_bytes = orjson.dumps(obj, default=self._default_handler) + return "json", json_bytes + + def loads_typed(self, data: tuple[str, bytes]) -> Any: + """Deserialize with custom revival for LangChain/LangGraph objects. + + Args: + data: Tuple of (type_str, data_bytes) + + Returns: + Deserialized object with proper revival of LangChain/LangGraph types + """ + type_, data_bytes = data + + if type_ == "null": + return None + elif type_ == "bytes": + return data_bytes + elif type_ == "bytearray": + return bytearray(data_bytes) + elif type_ == "json": + # Use orjson for parsing, then apply our custom revival + parsed = orjson.loads(data_bytes) return self._revive_if_needed(parsed) - except (orjson.JSONDecodeError, TypeError): - # Fallback: Parent handles msgpack and other formats via loads_typed - # Attempt to detect type and use loads_typed - try: - # Try loading as msgpack via parent's loads_typed - return super().loads_typed(("msgpack", data)) - except Exception: - # If that fails, try loading as json string - return super().loads_typed(("json", data)) + elif type_ == "msgpack": + # Handle backward compatibility with old checkpoints that used msgpack + return super().loads_typed(data) + else: + # Unknown type, try parent + return super().loads_typed(data) def _revive_if_needed(self, obj: Any) -> Any: """Recursively apply reviver to handle LangChain and LangGraph serialized objects. @@ -121,21 +159,3 @@ def _revive_if_needed(self, obj: Any) -> Any: else: # Return primitives as-is return obj - - def dumps_typed(self, obj: Any) -> tuple[str, str]: # type: ignore[override] - if isinstance(obj, (bytes, bytearray)): - return "base64", base64.b64encode(obj).decode("utf-8") - else: - # All objects should be JSON-serializable (LangChain objects are pre-serialized) - return "json", self.dumps(obj).decode("utf-8") - - def loads_typed(self, data: tuple[str, Union[str, bytes]]) -> Any: - type_, data_ = data - if type_ == "base64": - decoded = base64.b64decode( - data_ if isinstance(data_, bytes) else data_.encode() - ) - return decoded - elif type_ == "json": - data_bytes = data_ if isinstance(data_, bytes) else data_.encode() - return self.loads(data_bytes) diff --git a/tests/test_jsonplus_redis_serializer_v3.py b/tests/test_jsonplus_redis_serializer_v3.py new file mode 100644 index 0000000..6d22937 --- /dev/null +++ b/tests/test_jsonplus_redis_serializer_v3.py @@ -0,0 +1,190 @@ +""" +Test JsonPlusRedisSerializer compatibility with langgraph-checkpoint 3.0. + +This test suite verifies that our custom serializer works with the new +checkpoint 3.0 API which changed the dumps_typed/loads_typed signatures. +""" + +from langchain_core.messages import AIMessage, HumanMessage +from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer +from langgraph.types import Interrupt + + +def test_dumps_typed_returns_bytes_not_string() -> None: + """Test that dumps_typed returns tuple[str, bytes], not tuple[str, str].""" + serializer = JsonPlusRedisSerializer() + + # Test with simple object + obj = {"test": "data", "number": 42} + type_str, data = serializer.dumps_typed(obj) + + # Verify signature: must return (str, bytes) + assert isinstance(type_str, str), f"Expected str, got {type(type_str)}" + assert isinstance(data, bytes), f"Expected bytes, got {type(data)}" + + +def test_loads_typed_accepts_bytes() -> None: + """Test that loads_typed accepts tuple[str, bytes].""" + serializer = JsonPlusRedisSerializer() + + obj = {"test": "data"} + type_str, data_bytes = serializer.dumps_typed(obj) + + # loads_typed must accept (str, bytes) + result = serializer.loads_typed((type_str, data_bytes)) + assert result == obj + + +def test_serialization_roundtrip_simple_objects() -> None: + """Test serialization roundtrip for simple Python objects.""" + serializer = JsonPlusRedisSerializer() + + test_cases = [ + None, + {"key": "value"}, + [1, 2, 3], + "string", + 42, + 3.14, + True, + False, + ] + + for obj in test_cases: + type_str, data_bytes = serializer.dumps_typed(obj) + result = serializer.loads_typed((type_str, data_bytes)) + assert result == obj, f"Roundtrip failed for {obj}" + + +def test_serialization_roundtrip_bytes() -> None: + """Test serialization roundtrip for bytes objects.""" + serializer = JsonPlusRedisSerializer() + + test_bytes = b"hello world" + type_str, data_bytes = serializer.dumps_typed(test_bytes) + + assert type_str == "bytes" + assert isinstance(data_bytes, bytes) + + result = serializer.loads_typed((type_str, data_bytes)) + assert result == test_bytes + assert isinstance(result, bytes) + + +def test_serialization_roundtrip_bytearray() -> None: + """Test serialization roundtrip for bytearray objects.""" + serializer = JsonPlusRedisSerializer() + + test_bytearray = bytearray(b"hello world") + type_str, data_bytes = serializer.dumps_typed(test_bytearray) + + assert type_str == "bytearray" + assert isinstance(data_bytes, bytes) + + result = serializer.loads_typed((type_str, data_bytes)) + assert result == test_bytearray + assert isinstance(result, bytearray) + + +def test_serialization_roundtrip_langchain_messages() -> None: + """Test serialization roundtrip for LangChain message objects.""" + serializer = JsonPlusRedisSerializer() + + messages = [ + HumanMessage(content="Hello", id="human-1"), + AIMessage(content="Hi there!", id="ai-1"), + ] + + for msg in messages: + type_str, data_bytes = serializer.dumps_typed(msg) + + assert isinstance(type_str, str) + assert isinstance(data_bytes, bytes) + + result = serializer.loads_typed((type_str, data_bytes)) + + # Should deserialize back to the same message type + assert type(result) == type(msg) + assert result.content == msg.content + + +def test_serialization_roundtrip_interrupt_objects() -> None: + """Test serialization roundtrip for Interrupt objects (Issue #113).""" + serializer = JsonPlusRedisSerializer() + + interrupt = Interrupt(value={"test": "data"}, resumable=True) + + type_str, data_bytes = serializer.dumps_typed(interrupt) + + assert isinstance(type_str, str) + assert isinstance(data_bytes, bytes) + + result = serializer.loads_typed((type_str, data_bytes)) + + # CRITICAL: Must deserialize back to Interrupt, not dict + assert isinstance(result, Interrupt), ( + f"Expected Interrupt object, got {type(result)}. " + f"This is the Issue #113 regression!" + ) + assert result.value == {"test": "data"} + assert result.resumable is True + + +def test_serialization_roundtrip_nested_interrupts() -> None: + """Test serialization of nested Interrupt objects.""" + serializer = JsonPlusRedisSerializer() + + # Interrupt containing another Interrupt in value + nested = Interrupt( + value={"nested": Interrupt(value={"inner": "data"}, resumable=False)}, + resumable=True, + ) + + type_str, data_bytes = serializer.dumps_typed(nested) + result = serializer.loads_typed((type_str, data_bytes)) + + assert isinstance(result, Interrupt) + assert isinstance(result.value["nested"], Interrupt) + assert result.value["nested"].value == {"inner": "data"} + + +def test_serialization_roundtrip_list_of_interrupts() -> None: + """Test serialization of lists containing Interrupt objects.""" + serializer = JsonPlusRedisSerializer() + + pending_sends = [ + ("__interrupt__", [Interrupt(value={"test": "data"}, resumable=False)]), + ("messages", ["some message"]), + ] + + type_str, data_bytes = serializer.dumps_typed(pending_sends) + result = serializer.loads_typed((type_str, data_bytes)) + + assert isinstance(result, list) + assert len(result) == 2 + + channel, value = result[0] + assert channel == "__interrupt__" + assert isinstance(value, list) + assert len(value) == 1 + + # CRITICAL: Must be Interrupt object, not dict (Issue #113) + assert isinstance(value[0], Interrupt) + assert value[0].value == {"test": "data"} + assert value[0].resumable is False + + +def test_no_public_dumps_loads_methods() -> None: + """Verify that dumps/loads are not part of the SerializerProtocol in 3.0.""" + from langgraph.checkpoint.serde.base import SerializerProtocol + + # SerializerProtocol should only have dumps_typed and loads_typed + protocol_methods = [ + name for name in dir(SerializerProtocol) if not name.startswith("_") + ] + + assert "dumps_typed" in protocol_methods + assert "loads_typed" in protocol_methods + # In 3.0, dumps and loads are NOT in the protocol + assert "dumps" not in protocol_methods + assert "loads" not in protocol_methods From 697255e12371001ebe042bcb697e2a079f3f54c2 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 10:30:01 -0700 Subject: [PATCH 03/36] fix(base): update metadata serialization for checkpoint 3.0 API - Replace serde.dumps()/serde.loads() with serde.dumps_typed()/serde.loads_typed() - Update _load_metadata and _dump_metadata to use new API - Fixes type errors in base.py --- langgraph/checkpoint/redis/base.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/langgraph/checkpoint/redis/base.py b/langgraph/checkpoint/redis/base.py index ae00384..bf1bfd2 100644 --- a/langgraph/checkpoint/redis/base.py +++ b/langgraph/checkpoint/redis/base.py @@ -453,7 +453,9 @@ def _load_metadata(self, metadata: dict[str, Any]) -> CheckpointMetadata: Returns: Original metadata dictionary. """ - return self.serde.loads(self.serde.dumps(metadata)) + # Roundtrip through serializer to ensure proper type handling + type_str, data_bytes = self.serde.dumps_typed(metadata) + return self.serde.loads_typed((type_str, data_bytes)) def _dump_metadata(self, metadata: CheckpointMetadata) -> str: """Convert metadata to a Redis-compatible dictionary. @@ -464,9 +466,9 @@ def _dump_metadata(self, metadata: CheckpointMetadata) -> str: Returns: Dictionary representation of metadata for Redis storage. """ - serialized_metadata = self.serde.dumps(metadata) + type_str, serialized_bytes = self.serde.dumps_typed(metadata) # NOTE: we're using JSON serializer (not msgpack), so we need to remove null characters before writing - return serialized_metadata.decode().replace("\\u0000", "") + return serialized_bytes.decode().replace("\\u0000", "") def get_next_version( # type: ignore[override] self, current: Optional[str], channel: ChannelProtocol[Any, Any, Any] From e4717ee2c31760455e24c799d3894a7f5f9f8f50 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 10:45:40 -0700 Subject: [PATCH 04/36] fix(tests): update tests for checkpoint 3.0 API - Replace serializer.dumps()/loads() with dumps_typed()/loads_typed() - Add helper functions in test_jsonplus_serializer_default_handler.py - Update test_issue_113_interrupt_serialization.py - Update test_checkpoint_serialization.py - Update test_issue_85_message_coercion.py All test files now use the new SerializerProtocol API from checkpoint 3.0 --- tests/test_checkpoint_serialization.py | 2 +- .../test_issue_113_interrupt_serialization.py | 8 ++-- tests/test_issue_85_message_coercion.py | 2 +- ...est_jsonplus_serializer_default_handler.py | 37 +++++++++++++------ 4 files changed, 31 insertions(+), 18 deletions(-) diff --git a/tests/test_checkpoint_serialization.py b/tests/test_checkpoint_serialization.py index 4da7863..a5134af 100644 --- a/tests/test_checkpoint_serialization.py +++ b/tests/test_checkpoint_serialization.py @@ -702,7 +702,7 @@ def test_message_dict_format_handling(redis_url: str) -> None: json_str = json.dumps(message_dict) # This should properly deserialize to a HumanMessage - deserialized = serializer.loads(json_str.encode()) + deserialized = serializer.loads_typed(("json", json_str.encode())) # Should be a HumanMessage object, not a dict from langchain_core.messages import HumanMessage diff --git a/tests/test_issue_113_interrupt_serialization.py b/tests/test_issue_113_interrupt_serialization.py index f3c6390..6fb9d53 100644 --- a/tests/test_issue_113_interrupt_serialization.py +++ b/tests/test_issue_113_interrupt_serialization.py @@ -57,10 +57,10 @@ def test_interrupt_serialization_roundtrip(redis_url: str) -> None: original_interrupt = Interrupt(value={"test": "data"}, resumable=True) # Serialize it - serialized = serializer.dumps(original_interrupt) + type_str, serialized = serializer.dumps_typed(original_interrupt) # Deserialize it - deserialized = serializer.loads(serialized) + deserialized = serializer.loads_typed((type_str, serialized)) # This should be an Interrupt object, not a dict assert isinstance(deserialized, Interrupt), ( @@ -91,10 +91,10 @@ def test_interrupt_in_pending_sends(redis_url: str) -> None: ] # Serialize the pending_sends - serialized = serializer.dumps(pending_sends) + type_str, serialized = serializer.dumps_typed(pending_sends) # Deserialize - deserialized = serializer.loads(serialized) + deserialized = serializer.loads_typed((type_str, serialized)) # Check the structure assert isinstance(deserialized, list) diff --git a/tests/test_issue_85_message_coercion.py b/tests/test_issue_85_message_coercion.py index 1686bbe..4a64651 100644 --- a/tests/test_issue_85_message_coercion.py +++ b/tests/test_issue_85_message_coercion.py @@ -212,7 +212,7 @@ def test_message_dict_format_causes_error(): # Convert to JSON and back (simulating storage/retrieval) json_str = json.dumps(problematic_message_dict) - deserialized = serializer.loads(json_str.encode()) + deserialized = serializer.loads_typed(("json", json_str.encode())) # Should be a proper HumanMessage, not the dict assert isinstance( diff --git a/tests/test_jsonplus_serializer_default_handler.py b/tests/test_jsonplus_serializer_default_handler.py index faf603b..8dee7e2 100644 --- a/tests/test_jsonplus_serializer_default_handler.py +++ b/tests/test_jsonplus_serializer_default_handler.py @@ -14,6 +14,19 @@ from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer +# Helper functions for backward compatibility with tests +def dumps_helper(serializer: JsonPlusRedisSerializer, obj): + """Helper to simulate old dumps() method using dumps_typed().""" + type_str, data_bytes = serializer.dumps_typed(obj) + return data_bytes + + +def loads_helper(serializer: JsonPlusRedisSerializer, data_bytes): + """Helper to simulate old loads() method using loads_typed().""" + # Assume JSON type for these tests + return serializer.loads_typed(("json", data_bytes)) + + def test_serializer_uses_default_handler_for_messages(): """Test that dumps() uses the default handler for LangChain message objects. @@ -28,11 +41,11 @@ def test_serializer_uses_default_handler_for_messages(): human_msg = HumanMessage(content="What is the weather?", id="msg-1") # This should NOT raise TypeError - serialized_bytes = serializer.dumps(human_msg) + serialized_bytes = dumps_helper(serializer, human_msg) assert isinstance(serialized_bytes, bytes) # Deserialize and verify - deserialized = serializer.loads(serialized_bytes) + deserialized = loads_helper(serializer, serialized_bytes) assert isinstance(deserialized, HumanMessage) assert deserialized.content == "What is the weather?" assert deserialized.id == "msg-1" @@ -54,11 +67,11 @@ def test_serializer_handles_all_message_types(): for msg in messages: # Serialize - serialized = serializer.dumps(msg) + serialized = dumps_helper(serializer, msg) assert isinstance(serialized, bytes) # Deserialize - deserialized = serializer.loads(serialized) + deserialized = loads_helper(serializer, serialized) # Verify type is preserved assert type(deserialized) == type(msg) @@ -80,11 +93,11 @@ def test_serializer_handles_message_lists(): ] # Serialize the list - serialized = serializer.dumps(messages) + serialized = dumps_helper(serializer, messages) assert isinstance(serialized, bytes) # Deserialize - deserialized = serializer.loads(serialized) + deserialized = loads_helper(serializer, serialized) # Verify structure assert isinstance(deserialized, list) @@ -113,11 +126,11 @@ def test_serializer_handles_nested_structures_with_messages(): } # Serialize - serialized = serializer.dumps(state) + serialized = dumps_helper(serializer, state) assert isinstance(serialized, bytes) # Deserialize - deserialized = serializer.loads(serialized) + deserialized = loads_helper(serializer, serialized) # Verify structure assert "messages" in deserialized @@ -169,8 +182,8 @@ def test_serializer_backwards_compatible(): ] for obj in test_cases: - serialized = serializer.dumps(obj) - deserialized = serializer.loads(serialized) + serialized = dumps_helper(serializer, obj) + deserialized = loads_helper(serializer, serialized) assert deserialized == obj @@ -194,8 +207,8 @@ def test_serializer_with_langchain_serialized_format(): } # Serialize and deserialize - serialized = serializer.dumps(message_dict) - deserialized = serializer.loads(serialized) + serialized = dumps_helper(serializer, message_dict) + deserialized = loads_helper(serializer, serialized) # Should be revived as a HumanMessage assert isinstance(deserialized, HumanMessage) From 9ee842e3f1a06c1ae0d1b1fa78eec1d8b7c988fc Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 10:48:15 -0700 Subject: [PATCH 05/36] fix(base): encode blob bytes as base64 for Redis storage - Add _encode_blob() calls in put_writes() and _dump_writes() - Blob data from dumps_typed() is now bytes (not string) - Must base64-encode before storing in Redis JSON - Fixes TypeError: Object of type bytes is not JSON serializable --- langgraph/checkpoint/redis/base.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/langgraph/checkpoint/redis/base.py b/langgraph/checkpoint/redis/base.py index bf1bfd2..59dd21d 100644 --- a/langgraph/checkpoint/redis/base.py +++ b/langgraph/checkpoint/redis/base.py @@ -438,7 +438,7 @@ def _dump_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": t, - "blob": b, + "blob": self._encode_blob(b), # Encode bytes to base64 string for Redis } for idx, (channel, value) in enumerate(writes) for t, b in [self.serde.dumps_typed(value)] @@ -553,7 +553,7 @@ def put_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": blob, + "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) From e317d60782260d41051e7cfd2697fb31092a8d80 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 10:50:46 -0700 Subject: [PATCH 06/36] fix(sync,async): encode blob bytes in put_writes implementations - Add _encode_blob() in RedisSaver.put_writes() (__init__.py) - Add _encode_blob() in AsyncRedisSaver.aput_writes() (aio.py) - Both sync and async implementations now properly encode blob bytes - Completes blob encoding fix across all implementations --- langgraph/checkpoint/redis/__init__.py | 2 +- langgraph/checkpoint/redis/aio.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/langgraph/checkpoint/redis/__init__.py b/langgraph/checkpoint/redis/__init__.py index 50b4f37..079a4b3 100644 --- a/langgraph/checkpoint/redis/__init__.py +++ b/langgraph/checkpoint/redis/__init__.py @@ -583,7 +583,7 @@ def put_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": blob, + "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) diff --git a/langgraph/checkpoint/redis/aio.py b/langgraph/checkpoint/redis/aio.py index 9ad1d73..7f0c02d 100644 --- a/langgraph/checkpoint/redis/aio.py +++ b/langgraph/checkpoint/redis/aio.py @@ -1122,7 +1122,7 @@ async def aput_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": blob, + "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) From 84d9f8b960ae2963310f914a787ea9f814da5b67 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 10:55:32 -0700 Subject: [PATCH 07/36] fix(shallow): encode blob bytes in shallow implementations - Add _encode_blob() in ShallowRedisSaver.put_writes() - Add _encode_blob() in AsyncShallowRedisSaver.aput_writes() - Completes blob encoding fix across ALL implementations (regular and shallow) --- langgraph/checkpoint/redis/ashallow.py | 2 +- langgraph/checkpoint/redis/shallow.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/langgraph/checkpoint/redis/ashallow.py b/langgraph/checkpoint/redis/ashallow.py index 46cfe10..46c2423 100644 --- a/langgraph/checkpoint/redis/ashallow.py +++ b/langgraph/checkpoint/redis/ashallow.py @@ -534,7 +534,7 @@ async def aput_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": blob, + "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) diff --git a/langgraph/checkpoint/redis/shallow.py b/langgraph/checkpoint/redis/shallow.py index 0d63dbe..b47d40e 100644 --- a/langgraph/checkpoint/redis/shallow.py +++ b/langgraph/checkpoint/redis/shallow.py @@ -529,7 +529,7 @@ def put_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": blob, + "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) From 66cdd93a8afb81d6a5b7ec4deab6297a131bd47f Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 11:28:45 -0700 Subject: [PATCH 08/36] fix(checkpoint): prevent infinite recursion in _load_pending_writes fallback Call super()._load_pending_writes() instead of self._load_pending_writes() in the registry fallback path to avoid infinite recursion between _load_pending_writes and _load_pending_writes_with_registry_check. --- langgraph/checkpoint/redis/__init__.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/langgraph/checkpoint/redis/__init__.py b/langgraph/checkpoint/redis/__init__.py index 079a4b3..af01c9f 100644 --- a/langgraph/checkpoint/redis/__init__.py +++ b/langgraph/checkpoint/redis/__init__.py @@ -1438,7 +1438,8 @@ def _load_pending_writes_with_registry_check( pass # FALLBACK: Use FT.SEARCH if registry not available or failed - return self._load_pending_writes(thread_id, checkpoint_ns, checkpoint_id) + # Call the base class implementation to avoid recursion + return super()._load_pending_writes(thread_id, checkpoint_ns, checkpoint_id) def _load_pending_sends_with_registry_check( self, From cdef8514e8c85aed1eef145945b9b6130e377456 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 11:39:48 -0700 Subject: [PATCH 09/36] fix(checkpoint): decode base64 blobs when loading pending writes Add static _decode_blob_static() method to handle base64 decoding of blob data retrieved from Redis before passing to serializer. This fixes orjson.JSONDecodeError when loading pending writes. --- langgraph/checkpoint/redis/base.py | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/langgraph/checkpoint/redis/base.py b/langgraph/checkpoint/redis/base.py index 59dd21d..bc8c62a 100644 --- a/langgraph/checkpoint/redis/base.py +++ b/langgraph/checkpoint/redis/base.py @@ -732,12 +732,25 @@ def _load_writes( ( task_id, data["channel"], - serde.loads_typed((data["type"], data["blob"])), + serde.loads_typed((data["type"], BaseRedisSaver._decode_blob_static(data["blob"]))), ) for (task_id, _), data in task_id_to_data.items() ] return writes + @staticmethod + def _decode_blob_static(blob: bytes | str) -> bytes: + """Decode blob data from Redis storage (static method).""" + try: + # If it's already bytes, try to decode as base64 + if isinstance(blob, bytes): + return base64.b64decode(blob) + # If it's a string, encode to bytes first then decode + return base64.b64decode(blob.encode("utf-8")) + except (binascii.Error, TypeError, ValueError): + # Handle both malformed base64 data and incorrect input types + return blob.encode("utf-8") if isinstance(blob, str) else blob + @staticmethod def _parse_redis_checkpoint_writes_key(redis_key: str) -> dict: # Ensure redis_key is a string From ea8340df6e4e4ffda81664fc94ac5b0c84779907 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 11:45:04 -0700 Subject: [PATCH 10/36] test(checkpoint): update search_writes tests for base64 blobs Update blob assertions to decode base64 data before comparing. Blobs are now base64-encoded in Redis with checkpoint 3.0. --- tests/test_async.py | 8 +++++--- tests/test_sync.py | 8 +++++--- 2 files changed, 10 insertions(+), 6 deletions(-) diff --git a/tests/test_async.py b/tests/test_async.py index 6578adf..3d3feb1 100644 --- a/tests/test_async.py +++ b/tests/test_async.py @@ -516,9 +516,11 @@ async def test_search_writes_async(redis_url: str) -> None: doc2 = json.loads(results.docs[1].json) doc3 = json.loads(results.docs[2].json) - assert doc1["blob"] == '"value1"' - assert doc2["blob"] == '"value2"' - assert doc3["blob"] == '"value3"' + # Blobs are now base64-encoded in Redis (checkpoint 3.0) + import base64 + assert base64.b64decode(doc1["blob"]).decode() == '"value1"' + assert base64.b64decode(doc2["blob"]).decode() == '"value2"' + assert base64.b64decode(doc3["blob"]).decode() == '"value3"' @pytest.mark.asyncio diff --git a/tests/test_sync.py b/tests/test_sync.py index d418be8..04df074 100644 --- a/tests/test_sync.py +++ b/tests/test_sync.py @@ -267,9 +267,11 @@ def test_search_writes(redis_url: str) -> None: doc2 = json.loads(results.docs[1].json) doc3 = json.loads(results.docs[2].json) - assert doc1["blob"] == '"value1"' - assert doc2["blob"] == '"value2"' - assert doc3["blob"] == '"value3"' + # Blobs are now base64-encoded in Redis (checkpoint 3.0) + import base64 + assert base64.b64decode(doc1["blob"]).decode() == '"value1"' + assert base64.b64decode(doc2["blob"]).decode() == '"value2"' + assert base64.b64decode(doc3["blob"]).decode() == '"value3"' def test_from_conn_string_with_url(redis_url: str) -> None: From c64dca9db9469954ac809d705115972e3a9fec55 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 11:47:07 -0700 Subject: [PATCH 11/36] test(checkpoint): fix serializer test helpers for checkpoint 3.0 Update dumps_helper/loads_helper to preserve full (type_str, bytes) tuple. Update test_dumps_typed_with_messages to expect bytes not str. --- ...est_jsonplus_serializer_default_handler.py | 22 ++++++++++++------- 1 file changed, 14 insertions(+), 8 deletions(-) diff --git a/tests/test_jsonplus_serializer_default_handler.py b/tests/test_jsonplus_serializer_default_handler.py index 8dee7e2..780ab5a 100644 --- a/tests/test_jsonplus_serializer_default_handler.py +++ b/tests/test_jsonplus_serializer_default_handler.py @@ -16,15 +16,20 @@ # Helper functions for backward compatibility with tests def dumps_helper(serializer: JsonPlusRedisSerializer, obj): - """Helper to simulate old dumps() method using dumps_typed().""" - type_str, data_bytes = serializer.dumps_typed(obj) - return data_bytes + """Helper to simulate old dumps() method using dumps_typed(). + + Returns the full (type_str, data_bytes) tuple to preserve type information. + """ + return serializer.dumps_typed(obj) -def loads_helper(serializer: JsonPlusRedisSerializer, data_bytes): - """Helper to simulate old loads() method using loads_typed().""" - # Assume JSON type for these tests - return serializer.loads_typed(("json", data_bytes)) +def loads_helper(serializer: JsonPlusRedisSerializer, typed_data): + """Helper to simulate old loads() method using loads_typed(). + + Args: + typed_data: Full (type_str, data_bytes) tuple from dumps_helper + """ + return serializer.loads_typed(typed_data) def test_serializer_uses_default_handler_for_messages(): @@ -153,7 +158,8 @@ def test_dumps_typed_with_messages(): type_str, blob = serializer.dumps_typed(msg) assert type_str == "json" - assert isinstance(blob, str) + # Checkpoint 3.0: dumps_typed now returns bytes, not str + assert isinstance(blob, bytes) # Deserialize deserialized = serializer.loads_typed((type_str, blob)) From d21047d8af4e2dea82daad494080f3205df234d2 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 12:04:02 -0700 Subject: [PATCH 12/36] fix(checkpoint): handle bytes in nested structures with msgpack fallback - Add bytes detection in _default_handler to trigger msgpack serialization - Update dumps_typed to fallback to parent's msgpack for bytes in dicts - Update _dump_checkpoint to handle both JSON and msgpack types - Add __bytes__ marker for bytes in channel_values stored via msgpack - Update _recursive_deserialize to decode __bytes__ markers - Fix test assertions to expect bytes instead of str from dumps_typed --- langgraph/checkpoint/redis/base.py | 22 ++++++++++++++++++-- langgraph/checkpoint/redis/jsonplus_redis.py | 16 +++++++++++--- tests/test_checkpoint_serialization.py | 10 ++++----- 3 files changed, 38 insertions(+), 10 deletions(-) diff --git a/langgraph/checkpoint/redis/base.py b/langgraph/checkpoint/redis/base.py index bc8c62a..0e36c3a 100644 --- a/langgraph/checkpoint/redis/base.py +++ b/langgraph/checkpoint/redis/base.py @@ -310,8 +310,21 @@ def _dump_checkpoint(self, checkpoint: Checkpoint) -> dict[str, Any]: """Convert checkpoint to Redis format.""" type_, data = self.serde.dumps_typed(checkpoint) - # Since we're keeping JSON format, decode string data - checkpoint_data = cast(dict, orjson.loads(data)) + # Decode the serialized data - handle both JSON and msgpack + if type_ == "json": + checkpoint_data = cast(dict, orjson.loads(data)) + else: + # For msgpack or other types, deserialize with loads_typed + checkpoint_data = cast(dict, self.serde.loads_typed((type_, data))) + + # When using msgpack, bytes are preserved - but Redis JSON.SET can't handle them + # Encode bytes in channel_values with type marker for JSON storage + if "channel_values" in checkpoint_data: + for key, value in checkpoint_data["channel_values"].items(): + if isinstance(value, bytes): + checkpoint_data["channel_values"][key] = { + "__bytes__": self._encode_blob(value) + } # Ensure channel_versions are always strings to fix issue #40 if "channel_versions" in checkpoint_data: @@ -379,6 +392,11 @@ def _recursive_deserialize(self, obj: Any) -> Any: The deserialized object, with LangChain objects properly reconstructed. """ if isinstance(obj, dict): + # Check if this is a bytes marker from msgpack storage + if "__bytes__" in obj and len(obj) == 1: + # Decode base64-encoded bytes + return self._decode_blob(obj["__bytes__"]) + # Check if this is a LangChain serialized object if obj.get("lc") in (1, 2) and obj.get("type") == "constructor": try: diff --git a/langgraph/checkpoint/redis/jsonplus_redis.py b/langgraph/checkpoint/redis/jsonplus_redis.py index 8b2c274..77fc2fd 100644 --- a/langgraph/checkpoint/redis/jsonplus_redis.py +++ b/langgraph/checkpoint/redis/jsonplus_redis.py @@ -33,6 +33,10 @@ def _default_handler(self, obj: Any) -> Any: This handles LangChain objects by delegating to the parent's _encode_constructor_args method which creates the LC format. """ + # Bytes/bytearray in nested structures require msgpack - signal to fallback + if isinstance(obj, (bytes, bytearray)): + raise TypeError("bytes/bytearray in nested structure - use msgpack") + # Try to encode using parent's constructor args encoder # This creates the {"lc": 2, "type": "constructor", ...} format try: @@ -57,6 +61,8 @@ def _default_handler(self, obj: Any) -> Any: def dumps_typed(self, obj: Any) -> tuple[str, bytes]: """Serialize using orjson for JSON. + Falls back to msgpack for structures containing bytes/bytearray. + Returns: tuple[str, bytes]: Type identifier and serialized bytes """ @@ -67,9 +73,13 @@ def dumps_typed(self, obj: Any) -> tuple[str, bytes]: elif obj is None: return "null", b"" else: - # Use orjson for JSON serialization with custom default handler - json_bytes = orjson.dumps(obj, default=self._default_handler) - return "json", json_bytes + try: + # Try orjson first with custom default handler + json_bytes = orjson.dumps(obj, default=self._default_handler) + return "json", json_bytes + except (TypeError, orjson.JSONEncodeError): + # Fall back to parent's msgpack serialization for bytes in nested structures + return super().dumps_typed(obj) def loads_typed(self, data: tuple[str, bytes]) -> Any: """Deserialize with custom revival for LangChain/LangGraph objects. diff --git a/tests/test_checkpoint_serialization.py b/tests/test_checkpoint_serialization.py index a5134af..0f1802a 100644 --- a/tests/test_checkpoint_serialization.py +++ b/tests/test_checkpoint_serialization.py @@ -166,14 +166,13 @@ def test_issue_83_pending_sends_type_compatibility(redis_url: str) -> None: # Serialize type_str, blob = saver.serde.dumps_typed(test_data) assert isinstance(type_str, str) - assert isinstance(blob, str) # JsonPlusRedisSerializer returns strings + # Checkpoint 3.0: dumps_typed now returns bytes + assert isinstance(blob, bytes) - # Deserialize - should work with both string and bytes + # Deserialize with bytes (checkpoint 3.0 format) result1 = saver.serde.loads_typed((type_str, blob)) - result2 = saver.serde.loads_typed((type_str, blob.encode())) # bytes version assert result1 == test_data - assert result2 == test_data def test_load_blobs_method(redis_url: str) -> None: @@ -508,7 +507,8 @@ def test_langchain_message_serialization(redis_url: str) -> None: # Serialize type_, data = serializer.dumps_typed(human_msg) assert type_ == "json" - assert isinstance(data, str) + # Checkpoint 3.0: dumps_typed now returns bytes + assert isinstance(data, bytes) # Deserialize deserialized = serializer.loads_typed((type_, data)) From a834d1cca9c918fd9ebda5c2f741f6afd5c62ec8 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 12:09:21 -0700 Subject: [PATCH 13/36] test(checkpoint): fix dumps_helper usage in serializer tests Update tests to unpack (type_str, bytes) tuple from dumps_helper instead of expecting just bytes. --- ...est_jsonplus_serializer_default_handler.py | 20 +++++++++++-------- 1 file changed, 12 insertions(+), 8 deletions(-) diff --git a/tests/test_jsonplus_serializer_default_handler.py b/tests/test_jsonplus_serializer_default_handler.py index 780ab5a..0dce963 100644 --- a/tests/test_jsonplus_serializer_default_handler.py +++ b/tests/test_jsonplus_serializer_default_handler.py @@ -46,11 +46,12 @@ def test_serializer_uses_default_handler_for_messages(): human_msg = HumanMessage(content="What is the weather?", id="msg-1") # This should NOT raise TypeError - serialized_bytes = dumps_helper(serializer, human_msg) + typed_data = dumps_helper(serializer, human_msg) + type_str, serialized_bytes = typed_data assert isinstance(serialized_bytes, bytes) # Deserialize and verify - deserialized = loads_helper(serializer, serialized_bytes) + deserialized = loads_helper(serializer, typed_data) assert isinstance(deserialized, HumanMessage) assert deserialized.content == "What is the weather?" assert deserialized.id == "msg-1" @@ -72,11 +73,12 @@ def test_serializer_handles_all_message_types(): for msg in messages: # Serialize - serialized = dumps_helper(serializer, msg) + typed_data = dumps_helper(serializer, msg) + type_str, serialized = typed_data assert isinstance(serialized, bytes) # Deserialize - deserialized = loads_helper(serializer, serialized) + deserialized = loads_helper(serializer, typed_data) # Verify type is preserved assert type(deserialized) == type(msg) @@ -98,11 +100,12 @@ def test_serializer_handles_message_lists(): ] # Serialize the list - serialized = dumps_helper(serializer, messages) + typed_data = dumps_helper(serializer, messages) + type_str, serialized = typed_data assert isinstance(serialized, bytes) # Deserialize - deserialized = loads_helper(serializer, serialized) + deserialized = loads_helper(serializer, typed_data) # Verify structure assert isinstance(deserialized, list) @@ -131,11 +134,12 @@ def test_serializer_handles_nested_structures_with_messages(): } # Serialize - serialized = dumps_helper(serializer, state) + typed_data = dumps_helper(serializer, state) + type_str, serialized = typed_data assert isinstance(serialized, bytes) # Deserialize - deserialized = loads_helper(serializer, serialized) + deserialized = loads_helper(serializer, typed_data) # Verify structure assert "messages" in deserialized From 15baca3d7568648d619eed5ffc551d1f2c63e1a1 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 12:12:47 -0700 Subject: [PATCH 14/36] style(checkpoint): apply black formatting Auto-format code with black and isort for checkpoint 3.0 changes. --- langgraph/checkpoint/redis/__init__.py | 4 +++- langgraph/checkpoint/redis/aio.py | 4 +++- langgraph/checkpoint/redis/ashallow.py | 4 +++- langgraph/checkpoint/redis/base.py | 8 ++++++-- langgraph/checkpoint/redis/jsonplus_redis.py | 3 +-- langgraph/checkpoint/redis/shallow.py | 4 +++- tests/test_async.py | 1 + tests/test_jsonplus_redis_serializer_v3.py | 3 ++- tests/test_sync.py | 1 + 9 files changed, 23 insertions(+), 9 deletions(-) diff --git a/langgraph/checkpoint/redis/__init__.py b/langgraph/checkpoint/redis/__init__.py index af01c9f..2278c0d 100644 --- a/langgraph/checkpoint/redis/__init__.py +++ b/langgraph/checkpoint/redis/__init__.py @@ -583,7 +583,9 @@ def put_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis + "blob": self._encode_blob( + blob + ), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) diff --git a/langgraph/checkpoint/redis/aio.py b/langgraph/checkpoint/redis/aio.py index 7f0c02d..cdcf512 100644 --- a/langgraph/checkpoint/redis/aio.py +++ b/langgraph/checkpoint/redis/aio.py @@ -1122,7 +1122,9 @@ async def aput_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis + "blob": self._encode_blob( + blob + ), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) diff --git a/langgraph/checkpoint/redis/ashallow.py b/langgraph/checkpoint/redis/ashallow.py index 46c2423..287a413 100644 --- a/langgraph/checkpoint/redis/ashallow.py +++ b/langgraph/checkpoint/redis/ashallow.py @@ -534,7 +534,9 @@ async def aput_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis + "blob": self._encode_blob( + blob + ), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) diff --git a/langgraph/checkpoint/redis/base.py b/langgraph/checkpoint/redis/base.py index 0e36c3a..007d501 100644 --- a/langgraph/checkpoint/redis/base.py +++ b/langgraph/checkpoint/redis/base.py @@ -571,7 +571,9 @@ def put_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis + "blob": self._encode_blob( + blob + ), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) @@ -750,7 +752,9 @@ def _load_writes( ( task_id, data["channel"], - serde.loads_typed((data["type"], BaseRedisSaver._decode_blob_static(data["blob"]))), + serde.loads_typed( + (data["type"], BaseRedisSaver._decode_blob_static(data["blob"])) + ), ) for (task_id, _), data in task_id_to_data.items() ] diff --git a/langgraph/checkpoint/redis/jsonplus_redis.py b/langgraph/checkpoint/redis/jsonplus_redis.py index 77fc2fd..6dd6553 100644 --- a/langgraph/checkpoint/redis/jsonplus_redis.py +++ b/langgraph/checkpoint/redis/jsonplus_redis.py @@ -51,8 +51,7 @@ def _default_handler(self, obj: Any) -> Any: # For other objects, encode with constructor args # Pass the class and the instance's __dict__ as kwargs return self._encode_constructor_args( - type(obj), - kwargs=obj.__dict__ if hasattr(obj, "__dict__") else {} + type(obj), kwargs=obj.__dict__ if hasattr(obj, "__dict__") else {} ) except Exception: # For types we can't handle, raise TypeError diff --git a/langgraph/checkpoint/redis/shallow.py b/langgraph/checkpoint/redis/shallow.py index b47d40e..e84944d 100644 --- a/langgraph/checkpoint/redis/shallow.py +++ b/langgraph/checkpoint/redis/shallow.py @@ -529,7 +529,9 @@ def put_writes( "idx": WRITES_IDX_MAP.get(channel, idx), "channel": channel, "type": type_, - "blob": self._encode_blob(blob), # Encode bytes to base64 string for Redis + "blob": self._encode_blob( + blob + ), # Encode bytes to base64 string for Redis } writes_objects.append(write_obj) diff --git a/tests/test_async.py b/tests/test_async.py index 3d3feb1..5e2d6b9 100644 --- a/tests/test_async.py +++ b/tests/test_async.py @@ -518,6 +518,7 @@ async def test_search_writes_async(redis_url: str) -> None: # Blobs are now base64-encoded in Redis (checkpoint 3.0) import base64 + assert base64.b64decode(doc1["blob"]).decode() == '"value1"' assert base64.b64decode(doc2["blob"]).decode() == '"value2"' assert base64.b64decode(doc3["blob"]).decode() == '"value3"' diff --git a/tests/test_jsonplus_redis_serializer_v3.py b/tests/test_jsonplus_redis_serializer_v3.py index 6d22937..3891aad 100644 --- a/tests/test_jsonplus_redis_serializer_v3.py +++ b/tests/test_jsonplus_redis_serializer_v3.py @@ -6,9 +6,10 @@ """ from langchain_core.messages import AIMessage, HumanMessage -from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer from langgraph.types import Interrupt +from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer + def test_dumps_typed_returns_bytes_not_string() -> None: """Test that dumps_typed returns tuple[str, bytes], not tuple[str, str].""" diff --git a/tests/test_sync.py b/tests/test_sync.py index 04df074..f6c4292 100644 --- a/tests/test_sync.py +++ b/tests/test_sync.py @@ -269,6 +269,7 @@ def test_search_writes(redis_url: str) -> None: # Blobs are now base64-encoded in Redis (checkpoint 3.0) import base64 + assert base64.b64decode(doc1["blob"]).decode() == '"value1"' assert base64.b64decode(doc2["blob"]).decode() == '"value2"' assert base64.b64decode(doc3["blob"]).decode() == '"value3"' From afd711edba4e5e7901b5087b6335241e3de4d23d Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 17:43:24 -0700 Subject: [PATCH 15/36] test(serializer): update standalone test for checkpoint 3.0 API Convert all dumps/loads calls to dumps_typed/loads_typed. Update blob assertion to expect bytes instead of str. --- test_jsonplus_redis_serializer.py | 29 +++++++++++++++-------------- 1 file changed, 15 insertions(+), 14 deletions(-) diff --git a/test_jsonplus_redis_serializer.py b/test_jsonplus_redis_serializer.py index d348560..0817e39 100644 --- a/test_jsonplus_redis_serializer.py +++ b/test_jsonplus_redis_serializer.py @@ -15,12 +15,12 @@ def test_human_message_serialization(): serializer = JsonPlusRedisSerializer() msg = HumanMessage(content="What is the weather?", id="msg-1") - # This would raise TypeError before the fix - serialized = serializer.dumps(msg) - print(f" ✓ Serialized to {len(serialized)} bytes") + # Checkpoint 3.0: Use dumps_typed instead of dumps + type_str, serialized = serializer.dumps_typed(msg) + print(f" ✓ Serialized to {len(serialized)} bytes (type: {type_str})") # Deserialize - deserialized = serializer.loads(serialized) + deserialized = serializer.loads_typed((type_str, serialized)) assert isinstance(deserialized, HumanMessage) assert deserialized.content == "What is the weather?" assert deserialized.id == "msg-1" @@ -39,8 +39,8 @@ def test_all_message_types(): ] for msg in messages: - serialized = serializer.dumps(msg) - deserialized = serializer.loads(serialized) + type_str, serialized = serializer.dumps_typed(msg) + deserialized = serializer.loads_typed((type_str, serialized)) assert type(deserialized) == type(msg) print(f" ✓ {type(msg).__name__} works") @@ -56,8 +56,8 @@ def test_message_list(): HumanMessage(content="Question 2"), ] - serialized = serializer.dumps(messages) - deserialized = serializer.loads(serialized) + type_str, serialized = serializer.dumps_typed(messages) + deserialized = serializer.loads_typed((type_str, serialized)) assert isinstance(deserialized, list) assert len(deserialized) == 3 @@ -78,8 +78,8 @@ def test_nested_structure(): "step": 1, } - serialized = serializer.dumps(state) - deserialized = serializer.loads(serialized) + type_str, serialized = serializer.dumps_typed(state) + deserialized = serializer.loads_typed((type_str, serialized)) assert "messages" in deserialized assert len(deserialized["messages"]) == 2 @@ -97,8 +97,9 @@ def test_dumps_typed(): type_str, blob = serializer.dumps_typed(msg) assert type_str == "json" - assert isinstance(blob, str) - print(f" ✓ dumps_typed returns: type='{type_str}', blob={len(blob)} chars") + # Checkpoint 3.0: blob is now bytes, not str + assert isinstance(blob, bytes) + print(f" ✓ dumps_typed returns: type='{type_str}', blob={len(blob)} bytes") deserialized = serializer.loads_typed((type_str, blob)) assert isinstance(deserialized, HumanMessage) @@ -119,8 +120,8 @@ def test_backwards_compatibility(): ] for name, obj in test_cases: - serialized = serializer.dumps(obj) - deserialized = serializer.loads(serialized) + type_str, serialized = serializer.dumps_typed(obj) + deserialized = serializer.loads_typed((type_str, serialized)) assert deserialized == obj print(f" ✓ {name} works") From 64f1e16383569eac11bbe004eb6fd1cb39059185 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 21:10:15 -0700 Subject: [PATCH 16/36] feat(deps)!: upgrade to LangGraph 1.0.3 BREAKING CHANGE: Minimum Python version is now 3.10 (was 3.9) - Upgrade langgraph from 0.4.9 to 1.0.3 - Upgrade langchain-core from 0.3.74 to 1.0.5 - Upgrade langgraph-checkpoint from 2.x to 3.x - Add redisvl >=0.11.0 dependency (security fix CVE-2025-64439) --- poetry.lock | 78 +++++++++++++++++++++++++------------------------- pyproject.toml | 2 +- 2 files changed, 40 insertions(+), 40 deletions(-) diff --git a/poetry.lock b/poetry.lock index b3fcaea..3b16719 100644 --- a/poetry.lock +++ b/poetry.lock @@ -849,59 +849,59 @@ files = [ [[package]] name = "langchain-core" -version = "0.3.74" +version = "1.0.5" description = "Building applications with LLMs through composability" optional = false -python-versions = ">=3.9" +python-versions = "<4.0.0,>=3.10.0" groups = ["main", "dev"] files = [ - {file = "langchain_core-0.3.74-py3-none-any.whl", hash = "sha256:088338b5bc2f6a66892f9afc777992c24ee3188f41cbc603d09181e34a228ce7"}, - {file = "langchain_core-0.3.74.tar.gz", hash = "sha256:ff604441aeade942fbcc0a3860a592daba7671345230c2078ba2eb5f82b6ba76"}, + {file = "langchain_core-1.0.5-py3-none-any.whl", hash = "sha256:d24c0cf12cfcd96dd4bd479aa91425f3a6652226cd824228ae422a195067b74e"}, + {file = "langchain_core-1.0.5.tar.gz", hash = "sha256:7ecbad9a60dde626252733a9c18c7377f4468cfe00465ffa99f5e9c6cb9b82d2"}, ] [package.dependencies] -jsonpatch = ">=1.33,<2.0" -langsmith = ">=0.3.45" -packaging = ">=23.2" -pydantic = ">=2.7.4" -PyYAML = ">=5.3" +jsonpatch = ">=1.33.0,<2.0.0" +langsmith = ">=0.3.45,<1.0.0" +packaging = ">=23.2.0,<26.0.0" +pydantic = ">=2.7.4,<3.0.0" +pyyaml = ">=5.3.0,<7.0.0" tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0" -typing-extensions = ">=4.7" +typing-extensions = ">=4.7.0,<5.0.0" [[package]] name = "langchain-openai" -version = "0.3.30" +version = "0.3.34" description = "An integration package connecting OpenAI and LangChain" optional = false -python-versions = ">=3.9" +python-versions = "<4.0.0,>=3.9.0" groups = ["dev"] files = [ - {file = "langchain_openai-0.3.30-py3-none-any.whl", hash = "sha256:280f1f31004393228e3f75ff8353b1aae86bbc282abc7890a05beb5f43b89923"}, - {file = "langchain_openai-0.3.30.tar.gz", hash = "sha256:90df37509b2dcf5e057f491326fcbf78cf2a71caff5103a5a7de560320171842"}, + {file = "langchain_openai-0.3.34-py3-none-any.whl", hash = "sha256:08d61d68a6d869c70d542171e149b9065668dedfc4fafcd4de8aeb5b933030a9"}, + {file = "langchain_openai-0.3.34.tar.gz", hash = "sha256:57916d462be5b8fd19e5cb2f00d4e5cf0465266a292d583de2fc693a55ba190e"}, ] [package.dependencies] -langchain-core = ">=0.3.74,<1.0.0" -openai = ">=1.99.9,<2.0.0" -tiktoken = ">=0.7,<1" +langchain-core = ">=0.3.77,<2.0.0" +openai = ">=1.104.2,<3.0.0" +tiktoken = ">=0.7.0,<1.0.0" [[package]] name = "langgraph" -version = "0.4.9" +version = "1.0.3" description = "Building stateful, multi-actor applications with LLMs" optional = false -python-versions = ">=3.9" +python-versions = ">=3.10" groups = ["dev"] files = [ - {file = "langgraph-0.4.9-py3-none-any.whl", hash = "sha256:03312d769edec311dac3ec9ed83a595f1a74590b9ad141387f1fb006b5b3f753"}, - {file = "langgraph-0.4.9.tar.gz", hash = "sha256:f815d4cc804862fb32c280bb17e634c3f0e88b4e0df1fb6573aebb73fb959a1e"}, + {file = "langgraph-1.0.3-py3-none-any.whl", hash = "sha256:4a75146f09bd0d127a724876f4244f460c4c66353a993641bd641ed710cd010f"}, + {file = "langgraph-1.0.3.tar.gz", hash = "sha256:873a6aae6be054ef52a05c463be363a46da9711405b1b14454d595f543b68335"}, ] [package.dependencies] langchain-core = ">=0.1" -langgraph-checkpoint = ">=2.0.26" -langgraph-prebuilt = ">=0.2.0" -langgraph-sdk = ">=0.1.42" +langgraph-checkpoint = ">=2.1.0,<4.0.0" +langgraph-prebuilt = ">=1.0.2,<1.1.0" +langgraph-sdk = ">=0.2.2,<0.3.0" pydantic = ">=2.7.4" xxhash = ">=3.5.0" @@ -923,30 +923,30 @@ ormsgpack = ">=1.12.0" [[package]] name = "langgraph-prebuilt" -version = "0.2.2" +version = "1.0.4" description = "Library with high-level APIs for creating and executing LangGraph agents and tools." optional = false -python-versions = ">=3.9" +python-versions = ">=3.10" groups = ["dev"] files = [ - {file = "langgraph_prebuilt-0.2.2-py3-none-any.whl", hash = "sha256:72de5ef1d969a8f02ad7adc7cc1915bb9b4467912d57ba60da34b5a70fdad1f6"}, - {file = "langgraph_prebuilt-0.2.2.tar.gz", hash = "sha256:0a5d1f651f97c848cd1c3dd0ef017614f47ee74effb7375b59ac639e41b253f9"}, + {file = "langgraph_prebuilt-1.0.4-py3-none-any.whl", hash = "sha256:50b1aa2b434783b6da30785568cf7155136b484750cc2ec695c0d4255db08262"}, + {file = "langgraph_prebuilt-1.0.4.tar.gz", hash = "sha256:7b4f9e97a146d2d625695c3549bdb432974b80817165139ec2ec869721e72c0f"}, ] [package.dependencies] -langchain-core = ">=0.3.22" -langgraph-checkpoint = ">=2.0.10" +langchain-core = ">=1.0.0" +langgraph-checkpoint = ">=2.1.0,<4.0.0" [[package]] name = "langgraph-sdk" -version = "0.1.70" +version = "0.2.9" description = "SDK for interacting with LangGraph API" optional = false python-versions = ">=3.9" groups = ["dev"] files = [ - {file = "langgraph_sdk-0.1.70-py3-none-any.whl", hash = "sha256:47f2b04a964f40a610c1636b387ea52f961ce7a233afc21d3103e5faac8ca1e5"}, - {file = "langgraph_sdk-0.1.70.tar.gz", hash = "sha256:cc65ec33bcdf8c7008d43da2d2b0bc1dd09f98d21a7f636828d9379535069cf9"}, + {file = "langgraph_sdk-0.2.9-py3-none-any.whl", hash = "sha256:fbf302edadbf0fb343596f91c597794e936ef68eebc0d3e1d358b6f9f72a1429"}, + {file = "langgraph_sdk-0.2.9.tar.gz", hash = "sha256:b3bd04c6be4fa382996cd2be8fbc1e7cc94857d2bc6b6f4599a7f2a245975303"}, ] [package.dependencies] @@ -1221,28 +1221,28 @@ files = [ [[package]] name = "openai" -version = "1.99.9" +version = "2.8.0" description = "The official Python library for the openai API" optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" groups = ["dev"] files = [ - {file = "openai-1.99.9-py3-none-any.whl", hash = "sha256:9dbcdb425553bae1ac5d947147bebbd630d91bbfc7788394d4c4f3a35682ab3a"}, - {file = "openai-1.99.9.tar.gz", hash = "sha256:f2082d155b1ad22e83247c3de3958eb4255b20ccf4a1de2e6681b6957b554e92"}, + {file = "openai-2.8.0-py3-none-any.whl", hash = "sha256:ba975e347f6add2fe13529ccb94d54a578280e960765e5224c34b08d7e029ddf"}, + {file = "openai-2.8.0.tar.gz", hash = "sha256:4851908f6d6fcacbd47ba659c5ac084f7725b752b6bfa1e948b6fbfc111a6bad"}, ] [package.dependencies] anyio = ">=3.5.0,<5" distro = ">=1.7.0,<2" httpx = ">=0.23.0,<1" -jiter = ">=0.4.0,<1" +jiter = ">=0.10.0,<1" pydantic = ">=1.9.0,<3" sniffio = "*" tqdm = ">4" typing-extensions = ">=4.11,<5" [package.extras] -aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"] +aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.9)"] datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"] realtime = ["websockets (>=13,<16)"] voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"] diff --git a/pyproject.toml b/pyproject.toml index ee6cb95..985365a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langgraph-checkpoint-redis" -version = "0.1.3" +version = "0.2.0" description = "Redis implementation of the LangGraph agent checkpoint saver and store." authors = ["Redis Inc. ", "Brian Sam-Bodden "] license = "MIT" From b2b6b822aa17f03bc3037e3176253df5cccb2c0e Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 21:10:28 -0700 Subject: [PATCH 17/36] fix(serializer)!: update Interrupt deserialization for LangGraph 1.0 BREAKING CHANGE: Interrupt object structure changed in LangGraph 1.0 LangGraph 1.0 simplified the Interrupt class from 4 fields to 2 fields: - Removed: resumable, ns, when - Retained: value, id Updated JsonPlusRedisSerializer._revive_if_needed() to detect and reconstruct Interrupt objects using the new 2-field structure. Changes: - Check for len(obj) == 2 instead of len(obj) == 4 - Check for "id" field instead of "resumable" - Construct Interrupt(value=..., id=...) instead of old signature --- langgraph/checkpoint/redis/jsonplus_redis.py | 13 +++++-------- 1 file changed, 5 insertions(+), 8 deletions(-) diff --git a/langgraph/checkpoint/redis/jsonplus_redis.py b/langgraph/checkpoint/redis/jsonplus_redis.py index 6dd6553..7bc76b6 100644 --- a/langgraph/checkpoint/redis/jsonplus_redis.py +++ b/langgraph/checkpoint/redis/jsonplus_redis.py @@ -135,14 +135,13 @@ def _revive_if_needed(self, obj: Any) -> Any: return self._reviver(obj) # Check if this is a serialized Interrupt object - # Interrupt objects serialize to {"value": ..., "resumable": ..., "ns": ..., "when": ...} + # LangGraph 1.0+: Interrupt objects serialize to {"value": ..., "id": ...} # This must be done before recursively processing to avoid losing the structure if ( "value" in obj - and "resumable" in obj - and "when" in obj - and len(obj) == 4 - and isinstance(obj.get("resumable"), bool) + and "id" in obj + and len(obj) == 2 + and isinstance(obj.get("id"), str) ): # Try to reconstruct as an Interrupt object try: @@ -150,9 +149,7 @@ def _revive_if_needed(self, obj: Any) -> Any: return Interrupt( value=self._revive_if_needed(obj["value"]), - resumable=obj["resumable"], - ns=obj["ns"], - when=obj["when"], + id=obj["id"], ) except (ImportError, TypeError, ValueError) as e: # If we can't import or construct Interrupt, log and fall through From 578adbaefe1f7934fae624fbebb6cb85a3569f30 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 21:10:41 -0700 Subject: [PATCH 18/36] test: update Interrupt tests for LangGraph 1.0 API Update all Interrupt object creation and assertions to use the new LangGraph 1.0 API with only 'value' and 'id' fields. Changes: - Replace Interrupt(value=..., resumable=...) with Interrupt(value=..., id=...) - Remove assertions on removed fields (resumable, ns, when) - Add assertions for new 'id' field - Update test documentation to reflect LangGraph 1.0 changes Files updated: - tests/test_issue_113_interrupt_serialization.py (3 tests) - tests/test_jsonplus_redis_serializer_v3.py (3 tests) --- tests/test_issue_113_interrupt_serialization.py | 10 +++++----- tests/test_jsonplus_redis_serializer_v3.py | 13 +++++++------ 2 files changed, 12 insertions(+), 11 deletions(-) diff --git a/tests/test_issue_113_interrupt_serialization.py b/tests/test_issue_113_interrupt_serialization.py index 6fb9d53..57828c4 100644 --- a/tests/test_issue_113_interrupt_serialization.py +++ b/tests/test_issue_113_interrupt_serialization.py @@ -53,8 +53,8 @@ def test_interrupt_serialization_roundtrip(redis_url: str) -> None: serializer = JsonPlusRedisSerializer() - # Create an Interrupt object - original_interrupt = Interrupt(value={"test": "data"}, resumable=True) + # Create an Interrupt object (LangGraph 1.0 API: only value and id) + original_interrupt = Interrupt(value={"test": "data"}, id="test-interrupt-id") # Serialize it type_str, serialized = serializer.dumps_typed(original_interrupt) @@ -68,7 +68,7 @@ def test_interrupt_serialization_roundtrip(redis_url: str) -> None: f"This causes AttributeError when LangGraph tries to access attributes" ) assert deserialized.value == {"test": "data"} - assert deserialized.resumable is True + assert deserialized.id == "test-interrupt-id" def test_interrupt_in_pending_sends(redis_url: str) -> None: @@ -86,7 +86,7 @@ def test_interrupt_in_pending_sends(redis_url: str) -> None: # In the real scenario, pending_sends contains tuples of (channel, value) # where value might be an Interrupt object pending_sends = [ - ("__interrupt__", [Interrupt(value={"test": "data"}, resumable=False)]), + ("__interrupt__", [Interrupt(value={"test": "data"}, id="pending-interrupt")]), ("messages", ["some message"]), ] @@ -112,7 +112,7 @@ def test_interrupt_in_pending_sends(redis_url: str) -> None: f"This is the root cause of 'dict' object has no attribute error" ) assert value[0].value == {"test": "data"} - assert value[0].resumable is False + assert value[0].id == "pending-interrupt" def test_interrupt_resume_workflow(redis_url: str) -> None: diff --git a/tests/test_jsonplus_redis_serializer_v3.py b/tests/test_jsonplus_redis_serializer_v3.py index 3891aad..16e3ed7 100644 --- a/tests/test_jsonplus_redis_serializer_v3.py +++ b/tests/test_jsonplus_redis_serializer_v3.py @@ -113,7 +113,7 @@ def test_serialization_roundtrip_interrupt_objects() -> None: """Test serialization roundtrip for Interrupt objects (Issue #113).""" serializer = JsonPlusRedisSerializer() - interrupt = Interrupt(value={"test": "data"}, resumable=True) + interrupt = Interrupt(value={"test": "data"}, id="test-id") type_str, data_bytes = serializer.dumps_typed(interrupt) @@ -128,7 +128,7 @@ def test_serialization_roundtrip_interrupt_objects() -> None: f"This is the Issue #113 regression!" ) assert result.value == {"test": "data"} - assert result.resumable is True + assert result.id == "test-id" def test_serialization_roundtrip_nested_interrupts() -> None: @@ -137,8 +137,8 @@ def test_serialization_roundtrip_nested_interrupts() -> None: # Interrupt containing another Interrupt in value nested = Interrupt( - value={"nested": Interrupt(value={"inner": "data"}, resumable=False)}, - resumable=True, + value={"nested": Interrupt(value={"inner": "data"}, id="inner-id")}, + id="outer-id", ) type_str, data_bytes = serializer.dumps_typed(nested) @@ -147,6 +147,7 @@ def test_serialization_roundtrip_nested_interrupts() -> None: assert isinstance(result, Interrupt) assert isinstance(result.value["nested"], Interrupt) assert result.value["nested"].value == {"inner": "data"} + assert result.value["nested"].id == "inner-id" def test_serialization_roundtrip_list_of_interrupts() -> None: @@ -154,7 +155,7 @@ def test_serialization_roundtrip_list_of_interrupts() -> None: serializer = JsonPlusRedisSerializer() pending_sends = [ - ("__interrupt__", [Interrupt(value={"test": "data"}, resumable=False)]), + ("__interrupt__", [Interrupt(value={"test": "data"}, id="list-interrupt")]), ("messages", ["some message"]), ] @@ -172,7 +173,7 @@ def test_serialization_roundtrip_list_of_interrupts() -> None: # CRITICAL: Must be Interrupt object, not dict (Issue #113) assert isinstance(value[0], Interrupt) assert value[0].value == {"test": "data"} - assert value[0].resumable is False + assert value[0].id == "list-interrupt" def test_no_public_dumps_loads_methods() -> None: From 420625d0da34bf84566d899d13d9bf943e3fe96f Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 21:10:54 -0700 Subject: [PATCH 19/36] docs(examples): fix documentation and align dependency versions - Update redisvl version from >=0.5.1 to >=0.11.0 in Dockerfile and README - Fix .gitignore comment: /docs -> /examples - Fix README reference to parent directory mount path - Fix create-react-agent-hitl.ipynb to use uuid for unique thread IDs - Update notebook markdown to reference RedisStore instead of InMemoryStore - Update notebook markdown to reference RedisSaver instead of MemorySaver These changes ensure: 1. Security fix (CVE-2025-64439) via redisvl >=0.11.0 2. Accurate documentation matching actual implementations 3. Notebooks work correctly with checkpoint state isolation --- examples/.gitignore | 2 +- examples/Dockerfile.jupyter | 2 +- examples/README.md | 12 +- examples/create-react-agent-hitl.ipynb | 132 ++++-------------- .../cross-thread-persistence-functional.ipynb | 19 +-- examples/cross-thread-persistence.ipynb | 19 +-- examples/subgraph-persistence.ipynb | 6 +- 7 files changed, 40 insertions(+), 152 deletions(-) diff --git a/examples/.gitignore b/examples/.gitignore index 86bf35d..cbc0aa3 100644 --- a/examples/.gitignore +++ b/examples/.gitignore @@ -1,4 +1,4 @@ -# .gitignore for /docs directory +# .gitignore for /examples directory .ipynb_checkpoints *.pyc __pycache__ \ No newline at end of file diff --git a/examples/Dockerfile.jupyter b/examples/Dockerfile.jupyter index 2937197..d186df6 100644 --- a/examples/Dockerfile.jupyter +++ b/examples/Dockerfile.jupyter @@ -22,7 +22,7 @@ ENV PATH="/home/jupyter/venv/bin:$PATH" RUN pip install --no-cache-dir --upgrade pip && \ pip install --no-cache-dir "httpx>=0.24.0,<1.0.0" && \ pip install --no-cache-dir "langgraph>=0.3.0" && \ - pip install --no-cache-dir jupyter "redis>=5.2.1" "redisvl>=0.5.1" langchain-openai langchain-anthropic python-ulid + pip install --no-cache-dir jupyter "redis>=5.2.1" "redisvl>=0.11.0" langchain-openai langchain-anthropic python-ulid # Create a startup script that checks if local library is mounted RUN echo '#!