refactor(langchain): update runtime imports to langchain-core

Update Colang runtime imports to use canonical langchain-core paths for
callbacks and runnables. Part of the broader migration to langchain-core
for LangChain 1.x compatibility.

Author: Pouyanpi

nemoguardrails/actions/llm/utils.py

@@ -16,8 +16,8 @@
 import re
 from typing import Any, Dict, List, Optional, Sequence, Union
 
-from langchain.base_language import BaseLanguageModel
-from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackManager
+from langchain_core.callbacks.base import AsyncCallbackHandler, BaseCallbackManager
+from langchain_core.language_models import BaseLanguageModel
 from langchain_core.runnables import RunnableConfig
 from langchain_core.runnables.base import Runnable
 

nemoguardrails/colang/v1_0/runtime/runtime.py

@@ -22,7 +22,6 @@
 from urllib.parse import urljoin
 
 import aiohttp
-from langchain.chains.base import Chain
 
 from nemoguardrails.actions.actions import ActionResult
 from nemoguardrails.actions.core import create_event
@@ -658,12 +657,6 @@ async def _process_start_action(self, events: List[dict]) -> List[dict]:
                 parameters = inspect.signature(fn).parameters
                 action_type = "function"
 