/bin/bash\n\ diff --git a/examples/README.md b/examples/README.md index 70ee816..7195ae4 100644 --- a/examples/README.md +++ b/examples/README.md @@ -21,7 +21,7 @@ To run these notebooks using Docker (recommended for consistent environment): Note: - The first time you run this, it may take a few minutes to build the Docker image. -- When running with Docker Compose, the local library code from `../langgraph` is automatically mounted and installed, +- When running with Docker Compose, the local library code from `../` (parent directory) is automatically mounted and installed, allowing you to test changes to the library immediately without rebuilding. - If running the Docker image standalone (without docker-compose), it will install the library from PyPI instead. @@ -40,12 +40,12 @@ If you prefer to run these notebooks locally without Docker: ```bash pip install langgraph-checkpoint-redis - pip install langgraph>=0.3.0 - pip install jupyter redis>=5.2.1 redisvl>=0.5.1 - pip install langchain-openai langchain-anthropic + pip install langgraph>=0.3.0 + pip install jupyter redis>=5.2.1 redisvl>=0.11.0 + pip install langchain-openai langchain-anthropic pip install python-ulid "httpx>=0.24.0,<1.0.0" - - # Some notebooks may require additional packages, which will be installed + + # Some notebooks may require additional packages, which will be installed # within the notebooks themselves when needed ``` diff --git a/examples/create-react-agent-hitl.ipynb b/examples/create-react-agent-hitl.ipynb index e727bef..5e13d37 100644 --- a/examples/create-react-agent-hitl.ipynb +++ b/examples/create-react-agent-hitl.ipynb @@ -120,8 +120,19 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.1.0\n", - "18:45:35 langgraph.checkpoint.redis INFO Redis client is a standalone client\n" + "0.2.0\n", + "02:38:15 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "02:38:15 redisvl.index.index INFO Index already exists, not overwriting.\n", + "02:38:15 redisvl.index.index INFO Index already exists, not overwriting.\n", + "02:38:15 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_519/104821471.py:41: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" ] } ], @@ -198,35 +209,11 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what is the weather in SF, CA?\n", - "18:45:36 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " get_weather (call_lwlXXEJvgUaXb9Q8EIjSMLgJ)\n", - " Call ID: call_lwlXXEJvgUaXb9Q8EIjSMLgJ\n", - " Args:\n", - " location: SF, CA\n" - ] - } - ], - "source": [ - "\n", - "\n", - "config = {\"configurable\": {\"thread_id\": \"42\"}}\n", - "inputs = {\"messages\": [(\"user\", \"what is the weather in SF, CA?\")]}\n", - "\n", - "print_stream(graph.stream(inputs, config, stream_mode=\"values\"))" - ] + "outputs": [], + "source": "import uuid\n\nconfig = {\"configurable\": {\"thread_id\": str(uuid.uuid4())}}\ninputs = {\"messages\": [(\"user\", \"what is the weather in SF, CA?\")]}\n\nprint_stream(graph.stream(inputs, config, stream_mode=\"values\"))" }, { "cell_type": "markdown", @@ -238,18 +225,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "3decf001-7228-4ed5-8779-2b9ed98a74ea", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Next step: ('tools',)\n" - ] - } - ], + "outputs": [], "source": [ "snapshot = graph.get_state(config)\n", "print(\"Next step: \", snapshot.next)" @@ -267,35 +246,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "740bbaeb", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " get_weather (call_lwlXXEJvgUaXb9Q8EIjSMLgJ)\n", - " Call ID: call_lwlXXEJvgUaXb9Q8EIjSMLgJ\n", - " Args:\n", - " location: SF, CA\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: get_weather\n", - "\n", - "Error: AssertionError('Unknown Location')\n", - " Please fix your mistakes.\n", - "18:45:37 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " get_weather (call_ormEQsagC8POw6hpsc8mMS4W)\n", - " Call ID: call_ormEQsagC8POw6hpsc8mMS4W\n", - " Args:\n", - " location: San Francisco, CA\n" - ] - } - ], + "outputs": [], "source": [ "print_stream(graph.stream(None, config, stream_mode=\"values\"))" ] @@ -312,23 +266,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "1c81ed9f", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'configurable': {'thread_id': '42',\n", - " 'checkpoint_ns': '',\n", - " 'checkpoint_id': '1f072f58-b2bc-662b-8004-07d2cd61ee7e'}}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "state = graph.get_state(config)\n", "\n", @@ -340,31 +281,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "83148e08-63e8-49e5-a08b-02dc907bed1d", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " get_weather (call_ormEQsagC8POw6hpsc8mMS4W)\n", - " Call ID: call_ormEQsagC8POw6hpsc8mMS4W\n", - " Args:\n", - " location: San Francisco\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: get_weather\n", - "\n", - "It's always sunny in sf\n", - "18:45:38 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "The weather in San Francisco is always sunny.\n" - ] - } - ], + "outputs": [], "source": [ "print_stream(graph.stream(None, config, stream_mode=\"values\"))" ] @@ -394,9 +314,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/cross-thread-persistence-functional.ipynb b/examples/cross-thread-persistence-functional.ipynb index aad4d0d..c501fcb 100644 --- a/examples/cross-thread-persistence-functional.ipynb +++ b/examples/cross-thread-persistence-functional.ipynb @@ -119,22 +119,7 @@ "cell_type": "markdown", "id": "c4c550b5-1954-496b-8b9d-800361af17dc", "metadata": {}, - "source": [ - "### Define store\n", - "\n", - "In this example we will create a workflow that will be able to retrieve information about a user's preferences. We will do so by defining an `InMemoryStore` - an object that can store data in memory and query that data.\n", - "\n", - "When storing objects using the `Store` interface you define two things:\n", - "\n", - "* the namespace for the object, a tuple (similar to directories)\n", - "* the object key (similar to filenames)\n", - "\n", - "In our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n", - "\n", - "Importantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n", - "\n", - "Let's first define our store!" - ] + "source": "### Define store\n\nIn this example we will create a workflow that will be able to retrieve information about a user's preferences. We will do so by defining a `RedisStore` - an object that can store data in Redis and query that data.\n\nWhen storing objects using the `Store` interface you define two things:\n\n* the namespace for the object, a tuple (similar to directories)\n* the object key (similar to filenames)\n\nIn our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n\nImportantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n\nLet's first define our store!" }, { "cell_type": "code", @@ -417,4 +402,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/cross-thread-persistence.ipynb b/examples/cross-thread-persistence.ipynb index 6410a7f..0273992 100644 --- a/examples/cross-thread-persistence.ipynb +++ b/examples/cross-thread-persistence.ipynb @@ -105,22 +105,7 @@ "cell_type": "markdown", "id": "c4c550b5-1954-496b-8b9d-800361af17dc", "metadata": {}, - "source": [ - "## Define store\n", - "\n", - "In this example we will create a graph that will be able to retrieve information about a user's preferences. We will do so by defining an `InMemoryStore` - an object that can store data in memory and query that data. We will then pass the store object when compiling the graph. This allows each node in the graph to access the store: when you define node functions, you can define `store` keyword argument, and LangGraph will automatically pass the store object you compiled the graph with.\n", - "\n", - "When storing objects using the `Store` interface you define two things:\n", - "\n", - "* the namespace for the object, a tuple (similar to directories)\n", - "* the object key (similar to filenames)\n", - "\n", - "In our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n", - "\n", - "Importantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n", - "\n", - "Let's first define an `InMemoryStore` already populated with some memories about the users." - ] + "source": "## Define store\n\nIn this example we will create a graph that will be able to retrieve information about a user's preferences. We will do so by defining a `RedisStore` - an object that can store data in Redis and query that data. We will then pass the store object when compiling the graph. This allows each node in the graph to access the store: when you define node functions, you can define `store` keyword argument, and LangGraph will automatically pass the store object you compiled the graph with.\n\nWhen storing objects using the `Store` interface you define two things:\n\n* the namespace for the object, a tuple (similar to directories)\n* the object key (similar to filenames)\n\nIn our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n\nImportantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n\nLet's first define a `RedisStore` already populated with some memories about the users." }, { "cell_type": "code", @@ -410,4 +395,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/subgraph-persistence.ipynb b/examples/subgraph-persistence.ipynb index 116bcd9..a1ea5d5 100644 --- a/examples/subgraph-persistence.ipynb +++ b/examples/subgraph-persistence.ipynb @@ -175,9 +175,7 @@ "cell_type": "markdown", "id": "47084b1f-9fd5-40a9-9d75-89eb5f853d02", "metadata": {}, - "source": [ - "We can now compile the graph with an in-memory checkpointer (`MemorySaver`)." - ] + "source": "We can now compile the graph with a Redis checkpointer (`RedisSaver`)." }, { "cell_type": "code", @@ -392,4 +390,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file From 877fc60268f1fc16ec212f183919a643ea956b1a Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Sun, 16 Nov 2025 21:35:58 -0700 Subject: [PATCH 20/36] docs: add comprehensive migration guide for 0.2.0 and remove Python 3.9 from CI MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Add MIGRATION_0.2.0.md with detailed migration instructions for: * LangGraph 1.0 Interrupt API changes (4 fields → 2 fields) * Checkpoint 3.0 serialization changes (str → bytes) * Python 3.10+ requirement * Data migration strategies and troubleshooting - Rename MIGRATION.md to MIGRATION_0.1.0.md for version clarity - Remove Python 3.9 from CI test matrix (EOL and no longer supported) The migration guide covers: - Breaking changes with before/after code examples - Step-by-step migration process - Data compatibility and migration options - Comprehensive troubleshooting section - Testing recommendations --- .github/workflows/test.yml | 2 +- MIGRATION.md => MIGRATION_0.1.0.md | 10 +- MIGRATION_0.2.0.md | 651 +++++++++++++++++++++++++++++ 3 files changed, 659 insertions(+), 4 deletions(-) rename MIGRATION.md => MIGRATION_0.1.0.md (97%) create mode 100644 MIGRATION_0.2.0.md diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index eff3887..86cb69a 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -24,7 +24,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: [ 3.9, '3.10', 3.11, 3.12, 3.13 ] + python-version: [ '3.10', 3.11, 3.12, 3.13 ] redis-version: [ '6.2.6-v9', 'latest', '8.0.2' ] steps: diff --git a/MIGRATION.md b/MIGRATION_0.1.0.md similarity index 97% rename from MIGRATION.md rename to MIGRATION_0.1.0.md index 4c34b2b..71c56fa 100644 --- a/MIGRATION.md +++ b/MIGRATION_0.1.0.md @@ -24,14 +24,16 @@ This library is currently at version 0.1.0. As the library evolves, the followin The library uses structured Redis key patterns: **Standard RedisSaver (full history):** -``` + +```txt checkpoint:{thread_id}:{checkpoint_ns}:{checkpoint_id} checkpoint_blob:{thread_id}:{checkpoint_ns}:{channel}:{version} checkpoint_write:{thread_id}:{checkpoint_ns}:{checkpoint_id}:{task_id}:{idx} ``` **ShallowRedisSaver (latest only):** -``` + +```txt checkpoint:{thread_id}:{checkpoint_ns} # Single checkpoint per thread/namespace ``` @@ -88,10 +90,12 @@ saver = RedisSaver( ## Redis Module Requirements ### Redis 8.0+ + - Includes RedisJSON and RediSearch modules by default - Recommended for production use ### Redis < 8.0 + - Requires Redis Stack or manual installation of: - RedisJSON module - RediSearch module @@ -109,4 +113,4 @@ If you encounter issues during migration: 1. Check the [GitHub Issues](https://github.com/redis-developer/langgraph-redis/issues) for known problems 2. Review the [Release Notes](https://github.com/redis-developer/langgraph-redis/releases) for version changes -3. Open a new issue with details about your migration scenario \ No newline at end of file +3. Open a new issue with details about your migration scenario diff --git a/MIGRATION_0.2.0.md b/MIGRATION_0.2.0.md new file mode 100644 index 0000000..9ab0de1 --- /dev/null +++ b/MIGRATION_0.2.0.md @@ -0,0 +1,651 @@ +# Migration Guide: 0.1.x to 0.2.0 + +This guide helps you migrate from langgraph-checkpoint-redis 0.1.x to 0.2.0, which includes breaking changes due to upgrades to LangGraph 1.0 and LangGraph Checkpoint 3.0. + +## Table of Contents + +- [Overview](#overview) +- [Breaking Changes](#breaking-changes) +- [Dependency Updates](#dependency-updates) +- [Migration Steps](#migration-steps) +- [Code Changes Required](#code-changes-required) +- [Data Migration](#data-migration) +- [Troubleshooting](#troubleshooting) + +## Overview + +Version 0.2.0 represents a major upgrade that brings compatibility with: + +- **LangGraph 1.0.3** (from 0.4.9) +- **LangGraph Checkpoint 3.0** (from 2.x) +- **LangChain Core 1.0.5** (from 0.3.74) + +These upgrades include breaking API changes that require code modifications. + +## Breaking Changes + +### 1. Python Version Requirement + +**Changed:** Minimum Python version increased from **3.9 to 3.10** + +**Reason:** Python 3.9 reached end-of-life in October 2025 + +**Action Required:** + +```bash +# Ensure you're using Python 3.10 or higher +python --version # Should show 3.10.x or higher +``` + +### 2. Interrupt API Changes (LangGraph 1.0) + +**Changed:** The `Interrupt` class structure has been simplified from 4 fields to 2 fields. + +**Removed fields:** + +- `resumable` (bool) - Removed in LangGraph v0.6.0 +- `ns` (str) - Removed in LangGraph v0.6.0 +- `when` (str) - Removed in LangGraph v0.6.0 +- `interrupt_id` (property) - Deprecated in favor of `id` + +**Retained fields:** + +- `value` (Any) - The value associated with the interrupt +- `id` (str) - Unique identifier for the interrupt + +**Before (0.1.x):** + +```python +from langgraph.types import Interrupt + +# Creating an interrupt +interrupt = Interrupt( + value={"user_input": "data"}, + resumable=True, + ns="my_namespace", + when="before" +) + +# Accessing fields +if interrupt.resumable: + process(interrupt.value) +``` + +**After (0.2.0):** + +```python +from langgraph.types import Interrupt + +# Creating an interrupt +interrupt = Interrupt( + value={"user_input": "data"}, + id="unique-interrupt-id" +) + +# Accessing fields +# The 'id' field identifies the interrupt +process(interrupt.value, interrupt.id) +``` + +**Migration Note:** If you were using `resumable`, `ns`, or `when` fields to control interrupt behavior, you'll need to include this information in the `value` dict instead. + +### 3. Checkpoint Serialization API (Checkpoint 3.0) + +**Changed:** Serializer signatures now use `bytes` instead of `str` + +The `dumps_typed` and `loads_typed` methods now use `tuple[str, bytes]` instead of `tuple[str, str]`. + +**Before (Checkpoint 2.x):** + +```python +from langgraph.checkpoint.serde.base import SerializerProtocol + +class CustomSerializer(SerializerProtocol): + def dumps_typed(self, obj: Any) -> tuple[str, str]: + # Returns (type_string, data_string) + return ("json", json.dumps(obj)) + + def loads_typed(self, data: tuple[str, str]) -> Any: + type_str, data_str = data + return json.loads(data_str) +``` + +**After (Checkpoint 3.0):** + +```python +from langgraph.checkpoint.serde.base import SerializerProtocol + +class CustomSerializer(SerializerProtocol): + def dumps_typed(self, obj: Any) -> tuple[str, bytes]: + # Returns (type_string, data_bytes) + return ("json", json.dumps(obj).encode()) + + def loads_typed(self, data: tuple[str, bytes]) -> Any: + type_str, data_bytes = data + return json.loads(data_bytes.decode()) +``` + +**Impact:** This change is handled internally by `JsonPlusRedisSerializer`. **No action required** unless you've implemented a custom serializer. + +### 4. Blob Storage Format + +**Changed:** All checkpoint blobs are now stored as base64-encoded strings in Redis JSON documents. + +**Impact:** This is transparent to users - the library handles encoding/decoding automatically. + +**Internal Change:** + +```python +# 0.1.x: Blobs stored as JSON strings +{"channel": "messages", "data": "{...}"} + +# 0.2.0: Blobs stored as base64-encoded bytes +{"channel": "messages", "data": "eyJ0eXBlIjoi..."} # base64 string +``` + +**Note:** Existing checkpoints from 0.1.x will **not** be automatically migrated. See [Data Migration](#data-migration) section. + +## Dependency Updates + +```toml +# pyproject.toml changes + +[tool.poetry.dependencies] +# Before (0.1.x) +python = ">=3.9,<3.14" +langgraph = ">=0.3.0" +langgraph-checkpoint = ">=2.0.21,<3.0.0" + +# After (0.2.0) +python = ">=3.10,<3.14" +langgraph = ">=1.0.0" +langgraph-checkpoint = ">=3.0.0,<4.0.0" +redisvl = ">=0.11.0,<1.0.0" # New: Security fix for CVE-2025-64439 +``` + +### Updated Transitive Dependencies + +- `langchain-core`: 0.3.74 → 1.0.5 +- `langgraph-prebuilt`: 0.2.2 → 1.0.4 +- `langgraph-sdk`: (via langgraph) updated to 0.2.x + +## Migration Steps + +### Step 1: Check Python Version + +```bash +python --version +# Must be 3.10 or higher +``` + +If you're on Python 3.9, upgrade to Python 3.10+ before proceeding. + +### Step 2: Backup Your Data + +**Critical:** Create a backup of your Redis data before upgrading. + +```bash +# Option 1: Redis SAVE command +redis-cli -h -p SAVE + +# Option 2: Export specific keys (if you know the patterns) +redis-cli -h -p --scan --pattern "checkpoint:*" > checkpoint_keys.txt +``` + +### Step 3: Update Dependencies + +```bash +# Update langgraph-checkpoint-redis +pip install --upgrade langgraph-checkpoint-redis==0.2.0 + +# Or with poetry +poetry add langgraph-checkpoint-redis@^0.2.0 +poetry update +``` + +### Step 4: Update Your Code + +Review and update any code that uses: + +1. `Interrupt` objects (see [Interrupt API Changes](#2-interrupt-api-changes-langgraph-10)) +2. Custom serializers (see [Checkpoint Serialization API](#3-checkpoint-serialization-api-checkpoint-30)) + +### Step 5: Test Migration + +```python +# Test basic checkpoint operations +from langgraph.checkpoint.redis import RedisSaver + +with RedisSaver.from_conn_string("redis://localhost:6379") as saver: + saver.setup() + + # Test saving a checkpoint + from langgraph.checkpoint.base import Checkpoint + config = {"configurable": {"thread_id": "test-migration"}} + + checkpoint = Checkpoint( + v=1, + id="test-checkpoint", + ts="2025-01-01T00:00:00Z", + channel_values={}, + channel_versions={}, + versions_seen={}, + ) + + # This should work without errors + metadata = {"source": "migration_test"} + saver.put(config, checkpoint, metadata, {}) + + # Verify retrieval + retrieved = saver.get_tuple(config) + assert retrieved is not None + print("✓ Migration test passed!") +``` + +## Code Changes Required + +### If You Use Interrupts + +**Search for:** `Interrupt(` in your codebase + +**Update pattern:** + +```python +# Before +from langgraph.types import Interrupt +interrupt = Interrupt( + value=data, + resumable=True, + ns="my_ns", + when="before" +) + +# After +from langgraph.types import Interrupt +import uuid + +# Move metadata into the value if needed +interrupt = Interrupt( + value={ + "data": data, + # Optional: Include old metadata in value if needed + "_metadata": { + "resumable": True, + "ns": "my_ns", + "when": "before" + } + }, + id=str(uuid.uuid4()) # or your own ID generation +) +``` + +### If You Access Interrupt Fields + +**Search for:** `.resumable`, `.ns`, `.when`, `.interrupt_id` in your codebase + +**Update pattern:** + +```python +# Before +if interrupt.resumable: + handle_resumable(interrupt.value) + +namespace = interrupt.ns +timing = interrupt.when + +# After +# Check metadata in value instead +metadata = interrupt.value.get("_metadata", {}) +if metadata.get("resumable"): + handle_resumable(interrupt.value["data"]) + +namespace = metadata.get("ns") +timing = metadata.get("when") +``` + +### If You Have Custom Serializers + +**Search for:** Classes that inherit from `SerializerProtocol` or override `dumps_typed`/`loads_typed` + +**Update pattern:** + +```python +from langgraph.checkpoint.serde.base import SerializerProtocol +from typing import Any + +class MySerializer(SerializerProtocol): + # Before: Returns tuple[str, str] + # After: Returns tuple[str, bytes] + + def dumps_typed(self, obj: Any) -> tuple[str, bytes]: + import json + # Return bytes instead of str + return ("json", json.dumps(obj).encode("utf-8")) + + def loads_typed(self, data: tuple[str, bytes]) -> Any: + import json + type_str, data_bytes = data + # Expect bytes instead of str + return json.loads(data_bytes.decode("utf-8")) +``` + +## Data Migration + +### Checkpoint Data Compatibility + +**Important:** Checkpoints created with 0.1.x are **not directly compatible** with 0.2.0 due to: + +1. Blob encoding changes (base64 format) +2. Serialization format changes (bytes vs strings) +3. Interrupt object structure changes + +### Migration Options + +#### Option 1: Fresh Start (Recommended for Development) + +If you don't need to preserve checkpoint history: + +```python +from langgraph.checkpoint.redis import RedisSaver +import redis + +# Clear old checkpoints +redis_client = redis.from_url("redis://localhost:6379") +keys = redis_client.keys("checkpoint:*") +if keys: + redis_client.delete(*keys) + +# Recreate indices with new version +with RedisSaver.from_conn_string("redis://localhost:6379") as saver: + saver.setup() +``` + +#### Option 2: Parallel Deployment (Recommended for Production) + +Run both versions in parallel during transition: + +```python +# Deploy 0.2.0 with a different key prefix or database +REDIS_URL_NEW = "redis://localhost:6379/1" # Different database +REDIS_URL_OLD = "redis://localhost:6379/0" # Old database + +# New code uses 0.2.0 +from langgraph.checkpoint.redis import RedisSaver +saver_new = RedisSaver.from_conn_string(REDIS_URL_NEW) + +# Gradually migrate traffic to new version +# Old traffic continues on 0.1.x until fully migrated +``` + +#### Option 3: Custom Migration Script + +If you must migrate existing checkpoints: + +```python +from langgraph.checkpoint.redis import RedisSaver +import redis +import json +import base64 + +def migrate_checkpoints(): + """ + WARNING: This is a template. Test thoroughly before using in production. + """ + old_saver = RedisSaver.from_conn_string("redis://localhost:6379") + + # Get all checkpoint keys + redis_client = redis.from_url("redis://localhost:6379") + checkpoint_keys = redis_client.keys("checkpoint:*") + + for key in checkpoint_keys: + try: + # Read old checkpoint + old_data = redis_client.json().get(key) + + # Transform blobs to base64 if needed + if "channel_values" in old_data: + for channel, value in old_data["channel_values"].items(): + if isinstance(value, str): + # Encode to base64 + old_data["channel_values"][channel] = base64.b64encode( + value.encode() + ).decode() + + # Update Interrupt objects if present + # This requires inspecting your specific checkpoint structure + + # Write back + redis_client.json().set(key, "$", old_data) + print(f"✓ Migrated {key}") + + except Exception as e: + print(f"✗ Failed to migrate {key}: {e}") + raise + +# IMPORTANT: Test on a copy of your data first! +# migrate_checkpoints() +``` + +**Warning:** Custom migration scripts should be thoroughly tested on copies of your data. Consider the parallel deployment approach instead. + +### RedisStore Data + +`RedisStore` data (cross-thread persistence) should remain compatible. The store uses a different indexing scheme and doesn't rely on the checkpoint serialization format. + +## Troubleshooting + +### Issue: ImportError for Interrupt + +```python +ImportError: cannot import name 'Interrupt' from 'langgraph.types' +``` + +**Solution:** Ensure langgraph is upgraded to 1.0+ + +```bash +pip install --upgrade langgraph>=1.0.0 +``` + +### Issue: AttributeError: 'Interrupt' object has no attribute 'resumable' + +```python +AttributeError: 'Interrupt' object has no attribute 'resumable' +``` + +**Solution:** Update code to use only `value` and `id` fields (see [Interrupt API Changes](#2-interrupt-api-changes-langgraph-10)) + +### Issue: orjson.JSONDecodeError when loading checkpoints + +```python +orjson.JSONDecodeError: unexpected character: ... +``` + +**Solution:** This indicates you're trying to load a checkpoint created with 0.1.x. See [Data Migration](#data-migration) for options. + +### Issue: Tests failing after upgrade + +**Common causes:** + +1. Test mocks assume old Interrupt structure +2. Fixtures use old checkpoint format +3. Test assertions check removed fields + +**Solution:** Update tests to match new APIs: + +```python +# Before +def test_interrupt(): + interrupt = Interrupt(value={"test": "data"}, resumable=True) + assert interrupt.resumable is True + +# After +def test_interrupt(): + interrupt = Interrupt(value={"test": "data"}, id="test-id") + assert interrupt.id == "test-id" +``` + +### Issue: Existing checkpoints not loading + +**Symptoms:** `get_tuple()` returns None for previously saved checkpoints + +**Cause:** Blob encoding format changed from JSON strings to base64 bytes + +**Solutions:** + +1. Fresh start: Clear old data and recreate (see Option 1 in [Data Migration](#data-migration)) +2. Parallel deployment: Run 0.2.0 in parallel with 0.1.x (see Option 2) +3. Custom migration: Write a migration script (see Option 3) + +### Issue: SecurityError about redisvl version + +```python +WARNING: redisvl version <0.11.0 has known vulnerability CVE-2025-64439 +``` + +**Solution:** Ensure redisvl>=0.11.0 is installed + +```bash +pip install --upgrade redisvl>=0.11.0 +``` + +## Configuration Changes + +### TTL Configuration (Unchanged) + +TTL configuration remains the same: + +```python +from langgraph.checkpoint.redis import RedisSaver + +saver = RedisSaver( + redis_url="redis://localhost:6379", + ttl={ + "default_ttl": 60, # Still in MINUTES + "refresh_on_read": True + } +) +``` + +### Shallow Checkpointing (Unchanged) + +ShallowRedisSaver usage remains unchanged: + +```python +from langgraph.checkpoint.redis.shallow import ShallowRedisSaver + +saver = ShallowRedisSaver( + redis_url="redis://localhost:6379", + key_cache_max_size=2000, + channel_cache_max_size=200 +) +``` + +## Testing Your Migration + +Create a comprehensive test suite to verify the migration: + +```python +import pytest +from langgraph.checkpoint.redis import RedisSaver +from langgraph.types import Interrupt +import uuid + +def test_checkpoint_roundtrip(): + """Test basic checkpoint save/load""" + with RedisSaver.from_conn_string("redis://localhost:6379") as saver: + saver.setup() + + config = {"configurable": {"thread_id": str(uuid.uuid4())}} + + # Create and save checkpoint + from langgraph.checkpoint.base import Checkpoint + checkpoint = Checkpoint( + v=1, + id=str(uuid.uuid4()), + ts="2025-01-01T00:00:00Z", + channel_values={"messages": ["test"]}, + channel_versions={"messages": 1}, + versions_seen={}, + ) + + saver.put(config, checkpoint, {"test": True}, {}) + + # Retrieve and verify + retrieved = saver.get_tuple(config) + assert retrieved is not None + assert retrieved.checkpoint.channel_values == checkpoint.channel_values + +def test_interrupt_serialization(): + """Test Interrupt object handling""" + from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer + + serializer = JsonPlusRedisSerializer() + + # Create interrupt with new API + interrupt = Interrupt( + value={"test": "data"}, + id="test-interrupt-id" + ) + + # Serialize + type_str, data_bytes = serializer.dumps_typed(interrupt) + assert type_str == "json" + assert isinstance(data_bytes, bytes) + + # Deserialize + result = serializer.loads_typed((type_str, data_bytes)) + assert isinstance(result, Interrupt) + assert result.value == {"test": "data"} + assert result.id == "test-interrupt-id" + +def test_interrupt_in_checkpoint(): + """Test interrupts within checkpoint workflow""" + from langgraph.types import interrupt + + # The interrupt() function should work as expected + # This would be tested in an actual graph context + pass + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) +``` + +## Getting Help + +If you encounter issues during migration: + +1. **Check the release notes:** Review the [CHANGELOG](CHANGELOG.md) for detailed changes +2. **GitHub Issues:** Search [langgraph-redis issues](https://github.com/redis-developer/langgraph-redis/issues) for similar problems +3. **LangGraph Documentation:** Review [LangGraph 1.0 docs](https://langchain-ai.github.io/langgraph/) for upstream changes +4. **Open an issue:** If you find a bug, [open a new issue](https://github.com/redis-developer/langgraph-redis/issues/new) with: + - Your Python version + - Full error traceback + - Minimal code to reproduce the issue + - Version information: `pip list | grep langgraph` + +## Reference + +### Version Information + +```bash +# Check installed versions +pip show langgraph-checkpoint-redis langgraph langgraph-checkpoint langchain-core + +# Expected versions for 0.2.0: +# langgraph-checkpoint-redis: 0.2.0 +# langgraph: >=1.0.0 +# langgraph-checkpoint: >=3.0.0 +# langchain-core: >=1.0.0 +``` + +### Related Documentation + +- [LangGraph 1.0 Documentation](https://langchain-ai.github.io/langgraph/) +- [LangChain Core 1.0 Release](https://blog.langchain.com/langchain-langgraph-1dot0/) +- [Checkpoint 3.0 Changes](https://github.com/langchain-ai/langgraph/releases) +- [Migration from 0.1.0](MIGRATION_0.1.0.md) (previous migration guide) + +--- + +**Last Updated:** January 2025 +**Applies to:** langgraph-checkpoint-redis 0.2.0 From 2e1c882c73318a624c5e9416418dfcac8fad64f2 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 08:02:12 -0700 Subject: [PATCH 21/36] feat(client-info)!: add full library version info to Redis client tracking - Add client_setinfo calls in RedisSaver.configure_client() to register library version with Redis - Update all set_client_info/aset_client_info methods to use __full_lib_name__ instead of __redisvl_version__ - Ensure graceful error handling with fallback to echo() and silent failure - Remove redundant test_jsonplus_redis_serializer.py from root directory - Update all client info tests to expect full library name format - Add client_setinfo/echo mock methods to BaseMockRedis for cluster mode tests BREAKING CHANGE: Client info now sends complete version string format: redis-py(redisvl_v{version};langgraph-checkpoint-redis_v{version}) This provides better visibility in Redis CLIENT LIST for monitoring and debugging, showing redis-py client, RedisVL version, and checkpoint-redis library version. --- langgraph/checkpoint/redis/__init__.py | 15 + langgraph/checkpoint/redis/base.py | 9 +- langgraph/store/redis/base.py | 18 +- poetry.lock | 3068 +++++++++++++----------- test_jsonplus_redis_serializer.py | 167 -- tests/test_async.py | 10 +- tests/test_async_store.py | 17 +- tests/test_base_client_info_and_ttl.py | 8 +- tests/test_cluster_mode.py | 8 + tests/test_shallow_async.py | 17 +- tests/test_store.py | 14 +- 11 files changed, 1694 insertions(+), 1657 deletions(-) delete mode 100644 test_jsonplus_redis_serializer.py diff --git a/langgraph/checkpoint/redis/__init__.py b/langgraph/checkpoint/redis/__init__.py index 2278c0d..fc4727d 100644 --- a/langgraph/checkpoint/redis/__init__.py +++ b/langgraph/checkpoint/redis/__init__.py @@ -94,11 +94,26 @@ def configure_client( connection_args: Optional[Dict[str, Any]] = None, ) -> None: """Configure the Redis client.""" + from redis.exceptions import ResponseError + + from langgraph.checkpoint.redis.version import __full_lib_name__ + self._owns_its_client = redis_client is None self._redis = redis_client or RedisConnectionFactory.get_redis_connection( redis_url, **connection_args ) + # Set client info for Redis monitoring + try: + self._redis.client_setinfo("LIB-NAME", __full_lib_name__) + except (ResponseError, AttributeError): + # Fall back to a simple echo if client_setinfo is not available + try: + self._redis.echo(__full_lib_name__) + except Exception: + # Silently fail if even echo doesn't work + pass + def create_indexes(self) -> None: self.checkpoints_index = SearchIndex.from_dict( self.SCHEMAS[0], redis_client=self._redis diff --git a/langgraph/checkpoint/redis/base.py b/langgraph/checkpoint/redis/base.py index 007d501..29fbd9c 100644 --- a/langgraph/checkpoint/redis/base.py +++ b/langgraph/checkpoint/redis/base.py @@ -175,19 +175,16 @@ async def aset_client_info(self) -> None: """Set client info for Redis monitoring asynchronously.""" from redis.exceptions import ResponseError - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Create the client info string with only the redisvl version - client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ try: # Try to use client_setinfo command if available - await self._redis.client_setinfo("LIB-NAME", client_info) + await self._redis.client_setinfo("LIB-NAME", __full_lib_name__) except (ResponseError, AttributeError): # Fall back to a simple echo if client_setinfo is not available try: # Call with await to ensure it's an async call - echo_result = self._redis.echo(client_info) + echo_result = self._redis.echo(__full_lib_name__) if hasattr(echo_result, "__await__"): await echo_result except Exception: diff --git a/langgraph/store/redis/base.py b/langgraph/store/redis/base.py index bd278ec..becae85 100644 --- a/langgraph/store/redis/base.py +++ b/langgraph/store/redis/base.py @@ -325,18 +325,15 @@ def __init__( def set_client_info(self) -> None: """Set client info for Redis monitoring.""" - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Create the client info string with only the redisvl version - client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ try: # Try to use client_setinfo command if available - self._redis.client_setinfo("LIB-NAME", client_info) + self._redis.client_setinfo("LIB-NAME", __full_lib_name__) except (ResponseError, AttributeError): # Fall back to a simple echo if client_setinfo is not available try: - self._redis.echo(client_info) + self._redis.echo(__full_lib_name__) except Exception: # Silently fail if even echo doesn't work pass @@ -344,19 +341,16 @@ def set_client_info(self) -> None: async def aset_client_info(self) -> None: """Set client info for Redis monitoring asynchronously.""" - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Create the client info string with only the redisvl version - client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ try: # Try to use client_setinfo command if available - await self._redis.client_setinfo("LIB-NAME", client_info) + await self._redis.client_setinfo("LIB-NAME", __full_lib_name__) except (ResponseError, AttributeError): # Fall back to a simple echo if client_setinfo is not available try: # Call with await to ensure it's an async call - echo_result = self._redis.echo(client_info) + echo_result = self._redis.echo(__full_lib_name__) if hasattr(echo_result, "__await__"): await echo_result except Exception: diff --git a/poetry.lock b/poetry.lock index 3b16719..a527d57 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,21 +1,19 @@ # This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. -# This file is automatically @generated by Poetry 2.0.1 and should not be changed by hand. 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{file = "zstandard-0.25.0.tar.gz", hash = "sha256:7713e1179d162cf5c7906da876ec2ccb9c3a9dcbdffef0cc7f70c3667a205f0b"}, ] -[package.dependencies] -cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\""} - [package.extras] -cffi = ["cffi (>=1.11)"] +cffi = ["cffi (>=1.17,<2.0)", "cffi (>=2.0.0b)"] [metadata] lock-version = "2.1" diff --git a/test_jsonplus_redis_serializer.py b/test_jsonplus_redis_serializer.py deleted file mode 100644 index 0817e39..0000000 --- a/test_jsonplus_redis_serializer.py +++ /dev/null @@ -1,167 +0,0 @@ -"""Standalone test to verify the JsonPlusRedisSerializer fix works. - -This can be run directly without pytest infrastructure: - python test_fix_standalone.py -""" - -from langchain_core.messages import AIMessage, HumanMessage, SystemMessage -from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer - - -def test_human_message_serialization(): - """Test that HumanMessage can be serialized without TypeError.""" - print("Testing HumanMessage serialization...") - - serializer = JsonPlusRedisSerializer() - msg = HumanMessage(content="What is the weather?", id="msg-1") - - # Checkpoint 3.0: Use dumps_typed instead of dumps - type_str, serialized = serializer.dumps_typed(msg) - print(f" ✓ Serialized to {len(serialized)} bytes (type: {type_str})") - - # Deserialize - deserialized = serializer.loads_typed((type_str, serialized)) - assert isinstance(deserialized, HumanMessage) - assert deserialized.content == "What is the weather?" - assert deserialized.id == "msg-1" - print(f" ✓ Deserialized correctly: {deserialized.content}") - - -def test_all_message_types(): - """Test all LangChain message types.""" - print("\nTesting all message types...") - - serializer = JsonPlusRedisSerializer() - messages = [ - HumanMessage(content="Hello"), - AIMessage(content="Hi!"), - SystemMessage(content="System prompt"), - ] - - for msg in messages: - type_str, serialized = serializer.dumps_typed(msg) - deserialized = serializer.loads_typed((type_str, serialized)) - assert type(deserialized) == type(msg) - print(f" ✓ {type(msg).__name__} works") - - -def test_message_list(): - """Test list of messages (common pattern in LangGraph).""" - print("\nTesting message list...") - - serializer = JsonPlusRedisSerializer() - messages = [ - HumanMessage(content="Question 1"), - AIMessage(content="Answer 1"), - HumanMessage(content="Question 2"), - ] - - type_str, serialized = serializer.dumps_typed(messages) - deserialized = serializer.loads_typed((type_str, serialized)) - - assert isinstance(deserialized, list) - assert len(deserialized) == 3 - assert all(isinstance(m, (HumanMessage, AIMessage)) for m in deserialized) - print(f" ✓ List of {len(deserialized)} messages works") - - -def test_nested_structure(): - """Test nested structure with messages (realistic LangGraph state).""" - print("\nTesting nested structure with messages...") - - serializer = JsonPlusRedisSerializer() - state = { - "messages": [ - HumanMessage(content="Query"), - AIMessage(content="Response"), - ], - "step": 1, - } - - type_str, serialized = serializer.dumps_typed(state) - deserialized = serializer.loads_typed((type_str, serialized)) - - assert "messages" in deserialized - assert len(deserialized["messages"]) == 2 - assert isinstance(deserialized["messages"][0], HumanMessage) - assert isinstance(deserialized["messages"][1], AIMessage) - print(f" ✓ Nested structure works") - - -def test_dumps_typed(): - """Test dumps_typed (what checkpointer actually uses).""" - print("\nTesting dumps_typed...") - - serializer = JsonPlusRedisSerializer() - msg = HumanMessage(content="Test", id="test-123") - - type_str, blob = serializer.dumps_typed(msg) - assert type_str == "json" - # Checkpoint 3.0: blob is now bytes, not str - assert isinstance(blob, bytes) - print(f" ✓ dumps_typed returns: type='{type_str}', blob={len(blob)} bytes") - - deserialized = serializer.loads_typed((type_str, blob)) - assert isinstance(deserialized, HumanMessage) - assert deserialized.content == "Test" - print(f" ✓ loads_typed works correctly") - - -def test_backwards_compatibility(): - """Test that regular objects still work.""" - print("\nTesting backwards compatibility...") - - serializer = JsonPlusRedisSerializer() - test_cases = [ - ("string", "hello"), - ("int", 42), - ("dict", {"key": "value"}), - ("list", [1, 2, 3]), - ] - - for name, obj in test_cases: - type_str, serialized = serializer.dumps_typed(obj) - deserialized = serializer.loads_typed((type_str, serialized)) - assert deserialized == obj - print(f" ✓ {name} works") - - -def main(): - """Run all tests.""" - print("=" * 70) - print("JsonPlusRedisSerializer Fix Validation") - print("=" * 70) - - tests = [ - test_human_message_serialization, - test_all_message_types, - test_message_list, - test_nested_structure, - test_dumps_typed, - test_backwards_compatibility, - ] - - passed = 0 - failed = 0 - for test in tests: - try: - test() - passed += 1 - except Exception as e: - print(f" ✗ {test.__name__} FAILED: {e}") - failed += 1 - - print("\n" + "=" * 70) - print(f"Results: {passed}/{len(tests)} tests passed") - print("=" * 70) - - if failed == 0: - print("\n✅ ALL TESTS PASSED - Fix is working correctly!") - return 0 - else: - print(f"\n❌ {failed} TESTS FAILED - Fix may not be working") - return 1 - - -if __name__ == "__main__": - exit(main()) diff --git a/tests/test_async.py b/tests/test_async.py index 5e2d6b9..d427bf2 100644 --- a/tests/test_async.py +++ b/tests/test_async.py @@ -283,10 +283,7 @@ async def test_from_conn_string_cleanup(redis_url: str) -> None: @pytest.mark.asyncio async def test_async_client_info_setting(redis_url: str, monkeypatch) -> None: """Test that async client_setinfo is called with correct library information.""" - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Expected client info format - expected_client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ # Track if client_setinfo was called with the right parameters client_info_called = False @@ -297,9 +294,8 @@ async def test_async_client_info_setting(redis_url: str, monkeypatch) -> None: # Create a mock function for client_setinfo async def mock_client_setinfo(self, key, value): nonlocal client_info_called - # Note: RedisVL might call this with its own lib name first - # We only track calls with our full lib name - if key == "LIB-NAME" and value == expected_client_info: + # Track calls with our full lib name + if key == "LIB-NAME" and value == __full_lib_name__: client_info_called = True # Call original method to ensure normal function return await original_client_setinfo(self, key, value) diff --git a/tests/test_async_store.py b/tests/test_async_store.py index 6546860..26e52cf 100644 --- a/tests/test_async_store.py +++ b/tests/test_async_store.py @@ -544,10 +544,7 @@ async def test_async_redis_store_client_info(redis_url: str, monkeypatch) -> Non """Test that AsyncRedisStore sets client info correctly.""" from redis.asyncio import Redis - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Expected client info format - expected_client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ # Track if client_setinfo was called with the right parameters client_info_called = False @@ -558,9 +555,8 @@ async def test_async_redis_store_client_info(redis_url: str, monkeypatch) -> Non # Create a mock function for client_setinfo async def mock_client_setinfo(self, key, value): nonlocal client_info_called - # Note: RedisVL might call this with its own lib name first - # We only track calls with our full lib name - if key == "LIB-NAME" and value == expected_client_info: + # Track calls with our full lib name + if key == "LIB-NAME" and value == __full_lib_name__: client_info_called = True # Call original method to ensure normal function return await original_client_setinfo(self, key, value) @@ -584,10 +580,7 @@ async def test_async_redis_store_client_info_fallback( from redis.asyncio import Redis from redis.exceptions import ResponseError - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Expected client info format - expected_client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ # Remove client_setinfo to simulate older Redis version async def mock_client_setinfo(self, key, value): @@ -601,7 +594,7 @@ async def mock_client_setinfo(self, key, value): async def mock_echo(self, message): nonlocal echo_called echo_called = True - assert message == expected_client_info + assert message == __full_lib_name__ return await original_echo(self, message) # Apply the mocks diff --git a/tests/test_base_client_info_and_ttl.py b/tests/test_base_client_info_and_ttl.py index 0b3a8f1..0e84406 100644 --- a/tests/test_base_client_info_and_ttl.py +++ b/tests/test_base_client_info_and_ttl.py @@ -90,12 +90,10 @@ async def test_aset_client_info_success(): # Mock async client_setinfo saver._redis.client_setinfo = AsyncMock() - with patch("langgraph.checkpoint.redis.version.__redisvl_version__", "1.2.3"): + with patch("langgraph.checkpoint.redis.version.__full_lib_name__", "test-lib-v1.0"): await saver.aset_client_info() - saver._redis.client_setinfo.assert_called_once_with( - "LIB-NAME", "redis-py(redisvl_v1.2.3)" - ) + saver._redis.client_setinfo.assert_called_once_with("LIB-NAME", "test-lib-v1.0") @pytest.mark.asyncio @@ -112,7 +110,7 @@ async def mock_echo(msg): saver._redis.echo = mock_echo - with patch("langgraph.checkpoint.redis.version.__redisvl_version__", "1.2.3"): + with patch("langgraph.checkpoint.redis.version.__full_lib_name__", "test-lib-v1.0"): await saver.aset_client_info() saver._redis.client_setinfo.assert_called_once() diff --git a/tests/test_cluster_mode.py b/tests/test_cluster_mode.py index 205e230..0813c2a 100644 --- a/tests/test_cluster_mode.py +++ b/tests/test_cluster_mode.py @@ -92,6 +92,14 @@ def cluster(self, subcmd: str, *args, **kwargs): raise ResponseError("ERR This instance has cluster support disabled") return {} + def client_setinfo(self, key, value): + """Mock client_setinfo for testing.""" + return "OK" + + def echo(self, message): + """Mock echo for testing.""" + return message + class MockRedis(BaseMockRedis, Redis): pass diff --git a/tests/test_shallow_async.py b/tests/test_shallow_async.py index 75a4aea..e563117 100644 --- a/tests/test_shallow_async.py +++ b/tests/test_shallow_async.py @@ -262,10 +262,7 @@ async def test_from_conn_string_errors(redis_url: str) -> None: @pytest.mark.asyncio async def test_async_shallow_client_info_setting(redis_url: str, monkeypatch) -> None: """Test that client_setinfo is called with correct library information in AsyncShallowRedisSaver.""" - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Expected client info format - expected_client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ # Track if client_setinfo was called with the right parameters client_info_called = False @@ -276,9 +273,8 @@ async def test_async_shallow_client_info_setting(redis_url: str, monkeypatch) -> # Create a mock function for client_setinfo async def mock_client_setinfo(self, key, value): nonlocal client_info_called - # Note: RedisVL might call this with its own lib name first - # We only track calls with our full lib name - if key == "LIB-NAME" and value == expected_client_info: + # Track calls with our full lib name + if key == "LIB-NAME" and value == __full_lib_name__: client_info_called = True # Call original method to ensure normal function return await original_client_setinfo(self, key, value) @@ -300,10 +296,7 @@ async def test_async_shallow_client_info_fallback(redis_url: str, monkeypatch) - from redis.asyncio import Redis from redis.exceptions import ResponseError - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Expected client info format - expected_client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ # Create a Redis client directly first - this bypasses RedisVL validation client = Redis.from_url(redis_url) @@ -321,7 +314,7 @@ async def mock_client_setinfo(self, key, value): async def mock_echo(self, message): nonlocal echo_called, echo_messages echo_messages.append(message) - if message == expected_client_info: + if message == __full_lib_name__: echo_called = True return ( await original_echo(self, message) diff --git a/tests/test_store.py b/tests/test_store.py index c37e8d5..baa5263 100644 --- a/tests/test_store.py +++ b/tests/test_store.py @@ -530,10 +530,7 @@ def test_redis_store_client_info(redis_url: str, monkeypatch) -> None: """Test that RedisStore sets client info correctly.""" from redis import Redis as NativeRedis - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Expected client info format - expected_client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ # Create a direct Redis client to bypass RedisVL validation client = NativeRedis.from_url(redis_url) @@ -546,7 +543,7 @@ def test_redis_store_client_info(redis_url: str, monkeypatch) -> None: def mock_client_setinfo(self, key, value): nonlocal client_info_called # We only track calls with our full lib name - if key == "LIB-NAME" and value == expected_client_info: + if key == "LIB-NAME" and value == __full_lib_name__: client_info_called = True return original_client_setinfo(self, key, value) @@ -568,10 +565,7 @@ def test_redis_store_client_info_fallback(redis_url: str, monkeypatch) -> None: """Test that RedisStore falls back to echo when client_setinfo is not available.""" from redis import Redis as NativeRedis - from langgraph.checkpoint.redis.version import __redisvl_version__ - - # Expected client info format - expected_client_info = f"redis-py(redisvl_v{__redisvl_version__})" + from langgraph.checkpoint.redis.version import __full_lib_name__ # Create a direct Redis client to bypass RedisVL validation client = NativeRedis.from_url(redis_url) @@ -588,7 +582,7 @@ def mock_client_setinfo(self, key, value): def mock_echo(self, message): nonlocal echo_called # We only want to track our library's echo calls - if message == expected_client_info: + if message == __full_lib_name__: echo_called = True return original_echo(self, message) From 72367880a172f4358210d976b92035513b46ec8f Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 08:31:54 -0700 Subject: [PATCH 22/36] fix(serializer): fix false possitive interrupt detection - Move base64 imports to top of test files for better style (test_sync.py, test_async.py) - Make exception handling more specific in _default_handler (AttributeError, KeyError, ValueError, TypeError instead of bare Exception) - Fix false positive Interrupt detection by adding __interrupt__ type marker to prevent user data with {value, id} structure from being incorrectly deserialized as Interrupt objects - Add _preprocess_interrupts helper to recursively tag Interrupt objects before orjson serialization - Support preprocessing of nested structures (dicts, lists, tuples) This prevents critical bug where user data like {"value": "data", "id": "user-id"} would be incorrectly deserialized as Interrupt(value="data", id="user-id"). --- langgraph/checkpoint/redis/jsonplus_redis.py | 50 +++++++++++++++++--- tests/test_async.py | 3 +- tests/test_sync.py | 3 +- 3 files changed, 45 insertions(+), 11 deletions(-) diff --git a/langgraph/checkpoint/redis/jsonplus_redis.py b/langgraph/checkpoint/redis/jsonplus_redis.py index 7bc76b6..2fca376 100644 --- a/langgraph/checkpoint/redis/jsonplus_redis.py +++ b/langgraph/checkpoint/redis/jsonplus_redis.py @@ -37,6 +37,16 @@ def _default_handler(self, obj: Any) -> Any: if isinstance(obj, (bytes, bytearray)): raise TypeError("bytes/bytearray in nested structure - use msgpack") + # Handle Interrupt objects with a type marker to avoid false positives + from langgraph.types import Interrupt + + if isinstance(obj, Interrupt): + return { + "__interrupt__": True, + "value": obj.value, + "id": obj.id, + } + # Try to encode using parent's constructor args encoder # This creates the {"lc": 2, "type": "constructor", ...} format try: @@ -53,10 +63,34 @@ def _default_handler(self, obj: Any) -> Any: return self._encode_constructor_args( type(obj), kwargs=obj.__dict__ if hasattr(obj, "__dict__") else {} ) - except Exception: + except (AttributeError, KeyError, ValueError, TypeError): # For types we can't handle, raise TypeError raise TypeError(f"Object of type {type(obj)} is not JSON serializable") + def _preprocess_interrupts(self, obj: Any) -> Any: + """Recursively add type markers to Interrupt objects before serialization. + + This prevents false positives where user data with {value, id} fields + could be incorrectly deserialized as Interrupt objects. + """ + from langgraph.types import Interrupt + + if isinstance(obj, Interrupt): + # Add type marker to distinguish from plain dicts + return { + "__interrupt__": True, + "value": self._preprocess_interrupts(obj.value), + "id": obj.id, + } + elif isinstance(obj, dict): + return {k: self._preprocess_interrupts(v) for k, v in obj.items()} + elif isinstance(obj, (list, tuple)): + processed = [self._preprocess_interrupts(item) for item in obj] + # Preserve tuple type + return tuple(processed) if isinstance(obj, tuple) else processed + else: + return obj + def dumps_typed(self, obj: Any) -> tuple[str, bytes]: """Serialize using orjson for JSON. @@ -73,8 +107,10 @@ def dumps_typed(self, obj: Any) -> tuple[str, bytes]: return "null", b"" else: try: + # Preprocess to add type markers to Interrupt objects + processed_obj = self._preprocess_interrupts(obj) # Try orjson first with custom default handler - json_bytes = orjson.dumps(obj, default=self._default_handler) + json_bytes = orjson.dumps(processed_obj, default=self._default_handler) return "json", json_bytes except (TypeError, orjson.JSONEncodeError): # Fall back to parent's msgpack serialization for bytes in nested structures @@ -134,14 +170,14 @@ def _revive_if_needed(self, obj: Any) -> Any: # the actual LangChain object (e.g., HumanMessage, AIMessage) return self._reviver(obj) - # Check if this is a serialized Interrupt object - # LangGraph 1.0+: Interrupt objects serialize to {"value": ..., "id": ...} + # Check if this is a serialized Interrupt object with type marker + # LangGraph 1.0+: Interrupt objects serialize to {"__interrupt__": True, "value": ..., "id": ...} # This must be done before recursively processing to avoid losing the structure if ( - "value" in obj + obj.get("__interrupt__") is True + and "value" in obj and "id" in obj - and len(obj) == 2 - and isinstance(obj.get("id"), str) + and len(obj) == 3 ): # Try to reconstruct as an Interrupt object try: diff --git a/tests/test_async.py b/tests/test_async.py index d427bf2..73e53b8 100644 --- a/tests/test_async.py +++ b/tests/test_async.py @@ -1,6 +1,7 @@ """Tests for AsyncRedisSaver.""" import asyncio +import base64 import json import time from concurrent.futures import ThreadPoolExecutor @@ -513,8 +514,6 @@ async def test_search_writes_async(redis_url: str) -> None: doc3 = json.loads(results.docs[2].json) # Blobs are now base64-encoded in Redis (checkpoint 3.0) - import base64 - assert base64.b64decode(doc1["blob"]).decode() == '"value1"' assert base64.b64decode(doc2["blob"]).decode() == '"value2"' assert base64.b64decode(doc3["blob"]).decode() == '"value3"' diff --git a/tests/test_sync.py b/tests/test_sync.py index f6c4292..55f73e9 100644 --- a/tests/test_sync.py +++ b/tests/test_sync.py @@ -1,3 +1,4 @@ +import base64 import json import time from concurrent.futures import ThreadPoolExecutor @@ -268,8 +269,6 @@ def test_search_writes(redis_url: str) -> None: doc3 = json.loads(results.docs[2].json) # Blobs are now base64-encoded in Redis (checkpoint 3.0) - import base64 - assert base64.b64decode(doc1["blob"]).decode() == '"value1"' assert base64.b64decode(doc2["blob"]).decode() == '"value2"' assert base64.b64decode(doc3["blob"]).decode() == '"value3"' From d89b5ac798b3009a56537cdc669b9121b651d483 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 08:50:41 -0700 Subject: [PATCH 23/36] chore(tests): suppress testcontainers deprecation warnings Add pytest filterwarnings to ignore DeprecationWarning from testcontainers library's internal use of @wait_container_is_ready decorator. These warnings come from testcontainers v4.13.3 (latest) and are not our code to fix. The testcontainers maintainers haven't updated their own internal code yet despite deprecating the decorator. Warnings suppressed: - testcontainers.core.waiting_utils (line 215) - testcontainers.redis (line 46) This keeps test output clean while we wait for upstream fix. --- pyproject.toml | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 985365a..3f73e26 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -54,6 +54,11 @@ aiofiles = "^24.1.0" # section of the configuration file raise errors. addopts = "--strict-markers --strict-config --durations=5 -vv" asyncio_mode = "auto" +filterwarnings = [ + # Ignore testcontainers internal deprecation warnings (they haven't fixed their own code yet) + "ignore::DeprecationWarning:testcontainers.core.waiting_utils", + "ignore::DeprecationWarning:testcontainers.redis", +] [tool.poetry.scripts] format = "scripts:format" From b82a224dde232857e12ea83c24e351baf21eabc4 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 10:01:52 -0700 Subject: [PATCH 24/36] docs(notebook): update persistence-functional.ipynb to match source - Add missing 'Not needed for LangGraph API users' info box - Change 'LangGraph Cloud' to 'LangGraph Platform' terminology - Clear all outputs for clean execution - Verified against source notebook in langgraph docs Ready for end-to-end execution with Redis checkpoint implementation. --- examples/persistence-functional.ipynb | 82 ++++++--------------------- 1 file changed, 17 insertions(+), 65 deletions(-) diff --git a/examples/persistence-functional.ipynb b/examples/persistence-functional.ipynb index 6a57d2a..4a19c6e 100644 --- a/examples/persistence-functional.ipynb +++ b/examples/persistence-functional.ipynb @@ -16,6 +16,10 @@ " - [Memory](../../concepts/memory/)\n", " - [Chat Models](https://python.langchain.com/docs/concepts/chat_models/)\n", "\n", + "!!! info \"Not needed for LangGraph API users\"\n", + "\n", + " If you're using the LangGraph API, you needn't manually implement a checkpointer. The API automatically handles checkpointing for you. This guide is relevant when implementing LangGraph in your own custom server.\n", + "\n", "Many AI applications need memory to share context across multiple interactions on the same [thread](../../concepts/persistence#threads) (e.g., multiple turns of a conversation). In LangGraph functional API, this kind of memory can be added to any [entrypoint()][langgraph.func.entrypoint] workflow using [thread-level persistence](https://langchain-ai.github.io/langgraph/concepts/persistence).\n", "\n", "When creating a LangGraph workflow, you can set it up to persist its results by using a [checkpointer](https://langchain-ai.github.io/langgraph/reference/checkpoints/#basecheckpointsaver):\n", @@ -94,7 +98,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -113,18 +117,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -165,7 +161,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "892b54b9-75f0-4804-9ed0-88b5e5532989", "metadata": {}, "outputs": [], @@ -185,21 +181,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "87326ea6-34c5-46da-a41f-dda26ef9bd74", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:55:08 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "18:55:08 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:55:08 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:55:08 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import BaseMessage\n", "from langgraph.graph import add_messages\n", @@ -245,7 +230,7 @@ "source": [ "!!! note Note\n", "\n", - " If you're using LangGraph Cloud or LangGraph Studio, you __don't need__ to pass checkpointer to the entrypoint decorator, since it's done automatically." + " If you're using LangGraph Platform or LangGraph Studio, you __don't need__ to pass checkpointer to the entrypoint decorator, since it's done automatically." ] }, { @@ -258,21 +243,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "cfd140f0-a5a6-4697-8115-322242f197b5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:55:11 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hi Bob! I'm Claude. Nice to meet you. How can I help you today?\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"hi! I'm bob\"}\n", @@ -290,21 +264,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "08ae8246-11d5-40e1-8567-361e5bef8917", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:55:12 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Your name is Bob, based on what you just told me.\n" - ] - } - ], + "outputs": [], "source": [ "input_message = {\"role\": \"user\", \"content\": \"what's my name?\"}\n", "for chunk in workflow.stream([input_message], config, stream_mode=\"values\"):\n", @@ -321,21 +284,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "273d56a8-f40f-4a51-a27f-7c6bb2bda0ba", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:55:14 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "I don't know your name, as you haven't shared it with me. Each conversation with me starts fresh, so I don't have access to any previous conversations or personal information about you unless you specifically tell me.\n" - ] - } - ], + "outputs": [], "source": [ "input_message = {\"role\": \"user\", \"content\": \"what's my name?\"}\n", "for chunk in workflow.stream(\n", From 4b69ff434bc6ba20678e0f7d6a297b6393d2f880 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 10:03:49 -0700 Subject: [PATCH 25/36] docs(notebook): update cross-thread-persistence.ipynb - Change 'LangGraph Cloud' to 'LangGraph Platform' terminology - Clear all outputs for clean execution Ready for end-to-end execution with Redis store and checkpoint implementations. --- examples/cross-thread-persistence.ipynb | 118 ++++-------------------- 1 file changed, 16 insertions(+), 102 deletions(-) diff --git a/examples/cross-thread-persistence.ipynb b/examples/cross-thread-persistence.ipynb index 0273992..435e2ac 100644 --- a/examples/cross-thread-persistence.ipynb +++ b/examples/cross-thread-persistence.ipynb @@ -53,7 +53,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "3457aadf", "metadata": {}, "outputs": [], @@ -64,19 +64,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "aa2c64a7", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n", - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -109,20 +100,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "a7f303d6-612e-4e34-bf36-29d4ed25d802", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:53:37 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", - "18:53:37 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:53:37 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_openai import OpenAIEmbeddings\n", "from langgraph.store.redis import RedisStore\n", @@ -158,21 +139,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "2a30a362-528c-45ee-9df6-630d2d843588", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:53:37 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "18:53:37 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:53:37 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:53:37 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "import uuid\n", "\n", @@ -230,7 +200,7 @@ "
\n", "

Note

\n", "

\n", - " If you're using LangGraph Cloud or LangGraph Studio, you don't need to pass store when compiling the graph, since it's done automatically.\n", + " If you're using LangGraph Platform or LangGraph Studio, you don't need to pass store when compiling the graph, since it's done automatically.\n", "

\n", "
" ] @@ -253,26 +223,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "c871a073-a466-46ad-aafe-2b870831057e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "Hi! Remember: my name is Bob\n", - "18:53:38 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:53:39 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:53:40 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hello Bob! It's great to meet you. I'm glad you introduced yourself, and I'll certainly remember that your name is Bob. How can I assist you today?\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"Hi! Remember: my name is Bob\"}\n", @@ -282,25 +236,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "d862be40-1f8a-4057-81c4-b7bf073dc4c1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what is my name?\n", - "18:53:42 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:53:42 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Your name is Bob.\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", @@ -318,20 +257,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "76cde493-89cf-4709-a339-207d2b7e9ea7", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'data': 'User name is Bob'}\n", - "{'data': 'User name is Bob'}\n", - "{'data': 'User name is Bob'}\n" - ] - } - ], + "outputs": [], "source": [ "for memory in redis_store.search((\"memories\", \"1\")):\n", " print(memory.value)" @@ -347,25 +276,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "d362350b-d730-48bd-9652-983812fd7811", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what is my name?\n", - "18:53:43 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:53:44 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "I apologize, but I don't have any information about your name. As an AI language model, I don't have access to personal information about individual users unless it's provided in the conversation. If you'd like, you can tell me your name, and I'll be happy to use it in our conversation.\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"3\", \"user_id\": \"2\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", From 90b51ba28f7702b391c70c67a819b8ecddc83923 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 10:07:57 -0700 Subject: [PATCH 26/36] docs(notebook): update cross-thread-persistence-functional.ipynb - Change 'LangGraph Cloud' to 'LangGraph Platform' terminology - Clear all outputs for clean execution Ready for end-to-end execution with Redis store and checkpoint implementations. --- .../cross-thread-persistence-functional.ipynb | 108 +++--------------- 1 file changed, 16 insertions(+), 92 deletions(-) diff --git a/examples/cross-thread-persistence-functional.ipynb b/examples/cross-thread-persistence-functional.ipynb index c501fcb..fd9d087 100644 --- a/examples/cross-thread-persistence-functional.ipynb +++ b/examples/cross-thread-persistence-functional.ipynb @@ -59,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "3457aadf", "metadata": {}, "outputs": [], @@ -70,19 +70,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "aa2c64a7", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n", - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -123,20 +114,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "a7f303d6-612e-4e34-bf36-29d4ed25d802", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:52:26 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", - "18:52:26 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:52:26 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from langgraph.store.redis import RedisStore\n", "from langgraph.store.base import IndexConfig\n", @@ -172,21 +153,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "2a30a362-528c-45ee-9df6-630d2d843588", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:52:26 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "18:52:26 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:52:26 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:52:26 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "import uuid\n", "\n", @@ -249,7 +219,7 @@ "source": [ "!!! note Note\n", "\n", - " If you're using LangGraph Cloud or LangGraph Studio, you __don't need__ to pass store to the entrypoint decorator, since it's done automatically." + " If you're using LangGraph Platform or LangGraph Studio, you __don't need__ to pass store to the entrypoint decorator, since it's done automatically." ] }, { @@ -270,23 +240,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "c871a073-a466-46ad-aafe-2b870831057e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:52:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:52:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:52:29 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hi Bob! Yes, I remember that you're Bob. How can I help you today?\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"Hi! Remember: my name is Bob\"}\n", @@ -296,22 +253,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "d862be40-1f8a-4057-81c4-b7bf073dc4c1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:52:31 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:52:33 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Your name is Bob.\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", @@ -329,19 +274,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "76cde493-89cf-4709-a339-207d2b7e9ea7", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'data': 'User name is Bob'}\n", - "{'data': 'User name is Bob'}\n" - ] - } - ], + "outputs": [], "source": [ "for memory in redis_store.search((\"memories\", \"1\")):\n", " print(memory.value)" @@ -357,22 +293,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "d362350b-d730-48bd-9652-983812fd7811", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:52:42 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "18:52:43 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "I don't have any information about your name. While I can see some user info was meant to be provided, I don't actually have any specific details about you. Would you like to introduce yourself?\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"3\", \"user_id\": \"2\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", From 902a284ea5958362efd4b3852ea67ae02be29246 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 10:16:04 -0700 Subject: [PATCH 27/36] docs(notebook): update create-react-agent-manage-message-history.ipynb - Clear all outputs for clean execution - Ready for end-to-end execution with Redis checkpoint --- ...e-react-agent-manage-message-history.ipynb | 114 +++--------------- 1 file changed, 15 insertions(+), 99 deletions(-) diff --git a/examples/create-react-agent-manage-message-history.ipynb b/examples/create-react-agent-manage-message-history.ipynb index cbf21f3..43351ff 100644 --- a/examples/create-react-agent-manage-message-history.ipynb +++ b/examples/create-react-agent-manage-message-history.ipynb @@ -143,7 +143,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -154,18 +154,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -220,7 +212,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "eaad19ee-e174-4c6c-b2b8-3530d7acea40", "metadata": {}, "outputs": [], @@ -255,21 +247,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "b507eb58-6e02-4ac6-b48b-ea4defdc11f0", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:46:53 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "18:46:53 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:46:53 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:46:53 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from langgraph.prebuilt import create_react_agent\n", "from langgraph.checkpoint.redis import RedisSaver\n", @@ -318,21 +299,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "8182ab45-86b3-4d6f-b75e-58862a14fa4e", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from IPython.display import display, Image\n", "\n", @@ -349,7 +319,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], @@ -380,20 +350,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:46:56 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "18:46:58 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "18:47:07 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "\n", @@ -414,21 +374,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "41ba0253-5199-4d29-82ae-258cbbebddb4", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "421" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "messages = result[\"messages\"]\n", "count_tokens_approximately(messages)" @@ -448,40 +397,7 @@ "execution_count": null, "id": "26c53429-90ba-4d0b-abb9-423d9120ad26", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Update from node: pre_model_hook\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What's it known for?\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "New York City is known for a variety of iconic landmarks, cultural institutions, and vibrant neighborhoods. Some of the most notable features include:\n", - "\n", - "1. **Statue of Liberty**: A symbol of freedom and democracy, located on Liberty Island.\n", - "2. **Times Square**: Known for its bright lights, Broadway theaters, and bustling atmosphere.\n", - "3. **Central Park**: A large public park offering a natural oasis amidst the urban environment.\n", - "4. **Empire State Building**: An iconic skyscraper offering panoramic views of the city.\n", - "5. **Broadway**: Famous for its world-class theater productions.\n", - "6. **Wall Street**: The financial hub of the United States.\n", - "7. **Museums**: Including the Metropolitan Museum of Art, Museum of Modern Art (MoMA), and the American Museum of Natural History.\n", - "8. **Diverse Cuisine**: A melting pot of cultures reflected in its diverse food scene.\n", - "9. **Cultural Diversity**: A rich tapestry of cultures and ethnicities, contributing to its dynamic character.\n", - "10. **Fashion**: A global fashion capital, hosting events like New York Fashion Week.\n", - "\n", - "These are just a few highlights of what makes New York City a unique and exciting place.\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "where can i find the best bagel?\n", - "\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "inputs = {\"messages\": [(\"user\", \"where can i find the best bagel?\")]}\n", "print_stream(graph.stream(inputs, config=config, stream_mode=\"updates\"))" @@ -749,4 +665,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file From b267c85f22fbee11df46921f9eea4a881a3faec3 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 10:18:03 -0700 Subject: [PATCH 28/36] docs(notebook): update create-react-agent notebooks - Clear all outputs for clean execution on create-react-agent-memory.ipynb - Clear all outputs for clean execution on create-react-agent-hitl.ipynb - Ready for end-to-end execution with Redis checkpoint --- examples/create-react-agent-hitl.ipynb | 40 ++-------- examples/create-react-agent-memory.ipynb | 93 +++--------------------- 2 files changed, 17 insertions(+), 116 deletions(-) diff --git a/examples/create-react-agent-hitl.ipynb b/examples/create-react-agent-hitl.ipynb index 5e13d37..3f265fc 100644 --- a/examples/create-react-agent-hitl.ipynb +++ b/examples/create-react-agent-hitl.ipynb @@ -53,7 +53,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -64,18 +64,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -112,30 +104,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "7a154152-973e-4b5d-aa13-48c617744a4c", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.2.0\n", - "02:38:15 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "02:38:15 redisvl.index.index INFO Index already exists, not overwriting.\n", - "02:38:15 redisvl.index.index INFO Index already exists, not overwriting.\n", - "02:38:15 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_519/104821471.py:41: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", - " graph = create_react_agent(\n" - ] - } - ], + "outputs": [], "source": [ "# First we initialize the model we want to use.\n", "from langchain_openai import ChatOpenAI\n", @@ -192,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], diff --git a/examples/create-react-agent-memory.ipynb b/examples/create-react-agent-memory.ipynb index c4de6fb..0f15e50 100644 --- a/examples/create-react-agent-memory.ipynb +++ b/examples/create-react-agent-memory.ipynb @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -69,18 +69,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -117,21 +109,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "7a154152-973e-4b5d-aa13-48c617744a4c", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "18:47:40 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "18:47:40 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:47:40 redisvl.index.index INFO Index already exists, not overwriting.\n", - "18:47:40 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "# First we initialize the model we want to use.\n", "from langchain_openai import ChatOpenAI\n", @@ -186,7 +167,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], @@ -202,35 +183,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What's the weather in NYC?\n", - "18:47:41 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " get_weather (call_dszyH4rhcp3TcSjwI4iHLv4O)\n", - " Call ID: call_dszyH4rhcp3TcSjwI4iHLv4O\n", - " Args:\n", - " location: New York City, NY\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: get_weather\n", - "\n", - "It might be cloudy in nyc\n", - "18:47:43 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "The weather in New York City might be cloudy. If you need more detailed information, feel free to ask!\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "inputs = {\"messages\": [(\"user\", \"What's the weather in NYC?\")]}\n", @@ -248,37 +204,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "187479f9-32fa-4611-9487-cf816ba2e147", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What's it known for?\n", - "18:47:49 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "New York City is known for a wide array of iconic features and cultural landmarks, including:\n", - "\n", - "1. **Statue of Liberty**: A symbol of freedom and democracy, located on Liberty Island.\n", - "2. **Times Square**: Known for its bright lights, Broadway theaters, and bustling atmosphere.\n", - "3. **Central Park**: A massive urban park offering a natural escape in the heart of the city.\n", - "4. **Empire State Building**: An iconic skyscraper with observatories offering stunning city views.\n", - "5. **Broadway**: Famous for its world-class theater productions and musicals.\n", - "6. **Wall Street**: The financial hub of the U.S., home to the New York Stock Exchange.\n", - "7. **Cultural Diversity**: A melting pot of cultures, languages, and cuisines.\n", - "8. **Museums**: Including the Metropolitan Museum of Art, Museum of Modern Art (MoMA), and the American Museum of Natural History.\n", - "9. **Cuisine**: Known for diverse food offerings, including New York-style pizza and bagels.\n", - "10. **Fashion**: A global fashion capital, hosting events like New York Fashion Week.\n", - "\n", - "These are just a few highlights, as NYC is a city with endless attractions and a vibrant cultural scene.\n" - ] - } - ], + "outputs": [], "source": [ "inputs = {\"messages\": [(\"user\", \"What's it known for?\")]}\n", "print_stream(graph.stream(inputs, config=config, stream_mode=\"values\"))" @@ -314,4 +243,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file From 12d68efe70887bc5d1ff5e67e3add2a053cfd160 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 10:19:46 -0700 Subject: [PATCH 29/36] docs(notebook): update subgraph notebooks - Clear all outputs for clean execution on subgraph-persistence.ipynb - Clear all outputs for clean execution on subgraphs-manage-state.ipynb - Ready for end-to-end execution with Redis checkpoint --- examples/subgraph-persistence.ipynb | 94 +----- examples/subgraphs-manage-state.ipynb | 430 ++++---------------------- 2 files changed, 70 insertions(+), 454 deletions(-) diff --git a/examples/subgraph-persistence.ipynb b/examples/subgraph-persistence.ipynb index a1ea5d5..3886926 100644 --- a/examples/subgraph-persistence.ipynb +++ b/examples/subgraph-persistence.ipynb @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "77d1eafa-3252-45f6-9af0-d94e1f9c5c9e", "metadata": {}, "outputs": [], @@ -105,21 +105,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "0d76f0c0-bd77-4eca-9527-27bcdf85dd42", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from typing import TypedDict\n", "\n", @@ -179,18 +168,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "7657d285-c896-40c9-a569-b4a3b9c230c7", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:48:39 langgraph.checkpoint.redis INFO Redis client is a standalone client\n" - ] - } - ], + "outputs": [], "source": [ "from langgraph.checkpoint.redis import RedisSaver\n", "\n", @@ -224,7 +205,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "13da686e-6ed6-4b83-93e8-1631fcc8c2a9", "metadata": {}, "outputs": [], @@ -234,21 +215,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "8721f045-2e82-4bf0-9d85-5ba6ecf899d6", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'node_1': {'foo': 'hi! foo'}}\n", - "{'subgraph_node_1': {'bar': 'bar'}}\n", - "{'subgraph_node_2': {'foo': 'hi! foobar'}}\n", - "{'node_2': {'foo': 'hi! foobar'}}\n" - ] - } - ], + "outputs": [], "source": [ "for _, chunk in graph.stream({\"foo\": \"foo\"}, config, subgraphs=True):\n", " print(chunk)" @@ -264,21 +234,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "3e817283-142d-4fda-8cb1-8de34717f833", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'foo': 'hi! foobar'}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "graph.get_state(config).values" ] @@ -298,7 +257,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "e896628f-36b2-45eb-b7c5-c64c1098f328", "metadata": {}, "outputs": [], @@ -318,22 +277,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "21e96df3-946d-40f8-8d6d-055ae4177452", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'configurable': {'thread_id': '1',\n", - " 'checkpoint_ns': 'node_2:a17a6508-101f-059f-10ae-100a6b79cc4c'}}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "subgraph_config = state_with_subgraph.tasks[0].state\n", "subgraph_config" @@ -341,21 +288,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "1d2401b3-d52b-4895-a5d1-dccf015ba216", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'foo': 'hi! foobar', 'bar': 'bar'}" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "graph.get_state(subgraph_config).values" ] diff --git a/examples/subgraphs-manage-state.ipynb b/examples/subgraphs-manage-state.ipynb index f6790f2..a28d11b 100644 --- a/examples/subgraphs-manage-state.ipynb +++ b/examples/subgraphs-manage-state.ipynb @@ -51,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -68,17 +68,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -116,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -169,20 +161,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:17 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:49:17 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:49:17 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:49:17 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from typing import Literal\n", "from typing_extensions import TypedDict\n", @@ -241,20 +222,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from IPython.display import Image, display\n", "\n", @@ -271,20 +241,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:19 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'router_node': {'route': 'other'}}\n", - "19:49:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'normal_llm_node': {'messages': [AIMessage(content='Hello! How can I assist you today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 9, 'prompt_tokens': 9, 'total_tokens': 18, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_ff25b2783a', 'id': 'chatcmpl-C1eQSpmVa2WR20bVGksAXd8sb4RgG', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='run--24da8d0f-1db0-40da-987f-59ba7b544ce2-0', usage_metadata={'input_tokens': 9, 'output_tokens': 9, 'total_tokens': 18, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"hi!\"}]}\n", @@ -305,20 +264,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:22 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'router_node': {'route': 'weather'}}\n", - "19:49:24 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'__interrupt__': ()}\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -335,22 +283,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')]})\n", - "19:49:25 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')], 'route': 'weather'})\n", - "(('weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')]})\n", - "19:49:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "(('weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')], 'city': 'San Francisco'})\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"3\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -367,20 +302,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "('weather_graph',)" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "state = graph.get_state(config)\n", "state.next" @@ -395,20 +319,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(PregelTask(id='60555af0-33b1-dc09-4888-d57c08dc4db8', name='weather_graph', path=('__pregel_pull', 'weather_graph'), error=None, interrupts=(), state={'configurable': {'thread_id': '3', 'checkpoint_ns': 'weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8'}}, result=None),)" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "state.tasks" ] @@ -422,20 +335,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "PregelTask(id='60555af0-33b1-dc09-4888-d57c08dc4db8', name='weather_graph', path=('__pregel_pull', 'weather_graph'), error=None, interrupts=(), state=StateSnapshot(values={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')], 'city': 'San Francisco'}, next=('weather_node',), config={'configurable': {'thread_id': '3', 'checkpoint_ns': 'weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8', 'checkpoint_id': '1f072fe7-5fef-6d82-8001-128712d34fc6', 'checkpoint_map': {'': '1f072fe7-4dba-681c-8001-e1d2ab5eccf6', 'weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8': '1f072fe7-5fef-6d82-8001-128712d34fc6'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f072fe7-4dba-681c-8001-e1d2ab5eccf6'}}, created_at='2025-08-06T19:49:27.539023+00:00', parent_config={'configurable': {'thread_id': '3', 'checkpoint_ns': 'weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8', 'checkpoint_id': '1f072fe7-4dc0-6b54-8000-d7d6ffbeefa5', 'checkpoint_map': {'': '1f072fe7-4dba-681c-8001-e1d2ab5eccf6', 'weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8': '1f072fe7-4dc0-6b54-8000-d7d6ffbeefa5'}}}, tasks=(PregelTask(id='da7c4aa5-a62e-a941-1aad-f88a9cbf49e3', name='weather_node', path=('__pregel_pull', 'weather_node'), error=None, interrupts=(), state=None, result=None),), interrupts=()), result=None)" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "state = graph.get_state(config, subgraphs=True)\n", "state.tasks[0]" @@ -452,20 +354,9 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')], 'route': 'weather'})\n", - "(('weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')], 'city': 'San Francisco'})\n", - "(('weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485'), AIMessage(content=\"It's sunny in San Francisco!\", additional_kwargs={}, response_metadata={}, id='fa13351e-f130-47d0-ae4d-6174dcdbffb8')], 'city': 'San Francisco'})\n", - "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485'), AIMessage(content=\"It's sunny in San Francisco!\", additional_kwargs={}, response_metadata={}, id='fa13351e-f130-47d0-ae4d-6174dcdbffb8')], 'route': 'weather'})\n" - ] - } - ], + "outputs": [], "source": [ "for update in graph.stream(None, config=config, stream_mode=\"values\", subgraphs=True):\n", " print(update)" @@ -486,7 +377,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -497,7 +388,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -520,20 +411,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "('model_node',)" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "subgraph_state_before_model_node.next" ] @@ -547,20 +427,9 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')], 'route': 'weather'})\n", - "(('weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')]})\n", - "19:49:30 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "(('weather_graph:60555af0-33b1-dc09-4888-d57c08dc4db8',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='e8ca97fe-6457-4e19-b9dc-5253d686b485')], 'city': 'San Francisco'})\n" - ] - } - ], + "outputs": [], "source": [ "for value in graph.stream(\n", " None,\n", @@ -591,20 +460,9 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:31 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'router_node': {'route': 'weather'}}\n", - "19:49:31 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'__interrupt__': ()}\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"4\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -614,20 +472,9 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='fab08064-f16c-42bb-92c8-4d1ec3e03a0c')]" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "state = graph.get_state(config, subgraphs=True)\n", "state.values[\"messages\"]" @@ -642,24 +489,9 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'configurable': {'thread_id': '4',\n", - " 'checkpoint_ns': 'weather_graph:97c4037c-04a4-88f0-5f77-b5d0a58d573e',\n", - " 'checkpoint_id': '1f072fe7-86ff-6d31-8002-d83218057702',\n", - " 'checkpoint_map': {'': '1f072fe7-8217-6934-8001-43fd0d293d39',\n", - " 'weather_graph:97c4037c-04a4-88f0-5f77-b5d0a58d573e': '1f072fe7-86ff-6d31-8002-d83218057702'}}}" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "graph.update_state(state.tasks[0].state.config, {\"city\": \"la\"})" ] @@ -673,18 +505,9 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(('weather_graph:97c4037c-04a4-88f0-5f77-b5d0a58d573e',), {'weather_node': {'messages': [{'role': 'assistant', 'content': \"It's sunny in la!\"}]}})\n", - "((), {'weather_graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='fab08064-f16c-42bb-92c8-4d1ec3e03a0c'), AIMessage(content=\"It's sunny in la!\", additional_kwargs={}, response_metadata={}, id='85d1dba9-1872-4b48-ae35-dbceb7d5de08')]}})\n" - ] - } - ], + "outputs": [], "source": [ "for update in graph.stream(None, config=config, stream_mode=\"updates\", subgraphs=True):\n", " print(update)" @@ -703,24 +526,9 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:32 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "((), {'router_node': {'route': 'weather'}})\n", - "19:49:32 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "(('weather_graph:0f03bc0d-600b-8bcc-7aae-28e3848d8986',), {'model_node': {'city': 'San Francisco'}})\n", - "((), {'__interrupt__': ()})\n", - "interrupted!\n", - "((), {'weather_graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='0424d92e-33fa-4c0b-9d9a-426e9509e642'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='f507bd08-4145-4dff-a9dc-f7613737d1df')]}})\n", - "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='0424d92e-33fa-4c0b-9d9a-426e9509e642'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='f507bd08-4145-4dff-a9dc-f7613737d1df')]\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"14\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -758,23 +566,9 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:33 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "((), {'router_node': {'route': 'weather'}})\n", - "19:49:34 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "(('weather_graph:f8e64c8e-648f-6c34-a1f8-887d1d0e4a6d',), {'model_node': {'city': 'San Francisco'}})\n", - "((), {'__interrupt__': ()})\n", - "interrupted!\n", - "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1693421f-9586-478f-8919-0a6fee31cc13'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='f9c5b93e-ce41-49be-af80-2a29871d4f7e')]\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"8\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -811,20 +605,9 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:34 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:49:34 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:49:34 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:49:34 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from typing import Literal\n", "from typing_extensions import TypedDict\n", @@ -883,20 +666,9 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:49:34 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:49:34 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:49:34 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:49:34 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from langgraph.checkpoint.redis import RedisSaver\n", "\n", @@ -937,20 +709,9 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from IPython.display import Image, display\n", "\n", @@ -967,22 +728,9 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "((), {'router_node': {'to_continue': True}})\n", - "19:49:35 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "(('graph:c7c00782-3665-a049-2228-d98da6b23d48',), {'router_node': {'route': 'weather'}})\n", - "19:49:36 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "(('graph:c7c00782-3665-a049-2228-d98da6b23d48', 'weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93'), {'model_node': {'city': 'San Francisco'}})\n", - "((), {'__interrupt__': ()})\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -994,24 +742,9 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Grandparent State:\n", - "{'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024')], 'to_continue': True}\n", - "---------------\n", - "Parent Graph State:\n", - "{'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024')], 'route': 'weather'}\n", - "---------------\n", - "Subgraph State:\n", - "{'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024')], 'city': 'San Francisco'}\n" - ] - } - ], + "outputs": [], "source": [ "state = grandparent_graph.get_state(config, subgraphs=True)\n", "print(\"Grandparent State:\")\n", @@ -1033,19 +766,9 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(('graph:c7c00782-3665-a049-2228-d98da6b23d48',), {'weather_graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='9773b21f-7e75-4e67-91a8-5ab80fa37ee7')]}})\n", - "((), {'graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='9773b21f-7e75-4e67-91a8-5ab80fa37ee7')]}})\n", - "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='9773b21f-7e75-4e67-91a8-5ab80fa37ee7')]\n" - ] - } - ], + "outputs": [], "source": [ "grandparent_graph_state = state\n", "parent_graph_state = grandparent_graph_state.tasks[0].state\n", @@ -1074,52 +797,9 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-2625-6cb4-bfff-0577231ac0ec'}}, metadata={'source': 'input', 'step': -1, 'parents': {}}, created_at='2025-08-06T19:49:21.479383+00:00', parent_config=None, tasks=(PregelTask(id='7d06c21b-984b-2fc1-f4f5-7bcc52efbbd7', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [{'role': 'user', 'content': \"what's the weather in sf\"}]}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}]}, next=('router_node',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-262e-66ce-8000-aa07c2d13b6a'}}, metadata={'source': 'loop', 'step': 0, 'parents': {}}, created_at='2025-08-06T19:49:21.482906+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-2625-6cb4-bfff-0577231ac0ec'}}, tasks=(PregelTask(id='aaa44ca4-9044-10fc-b337-87526cda849d', name='router_node', path=('__pregel_pull', 'router_node'), error=None, interrupts=(), state=None, result={}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-2d45-6246-8001-98a17f4d33ab'}}, metadata={'source': 'loop', 'step': 1, 'parents': {}}, created_at='2025-08-06T19:49:22.226227+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-262e-66ce-8000-aa07c2d13b6a'}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150', 'checkpoint_id': '1f072fe7-2d49-6e48-bfff-84a69c927b9e', 'checkpoint_map': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab', 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150': '1f072fe7-2d49-6e48-bfff-84a69c927b9e'}}}, metadata={'source': 'input', 'step': -1, 'parents': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab'}}, created_at='2025-08-06T19:49:22.228176+00:00', parent_config=None, tasks=(PregelTask(id='7c096b4f-baa3-5993-f80e-4b94a9c1b50e', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4')]}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150', 'checkpoint_id': '1f072fe7-2d4c-63dd-8000-35de079e3213', 'checkpoint_map': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab', 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150': '1f072fe7-2d4c-63dd-8000-35de079e3213'}}}, metadata={'source': 'loop', 'step': 0, 'parents': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab'}}, created_at='2025-08-06T19:49:22.229136+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150', 'checkpoint_id': '1f072fe7-2d49-6e48-bfff-84a69c927b9e', 'checkpoint_map': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab', 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150': '1f072fe7-2d49-6e48-bfff-84a69c927b9e'}}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150', 'checkpoint_id': '1f072fe7-46b2-6d74-8001-274ee769e640', 'checkpoint_map': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab', 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150': '1f072fe7-46b2-6d74-8001-274ee769e640'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab'}}, created_at='2025-08-06T19:49:24.892599+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150', 'checkpoint_id': '1f072fe7-2d4c-63dd-8000-35de079e3213', 'checkpoint_map': {'': '1f072fe7-2d45-6246-8001-98a17f4d33ab', 'weather_graph:39f41d26-c005-4401-f6f7-6bd3b7868150': '1f072fe7-2d4c-63dd-8000-35de079e3213'}}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}]}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-a5ab-604a-8002-bf1ff5658bc0'}}, metadata={'source': 'input', 'step': 2, 'parents': {}}, created_at='2025-08-06T19:49:34.850869+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-2d45-6246-8001-98a17f4d33ab'}}, tasks=(PregelTask(id='114268c9-db18-46e1-da86-75c3db8904d0', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [{'role': 'user', 'content': \"what's the weather in sf\"}]}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}]}, next=('router_node',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-a5ad-68f4-8003-6c6fc3090288'}}, metadata={'source': 'loop', 'step': 3, 'parents': {}}, created_at='2025-08-06T19:49:34.851907+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-a5ab-604a-8002-bf1ff5658bc0'}}, tasks=(PregelTask(id='3b74181a-192f-d700-9db9-95a3d7aac383', name='router_node', path=('__pregel_pull', 'router_node'), error=None, interrupts=(), state=None, result={'to_continue': True}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48', 'checkpoint_id': '1f072fe7-a5b4-6349-bfff-8d1f3e67a3af', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-a5b4-6349-bfff-8d1f3e67a3af'}}}, metadata={'source': 'input', 'step': -1, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5'}}, created_at='2025-08-06T19:49:34.854635+00:00', parent_config=None, tasks=(PregelTask(id='7299899d-197c-8ca4-fa8b-bfe52c56664f', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024')]}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}]}, next=('router_node',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48', 'checkpoint_id': '1f072fe7-a5b6-653c-8000-24b05222bc56', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-a5b6-653c-8000-24b05222bc56'}}}, metadata={'source': 'loop', 'step': 0, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5'}}, created_at='2025-08-06T19:49:34.855502+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48', 'checkpoint_id': '1f072fe7-a5b4-6349-bfff-8d1f3e67a3af', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-a5b4-6349-bfff-8d1f3e67a3af'}}}, tasks=(PregelTask(id='c6e0cae4-d8c6-b14d-1362-cbe293753fa7', name='router_node', path=('__pregel_pull', 'router_node'), error=None, interrupts=(), state=None, result={}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93', 'checkpoint_id': '1f072fe7-aa68-6503-bfff-a4d8342b08aa', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93': '1f072fe7-aa68-6503-bfff-a4d8342b08aa'}}}, metadata={'source': 'input', 'step': -1, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7'}}, created_at='2025-08-06T19:49:35.347837+00:00', parent_config=None, tasks=(PregelTask(id='242fe40c-4451-c4b2-7391-d884b8af3ecb', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result=None),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93', 'checkpoint_id': '1f072fe7-aa6b-6918-8000-c04fc9c43ab2', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93': '1f072fe7-aa6b-6918-8000-c04fc9c43ab2'}}}, metadata={'source': 'loop', 'step': 0, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7'}}, created_at='2025-08-06T19:49:35.349169+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93', 'checkpoint_id': '1f072fe7-aa68-6503-bfff-a4d8342b08aa', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93': '1f072fe7-aa68-6503-bfff-a4d8342b08aa'}}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93', 'checkpoint_id': '1f072fe7-b15b-65ac-8001-eb9037055f0a', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93': '1f072fe7-b15b-65ac-8001-eb9037055f0a'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7'}}, created_at='2025-08-06T19:49:36.076527+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93', 'checkpoint_id': '1f072fe7-aa6b-6918-8000-c04fc9c43ab2', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93': '1f072fe7-aa6b-6918-8000-c04fc9c43ab2'}}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'rainy', 'type': 'ai', 'id': '9773b21f-7e75-4e67-91a8-5ab80fa37ee7', 'tool_calls': [], 'invalid_tool_calls': []}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93', 'checkpoint_id': '1f072fe7-b176-65cc-8002-99de1c8214e6', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93': '1f072fe7-b176-65cc-8002-99de1c8214e6'}}}, metadata={'source': 'update', 'step': 2, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7'}}, created_at='2025-08-06T19:49:36.087591+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93', 'checkpoint_id': '1f072fe7-b15b-65ac-8001-eb9037055f0a', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'graph:c7c00782-3665-a049-2228-d98da6b23d48|weather_graph:0e5f154a-2df4-e57d-2dc8-5446514d1f93': '1f072fe7-b15b-65ac-8001-eb9037055f0a'}}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48', 'checkpoint_id': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5'}}, created_at='2025-08-06T19:49:35.346773+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48', 'checkpoint_id': '1f072fe7-a5b6-653c-8000-24b05222bc56', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-a5b6-653c-8000-24b05222bc56'}}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'rainy', 'type': 'ai', 'id': '9773b21f-7e75-4e67-91a8-5ab80fa37ee7', 'tool_calls': [], 'invalid_tool_calls': []}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48', 'checkpoint_id': '1f072fe7-b182-6295-8002-e699a61cebcd', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-b182-6295-8002-e699a61cebcd'}}}, metadata={'source': 'loop', 'step': 2, 'parents': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5'}}, created_at='2025-08-06T19:49:36.092422+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48', 'checkpoint_id': '1f072fe7-aa65-6ba2-8001-1d681f52eda7', 'checkpoint_map': {'': '1f072fe7-a5b1-692c-8004-bd30259081c5', 'graph:c7c00782-3665-a049-2228-d98da6b23d48': '1f072fe7-aa65-6ba2-8001-1d681f52eda7'}}}, tasks=(), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}], 'to_continue': True}, next=('graph',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-a5b1-692c-8004-bd30259081c5'}}, metadata={'source': 'loop', 'step': 4, 'parents': {}}, created_at='2025-08-06T19:49:34.853553+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-a5ad-68f4-8003-6c6fc3090288'}}, tasks=(PregelTask(id='c7c00782-3665-a049-2228-d98da6b23d48', name='graph', path=('__pregel_pull', 'graph'), error=None, interrupts=(), state={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:c7c00782-3665-a049-2228-d98da6b23d48'}}, result={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='9773b21f-7e75-4e67-91a8-5ab80fa37ee7')]}),), interrupts=())\n", - "-----\n", - "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'd7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '28ef5b05-b571-4454-9753-10d194e52024'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'rainy', 'type': 'ai', 'id': '9773b21f-7e75-4e67-91a8-5ab80fa37ee7', 'tool_calls': [], 'invalid_tool_calls': []}}], 'to_continue': True}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-b186-6eac-8005-7ac703cf3254'}}, metadata={'source': 'loop', 'step': 5, 'parents': {}}, created_at='2025-08-06T19:49:36.094373+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f072fe7-a5b1-692c-8004-bd30259081c5'}}, tasks=(), interrupts=())\n", - "-----\n" - ] - } - ], + "outputs": [], "source": [ "for state in grandparent_graph.get_state_history(config):\n", " print(state)\n", @@ -1148,4 +828,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file From 8a382db390c178e04ebdea59f378edd81ba0391e Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 10:21:12 -0700 Subject: [PATCH 30/36] docs(notebook): update human_in_the_loop and memory notebooks - Clear all outputs for clean execution on all 11 notebooks - 7 human_in_the_loop notebooks: breakpoints, dynamic_breakpoints, edit-graph-state, review-tool-calls-openai, review-tool-calls, time-travel, wait-user-input - 4 memory notebooks: add-summary-conversation-history, delete-messages, manage-conversation-history, semantic-search - Ready for end-to-end execution with Redis checkpoint --- examples/human_in_the_loop/breakpoints.ipynb | 140 +--------- .../dynamic_breakpoints.ipynb | 201 ++----------- .../human_in_the_loop/edit-graph-state.ipynb | 187 ++----------- .../review-tool-calls-openai.ipynb | 255 ++--------------- .../human_in_the_loop/review-tool-calls.ipynb | 255 ++--------------- examples/human_in_the_loop/time-travel.ipynb | 263 +++--------------- .../human_in_the_loop/wait-user-input.ipynb | 196 ++----------- .../add-summary-conversation-history.ipynb | 251 ++--------------- examples/memory/delete-messages.ipynb | 165 ++--------- .../memory/manage-conversation-history.ipynb | 96 +------ examples/memory/semantic-search.ipynb | 195 ++----------- 11 files changed, 246 insertions(+), 1958 deletions(-) diff --git a/examples/human_in_the_loop/breakpoints.ipynb b/examples/human_in_the_loop/breakpoints.ipynb index cd8636d..b8f91a9 100644 --- a/examples/human_in_the_loop/breakpoints.ipynb +++ b/examples/human_in_the_loop/breakpoints.ipynb @@ -39,7 +39,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, "outputs": [], @@ -106,31 +106,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "9b53f191-1e86-4881-a667-d46a3d66958b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "20:38:59 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "20:38:59 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:38:59 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:38:59 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from typing_extensions import TypedDict\n", "from langgraph.graph import StateGraph, START, END\n", @@ -194,48 +173,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "dfe04a7f-988e-4a36-8ce8-2c49fab0130a", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello world'}\n", - "---Step 1---\n", - "---Step 2---\n" - ] - }, - { - "name": "stdin", - "output_type": "stream", - "text": [ - "Do you want to go to Step 3? (yes/no): yes\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello world'}\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Do you want to go to Step 3? (yes/no): yes\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---Step 3---\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"input\": \"hello world\"}\n", @@ -276,31 +217,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "6098e5cb", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "20:39:05 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "20:39:05 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:39:05 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:39:05 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Set up the tool\n", "from langchain_anthropic import ChatAnthropic\n", @@ -421,29 +341,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "cfd140f0-a5a6-4697-8115-322242f197b5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "search for the weather in sf now\n", - "20:39:07 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "[{'text': \"Certainly! I'll use the search function to look up the current weather in San Francisco for you. Let me do that now.\", 'type': 'text'}, {'id': 'toolu_013wUCUCqaBFjxKAWqzhNESq', 'input': {'query': 'current weather in San Francisco'}, 'name': 'search', 'type': 'tool_use'}]\n", - "Tool Calls:\n", - " search (toolu_013wUCUCqaBFjxKAWqzhNESq)\n", - " Call ID: toolu_013wUCUCqaBFjxKAWqzhNESq\n", - " Args:\n", - " query: current weather in San Francisco\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -469,25 +370,10 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "51923913-20f7-4ee1-b9ba-d01f5fb2869b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "[{'text': \"Certainly! I'll use the search function to look up the current weather in San Francisco for you. Let me do that now.\", 'type': 'text'}, {'id': 'toolu_013wUCUCqaBFjxKAWqzhNESq', 'input': {'query': 'current weather in San Francisco'}, 'name': 'search', 'type': 'tool_use'}]\n", - "Tool Calls:\n", - " search (toolu_013wUCUCqaBFjxKAWqzhNESq)\n", - " Call ID: toolu_013wUCUCqaBFjxKAWqzhNESq\n", - " Args:\n", - " query: current weather in San Francisco\n" - ] - } - ], + "outputs": [], "source": [ "for event in app.stream(None, thread, stream_mode=\"values\"):\n", " event[\"messages\"][-1].pretty_print()" @@ -515,4 +401,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/human_in_the_loop/dynamic_breakpoints.ipynb b/examples/human_in_the_loop/dynamic_breakpoints.ipynb index 0bc791b..7090631 100644 --- a/examples/human_in_the_loop/dynamic_breakpoints.ipynb +++ b/examples/human_in_the_loop/dynamic_breakpoints.ipynb @@ -26,7 +26,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "2013d058-c245-498e-ba05-5af99b9b8a1b", "metadata": {}, "outputs": [], @@ -58,31 +58,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "9a14c8b2-5c25-4201-93ea-e5358ee99bcb", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "20:38:35 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "20:38:35 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:38:35 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:38:35 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from IPython.display import Image, display\n", "from langgraph.types import interrupt, Command\n", @@ -168,24 +147,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "b2d281f1-3349-4378-8918-7665fa7a7457", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello'}\n", - "---Step 1---\n", - "{'input': 'hello'}\n", - "---Step 2---\n", - "{'input': 'hello'}\n", - "---Step 3---\n", - "{'input': 'hello'}\n" - ] - } - ], + "outputs": [], "source": [ "initial_input = {\"input\": \"hello\"}\n", "thread_config = {\"configurable\": {\"thread_id\": \"1\"}}\n", @@ -204,19 +169,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "4eac1455-e7ef-4a32-8c14-0d5789409689", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "()\n", - "()\n" - ] - } - ], + "outputs": [], "source": [ "state = graph.get_state(thread_config)\n", "print(state.next)\n", @@ -234,20 +190,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "c06192ad-13a4-4d2e-8e30-f1c08578fe77", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello world'}\n", - "---Step 1---\n", - "{'input': 'hello world'}\n" - ] - } - ], + "outputs": [], "source": [ "initial_input = {\"input\": \"hello world\"}\n", "thread_config = {\"configurable\": {\"thread_id\": \"2\"}}\n", @@ -267,19 +213,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "2058593c-178e-4a23-a4c4-860d4a9c2198", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Next node: ('step_2',)\n", - "Tasks: (PregelTask(id='715fdd24-c3bb-ba79-2892-414b70f14f36', name='step_2', path=('__pregel_pull', 'step_2'), error=None, interrupts=(), state=None, result=None),)\n" - ] - } - ], + "outputs": [], "source": [ "state = graph.get_state(thread_config)\n", "print(\"Next node:\", state.next)\n", @@ -303,21 +240,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "872e7a69-9784-4f81-90c6-6b6af2fa6480", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello world'}\n", - "{'input': 'short'}\n", - "---Step 3---\n", - "{'input': 'short'}\n" - ] - } - ], + "outputs": [], "source": [ "# Let's try resuming with a shorter input value using the Command object\n", "# This will provide a value to the interrupt, which our step_2 function can use\n", @@ -327,19 +253,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "3275f899-7039-4029-8814-0bb5c33fabfe", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Next node: ()\n", - "Final state: {'input': 'short'}\n" - ] - } - ], + "outputs": [], "source": [ "state = graph.get_state(thread_config)\n", "print(\"Next node:\", state.next)\n", @@ -372,33 +289,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "2ba8dc8d-b90e-45f5-92cd-2192fc66f270", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello world'}\n", - "---Step 1---\n", - "{'input': 'hello world'}\n", - "\n", - "--- Interrupted due to long input ---\n", - "\n", - "State updated with shorter input\n", - "\n", - "{'input': 'foo'}\n", - "---Step 2---\n", - "{'input': 'foo'}\n", - "---Step 3---\n", - "{'input': 'foo'}\n", - "\n", - "Final state: {'input': 'foo'}\n", - "Next nodes: ()\n" - ] - } - ], + "outputs": [], "source": [ "# Start fresh with a new thread\n", "initial_input = {\"input\": \"hello world\"}\n", @@ -433,22 +327,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "9a48e564-d979-4ac2-b815-c667345a9f07", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello world'}\n", - "---Step 1---\n", - "{'input': 'hello world'}\n", - "\n", - "--- Interrupted due to long input ---\n" - ] - } - ], + "outputs": [], "source": [ "initial_input = {\"input\": \"hello world\"}\n", "thread_config = {\"configurable\": {\"thread_id\": \"4\"}}\n", @@ -462,25 +344,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "17f973ab-00ce-4f16-a452-641e76625fde", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Skipped step_2 by updating state as that node\n", - "\n", - "{'input': 'hello world'}\n", - "---Step 3---\n", - "{'input': 'hello world'}\n", - "\n", - "Final state: {'input': 'hello world'}\n", - "Next nodes: ()\n" - ] - } - ], + "outputs": [], "source": [ "# Update the state as node `step_2` to skip it altogether\n", "graph.update_state(config=thread_config, values=None, as_node=\"step_2\")\n", @@ -507,30 +374,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "yh6l8suqqu", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Running with long input...\n", - "{'input': 'hello world'}\n", - "---Step 1---\n", - "{'input': 'hello world'}\n", - "\n", - "--- Resuming with shorter input via Command ---\n", - "{'input': 'hello world'}\n", - "{'input': 'hi'}\n", - "---Step 3---\n", - "{'input': 'hi'}\n", - "\n", - "Final state: {'input': 'hi'}\n", - "Completed: True\n" - ] - } - ], + "outputs": [], "source": [ "initial_input = {\"input\": \"hello world\"}\n", "thread_config = {\"configurable\": {\"thread_id\": \"5\"}}\n", @@ -602,4 +449,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/human_in_the_loop/edit-graph-state.ipynb b/examples/human_in_the_loop/edit-graph-state.ipynb index be4722a..71121de 100644 --- a/examples/human_in_the_loop/edit-graph-state.ipynb +++ b/examples/human_in_the_loop/edit-graph-state.ipynb @@ -40,7 +40,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -59,18 +59,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -117,31 +109,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "85e452f8-f33a-4ead-bb4d-7386cdba8edc", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:01:50 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "21:01:50 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:01:50 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:01:50 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import uuid\n", "from typing_extensions import TypedDict\n", @@ -194,19 +165,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "1b3aa6fc-c7fb-4819-8d7f-ba6057cc4edf", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello world'}\n", - "---Step 1---\n" - ] - } - ], + "outputs": [], "source": [ "import uuid\n", "\n", @@ -231,23 +193,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "49d61230-e5dc-4272-b8ab-09b0af30f088", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Current state!\n", - "{'input': 'hello world'}\n", - "---\n", - "---\n", - "Updated state!\n", - "{'input': 'hello universe!'}\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Current state!\")\n", "print(graph.get_state(thread).values)\n", @@ -260,22 +209,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "cf77f6eb-4cc0-4615-a095-eb5ae7027b7a", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'input': 'hello universe!'}\n", - "---Step 2---\n", - "---Step 3---\n", - "---Step 2---\n", - "---Step 3---\n" - ] - } - ], + "outputs": [], "source": [ "# Continue the graph execution from the interruption point\n", "for event in graph.stream(None, thread, stream_mode=\"values\"):\n", @@ -300,21 +237,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "6098e5cb", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:01:50 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "21:01:50 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:01:50 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:01:50 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "# Set up the tool\n", "from langchain_anthropic import ChatAnthropic\n", @@ -435,29 +361,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "cfd140f0-a5a6-4697-8115-322242f197b5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "search for the weather in sf now\n", - "21:01:52 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "[{'text': \"Certainly! I'll search for the current weather in San Francisco for you. Let me use the search function to find this information.\", 'type': 'text'}, {'id': 'toolu_014fxXBNt7hmzjbysvZTeZu3', 'input': {'query': 'current weather in San Francisco'}, 'name': 'search', 'type': 'tool_use'}]\n", - "Tool Calls:\n", - " search (toolu_014fxXBNt7hmzjbysvZTeZu3)\n", - " Call ID: toolu_014fxXBNt7hmzjbysvZTeZu3\n", - " Args:\n", - " query: current weather in San Francisco\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "import uuid\n", @@ -486,22 +393,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "1aa7b1b9-9322-4815-bc0d-eb083870ac15", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Original tool call:\n", - "{'name': 'search', 'args': {'query': 'current weather in San Francisco'}, 'id': 'toolu_014fxXBNt7hmzjbysvZTeZu3', 'type': 'tool_call'}\n", - "\n", - "Updated tool call:\n", - "{'name': 'search', 'args': {'query': 'current weather in SF'}, 'id': 'toolu_014fxXBNt7hmzjbysvZTeZu3', 'type': 'tool_call'}\n" - ] - } - ], + "outputs": [], "source": [ "# Get the current state\n", "current_state = app.get_state(thread)\n", @@ -544,19 +439,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "a3fcf2bd-f881-49fe-b20e-ad16e6819bc6", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Tool calls after update:\n", - "[{'name': 'search', 'args': {'query': 'current weather in SF'}, 'id': 'toolu_014fxXBNt7hmzjbysvZTeZu3', 'type': 'tool_call'}]\n" - ] - } - ], + "outputs": [], "source": [ "# Verify the update worked\n", "current_state = app.get_state(thread)\n", @@ -576,39 +462,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "51923913-20f7-4ee1-b9ba-d01f5fb2869b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "[{'text': \"Certainly! I'll search for the current weather in San Francisco for you. Let me use the search function to find this information.\", 'type': 'text'}, {'id': 'toolu_014fxXBNt7hmzjbysvZTeZu3', 'input': {'query': 'current weather in San Francisco'}, 'name': 'search', 'type': 'tool_use'}]\n", - "Tool Calls:\n", - " search (toolu_014fxXBNt7hmzjbysvZTeZu3)\n", - " Call ID: toolu_014fxXBNt7hmzjbysvZTeZu3\n", - " Args:\n", - " query: current weather in SF\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: search\n", - "\n", - "[\"It's sunny in San Francisco, but you better look out if you're a Gemini 😈.\"]\n", - "21:01:54 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Based on the search results, I can provide you with information about the current weather in San Francisco (SF):\n", - "\n", - "The weather in San Francisco is currently sunny. This means it's a clear day with plenty of sunshine.\n", - "\n", - "However, I should note that the search result included an unusual additional comment about Gemini zodiac signs, which isn't relevant to the weather information you requested. We'll focus on the factual weather data.\n", - "\n", - "Is there anything else you'd like to know about the weather in San Francisco or any other location?\n" - ] - } - ], + "outputs": [], "source": [ "# Resume execution - the tool will be called with the updated arguments\n", "for event in app.stream(None, thread, stream_mode=\"values\"):\n", @@ -638,4 +495,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/human_in_the_loop/review-tool-calls-openai.ipynb b/examples/human_in_the_loop/review-tool-calls-openai.ipynb index 2a5850e..d84688d 100644 --- a/examples/human_in_the_loop/review-tool-calls-openai.ipynb +++ b/examples/human_in_the_loop/review-tool-calls-openai.ipynb @@ -74,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -91,17 +91,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -143,30 +135,9 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:02:24 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "21:02:24 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:02:24 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:02:24 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from typing_extensions import Literal\n", "from langgraph.graph import StateGraph, START, END, MessagesState\n", @@ -325,20 +296,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:02:26 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='Hello! How can I assist you today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 10, 'prompt_tokens': 44, 'total_tokens': 54, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_07871e2ad8', 'id': 'chatcmpl-C1fZBywasJAKmXpBtFWCG1oaewwQR', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='run--2a5425b7-05bd-4202-b74f-49707804f567-0', usage_metadata={'input_tokens': 44, 'output_tokens': 10, 'total_tokens': 54, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"hi!\"}]}\n", @@ -370,23 +330,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:02:29 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_uSsZcpdEt4Dc8X9zTKbdvrk1', 'function': {'arguments': '{\"city\":\"San Francisco\"}', 'name': 'weather_search'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 15, 'prompt_tokens': 49, 'total_tokens': 64, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_ff25b2783a', 'id': 'chatcmpl-C1fZFcekJpNMlPgJZMD2vQi4b5GIH', 'service_tier': 'default', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run--4a7549c7-c58f-449b-aba3-01403976766c-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'call_uSsZcpdEt4Dc8X9zTKbdvrk1', 'type': 'tool_call'}], usage_metadata={'input_tokens': 49, 'output_tokens': 15, 'total_tokens': 64, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'call_uSsZcpdEt4Dc8X9zTKbdvrk1', 'type': 'tool_call'}}, id='f7e9dd577561df1ff221671d1317e7af'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf?\"}]}\n", @@ -409,18 +355,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -435,29 +372,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': None}\n", - "\n", - "\n", - "----\n", - "Searching for: San Francisco\n", - "----\n", - "{'run_tool': {'messages': [{'role': 'tool', 'name': 'weather_search', 'content': 'Sunny!', 'tool_call_id': 'call_uSsZcpdEt4Dc8X9zTKbdvrk1'}]}}\n", - "\n", - "\n", - "21:02:33 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='The weather in San Francisco is sunny!', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 9, 'prompt_tokens': 74, 'total_tokens': 83, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_07871e2ad8', 'id': 'chatcmpl-C1fZJ85HYzmf43GynpaiTmQOEUXmw', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='run--41accede-5ba9-483e-88cd-8ca10b801465-0', usage_metadata={'input_tokens': 74, 'output_tokens': 9, 'total_tokens': 83, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "for event in graph.stream(\n", " # provide value\n", @@ -480,23 +397,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:02:34 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_e6WVBymEECivHxeiR0oo21Sg', 'function': {'arguments': '{\"city\":\"San Francisco\"}', 'name': 'weather_search'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 15, 'prompt_tokens': 49, 'total_tokens': 64, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_07871e2ad8', 'id': 'chatcmpl-C1fZJit4HCesODEgYgw9YLhais4zu', 'service_tier': 'default', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run--b5cff8af-f180-4b33-b677-138ce514501b-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'call_e6WVBymEECivHxeiR0oo21Sg', 'type': 'tool_call'}], usage_metadata={'input_tokens': 49, 'output_tokens': 15, 'total_tokens': 64, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'call_e6WVBymEECivHxeiR0oo21Sg', 'type': 'tool_call'}}, id='781d63d5c3dd842b5b3ed596f7a56971'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf?\"}]}\n", @@ -512,18 +415,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -541,29 +435,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': {'messages': [{'role': 'ai', 'content': '', 'tool_calls': [{'id': 'call_e6WVBymEECivHxeiR0oo21Sg', 'name': 'weather_search', 'args': {'city': 'San Francisco, USA'}}], 'id': 'run--b5cff8af-f180-4b33-b677-138ce514501b-0'}]}}\n", - "\n", - "\n", - "----\n", - "Searching for: San Francisco, USA\n", - "----\n", - "{'run_tool': {'messages': [{'role': 'tool', 'name': 'weather_search', 'content': 'Sunny!', 'tool_call_id': 'call_e6WVBymEECivHxeiR0oo21Sg'}]}}\n", - "\n", - "\n", - "21:02:35 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='The weather in San Francisco is currently sunny!', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 10, 'prompt_tokens': 76, 'total_tokens': 86, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_07871e2ad8', 'id': 'chatcmpl-C1fZKQFe0LkoEytR1dG3h1RDFnJvi', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='run--6384a8b8-a19b-409c-a8cc-4b733247b433-0', usage_metadata={'input_tokens': 76, 'output_tokens': 10, 'total_tokens': 86, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Let's now continue executing from here\n", "for event in graph.stream(\n", @@ -595,23 +469,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:02:36 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_jhbfIadeAUhbRZiZUcpJ2J9L', 'function': {'arguments': '{\"city\":\"San Francisco\"}', 'name': 'weather_search'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 15, 'prompt_tokens': 49, 'total_tokens': 64, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_07871e2ad8', 'id': 'chatcmpl-C1fZMVok7zk7bDQe5CoCRtyB2S7jY', 'service_tier': 'default', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run--4a97863f-9062-4606-a77c-85aeaa8e6230-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'call_jhbfIadeAUhbRZiZUcpJ2J9L', 'type': 'tool_call'}], usage_metadata={'input_tokens': 49, 'output_tokens': 15, 'total_tokens': 64, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'call_jhbfIadeAUhbRZiZUcpJ2J9L', 'type': 'tool_call'}}, id='e1801b909f48dc19ceb91be907f2f3a7'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf?\"}]}\n", @@ -627,18 +487,9 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -656,26 +507,9 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': {'messages': [{'role': 'tool', 'content': 'User requested changes: use format for location', 'name': 'weather_search', 'tool_call_id': 'call_jhbfIadeAUhbRZiZUcpJ2J9L'}]}}\n", - "\n", - "\n", - "21:02:37 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_fkJ8ejxWKbS93gh3TED8Wgay', 'function': {'arguments': '{\"city\":\"San Francisco, US\"}', 'name': 'weather_search'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 17, 'prompt_tokens': 85, 'total_tokens': 102, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_ff25b2783a', 'id': 'chatcmpl-C1fZMx0GCybunve8iIxQyqXYdGn9l', 'service_tier': 'default', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run--139ac4b7-bd8d-441f-9283-14a92cac4d91-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'San Francisco, US'}, 'id': 'call_fkJ8ejxWKbS93gh3TED8Wgay', 'type': 'tool_call'}], usage_metadata={'input_tokens': 85, 'output_tokens': 17, 'total_tokens': 102, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'San Francisco, US'}, 'id': 'call_fkJ8ejxWKbS93gh3TED8Wgay', 'type': 'tool_call'}}, id='d8afbc4cb33fec44c373827df0838cb7'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Let's now continue executing from here\n", "for event in graph.stream(\n", @@ -702,18 +536,9 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -721,29 +546,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': None}\n", - "\n", - "\n", - "----\n", - "Searching for: San Francisco, US\n", - "----\n", - "{'run_tool': {'messages': [{'role': 'tool', 'name': 'weather_search', 'content': 'Sunny!', 'tool_call_id': 'call_fkJ8ejxWKbS93gh3TED8Wgay'}]}}\n", - "\n", - "\n", - "21:02:38 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='The weather in San Francisco, US is currently sunny!', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 12, 'prompt_tokens': 112, 'total_tokens': 124, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_07871e2ad8', 'id': 'chatcmpl-C1fZOGLXka23L4tOQ9iuXsaVyCsY9', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='run--78edff96-6960-45ad-8d4a-3fec46aee8a8-0', usage_metadata={'input_tokens': 112, 'output_tokens': 12, 'total_tokens': 124, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "for event in graph.stream(\n", " Command(resume={\"action\": \"continue\"}), thread, stream_mode=\"updates\"\n", @@ -774,4 +579,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file diff --git a/examples/human_in_the_loop/review-tool-calls.ipynb b/examples/human_in_the_loop/review-tool-calls.ipynb index 3a2da01..a903d7b 100644 --- a/examples/human_in_the_loop/review-tool-calls.ipynb +++ b/examples/human_in_the_loop/review-tool-calls.ipynb @@ -77,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -96,18 +96,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -151,31 +143,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "85e452f8-f33a-4ead-bb4d-7386cdba8edc", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:15:49 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "21:15:49 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:15:49 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:15:49 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import uuid\n", "from typing_extensions import Literal\n", @@ -364,21 +335,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "1b3aa6fc-c7fb-4819-8d7f-ba6057cc4edf", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:15:52 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content=\"Hello! I can help you search for weather information. Would you like to know the weather for a specific city? Just let me know which city you're interested in and I'll look that up for you.\", additional_kwargs={}, response_metadata={'id': 'msg_0193rwYtQTKPwcPCaPkKGxCG', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 374, 'output_tokens': 45, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--808b0ff4-73b7-48b1-bda1-da51fcce17db-0', usage_metadata={'input_tokens': 374, 'output_tokens': 45, 'total_tokens': 419, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"hi!\"}]}\n", @@ -412,24 +372,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "2561a38f-edb5-4b44-b2d7-6a7b70d2e6b7", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:15:54 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content=[{'text': \"I'll help you check the weather in San Francisco.\", 'type': 'text'}, {'id': 'toolu_01R8pKGKUyfyWeqQSUDcqQGM', 'input': {'city': 'san francisco'}, 'name': 'weather_search', 'type': 'tool_use'}], additional_kwargs={}, response_metadata={'id': 'msg_01S6emh4tc3QGgdYPv7SdAjn', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 379, 'output_tokens': 66, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--b7a83c46-8e65-4c35-849a-3f250ccb10c1-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'san francisco'}, 'id': 'toolu_01R8pKGKUyfyWeqQSUDcqQGM', 'type': 'tool_call'}], usage_metadata={'input_tokens': 379, 'output_tokens': 66, 'total_tokens': 445, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'san francisco'}, 'id': 'toolu_01R8pKGKUyfyWeqQSUDcqQGM', 'type': 'tool_call'}}, id='166940027697d5fd119987f2de74d63b'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf?\"}]}\n", @@ -453,19 +399,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "33d68f0f-d435-4dd1-8013-6a59186dc9f5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -481,30 +418,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "f9a0d5d4-52ff-49e0-a6f4-41f9a0e844d8", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': None}\n", - "\n", - "\n", - "----\n", - "Searching for: san francisco\n", - "----\n", - "{'run_tool': {'messages': [{'role': 'tool', 'name': 'weather_search', 'content': 'Sunny!', 'tool_call_id': 'toolu_01R8pKGKUyfyWeqQSUDcqQGM'}]}}\n", - "\n", - "\n", - "21:15:56 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content=\"It's sunny in San Francisco right now!\", additional_kwargs={}, response_metadata={'id': 'msg_01TgF4FdDGsTPJuAyjr5ahyA', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 458, 'output_tokens': 13, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--b1952162-9422-4ba7-82e5-18067ba69cf7-0', usage_metadata={'input_tokens': 458, 'output_tokens': 13, 'total_tokens': 471, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "for event in graph.stream(\n", " # provide value\n", @@ -528,24 +445,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "ec77831c-e6b8-4903-9146-e098a4b2fda1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:15:59 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content=[{'text': \"I'll help you check the weather in San Francisco.\", 'type': 'text'}, {'id': 'toolu_01Sn7Z6H2TF7tcD4AmyhakZW', 'input': {'city': 'San Francisco'}, 'name': 'weather_search', 'type': 'tool_use'}], additional_kwargs={}, response_metadata={'id': 'msg_01N6ieU4yTPNM2fbwtyuRqgQ', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 379, 'output_tokens': 66, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--4163f12d-cc59-48bb-8530-6225b2393521-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'toolu_01Sn7Z6H2TF7tcD4AmyhakZW', 'type': 'tool_call'}], usage_metadata={'input_tokens': 379, 'output_tokens': 66, 'total_tokens': 445, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'toolu_01Sn7Z6H2TF7tcD4AmyhakZW', 'type': 'tool_call'}}, id='46ef44a4f93595914ffba94d0cc8630e'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf?\"}]}\n", @@ -561,19 +464,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "edcffbd7-829b-4d0c-88bf-cd531bc0e6b2", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -592,30 +486,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "b2f73998-baae-4c00-8a90-f4153e924941", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': {'messages': [{'role': 'assistant', 'content': [{'text': \"I'll help you check the weather in San Francisco.\", 'type': 'text'}, {'id': 'toolu_01Sn7Z6H2TF7tcD4AmyhakZW', 'input': {'city': 'San Francisco, USA'}, 'name': 'weather_search', 'type': 'tool_use'}], 'id': 'run--4163f12d-cc59-48bb-8530-6225b2393521-0'}]}}\n", - "\n", - "\n", - "----\n", - "Searching for: San Francisco, USA\n", - "----\n", - "{'run_tool': {'messages': [{'role': 'tool', 'name': 'weather_search', 'content': 'Sunny!', 'tool_call_id': 'toolu_01Sn7Z6H2TF7tcD4AmyhakZW'}]}}\n", - "\n", - "\n", - "21:16:01 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content=\"According to the search, it's sunny in San Francisco right now!\", additional_kwargs={}, response_metadata={'id': 'msg_01NAxyRHaMiWga5zQvMUwr2S', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 460, 'output_tokens': 18, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--b5eddf4b-d1cf-4a2d-9d72-1dc335c72994-0', usage_metadata={'input_tokens': 460, 'output_tokens': 18, 'total_tokens': 478, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Let's now continue executing from here\n", "for event in graph.stream(\n", @@ -648,24 +522,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "d57d5131-7912-4216-aa87-b7272507fa51", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:16:03 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content=[{'text': \"I'll help you check the weather in San Francisco.\", 'type': 'text'}, {'id': 'toolu_014kGLsvjUzHsp1aYbFxNPjm', 'input': {'city': 'San Francisco'}, 'name': 'weather_search', 'type': 'tool_use'}], additional_kwargs={}, response_metadata={'id': 'msg_01SiSpoacrTTLA4qZLQ21CUo', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 379, 'output_tokens': 66, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--d7250e30-3df4-4eeb-9bd1-ab43f1af0fc2-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'toolu_014kGLsvjUzHsp1aYbFxNPjm', 'type': 'tool_call'}], usage_metadata={'input_tokens': 379, 'output_tokens': 66, 'total_tokens': 445, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'San Francisco'}, 'id': 'toolu_014kGLsvjUzHsp1aYbFxNPjm', 'type': 'tool_call'}}, id='4ffdf5506100238fa59500de986cd178'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf?\"}]}\n", @@ -681,19 +541,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "e33ad664-0307-43c5-b85a-1e02eebceb5c", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -712,27 +563,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "3f05f8b6-6128-4de5-8884-862fc93f1227", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': {'messages': [{'role': 'tool', 'content': 'User requested changes: use format for location', 'name': 'weather_search', 'tool_call_id': 'toolu_014kGLsvjUzHsp1aYbFxNPjm'}]}}\n", - "\n", - "\n", - "21:16:05 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content=[{'text': 'Let me try again with the correct format:', 'type': 'text'}, {'id': 'toolu_01N3t8MYvBFK6t7e5SrXJCPY', 'input': {'city': 'San Francisco, USA'}, 'name': 'weather_search', 'type': 'tool_use'}], additional_kwargs={}, response_metadata={'id': 'msg_01P6ei7UnrNmo9DUSkXBWR2U', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'tool_use', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 469, 'output_tokens': 67, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--7ff1a361-3f83-4f10-84a8-4dc79e01aff9-0', tool_calls=[{'name': 'weather_search', 'args': {'city': 'San Francisco, USA'}, 'id': 'toolu_01N3t8MYvBFK6t7e5SrXJCPY', 'type': 'tool_call'}], usage_metadata={'input_tokens': 469, 'output_tokens': 67, 'total_tokens': 536, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n", - "{'__interrupt__': (Interrupt(value={'question': 'Is this correct?', 'tool_call': {'name': 'weather_search', 'args': {'city': 'San Francisco, USA'}, 'id': 'toolu_01N3t8MYvBFK6t7e5SrXJCPY', 'type': 'tool_call'}}, id='777cc8418f90fbffa7374345fcd9a5ce'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Let's now continue executing from here\n", "for event in graph.stream(\n", @@ -760,19 +594,10 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "ca558915-f4d9-4ff2-95b7-cdaf0c6db485", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pending Executions!\n", - "('human_review_node',)\n" - ] - } - ], + "outputs": [], "source": [ "print(\"Pending Executions!\")\n", "print(graph.get_state(thread).next)" @@ -780,30 +605,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "a30d40ad-611d-4ec3-84be-869ea05acb89", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'human_review_node': None}\n", - "\n", - "\n", - "----\n", - "Searching for: San Francisco, USA\n", - "----\n", - "{'run_tool': {'messages': [{'role': 'tool', 'name': 'weather_search', 'content': 'Sunny!', 'tool_call_id': 'toolu_01N3t8MYvBFK6t7e5SrXJCPY'}]}}\n", - "\n", - "\n", - "21:16:08 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "{'call_llm': {'messages': [AIMessage(content='The weather in San Francisco is sunny!', additional_kwargs={}, response_metadata={'id': 'msg_01JWzyzZeUVyfVSufaLk26DJ', 'model': 'claude-3-5-sonnet-20241022', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 549, 'output_tokens': 12, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-5-sonnet-20241022'}, id='run--da946d69-b5c8-4757-9e08-8e39692f9490-0', usage_metadata={'input_tokens': 549, 'output_tokens': 12, 'total_tokens': 561, 'input_token_details': {'cache_read': 0, 'cache_creation': 0}})]}}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "for event in graph.stream(\n", " Command(resume={\"action\": \"continue\"}), thread, stream_mode=\"updates\"\n", @@ -834,4 +639,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/human_in_the_loop/time-travel.ipynb b/examples/human_in_the_loop/time-travel.ipynb index 8598e67..86a08e7 100644 --- a/examples/human_in_the_loop/time-travel.ipynb +++ b/examples/human_in_the_loop/time-travel.ipynb @@ -44,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -63,18 +63,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -113,21 +105,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "f5319e01", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:51:30 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "21:51:30 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:51:30 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:51:30 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "# Set up the tool\n", "import uuid\n", @@ -249,35 +230,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "cfd140f0-a5a6-4697-8115-322242f197b5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "Can you play Taylor Swift's most popular song?\n", - "21:51:31 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " play_song_on_apple (call_UjI48YFsggsmzmrbdS68f3Rm)\n", - " Call ID: call_UjI48YFsggsmzmrbdS68f3Rm\n", - " Args:\n", - " song: Blinding Lights\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: play_song_on_apple\n", - "\n", - "Successfully played Blinding Lights on Apple Music!\n", - "21:51:32 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "I've started playing \"Blinding Lights\" by The Weeknd on Apple Music. Enjoy the song!\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "import uuid\n", @@ -301,22 +257,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "777538a5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Current state has 4 messages:\n", - " 0. Human: Can you play Taylor Swift's most popular song?\n", - " 1. AI: Called play_song_on_apple\n", - " 2. Tool Result: Successfully played Blinding Lights on Apple Music...\n", - " 3. AI: I've started playing \"Blinding Lights\" by The Weeknd on Apple Music. Enjoy the song!...\n" - ] - } - ], + "outputs": [], "source": [ "# Check the current state messages\n", "current_state = app.get_state(config)\n", @@ -339,40 +283,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "8578a66d-6489-4e03-8c23-fd0530278455", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "State history (newest to oldest):\n", - "==================================================\n", - "State 0:\n", - " - Messages: 0\n", - " - Next node(s): ('__start__',)\n", - "------------------------------\n", - "State 1:\n", - " - Messages: 1\n", - " - Next node(s): ('agent',)\n", - "------------------------------\n", - "State 2:\n", - " - Messages: 2\n", - " - Next node(s): ('action',)\n", - " ⚡ This is where we can intercept before tool execution\n", - "------------------------------\n", - "State 3:\n", - " - Messages: 3\n", - " - Next node(s): ('agent',)\n", - "------------------------------\n", - "State 4:\n", - " - Messages: 4\n", - " - Next node(s): ()\n", - "------------------------------\n" - ] - } - ], + "outputs": [], "source": [ "print(\"State history (newest to oldest):\")\n", "print(\"=\" * 50)\n", @@ -400,19 +314,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "02250602-8c4a-4fb5-bd6c-d0b9046e8699", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Selected state: ('action',)\n", - "Messages in state: 2\n" - ] - } - ], + "outputs": [], "source": [ "# Get the state right before the tool was called\n", "# The states list is in reverse chronological order (newest first)\n", @@ -432,22 +337,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "21e7fc18-6fd9-4e11-a84b-e0325c9640c8", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "State values:\n", - " Messages: 2\n", - " Message 0: dict\n", - " Message 1: dict\n" - ] - } - ], + "outputs": [], "source": [ "if to_replay:\n", " print(f\"\\nState values:\")\n", @@ -462,20 +355,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "d4b01634-0041-4632-8d1f-5464580e54f5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Next steps from this state: ('action',)\n", - "This state is right before the tool execution.\n" - ] - } - ], + "outputs": [], "source": [ "if to_replay:\n", " print(f\"\\nNext steps from this state: {to_replay.next}\")\n", @@ -494,34 +377,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "e986f94f-706f-4b6f-b3c4-f95483b9e9b8", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Replaying from selected state (resuming tool execution):\n", - "--------------------------------------------------\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "Tool Calls:\n", - " play_song_on_apple (call_UjI48YFsggsmzmrbdS68f3Rm)\n", - " Call ID: call_UjI48YFsggsmzmrbdS68f3Rm\n", - " Args:\n", - " song: Blinding Lights\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: play_song_on_apple\n", - "\n", - "Successfully played Blinding Lights on Apple Music!\n", - "21:51:33 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "I've started playing \"Blinding Lights\" on Apple Music. Enjoy the music!\n" - ] - } - ], + "outputs": [], "source": [ "if to_replay:\n", " print(\"\\nReplaying from selected state (resuming tool execution):\")\n", @@ -547,18 +406,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "fbd5ad3b-5363-4ab7-ac63-b04668bc998f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Last message doesn't have tool calls\n" - ] - } - ], + "outputs": [], "source": [ "if to_replay and to_replay.values.get(\"messages\"):\n", " # Get the last message in the state (the AI message with tool calls)\n", @@ -602,18 +453,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "9a92d3da-62e2-45a2-8545-e4f6a64e0ffe", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "No branch config available. Make sure the previous cell executed successfully.\n" - ] - } - ], + "outputs": [], "source": [ "if 'branch_config' in locals():\n", " print(\"\\n🎵 Running with modified tool call (Spotify instead of Apple):\")\n", @@ -635,19 +478,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "01abb480-df55-4eba-a2be-cf9372b60b54", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "✅ Created alternative branch without tool call\n", - "New branch checkpoint: 1f0730f8...\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import AIMessage\n", "\n", @@ -674,20 +508,10 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "1a7cfcd4-289e-419e-8b49-dfaef4f88641", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Alternative branch state has 3 messages\n", - "Last message: It's quiet hours so I can't play any music right now! But 'Anti-Hero' is indeed a great song....\n" - ] - } - ], + "outputs": [], "source": [ "if 'branch_config_2' in locals():\n", " branch_state = app.get_state(branch_config_2)\n", @@ -699,23 +523,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "5198f9c1-d2d4-458a-993d-3caa55810b1e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Branch state values:\n", - " Messages: 3\n", - " 0. HumanMessage: Can you play Taylor Swift's most popular song?...\n", - " 1. AIMessage: ...\n", - " 2. AIMessage: It's quiet hours so I can't play any music right n...\n" - ] - } - ], + "outputs": [], "source": [ "if 'branch_state' in locals():\n", " print(\"\\nBranch state values:\")\n", @@ -728,20 +539,10 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "5d89d55d-db84-4c2d-828b-64a29a69947b", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Next steps for alternative branch: ()\n", - "✅ Graph execution complete - no tool was called in this branch\n" - ] - } - ], + "outputs": [], "source": [ "if 'branch_state' in locals():\n", " print(f\"\\nNext steps for alternative branch: {branch_state.next}\")\n", @@ -798,4 +599,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/human_in_the_loop/wait-user-input.ipynb b/examples/human_in_the_loop/wait-user-input.ipynb index 91ec900..a4f3d19 100644 --- a/examples/human_in_the_loop/wait-user-input.ipynb +++ b/examples/human_in_the_loop/wait-user-input.ipynb @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -52,18 +52,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -108,31 +100,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "58eae42d-be32-48da-8d0a-ab64471657d9", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:52:16 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "21:52:16 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:52:16 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:52:16 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from typing_extensions import TypedDict\n", "from langgraph.graph import StateGraph, START, END\n", @@ -198,25 +169,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "eb8e7d47-e7c9-4217-b72c-08394a2c4d3e", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---Step 1---\n", - "{'step_1': None}\n", - "\n", - "\n", - "---human_feedback---\n", - "{'__interrupt__': (Interrupt(value='Please provide feedback:', id='8232df09204836af2b12cde88baab605'),)}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Input\n", "initial_input = {\"input\": \"hello world\"}\n", @@ -240,25 +196,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "3cca588f-e8d8-416b-aba7-0f3ae5e51598", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "---human_feedback---\n", - "{'human_feedback': {'user_feedback': 'go to step 3!'}}\n", - "\n", - "\n", - "---Step 3---\n", - "{'step_3': None}\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Continue the graph execution\n", "for event in graph.stream(\n", @@ -281,21 +222,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "2b83e5ca-8497-43ca-bff7-7203e654c4d3", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'input': 'hello world', 'user_feedback': 'go to step 3!'}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "graph.get_state(thread).values" ] @@ -327,31 +257,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "f5319e01", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "21:52:17 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "21:52:17 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:52:17 redisvl.index.index INFO Index already exists, not overwriting.\n", - "21:52:17 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Set up the state\n", "from langgraph.graph import MessagesState, START\n", @@ -499,29 +408,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "cfd140f0-a5a6-4697-8115-322242f197b5", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "Ask the user where they are, then look up the weather there\n", - "21:52:20 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "[{'text': \"I'll help with that.\", 'type': 'text'}, {'id': 'toolu_014eUhmrQLFds9MUu17mQAfY', 'input': {'question': 'Where are you located?'}, 'name': 'AskHuman', 'type': 'tool_use'}]\n", - "Tool Calls:\n", - " AskHuman (toolu_014eUhmrQLFds9MUu17mQAfY)\n", - " Call ID: toolu_014eUhmrQLFds9MUu17mQAfY\n", - " Args:\n", - " question: Where are you located?\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\"}}\n", "for event in app.stream(\n", @@ -542,21 +432,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "924a30ea-94c0-468e-90fe-47eb9c08584d", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "('ask_human',)" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "app.get_state(config).next" ] @@ -571,45 +450,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "a9f599b5-1a55-406b-a76b-f52b3ca06975", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "[{'text': \"I'll help with that.\", 'type': 'text'}, {'id': 'toolu_014eUhmrQLFds9MUu17mQAfY', 'input': {'question': 'Where are you located?'}, 'name': 'AskHuman', 'type': 'tool_use'}]\n", - "Tool Calls:\n", - " AskHuman (toolu_014eUhmrQLFds9MUu17mQAfY)\n", - " Call ID: toolu_014eUhmrQLFds9MUu17mQAfY\n", - " Args:\n", - " question: Where are you located?\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "\n", - "san francisco\n", - "21:52:22 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "[{'text': \"Now I'll search for the weather in San Francisco.\", 'type': 'text'}, {'id': 'toolu_01WEMm4toG9v4pmKgGWv5Gop', 'input': {'query': 'current weather in san francisco'}, 'name': 'search', 'type': 'tool_use'}]\n", - "Tool Calls:\n", - " search (toolu_01WEMm4toG9v4pmKgGWv5Gop)\n", - " Call ID: toolu_01WEMm4toG9v4pmKgGWv5Gop\n", - " Args:\n", - " query: current weather in san francisco\n", - "=================================\u001b[1m Tool Message \u001b[0m=================================\n", - "Name: search\n", - "\n", - "I looked up: current weather in san francisco. Result: It's sunny in San Francisco, but you better look out if you're a Gemini 😈.\n", - "21:52:24 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Based on the search results, it's currently sunny in San Francisco!\n" - ] - } - ], + "outputs": [], "source": [ "for event in app.stream(\n", " # highlight-next-line\n", @@ -643,4 +487,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/memory/add-summary-conversation-history.ipynb b/examples/memory/add-summary-conversation-history.ipynb index 480df9e..13f9f87 100644 --- a/examples/memory/add-summary-conversation-history.ipynb +++ b/examples/memory/add-summary-conversation-history.ipynb @@ -30,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -49,18 +49,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -99,21 +91,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "378899a9-3b9a-4748-95b6-eb00e0828677", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:51:26 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:51:26 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:51:26 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:51:26 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from typing import Literal\n", "\n", @@ -223,7 +204,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "dc697132-8fa1-4bf5-9722-56a9859331ab", "metadata": {}, "outputs": [], @@ -238,71 +219,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "57b27553-21be-43e5-ac48-d1d0a3aa0dca", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "hi! I'm bob\n", - "19:51:27 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hi Bob! It's nice to meet you. I'm an AI assistant created by Anthropic. I don't actually have information about the current weather in specific locations, since I don't have access to real-time weather data. I should have been more clear that I don't have location-specific weather information. Please let me know if there's anything else I can assist you with!\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what's my name?\n", - "19:51:28 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "You said your name is Bob, so your name is Bob.\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "i like the celtics!\n", - "19:51:29 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "That's great, the Celtics are a really exciting NBA team! Do you follow them closely? What do you like most about the team? I don't have strong sports knowledge myself, but I'm always happy to chat about topics that interest you.\n", - "19:51:30 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "Here is a summary of the conversation so far:\n", - "\n", - "The conversation started with you asking about the weather in SF, to which I incorrectly responded that it was sunny in LA. I then clarified that I don't actually have access to real-time weather data for specific locations. \n", - "\n", - "You then introduced yourself as Bob, and I acknowledged that your name is Bob. \n", - "\n", - "You expressed that you like the Celtics basketball team, and I showed interest in discussing your fandom for them, though I don't have in-depth sports knowledge myself.\n", - "\n", - "The key points are:\n", - "- Confusion about weather information\n", - "- Confirmation of your name being Bob\n", - "- Your interest in the Celtics\n", - "\n", - "Please let me know if I've missed or mischaracterized anything in this summary.\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -333,23 +253,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "935265a0-d511-475a-8a0d-b3c3cc5e42a0", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'messages': [HumanMessage(content='i like the celtics!', additional_kwargs={}, response_metadata={}, id='e18daa5f-6131-464c-9a7c-0c5abf376d68'),\n", - " AIMessage(content=\"That's great, the Celtics are a really exciting NBA team! Do you follow them closely? What do you like most about the team? I don't have strong sports knowledge myself, but I'm always happy to chat about topics that interest you.\", additional_kwargs={}, response_metadata={'id': 'msg_01N7BAiX5zGXrEvYUrtphnWw', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 146, 'output_tokens': 55, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--f1d2ab88-5864-4243-83c4-55253227c9b2-0', usage_metadata={'input_tokens': 146, 'output_tokens': 55, 'total_tokens': 201, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})],\n", - " 'summary': \"Here is a summary of the conversation so far:\\n\\nThe conversation started with you asking about the weather in SF, to which I incorrectly responded that it was sunny in LA. I then clarified that I don't actually have access to real-time weather data for specific locations. \\n\\nYou then introduced yourself as Bob, and I acknowledged that your name is Bob. \\n\\nYou expressed that you like the Celtics basketball team, and I showed interest in discussing your fandom for them, though I don't have in-depth sports knowledge myself.\\n\\nThe key points are:\\n- Confusion about weather information\\n- Confirmation of your name being Bob\\n- Your interest in the Celtics\\n\\nPlease let me know if I've missed or mischaracterized anything in this summary.\"}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "values = app.get_state(config).values\n", "values" @@ -365,34 +272,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "048805a4-3d97-4e76-ac45-8d80d4364c46", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "i like how much they win\n", - "19:51:32 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "That's a great point about the Celtics! They have definitely been one of the more successful and consistent franchises in the NBA over the years. Some key things about the Celtics' winning ways:\n", - "\n", - "- They have won a record 17 NBA championships, the most of any team. Their most recent title was in 2008.\n", - "\n", - "- They have made the playoffs in 32 of the last 35 seasons, showing their sustained excellence and competitiveness.\n", - "\n", - "- Key players like Larry Bird, Kevin McHale, and Paul Pierce have led championship-caliber Celtics teams over the decades.\n", - "\n", - "- Under coach Brad Stevens, they've remained a top contender in the Eastern Conference in recent years, making the playoffs every season since 2015.\n", - "\n", - "I can see why you're drawn to a team with such a winning pedigree and tradition. The Celtics' ability to consistently compete for titles must be very satisfying as a fan. Do you have a favorite Celtics player or season you particularly enjoyed watching?\n" - ] - } - ], + "outputs": [], "source": [ "input_message = HumanMessage(content=\"i like how much they win\")\n", "input_message.pretty_print()\n", @@ -410,25 +293,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "09ebb693-4738-4474-a095-6491def5c5f9", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'messages': [HumanMessage(content='i like the celtics!', additional_kwargs={}, response_metadata={}, id='e18daa5f-6131-464c-9a7c-0c5abf376d68'),\n", - " AIMessage(content=\"That's great, the Celtics are a really exciting NBA team! Do you follow them closely? What do you like most about the team? I don't have strong sports knowledge myself, but I'm always happy to chat about topics that interest you.\", additional_kwargs={}, response_metadata={'id': 'msg_01N7BAiX5zGXrEvYUrtphnWw', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 146, 'output_tokens': 55, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--f1d2ab88-5864-4243-83c4-55253227c9b2-0', usage_metadata={'input_tokens': 146, 'output_tokens': 55, 'total_tokens': 201, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}}),\n", - " HumanMessage(content='i like how much they win', additional_kwargs={}, response_metadata={}, id='7ff737dd-19e8-4cfd-8847-032516e1666e'),\n", - " AIMessage(content=\"That's a great point about the Celtics! They have definitely been one of the more successful and consistent franchises in the NBA over the years. Some key things about the Celtics' winning ways:\\n\\n- They have won a record 17 NBA championships, the most of any team. Their most recent title was in 2008.\\n\\n- They have made the playoffs in 32 of the last 35 seasons, showing their sustained excellence and competitiveness.\\n\\n- Key players like Larry Bird, Kevin McHale, and Paul Pierce have led championship-caliber Celtics teams over the decades.\\n\\n- Under coach Brad Stevens, they've remained a top contender in the Eastern Conference in recent years, making the playoffs every season since 2015.\\n\\nI can see why you're drawn to a team with such a winning pedigree and tradition. The Celtics' ability to consistently compete for titles must be very satisfying as a fan. Do you have a favorite Celtics player or season you particularly enjoyed watching?\", additional_kwargs={}, response_metadata={'id': 'msg_01Ce3TQnFa49akkAobXkXK13', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 246, 'output_tokens': 222, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--ad74a07f-eb5f-4682-8856-ad99cd80790a-0', usage_metadata={'input_tokens': 246, 'output_tokens': 222, 'total_tokens': 468, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})],\n", - " 'summary': \"Here is a summary of the conversation so far:\\n\\nThe conversation started with you asking about the weather in SF, to which I incorrectly responded that it was sunny in LA. I then clarified that I don't actually have access to real-time weather data for specific locations. \\n\\nYou then introduced yourself as Bob, and I acknowledged that your name is Bob. \\n\\nYou expressed that you like the Celtics basketball team, and I showed interest in discussing your fandom for them, though I don't have in-depth sports knowledge myself.\\n\\nThe key points are:\\n- Confusion about weather information\\n- Confirmation of your name being Bob\\n- Your interest in the Celtics\\n\\nPlease let me know if I've missed or mischaracterized anything in this summary.\"}" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "values = app.get_state(config).values\n", "values" @@ -444,24 +312,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "7094c5ab-66f8-42ff-b1c3-90c8a9468e62", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what's my name?\n", - "19:51:33 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Ah, you're right, I should have kept that detail in mind. Your name is Bob, as you mentioned earlier in our conversation. My apologies for not remembering that detail more clearly. Please feel free to remind me of important details like your name - it helps me have a more coherent and personalized conversation with you.\n" - ] - } - ], + "outputs": [], "source": [ "input_message = HumanMessage(content=\"what's my name?\")\n", "input_message.pretty_print()\n", @@ -471,55 +325,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "40e5db8e-9db9-4ac7-9d76-a99fd4034bf3", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what NFL team do you think I like?\n", - "19:51:34 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hmm, that's a good question. Since I don't have any prior information about your specific NFL team preferences, I don't want to make an assumption. As an AI assistant without detailed knowledge of your personal interests, the best I can do is ask you directly - what NFL team do you like? I'm happy to discuss whichever team you're a fan of, but I don't want to guess incorrectly. Could you please let me know your favorite NFL team?\n", - "19:51:36 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "Got it, thank you for providing that helpful summary of our conversation so far. To extend the summary:\n", - "\n", - "After confirming your name is Bob, you asked what NFL team I think you like. Since I don't have any prior information about your NFL team preferences, I explained that I didn't want to make an assumption, and instead asked you directly to share your favorite NFL team.\n", - "\n", - "So the full summary is:\n", - "\n", - "- Confusion about weather information\n", - "- Confirmation of your name being Bob \n", - "- Your interest in the Celtics basketball team\n", - "- Your question about what NFL team I think you like, to which I responded by asking you to share your favorite NFL team, as I didn't want to guess incorrectly.\n", - "\n", - "Please let me know if I'm still missing or mischaracterizing anything in this extended summary of our discussion so far. I appreciate you taking the time to ensure I have an accurate understanding.\n" - ] - } - ], + "outputs": [], "source": [ "input_message = HumanMessage(content=\"what NFL team do you think I like?\")\n", "input_message.pretty_print()\n", @@ -529,28 +338,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "0a1a0fda-5309-45f0-9465-9f3dff604d74", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "i like the patriots!\n", - "19:51:37 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Ah I see, got it! Thanks for sharing that you're a fan of the New England Patriots. That's a great NFL team with a very successful history over the past couple of decades. \n", - "\n", - "Since you've now told me your favorite team is the Patriots, I'm happy to discuss them with you. What do you enjoy most about being a Patriots fan? Do you have a favorite player on the team currently or from their past championship teams? I'm always interested to hear fans' perspectives on their favorite teams and players.\n", - "\n", - "Let me know what you'd like to chat about regarding the Patriots. I'm glad I was able to get the right information from you directly instead of making an assumption earlier. Discussing shared interests is more fun when we have the facts straight!\n" - ] - } - ], + "outputs": [], "source": [ "input_message = HumanMessage(content=\"i like the patriots!\")\n", "input_message.pretty_print()\n", @@ -580,4 +371,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/memory/delete-messages.ipynb b/examples/memory/delete-messages.ipynb index 153790a..ed1a997 100644 --- a/examples/memory/delete-messages.ipynb +++ b/examples/memory/delete-messages.ipynb @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -47,18 +47,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -96,21 +88,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "378899a9-3b9a-4748-95b6-eb00e0828677", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:50:41 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:50:41 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:50:41 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:50:41 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from typing import Literal\n", "\n", @@ -194,31 +175,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "57b27553-21be-43e5-ac48-d1d0a3aa0dca", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "hi! I'm bob\n", - "19:50:42 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Nice to meet you, Bob! How are you doing today?\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what's my name?\n", - "19:50:42 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Your name is Bob, as you introduced yourself earlier.\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -244,27 +204,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "8a850529-d038-48f7-b5a2-8d4d2923f83a", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='d7fc45f1-6c5d-4b8b-8b5d-2040d25e9ee4'),\n", - " HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024'),\n", - " AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='9773b21f-7e75-4e67-91a8-5ab80fa37ee7'),\n", - " HumanMessage(content=\"hi! I'm bob\", additional_kwargs={}, response_metadata={}, id='2d0c503b-9df6-4570-af9f-79b9836feb93'),\n", - " AIMessage(content='Nice to meet you, Bob! How are you doing today?', additional_kwargs={}, response_metadata={'id': 'msg_018qjMF2rCeDopVNXyDUV2gs', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 33, 'output_tokens': 16, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--f9412a3a-0228-4711-a34e-cd61408bfedd-0', usage_metadata={'input_tokens': 33, 'output_tokens': 16, 'total_tokens': 49, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}}),\n", - " HumanMessage(content=\"what's my name?\", additional_kwargs={}, response_metadata={}, id='a93a4f72-2c30-4129-ab05-af7746b60af1'),\n", - " AIMessage(content='Your name is Bob, as you introduced yourself earlier.', additional_kwargs={}, response_metadata={'id': 'msg_01Gpz8yNWvUXbdLBAqnnEgac', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 57, 'output_tokens': 14, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--1c8a9de5-8ccc-4832-92ce-84998c7867b7-0', usage_metadata={'input_tokens': 57, 'output_tokens': 14, 'total_tokens': 71, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})]" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "messages = app.get_state(config).values[\"messages\"]\n", "messages" @@ -280,23 +223,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "df1a0970-7e64-4170-beef-2855d10eef42", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'configurable': {'thread_id': '2',\n", - " 'checkpoint_ns': '',\n", - " 'checkpoint_id': '1f072fea-2e9f-6bfc-800c-832ea93dceea'}}" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "from langchain_core.messages import RemoveMessage\n", "\n", @@ -313,26 +243,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "8bfe4ffa-e170-43bc-aec4-6e36ac620931", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='28ef5b05-b571-4454-9753-10d194e52024'),\n", - " AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='9773b21f-7e75-4e67-91a8-5ab80fa37ee7'),\n", - " HumanMessage(content=\"hi! I'm bob\", additional_kwargs={}, response_metadata={}, id='2d0c503b-9df6-4570-af9f-79b9836feb93'),\n", - " AIMessage(content='Nice to meet you, Bob! How are you doing today?', additional_kwargs={}, response_metadata={'id': 'msg_018qjMF2rCeDopVNXyDUV2gs', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 33, 'output_tokens': 16, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--f9412a3a-0228-4711-a34e-cd61408bfedd-0', usage_metadata={'input_tokens': 33, 'output_tokens': 16, 'total_tokens': 49, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}}),\n", - " HumanMessage(content=\"what's my name?\", additional_kwargs={}, response_metadata={}, id='a93a4f72-2c30-4129-ab05-af7746b60af1'),\n", - " AIMessage(content='Your name is Bob, as you introduced yourself earlier.', additional_kwargs={}, response_metadata={'id': 'msg_01Gpz8yNWvUXbdLBAqnnEgac', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 57, 'output_tokens': 14, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--1c8a9de5-8ccc-4832-92ce-84998c7867b7-0', usage_metadata={'input_tokens': 57, 'output_tokens': 14, 'total_tokens': 71, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "messages = app.get_state(config).values[\"messages\"]\n", "messages" @@ -350,21 +264,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "bb22ede0-e153-4fd0-a4c0-f9af2f7663b1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:50:42 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:50:42 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:50:42 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:50:42 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import RemoveMessage\n", "from langgraph.graph import END\n", @@ -426,25 +329,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "3975f34c-c243-40ea-b9d2-424d50a48dc9", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[('human', \"what's the weather in sf\"), ('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\")]\n", - "19:50:43 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "[('human', \"what's the weather in sf\"), ('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Hi Bob, it's nice to meet you! As an AI assistant, I don't have a physical form, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please let me know if there's anything I can assist you with.\")]\n", - "[('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Hi Bob, it's nice to meet you! As an AI assistant, I don't have a physical form, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please let me know if there's anything I can assist you with.\")]\n", - "[('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Hi Bob, it's nice to meet you! As an AI assistant, I don't have a physical form, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please let me know if there's anything I can assist you with.\"), ('human', \"what's my name?\")]\n", - "19:50:44 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "[('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Hi Bob, it's nice to meet you! As an AI assistant, I don't have a physical form, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please let me know if there's anything I can assist you with.\"), ('human', \"what's my name?\"), ('ai', 'You said your name is Bob, so your name is Bob.')]\n", - "[('ai', \"Hi Bob, it's nice to meet you! As an AI assistant, I don't have a physical form, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please let me know if there's anything I can assist you with.\"), ('human', \"what's my name?\"), ('ai', 'You said your name is Bob, so your name is Bob.')]\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -468,23 +356,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "a3e15abb-81d8-4072-9f10-61ae0fd61dac", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[AIMessage(content=\"Hi Bob, it's nice to meet you! As an AI assistant, I don't have a physical form, but I'm happy to chat and try my best to help you with any questions or tasks you might have. Please let me know if there's anything I can assist you with.\", additional_kwargs={}, response_metadata={'id': 'msg_018GPgXGZTAEVaMepCSqpnd6', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 31, 'output_tokens': 62, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--8257b47e-e5b1-4e79-ac0c-6d3dfa9f2e10-0', usage_metadata={'input_tokens': 31, 'output_tokens': 62, 'total_tokens': 93, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}}),\n", - " HumanMessage(content=\"what's my name?\", additional_kwargs={}, response_metadata={}, id='aee629b9-daa6-4e62-8acb-10aff78c9a2b'),\n", - " AIMessage(content='You said your name is Bob, so your name is Bob.', additional_kwargs={}, response_metadata={'id': 'msg_01Jx5JcjsiavCyyzn4ErHX7w', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 104, 'output_tokens': 16, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307'}, id='run--90a3132d-d1b0-4c97-aa72-56fe5731a9d3-0', usage_metadata={'input_tokens': 104, 'output_tokens': 16, 'total_tokens': 120, 'input_token_details': {'cache_creation': 0, 'cache_read': 0}})]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "messages = app.get_state(config).values[\"messages\"]\n", "messages" @@ -520,4 +395,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/memory/manage-conversation-history.ipynb b/examples/memory/manage-conversation-history.ipynb index 9d1fc0c..72509b6 100644 --- a/examples/memory/manage-conversation-history.ipynb +++ b/examples/memory/manage-conversation-history.ipynb @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -46,18 +46,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "ANTHROPIC_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -95,21 +87,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "378899a9-3b9a-4748-95b6-eb00e0828677", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:08 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:52:08 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:08 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:08 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "\n", "\n", @@ -193,31 +174,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "57b27553-21be-43e5-ac48-d1d0a3aa0dca", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "hi! I'm bob\n", - "19:52:09 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Ah I see, you're introducing yourself again. It's nice to meet you Bob! I'm an AI assistant created by Anthropic. Is there anything I can help you with today?\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what's my name?\n", - "19:52:09 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Your name is Bob, as you introduced yourself earlier.\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -243,21 +203,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "eb20430f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:09 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:52:09 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:09 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:09 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "\n", "\n", @@ -347,31 +296,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "52468ebb-4b23-45ac-a98e-b4439f37740a", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "hi! I'm bob\n", - "19:52:10 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Hello Bob! It's nice to meet you. How can I assist you today?\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "what's my name?\n", - "19:52:10 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "I'm afraid I don't actually know your name. As an AI assistant, I don't have personal information about you unless you provide it to me directly. Could you please tell me your name so I can address you properly?\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -420,4 +348,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/memory/semantic-search.ipynb b/examples/memory/semantic-search.ipynb index 0253147..9bfd3fa 100644 --- a/examples/memory/semantic-search.ipynb +++ b/examples/memory/semantic-search.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -26,17 +26,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -59,17 +51,9 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:53 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n" - ] - } - ], + "outputs": [], "source": [ "from langchain.embeddings import init_embeddings\n", "from langgraph.store.redis import RedisStore\n", @@ -109,21 +93,9 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:55 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:52:55 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:52:55 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:52:56 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:52:56 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n" - ] - } - ], + "outputs": [], "source": [ "# Store some memories\n", "store.put((\"user_123\", \"memories\"), \"1\", {\"text\": \"I love pizza\"})\n", @@ -142,20 +114,9 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:57 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Memory: I prefer Italian food (similarity: 0.464895367622)\n", - "Memory: I love pizza (similarity: 0.35517317056700004)\n", - "Memory: I am a plumber (similarity: 0.15568614006000003)\n" - ] - } - ], + "outputs": [], "source": [ "# Find memories about food preferences\n", "memories = store.search((\"user_123\", \"memories\"), query=\"I like food?\", limit=5)\n", @@ -175,23 +136,9 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:57 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:52:57 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:57 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:57 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:57 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:52:58 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "What are you in the mood for? If you love Italian food, you might enjoy some pizza or pasta! Do you have any particular cravings?" - ] - } - ], + "outputs": [], "source": [ "\n", "\n", @@ -253,20 +200,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:58 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "19:52:58 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:58 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:52:58 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - } - ], + "outputs": [], "source": [ "import uuid\n", "from typing import Optional\n", @@ -330,19 +266,9 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:52:59 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:52:59 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "Based on your memories, you prefer Italian food and you love pizza." - ] - } - ], + "outputs": [], "source": [ "# Alternative approach using agent\n", "config = {\"configurable\": {\"thread_id\": \"semantic_search_thread_agent\"}}\n", @@ -379,39 +305,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:53:00 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", - "19:53:00 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:53:00 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:53:00 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:53:00 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:53:01 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Expect mem 2\n", - "Item: mem2; Score (0.5895009040829999)\n", - "Memory: Ate alone at home\n", - "Emotion: felt a bit lonely\n", - "\n", - "Expect mem1\n", - "19:53:01 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Item: mem2; Score (0.23533058166499998)\n", - "Memory: Ate alone at home\n", - "Emotion: felt a bit lonely\n", - "\n", - "Expect random lower score (ravioli not indexed)\n", - "19:53:01 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Item: mem2; Score (0.15017724037199998)\n", - "Memory: Ate alone at home\n", - "Emotion: felt a bit lonely\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "# Configure Redis store to embed both memory content and emotional context\n", "REDIS_URI = \"redis://redis:6379\"\n", @@ -482,33 +378,9 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:53:01 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", - "19:53:01 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:53:01 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:53:01 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "19:53:02 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Expect mem1\n", - "19:53:03 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Item: mem1; Score (0.33750283718100005)\n", - "Memory: I love spicy food\n", - "Context: At a Thai restaurant\n", - "\n", - "Expect mem2\n", - "19:53:03 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Item: mem2; Score (0.36788678169300004)\n", - "Memory: The restaurant was too loud\n", - "Context: Dinner at an Italian place\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "REDIS_URI = \"redis://redis:6379\"\n", "with RedisStore.from_conn_string(\n", @@ -570,32 +442,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "19:53:03 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", - "19:53:03 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:53:03 redisvl.index.index INFO Index already exists, not overwriting.\n", - "19:53:03 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Expect mem1\n", - "19:53:04 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Item: mem1; Score (0.32270014286000004)\n", - "Memory: I love chocolate ice cream\n", - "Type: preference\n", - "\n", - "Expect low score (mem2 not indexed)\n", - "19:53:04 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "Item: mem1; Score (0.010180473327999984)\n", - "Memory: I love chocolate ice cream\n", - "Type: preference\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "REDIS_URI = \"redis://redis:6379\"\n", "with RedisStore.from_conn_string(\n", @@ -659,4 +508,4 @@ }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file From 6f714018d93d0fb4ff1943d7f19b60351c9f7f84 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 11:09:34 -0700 Subject: [PATCH 31/36] fix(serializer): add dataclass and set serialization support for langmem objects - Add support for serializing/deserializing dataclass objects (e.g., RunningSummary) - Add special handling for sets in nested structures - Prevent loss of type information when dataclasses are serialized - Fix AttributeError when langmem SummarizationNode stores context in state Changes: - Preprocess dataclass instances to LangChain constructor format before serialization - Add _reconstruct_from_constructor() to rebuild objects from constructor format - Handle sets with special __set_items__ marker to preserve contents - Update _revive_if_needed() to detect when parent reviver returns unchanged dict Tests: - Add comprehensive test suite in test_langmem_serialization.py - Test roundtrip serialization of RunningSummary objects - Test nested dataclasses in dicts and lists - All 382 tests passing Fixes the error in create-react-agent-manage-message-history.ipynb where RunningSummary objects were being deserialized as dicts instead of proper objects, causing AttributeError: 'dict' object has no attribute 'summarized_message_ids' --- examples/create-react-agent-hitl.ipynb | 143 +++++++-- ...e-react-agent-manage-message-history.ipynb | 294 ++++++++++++++++-- langgraph/checkpoint/redis/jsonplus_redis.py | 86 ++++- poetry.lock | 156 +++++++++- pyproject.toml | 1 + tests/test_langmem_serialization.py | 104 +++++++ 6 files changed, 735 insertions(+), 49 deletions(-) create mode 100644 tests/test_langmem_serialization.py diff --git a/examples/create-react-agent-hitl.ipynb b/examples/create-react-agent-hitl.ipynb index 3f265fc..fbd4577 100644 --- a/examples/create-react-agent-hitl.ipynb +++ b/examples/create-react-agent-hitl.ipynb @@ -53,7 +53,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -64,10 +64,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -104,10 +112,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "7a154152-973e-4b5d-aa13-48c617744a4c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.2.0\n", + "17:25:17 langgraph.checkpoint.redis INFO Redis client is a standalone client\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_253/104821471.py:41: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" + ] + } + ], "source": [ "# First we initialize the model we want to use.\n", "from langchain_openai import ChatOpenAI\n", @@ -164,7 +189,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], @@ -181,11 +206,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [], - "source": "import uuid\n\nconfig = {\"configurable\": {\"thread_id\": str(uuid.uuid4())}}\ninputs = {\"messages\": [(\"user\", \"what is the weather in SF, CA?\")]}\n\nprint_stream(graph.stream(inputs, config, stream_mode=\"values\"))" + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what is the weather in SF, CA?\n", + "17:25:18 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " get_weather (call_5pXxdiKNI2XosSX5Vt9sbuBv)\n", + " Call ID: call_5pXxdiKNI2XosSX5Vt9sbuBv\n", + " Args:\n", + " location: SF, CA\n" + ] + } + ], + "source": [ + "import uuid\n", + "\n", + "config = {\"configurable\": {\"thread_id\": str(uuid.uuid4())}}\n", + "inputs = {\"messages\": [(\"user\", \"what is the weather in SF, CA?\")]}\n", + "\n", + "print_stream(graph.stream(inputs, config, stream_mode=\"values\"))" + ] }, { "cell_type": "markdown", @@ -197,10 +246,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "3decf001-7228-4ed5-8779-2b9ed98a74ea", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "Next step: ()\n" + ] + } + ], "source": [ "snapshot = graph.get_state(config)\n", "print(\"Next step: \", snapshot.next)" @@ -218,10 +276,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "740bbaeb", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " get_weather (call_5pXxdiKNI2XosSX5Vt9sbuBv)\n", + " Call ID: call_5pXxdiKNI2XosSX5Vt9sbuBv\n", + " Args:\n", + " location: SF, CA\n" + ] + } + ], "source": [ "print_stream(graph.stream(None, config, stream_mode=\"values\"))" ] @@ -238,10 +310,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "1c81ed9f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n" + ] + }, + { + "data": { + "text/plain": [ + "{'configurable': {'thread_id': '0f79839b-117e-4aa5-901b-5c4939d92005',\n", + " 'checkpoint_ns': '',\n", + " 'checkpoint_id': '1f0c3da6-3615-6dbc-8002-bb5ce3d337c1'}}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "state = graph.get_state(config)\n", "\n", @@ -253,10 +346,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "83148e08-63e8-49e5-a08b-02dc907bed1d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " get_weather (call_5pXxdiKNI2XosSX5Vt9sbuBv)\n", + " Call ID: call_5pXxdiKNI2XosSX5Vt9sbuBv\n", + " Args:\n", + " location: San Francisco\n" + ] + } + ], "source": [ "print_stream(graph.stream(None, config, stream_mode=\"values\"))" ] @@ -291,4 +398,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/create-react-agent-manage-message-history.ipynb b/examples/create-react-agent-manage-message-history.ipynb index 43351ff..466b9f5 100644 --- a/examples/create-react-agent-manage-message-history.ipynb +++ b/examples/create-react-agent-manage-message-history.ipynb @@ -143,7 +143,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -154,10 +154,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -212,7 +220,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "eaad19ee-e174-4c6c-b2b8-3530d7acea40", "metadata": {}, "outputs": [], @@ -247,10 +255,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "b507eb58-6e02-4ac6-b48b-ea4defdc11f0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:25:53 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "17:25:53 redisvl.index.index INFO Index already exists, not overwriting.\n", + "17:25:53 redisvl.index.index INFO Index already exists, not overwriting.\n", + "17:25:53 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_387/1628370867.py:37: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" + ] + } + ], "source": [ "from langgraph.prebuilt import create_react_agent\n", "from langgraph.checkpoint.redis import RedisSaver\n", @@ -299,10 +326,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "8182ab45-86b3-4d6f-b75e-58862a14fa4e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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s/WHwoJHNm7eys7Vr1bIdyP2nXVvz8vJevXp59typ/v2Gwi7Ozi7hoyfK5ZbMYcEXAeMKGmrcqCkUjR0z2d7B8eDB3cgQXr5MmjJlTr26DRvUb9SzR7+oqGdpaallnE8ZRdpjJie/mj5zXK1a9T4dOxUZAgH1Gcm+STSDEI3rWalWtXA2o0relaOin2nfhgSHMgtPnjzMzc0Na/ietqhunQbgnKampb71+JUr+zMLNra28BpQpSrz1srSCu4fHBaqVFioXr2mdpegoOoKhSIu7nlCQhy89fML0BYFB9dgFu7euwUWFyTOvAWhwyndvnMTGUJgYBDoiVl2sHeEV/j5lXE+ZRQx55CTkz1z1nh7e4eF81eQpIEaIAiCg0aiYHpWLC2tdJYtMzIU2rdgJpkFhSIdXksGO16nJIOBRGVS7H6UvD0pKa/UH11g6gArK2t4zcrKTE1TP0xkrXmbX1RwtnBKoAloeuoeytHRCRkCGGbtMlHwGy7jfMooQpq5G3/e/xM0y57ldQAAEABJREFUpmvUqKW9dOWHLpgAg13MIERSQhjR1cyIjAHsga4utbi4usHrtKlzK1WqrLve3d0TvTM2NmpLmZWdpV0DzVN4dXZ2ZeaHzc7JLlakPiUXVysrq2VLv9Y9lISUIC7PhzkTvUXM22rVQkaPnDBrzkRot3wyNBzxADMIkVIZ81A/tPehxcMsQ6NNW3Xq4lPJVy6XwwI0p5g1r1+nwIdZW1ujdwbqR4lEcv/+7eoh+S2Bhw/vQY3p5ubOmM97924HB1WHBTCB129cYcwe7JWVlQW/hErePsxe8Qlxjg6GWURDz8fK2rq0IuZtk8bN69ZtMCZ8MvhhjcKagmlE5kYwzsq165euXL0ICxCs+ffW9XbtOpbcBgQHv2/4lYOLAK068JehPQ7+L2IDezv79u06/bRr28WLf6elp0GM5pfD+3r3HggqhBtcs2adHTs2QeMMHCYI1mhtPrgXjRo1Xb16SVJSYmrqm8NH9o8ZO/j334+id6aM8ymjSPcI3bv1ady42aIls6CGQeZGMAHtAf0+2bp1w6zZE+Fq9uzZ76NO3fVu1q/vEDAVu/fuuHnzKlReoTVqT5s2D7EERI7g05csmwN1sbe3z4D+w8BTZoogfrR27fLRYwaCOfywQxdw2OEHwxQtX7b26LGDi5fOfvDgbuXKfvATgvNHbFDG+ZRRpMuszxYNH/HxwUN7Bg4YhsyKGea+WT81ok5L57qtnMu5Pbi9EMr+39ff1a5dD2HMzZ6VkQ4ukr5TWZ4WzCzDwBBGwNBFp9tjCbMMA0MmZveeHXv27NBb5OcfsP6bbcisdOnaqrSizz77vHmzVqgCIIA2YkBA1bOnr6N3oEuXXq1bf6C3SCox/xXYsqXUjhboEkQ8g0BieZzU9M+rQORC2zPBQ6DrEgkILvpVzGMR8cNTgoZASCRdfBR+eErAaLr42L99eGAshhdgIWJ4ARYihhfgSZgwhlGQU4hl8CRMGMNQ52ISxwP2GExJsBAxvMAMQpRZkBILFoYoY8yC3JK0smb/9plBiBZyyesE9lMXYUxDbi7l7GmJ2MYMQ7L8QqwTojIRRoCkvlQqc+n3e7A/FMMMQmzT340kiOOb4xFGaBz//nmNMEfEAWbL13xgTWx6uqpSVbtKfpa5quIptQjdaS0KcnXrmelCHdSiUckBjkxy7pJ7ENoUzOrxndp4JkEUvQ6FKZyLLGv2Kjxoib10czcXbFaYUlrfwUueo/qg6gTV+qf1KJpeufCAqJTtdU9D+y00/4qeUf4XoQu+YpHPlEnysuiYh4qXsZkdh3n5BnOSR9GcGex//+FFXERmXi6lzC1zrCzNDNjRK0SkyelNlFzP3BpC3/oiC3opIkSdLbX5wpGegxT5uPJ9EK13HEtpX6r0o9EGjocpbXu960GmUgvCxlb6Xie3wPpcZfM0pxB5wq5du1JTU8eNG4cEyP79+9euXZuTk2NnZ2djYyOVSmGhUqVKgYGBo0aNQsKhogtx3bp1SqVyypQpSLCMHDny5s2b2kdFVSoV2DCKom7duoWEQ4V+kGnRokX29vaCViEQHh7u7u6ufSuRSECU3t6CGvVdkYU4adKk+vXrDx06FAmcsLCwevXq6dZs1tbWJ06cQIKiggpx0KBBffv27dKlCxIF0ByEdiGzDFVzbm7uqVOnkKCoiELs1KnTvHnzmjZtisRCQEBAmzZtmOXKlStfvnz5zJkzc+bMQcKhYgkRvOMmTZrs2LEjJCQEiYvhw4d7eXnZ2toePaqeWGf58uWtWrWCL3v+vIHTEpuJCuQ1R0ZGgoP5xx9/QHMeVQwgIDB9+nQXF5f58+cjflNRLOKNGzdmzpx5+vTpiqNCpJnhE6KMderUad269fXr7zRJAddUCIsILfcDBw5s3rwZVVTS09NnzJgBUW54RbxE/BZx37590HKvyCoEoLtl06ZNvr6+4Kjdv38f8Q+RW8SNGzcqFAremgHT8+LFC2iiNGjQYMKECYhPiNkiLl26VC6XYxXqAn0wEDSA/qRevXo9ffoU8QbRWsSpU6e2aNGie/fuCKOP6OhoMI3t27eHSALiAeK0iJ988kl3DQhTCn5+ftB6hvjOwIED4+PNP0hZhBYROu5WrFgRGhqKMOXg8ePH0HqBDk9QJDIforKIGRkZzZo127JlC1Zh+QkODobOGHBioI5OSUlBZkI8FjEmJmbIkCEnT55kUq1gDOX27dtgGseMGdOzZ09kckRiEeEiTp48+dy5c1iFRgMdMND/CTX1+PHjs7KykGkRgxAhXr1u3bpDhw4hzDsze/bsQYMGffDBByYe0Sj4qhn67q5evbpy5UqEYZUFCxaAXVy1ahUyCcK2iOCXREREYBVyweLFi6E/MCwsDCocxD0CtojLly93cXEZPXo0wnAJxL0tLS1Bl4hLhGoRwb8LCgrCKjQBUOE0adKkefPm4McgzhCkRfz5559TU1OF9dyu0MnOzp44ceLChQu1D8ewiyAtYlRUFHTbI4wJgdoZtAi/f8QNgpyoUyaTMUnjMaJBkEKUSqVYiCIDCxHDC7AQMbxAkM4KFqL4wBYRwwuwEDG8AAsRwwuwEDG8AAsRwwuwEDG8QKhdfHl5eQgjIrBFxPACLEQML8BCxPACLEQMLxCSEHv06BEVFUWSJDOqvH79+kxmm3///RdhBI6QBj2MGTPG2dkZxEcWAIqsXbs2wggfIQmxQ4cOAQEBumvs7Oz69euHMMJHYMPABg8e7OLion3r6+vbsWNHhBE+AhNiixYttClS5HI5tBoRRhQIb2DskCFDPD09kSbFUteuXRFGFHDoNT/5Nys3u7wdcSVSVpdM7Z6/nRxVC6ve+zH5uE2TNo+uZRbm+C66B/Ou+GGJglWlPMxNEsjaTuYfylV6bExpcCLE3Svi3iRnkySRVyI1fUkl5K8hNFnbi26g0Rih3Qzla4t2Rs3fC2yWFU2cjX5R7MiFbxmBErA5UfLTUSkJ5kmCkMjU5e5+lj3HCSzTrKBhX4jbF0ZZ2ct6Tw60skUC5UVM7t8HEw+vj+8+HmvRRLDcRtw6P9Ldz+ajkZWEq0LA3dei9xTfDAW1e+VzhDEJbArxn1+SKYpo0csNiYKuY31SX+WlxFWUpJnmhU0hPn+c5eAiqpmDLa0kV/58iTDcw6YQszLzpCKbwZqkM9JyEYZ72HRWVHlImadCIkKZi5TZovpGvEWQw8Aw4gMLsSwgGEmQBMJwD5tCJEgksrsGIXGawl6zKWDTWaEpJLK7RkhoUir+3Op8gE2LSBM0ITKLqCIoJYUw3MNq1QxKFF89hpuIJoHlNiK+axjjYLVqppAIG/bYVzEJ7IZvaBHeNmzkTQKrLqE67IbERf4oSQzXsFo10+KziARB4LrZFLDqrCDxWUTcRjQRFSha26NX+/iEOIThJaw6KzwO3yQmJrx58xoZAW4imgRWLaLh4ZvIyKf/++bLocN6d+jYNHzMoCNHD2iLHjy4Ozp8YKfO7382e+L9+3cmTBrx9drlTFFKSvLSZXP7DejcvWe7ZcvnP38ezaz/5fDPPXt/EBMTNWzEx63bNhwxqt/vJ4/B+n9vXe8/sAssDBzUbfVXS1H5IShCZJ1FfIVViwjtegNv24Zvv0pMjJ86dS7cbxAQiNLDw6tJ42bZ2dlz5k0JDqq+eNHqtPTUtf9bkZLyKjCgGuyiUqmmTAvPyFDMmL6gWtXgvft+HPfp0E2bfqrk7SOTyRSK9G/WrZwxbX716jV3/rR15arF9eqG1avbcPmytbPnTt710xFvLwOyvBI4Rm8qWA7fGNrHN3/+8lWrvq1fT62Vbl17g/KuXrsI6y9fOZ+a+iZ89CRPT6+gaiGjRo5PSkpkdrl79xZIds7sJY0bNXV2dhk7ZrK9g+PBg7uZ0ry8vKFDRteoUQvOpcMHncGRj4gwPt21OkSvwt6KKWDVIhrRs0LThw7tvXL1grZ69dJYrMjICFtb24CAqsxKkKmdXX6C5rv3boHlA+0yb0Fwdes0uH3npvaQISGhzAKzC9hI9C5gi1iAlRWH8w6Y01mhKGrWnEl5eblg8OqC1GztoCHIFKUr0q2tbXQ3dnR0YhZAWGD2oAmotxRppIlYBBvEArKyshBnmNMiPvnv0aNH91ev+rZB/UbMGhCZm6s7LFjKLXNzizy1lJyc/zSdi4sr/DSXLf1at1RCShAXQKuXxOMRTQHL4xENMonQCoRXRnlAVNQz+KviHwjLlSpVhmgLeMfQCkQatzczM5PZLDAwCH6a7u6e4J0wayA66OjghDiAILDTbCLY/LmTBt41f78AqVS67+edaelp4H+sW78qrGGTxKQEKGrSuLlEIoE1GRkZsXHPd+783s0tX69gPhs1arp69RJwX0DKh4/sHzN28O+/Hy37syr7+sPruXOn/jPEd8HOislg+VEBg5xmDw/PuXOWPnh4t1v3NhCsGTni065dez98eA/CilD/Tpk8G1yQXn0++HLl5wMGDLOyspZKZcyOEItp2bLd4qWzIY546Je97dp17NnzLfPGgvn8sEOX7Ts27d69HWH4B0GzN6j6u7mRjm6yD4f5IDaIi48Ft9de4/nCSXbu2nL4J2N79eqPTMi+1VF2TmTfqb4Io5mZctasWTVq1EAcwPLoG5qlaAfUuRCmrhoYNGLEp05Ozlu3biAJslWr9sjEiPDRB57CdkCbpWiHg4Pjii/+B8JesHB6ePjA9PS0Det3QH2NTAsN/hduI5oEcwe0Swf66NZ8tQmZFXUPH37A3iTgh6fKQu1+4QfsTQLb0VpxRX/pknN7Y7iB9blvRHXbiDLmfcewCtuPk+KKDGMUbLcRcT2GMQqWLSKuxzDGwapFhG4aUlRKJKUIzwZmGth9VIAgKFHVzZQS4dnATAOe+wbDC9i1iAiDMQ42hSizIKQybkZKmwkLOWFpKUMY7mFTiHJrSV6WqFpUKhVt7YjnuzcFbLqEQbUdUl+XNy+uIMjJotr2cEcY7mFTiA0/tLewIH7bGo9EwYE1MW6VLSVCzm4pIFgOkn2y0E+lpA598/zpvwokWO6cT9u3KtKvhlXvCThNrolgvwHUf6bPwXUJV06+uHQ8SaksEc/RO5yF1jdXSakDX/QfQv/WpR2klPWwjpQQpJQOrOXQpq9I0qwKAk5a4r0meKn/U6AsVYlEdprM8nSxyUkIba56onB0PlG4HPP8+Zcrlm/Y8C1SP7SqftpYI1ydeUF1R8mUHDGjm7O+2PpiKyXIykqyZeuWRMoKocEIYyq4dAltkRViJ5rz+K871UL9rRxMFBsaPXr08ePHEcaECKMjtWvXrrNnz0Ym5KOPPoLX5cuXR0REIAz3CEOIGRkZFGWGCOXMmTOXLjVkPkWMsQhAiOnp6Z07dybNMQeNRCLZsWMHLFy8eBFhuEQAQnz8+HGLFi2QWXF1dR08GPsuHCKA/quGGpBZCQoKmjNnTnJyslQqdXBwQBi2EYBFjIuLy1dEWsgAABAASURBVM7ORuamevXqLi4u4Lvs3bsXYdhGAELs1asX2CHEDxo0aBAbGxsTE4MwrMJ3IUZHR3fs2JE/QgSmT59ua2v79OlThULA3Zh8g+9C9PPzW7hwIeIZzs7OPj4+4Mu/fPkSYdiA70IEwwMuAuIfcrn83Llzz549KzbFMsY4+C7EKVOm5OTkIL7SuHFj6DmfMWMGwrwbvBZiWloaBG68vXk9FgtMY6dOnXbt2oUw7wCv44j29vYLFixAvKd169bQCQkLly5deu+99xDGcHhtEaFPJTIyEgkBGxt1Vpjffvvt9OnTCGM4vBbiihUrhBUiWbx4sUyGn/ozBv4KEZyA4ODgWrVqIUHBdIt/+umnSUlJCFNu+CtEgiBmzZqFhMmqVavWrFmDMOWGv0K8f//+zZs3kTCxtrb+8ssvYQGP9C4n/BXi9u3bIXyDBI6Tk9OkSZMQ5m3wN3xTv359CBcjgdO0aVNm2Bj0D7m4uCBMKfBXiAMGDECiIDRUnT/6zJkz4FB3794dYfTB06r54cOHJ06cQCKiT58+9+7dwx3TpcFTIf7zzz9IdMybN08ikZw7dw4JE39/fzh/xA08FSK0DiGIiEQH3EiIjPbt2xcJkD///LNKlSqIG3jaRqxTpw4SKeCyfPHFF9nZ2ZaWlkg4xMTEeHp6WlhYIG7gqUWEpv3Vq1eRSAkMDJTL5T/88AMSDhEREdWqVUOcwVMhPtCAxAv0G/Xr169Vq1ZIIPz3339Vq1ZFnMHTqrl169bctYt5AhjFs2fPIs08FszgHT4DFrFTp06IM3hqESH2FhISgsQOoZmMb9u2bXFxcYjfgEWsiFXz+fPnRRnB0cuECROWL1+OeAy4Vq9evfLx8UGcwVMhPnnyBMK/qMKwfv16pKn+EC+BE+O0gYh420Zs1qxZXp6o5oUvD6dPn05PT69Xrx7iGVzXy4i3FhGi2TVr1kQVjPDw8EuXLiH+wXXsBvFWiNevX4c4Pqp4jBs3DmnCqIhPgBAh9om4hKdCfPbsmXBHxb478fHxf//9N+INFbdqDgsLa9++PaqoDBo0KCsrC/GDFy9eQG+kvb094hKeChE613nYZjclHTp0gNfNmzcjc2OCBiLirRDv3r3766+/ogqPl5fXyZMnkVnhunOPgadCjI2NvXLlCqrwdO3aldMwcnkwQRAR8VaItWrV6tKlC8IUPGkwceJEZCZM4KkABE3jrPMC4OrVq9DJph12AJZSLpfv378fcQ84jteuXUMcw1OLCL/CgwcPIkwBjTRAvwss9+zZE+I74MxeuHABcYwJIogMPBViUlJSxRn0UE5cXV2tra3BPjEzeCsUilOnTiGOMU29jHgrRPjyffr0QZiifPzxx9qmFEEQEFtgbCR3mCZ2g3grRA8Pj2bNmiFMUaKjo3XfJiYmcl1vmMZlRrwVItQ+eA7WYoCDIpPJdJ1L6H3hOspomiAi4q0QX79+zQyjx2g5evTozJkz33///cqVK0OHGyiSJEnolIeYK+KG1NTUnJwcd3d3xD08Dd+kpKTcvn27devW0CqCa3HkyBGEKeDNmzeHv03IeE3SKpKmCe16de51zTtak10d5adhJ7RvmYztuguaxOlEkZ0LVxVBpxzRFCJ0LZjODrqbASRJkBLC1l7aI9zX1g2VAb8Gxi5YsODYsWPwQy9Icq/+0bu5uSGMDsc3p9NKm4ZtHarWdFBRqnzJIY1B0WgiXwwgCpJAFF2oSeYtULBAk4hg0g8X6rZAoFoDRRRITf2q2QYVLOS/5n944UG0WEjSEnLvXEre+eXTEUsCLaxK/VL8EuKQIUPAEMbFxTG/V0aLgps0llO2LYy2c7TsOsajYAXfn3W0CrBoH+AFC9sXRXYb7e8ZQOjdjF9tRGgXF5uKDoJnUDsjjIbzh1MoFf3hcA8kQHxD7E78UGoOQ945K4MHD/b19WWWKYoKCgoye45c/hB5X+HkIUfCpHkP1+wMJVLpL+WdEMElbNGiBeNCOTk5iWaWRFbIyVZZ2ws6awEdF6V/Yj4+hm/69u1bpUoVMIfQy4nz5+iSl0Pl5Qh4hkWVCtFK/SbxXZ2VxGe5EbcVyYlZmQpKRdG0CvxcgqJoxtlQu70SpHbsQPA0ofGFC7wuJqyg44ShAs8M1rSsMq+eazo0EHcujyY1xRRV0LVFqh0zimK8mcLdCZ1tmGAFKghtyCygVGJtL3HxtKjTwsnGQQBZqkWJ+v7q91WMFeKja4rrf6akJufB7ZZISJrUOLgEQapjAVrvnVJrUSfGpN1dEwegSpxUYfDAQuLo6uhIK1FGKqX5AkW2pAiaLBr91IbKtG9ptWK12oWTU715lRfzKOPGmRQ4YffKlm0/9nTyEt70OjQikKApJWxtsBAfXlX8c/iFMpeW21p4B7s6+dgiofEyIvXNK8WuVZGWNpIhn/lb2Arp1pKCHj9aNNyti2FC3PlFTFqK0tHDtlJNAU+Q71bVAf5gIfJawub5EZWq2PScyOsEqLrQgjaIRGkG0RBnZeP0Z3k5ZGhbP0GrUJcqYV61Pgh4EZ/z/bwohOEemmmr6aO8Qlw/NcI1wCmgiRcSHSEtfWVWVlvnRSMhQAi5jViGs1IuIW6Y/rRaA1+3Ktw+Ym1G/Oq7Sq0tNs96hngOodsHLFCM7eLb+NlTz6rOcmeRz9/qV8/dytFy+yJ+20WBi5CmS23ivkWIO5fFWFjJXfxEawt18a3jkZtDn9iO09tyBUEUHZujQ1lCvH9RkfZaGdhYhO3C0ghuVvnZXX6nKhd29KZUyhLi+WMvnDyFFyZ8J0hk7WCxe+VzxEsk0KskFbizUkpRqUK8fyldlUt7h1a4hJoBDb1TEnMQL1FBb5RKwCaRRsjgNuKNP1Ms7fk74ujW3T+nz2+syHiNWIdEUgvJr98lIIyG7j3b/bjze8QGahWSBnrN6W+Urv5OqEJi62ydGJ2NRMGixbNO/MaXJ37UxpwyxFmJvpcF6rV3F1KyOBZxreKUk00hUfD4sTASeOnva35yO00i5XCsVFTMnT/Ofv889oGtjVP14OYftB5paalOvXTh8v5Tf20bO3zjj3tnJ7145uVRtUXT/mH1OzN7/fr7uuu3T8gtrOvV7uDu6os4w9JWHTSNupvlX8sK8QlCQhMSA+5L67bqwe2rVi/ZuOnrY0fOwfKFC3/98OOW6JhIBwfHqlWDJ034zMPDk9m4jCIGiAIePLTn5Mlfn8dG+/lWadiwyfBhYw1KEGaws5KaopRIuYpgv0p+vnnHhLy8nPGjvx864MuEpP82bhurUimhSCKVZWWlHz6++uPuc1Ytvly7ZpufDy99/SYRii5ePXjx6oGeH82YFL7dxcn71NmtiEtICRn/jHe1M60iaJUBpvr3E+pZmmZMn8+o8PqNKws+n/HBBx/9vPfEwvkrkpIS1n6zgtmyjCIthw7t/WnXtt69Buzd/WuXLr2Onzi8d9+PyBCKjdbTRb8Qc7NV3HVp3rz9u1Qi+6T/lx5u/p7uAX26zY1LeHzv4V9MqUqV1771SL/KtSD42bDuR/ArjEt4AuvPX/q5dmhbkKa1tT3YyKoBHD/IQtOKdJ76zkazbfvGFu+3ASWBzQsNrT1u7NTLl88/0tTdZRRpuX3nZnBwjQ4dOjs6OnX+qMeG9TsaNzJsWhhmNLTeolLsvIrDuCnUy5V9atjYODJvnZ28XJx9IqNvaTfwrRTKLFhbqXt0srLTQY6vUp57uFfRbuPjzW2mPkLzGDnveDfr8OzZfyEhodq3wUE14PXRo/tlF2mpWbPOjRtXVq5a/PvJY6lpqZW8fapWDUIGYth4RKmcROmlPG71zmRlK57HPYDgi+7KtPRk7TJR4mSzczIoSiWXW2vXWFhw23oDEVrb8e8xpXcwDwqFIicnRy4vdECtrdXXMzMzo4wi3SOAvbS2trlw8a8vVy6SSqWtWrUPHzXR1dWA6Q9oZOAIbTsnWUqSEnGDnZ1LFb+6HdqM1l1pY+NQxi6WchuSlOTlFTbacnIzEZfQFO3qzbswqvp5HcJIq2hpqdZZdnZh1owMjc5cnF3LKNI9AkmSUCPDX1TUs5s3r+74cUtGhuKLpV+jcpM/J4U+9AvRN8Sauy5Xb49qN26fCPCvB1+MWZP44pmbS1leMFx9J0evqJi7LQvaJA8fczhZKqWCP6p6Y951b0Jrwei5isCGBQdVv3//jnYNsxwQWK2MIt0jgL8cFFS9SpVAf/8A+EtXpB8/8QsyBJo2sGcltIkdRVE5Ck7SMkJEBg5+9Levc3OzX7yM/vXk+q/WD0hIektizjo12919cBY6VGD5zD8/RsdymLs08UkyKRH4M0oa5HK5m5v79euX/711XalU9uje9/yFcwcP7klLT4M1325cU79eWLWqwbBlGUVaTp/5HTzrixf/hgYiuDL/nD9TM7QOMohSB9+U/syKpbU04UmKf332Z7cAt3f6+N1n/9m5dtPQFy+jfH1C+3Sf+1bno13LYRkZrw+f+Oqnn+dCzd614+Td+xdwNJVZ2osMFy+hTqhQjIEDhm/fsenqtYt7dv8K0ZmXr17s279z/bdfQYywYYMmo0aOZzYro0jLtKnz1m9YPXf+VFh2dnaBOrpP70HIEMoYoV3qtHR/HXx571JaaFt/VPG4dyqy33RfV28LxDM2znxaqapV676CedSrGDs+j+gxppJPsB5Hs9QwfctebtBgT4nhdopmHhJ1M8nCUsJDFYqbsh4nrVbX7umdZGdfO72lb1KTVq/XPzGNldw2K0e/r+PpFjB+9HeIPeYta1taEfTWSCR6vqC/b+2Rg0v19RTJmV1GVEK8hFBPZCDOh6fKEmKHIR6bPsuIvZfso+/5UXs7t7lTD+vdMU+ZK5OWYlHYvo6lnQMqXYgQCSptl6cX4x3dLfxC+dXFrAXqKEEnaCrjcdK3PGA/5ouA9TMi9AoRgi9WVvqNpSlvY2nnYASvYtJzsnJHLDFFfhvjUE/xI/QpR0rhbUM5JKhlT48HZ6KQ2IHYYdKT5HGr+atCpInDCf1xUuOfa67V3K7XeJ97p6KQeMl4lfPgTOSnK3mtQnHwTjM9ePjJ2w9wh6BG0n9vkOiIvpkU+W/8+DVVeT8dtRrBzwZWCuWdhCm4oV3lENsfFkemJil861WytBHD5XgTmxH/5JVUhtQqFAiEwJ8nZWE2MGtbYuzKgCObEp5ejpbKJE4+Du4BQn3wPv5eStqLdPBBqzdyaP2xK8KYBMKILr7S6DZG/bz94W/jk2Jev4xMkUhJUiaRW0olMlIna0fpZ0G8bSwTkT+XrOaUC54/VP+OqPzhvYW767zRTfVR4viEhKSUtDJXlZuVC6+UipLLpYG17doPxhlcTEoZd97IGWO7j1P3MiVF5936O+VlbHZ2Zm5WOkWppy4u3IaZw1j7lijIS6ObMEZbpLucH2+ii2eXKb6ANEmBqML1RNH8R9pXqUwdBialhI2dxDvApnkYSYnRAAABTklEQVQXNwtrhOEV7zSHtoefrMNgQeb8wPANfmWewpQNKSM4fbqSa0gJSZQSqMFCFBKWFlJVrpCFSNDObvrH1+FED0LCrbI8OUmoU1DcOvtaakFYOesvxUIUEp2Ge+RmqZ7eEqQWH99IDW1U6iQ2PM3XjCmDzTOeVQqxa9lbMLGnp7cyL59IbN3LLbhRqSNUsBAFyfbPo7MylRIJqczRCdyq02/RNJUfxMoPdZWMsBZNy1WYjlnfSu0BCwNnEs0T3yVDbxIaqYhiH0fK1McgCSK4oX3L3mVNcYiFKFQUqerKLidD5wE3QpMQvECZBZFUktbEWpnk1+oCktBMH1CQlosg8hPaEzRdfN/ClYU5xyUkrY4YF0iNIDRvNAJV6ehSsySREK4+1oG13z4wEAsRwwtw+AbDC7AQMbwACxHDC7AQMbwACxHDC7AQMbzg/wAAAP//K3p4RAAAAAZJREFUAwDHZPXhrOAZOwAAAABJRU5ErkJggg==", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from IPython.display import display, Image\n", "\n", @@ -319,7 +357,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], @@ -350,10 +388,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:25:55 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "17:25:57 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "17:26:07 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "\n", @@ -374,10 +422,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "41ba0253-5199-4d29-82ae-258cbbebddb4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "432" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "messages = result[\"messages\"]\n", "count_tokens_approximately(messages)" @@ -394,10 +453,61 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "26c53429-90ba-4d0b-abb9-423d9120ad26", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Update from node: pre_model_hook\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What's it known for?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is known for a variety of iconic landmarks, cultural institutions, and vibrant neighborhoods. Some of the most notable features include:\n", + "\n", + "1. **Statue of Liberty**: A symbol of freedom and democracy, located on Liberty Island.\n", + "2. **Times Square**: Known for its bright lights, Broadway theaters, and bustling atmosphere.\n", + "3. **Central Park**: A large public park offering a natural oasis amidst the urban environment.\n", + "4. **Empire State Building**: An iconic skyscraper offering panoramic views of the city.\n", + "5. **Broadway**: Famous for its world-class theater productions and musicals.\n", + "6. **Wall Street**: The financial hub of the city, home to the New York Stock Exchange.\n", + "7. **Museums**: Including the Metropolitan Museum of Art, Museum of Modern Art (MoMA), and the American Museum of Natural History.\n", + "8. **Diverse Cuisine**: A melting pot of cultures, offering a wide range of international foods.\n", + "9. **Cultural Diversity**: Known for its diverse population and vibrant cultural scene.\n", + "10. **Fashion**: A global fashion capital, hosting events like New York Fashion Week.\n", + "\n", + "These are just a few highlights of what makes New York City a unique and exciting place to visit or live.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "where can i find the best bagel?\n", + "\n", + "\n", + "\n", + "17:26:17 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: agent\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Finding the \"best\" bagel in New York City can be subjective, as it often depends on personal taste preferences. However, several bagel shops are frequently mentioned as top contenders:\n", + "\n", + "1. **Ess-a-Bagel**: Known for its large, chewy bagels and a wide variety of spreads.\n", + "2. **Russ & Daughters**: Famous for its traditional bagels and high-quality smoked fish.\n", + "3. **Absolute Bagels**: Popular for its fresh, fluffy bagels and authentic taste.\n", + "4. **Murray’s Bagels**: Offers a classic New York bagel experience with no toasting policy.\n", + "5. **Tompkins Square Bagels**: Known for its creative cream cheese flavors and hearty bagels.\n", + "6. **Bagel Hole**: Celebrated for its smaller, denser bagels with a crispy crust.\n", + "7. **Black Seed Bagels**: Offers a unique Montreal-style bagel with a New York twist.\n", + "\n", + "These spots are scattered throughout the city, so you can find a great bagel in various neighborhoods. It's always a good idea to try a few different places to find your personal favorite!\n", + "\n", + "\n", + "\n" + ] + } + ], "source": [ "inputs = {\"messages\": [(\"user\", \"where can i find the best bagel?\")]}\n", "print_stream(graph.stream(inputs, config=config, stream_mode=\"updates\"))" @@ -413,7 +523,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "7ecfc310-8f9e-4aa0-9e58-17e71551639a", "metadata": {}, "outputs": [], @@ -442,10 +552,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "48c2a65b-685a-4750-baa6-2d61efe76b5f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:26:17 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "17:26:17 redisvl.index.index INFO Index already exists, not overwriting.\n", + "17:26:17 redisvl.index.index INFO Index already exists, not overwriting.\n", + "17:26:17 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_387/2986813568.py:27: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" + ] + } + ], "source": [ "from langchain_core.messages import RemoveMessage\n", "from langgraph.graph.message import REMOVE_ALL_MESSAGES\n", @@ -492,10 +621,69 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "831be36a-78a1-4885-9a03-8d085dfd7e37", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:26:30 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "17:26:39 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: pre_model_hook\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What's it known for?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is famous for its bagels, and there are several places renowned for serving some of the best. Here are a few top spots where you can find delicious bagels in NYC:\n", + "\n", + "1. **Ess-a-Bagel**: Known for their large, chewy bagels with a variety of spreads and toppings.\n", + "2. **Russ & Daughters**: A classic spot offering traditional bagels with high-quality smoked fish and cream cheese.\n", + "3. **H&H Bagels**: Famous for their fresh, hand-rolled bagels with a perfect balance of crust and chewiness.\n", + "4. **Murray’s Bagels**: Offers a wide selection of bagels and toppings, known for their authentic New York taste.\n", + "5. **Absolute Bagels**: A favorite on the Upper West Side, known for their fresh and flavorful bagels.\n", + "6. **Tompkins Square Bagels**: Offers creative cream cheese flavors and a cozy atmosphere.\n", + "7. **Bagel Hole**: Known for their smaller, denser bagels with a crispy crust.\n", + "\n", + "Each of these places has its own unique style and flavor, so it might be worth trying a few to find your personal favorite!\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "where can i find the best bagel?\n", + "\n", + "\n", + "\n", + "17:26:47 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: agent\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is famous for its bagels, and there are several places renowned for serving some of the best. Here are a few top spots where you can find delicious bagels in NYC:\n", + "\n", + "1. **Ess-a-Bagel**: Known for their large, chewy bagels with a variety of spreads and toppings. Locations in Midtown and Gramercy.\n", + "\n", + "2. **Russ & Daughters**: A historic appetizing store on the Lower East Side, famous for its bagels with lox and cream cheese.\n", + "\n", + "3. **Absolute Bagels**: Located on the Upper West Side, this spot is popular for its fresh, fluffy bagels.\n", + "\n", + "4. **Murray’s Bagels**: Known for their traditional, hand-rolled bagels. Located in Greenwich Village.\n", + "\n", + "5. **Tompkins Square Bagels**: Offers a wide range of bagels and creative cream cheese flavors. Located in the East Village.\n", + "\n", + "6. **Bagel Hole**: A small shop in Park Slope, Brooklyn, known for its classic New York-style bagels.\n", + "\n", + "7. **Leo’s Bagels**: Located in the Financial District, offering a variety of bagels and toppings.\n", + "\n", + "Each of these places has its own unique style and flavor, so it might be worth trying a few to find your personal favorite!\n", + "\n", + "\n", + "\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "\n", @@ -523,7 +711,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "394f72f8-f817-472d-a193-e01509a86132", "metadata": {}, "outputs": [], @@ -546,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "aa6e4bdf", "metadata": {}, "outputs": [], @@ -567,10 +755,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "b9540c1c-2eba-42da-ba4e-478521161a1f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:26:49 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "17:26:49 redisvl.index.index INFO Index already exists, not overwriting.\n", + "17:26:49 redisvl.index.index INFO Index already exists, not overwriting.\n", + "17:26:49 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_387/3065461601.py:33: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" + ] + } + ], "source": [ "# highlight-next-line\n", "from langmem.short_term import SummarizationNode\n", @@ -618,10 +825,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "8eccaaca-5d9c-4faf-b997-d4b8e84b59ac", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "17:26:52 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "17:26:54 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "17:26:58 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" + ] + }, + { + "ename": "AttributeError", + "evalue": "'dict' object has no attribute 'summarized_message_ids'", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[16]\u001b[39m\u001b[32m, line 7\u001b[39m\n\u001b[32m 4\u001b[39m result = graph.invoke(inputs, config=config)\n\u001b[32m 6\u001b[39m inputs = {\u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m: [(\u001b[33m\"\u001b[39m\u001b[33muser\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mWhat\u001b[39m\u001b[33m'\u001b[39m\u001b[33ms it known for?\u001b[39m\u001b[33m\"\u001b[39m)]}\n\u001b[32m----> \u001b[39m\u001b[32m7\u001b[39m result = \u001b[43mgraph\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 9\u001b[39m inputs = {\u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m: [(\u001b[33m\"\u001b[39m\u001b[33muser\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mwhere can i find the best bagel?\u001b[39m\u001b[33m\"\u001b[39m)]}\n\u001b[32m 10\u001b[39m print_stream(graph.stream(inputs, config=config, stream_mode=\u001b[33m\"\u001b[39m\u001b[33mupdates\u001b[39m\u001b[33m\"\u001b[39m))\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/main.py:3050\u001b[39m, in \u001b[36mPregel.invoke\u001b[39m\u001b[34m(self, input, config, context, stream_mode, print_mode, output_keys, interrupt_before, interrupt_after, durability, **kwargs)\u001b[39m\n\u001b[32m 3047\u001b[39m chunks: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any] | Any] = []\n\u001b[32m 3048\u001b[39m interrupts: \u001b[38;5;28mlist\u001b[39m[Interrupt] = []\n\u001b[32m-> \u001b[39m\u001b[32m3050\u001b[39m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 3051\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 3052\u001b[39m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3053\u001b[39m \u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3054\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m=\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mupdates\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 3055\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m \u001b[49m\u001b[43m==\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\n\u001b[32m 3056\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3057\u001b[39m \u001b[43m \u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3058\u001b[39m \u001b[43m \u001b[49m\u001b[43moutput_keys\u001b[49m\u001b[43m=\u001b[49m\u001b[43moutput_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3059\u001b[39m \u001b[43m \u001b[49m\u001b[43minterrupt_before\u001b[49m\u001b[43m=\u001b[49m\u001b[43minterrupt_before\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3060\u001b[39m \u001b[43m \u001b[49m\u001b[43minterrupt_after\u001b[49m\u001b[43m=\u001b[49m\u001b[43minterrupt_after\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3061\u001b[39m \u001b[43m \u001b[49m\u001b[43mdurability\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdurability\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3062\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3063\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 3064\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m \u001b[49m\u001b[43m==\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\n\u001b[32m 3065\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[43m==\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m2\u001b[39;49m\u001b[43m:\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/main.py:2633\u001b[39m, in \u001b[36mPregel.stream\u001b[39m\u001b[34m(self, input, config, context, stream_mode, print_mode, output_keys, interrupt_before, interrupt_after, durability, subgraphs, debug, **kwargs)\u001b[39m\n\u001b[32m 2631\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m task \u001b[38;5;129;01min\u001b[39;00m loop.match_cached_writes():\n\u001b[32m 2632\u001b[39m loop.output_writes(task.id, task.writes, cached=\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[32m-> \u001b[39m\u001b[32m2633\u001b[39m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrunner\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtick\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2634\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtasks\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m.\u001b[49m\u001b[43mwrites\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2635\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mstep_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2636\u001b[39m \u001b[43m \u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m=\u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2637\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43maccept_push\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2638\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 2639\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# emit output\u001b[39;49;00m\n\u001b[32m 2640\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01myield from\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_output\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2641\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msubgraphs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mqueue\u001b[49m\u001b[43m.\u001b[49m\u001b[43mEmpty\u001b[49m\n\u001b[32m 2642\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 2643\u001b[39m loop.after_tick()\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_runner.py:167\u001b[39m, in \u001b[36mPregelRunner.tick\u001b[39m\u001b[34m(self, tasks, reraise, timeout, retry_policy, get_waiter, schedule_task)\u001b[39m\n\u001b[32m 165\u001b[39m t = tasks[\u001b[32m0\u001b[39m]\n\u001b[32m 166\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m167\u001b[39m \u001b[43mrun_with_retry\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 168\u001b[39m \u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 169\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 170\u001b[39m \u001b[43m \u001b[49m\u001b[43mconfigurable\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\n\u001b[32m 171\u001b[39m \u001b[43m \u001b[49m\u001b[43mCONFIG_KEY_CALL\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpartial\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 172\u001b[39m \u001b[43m \u001b[49m\u001b[43m_call\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 173\u001b[39m \u001b[43m \u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 174\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m=\u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 175\u001b[39m \u001b[43m \u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m=\u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 176\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 177\u001b[39m \u001b[43m \u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 178\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 179\u001b[39m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 180\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 181\u001b[39m \u001b[38;5;28mself\u001b[39m.commit(t, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m 182\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_retry.py:42\u001b[39m, in \u001b[36mrun_with_retry\u001b[39m\u001b[34m(task, retry_policy, configurable)\u001b[39m\n\u001b[32m 40\u001b[39m task.writes.clear()\n\u001b[32m 41\u001b[39m \u001b[38;5;66;03m# run the task\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m42\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43mproc\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43minput\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 43\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m ParentCommand \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[32m 44\u001b[39m ns: \u001b[38;5;28mstr\u001b[39m = config[CONF][CONFIG_KEY_CHECKPOINT_NS]\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:656\u001b[39m, in \u001b[36mRunnableSeq.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 654\u001b[39m \u001b[38;5;66;03m# run in context\u001b[39;00m\n\u001b[32m 655\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m set_config_context(config, run) \u001b[38;5;28;01mas\u001b[39;00m context:\n\u001b[32m--> \u001b[39m\u001b[32m656\u001b[39m \u001b[38;5;28minput\u001b[39m = \u001b[43mcontext\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstep\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 657\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 658\u001b[39m \u001b[38;5;28minput\u001b[39m = step.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:400\u001b[39m, in \u001b[36mRunnableCallable.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 398\u001b[39m run_manager.on_chain_end(ret)\n\u001b[32m 399\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m400\u001b[39m ret = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 401\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.recurse \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, Runnable):\n\u001b[32m 402\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m ret.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langmem/short_term/summarization.py:832\u001b[39m, in \u001b[36mSummarizationNode._func\u001b[39m\u001b[34m(self, input)\u001b[39m\n\u001b[32m 830\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_func\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any] | BaseModel) -> \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any]:\n\u001b[32m 831\u001b[39m messages, context = \u001b[38;5;28mself\u001b[39m._parse_input(\u001b[38;5;28minput\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m832\u001b[39m summarization_result = \u001b[43msummarize_messages\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 833\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 834\u001b[39m \u001b[43m \u001b[49m\u001b[43mrunning_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrunning_summary\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 835\u001b[39m \u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 836\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 837\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 838\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 839\u001b[39m \u001b[43m \u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 840\u001b[39m \u001b[43m \u001b[49m\u001b[43minitial_summary_prompt\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43minitial_summary_prompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 841\u001b[39m \u001b[43m \u001b[49m\u001b[43mexisting_summary_prompt\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mexisting_summary_prompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 842\u001b[39m \u001b[43m \u001b[49m\u001b[43mfinal_prompt\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfinal_prompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 843\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 844\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._prepare_state_update(context, summarization_result)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langmem/short_term/summarization.py:445\u001b[39m, in \u001b[36msummarize_messages\u001b[39m\u001b[34m(messages, running_summary, model, max_tokens, max_tokens_before_summary, max_summary_tokens, token_counter, initial_summary_prompt, existing_summary_prompt, final_prompt)\u001b[39m\n\u001b[32m 337\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34msummarize_messages\u001b[39m(\n\u001b[32m 338\u001b[39m messages: \u001b[38;5;28mlist\u001b[39m[AnyMessage],\n\u001b[32m 339\u001b[39m *,\n\u001b[32m (...)\u001b[39m\u001b[32m 348\u001b[39m final_prompt: ChatPromptTemplate = DEFAULT_FINAL_SUMMARY_PROMPT,\n\u001b[32m 349\u001b[39m ) -> SummarizationResult:\n\u001b[32m 350\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Summarize messages when they exceed a token limit and replace them with a summary message.\u001b[39;00m\n\u001b[32m 351\u001b[39m \n\u001b[32m 352\u001b[39m \u001b[33;03m This function processes the messages from oldest to newest: once the cumulative number of message tokens\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 443\u001b[39m \u001b[33;03m ```\u001b[39;00m\n\u001b[32m 444\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m445\u001b[39m preprocessed_messages = \u001b[43m_preprocess_messages\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 446\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 447\u001b[39m \u001b[43m \u001b[49m\u001b[43mrunning_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrunning_summary\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 448\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 449\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 450\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 451\u001b[39m \u001b[43m \u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 452\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 453\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m preprocessed_messages.existing_system_message:\n\u001b[32m 454\u001b[39m messages = messages[\u001b[32m1\u001b[39m:]\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langmem/short_term/summarization.py:145\u001b[39m, in \u001b[36m_preprocess_messages\u001b[39m\u001b[34m(messages, running_summary, max_tokens, max_tokens_before_summary, max_summary_tokens, token_counter)\u001b[39m\n\u001b[32m 143\u001b[39m total_summarized_messages = \u001b[32m0\u001b[39m\n\u001b[32m 144\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m running_summary:\n\u001b[32m--> \u001b[39m\u001b[32m145\u001b[39m summarized_message_ids = \u001b[43mrunning_summary\u001b[49m\u001b[43m.\u001b[49m\u001b[43msummarized_message_ids\u001b[49m\n\u001b[32m 146\u001b[39m \u001b[38;5;66;03m# Adjust the summarization token budget to account for the previous summary\u001b[39;00m\n\u001b[32m 147\u001b[39m max_tokens_to_summarize -= token_counter(\n\u001b[32m 148\u001b[39m [SystemMessage(content=running_summary.summary)]\n\u001b[32m 149\u001b[39m )\n", + "\u001b[31mAttributeError\u001b[39m: 'dict' object has no attribute 'summarized_message_ids'", + "During task with name 'pre_model_hook' and id '38a6ec6c-13cc-a2ff-ed87-b517db665815'" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "inputs = {\"messages\": [(\"user\", \"What's the weather in NYC?\")]}\n", @@ -660,9 +898,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/langgraph/checkpoint/redis/jsonplus_redis.py b/langgraph/checkpoint/redis/jsonplus_redis.py index 2fca376..5d1cf35 100644 --- a/langgraph/checkpoint/redis/jsonplus_redis.py +++ b/langgraph/checkpoint/redis/jsonplus_redis.py @@ -1,3 +1,4 @@ +import dataclasses import logging from typing import Any @@ -72,6 +73,8 @@ def _preprocess_interrupts(self, obj: Any) -> Any: This prevents false positives where user data with {value, id} fields could be incorrectly deserialized as Interrupt objects. + + Also handles dataclass instances to preserve type information during serialization. """ from langgraph.types import Interrupt @@ -82,6 +85,24 @@ def _preprocess_interrupts(self, obj: Any) -> Any: "value": self._preprocess_interrupts(obj.value), "id": obj.id, } + elif isinstance(obj, set): + # Handle sets by converting to list for JSON serialization + # Will be reconstructed back to set on deserialization + return { + "lc": 2, + "type": "constructor", + "id": ["builtins", "set"], + "kwargs": {"__set_items__": [self._preprocess_interrupts(item) for item in obj]}, + } + elif dataclasses.is_dataclass(obj) and not isinstance(obj, type): + # Handle dataclass instances (like langmem's RunningSummary) + # Convert to LangChain constructor format to preserve type information + # Recursively process the dataclass fields + processed_dict = { + k: self._preprocess_interrupts(v) + for k, v in dataclasses.asdict(obj).items() + } + return self._encode_constructor_args(type(obj), kwargs=processed_dict) elif isinstance(obj, dict): return {k: self._preprocess_interrupts(v) for k, v in obj.items()} elif isinstance(obj, (list, tuple)): @@ -144,6 +165,51 @@ def loads_typed(self, data: tuple[str, bytes]) -> Any: # Unknown type, try parent return super().loads_typed(data) + def _reconstruct_from_constructor(self, obj: dict[str, Any]) -> Any: + """Reconstruct an object from LangChain constructor format. + + This handles objects that were serialized using _encode_constructor_args + but are not LangChain objects (e.g., dataclasses, regular classes, sets). + + Args: + obj: Dict with 'lc', 'type', 'id', and 'kwargs' keys + + Returns: + Reconstructed object instance + + Raises: + Exception: If object cannot be reconstructed + """ + # Get the class from the id field + id_parts = obj.get("id", []) + if not id_parts or len(id_parts) < 2: + raise ValueError(f"Invalid constructor format: {obj}") + + # Import the module and get the class + module_path = ".".join(id_parts[:-1]) + class_name = id_parts[-1] + + try: + import importlib + + module = importlib.import_module(module_path) + cls = getattr(module, class_name) + except (ImportError, AttributeError) as e: + raise ValueError( + f"Cannot import {class_name} from {module_path}: {e}" + ) from e + + # Get the kwargs and recursively revive nested objects + kwargs = obj.get("kwargs", {}) + revived_kwargs = {k: self._revive_if_needed(v) for k, v in kwargs.items()} + + # Special handling for sets + if cls is set and "__set_items__" in revived_kwargs: + return set(revived_kwargs["__set_items__"]) + + # Reconstruct the object + return cls(**revived_kwargs) + def _revive_if_needed(self, obj: Any) -> Any: """Recursively apply reviver to handle LangChain and LangGraph serialized objects. @@ -156,6 +222,9 @@ def _revive_if_needed(self, obj: Any) -> Any: It also handles LangGraph Interrupt objects which serialize to {"value": ..., "resumable": ..., "ns": ..., "when": ...} and must be reconstructed to prevent AttributeError when accessing Interrupt attributes. + Additionally, it handles dataclass objects (like langmem's RunningSummary) that are serialized + using the LangChain constructor format but need special reconstruction logic. + Args: obj: The object to potentially revive, which may be a dict, list, or primitive. @@ -165,10 +234,23 @@ def _revive_if_needed(self, obj: Any) -> Any: if isinstance(obj, dict): # Check if this is a LangChain serialized object if obj.get("lc") in (1, 2) and obj.get("type") == "constructor": - # Use parent's reviver method to reconstruct the object + # First try to use parent's reviver method to reconstruct LangChain objects # This converts {'lc': 1, 'type': 'constructor', ...} back to # the actual LangChain object (e.g., HumanMessage, AIMessage) - return self._reviver(obj) + revived = self._reviver(obj) + + # If reviver returns a dict unchanged, it means it couldn't reconstruct it + # This happens with dataclasses or other non-LangChain objects + if isinstance(revived, dict) and revived.get("lc") in (1, 2): + # Try to reconstruct it manually + try: + return self._reconstruct_from_constructor(obj) + except Exception: + # If reconstruction fails, fall through to recursive dict processing + pass + else: + # Reviver successfully reconstructed the object + return revived # Check if this is a serialized Interrupt object with type marker # LangGraph 1.0+: Interrupt objects serialize to {"__interrupt__": True, "value": ..., "id": ...} diff --git a/poetry.lock b/poetry.lock index a527d57..4b921a0 100644 --- a/poetry.lock +++ b/poetry.lock @@ -39,6 +39,33 @@ files = [ {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"}, ] +[[package]] +name = "anthropic" +version = "0.73.0" +description = "The official Python library for the anthropic API" +optional = false +python-versions = ">=3.9" +groups = ["dev"] +files = [ + {file = "anthropic-0.73.0-py3-none-any.whl", hash = "sha256:0d56cd8b3ca3fea9c9b5162868bdfd053fbc189b8b56d4290bd2d427b56db769"}, + {file = "anthropic-0.73.0.tar.gz", hash = "sha256:30f0d7d86390165f86af6ca7c3041f8720bb2e1b0e12a44525c8edfdbd2c5239"}, +] + +[package.dependencies] +anyio = ">=3.5.0,<5" +distro = ">=1.7.0,<2" +docstring-parser = ">=0.15,<1" +httpx = ">=0.25.0,<1" +jiter = ">=0.4.0,<1" +pydantic = ">=1.9.0,<3" +sniffio = "*" +typing-extensions = ">=4.10,<5" + +[package.extras] +aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.9)"] +bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"] +vertex = ["google-auth[requests] (>=2,<3)"] + [[package]] name = "anyio" version = "4.11.0" @@ -638,6 +665,41 @@ docs = ["myst-parser (==0.18.0)", "sphinx (==5.1.1)"] ssh = ["paramiko (>=2.4.3)"] websockets = ["websocket-client (>=1.3.0)"] +[[package]] +name = "docstring-parser" +version = "0.17.0" +description = "Parse Python docstrings in reST, Google and Numpydoc format" +optional = false +python-versions = ">=3.8" +groups = ["dev"] +files = [ + {file = "docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708"}, + {file = "docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912"}, +] + +[package.extras] +dev = ["pre-commit (>=2.16.0)", "pydoctor (>=25.4.0)", "pytest"] +docs = ["pydoctor (>=25.4.0)"] +test = ["pytest"] + +[[package]] +name = "dydantic" +version = "0.0.8" +description = "Dynamically generate pydantic models from JSON schema." +optional = false +python-versions = "<4.0,>=3.9" +groups = ["dev"] +files = [ + {file = "dydantic-0.0.8-py3-none-any.whl", hash = "sha256:cd0a991f523bd8632699872f1c0c4278415dd04783e36adec5428defa0afb721"}, + {file = "dydantic-0.0.8.tar.gz", hash = "sha256:14a31d4cdfce314ce3e69e8f8c7c46cbc26ce3ce4485de0832260386c612942f"}, +] + +[package.dependencies] +pydantic = ">=2,<3" + +[package.extras] +email = ["email-validator (>=2.1,<3.0)"] + [[package]] name = "exceptiongroup" version = "1.3.0" @@ -929,6 +991,59 @@ files = [ {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"}, ] +[[package]] +name = "langchain" +version = "1.0.7" +description = "Building applications with LLMs through composability" +optional = false +python-versions = "<4.0.0,>=3.10.0" +groups = ["dev"] +files = [ + {file = "langchain-1.0.7-py3-none-any.whl", hash = "sha256:cf33b4d60d7a2ff7f0f313441628927853192cdbab9d6d8ce229909a868bbf12"}, + {file = "langchain-1.0.7.tar.gz", hash = "sha256:e3f8ad742b4cdc91d728f96bd70e4688bc11ffeca3bd160c5fe9937625d541b9"}, +] + +[package.dependencies] +langchain-core = ">=1.0.4,<2.0.0" +langgraph = ">=1.0.2,<1.1.0" +pydantic = ">=2.7.4,<3.0.0" + +[package.extras] +anthropic = ["langchain-anthropic"] +aws = ["langchain-aws"] +azure-ai = ["langchain-azure-ai"] +community = ["langchain-community"] +deepseek = ["langchain-deepseek"] +fireworks = ["langchain-fireworks"] +google-genai = ["langchain-google-genai"] +google-vertexai = ["langchain-google-vertexai"] +groq = ["langchain-groq"] +huggingface = ["langchain-huggingface"] +mistralai = ["langchain-mistralai"] +model-profiles = ["langchain-model-profiles"] +ollama = ["langchain-ollama"] +openai = ["langchain-openai"] +perplexity = ["langchain-perplexity"] +together = ["langchain-together"] +xai = ["langchain-xai"] + +[[package]] +name = "langchain-anthropic" +version = "1.0.4" +description = "Integration package connecting Claude (Anthropic) APIs and LangChain" +optional = false +python-versions = "<4.0.0,>=3.10.0" +groups = ["dev"] +files = [ + {file = "langchain_anthropic-1.0.4-py3-none-any.whl", hash = "sha256:ba3e580ac0691b268082b82280bb898af485b58dbf23a65f27e692c009e543ad"}, + {file = "langchain_anthropic-1.0.4.tar.gz", hash = "sha256:46e2a842755609d4a0e9dcc505779093b1a462b04ee9024cbd751ea6853a8890"}, +] + +[package.dependencies] +anthropic = ">=0.69.0,<1.0.0" +langchain-core = ">=1.0.4,<2.0.0" +pydantic = ">=2.7.4,<3.0.0" + [[package]] name = "langchain-core" version = "1.0.5" @@ -1035,6 +1150,28 @@ files = [ httpx = ">=0.25.2" orjson = ">=3.10.1" +[[package]] +name = "langmem" +version = "0.0.30" +description = "Prebuilt utilities for memory management and retrieval." +optional = false +python-versions = ">=3.10" +groups = ["dev"] +files = [ + {file = "langmem-0.0.30-py3-none-any.whl", hash = "sha256:142f040014493eebd67e1055c0642f9ab38868b5b1fde5c8f2d39add57f4ba5b"}, + {file = "langmem-0.0.30.tar.gz", hash = "sha256:4e27920979f8253a96d279f4f97b1aebbfb49e95a46d5269433488ed044756e1"}, +] + +[package.dependencies] +langchain = ">=0.3.15" +langchain-anthropic = ">=0.3.3" +langchain-core = ">=0.3.46" +langchain-openai = ">=0.3.1" +langgraph = ">=0.6.0,<2" +langgraph-checkpoint = ">=2.0.12" +langsmith = ">=0.3.8" +trustcall = ">=0.0.39" + [[package]] name = "langsmith" version = "0.4.43" @@ -2445,6 +2582,23 @@ notebook = ["ipywidgets (>=6)"] slack = ["slack-sdk"] telegram = ["requests"] +[[package]] +name = "trustcall" +version = "0.0.39" +description = "Tenacious & trustworthy tool calling built on LangGraph." +optional = false +python-versions = "<4.0,>=3.10" +groups = ["dev"] +files = [ + {file = "trustcall-0.0.39-py3-none-any.whl", hash = "sha256:d7da42e0bba816c0539b2936dfed90ffb3ea8d789e548e73865d416f8ac4ee64"}, + {file = "trustcall-0.0.39.tar.gz", hash = "sha256:ec315818224501b9537ce6b7618dbc21be41210c6e8f2e239169a5a00912cd6e"}, +] + +[package.dependencies] +dydantic = ">=0.0.8,<1.0.0" +jsonpatch = ">=1.33,<2.0" +langgraph = ">=0.2.25" + [[package]] name = "typing-extensions" version = "4.15.0" @@ -2890,4 +3044,4 @@ cffi = ["cffi (>=1.17,<2.0)", "cffi (>=2.0.0b)"] [metadata] lock-version = "2.1" python-versions = ">=3.10,<3.14" -content-hash = "dccd46f6b24814fd786541e4b647ed0d95bfd756b3c60921ce08320f8e69707f" +content-hash = "f5f666ea14e2dc6ba66c89bf8e3ec396f8da16e6d9c8690cd88fac81c18349fc" diff --git a/pyproject.toml b/pyproject.toml index 3f73e26..1ff8ee4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -44,6 +44,7 @@ pytest-cov = "^6.2.1" vulture = "^2.14" pympler = "^1.1" aiofiles = "^24.1.0" +langmem = "^0.0.30" [tool.pytest.ini_options] # --strict-markers will raise errors on unknown marks. diff --git a/tests/test_langmem_serialization.py b/tests/test_langmem_serialization.py new file mode 100644 index 0000000..1495c20 --- /dev/null +++ b/tests/test_langmem_serialization.py @@ -0,0 +1,104 @@ +"""Integration tests for langmem object serialization with JsonPlusRedisSerializer.""" +import pytest +from langmem.short_term.summarization import RunningSummary +from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer + + +class TestLangmemSerialization: + """Test that langmem objects are properly serialized and deserialized.""" + + def test_running_summary_serialization(self) -> None: + """Test that RunningSummary objects roundtrip correctly through serialization.""" + serializer = JsonPlusRedisSerializer() + + # Create a RunningSummary object similar to what langmem creates + original = RunningSummary( + summary="This is a summary of the conversation", + summarized_message_ids={"msg1", "msg2", "msg3"}, + last_summarized_message_id="msg3", + ) + + # Serialize it + type_str, data_bytes = serializer.dumps_typed(original) + + # Deserialize it + deserialized = serializer.loads_typed((type_str, data_bytes)) + + # Check that it's still a RunningSummary object, not a dict + assert isinstance( + deserialized, RunningSummary + ), f"Expected RunningSummary, got {type(deserialized)}" + assert deserialized.summary == original.summary + assert deserialized.summarized_message_ids == original.summarized_message_ids + assert ( + deserialized.last_summarized_message_id + == original.last_summarized_message_id + ) + + def test_state_with_context_containing_running_summary(self) -> None: + """Test that state dicts with RunningSummary in context are properly handled. + + This tests the real-world scenario where create_react_agent stores + RunningSummary objects in the state's context field. + """ + serializer = JsonPlusRedisSerializer() + + # Create a state similar to what create_react_agent uses + state = { + "messages": [], + "context": { + "running_summary": RunningSummary( + summary="Previous conversation summary", + summarized_message_ids={"msg1", "msg2"}, + last_summarized_message_id="msg2", + ) + }, + } + + # Serialize it + type_str, data_bytes = serializer.dumps_typed(state) + + # Deserialize it + deserialized = serializer.loads_typed((type_str, data_bytes)) + + # Check that the running_summary is still a RunningSummary object + assert "context" in deserialized + assert "running_summary" in deserialized["context"] + running_summary = deserialized["context"]["running_summary"] + + assert isinstance( + running_summary, RunningSummary + ), f"Expected RunningSummary, got {type(running_summary)}" + assert hasattr( + running_summary, "summarized_message_ids" + ), "Missing summarized_message_ids attribute" + assert running_summary.summarized_message_ids == {"msg1", "msg2"} + + def test_nested_running_summary_in_list(self) -> None: + """Test that RunningSummary objects nested in lists are properly handled.""" + serializer = JsonPlusRedisSerializer() + + state = { + "summaries": [ + RunningSummary( + summary="First summary", + summarized_message_ids={"msg1"}, + last_summarized_message_id="msg1", + ), + RunningSummary( + summary="Second summary", + summarized_message_ids={"msg2", "msg3"}, + last_summarized_message_id="msg3", + ), + ] + } + + # Serialize and deserialize + type_str, data_bytes = serializer.dumps_typed(state) + deserialized = serializer.loads_typed((type_str, data_bytes)) + + # Check both summaries are properly reconstructed + assert len(deserialized["summaries"]) == 2 + for summary in deserialized["summaries"]: + assert isinstance(summary, RunningSummary) + assert hasattr(summary, "summarized_message_ids") From 6c7e998a3f7e8545f0eb2ef31a86fdd9b892cbe0 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 13:26:19 -0700 Subject: [PATCH 32/36] chore(tests): suppress trustcall deprecation warning Add pytest filter to suppress LangGraphDeprecatedSinceV10 warning from trustcall library (a dependency of langmem). The warning is about trustcall using deprecated 'from langgraph.constants import Send' instead of 'from langgraph.types import Send'. This is an issue in their library, not ours. --- pyproject.toml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 1ff8ee4..ee45de2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -59,6 +59,8 @@ filterwarnings = [ # Ignore testcontainers internal deprecation warnings (they haven't fixed their own code yet) "ignore::DeprecationWarning:testcontainers.core.waiting_utils", "ignore::DeprecationWarning:testcontainers.redis", + # Ignore trustcall library's deprecated import (used by langmem) + "ignore:Importing Send from langgraph.constants is deprecated.*:langgraph.errors.LangGraphDeprecatedSinceV10:trustcall._base", ] [tool.poetry.scripts] From 15441f1a4ab7a14df1546c840bbb6cd87b5fc0b9 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 13:43:18 -0700 Subject: [PATCH 33/36] fix(notebooks): add Redis flush to clear old checkpoints Add Redis flush command at the start of notebooks to clear old checkpoints that were created with the buggy serializer (before dataclass support was added). This is necessary because: 1. Jupyter kernels cache Python modules 2. Old checkpoints in Redis were serialized without dataclass support 3. Deserializing old checkpoints causes AttributeError even with fixed code The flush ensures notebooks start fresh with the updated serializer. --- ...e-react-agent-manage-message-history.ipynb | 305 +++--------------- .../cross-thread-persistence-functional.ipynb | 32 +- 2 files changed, 70 insertions(+), 267 deletions(-) diff --git a/examples/create-react-agent-manage-message-history.ipynb b/examples/create-react-agent-manage-message-history.ipynb index 466b9f5..b15f827 100644 --- a/examples/create-react-agent-manage-message-history.ipynb +++ b/examples/create-react-agent-manage-message-history.ipynb @@ -143,7 +143,20 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# IMPORTANT: Clear Redis to remove old checkpoints created with buggy serializer\n", + "import redis\n", + "r = redis.Redis(host=\"redis\", port=6379, decode_responses=False)\n", + "r.flushdb()\n", + "print(\"Redis flushed - ready for fresh execution\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -154,18 +167,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [ - { - "name": "stdin", - "output_type": "stream", - "text": [ - "OPENAI_API_KEY: ········\n" - ] - } - ], + "outputs": [], "source": [ "import getpass\n", "import os\n", @@ -220,7 +225,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "eaad19ee-e174-4c6c-b2b8-3530d7acea40", "metadata": {}, "outputs": [], @@ -255,29 +260,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "b507eb58-6e02-4ac6-b48b-ea4defdc11f0", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17:25:53 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "17:25:53 redisvl.index.index INFO Index already exists, not overwriting.\n", - "17:25:53 redisvl.index.index INFO Index already exists, not overwriting.\n", - "17:25:53 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_387/1628370867.py:37: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", - " graph = create_react_agent(\n" - ] - } - ], + "outputs": [], "source": [ "from langgraph.prebuilt import create_react_agent\n", "from langgraph.checkpoint.redis import RedisSaver\n", @@ -326,21 +312,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "8182ab45-86b3-4d6f-b75e-58862a14fa4e", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "from IPython.display import display, Image\n", "\n", @@ -357,7 +332,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], @@ -388,20 +363,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17:25:55 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "17:25:57 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "17:26:07 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "\n", @@ -422,21 +387,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "41ba0253-5199-4d29-82ae-258cbbebddb4", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "432" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "messages = result[\"messages\"]\n", "count_tokens_approximately(messages)" @@ -453,61 +407,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "26c53429-90ba-4d0b-abb9-423d9120ad26", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Update from node: pre_model_hook\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What's it known for?\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "New York City is known for a variety of iconic landmarks, cultural institutions, and vibrant neighborhoods. Some of the most notable features include:\n", - "\n", - "1. **Statue of Liberty**: A symbol of freedom and democracy, located on Liberty Island.\n", - "2. **Times Square**: Known for its bright lights, Broadway theaters, and bustling atmosphere.\n", - "3. **Central Park**: A large public park offering a natural oasis amidst the urban environment.\n", - "4. **Empire State Building**: An iconic skyscraper offering panoramic views of the city.\n", - "5. **Broadway**: Famous for its world-class theater productions and musicals.\n", - "6. **Wall Street**: The financial hub of the city, home to the New York Stock Exchange.\n", - "7. **Museums**: Including the Metropolitan Museum of Art, Museum of Modern Art (MoMA), and the American Museum of Natural History.\n", - "8. **Diverse Cuisine**: A melting pot of cultures, offering a wide range of international foods.\n", - "9. **Cultural Diversity**: Known for its diverse population and vibrant cultural scene.\n", - "10. **Fashion**: A global fashion capital, hosting events like New York Fashion Week.\n", - "\n", - "These are just a few highlights of what makes New York City a unique and exciting place to visit or live.\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "where can i find the best bagel?\n", - "\n", - "\n", - "\n", - "17:26:17 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "Update from node: agent\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "Finding the \"best\" bagel in New York City can be subjective, as it often depends on personal taste preferences. However, several bagel shops are frequently mentioned as top contenders:\n", - "\n", - "1. **Ess-a-Bagel**: Known for its large, chewy bagels and a wide variety of spreads.\n", - "2. **Russ & Daughters**: Famous for its traditional bagels and high-quality smoked fish.\n", - "3. **Absolute Bagels**: Popular for its fresh, fluffy bagels and authentic taste.\n", - "4. **Murray’s Bagels**: Offers a classic New York bagel experience with no toasting policy.\n", - "5. **Tompkins Square Bagels**: Known for its creative cream cheese flavors and hearty bagels.\n", - "6. **Bagel Hole**: Celebrated for its smaller, denser bagels with a crispy crust.\n", - "7. **Black Seed Bagels**: Offers a unique Montreal-style bagel with a New York twist.\n", - "\n", - "These spots are scattered throughout the city, so you can find a great bagel in various neighborhoods. It's always a good idea to try a few different places to find your personal favorite!\n", - "\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "inputs = {\"messages\": [(\"user\", \"where can i find the best bagel?\")]}\n", "print_stream(graph.stream(inputs, config=config, stream_mode=\"updates\"))" @@ -523,7 +426,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "7ecfc310-8f9e-4aa0-9e58-17e71551639a", "metadata": {}, "outputs": [], @@ -552,29 +455,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "48c2a65b-685a-4750-baa6-2d61efe76b5f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17:26:17 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "17:26:17 redisvl.index.index INFO Index already exists, not overwriting.\n", - "17:26:17 redisvl.index.index INFO Index already exists, not overwriting.\n", - "17:26:17 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_387/2986813568.py:27: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", - " graph = create_react_agent(\n" - ] - } - ], + "outputs": [], "source": [ "from langchain_core.messages import RemoveMessage\n", "from langgraph.graph.message import REMOVE_ALL_MESSAGES\n", @@ -621,69 +505,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "831be36a-78a1-4885-9a03-8d085dfd7e37", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17:26:30 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "17:26:39 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "Update from node: pre_model_hook\n", - "================================\u001b[1m Remove Message \u001b[0m================================\n", - "\n", - "\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "What's it known for?\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "New York City is famous for its bagels, and there are several places renowned for serving some of the best. Here are a few top spots where you can find delicious bagels in NYC:\n", - "\n", - "1. **Ess-a-Bagel**: Known for their large, chewy bagels with a variety of spreads and toppings.\n", - "2. **Russ & Daughters**: A classic spot offering traditional bagels with high-quality smoked fish and cream cheese.\n", - "3. **H&H Bagels**: Famous for their fresh, hand-rolled bagels with a perfect balance of crust and chewiness.\n", - "4. **Murray’s Bagels**: Offers a wide selection of bagels and toppings, known for their authentic New York taste.\n", - "5. **Absolute Bagels**: A favorite on the Upper West Side, known for their fresh and flavorful bagels.\n", - "6. **Tompkins Square Bagels**: Offers creative cream cheese flavors and a cozy atmosphere.\n", - "7. **Bagel Hole**: Known for their smaller, denser bagels with a crispy crust.\n", - "\n", - "Each of these places has its own unique style and flavor, so it might be worth trying a few to find your personal favorite!\n", - "================================\u001b[1m Human Message \u001b[0m=================================\n", - "\n", - "where can i find the best bagel?\n", - "\n", - "\n", - "\n", - "17:26:47 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "Update from node: agent\n", - "==================================\u001b[1m Ai Message \u001b[0m==================================\n", - "\n", - "New York City is famous for its bagels, and there are several places renowned for serving some of the best. Here are a few top spots where you can find delicious bagels in NYC:\n", - "\n", - "1. **Ess-a-Bagel**: Known for their large, chewy bagels with a variety of spreads and toppings. Locations in Midtown and Gramercy.\n", - "\n", - "2. **Russ & Daughters**: A historic appetizing store on the Lower East Side, famous for its bagels with lox and cream cheese.\n", - "\n", - "3. **Absolute Bagels**: Located on the Upper West Side, this spot is popular for its fresh, fluffy bagels.\n", - "\n", - "4. **Murray’s Bagels**: Known for their traditional, hand-rolled bagels. Located in Greenwich Village.\n", - "\n", - "5. **Tompkins Square Bagels**: Offers a wide range of bagels and creative cream cheese flavors. Located in the East Village.\n", - "\n", - "6. **Bagel Hole**: A small shop in Park Slope, Brooklyn, known for its classic New York-style bagels.\n", - "\n", - "7. **Leo’s Bagels**: Located in the Financial District, offering a variety of bagels and toppings.\n", - "\n", - "Each of these places has its own unique style and flavor, so it might be worth trying a few to find your personal favorite!\n", - "\n", - "\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "\n", @@ -711,7 +536,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "394f72f8-f817-472d-a193-e01509a86132", "metadata": {}, "outputs": [], @@ -734,7 +559,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "aa6e4bdf", "metadata": {}, "outputs": [], @@ -755,29 +580,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "b9540c1c-2eba-42da-ba4e-478521161a1f", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17:26:49 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "17:26:49 redisvl.index.index INFO Index already exists, not overwriting.\n", - "17:26:49 redisvl.index.index INFO Index already exists, not overwriting.\n", - "17:26:49 redisvl.index.index INFO Index already exists, not overwriting.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_387/3065461601.py:33: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", - " graph = create_react_agent(\n" - ] - } - ], + "outputs": [], "source": [ "# highlight-next-line\n", "from langmem.short_term import SummarizationNode\n", @@ -825,41 +631,10 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "8eccaaca-5d9c-4faf-b997-d4b8e84b59ac", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "17:26:52 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "17:26:54 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", - "17:26:58 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" - ] - }, - { - "ename": "AttributeError", - "evalue": "'dict' object has no attribute 'summarized_message_ids'", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[16]\u001b[39m\u001b[32m, line 7\u001b[39m\n\u001b[32m 4\u001b[39m result = graph.invoke(inputs, config=config)\n\u001b[32m 6\u001b[39m inputs = {\u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m: [(\u001b[33m\"\u001b[39m\u001b[33muser\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mWhat\u001b[39m\u001b[33m'\u001b[39m\u001b[33ms it known for?\u001b[39m\u001b[33m\"\u001b[39m)]}\n\u001b[32m----> \u001b[39m\u001b[32m7\u001b[39m result = \u001b[43mgraph\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 9\u001b[39m inputs = {\u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m: [(\u001b[33m\"\u001b[39m\u001b[33muser\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mwhere can i find the best bagel?\u001b[39m\u001b[33m\"\u001b[39m)]}\n\u001b[32m 10\u001b[39m print_stream(graph.stream(inputs, config=config, stream_mode=\u001b[33m\"\u001b[39m\u001b[33mupdates\u001b[39m\u001b[33m\"\u001b[39m))\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/main.py:3050\u001b[39m, in \u001b[36mPregel.invoke\u001b[39m\u001b[34m(self, input, config, context, stream_mode, print_mode, output_keys, interrupt_before, interrupt_after, durability, **kwargs)\u001b[39m\n\u001b[32m 3047\u001b[39m chunks: \u001b[38;5;28mlist\u001b[39m[\u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any] | Any] = []\n\u001b[32m 3048\u001b[39m interrupts: \u001b[38;5;28mlist\u001b[39m[Interrupt] = []\n\u001b[32m-> \u001b[39m\u001b[32m3050\u001b[39m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 3051\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 3052\u001b[39m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3053\u001b[39m \u001b[43m \u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3054\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m=\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mupdates\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 3055\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m \u001b[49m\u001b[43m==\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\n\u001b[32m 3056\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3057\u001b[39m \u001b[43m \u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m=\u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3058\u001b[39m \u001b[43m \u001b[49m\u001b[43moutput_keys\u001b[49m\u001b[43m=\u001b[49m\u001b[43moutput_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3059\u001b[39m \u001b[43m \u001b[49m\u001b[43minterrupt_before\u001b[49m\u001b[43m=\u001b[49m\u001b[43minterrupt_before\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3060\u001b[39m \u001b[43m \u001b[49m\u001b[43minterrupt_after\u001b[49m\u001b[43m=\u001b[49m\u001b[43minterrupt_after\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3061\u001b[39m \u001b[43m \u001b[49m\u001b[43mdurability\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdurability\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3062\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 3063\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 3064\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m \u001b[49m\u001b[43m==\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\n\u001b[32m 3065\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[43m==\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m2\u001b[39;49m\u001b[43m:\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/main.py:2633\u001b[39m, in \u001b[36mPregel.stream\u001b[39m\u001b[34m(self, input, config, context, stream_mode, print_mode, output_keys, interrupt_before, interrupt_after, durability, subgraphs, debug, **kwargs)\u001b[39m\n\u001b[32m 2631\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m task \u001b[38;5;129;01min\u001b[39;00m loop.match_cached_writes():\n\u001b[32m 2632\u001b[39m loop.output_writes(task.id, task.writes, cached=\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[32m-> \u001b[39m\u001b[32m2633\u001b[39m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrunner\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtick\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2634\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtasks\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m.\u001b[49m\u001b[43mwrites\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2635\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mstep_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2636\u001b[39m \u001b[43m \u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m=\u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2637\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43maccept_push\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2638\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 2639\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# emit output\u001b[39;49;00m\n\u001b[32m 2640\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01myield from\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_output\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2641\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msubgraphs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mqueue\u001b[49m\u001b[43m.\u001b[49m\u001b[43mEmpty\u001b[49m\n\u001b[32m 2642\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 2643\u001b[39m loop.after_tick()\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_runner.py:167\u001b[39m, in \u001b[36mPregelRunner.tick\u001b[39m\u001b[34m(self, tasks, reraise, timeout, retry_policy, get_waiter, schedule_task)\u001b[39m\n\u001b[32m 165\u001b[39m t = tasks[\u001b[32m0\u001b[39m]\n\u001b[32m 166\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m167\u001b[39m \u001b[43mrun_with_retry\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 168\u001b[39m \u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 169\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 170\u001b[39m \u001b[43m \u001b[49m\u001b[43mconfigurable\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\n\u001b[32m 171\u001b[39m \u001b[43m \u001b[49m\u001b[43mCONFIG_KEY_CALL\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpartial\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 172\u001b[39m \u001b[43m \u001b[49m\u001b[43m_call\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 173\u001b[39m \u001b[43m \u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 174\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m=\u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 175\u001b[39m \u001b[43m \u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m=\u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 176\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 177\u001b[39m \u001b[43m \u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 178\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 179\u001b[39m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 180\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 181\u001b[39m \u001b[38;5;28mself\u001b[39m.commit(t, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m 182\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_retry.py:42\u001b[39m, in \u001b[36mrun_with_retry\u001b[39m\u001b[34m(task, retry_policy, configurable)\u001b[39m\n\u001b[32m 40\u001b[39m task.writes.clear()\n\u001b[32m 41\u001b[39m \u001b[38;5;66;03m# run the task\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m42\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43mproc\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43minput\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 43\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m ParentCommand \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[32m 44\u001b[39m ns: \u001b[38;5;28mstr\u001b[39m = config[CONF][CONFIG_KEY_CHECKPOINT_NS]\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:656\u001b[39m, in \u001b[36mRunnableSeq.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 654\u001b[39m \u001b[38;5;66;03m# run in context\u001b[39;00m\n\u001b[32m 655\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m set_config_context(config, run) \u001b[38;5;28;01mas\u001b[39;00m context:\n\u001b[32m--> \u001b[39m\u001b[32m656\u001b[39m \u001b[38;5;28minput\u001b[39m = \u001b[43mcontext\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstep\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 657\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 658\u001b[39m \u001b[38;5;28minput\u001b[39m = step.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:400\u001b[39m, in \u001b[36mRunnableCallable.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 398\u001b[39m run_manager.on_chain_end(ret)\n\u001b[32m 399\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m400\u001b[39m ret = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 401\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.recurse \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, Runnable):\n\u001b[32m 402\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m ret.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langmem/short_term/summarization.py:832\u001b[39m, in \u001b[36mSummarizationNode._func\u001b[39m\u001b[34m(self, input)\u001b[39m\n\u001b[32m 830\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_func\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m: \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any] | BaseModel) -> \u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any]:\n\u001b[32m 831\u001b[39m messages, context = \u001b[38;5;28mself\u001b[39m._parse_input(\u001b[38;5;28minput\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m832\u001b[39m summarization_result = \u001b[43msummarize_messages\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 833\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 834\u001b[39m \u001b[43m \u001b[49m\u001b[43mrunning_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcontext\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrunning_summary\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 835\u001b[39m \u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 836\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 837\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 838\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 839\u001b[39m \u001b[43m \u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 840\u001b[39m \u001b[43m \u001b[49m\u001b[43minitial_summary_prompt\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43minitial_summary_prompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 841\u001b[39m \u001b[43m \u001b[49m\u001b[43mexisting_summary_prompt\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mexisting_summary_prompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 842\u001b[39m \u001b[43m \u001b[49m\u001b[43mfinal_prompt\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfinal_prompt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 843\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 844\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._prepare_state_update(context, summarization_result)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langmem/short_term/summarization.py:445\u001b[39m, in \u001b[36msummarize_messages\u001b[39m\u001b[34m(messages, running_summary, model, max_tokens, max_tokens_before_summary, max_summary_tokens, token_counter, initial_summary_prompt, existing_summary_prompt, final_prompt)\u001b[39m\n\u001b[32m 337\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34msummarize_messages\u001b[39m(\n\u001b[32m 338\u001b[39m messages: \u001b[38;5;28mlist\u001b[39m[AnyMessage],\n\u001b[32m 339\u001b[39m *,\n\u001b[32m (...)\u001b[39m\u001b[32m 348\u001b[39m final_prompt: ChatPromptTemplate = DEFAULT_FINAL_SUMMARY_PROMPT,\n\u001b[32m 349\u001b[39m ) -> SummarizationResult:\n\u001b[32m 350\u001b[39m \u001b[38;5;250m \u001b[39m\u001b[33;03m\"\"\"Summarize messages when they exceed a token limit and replace them with a summary message.\u001b[39;00m\n\u001b[32m 351\u001b[39m \n\u001b[32m 352\u001b[39m \u001b[33;03m This function processes the messages from oldest to newest: once the cumulative number of message tokens\u001b[39;00m\n\u001b[32m (...)\u001b[39m\u001b[32m 443\u001b[39m \u001b[33;03m ```\u001b[39;00m\n\u001b[32m 444\u001b[39m \u001b[33;03m \"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m445\u001b[39m preprocessed_messages = \u001b[43m_preprocess_messages\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 446\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 447\u001b[39m \u001b[43m \u001b[49m\u001b[43mrunning_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrunning_summary\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 448\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 449\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_tokens_before_summary\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 450\u001b[39m \u001b[43m \u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmax_summary_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 451\u001b[39m \u001b[43m \u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtoken_counter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 452\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 453\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m preprocessed_messages.existing_system_message:\n\u001b[32m 454\u001b[39m messages = messages[\u001b[32m1\u001b[39m:]\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langmem/short_term/summarization.py:145\u001b[39m, in \u001b[36m_preprocess_messages\u001b[39m\u001b[34m(messages, running_summary, max_tokens, max_tokens_before_summary, max_summary_tokens, token_counter)\u001b[39m\n\u001b[32m 143\u001b[39m total_summarized_messages = \u001b[32m0\u001b[39m\n\u001b[32m 144\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m running_summary:\n\u001b[32m--> \u001b[39m\u001b[32m145\u001b[39m summarized_message_ids = \u001b[43mrunning_summary\u001b[49m\u001b[43m.\u001b[49m\u001b[43msummarized_message_ids\u001b[49m\n\u001b[32m 146\u001b[39m \u001b[38;5;66;03m# Adjust the summarization token budget to account for the previous summary\u001b[39;00m\n\u001b[32m 147\u001b[39m max_tokens_to_summarize -= token_counter(\n\u001b[32m 148\u001b[39m [SystemMessage(content=running_summary.summary)]\n\u001b[32m 149\u001b[39m )\n", - "\u001b[31mAttributeError\u001b[39m: 'dict' object has no attribute 'summarized_message_ids'", - "During task with name 'pre_model_hook' and id '38a6ec6c-13cc-a2ff-ed87-b517db665815'" - ] - } - ], + "outputs": [], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "inputs = {\"messages\": [(\"user\", \"What's the weather in NYC?\")]}\n", @@ -903,4 +678,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/examples/cross-thread-persistence-functional.ipynb b/examples/cross-thread-persistence-functional.ipynb index fd9d087..258b017 100644 --- a/examples/cross-thread-persistence-functional.ipynb +++ b/examples/cross-thread-persistence-functional.ipynb @@ -57,6 +57,19 @@ "First, let's install the required packages and set our API keys" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# IMPORTANT: Clear Redis to remove old checkpoints created with buggy serializer\n", + "import redis\n", + "r = redis.Redis(host=\"redis\", port=6379, decode_responses=False)\n", + "r.flushdb()\n", + "print(\"Redis flushed - ready for fresh execution\")" + ] + }, { "cell_type": "code", "execution_count": null, @@ -110,7 +123,22 @@ "cell_type": "markdown", "id": "c4c550b5-1954-496b-8b9d-800361af17dc", "metadata": {}, - "source": "### Define store\n\nIn this example we will create a workflow that will be able to retrieve information about a user's preferences. We will do so by defining a `RedisStore` - an object that can store data in Redis and query that data.\n\nWhen storing objects using the `Store` interface you define two things:\n\n* the namespace for the object, a tuple (similar to directories)\n* the object key (similar to filenames)\n\nIn our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n\nImportantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n\nLet's first define our store!" + "source": [ + "### Define store\n", + "\n", + "In this example we will create a workflow that will be able to retrieve information about a user's preferences. We will do so by defining a `RedisStore` - an object that can store data in Redis and query that data.\n", + "\n", + "When storing objects using the `Store` interface you define two things:\n", + "\n", + "* the namespace for the object, a tuple (similar to directories)\n", + "* the object key (similar to filenames)\n", + "\n", + "In our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n", + "\n", + "Importantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n", + "\n", + "Let's first define our store!" + ] }, { "cell_type": "code", @@ -321,7 +349,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, From 2f207ce47f8138995add3fe156dd4f436cc6d156 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 13:44:22 -0700 Subject: [PATCH 34/36] fix(notebook): update to current Claude model version Replace deprecated claude-3-5-sonnet-20240620 with claude-3-5-sonnet-20241022 to fix NotFoundError when running notebook. The old model version reached end-of-life and returns 404 errors. --- examples/cross-thread-persistence.ipynb | 112 +++++++++++++++++++++--- 1 file changed, 99 insertions(+), 13 deletions(-) diff --git a/examples/cross-thread-persistence.ipynb b/examples/cross-thread-persistence.ipynb index 435e2ac..091533a 100644 --- a/examples/cross-thread-persistence.ipynb +++ b/examples/cross-thread-persistence.ipynb @@ -53,7 +53,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "3457aadf", "metadata": {}, "outputs": [], @@ -64,10 +64,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "aa2c64a7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "ANTHROPIC_API_KEY: ········\n", + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -96,14 +105,39 @@ "cell_type": "markdown", "id": "c4c550b5-1954-496b-8b9d-800361af17dc", "metadata": {}, - "source": "## Define store\n\nIn this example we will create a graph that will be able to retrieve information about a user's preferences. We will do so by defining a `RedisStore` - an object that can store data in Redis and query that data. We will then pass the store object when compiling the graph. This allows each node in the graph to access the store: when you define node functions, you can define `store` keyword argument, and LangGraph will automatically pass the store object you compiled the graph with.\n\nWhen storing objects using the `Store` interface you define two things:\n\n* the namespace for the object, a tuple (similar to directories)\n* the object key (similar to filenames)\n\nIn our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n\nImportantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n\nLet's first define a `RedisStore` already populated with some memories about the users." + "source": [ + "## Define store\n", + "\n", + "In this example we will create a graph that will be able to retrieve information about a user's preferences. We will do so by defining a `RedisStore` - an object that can store data in Redis and query that data. We will then pass the store object when compiling the graph. This allows each node in the graph to access the store: when you define node functions, you can define `store` keyword argument, and LangGraph will automatically pass the store object you compiled the graph with.\n", + "\n", + "When storing objects using the `Store` interface you define two things:\n", + "\n", + "* the namespace for the object, a tuple (similar to directories)\n", + "* the object key (similar to filenames)\n", + "\n", + "In our example, we'll be using `(\"memories\", )` as namespace and random UUID as key for each new memory.\n", + "\n", + "Importantly, to determine the user, we will be passing `user_id` via the config keyword argument of the node function.\n", + "\n", + "Let's first define a `RedisStore` already populated with some memories about the users." + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "a7f303d6-612e-4e34-bf36-29d4ed25d802", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "20:42:20 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", + "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n", + "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from langchain_openai import OpenAIEmbeddings\n", "from langgraph.store.redis import RedisStore\n", @@ -139,10 +173,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "2a30a362-528c-45ee-9df6-630d2d843588", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "20:42:20 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n", + "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n", + "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "import uuid\n", "\n", @@ -152,7 +197,7 @@ "from langgraph.checkpoint.redis import RedisSaver\n", "from langgraph.store.base import BaseStore\n", "\n", - "model = ChatAnthropic(model=\"claude-3-5-sonnet-20240620\")\n", + "model = ChatAnthropic(model=\"claude-3-5-sonnet-20241022\")\n", "\n", "\n", "# NOTE: we're passing the Store param to the node --\n", @@ -223,10 +268,51 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "c871a073-a466-46ad-aafe-2b870831057e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "Hi! Remember: my name is Bob\n", + "20:42:20 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "20:42:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "20:42:21 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 404 Not Found\"\n" + ] + }, + { + "ename": "NotFoundError", + "evalue": "Error code: 404 - {'type': 'error', 'error': {'type': 'not_found_error', 'message': 'model: claude-3-5-sonnet-20241022'}, 'request_id': 'req_011CVE7Pi9nafi1huJ3xWNfm'}", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mNotFoundError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[5]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m 1\u001b[39m config = {\u001b[33m\"\u001b[39m\u001b[33mconfigurable\u001b[39m\u001b[33m\"\u001b[39m: {\u001b[33m\"\u001b[39m\u001b[33mthread_id\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33m1\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33muser_id\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33m1\u001b[39m\u001b[33m\"\u001b[39m}}\n\u001b[32m 2\u001b[39m input_message = {\u001b[33m\"\u001b[39m\u001b[33mrole\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33muser\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mcontent\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mHi! Remember: my name is Bob\u001b[39m\u001b[33m\"\u001b[39m}\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m \u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mgraph\u001b[49m\u001b[43m.\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43minput_message\u001b[49m\u001b[43m]\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 4\u001b[39m \u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[43m-\u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m.\u001b[49m\u001b[43mpretty_print\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/main.py:2633\u001b[39m, in \u001b[36mPregel.stream\u001b[39m\u001b[34m(self, input, config, context, stream_mode, print_mode, output_keys, interrupt_before, interrupt_after, durability, subgraphs, debug, **kwargs)\u001b[39m\n\u001b[32m 2631\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m task \u001b[38;5;129;01min\u001b[39;00m loop.match_cached_writes():\n\u001b[32m 2632\u001b[39m loop.output_writes(task.id, task.writes, cached=\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[32m-> \u001b[39m\u001b[32m2633\u001b[39m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrunner\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtick\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2634\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtasks\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m.\u001b[49m\u001b[43mwrites\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2635\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mstep_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2636\u001b[39m \u001b[43m \u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m=\u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2637\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43maccept_push\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2638\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 2639\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# emit output\u001b[39;49;00m\n\u001b[32m 2640\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01myield from\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_output\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2641\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msubgraphs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mqueue\u001b[49m\u001b[43m.\u001b[49m\u001b[43mEmpty\u001b[49m\n\u001b[32m 2642\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 2643\u001b[39m loop.after_tick()\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_runner.py:167\u001b[39m, in \u001b[36mPregelRunner.tick\u001b[39m\u001b[34m(self, tasks, reraise, timeout, retry_policy, get_waiter, schedule_task)\u001b[39m\n\u001b[32m 165\u001b[39m t = tasks[\u001b[32m0\u001b[39m]\n\u001b[32m 166\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m167\u001b[39m \u001b[43mrun_with_retry\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 168\u001b[39m \u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 169\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 170\u001b[39m \u001b[43m \u001b[49m\u001b[43mconfigurable\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\n\u001b[32m 171\u001b[39m \u001b[43m \u001b[49m\u001b[43mCONFIG_KEY_CALL\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpartial\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 172\u001b[39m \u001b[43m \u001b[49m\u001b[43m_call\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 173\u001b[39m \u001b[43m \u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 174\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m=\u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 175\u001b[39m \u001b[43m \u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m=\u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 176\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 177\u001b[39m \u001b[43m \u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 178\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 179\u001b[39m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 180\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 181\u001b[39m \u001b[38;5;28mself\u001b[39m.commit(t, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m 182\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_retry.py:42\u001b[39m, in \u001b[36mrun_with_retry\u001b[39m\u001b[34m(task, retry_policy, configurable)\u001b[39m\n\u001b[32m 40\u001b[39m task.writes.clear()\n\u001b[32m 41\u001b[39m \u001b[38;5;66;03m# run the task\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m42\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43mproc\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43minput\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 43\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m ParentCommand \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[32m 44\u001b[39m ns: \u001b[38;5;28mstr\u001b[39m = config[CONF][CONFIG_KEY_CHECKPOINT_NS]\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:656\u001b[39m, in \u001b[36mRunnableSeq.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 654\u001b[39m \u001b[38;5;66;03m# run in context\u001b[39;00m\n\u001b[32m 655\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m set_config_context(config, run) \u001b[38;5;28;01mas\u001b[39;00m context:\n\u001b[32m--> \u001b[39m\u001b[32m656\u001b[39m \u001b[38;5;28minput\u001b[39m = \u001b[43mcontext\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstep\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 657\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 658\u001b[39m \u001b[38;5;28minput\u001b[39m = step.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:400\u001b[39m, in \u001b[36mRunnableCallable.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 398\u001b[39m run_manager.on_chain_end(ret)\n\u001b[32m 399\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m400\u001b[39m ret = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 401\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.recurse \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, Runnable):\n\u001b[32m 402\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m ret.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 27\u001b[39m, in \u001b[36mcall_model\u001b[39m\u001b[34m(state, config, store)\u001b[39m\n\u001b[32m 24\u001b[39m memory = \u001b[33m\"\u001b[39m\u001b[33mUser name is Bob\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 25\u001b[39m store.put(namespace, \u001b[38;5;28mstr\u001b[39m(uuid.uuid4()), {\u001b[33m\"\u001b[39m\u001b[33mdata\u001b[39m\u001b[33m\"\u001b[39m: memory})\n\u001b[32m---> \u001b[39m\u001b[32m27\u001b[39m response = \u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 28\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrole\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43msystem\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mcontent\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43msystem_msg\u001b[49m\u001b[43m}\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[43m+\u001b[49m\u001b[43m \u001b[49m\u001b[43mstate\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 29\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 30\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m {\u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m: response}\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:385\u001b[39m, in \u001b[36mBaseChatModel.invoke\u001b[39m\u001b[34m(self, input, config, stop, **kwargs)\u001b[39m\n\u001b[32m 371\u001b[39m \u001b[38;5;129m@override\u001b[39m\n\u001b[32m 372\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34minvoke\u001b[39m(\n\u001b[32m 373\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 378\u001b[39m **kwargs: Any,\n\u001b[32m 379\u001b[39m ) -> AIMessage:\n\u001b[32m 380\u001b[39m config = ensure_config(config)\n\u001b[32m 381\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cast(\n\u001b[32m 382\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mAIMessage\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 383\u001b[39m cast(\n\u001b[32m 384\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mChatGeneration\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m--> \u001b[39m\u001b[32m385\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mgenerate_prompt\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 386\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_convert_input\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 387\u001b[39m \u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 388\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mcallbacks\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 389\u001b[39m \u001b[43m \u001b[49m\u001b[43mtags\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtags\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 390\u001b[39m \u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmetadata\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 391\u001b[39m \u001b[43m \u001b[49m\u001b[43mrun_name\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrun_name\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 392\u001b[39m \u001b[43m \u001b[49m\u001b[43mrun_id\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mpop\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrun_id\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 393\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 394\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m.generations[\u001b[32m0\u001b[39m][\u001b[32m0\u001b[39m],\n\u001b[32m 395\u001b[39m ).message,\n\u001b[32m 396\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:1104\u001b[39m, in \u001b[36mBaseChatModel.generate_prompt\u001b[39m\u001b[34m(self, prompts, stop, callbacks, **kwargs)\u001b[39m\n\u001b[32m 1095\u001b[39m \u001b[38;5;129m@override\u001b[39m\n\u001b[32m 1096\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mgenerate_prompt\u001b[39m(\n\u001b[32m 1097\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 1101\u001b[39m **kwargs: Any,\n\u001b[32m 1102\u001b[39m ) -> LLMResult:\n\u001b[32m 1103\u001b[39m prompt_messages = [p.to_messages() \u001b[38;5;28;01mfor\u001b[39;00m p \u001b[38;5;129;01min\u001b[39;00m prompts]\n\u001b[32m-> \u001b[39m\u001b[32m1104\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mgenerate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprompt_messages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:914\u001b[39m, in \u001b[36mBaseChatModel.generate\u001b[39m\u001b[34m(self, messages, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)\u001b[39m\n\u001b[32m 911\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m i, m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(input_messages):\n\u001b[32m 912\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 913\u001b[39m results.append(\n\u001b[32m--> \u001b[39m\u001b[32m914\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_generate_with_cache\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 915\u001b[39m \u001b[43m \u001b[49m\u001b[43mm\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 916\u001b[39m \u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 917\u001b[39m \u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrun_managers\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrun_managers\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 918\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 919\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 920\u001b[39m )\n\u001b[32m 921\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 922\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m run_managers:\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:1208\u001b[39m, in \u001b[36mBaseChatModel._generate_with_cache\u001b[39m\u001b[34m(self, messages, stop, run_manager, **kwargs)\u001b[39m\n\u001b[32m 1206\u001b[39m result = generate_from_stream(\u001b[38;5;28miter\u001b[39m(chunks))\n\u001b[32m 1207\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m inspect.signature(\u001b[38;5;28mself\u001b[39m._generate).parameters.get(\u001b[33m\"\u001b[39m\u001b[33mrun_manager\u001b[39m\u001b[33m\"\u001b[39m):\n\u001b[32m-> \u001b[39m\u001b[32m1208\u001b[39m result = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_generate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 1209\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\n\u001b[32m 1210\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1211\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 1212\u001b[39m result = \u001b[38;5;28mself\u001b[39m._generate(messages, stop=stop, **kwargs)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_anthropic/chat_models.py:1866\u001b[39m, in \u001b[36mChatAnthropic._generate\u001b[39m\u001b[34m(self, messages, stop, run_manager, **kwargs)\u001b[39m\n\u001b[32m 1864\u001b[39m payload = \u001b[38;5;28mself\u001b[39m._get_request_payload(messages, stop=stop, **kwargs)\n\u001b[32m 1865\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1866\u001b[39m data = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_create\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpayload\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1867\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m anthropic.BadRequestError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 1868\u001b[39m _handle_anthropic_bad_request(e)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_anthropic/chat_models.py:1728\u001b[39m, in \u001b[36mChatAnthropic._create\u001b[39m\u001b[34m(self, payload)\u001b[39m\n\u001b[32m 1726\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mbetas\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m payload:\n\u001b[32m 1727\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._client.beta.messages.create(**payload)\n\u001b[32m-> \u001b[39m\u001b[32m1728\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_client\u001b[49m\u001b[43m.\u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mpayload\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/_utils/_utils.py:282\u001b[39m, in \u001b[36mrequired_args..inner..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 280\u001b[39m msg = \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mMissing required argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquote(missing[\u001b[32m0\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 281\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[32m--> \u001b[39m\u001b[32m282\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/resources/messages/messages.py:930\u001b[39m, in \u001b[36mMessages.create\u001b[39m\u001b[34m(self, max_tokens, messages, model, metadata, service_tier, stop_sequences, stream, system, temperature, thinking, tool_choice, tools, top_k, top_p, extra_headers, extra_query, extra_body, timeout)\u001b[39m\n\u001b[32m 923\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m model \u001b[38;5;129;01min\u001b[39;00m DEPRECATED_MODELS:\n\u001b[32m 924\u001b[39m warnings.warn(\n\u001b[32m 925\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mThe model \u001b[39m\u001b[33m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodel\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m'\u001b[39m\u001b[33m is deprecated and will reach end-of-life on \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mDEPRECATED_MODELS[model]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mPlease migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 926\u001b[39m \u001b[38;5;167;01mDeprecationWarning\u001b[39;00m,\n\u001b[32m 927\u001b[39m stacklevel=\u001b[32m3\u001b[39m,\n\u001b[32m 928\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m930\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_post\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 931\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m/v1/messages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 932\u001b[39m \u001b[43m \u001b[49m\u001b[43mbody\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 933\u001b[39m \u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[32m 934\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmax_tokens\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 935\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 936\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmodel\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 937\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmetadata\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 938\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mservice_tier\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mservice_tier\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 939\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mstop_sequences\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop_sequences\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 940\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mstream\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 941\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43msystem\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43msystem\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 942\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtemperature\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 943\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mthinking\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mthinking\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 944\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtool_choice\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtool_choice\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 945\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtools\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtools\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 946\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtop_k\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 947\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtop_p\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtop_p\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 948\u001b[39m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 949\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessage_create_params\u001b[49m\u001b[43m.\u001b[49m\u001b[43mMessageCreateParamsStreaming\u001b[49m\n\u001b[32m 950\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\n\u001b[32m 951\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmessage_create_params\u001b[49m\u001b[43m.\u001b[49m\u001b[43mMessageCreateParamsNonStreaming\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 952\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 953\u001b[39m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmake_request_options\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 954\u001b[39m \u001b[43m \u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_query\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_query\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_body\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\n\u001b[32m 955\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 956\u001b[39m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m=\u001b[49m\u001b[43mMessage\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 957\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 958\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m=\u001b[49m\u001b[43mStream\u001b[49m\u001b[43m[\u001b[49m\u001b[43mRawMessageStreamEvent\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 959\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/_base_client.py:1326\u001b[39m, in \u001b[36mSyncAPIClient.post\u001b[39m\u001b[34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[39m\n\u001b[32m 1312\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mpost\u001b[39m(\n\u001b[32m 1313\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m 1314\u001b[39m path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 1321\u001b[39m stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] | \u001b[38;5;28;01mNone\u001b[39;00m = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 1322\u001b[39m ) -> ResponseT | _StreamT:\n\u001b[32m 1323\u001b[39m opts = FinalRequestOptions.construct(\n\u001b[32m 1324\u001b[39m method=\u001b[33m\"\u001b[39m\u001b[33mpost\u001b[39m\u001b[33m\"\u001b[39m, url=path, json_data=body, files=to_httpx_files(files), **options\n\u001b[32m 1325\u001b[39m )\n\u001b[32m-> \u001b[39m\u001b[32m1326\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n", + "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/_base_client.py:1114\u001b[39m, in \u001b[36mSyncAPIClient.request\u001b[39m\u001b[34m(self, cast_to, options, stream, stream_cls)\u001b[39m\n\u001b[32m 1111\u001b[39m err.response.read()\n\u001b[32m 1113\u001b[39m log.debug(\u001b[33m\"\u001b[39m\u001b[33mRe-raising status error\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m-> \u001b[39m\u001b[32m1114\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m._make_status_error_from_response(err.response) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 1116\u001b[39m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[32m 1118\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m response \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[33m\"\u001b[39m\u001b[33mcould not resolve response (should never happen)\u001b[39m\u001b[33m\"\u001b[39m\n", + "\u001b[31mNotFoundError\u001b[39m: Error code: 404 - {'type': 'error', 'error': {'type': 'not_found_error', 'message': 'model: claude-3-5-sonnet-20241022'}, 'request_id': 'req_011CVE7Pi9nafi1huJ3xWNfm'}", + "During task with name 'call_model' and id '406a4cea-f81e-7b24-dad8-892c428325df'" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"Hi! Remember: my name is Bob\"}\n", @@ -304,9 +390,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} From a24a8258d42f140d41ebf0abe9d990490509ac28 Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 17:45:22 -0700 Subject: [PATCH 35/36] refactor: update notebooks --- examples/Dockerfile.jupyter | 1 + examples/create-react-agent-hitl.ipynb | 32 +- ...e-react-agent-manage-message-history.ipynb | 344 ++++++++++++-- examples/create-react-agent-memory.ipynb | 112 ++++- .../cross-thread-persistence-functional.ipynb | 125 +++-- examples/cross-thread-persistence.ipynb | 106 +++-- .../add-summary-conversation-history.ipynb | 253 +++++++++- examples/memory/delete-messages.ipynb | 169 ++++++- .../memory/manage-conversation-history.ipynb | 98 +++- examples/memory/semantic-search.ipynb | 205 ++++++++- examples/persistence-functional.ipynb | 70 ++- examples/subgraph-persistence.ipynb | 102 ++++- examples/subgraphs-manage-state.ipynb | 432 +++++++++++++++--- langgraph/checkpoint/redis/jsonplus_redis.py | 4 +- tests/test_langmem_serialization.py | 2 + 15 files changed, 1750 insertions(+), 305 deletions(-) diff --git a/examples/Dockerfile.jupyter b/examples/Dockerfile.jupyter index d186df6..388d25e 100644 --- a/examples/Dockerfile.jupyter +++ b/examples/Dockerfile.jupyter @@ -17,6 +17,7 @@ USER jupyter # Set up virtual environment RUN python -m venv /home/jupyter/venv ENV PATH="/home/jupyter/venv/bin:$PATH" +ENV PYTHONDONTWRITEBYTECODE=1 # Install dependencies RUN pip install --no-cache-dir --upgrade pip && \ diff --git a/examples/create-react-agent-hitl.ipynb b/examples/create-react-agent-hitl.ipynb index fbd4577..7a5bc1c 100644 --- a/examples/create-react-agent-hitl.ipynb +++ b/examples/create-react-agent-hitl.ipynb @@ -121,14 +121,14 @@ "output_type": "stream", "text": [ "0.2.0\n", - "17:25:17 langgraph.checkpoint.redis INFO Redis client is a standalone client\n" + "20:54:48 langgraph.checkpoint.redis INFO Redis client is a standalone client\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "/tmp/ipykernel_253/104821471.py:41: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + "/tmp/ipykernel_196/104821471.py:41: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", " graph = create_react_agent(\n" ] } @@ -217,11 +217,11 @@ "================================\u001b[1m Human Message \u001b[0m=================================\n", "\n", "what is the weather in SF, CA?\n", - "17:25:18 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "20:54:49 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "Tool Calls:\n", - " get_weather (call_5pXxdiKNI2XosSX5Vt9sbuBv)\n", - " Call ID: call_5pXxdiKNI2XosSX5Vt9sbuBv\n", + " get_weather (call_JQR9gMUJPiZEZ1HgkJsUYIYA)\n", + " Call ID: call_JQR9gMUJPiZEZ1HgkJsUYIYA\n", " Args:\n", " location: SF, CA\n" ] @@ -254,7 +254,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "20:54:49 langgraph WARNING Ignoring invalid packet type in pending sends\n", "Next step: ()\n" ] } @@ -284,11 +284,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "20:54:49 langgraph WARNING Ignoring invalid packet type in pending sends\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "Tool Calls:\n", - " get_weather (call_5pXxdiKNI2XosSX5Vt9sbuBv)\n", - " Call ID: call_5pXxdiKNI2XosSX5Vt9sbuBv\n", + " get_weather (call_JQR9gMUJPiZEZ1HgkJsUYIYA)\n", + " Call ID: call_JQR9gMUJPiZEZ1HgkJsUYIYA\n", " Args:\n", " location: SF, CA\n" ] @@ -318,16 +318,16 @@ "name": "stdout", "output_type": "stream", "text": [ - "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", - "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n" + "20:54:49 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "20:54:49 langgraph WARNING Ignoring invalid packet type in pending sends\n" ] }, { "data": { "text/plain": [ - "{'configurable': {'thread_id': '0f79839b-117e-4aa5-901b-5c4939d92005',\n", + "{'configurable': {'thread_id': '18c43cd5-0bf0-40dd-a7f2-316450e0022e',\n", " 'checkpoint_ns': '',\n", - " 'checkpoint_id': '1f0c3da6-3615-6dbc-8002-bb5ce3d337c1'}}" + " 'checkpoint_id': '1f0c3f7a-8519-617a-8002-a6eecd3547b9'}}" ] }, "execution_count": 8, @@ -354,11 +354,11 @@ "name": "stdout", "output_type": "stream", "text": [ - "17:25:18 langgraph WARNING Ignoring invalid packet type in pending sends\n", + "20:54:49 langgraph WARNING Ignoring invalid packet type in pending sends\n", "==================================\u001b[1m Ai Message \u001b[0m==================================\n", "Tool Calls:\n", - " get_weather (call_5pXxdiKNI2XosSX5Vt9sbuBv)\n", - " Call ID: call_5pXxdiKNI2XosSX5Vt9sbuBv\n", + " get_weather (call_JQR9gMUJPiZEZ1HgkJsUYIYA)\n", + " Call ID: call_JQR9gMUJPiZEZ1HgkJsUYIYA\n", " Args:\n", " location: San Francisco\n" ] diff --git a/examples/create-react-agent-manage-message-history.ipynb b/examples/create-react-agent-manage-message-history.ipynb index b15f827..2fb9aa7 100644 --- a/examples/create-react-agent-manage-message-history.ipynb +++ b/examples/create-react-agent-manage-message-history.ipynb @@ -143,9 +143,18 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 1, + "id": "a6695ddf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Redis flushed - ready for fresh execution\n" + ] + } + ], "source": [ "# IMPORTANT: Clear Redis to remove old checkpoints created with buggy serializer\n", "import redis\n", @@ -156,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -167,10 +176,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -225,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "eaad19ee-e174-4c6c-b2b8-3530d7acea40", "metadata": {}, "outputs": [], @@ -260,10 +277,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "b507eb58-6e02-4ac6-b48b-ea4defdc11f0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:07 langgraph.checkpoint.redis INFO Redis client is a standalone client\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_1893/1628370867.py:37: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" + ] + } + ], "source": [ "from langgraph.prebuilt import create_react_agent\n", "from langgraph.checkpoint.redis import RedisSaver\n", @@ -312,10 +345,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "8182ab45-86b3-4d6f-b75e-58862a14fa4e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from IPython.display import display, Image\n", "\n", @@ -332,7 +376,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], @@ -363,12 +407,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:08 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "00:25:09 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "00:25:13 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" + ] + } + ], "source": [ - "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", + "config = {\"configurable\": {\"thread_id\": \"trim-example-1\"}}\n", "\n", "inputs = {\"messages\": [(\"user\", \"What's the weather in NYC?\")]}\n", "result = graph.invoke(inputs, config=config)\n", @@ -387,10 +441,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "41ba0253-5199-4d29-82ae-258cbbebddb4", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "441" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "messages = result[\"messages\"]\n", "count_tokens_approximately(messages)" @@ -407,10 +472,61 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "26c53429-90ba-4d0b-abb9-423d9120ad26", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Update from node: pre_model_hook\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What's it known for?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is known for a variety of iconic landmarks, cultural institutions, and vibrant neighborhoods. Some of the most notable features include:\n", + "\n", + "1. **Statue of Liberty**: A symbol of freedom and democracy, located on Liberty Island.\n", + "2. **Times Square**: Known for its bright lights, Broadway theaters, and bustling atmosphere.\n", + "3. **Central Park**: A large public park offering a natural oasis amidst the urban environment.\n", + "4. **Empire State Building**: An iconic skyscraper offering panoramic views of the city.\n", + "5. **Broadway**: Famous for its world-class theater productions.\n", + "6. **Wall Street**: The financial hub of the United States.\n", + "7. **Museums**: Including the Metropolitan Museum of Art, Museum of Modern Art (MoMA), and the American Museum of Natural History.\n", + "8. **Diverse Cuisine**: A melting pot of cultures reflected in its diverse food scene, from street food to Michelin-starred restaurants.\n", + "9. **Cultural Diversity**: A rich tapestry of cultures and communities, making it one of the most diverse cities in the world.\n", + "10. **Fashion**: A global fashion capital, hosting events like New York Fashion Week.\n", + "\n", + "These are just a few highlights of what makes New York City a unique and exciting place to visit or live.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "where can i find the best bagel?\n", + "\n", + "\n", + "\n", + "00:25:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: agent\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Finding the \"best\" bagel in New York City can be subjective, as it often depends on personal taste preferences. However, several bagel shops are frequently mentioned as top contenders for the best bagels in the city:\n", + "\n", + "1. **Ess-a-Bagel**: Known for its large, chewy bagels and a wide variety of spreads and toppings.\n", + "2. **Russ & Daughters**: Famous for its traditional bagels and high-quality smoked fish.\n", + "3. **Absolute Bagels**: A favorite on the Upper West Side, known for its fresh and fluffy bagels.\n", + "4. **Murray’s Bagels**: Offers a classic New York bagel experience with a no-toasting policy to preserve freshness.\n", + "5. **Tompkins Square Bagels**: Known for its creative cream cheese flavors and hearty bagels.\n", + "6. **Bagel Hole**: A small shop in Park Slope, Brooklyn, known for its dense and flavorful bagels.\n", + "7. **Leo’s Bagels**: Offers a wide variety of bagels and toppings, known for its quality and taste.\n", + "\n", + "These spots are beloved by locals and visitors alike, and each offers a unique take on the classic New York bagel.\n", + "\n", + "\n", + "\n" + ] + } + ], "source": [ "inputs = {\"messages\": [(\"user\", \"where can i find the best bagel?\")]}\n", "print_stream(graph.stream(inputs, config=config, stream_mode=\"updates\"))" @@ -426,7 +542,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "7ecfc310-8f9e-4aa0-9e58-17e71551639a", "metadata": {}, "outputs": [], @@ -455,10 +571,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "48c2a65b-685a-4750-baa6-2d61efe76b5f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:21 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:25:21 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:25:21 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:25:21 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_1893/2986813568.py:27: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" + ] + } + ], "source": [ "from langchain_core.messages import RemoveMessage\n", "from langgraph.graph.message import REMOVE_ALL_MESSAGES\n", @@ -505,12 +640,75 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "831be36a-78a1-4885-9a03-8d085dfd7e37", "metadata": {}, - "outputs": [], - "source": [ - "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:22 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "00:25:22 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "00:25:28 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: pre_model_hook\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What's it known for?\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is known for a variety of iconic landmarks, cultural institutions, and vibrant neighborhoods. Some of the most notable features include:\n", + "\n", + "1. **Statue of Liberty**: A symbol of freedom and democracy, located on Liberty Island.\n", + "2. **Times Square**: Known for its bright lights, Broadway theaters, and bustling atmosphere.\n", + "3. **Central Park**: A large public park offering a natural oasis amidst the urban environment.\n", + "4. **Empire State Building**: An iconic skyscraper offering panoramic views of the city.\n", + "5. **Broadway**: Famous for its world-class theater productions and musicals.\n", + "6. **Wall Street**: The financial hub of the United States, located in the Financial District.\n", + "7. **Museums**: Including the Metropolitan Museum of Art, Museum of Modern Art (MoMA), and the American Museum of Natural History.\n", + "8. **Diverse Cuisine**: A melting pot of cultures, offering a wide range of international foods.\n", + "9. **Cultural Diversity**: Known for its diverse population and vibrant cultural scene.\n", + "10. **Brooklyn Bridge**: An iconic suspension bridge connecting Manhattan and Brooklyn.\n", + "\n", + "These are just a few highlights of what makes New York City a unique and exciting place to visit or live.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "where can i find the best bagel?\n", + "\n", + "\n", + "\n", + "00:25:34 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: agent\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is famous for its bagels, and there are several places renowned for serving some of the best. Here are a few top spots where you can find delicious bagels in NYC:\n", + "\n", + "1. **Ess-a-Bagel**: Known for their large, chewy bagels with a variety of spreads and toppings. Locations in Midtown and Gramercy.\n", + "\n", + "2. **Russ & Daughters**: A historic appetizing store on the Lower East Side, famous for its bagels with lox and cream cheese.\n", + "\n", + "3. **Absolute Bagels**: Located on the Upper West Side, this spot is popular for its fresh, fluffy bagels.\n", + "\n", + "4. **Murray’s Bagels**: Known for their traditional, hand-rolled bagels. Located in Greenwich Village.\n", + "\n", + "5. **Tompkins Square Bagels**: Offers a wide selection of bagels and creative cream cheese flavors. Located in the East Village.\n", + "\n", + "6. **Bagel Hole**: A small shop in Park Slope, Brooklyn, known for its classic New York-style bagels.\n", + "\n", + "7. **Leo’s Bagels**: Located in the Financial District, offering a variety of bagels and toppings.\n", + "\n", + "Each of these places has its own unique style and flavor, so it might be worth trying a few to find your personal favorite!\n", + "\n", + "\n", + "\n" + ] + } + ], + "source": [ + "config = {\"configurable\": {\"thread_id\": \"trim-example-2\"}}\n", "\n", "inputs = {\"messages\": [(\"user\", \"What's the weather in NYC?\")]}\n", "result = graph.invoke(inputs, config=config)\n", @@ -536,7 +734,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "394f72f8-f817-472d-a193-e01509a86132", "metadata": {}, "outputs": [], @@ -559,7 +757,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "aa6e4bdf", "metadata": {}, "outputs": [], @@ -580,10 +778,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "b9540c1c-2eba-42da-ba4e-478521161a1f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:35 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:25:35 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:25:35 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:25:35 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_1893/3065461601.py:33: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(\n" + ] + } + ], "source": [ "# highlight-next-line\n", "from langmem.short_term import SummarizationNode\n", @@ -631,12 +848,69 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "8eccaaca-5d9c-4faf-b997-d4b8e84b59ac", "metadata": {}, - "outputs": [], - "source": [ - "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:36 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "00:25:38 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "00:25:47 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/jupyter/venv/lib/python3.11/site-packages/langmem/short_term/summarization.py:246: RuntimeWarning: Failed to trim messages to fit within max_tokens limit before summarization - falling back to the original message list. This may lead to exceeding the context window of the summarization LLM.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:50 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: pre_model_hook\n", + "================================\u001b[1m System Message \u001b[0m================================\n", + "\n", + "Summary of the conversation so far: In our conversation, you initially inquired about the current weather in New York City, and it was noted that it might be cloudy with a chance of rain and temperatures up to 80 degrees. You then asked what NYC is known for, and I provided a list of key features and attractions, including the Statue of Liberty, Times Square, Broadway, Central Park, the Empire State Building, Wall Street, its diverse culture and cuisine, world-class museums, unique neighborhoods, and significant historic sites.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "where can i find the best bagel?\n", + "\n", + "\n", + "\n", + "00:25:56 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Update from node: agent\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is famous for its delicious bagels, and you can find some of the best in various neighborhoods across the city. Here are a few top spots to check out for an amazing bagel:\n", + "\n", + "1. **Ess-a-Bagel**: Known for its large, chewy bagels and generous cream cheese spreads, Ess-a-Bagel is a classic NYC bagel shop with locations in Manhattan.\n", + "\n", + "2. **Russ & Daughters**: This iconic Jewish deli has been serving New Yorkers since 1914. They offer a range of traditional bagels with high-quality toppings like smoked fish and cream cheese.\n", + "\n", + "3. **Bagel Hole**: Located in Brooklyn, Bagel Hole is known for its authentic, no-frills bagels that are often described as perfectly balanced – not too dense, not too fluffy.\n", + "\n", + "4. **Murray's Bagels**: Found in Greenwich Village, Murray's Bagels doesn’t toast their bagels, but their fresh and flavorful offerings make up for it. They have a wide variety of bagels and spreads.\n", + "\n", + "5. **Tompkins Square Bagels**: This spot in the East Village is famous for its creative cream cheese flavors, like sriracha or cannoli, along with its fresh, hand-rolled bagels.\n", + "\n", + "6. **Absolute Bagels**: Located on the Upper West Side, Absolute Bagels is loved for their freshly baked bagels and diverse selection of toppings.\n", + "\n", + "These are just a few of the beloved bagel spots in NYC, offering a variety of flavors, textures, and toppings to satisfy any bagel enthusiast.\n", + "\n", + "\n", + "\n" + ] + } + ], + "source": [ + "config = {\"configurable\": {\"thread_id\": \"summarization-example\"}}\n", "inputs = {\"messages\": [(\"user\", \"What's the weather in NYC?\")]}\n", "\n", "result = graph.invoke(inputs, config=config)\n", @@ -678,4 +952,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/create-react-agent-memory.ipynb b/examples/create-react-agent-memory.ipynb index 0f15e50..24055c4 100644 --- a/examples/create-react-agent-memory.ipynb +++ b/examples/create-react-agent-memory.ipynb @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "a213e11a-5c62-4ddb-a707-490d91add383", "metadata": {}, "outputs": [], @@ -69,10 +69,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "23a1885c-04ab-4750-aefa-105891fddf3e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -109,10 +117,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "7a154152-973e-4b5d-aa13-48c617744a4c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:25:12 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:25:12 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:25:12 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:25:12 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_1924/1444546798.py:39: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " graph = create_react_agent(model, tools=tools, checkpointer=memory)\n" + ] + } + ], "source": [ "# First we initialize the model we want to use.\n", "from langchain_openai import ChatOpenAI\n", @@ -167,7 +194,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "16636975-5f2d-4dc7-ab8e-d0bea0830a28", "metadata": {}, "outputs": [], @@ -183,10 +210,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "9ffff6c3-a4f5-47c9-b51d-97caaee85cd6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What's the weather in NYC?\n", + "00:25:13 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "Tool Calls:\n", + " get_weather (call_3ipbdgl0CGTjmjZmWDzwdDUR)\n", + " Call ID: call_3ipbdgl0CGTjmjZmWDzwdDUR\n", + " Args:\n", + " location: New York City\n", + "=================================\u001b[1m Tool Message \u001b[0m=================================\n", + "Name: get_weather\n", + "\n", + "It might be cloudy in nyc\n", + "00:25:14 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "The weather in New York City might be cloudy.\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "inputs = {\"messages\": [(\"user\", \"What's the weather in NYC?\")]}\n", @@ -204,10 +256,46 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "187479f9-32fa-4611-9487-cf816ba2e147", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "What's it known for?\n", + "00:25:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "New York City is known for many things, including:\n", + "\n", + "1. **Landmarks and Attractions**: The Statue of Liberty, Times Square, Central Park, Empire State Building, and Broadway theaters.\n", + " \n", + "2. **Cultural Diversity**: A melting pot of cultures, languages, and cuisines from around the world.\n", + "\n", + "3. **Financial Hub**: Home to Wall Street and the New York Stock Exchange, making it a global financial center.\n", + "\n", + "4. **Arts and Entertainment**: Renowned museums like the Metropolitan Museum of Art and the Museum of Modern Art, as well as a vibrant music and theater scene.\n", + "\n", + "5. **Fashion**: A major fashion capital, hosting New York Fashion Week and housing numerous designer boutiques.\n", + "\n", + "6. **Cuisine**: Famous for its diverse food scene, including iconic foods like New York-style pizza and bagels.\n", + "\n", + "7. **Media and Publishing**: Headquarters for major media companies and publishers, including The New York Times and NBC.\n", + "\n", + "8. **Skyscrapers**: Known for its impressive skyline, featuring some of the tallest buildings in the world.\n", + "\n", + "9. **Public Transportation**: An extensive subway system that operates 24/7, making it easy to navigate the city.\n", + "\n", + "10. **Sports**: Home to several major sports teams, including the New York Yankees, New York Mets, New York Knicks, and New York Giants.\n", + "\n", + "These are just a few highlights of what makes New York City a unique and vibrant place.\n" + ] + } + ], "source": [ "inputs = {\"messages\": [(\"user\", \"What's it known for?\")]}\n", "print_stream(graph.stream(inputs, config=config, stream_mode=\"values\"))" @@ -238,9 +326,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/cross-thread-persistence-functional.ipynb b/examples/cross-thread-persistence-functional.ipynb index 258b017..a775c36 100644 --- a/examples/cross-thread-persistence-functional.ipynb +++ b/examples/cross-thread-persistence-functional.ipynb @@ -59,20 +59,7 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# IMPORTANT: Clear Redis to remove old checkpoints created with buggy serializer\n", - "import redis\n", - "r = redis.Redis(host=\"redis\", port=6379, decode_responses=False)\n", - "r.flushdb()\n", - "print(\"Redis flushed - ready for fresh execution\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "3457aadf", "metadata": {}, "outputs": [], @@ -83,10 +70,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "aa2c64a7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "ANTHROPIC_API_KEY: ········\n", + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -142,10 +138,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "a7f303d6-612e-4e34-bf36-29d4ed25d802", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:35:16 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", + "00:35:16 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:35:16 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from langgraph.store.redis import RedisStore\n", "from langgraph.store.base import IndexConfig\n", @@ -181,10 +187,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "2a30a362-528c-45ee-9df6-630d2d843588", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:35:16 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:35:16 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:35:16 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:35:16 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "import uuid\n", "\n", @@ -196,7 +213,7 @@ "from langgraph.checkpoint.redis import RedisSaver\n", "from langgraph.store.base import BaseStore\n", "\n", - "model = ChatAnthropic(model=\"claude-3-5-sonnet-latest\")\n", + "model = ChatAnthropic(model=\"claude-sonnet-4-20250514\")\n", "\n", "\n", "@task\n", @@ -268,10 +285,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "c871a073-a466-46ad-aafe-2b870831057e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:35:16 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:16 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:19 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hello Bob! Nice to meet you. I'll remember that your name is Bob. How can I help you today?\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"Hi! Remember: my name is Bob\"}\n", @@ -281,10 +311,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "d862be40-1f8a-4057-81c4-b7bf073dc4c1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:35:19 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:21 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Your name is Bob! How can I help you today, Bob?\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", @@ -302,10 +344,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "76cde493-89cf-4709-a339-207d2b7e9ea7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'data': 'User name is Bob'}\n", + "{'data': 'User name is Bob'}\n", + "{'data': 'User name is Bob'}\n", + "{'data': 'User name is Bob'}\n" + ] + } + ], "source": [ "for memory in redis_store.search((\"memories\", \"1\")):\n", " print(memory.value)" @@ -321,10 +374,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "d362350b-d730-48bd-9652-983812fd7811", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:35:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:24 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "I don't have any information about your name. You haven't introduced yourself to me yet! What would you like me to call you?\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"3\", \"user_id\": \"2\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", @@ -354,4 +419,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/cross-thread-persistence.ipynb b/examples/cross-thread-persistence.ipynb index 091533a..0fa261e 100644 --- a/examples/cross-thread-persistence.ipynb +++ b/examples/cross-thread-persistence.ipynb @@ -132,9 +132,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "20:42:20 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", - "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n" + "00:35:11 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", + "00:35:11 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:35:11 redisvl.index.index INFO Index already exists, not overwriting.\n" ] } ], @@ -181,10 +181,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "20:42:20 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", - "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n", - "20:42:20 redisvl.index.index INFO Index already exists, not overwriting.\n" + "00:35:11 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:35:11 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:35:11 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:35:11 redisvl.index.index INFO Index already exists, not overwriting.\n" ] } ], @@ -197,7 +197,7 @@ "from langgraph.checkpoint.redis import RedisSaver\n", "from langgraph.store.base import BaseStore\n", "\n", - "model = ChatAnthropic(model=\"claude-3-5-sonnet-20241022\")\n", + "model = ChatAnthropic(model=\"claude-sonnet-4-20250514\")\n", "\n", "\n", "# NOTE: we're passing the Store param to the node --\n", @@ -279,37 +279,12 @@ "================================\u001b[1m Human Message \u001b[0m=================================\n", "\n", "Hi! Remember: my name is Bob\n", - "20:42:20 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "20:42:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", - "20:42:21 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 404 Not Found\"\n" - ] - }, - { - "ename": "NotFoundError", - "evalue": "Error code: 404 - {'type': 'error', 'error': {'type': 'not_found_error', 'message': 'model: claude-3-5-sonnet-20241022'}, 'request_id': 'req_011CVE7Pi9nafi1huJ3xWNfm'}", - "output_type": "error", - "traceback": [ - "\u001b[31m---------------------------------------------------------------------------\u001b[39m", - "\u001b[31mNotFoundError\u001b[39m Traceback (most recent call last)", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[5]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m 1\u001b[39m config = {\u001b[33m\"\u001b[39m\u001b[33mconfigurable\u001b[39m\u001b[33m\"\u001b[39m: {\u001b[33m\"\u001b[39m\u001b[33mthread_id\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33m1\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33muser_id\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33m1\u001b[39m\u001b[33m\"\u001b[39m}}\n\u001b[32m 2\u001b[39m input_message = {\u001b[33m\"\u001b[39m\u001b[33mrole\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33muser\u001b[39m\u001b[33m\"\u001b[39m, \u001b[33m\"\u001b[39m\u001b[33mcontent\u001b[39m\u001b[33m\"\u001b[39m: \u001b[33m\"\u001b[39m\u001b[33mHi! Remember: my name is Bob\u001b[39m\u001b[33m\"\u001b[39m}\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m \u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mgraph\u001b[49m\u001b[43m.\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43minput_message\u001b[49m\u001b[43m]\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m=\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mvalues\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 4\u001b[39m \u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[43m-\u001b[49m\u001b[32;43m1\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m.\u001b[49m\u001b[43mpretty_print\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/main.py:2633\u001b[39m, in \u001b[36mPregel.stream\u001b[39m\u001b[34m(self, input, config, context, stream_mode, print_mode, output_keys, interrupt_before, interrupt_after, durability, subgraphs, debug, **kwargs)\u001b[39m\n\u001b[32m 2631\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m task \u001b[38;5;129;01min\u001b[39;00m loop.match_cached_writes():\n\u001b[32m 2632\u001b[39m loop.output_writes(task.id, task.writes, cached=\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[32m-> \u001b[39m\u001b[32m2633\u001b[39m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrunner\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtick\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2634\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43mtasks\u001b[49m\u001b[43m.\u001b[49m\u001b[43mvalues\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m.\u001b[49m\u001b[43mwrites\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2635\u001b[39m \u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mstep_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2636\u001b[39m \u001b[43m \u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m=\u001b[49m\u001b[43mget_waiter\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2637\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mloop\u001b[49m\u001b[43m.\u001b[49m\u001b[43maccept_push\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 2638\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m 2639\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# emit output\u001b[39;49;00m\n\u001b[32m 2640\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01myield from\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m_output\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 2641\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprint_mode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msubgraphs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mqueue\u001b[49m\u001b[43m.\u001b[49m\u001b[43mEmpty\u001b[49m\n\u001b[32m 2642\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 2643\u001b[39m loop.after_tick()\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_runner.py:167\u001b[39m, in \u001b[36mPregelRunner.tick\u001b[39m\u001b[34m(self, tasks, reraise, timeout, retry_policy, get_waiter, schedule_task)\u001b[39m\n\u001b[32m 165\u001b[39m t = tasks[\u001b[32m0\u001b[39m]\n\u001b[32m 166\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m167\u001b[39m \u001b[43mrun_with_retry\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 168\u001b[39m \u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 169\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 170\u001b[39m \u001b[43m \u001b[49m\u001b[43mconfigurable\u001b[49m\u001b[43m=\u001b[49m\u001b[43m{\u001b[49m\n\u001b[32m 171\u001b[39m \u001b[43m \u001b[49m\u001b[43mCONFIG_KEY_CALL\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpartial\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 172\u001b[39m \u001b[43m \u001b[49m\u001b[43m_call\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 173\u001b[39m \u001b[43m \u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mt\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 174\u001b[39m \u001b[43m \u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m=\u001b[49m\u001b[43mretry_policy\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 175\u001b[39m \u001b[43m \u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m=\u001b[49m\u001b[43mweakref\u001b[49m\u001b[43m.\u001b[49m\u001b[43mref\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfutures\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 176\u001b[39m \u001b[43m \u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m=\u001b[49m\u001b[43mschedule_task\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 177\u001b[39m \u001b[43m \u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43msubmit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 178\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 179\u001b[39m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 180\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 181\u001b[39m \u001b[38;5;28mself\u001b[39m.commit(t, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m 182\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/pregel/_retry.py:42\u001b[39m, in \u001b[36mrun_with_retry\u001b[39m\u001b[34m(task, retry_policy, configurable)\u001b[39m\n\u001b[32m 40\u001b[39m task.writes.clear()\n\u001b[32m 41\u001b[39m \u001b[38;5;66;03m# run the task\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m42\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43mproc\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtask\u001b[49m\u001b[43m.\u001b[49m\u001b[43minput\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 43\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m ParentCommand \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[32m 44\u001b[39m ns: \u001b[38;5;28mstr\u001b[39m = config[CONF][CONFIG_KEY_CHECKPOINT_NS]\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:656\u001b[39m, in \u001b[36mRunnableSeq.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 654\u001b[39m \u001b[38;5;66;03m# run in context\u001b[39;00m\n\u001b[32m 655\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m set_config_context(config, run) \u001b[38;5;28;01mas\u001b[39;00m context:\n\u001b[32m--> \u001b[39m\u001b[32m656\u001b[39m \u001b[38;5;28minput\u001b[39m = \u001b[43mcontext\u001b[49m\u001b[43m.\u001b[49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstep\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 657\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 658\u001b[39m \u001b[38;5;28minput\u001b[39m = step.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langgraph/_internal/_runnable.py:400\u001b[39m, in \u001b[36mRunnableCallable.invoke\u001b[39m\u001b[34m(self, input, config, **kwargs)\u001b[39m\n\u001b[32m 398\u001b[39m run_manager.on_chain_end(ret)\n\u001b[32m 399\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m400\u001b[39m ret = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 401\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.recurse \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, Runnable):\n\u001b[32m 402\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m ret.invoke(\u001b[38;5;28minput\u001b[39m, config)\n", - "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[4]\u001b[39m\u001b[32m, line 27\u001b[39m, in \u001b[36mcall_model\u001b[39m\u001b[34m(state, config, store)\u001b[39m\n\u001b[32m 24\u001b[39m memory = \u001b[33m\"\u001b[39m\u001b[33mUser name is Bob\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m 25\u001b[39m store.put(namespace, \u001b[38;5;28mstr\u001b[39m(uuid.uuid4()), {\u001b[33m\"\u001b[39m\u001b[33mdata\u001b[39m\u001b[33m\"\u001b[39m: memory})\n\u001b[32m---> \u001b[39m\u001b[32m27\u001b[39m response = \u001b[43mmodel\u001b[49m\u001b[43m.\u001b[49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 28\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43m{\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrole\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43msystem\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mcontent\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43msystem_msg\u001b[49m\u001b[43m}\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[43m+\u001b[49m\u001b[43m \u001b[49m\u001b[43mstate\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 29\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 30\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m {\u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m: response}\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:385\u001b[39m, in \u001b[36mBaseChatModel.invoke\u001b[39m\u001b[34m(self, input, config, stop, **kwargs)\u001b[39m\n\u001b[32m 371\u001b[39m \u001b[38;5;129m@override\u001b[39m\n\u001b[32m 372\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34minvoke\u001b[39m(\n\u001b[32m 373\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 378\u001b[39m **kwargs: Any,\n\u001b[32m 379\u001b[39m ) -> AIMessage:\n\u001b[32m 380\u001b[39m config = ensure_config(config)\n\u001b[32m 381\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cast(\n\u001b[32m 382\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mAIMessage\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 383\u001b[39m cast(\n\u001b[32m 384\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mChatGeneration\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m--> \u001b[39m\u001b[32m385\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mgenerate_prompt\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 386\u001b[39m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_convert_input\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 387\u001b[39m \u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 388\u001b[39m \u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mcallbacks\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 389\u001b[39m \u001b[43m \u001b[49m\u001b[43mtags\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtags\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 390\u001b[39m \u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmetadata\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 391\u001b[39m \u001b[43m \u001b[49m\u001b[43mrun_name\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrun_name\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 392\u001b[39m \u001b[43m \u001b[49m\u001b[43mrun_id\u001b[49m\u001b[43m=\u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m.\u001b[49m\u001b[43mpop\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mrun_id\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 393\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 394\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m.generations[\u001b[32m0\u001b[39m][\u001b[32m0\u001b[39m],\n\u001b[32m 395\u001b[39m ).message,\n\u001b[32m 396\u001b[39m )\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:1104\u001b[39m, in \u001b[36mBaseChatModel.generate_prompt\u001b[39m\u001b[34m(self, prompts, stop, callbacks, **kwargs)\u001b[39m\n\u001b[32m 1095\u001b[39m \u001b[38;5;129m@override\u001b[39m\n\u001b[32m 1096\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mgenerate_prompt\u001b[39m(\n\u001b[32m 1097\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 1101\u001b[39m **kwargs: Any,\n\u001b[32m 1102\u001b[39m ) -> LLMResult:\n\u001b[32m 1103\u001b[39m prompt_messages = [p.to_messages() \u001b[38;5;28;01mfor\u001b[39;00m p \u001b[38;5;129;01min\u001b[39;00m prompts]\n\u001b[32m-> \u001b[39m\u001b[32m1104\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mgenerate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprompt_messages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m=\u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:914\u001b[39m, in \u001b[36mBaseChatModel.generate\u001b[39m\u001b[34m(self, messages, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)\u001b[39m\n\u001b[32m 911\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m i, m \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(input_messages):\n\u001b[32m 912\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m 913\u001b[39m results.append(\n\u001b[32m--> \u001b[39m\u001b[32m914\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_generate_with_cache\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 915\u001b[39m \u001b[43m \u001b[49m\u001b[43mm\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 916\u001b[39m \u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 917\u001b[39m \u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrun_managers\u001b[49m\u001b[43m[\u001b[49m\u001b[43mi\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrun_managers\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 918\u001b[39m \u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 919\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 920\u001b[39m )\n\u001b[32m 921\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 922\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m run_managers:\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:1208\u001b[39m, in \u001b[36mBaseChatModel._generate_with_cache\u001b[39m\u001b[34m(self, messages, stop, run_manager, **kwargs)\u001b[39m\n\u001b[32m 1206\u001b[39m result = generate_from_stream(\u001b[38;5;28miter\u001b[39m(chunks))\n\u001b[32m 1207\u001b[39m \u001b[38;5;28;01melif\u001b[39;00m inspect.signature(\u001b[38;5;28mself\u001b[39m._generate).parameters.get(\u001b[33m\"\u001b[39m\u001b[33mrun_manager\u001b[39m\u001b[33m\"\u001b[39m):\n\u001b[32m-> \u001b[39m\u001b[32m1208\u001b[39m result = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_generate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 1209\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\n\u001b[32m 1210\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1211\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 1212\u001b[39m result = \u001b[38;5;28mself\u001b[39m._generate(messages, stop=stop, **kwargs)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_anthropic/chat_models.py:1866\u001b[39m, in \u001b[36mChatAnthropic._generate\u001b[39m\u001b[34m(self, messages, stop, run_manager, **kwargs)\u001b[39m\n\u001b[32m 1864\u001b[39m payload = \u001b[38;5;28mself\u001b[39m._get_request_payload(messages, stop=stop, **kwargs)\n\u001b[32m 1865\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1866\u001b[39m data = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_create\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpayload\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 1867\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m anthropic.BadRequestError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[32m 1868\u001b[39m _handle_anthropic_bad_request(e)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/langchain_anthropic/chat_models.py:1728\u001b[39m, in \u001b[36mChatAnthropic._create\u001b[39m\u001b[34m(self, payload)\u001b[39m\n\u001b[32m 1726\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[33m\"\u001b[39m\u001b[33mbetas\u001b[39m\u001b[33m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m payload:\n\u001b[32m 1727\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._client.beta.messages.create(**payload)\n\u001b[32m-> \u001b[39m\u001b[32m1728\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_client\u001b[49m\u001b[43m.\u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m.\u001b[49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mpayload\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/_utils/_utils.py:282\u001b[39m, in \u001b[36mrequired_args..inner..wrapper\u001b[39m\u001b[34m(*args, **kwargs)\u001b[39m\n\u001b[32m 280\u001b[39m msg = \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mMissing required argument: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mquote(missing[\u001b[32m0\u001b[39m])\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m\"\u001b[39m\n\u001b[32m 281\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[32m--> \u001b[39m\u001b[32m282\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/resources/messages/messages.py:930\u001b[39m, in \u001b[36mMessages.create\u001b[39m\u001b[34m(self, max_tokens, messages, model, metadata, service_tier, stop_sequences, stream, system, temperature, thinking, tool_choice, tools, top_k, top_p, extra_headers, extra_query, extra_body, timeout)\u001b[39m\n\u001b[32m 923\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m model \u001b[38;5;129;01min\u001b[39;00m DEPRECATED_MODELS:\n\u001b[32m 924\u001b[39m warnings.warn(\n\u001b[32m 925\u001b[39m \u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mThe model \u001b[39m\u001b[33m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmodel\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m'\u001b[39m\u001b[33m is deprecated and will reach end-of-life on \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mDEPRECATED_MODELS[model]\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m.\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mPlease migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.\u001b[39m\u001b[33m\"\u001b[39m,\n\u001b[32m 926\u001b[39m \u001b[38;5;167;01mDeprecationWarning\u001b[39;00m,\n\u001b[32m 927\u001b[39m stacklevel=\u001b[32m3\u001b[39m,\n\u001b[32m 928\u001b[39m )\n\u001b[32m--> \u001b[39m\u001b[32m930\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_post\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 931\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m/v1/messages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m 932\u001b[39m \u001b[43m \u001b[49m\u001b[43mbody\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmaybe_transform\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 933\u001b[39m \u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[32m 934\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmax_tokens\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_tokens\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 935\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmessages\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 936\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmodel\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 937\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mmetadata\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 938\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mservice_tier\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mservice_tier\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 939\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mstop_sequences\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstop_sequences\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 940\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mstream\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 941\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43msystem\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43msystem\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 942\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtemperature\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 943\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mthinking\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mthinking\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 944\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtool_choice\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtool_choice\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 945\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtools\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtools\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 946\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtop_k\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtop_k\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 947\u001b[39m \u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mtop_p\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mtop_p\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 948\u001b[39m \u001b[43m \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 949\u001b[39m \u001b[43m \u001b[49m\u001b[43mmessage_create_params\u001b[49m\u001b[43m.\u001b[49m\u001b[43mMessageCreateParamsStreaming\u001b[49m\n\u001b[32m 950\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\n\u001b[32m 951\u001b[39m \u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mmessage_create_params\u001b[49m\u001b[43m.\u001b[49m\u001b[43mMessageCreateParamsNonStreaming\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 952\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 953\u001b[39m \u001b[43m \u001b[49m\u001b[43moptions\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmake_request_options\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m 954\u001b[39m \u001b[43m \u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_headers\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_query\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_query\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextra_body\u001b[49m\u001b[43m=\u001b[49m\u001b[43mextra_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m=\u001b[49m\u001b[43mtimeout\u001b[49m\n\u001b[32m 955\u001b[39m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 956\u001b[39m \u001b[43m \u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m=\u001b[49m\u001b[43mMessage\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 957\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[32m 958\u001b[39m \u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m=\u001b[49m\u001b[43mStream\u001b[49m\u001b[43m[\u001b[49m\u001b[43mRawMessageStreamEvent\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m 959\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/_base_client.py:1326\u001b[39m, in \u001b[36mSyncAPIClient.post\u001b[39m\u001b[34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[39m\n\u001b[32m 1312\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mpost\u001b[39m(\n\u001b[32m 1313\u001b[39m \u001b[38;5;28mself\u001b[39m,\n\u001b[32m 1314\u001b[39m path: \u001b[38;5;28mstr\u001b[39m,\n\u001b[32m (...)\u001b[39m\u001b[32m 1321\u001b[39m stream_cls: \u001b[38;5;28mtype\u001b[39m[_StreamT] | \u001b[38;5;28;01mNone\u001b[39;00m = \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[32m 1322\u001b[39m ) -> ResponseT | _StreamT:\n\u001b[32m 1323\u001b[39m opts = FinalRequestOptions.construct(\n\u001b[32m 1324\u001b[39m method=\u001b[33m\"\u001b[39m\u001b[33mpost\u001b[39m\u001b[33m\"\u001b[39m, url=path, json_data=body, files=to_httpx_files(files), **options\n\u001b[32m 1325\u001b[39m )\n\u001b[32m-> \u001b[39m\u001b[32m1326\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m cast(ResponseT, \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcast_to\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mopts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m=\u001b[49m\u001b[43mstream_cls\u001b[49m\u001b[43m)\u001b[49m)\n", - "\u001b[36mFile \u001b[39m\u001b[32m~/venv/lib/python3.11/site-packages/anthropic/_base_client.py:1114\u001b[39m, in \u001b[36mSyncAPIClient.request\u001b[39m\u001b[34m(self, cast_to, options, stream, stream_cls)\u001b[39m\n\u001b[32m 1111\u001b[39m err.response.read()\n\u001b[32m 1113\u001b[39m log.debug(\u001b[33m\"\u001b[39m\u001b[33mRe-raising status error\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m-> \u001b[39m\u001b[32m1114\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m._make_status_error_from_response(err.response) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m 1116\u001b[39m \u001b[38;5;28;01mbreak\u001b[39;00m\n\u001b[32m 1118\u001b[39m \u001b[38;5;28;01massert\u001b[39;00m response \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m, \u001b[33m\"\u001b[39m\u001b[33mcould not resolve response (should never happen)\u001b[39m\u001b[33m\"\u001b[39m\n", - "\u001b[31mNotFoundError\u001b[39m: Error code: 404 - {'type': 'error', 'error': {'type': 'not_found_error', 'message': 'model: claude-3-5-sonnet-20241022'}, 'request_id': 'req_011CVE7Pi9nafi1huJ3xWNfm'}", - "During task with name 'call_model' and id '406a4cea-f81e-7b24-dad8-892c428325df'" + "00:35:12 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:12 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:14 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hi Bob! Nice to meet you. I'll remember that your name is Bob. How are you doing today?\n" ] } ], @@ -322,10 +297,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "d862be40-1f8a-4057-81c4-b7bf073dc4c1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what is my name?\n", + "00:35:15 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:17 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Your name is Bob.\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\", \"user_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", @@ -343,10 +333,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "76cde493-89cf-4709-a339-207d2b7e9ea7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'data': 'User name is Bob'}\n", + "{'data': 'User name is Bob'}\n", + "{'data': 'User name is Bob'}\n", + "{'data': 'User name is Bob'}\n" + ] + } + ], "source": [ "for memory in redis_store.search((\"memories\", \"1\")):\n", " print(memory.value)" @@ -362,10 +363,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "d362350b-d730-48bd-9652-983812fd7811", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what is my name?\n", + "00:35:18 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:35:19 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "I don't have any information about your name. Could you please tell me what you'd like me to call you?\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"3\", \"user_id\": \"2\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"what is my name?\"}\n", diff --git a/examples/memory/add-summary-conversation-history.ipynb b/examples/memory/add-summary-conversation-history.ipynb index 13f9f87..55a70ab 100644 --- a/examples/memory/add-summary-conversation-history.ipynb +++ b/examples/memory/add-summary-conversation-history.ipynb @@ -30,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -49,10 +49,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "ANTHROPIC_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -91,10 +99,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "378899a9-3b9a-4748-95b6-eb00e0828677", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:42:58 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:42:58 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:42:58 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:42:58 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from typing import Literal\n", "\n", @@ -204,7 +223,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "dc697132-8fa1-4bf5-9722-56a9859331ab", "metadata": {}, "outputs": [], @@ -219,10 +238,68 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "57b27553-21be-43e5-ac48-d1d0a3aa0dca", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "hi! I'm bob\n", + "00:42:59 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hi Bob! Nice to meet you. I'm Claude, an AI assistant created by Anthropic. How are you doing today? Let me know if you have any questions or if there's anything I can help you with.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what's my name?\n", + "00:42:59 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Your name is Bob, as you told me earlier in our conversation.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "i like the celtics!\n", + "00:43:00 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "That's great, I'm glad you like the Celtics! Basketball is a really exciting sport to follow. Do you have a favorite player on the Celtics team? I'd be curious to hear more about what you enjoy about watching them play.\n", + "00:43:02 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "Here is a summary of our conversation so far:\n", + "\n", + "The conversation started with you asking about the weather in San Francisco, to which I incorrectly responded that it was sunny in Los Angeles. \n", + "\n", + "You then introduced yourself as Bob, and I greeted you and explained that I am an AI assistant named Claude.\n", + "\n", + "You asked me what your name was, and I correctly recalled that you had introduced yourself as Bob earlier.\n", + "\n", + "Finally, you expressed that you like the Boston Celtics basketball team, and I asked if you had a favorite player on the team, showing interest in learning more about your fandom.\n", + "\n", + "The key points are your name is Bob, you're a fan of the Celtics, and we had a bit of back-and-forth as I introduced myself as an AI assistant named Claude.\n" + ] + } + ], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -253,10 +330,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "935265a0-d511-475a-8a0d-b3c3cc5e42a0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'messages': [HumanMessage(content='i like the celtics!', additional_kwargs={}, response_metadata={}, id='95a53b16-7630-466e-be0a-896bbd58bc06'),\n", + " AIMessage(content=\"That's great, I'm glad you like the Celtics! Basketball is a really exciting sport to follow. Do you have a favorite player on the Celtics team? I'd be curious to hear more about what you enjoy about watching them play.\", additional_kwargs={}, response_metadata={'id': 'msg_0183Pgv8iMvNtpwmT8PbbgMT', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 113, 'output_tokens': 55, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--2e844ea2-d3c2-4f6b-87f7-0e17517c7a62-0', usage_metadata={'input_tokens': 113, 'output_tokens': 55, 'total_tokens': 168, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}})],\n", + " 'summary': \"Here is a summary of our conversation so far:\\n\\nThe conversation started with you asking about the weather in San Francisco, to which I incorrectly responded that it was sunny in Los Angeles. \\n\\nYou then introduced yourself as Bob, and I greeted you and explained that I am an AI assistant named Claude.\\n\\nYou asked me what your name was, and I correctly recalled that you had introduced yourself as Bob earlier.\\n\\nFinally, you expressed that you like the Boston Celtics basketball team, and I asked if you had a favorite player on the team, showing interest in learning more about your fandom.\\n\\nThe key points are your name is Bob, you're a fan of the Celtics, and we had a bit of back-and-forth as I introduced myself as an AI assistant named Claude.\"}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "values = app.get_state(config).values\n", "values" @@ -272,10 +362,34 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "048805a4-3d97-4e76-ac45-8d80d4364c46", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "i like how much they win\n", + "00:43:04 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "That's a good point about the Celtics - they have been a very successful franchise over the years. A few thoughts on their winning ways:\n", + "\n", + "- The Celtics are one of the most storied franchises in the NBA, with 17 championship titles, the most of any team. Their history of winning is impressive.\n", + "\n", + "- This season, the Celtics have the best record in the Eastern Conference and are contending for another title. Their consistent ability to compete for championships year after year is admirable.\n", + "\n", + "- Players like Jayson Tatum and Jaylen Brown have emerged as elite talents, helping keep the Celtics among the NBA's elite teams. Their young core has a lot of potential.\n", + "\n", + "- Coaching stability with Brad Stevens and now Joe Mazzulla has allowed the Celtics to maintain their high level of play over time.\n", + "\n", + "I can see why you enjoy following a team that wins as much as the Celtics do. Their sustained success and ability to compete for championships must make them very fun to root for. Do you have a favorite Celtics championship team or season from their history?\n" + ] + } + ], "source": [ "input_message = HumanMessage(content=\"i like how much they win\")\n", "input_message.pretty_print()\n", @@ -293,10 +407,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "09ebb693-4738-4474-a095-6491def5c5f9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'messages': [HumanMessage(content='i like the celtics!', additional_kwargs={}, response_metadata={}, id='95a53b16-7630-466e-be0a-896bbd58bc06'),\n", + " AIMessage(content=\"That's great, I'm glad you like the Celtics! Basketball is a really exciting sport to follow. Do you have a favorite player on the Celtics team? I'd be curious to hear more about what you enjoy about watching them play.\", additional_kwargs={}, response_metadata={'id': 'msg_0183Pgv8iMvNtpwmT8PbbgMT', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 113, 'output_tokens': 55, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--2e844ea2-d3c2-4f6b-87f7-0e17517c7a62-0', usage_metadata={'input_tokens': 113, 'output_tokens': 55, 'total_tokens': 168, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}}),\n", + " HumanMessage(content='i like how much they win', additional_kwargs={}, response_metadata={}, id='3d4a2b4f-a111-42de-a382-d59e90389a2f'),\n", + " AIMessage(content=\"That's a good point about the Celtics - they have been a very successful franchise over the years. A few thoughts on their winning ways:\\n\\n- The Celtics are one of the most storied franchises in the NBA, with 17 championship titles, the most of any team. Their history of winning is impressive.\\n\\n- This season, the Celtics have the best record in the Eastern Conference and are contending for another title. Their consistent ability to compete for championships year after year is admirable.\\n\\n- Players like Jayson Tatum and Jaylen Brown have emerged as elite talents, helping keep the Celtics among the NBA's elite teams. Their young core has a lot of potential.\\n\\n- Coaching stability with Brad Stevens and now Joe Mazzulla has allowed the Celtics to maintain their high level of play over time.\\n\\nI can see why you enjoy following a team that wins as much as the Celtics do. Their sustained success and ability to compete for championships must make them very fun to root for. Do you have a favorite Celtics championship team or season from their history?\", additional_kwargs={}, response_metadata={'id': 'msg_01SQizVtWWsq9zAnBW6Jg4Ub', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 249, 'output_tokens': 240, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--a87a6f62-2eba-4d8b-9165-96a4f76ccd0e-0', usage_metadata={'input_tokens': 249, 'output_tokens': 240, 'total_tokens': 489, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}})],\n", + " 'summary': \"Here is a summary of our conversation so far:\\n\\nThe conversation started with you asking about the weather in San Francisco, to which I incorrectly responded that it was sunny in Los Angeles. \\n\\nYou then introduced yourself as Bob, and I greeted you and explained that I am an AI assistant named Claude.\\n\\nYou asked me what your name was, and I correctly recalled that you had introduced yourself as Bob earlier.\\n\\nFinally, you expressed that you like the Boston Celtics basketball team, and I asked if you had a favorite player on the team, showing interest in learning more about your fandom.\\n\\nThe key points are your name is Bob, you're a fan of the Celtics, and we had a bit of back-and-forth as I introduced myself as an AI assistant named Claude.\"}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "values = app.get_state(config).values\n", "values" @@ -312,10 +441,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "7094c5ab-66f8-42ff-b1c3-90c8a9468e62", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what's my name?\n", + "00:43:04 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "I apologize, I don't actually remember your name. Earlier in our conversation you introduced yourself as Bob, but I don't have that information stored currently. What is your name?\n" + ] + } + ], "source": [ "input_message = HumanMessage(content=\"what's my name?\")\n", "input_message.pretty_print()\n", @@ -325,10 +468,58 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "40e5db8e-9db9-4ac7-9d76-a99fd4034bf3", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what NFL team do you think I like?\n", + "00:43:06 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hmm, without any additional context about your preferences, it's hard for me to confidently guess which NFL team you might like. Since you've expressed interest in the Boston Celtics basketball team, one possibility could be that you're a fan of a New England-based NFL team, like the Patriots. But I don't want to assume that without more information from you. What NFL team do you actually support?\n", + "00:43:08 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "================================\u001b[1m Remove Message \u001b[0m================================\n", + "\n", + "\n", + "Okay, got it. Let me summarize our conversation so far, including the latest exchange:\n", + "\n", + "The conversation started with me incorrectly stating the weather in Los Angeles when you asked about San Francisco. \n", + "\n", + "You then introduced yourself as Bob, and I greeted you and explained that I am an AI assistant named Claude.\n", + "\n", + "You expressed that you like the Boston Celtics basketball team, and I asked if you had a favorite player or Celtics team. \n", + "\n", + "You said you like how much the Celtics win, and we discussed their history of success and sustained competitiveness.\n", + "\n", + "You then asked what your name was, and I correctly recalled that you had introduced yourself as Bob earlier.\n", + "\n", + "Finally, you asked what NFL team I think you might like, but I explained I didn't have enough information to guess that without more context about your preferences.\n", + "\n", + "So in summary, the key points are you are a fan of the Boston Celtics, your name is Bob, and we've had a friendly back-and-forth as I've tried to have a natural conversation with you as an AI assistant. Please let me know if I'm missing or misstating anything from our discussion so far.\n" + ] + } + ], "source": [ "input_message = HumanMessage(content=\"what NFL team do you think I like?\")\n", "input_message.pretty_print()\n", @@ -338,10 +529,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "0a1a0fda-5309-45f0-9465-9f3dff604d74", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "i like the patriots!\n", + "00:43:10 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Ah I see, that's a great guess on my part then! I suspected you might be a Patriots fan since they are the NFL team based in the New England region, just like your favorite basketball team the Boston Celtics.\n", + "\n", + "The Patriots have been one of the most successful and consistently competitive NFL franchises over the past couple of decades, so it makes a lot of sense that you would be a fan of theirs. They've won 6 Super Bowls since 2001, establishing an impressive dynasty under head coach Bill Belichick and star quarterback Tom Brady.\n", + "\n", + "I'm glad I was able to correctly deduce that the Patriots are likely your preferred NFL team based on your affinity for the Boston Celtics. It's always satisfying when an AI assistant can make an accurate inference about a user's preferences and interests. Let me know if you have any other thoughts on the Patriots or the NFL in general!\n" + ] + } + ], "source": [ "input_message = HumanMessage(content=\"i like the patriots!\")\n", "input_message.pretty_print()\n", @@ -366,9 +575,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/memory/delete-messages.ipynb b/examples/memory/delete-messages.ipynb index ed1a997..62ce4c9 100644 --- a/examples/memory/delete-messages.ipynb +++ b/examples/memory/delete-messages.ipynb @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -47,10 +47,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "ANTHROPIC_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -88,10 +96,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "378899a9-3b9a-4748-95b6-eb00e0828677", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:42:29 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:42:29 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:42:29 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:42:29 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from typing import Literal\n", "\n", @@ -175,10 +194,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "57b27553-21be-43e5-ac48-d1d0a3aa0dca", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "hi! I'm bob\n", + "00:42:30 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hi there! It's nice to meet you Bob. How are you doing today?\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what's my name?\n", + "00:42:31 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "You said your name is Bobhi, but then you said \"I'm bob\". So I'm not entirely sure which name you prefer to go by - Bobhi or Bob. Could you please clarify which name you would like me to call you?\n" + ] + } + ], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -204,10 +244,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "8a850529-d038-48f7-b5a2-8d4d2923f83a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'),\n", + " HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be'),\n", + " AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='86510037-f2d0-452f-b007-d335fa4d6482'),\n", + " HumanMessage(content=\"hi! I'm bob\", additional_kwargs={}, response_metadata={}, id='1ae41bbc-7e24-4f7e-977c-1b3fdcc32b17'),\n", + " HumanMessage(content=\"hi! I'm bob\", additional_kwargs={}, response_metadata={}, id='a2bfd9d6-eb79-4a4e-8442-e24f2e2aeaa0'),\n", + " AIMessage(content=\"Hi there! It's nice to meet you Bob. How are you doing today?\", additional_kwargs={}, response_metadata={'id': 'msg_017s4qmQuzYRURfeKbSBBrg2', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 38, 'output_tokens': 20, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--30df87d3-74c8-440b-b276-9f148dd51103-0', usage_metadata={'input_tokens': 38, 'output_tokens': 20, 'total_tokens': 58, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}}),\n", + " HumanMessage(content=\"what's my name?\", additional_kwargs={}, response_metadata={}, id='5f52b451-f3da-4f99-b19a-6a36b18707ea'),\n", + " AIMessage(content='You said your name is Bobhi, but then you said \"I\\'m bob\". So I\\'m not entirely sure which name you prefer to go by - Bobhi or Bob. Could you please clarify which name you would like me to call you?', additional_kwargs={}, response_metadata={'id': 'msg_019TGAG3hZeYU3CNEQhrTCg6', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 66, 'output_tokens': 56, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--766d6be9-a776-41c7-a4a3-0d74ea1b56bb-0', usage_metadata={'input_tokens': 66, 'output_tokens': 56, 'total_tokens': 122, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}})]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "messages = app.get_state(config).values[\"messages\"]\n", "messages" @@ -223,10 +281,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "df1a0970-7e64-4170-beef-2855d10eef42", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'configurable': {'thread_id': '2',\n", + " 'checkpoint_ns': '',\n", + " 'checkpoint_id': '1f0c4177-727b-6981-800e-48d86665e9b9'}}" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from langchain_core.messages import RemoveMessage\n", "\n", @@ -243,10 +314,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "8bfe4ffa-e170-43bc-aec4-6e36ac620931", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be'),\n", + " AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='86510037-f2d0-452f-b007-d335fa4d6482'),\n", + " HumanMessage(content=\"hi! I'm bob\", additional_kwargs={}, response_metadata={}, id='1ae41bbc-7e24-4f7e-977c-1b3fdcc32b17'),\n", + " HumanMessage(content=\"hi! I'm bob\", additional_kwargs={}, response_metadata={}, id='a2bfd9d6-eb79-4a4e-8442-e24f2e2aeaa0'),\n", + " AIMessage(content=\"Hi there! It's nice to meet you Bob. How are you doing today?\", additional_kwargs={}, response_metadata={'id': 'msg_017s4qmQuzYRURfeKbSBBrg2', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 38, 'output_tokens': 20, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--30df87d3-74c8-440b-b276-9f148dd51103-0', usage_metadata={'input_tokens': 38, 'output_tokens': 20, 'total_tokens': 58, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}}),\n", + " HumanMessage(content=\"what's my name?\", additional_kwargs={}, response_metadata={}, id='5f52b451-f3da-4f99-b19a-6a36b18707ea'),\n", + " AIMessage(content='You said your name is Bobhi, but then you said \"I\\'m bob\". So I\\'m not entirely sure which name you prefer to go by - Bobhi or Bob. Could you please clarify which name you would like me to call you?', additional_kwargs={}, response_metadata={'id': 'msg_019TGAG3hZeYU3CNEQhrTCg6', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 66, 'output_tokens': 56, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--766d6be9-a776-41c7-a4a3-0d74ea1b56bb-0', usage_metadata={'input_tokens': 66, 'output_tokens': 56, 'total_tokens': 122, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}})]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "messages = app.get_state(config).values[\"messages\"]\n", "messages" @@ -264,10 +352,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "bb22ede0-e153-4fd0-a4c0-f9af2f7663b1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:42:31 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:42:31 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:42:31 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:42:31 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from langchain_core.messages import RemoveMessage\n", "from langgraph.graph import END\n", @@ -329,10 +428,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "3975f34c-c243-40ea-b9d2-424d50a48dc9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[('human', \"what's the weather in sf\"), ('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\")]\n", + "00:42:31 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "[('human', \"what's the weather in sf\"), ('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Nice to meet you, Bob! As an AI assistant, I don't have a physical form, but I'm happy to chat and help out however I can. Please let me know if you have any questions or if there's anything I can assist you with.\")]\n", + "[('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Nice to meet you, Bob! As an AI assistant, I don't have a physical form, but I'm happy to chat and help out however I can. Please let me know if you have any questions or if there's anything I can assist you with.\")]\n", + "[('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Nice to meet you, Bob! As an AI assistant, I don't have a physical form, but I'm happy to chat and help out however I can. Please let me know if you have any questions or if there's anything I can assist you with.\"), ('human', \"what's my name?\")]\n", + "00:42:32 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "[('ai', \"It's sunny in San Francisco!\"), ('human', \"hi! I'm bob\"), ('ai', \"Nice to meet you, Bob! As an AI assistant, I don't have a physical form, but I'm happy to chat and help out however I can. Please let me know if you have any questions or if there's anything I can assist you with.\"), ('human', \"what's my name?\"), ('ai', 'You just told me your name is Bob.')]\n", + "[('ai', \"Nice to meet you, Bob! As an AI assistant, I don't have a physical form, but I'm happy to chat and help out however I can. Please let me know if you have any questions or if there's anything I can assist you with.\"), ('human', \"what's my name?\"), ('ai', 'You just told me your name is Bob.')]\n" + ] + } + ], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -356,10 +470,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "a3e15abb-81d8-4072-9f10-61ae0fd61dac", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[AIMessage(content=\"Nice to meet you, Bob! As an AI assistant, I don't have a physical form, but I'm happy to chat and help out however I can. Please let me know if you have any questions or if there's anything I can assist you with.\", additional_kwargs={}, response_metadata={'id': 'msg_01Mj7ySSpyuJ2WDLwKP2BRzx', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 31, 'output_tokens': 56, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--a0533b69-48a1-4eff-8ab7-1d481d70eddc-0', usage_metadata={'input_tokens': 31, 'output_tokens': 56, 'total_tokens': 87, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}}),\n", + " HumanMessage(content=\"what's my name?\", additional_kwargs={}, response_metadata={}, id='f86a5f02-10d3-4411-873e-fe467ba992dd'),\n", + " AIMessage(content='You just told me your name is Bob.', additional_kwargs={}, response_metadata={'id': 'msg_01BTHe5pJ4PnJfFEAhwTRjqB', 'model': 'claude-3-haiku-20240307', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'cache_creation': {'ephemeral_1h_input_tokens': 0, 'ephemeral_5m_input_tokens': 0}, 'cache_creation_input_tokens': 0, 'cache_read_input_tokens': 0, 'input_tokens': 98, 'output_tokens': 12, 'server_tool_use': None, 'service_tier': 'standard'}, 'model_name': 'claude-3-haiku-20240307', 'model_provider': 'anthropic'}, id='lc_run--d479edfe-b6bf-4e9b-8cfe-271673012c6b-0', usage_metadata={'input_tokens': 98, 'output_tokens': 12, 'total_tokens': 110, 'input_token_details': {'cache_creation': 0, 'cache_read': 0, 'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}})]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "messages = app.get_state(config).values[\"messages\"]\n", "messages" @@ -390,9 +517,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/memory/manage-conversation-history.ipynb b/examples/memory/manage-conversation-history.ipynb index 72509b6..c439df8 100644 --- a/examples/memory/manage-conversation-history.ipynb +++ b/examples/memory/manage-conversation-history.ipynb @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -46,10 +46,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "ANTHROPIC_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -87,10 +95,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "378899a9-3b9a-4748-95b6-eb00e0828677", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:43:40 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:43:40 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:43:40 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:43:40 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "\n", "\n", @@ -174,10 +193,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "57b27553-21be-43e5-ac48-d1d0a3aa0dca", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "hi! I'm bob\n", + "00:43:41 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Okay, got it! It's nice to meet you Bob. Thanks for clarifying your name. How are you doing today?\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what's my name?\n", + "00:43:41 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Based on our conversation, your name is Bob. You've told me twice now that your name is Bob, so I will refer to you as Bob going forward.\n" + ] + } + ], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -203,10 +243,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "eb20430f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:43:41 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:43:41 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:43:41 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:43:41 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "\n", "\n", @@ -296,10 +347,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "52468ebb-4b23-45ac-a98e-b4439f37740a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "hi! I'm bob\n", + "00:43:42 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "It's nice to meet you, Bob! As an AI assistant, I'm here to help you with any questions or tasks you may have. Please feel free to ask me anything, and I'll do my best to assist you.\n", + "================================\u001b[1m Human Message \u001b[0m=================================\n", + "\n", + "what's my name?\n", + "00:43:43 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "I'm afraid I don't actually know your name. As an AI assistant, I don't have any specific information about you or your name unless you provide that to me directly.\n" + ] + } + ], "source": [ "from langchain_core.messages import HumanMessage\n", "\n", @@ -343,9 +415,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/memory/semantic-search.ipynb b/examples/memory/semantic-search.ipynb index 9bfd3fa..36f55f6 100644 --- a/examples/memory/semantic-search.ipynb +++ b/examples/memory/semantic-search.ipynb @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -26,9 +26,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -51,9 +59,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:20 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n" + ] + } + ], "source": [ "from langchain.embeddings import init_embeddings\n", "from langgraph.store.redis import RedisStore\n", @@ -93,9 +109,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:22 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n" + ] + } + ], "source": [ "# Store some memories\n", "store.put((\"user_123\", \"memories\"), \"1\", {\"text\": \"I love pizza\"})\n", @@ -114,9 +142,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:22 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Memory: I prefer Italian food (similarity: 0.464826762676)\n", + "Memory: I love pizza (similarity: 0.35514843463900003)\n", + "Memory: I am a plumber (similarity: 0.15569871664)\n" + ] + } + ], "source": [ "# Find memories about food preferences\n", "memories = store.search((\"user_123\", \"memories\"), query=\"I like food?\", limit=5)\n", @@ -136,9 +175,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:22 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:44:22 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:22 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:22 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:22 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:23 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "What are you in the mood for? Since you love Italian food and pizza, would you like to order a pizza or perhaps make one at home?" + ] + } + ], "source": [ "\n", "\n", @@ -200,9 +253,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:24 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:44:24 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:24 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:24 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_3503/975175168.py:50: LangGraphDeprecatedSinceV10: create_react_agent has been moved to `langchain.agents`. Please update your import to `from langchain.agents import create_agent`. Deprecated in LangGraph V1.0 to be removed in V2.0.\n", + " agent = create_react_agent(\n" + ] + } + ], "source": [ "import uuid\n", "from typing import Optional\n", @@ -266,9 +338,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:24 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:25 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "Based on your memories, you prefer Italian food and you love pizza." + ] + } + ], "source": [ "# Alternative approach using agent\n", "config = {\"configurable\": {\"thread_id\": \"semantic_search_thread_agent\"}}\n", @@ -305,9 +387,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:25 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", + "00:44:25 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:25 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:25 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:26 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:26 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Expect mem 2\n", + "Item: mem2; Score (0.589555978775)\n", + "Memory: Ate alone at home\n", + "Emotion: felt a bit lonely\n", + "\n", + "Expect mem1\n", + "00:44:26 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Item: mem2; Score (0.23533296585100005)\n", + "Memory: Ate alone at home\n", + "Emotion: felt a bit lonely\n", + "\n", + "Expect random lower score (ravioli not indexed)\n", + "00:44:26 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Item: mem2; Score (0.15022909641299997)\n", + "Memory: Ate alone at home\n", + "Emotion: felt a bit lonely\n", + "\n" + ] + } + ], "source": [ "# Configure Redis store to embed both memory content and emotional context\n", "REDIS_URI = \"redis://redis:6379\"\n", @@ -378,9 +490,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:26 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", + "00:44:26 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:26 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "00:44:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Expect mem1\n", + "00:44:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Item: mem1; Score (0.337496876717)\n", + "Memory: I love spicy food\n", + "Context: At a Thai restaurant\n", + "\n", + "Expect mem2\n", + "00:44:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Item: mem2; Score (0.36784017086)\n", + "Memory: The restaurant was too loud\n", + "Context: Dinner at an Italian place\n", + "\n" + ] + } + ], "source": [ "REDIS_URI = \"redis://redis:6379\"\n", "with RedisStore.from_conn_string(\n", @@ -442,9 +578,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:44:27 langgraph.store.redis INFO Redis standalone client detected for RedisStore.\n", + "00:44:27 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:27 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:44:28 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Expect mem1\n", + "00:44:28 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Item: mem1; Score (0.322699844837)\n", + "Memory: I love chocolate ice cream\n", + "Type: preference\n", + "\n", + "Expect low score (mem2 not indexed)\n", + "00:44:28 httpx INFO HTTP Request: POST https://api.openai.com/v1/embeddings \"HTTP/1.1 200 OK\"\n", + "Item: mem1; Score (0.010241627692999966)\n", + "Memory: I love chocolate ice cream\n", + "Type: preference\n", + "\n" + ] + } + ], "source": [ "REDIS_URI = \"redis://redis:6379\"\n", "with RedisStore.from_conn_string(\n", @@ -503,9 +662,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/examples/persistence-functional.ipynb b/examples/persistence-functional.ipynb index 4a19c6e..ea1f1d9 100644 --- a/examples/persistence-functional.ipynb +++ b/examples/persistence-functional.ipynb @@ -98,7 +98,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "af4ce0ba-7596-4e5f-8bf8-0b0bd6e62833", "metadata": {}, "outputs": [], @@ -117,7 +117,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "c903a1cf-2977-4e2d-ad7d-8b3946821d89", "metadata": {}, "outputs": [], @@ -161,14 +161,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "892b54b9-75f0-4804-9ed0-88b5e5532989", "metadata": {}, "outputs": [], "source": [ "from langchain_anthropic import ChatAnthropic\n", "\n", - "model = ChatAnthropic(model=\"claude-3-5-sonnet-latest\")" + "model = ChatAnthropic(model=\"claude-sonnet-4-20250514\")" ] }, { @@ -181,10 +181,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "87326ea6-34c5-46da-a41f-dda26ef9bd74", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:36:43 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:36:43 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:36:43 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:36:43 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from langchain_core.messages import BaseMessage\n", "from langgraph.graph import add_messages\n", @@ -243,10 +254,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "cfd140f0-a5a6-4697-8115-322242f197b5", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:36:45 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Hi Bob! Good to hear from you again. How are you doing today?\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "input_message = {\"role\": \"user\", \"content\": \"hi! I'm bob\"}\n", @@ -264,10 +286,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "08ae8246-11d5-40e1-8567-361e5bef8917", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:36:48 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "Your name is Bob! You introduced yourself to me at the beginning of our conversation.\n" + ] + } + ], "source": [ "input_message = {\"role\": \"user\", \"content\": \"what's my name?\"}\n", "for chunk in workflow.stream([input_message], config, stream_mode=\"values\"):\n", @@ -284,10 +317,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "273d56a8-f40f-4a51-a27f-7c6bb2bda0ba", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:36:50 httpx INFO HTTP Request: POST https://api.anthropic.com/v1/messages \"HTTP/1.1 200 OK\"\n", + "==================================\u001b[1m Ai Message \u001b[0m==================================\n", + "\n", + "I don't actually know your name. I don't have access to information about who you are unless you tell me directly in our conversation. If you'd like me to know your name, please feel free to share it with me!\n" + ] + } + ], "source": [ "input_message = {\"role\": \"user\", \"content\": \"what's my name?\"}\n", "for chunk in workflow.stream(\n", @@ -325,7 +369,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, diff --git a/examples/subgraph-persistence.ipynb b/examples/subgraph-persistence.ipynb index 3886926..a8e9bfc 100644 --- a/examples/subgraph-persistence.ipynb +++ b/examples/subgraph-persistence.ipynb @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "77d1eafa-3252-45f6-9af0-d94e1f9c5c9e", "metadata": {}, "outputs": [], @@ -105,10 +105,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "0d76f0c0-bd77-4eca-9527-27bcdf85dd42", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "from typing import TypedDict\n", "\n", @@ -164,14 +175,24 @@ "cell_type": "markdown", "id": "47084b1f-9fd5-40a9-9d75-89eb5f853d02", "metadata": {}, - "source": "We can now compile the graph with a Redis checkpointer (`RedisSaver`)." + "source": [ + "We can now compile the graph with a Redis checkpointer (`RedisSaver`)." + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "7657d285-c896-40c9-a569-b4a3b9c230c7", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:39:44 langgraph.checkpoint.redis INFO Redis client is a standalone client\n" + ] + } + ], "source": [ "from langgraph.checkpoint.redis import RedisSaver\n", "\n", @@ -205,7 +226,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "13da686e-6ed6-4b83-93e8-1631fcc8c2a9", "metadata": {}, "outputs": [], @@ -215,10 +236,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "8721f045-2e82-4bf0-9d85-5ba6ecf899d6", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'node_1': {'foo': 'hi! foo'}}\n", + "{'subgraph_node_1': {'bar': 'bar'}}\n", + "{'subgraph_node_2': {'foo': 'hi! foobar'}}\n", + "{'node_2': {'foo': 'hi! foobar'}}\n" + ] + } + ], "source": [ "for _, chunk in graph.stream({\"foo\": \"foo\"}, config, subgraphs=True):\n", " print(chunk)" @@ -234,10 +266,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "3e817283-142d-4fda-8cb1-8de34717f833", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'foo': 'hi! foobar'}" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "graph.get_state(config).values" ] @@ -257,7 +300,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "e896628f-36b2-45eb-b7c5-c64c1098f328", "metadata": {}, "outputs": [], @@ -277,10 +320,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "21e96df3-946d-40f8-8d6d-055ae4177452", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'configurable': {'thread_id': '1',\n", + " 'checkpoint_ns': 'node_2:562da115-4861-6138-1125-59718cde6ec8'}}" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "subgraph_config = state_with_subgraph.tasks[0].state\n", "subgraph_config" @@ -288,10 +343,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "1d2401b3-d52b-4895-a5d1-dccf015ba216", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'foo': 'hi! foobar', 'bar': 'bar'}" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "graph.get_state(subgraph_config).values" ] @@ -321,9 +387,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 -} \ No newline at end of file +} diff --git a/examples/subgraphs-manage-state.ipynb b/examples/subgraphs-manage-state.ipynb index a28d11b..76d6abd 100644 --- a/examples/subgraphs-manage-state.ipynb +++ b/examples/subgraphs-manage-state.ipynb @@ -51,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -68,9 +68,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdin", + "output_type": "stream", + "text": [ + "OPENAI_API_KEY: ········\n" + ] + } + ], "source": [ "import getpass\n", "import os\n", @@ -108,7 +116,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -161,9 +169,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:20 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:40:20 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:40:20 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:40:20 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from typing import Literal\n", "from typing_extensions import TypedDict\n", @@ -222,9 +241,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from IPython.display import Image, display\n", "\n", @@ -241,9 +271,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:21 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "{'router_node': {'route': 'other'}}\n", + "00:40:22 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "{'normal_llm_node': {'messages': [AIMessage(content='Hello! How can I assist you today?', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 9, 'prompt_tokens': 9, 'total_tokens': 18, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}, 'model_provider': 'openai', 'model_name': 'gpt-4o-2024-08-06', 'system_fingerprint': 'fp_b1442291a8', 'id': 'chatcmpl-Cd43ZihdZFv10P6lgrnIWWijHENhJ', 'service_tier': 'default', 'finish_reason': 'stop', 'logprobs': None}, id='lc_run--e37f863f-5d5c-425e-b3b9-531240e43f13-0', usage_metadata={'input_tokens': 9, 'output_tokens': 9, 'total_tokens': 18, 'input_token_details': {'audio': 0, 'cache_read': 0}, 'output_token_details': {'audio': 0, 'reasoning': 0}})]}}\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"1\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"hi!\"}]}\n", @@ -264,9 +305,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:23 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "{'router_node': {'route': 'weather'}}\n", + "00:40:24 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "{'__interrupt__': ()}\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -283,9 +335,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')]})\n", + "00:40:24 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')], 'route': 'weather'})\n", + "(('weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')]})\n", + "00:40:26 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "(('weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')], 'city': 'San Francisco'})\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"3\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -302,9 +367,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "('weather_graph',)" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "state = graph.get_state(config)\n", "state.next" @@ -319,9 +395,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(PregelTask(id='ab9927db-776e-778c-fecb-c7c5c3428da0', name='weather_graph', path=('__pregel_pull', 'weather_graph'), error=None, interrupts=(), state={'configurable': {'thread_id': '3', 'checkpoint_ns': 'weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0'}}, result=None),)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "state.tasks" ] @@ -335,9 +422,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "PregelTask(id='ab9927db-776e-778c-fecb-c7c5c3428da0', name='weather_graph', path=('__pregel_pull', 'weather_graph'), error=None, interrupts=(), state=StateSnapshot(values={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')], 'city': 'San Francisco'}, next=('weather_node',), config={'configurable': {'thread_id': '3', 'checkpoint_ns': 'weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0', 'checkpoint_id': '1f0c4172-d2ba-6250-8001-56721d7a79ce', 'checkpoint_map': {'': '1f0c4172-bdc6-68d4-8001-dbbae4a9b92e', 'weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0': '1f0c4172-d2ba-6250-8001-56721d7a79ce'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f0c4172-bdc6-68d4-8001-dbbae4a9b92e'}}, created_at='2025-11-18T00:40:26.961141+00:00', parent_config={'configurable': {'thread_id': '3', 'checkpoint_ns': 'weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0', 'checkpoint_id': '1f0c4172-bdcd-6a40-8000-49cf47919c06', 'checkpoint_map': {'': '1f0c4172-bdc6-68d4-8001-dbbae4a9b92e', 'weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0': '1f0c4172-bdcd-6a40-8000-49cf47919c06'}}}, tasks=(PregelTask(id='2853d1bd-40ee-07fe-aa8e-993ea3cc7b00', name='weather_node', path=('__pregel_pull', 'weather_node'), error=None, interrupts=(), state=None, result=None),), interrupts=()), result=None)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "state = graph.get_state(config, subgraphs=True)\n", "state.tasks[0]" @@ -354,9 +452,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')], 'route': 'weather'})\n", + "(('weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')], 'city': 'San Francisco'})\n", + "(('weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717'), AIMessage(content=\"It's sunny in San Francisco!\", additional_kwargs={}, response_metadata={}, id='43011c48-4d6a-4e1d-beef-f19fb2b76d8c')], 'city': 'San Francisco'})\n", + "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717'), AIMessage(content=\"It's sunny in San Francisco!\", additional_kwargs={}, response_metadata={}, id='43011c48-4d6a-4e1d-beef-f19fb2b76d8c')], 'route': 'weather'})\n" + ] + } + ], "source": [ "for update in graph.stream(None, config=config, stream_mode=\"values\", subgraphs=True):\n", " print(update)" @@ -377,7 +486,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -388,7 +497,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -411,9 +520,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "('model_node',)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "subgraph_state_before_model_node.next" ] @@ -427,9 +547,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "((), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')], 'route': 'weather'})\n", + "(('weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')]})\n", + "00:40:27 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "(('weather_graph:ab9927db-776e-778c-fecb-c7c5c3428da0',), {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='486b23fb-f66a-4691-a980-963bd6ba0717')], 'city': 'San Francisco'})\n" + ] + } + ], "source": [ "for value in graph.stream(\n", " None,\n", @@ -460,9 +591,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:28 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "{'router_node': {'route': 'weather'}}\n", + "00:40:29 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "{'__interrupt__': ()}\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"4\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -472,9 +614,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='10ace146-e3e3-45b6-87a6-2af70592d19a')]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "state = graph.get_state(config, subgraphs=True)\n", "state.values[\"messages\"]" @@ -489,9 +642,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "{'configurable': {'thread_id': '4',\n", + " 'checkpoint_ns': 'weather_graph:98bb2966-50c9-a970-9b65-91ddf06c0081',\n", + " 'checkpoint_id': '1f0c4172-e73d-60f8-8002-2fa7cf3ee206',\n", + " 'checkpoint_map': {'': '1f0c4172-dfbe-6003-8001-4c28f9e28ab0',\n", + " 'weather_graph:98bb2966-50c9-a970-9b65-91ddf06c0081': '1f0c4172-e73d-60f8-8002-2fa7cf3ee206'}}}" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "graph.update_state(state.tasks[0].state.config, {\"city\": \"la\"})" ] @@ -505,9 +673,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(('weather_graph:98bb2966-50c9-a970-9b65-91ddf06c0081',), {'weather_node': {'messages': [{'role': 'assistant', 'content': \"It's sunny in la!\"}]}})\n", + "((), {'weather_graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='10ace146-e3e3-45b6-87a6-2af70592d19a'), AIMessage(content=\"It's sunny in la!\", additional_kwargs={}, response_metadata={}, id='25e0b022-8b46-45d6-a879-b1d59d551418')]}})\n" + ] + } + ], "source": [ "for update in graph.stream(None, config=config, stream_mode=\"updates\", subgraphs=True):\n", " print(update)" @@ -526,9 +703,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:29 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "((), {'router_node': {'route': 'weather'}})\n", + "00:40:30 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "(('weather_graph:a8cee305-a4e1-1619-c9ed-922f8eb82574',), {'model_node': {'city': 'San Francisco'}})\n", + "((), {'__interrupt__': ()})\n", + "interrupted!\n", + "((), {'weather_graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='82a0cf58-ac94-40f9-bedb-3c3cad1f1415'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='b3845890-7652-459f-819b-370b896c4289')]}})\n", + "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='82a0cf58-ac94-40f9-bedb-3c3cad1f1415'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='b3845890-7652-459f-819b-370b896c4289')]\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"14\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -566,9 +758,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:31 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "((), {'router_node': {'route': 'weather'}})\n", + "00:40:31 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "(('weather_graph:bce0a8d8-7c21-907f-e1eb-fc3c389850f8',), {'model_node': {'city': 'San Francisco'}})\n", + "((), {'__interrupt__': ()})\n", + "interrupted!\n", + "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='70727bad-3d7a-4a62-911d-38ef4d75495e'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='96719b2b-fc92-43f6-b9b2-b0cf6b3638a4')]\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"8\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -605,9 +811,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:31 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:40:31 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:40:31 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:40:31 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from typing import Literal\n", "from typing_extensions import TypedDict\n", @@ -666,9 +883,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "00:40:31 langgraph.checkpoint.redis INFO Redis client is a standalone client\n", + "00:40:31 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:40:31 redisvl.index.index INFO Index already exists, not overwriting.\n", + "00:40:31 redisvl.index.index INFO Index already exists, not overwriting.\n" + ] + } + ], "source": [ "from langgraph.checkpoint.redis import RedisSaver\n", "\n", @@ -709,9 +937,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "from IPython.display import Image, display\n", "\n", @@ -728,9 +967,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "((), {'router_node': {'to_continue': True}})\n", + "00:40:32 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "(('graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83',), {'router_node': {'route': 'weather'}})\n", + "00:40:33 httpx INFO HTTP Request: POST https://api.openai.com/v1/chat/completions \"HTTP/1.1 200 OK\"\n", + "(('graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7'), {'model_node': {'city': 'San Francisco'}})\n", + "((), {'__interrupt__': ()})\n" + ] + } + ], "source": [ "config = {\"configurable\": {\"thread_id\": \"2\"}}\n", "inputs = {\"messages\": [{\"role\": \"user\", \"content\": \"what's the weather in sf\"}]}\n", @@ -742,9 +994,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Grandparent State:\n", + "{'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be')], 'to_continue': True}\n", + "---------------\n", + "Parent Graph State:\n", + "{'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be')], 'route': 'weather'}\n", + "---------------\n", + "Subgraph State:\n", + "{'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be')], 'city': 'San Francisco'}\n" + ] + } + ], "source": [ "state = grandparent_graph.get_state(config, subgraphs=True)\n", "print(\"Grandparent State:\")\n", @@ -766,9 +1033,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(('graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83',), {'weather_graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='86510037-f2d0-452f-b007-d335fa4d6482')]}})\n", + "((), {'graph': {'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='86510037-f2d0-452f-b007-d335fa4d6482')]}})\n", + "[HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='86510037-f2d0-452f-b007-d335fa4d6482')]\n" + ] + } + ], "source": [ "grandparent_graph_state = state\n", "parent_graph_state = grandparent_graph_state.tasks[0].state\n", @@ -797,9 +1074,52 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'rainy', 'type': 'ai', 'id': '86510037-f2d0-452f-b007-d335fa4d6482', 'tool_calls': [], 'invalid_tool_calls': []}}], 'to_continue': True}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4173-11ed-66bb-8005-abfb7c9b5673'}}, metadata={'source': 'loop', 'step': 5, 'parents': {}}, created_at='2025-11-18T00:40:33.588184+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4173-0614-681b-8004-bb0145b1cb63'}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'rainy', 'type': 'ai', 'id': '86510037-f2d0-452f-b007-d335fa4d6482', 'tool_calls': [], 'invalid_tool_calls': []}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'checkpoint_id': '1f0c4173-11e8-610c-8002-472a695abcd0', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-11e8-610c-8002-472a695abcd0'}}}, metadata={'source': 'loop', 'step': 2, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63'}}, created_at='2025-11-18T00:40:33.585990+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'checkpoint_id': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd'}}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'AIMessage'], 'kwargs': {'content': 'rainy', 'type': 'ai', 'id': '86510037-f2d0-452f-b007-d335fa4d6482', 'tool_calls': [], 'invalid_tool_calls': []}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7', 'checkpoint_id': '1f0c4173-11de-6130-8002-1910b4333394', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7': '1f0c4173-11de-6130-8002-1910b4333394'}}}, metadata={'source': 'update', 'step': 2, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd'}}, created_at='2025-11-18T00:40:33.581895+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7', 'checkpoint_id': '1f0c4173-11b3-6f00-8001-3ebd6a4dec99', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7': '1f0c4173-11b3-6f00-8001-3ebd6a4dec99'}}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7', 'checkpoint_id': '1f0c4173-11b3-6f00-8001-3ebd6a4dec99', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7': '1f0c4173-11b3-6f00-8001-3ebd6a4dec99'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd'}}, created_at='2025-11-18T00:40:33.564619+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7', 'checkpoint_id': '1f0c4173-0af7-6666-8000-2c7166449cf7', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7': '1f0c4173-0af7-6666-8000-2c7166449cf7'}}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7', 'checkpoint_id': '1f0c4173-0af7-6666-8000-2c7166449cf7', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7': '1f0c4173-0af7-6666-8000-2c7166449cf7'}}}, metadata={'source': 'loop', 'step': 0, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd'}}, created_at='2025-11-18T00:40:32.858264+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7', 'checkpoint_id': '1f0c4173-0af2-63b4-bfff-e50626d4b8b1', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7': '1f0c4173-0af2-63b4-bfff-e50626d4b8b1'}}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7', 'checkpoint_id': '1f0c4173-0af2-63b4-bfff-e50626d4b8b1', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83|weather_graph:f2a6b816-81df-d70a-ab45-b44861ae97e7': '1f0c4173-0af2-63b4-bfff-e50626d4b8b1'}}}, metadata={'source': 'input', 'step': -1, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd'}}, created_at='2025-11-18T00:40:32.856154+00:00', parent_config=None, tasks=(PregelTask(id='8ab57b9a-ae9f-e8d6-9e2f-ecd918975654', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result=None),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'checkpoint_id': '1f0c4173-0af0-644b-8001-5845b26dd1fd', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0af0-644b-8001-5845b26dd1fd'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63'}}, created_at='2025-11-18T00:40:32.855344+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'checkpoint_id': '1f0c4173-061b-66c8-8000-829ec3811afe', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-061b-66c8-8000-829ec3811afe'}}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}]}, next=('router_node',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'checkpoint_id': '1f0c4173-061b-66c8-8000-829ec3811afe', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-061b-66c8-8000-829ec3811afe'}}}, metadata={'source': 'loop', 'step': 0, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63'}}, created_at='2025-11-18T00:40:32.348738+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'checkpoint_id': '1f0c4173-0619-6899-bfff-c06e1a2af2b8', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0619-6899-bfff-c06e1a2af2b8'}}}, tasks=(PregelTask(id='79d70b40-ba2e-7c12-a763-5e078c2f315e', name='router_node', path=('__pregel_pull', 'router_node'), error=None, interrupts=(), state=None, result={}),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83', 'checkpoint_id': '1f0c4173-0619-6899-bfff-c06e1a2af2b8', 'checkpoint_map': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63', 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83': '1f0c4173-0619-6899-bfff-c06e1a2af2b8'}}}, metadata={'source': 'input', 'step': -1, 'parents': {'': '1f0c4173-0614-681b-8004-bb0145b1cb63'}}, created_at='2025-11-18T00:40:32.347967+00:00', parent_config=None, tasks=(PregelTask(id='c396d014-6d5e-eacd-595c-f1e589c2c502', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be')]}),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}], 'to_continue': True}, next=('graph',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4173-0614-681b-8004-bb0145b1cb63'}}, metadata={'source': 'loop', 'step': 4, 'parents': {}}, created_at='2025-11-18T00:40:32.345904+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4173-0611-6358-8003-a8dbd700740c'}}, tasks=(PregelTask(id='a6d3756e-3f64-22db-f9c7-37d129fc0a83', name='graph', path=('__pregel_pull', 'graph'), error=None, interrupts=(), state={'configurable': {'thread_id': '2', 'checkpoint_ns': 'graph:a6d3756e-3f64-22db-f9c7-37d129fc0a83'}}, result={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'), HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='eaa3e056-eca2-4788-bbab-c8a83e9878be'), AIMessage(content='rainy', additional_kwargs={}, response_metadata={}, id='86510037-f2d0-452f-b007-d335fa4d6482')]}),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}, {'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': 'eaa3e056-eca2-4788-bbab-c8a83e9878be'}}]}, next=('router_node',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4173-0611-6358-8003-a8dbd700740c'}}, metadata={'source': 'loop', 'step': 3, 'parents': {}}, created_at='2025-11-18T00:40:32.344554+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4173-060e-6c6e-8002-601a907b6eb1'}}, tasks=(PregelTask(id='a435de3f-68e5-6207-f047-7d43359fa425', name='router_node', path=('__pregel_pull', 'router_node'), error=None, interrupts=(), state=None, result={'to_continue': True}),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}]}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4173-060e-6c6e-8002-601a907b6eb1'}}, metadata={'source': 'input', 'step': 2, 'parents': {}}, created_at='2025-11-18T00:40:32.343557+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f'}}, tasks=(PregelTask(id='b2aca149-5c03-e0a1-a4f3-4ec87c5cf341', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [{'role': 'user', 'content': \"what's the weather in sf\"}]}),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302', 'checkpoint_id': '1f0c4172-b70d-61a4-8001-93ba36ca7301', 'checkpoint_map': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f', 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302': '1f0c4172-b70d-61a4-8001-93ba36ca7301'}}}, metadata={'source': 'loop', 'step': 1, 'parents': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f'}}, created_at='2025-11-18T00:40:24.059107+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302', 'checkpoint_id': '1f0c4172-b200-6b83-8000-83bcc4964821', 'checkpoint_map': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f', 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302': '1f0c4172-b200-6b83-8000-83bcc4964821'}}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302', 'checkpoint_id': '1f0c4172-b200-6b83-8000-83bcc4964821', 'checkpoint_map': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f', 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302': '1f0c4172-b200-6b83-8000-83bcc4964821'}}}, metadata={'source': 'loop', 'step': 0, 'parents': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f'}}, created_at='2025-11-18T00:40:23.529751+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302', 'checkpoint_id': '1f0c4172-b1fb-60f7-bfff-eed60bd332d0', 'checkpoint_map': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f', 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302': '1f0c4172-b1fb-60f7-bfff-eed60bd332d0'}}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302', 'checkpoint_id': '1f0c4172-b1fb-60f7-bfff-eed60bd332d0', 'checkpoint_map': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f', 'weather_graph:b6a694a7-73e2-a795-161e-4510c4f4a302': '1f0c4172-b1fb-60f7-bfff-eed60bd332d0'}}}, metadata={'source': 'input', 'step': -1, 'parents': {'': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f'}}, created_at='2025-11-18T00:40:23.527428+00:00', parent_config=None, tasks=(PregelTask(id='b26425c9-d625-0489-dbfd-05cb1f078fe7', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [HumanMessage(content=\"what's the weather in sf\", additional_kwargs={}, response_metadata={}, id='1f3c6235-3e8a-4e36-9a09-dcd2240c9e59')]}),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}]}, next=(), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4172-b1f1-6d8e-8001-08dd4c84fc5f'}}, metadata={'source': 'loop', 'step': 1, 'parents': {}}, created_at='2025-11-18T00:40:23.523655+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4172-a741-6f3a-8000-09fe865ab1ae'}}, tasks=(), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': [{'lc': 1, 'type': 'constructor', 'id': ['langchain', 'schema', 'messages', 'HumanMessage'], 'kwargs': {'content': \"what's the weather in sf\", 'type': 'human', 'id': '1f3c6235-3e8a-4e36-9a09-dcd2240c9e59'}}]}, next=('router_node',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4172-a741-6f3a-8000-09fe865ab1ae'}}, metadata={'source': 'loop', 'step': 0, 'parents': {}}, created_at='2025-11-18T00:40:22.403046+00:00', parent_config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4172-a73e-6c5d-bfff-a55ef48917fb'}}, tasks=(PregelTask(id='e8f483d4-18ee-b8b2-41f9-2d35312ae295', name='router_node', path=('__pregel_pull', 'router_node'), error=None, interrupts=(), state=None, result={}),), interrupts=())\n", + "-----\n", + "StateSnapshot(values={'messages': []}, next=('__start__',), config={'configurable': {'thread_id': '2', 'checkpoint_ns': '', 'checkpoint_id': '1f0c4172-a73e-6c5d-bfff-a55ef48917fb'}}, metadata={'source': 'input', 'step': -1, 'parents': {}}, created_at='2025-11-18T00:40:22.401745+00:00', parent_config=None, tasks=(PregelTask(id='7703781b-4ff0-1848-2931-3c363a415d4b', name='__start__', path=('__pregel_pull', '__start__'), error=None, interrupts=(), state=None, result={'messages': [{'role': 'user', 'content': \"what's the weather in sf\"}]}),), interrupts=())\n", + "-----\n" + ] + } + ], "source": [ "for state in grandparent_graph.get_state_history(config):\n", " print(state)\n", @@ -823,9 +1143,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.13" + "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 4 -} \ No newline at end of file +} diff --git a/langgraph/checkpoint/redis/jsonplus_redis.py b/langgraph/checkpoint/redis/jsonplus_redis.py index 5d1cf35..a203b74 100644 --- a/langgraph/checkpoint/redis/jsonplus_redis.py +++ b/langgraph/checkpoint/redis/jsonplus_redis.py @@ -92,7 +92,9 @@ def _preprocess_interrupts(self, obj: Any) -> Any: "lc": 2, "type": "constructor", "id": ["builtins", "set"], - "kwargs": {"__set_items__": [self._preprocess_interrupts(item) for item in obj]}, + "kwargs": { + "__set_items__": [self._preprocess_interrupts(item) for item in obj] + }, } elif dataclasses.is_dataclass(obj) and not isinstance(obj, type): # Handle dataclass instances (like langmem's RunningSummary) diff --git a/tests/test_langmem_serialization.py b/tests/test_langmem_serialization.py index 1495c20..e89648d 100644 --- a/tests/test_langmem_serialization.py +++ b/tests/test_langmem_serialization.py @@ -1,6 +1,8 @@ """Integration tests for langmem object serialization with JsonPlusRedisSerializer.""" + import pytest from langmem.short_term.summarization import RunningSummary + from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer From 587b768206012fa1dc4856d4f7f864b68307338a Mon Sep 17 00:00:00 2001 From: Brian Sam-Bodden Date: Mon, 17 Nov 2025 18:02:34 -0700 Subject: [PATCH 36/36] fix(tests): skip langmem tests on Python 3.10 Add Python version check to skip langmem serialization tests on Python < 3.11. The langmem library uses typing.NotRequired which was introduced in Python 3.11, causing import failures on Python 3.10 in CI. Tests will: - Skip on Python 3.10 (379 tests run) - Run on Python 3.11+ (382 tests run) Fixes CI test collection failures on Python 3.10. --- tests/test_langmem_serialization.py | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/tests/test_langmem_serialization.py b/tests/test_langmem_serialization.py index e89648d..ee65403 100644 --- a/tests/test_langmem_serialization.py +++ b/tests/test_langmem_serialization.py @@ -1,10 +1,22 @@ """Integration tests for langmem object serialization with JsonPlusRedisSerializer.""" +import sys + import pytest -from langmem.short_term.summarization import RunningSummary from langgraph.checkpoint.redis.jsonplus_redis import JsonPlusRedisSerializer +# langmem requires Python 3.11+ (uses typing.NotRequired) +# Try to import, skip all tests if it fails +try: + from langmem.short_term.summarization import RunningSummary +except (ImportError, AttributeError): + # Skip entire module if langmem can't be imported (Python < 3.11) + pytestmark = pytest.mark.skip( + reason="langmem requires Python 3.11+ (uses typing.NotRequired)" + ) + RunningSummary = None # type: ignore + class TestLangmemSerialization: """Test that langmem objects are properly serialized and deserialized."""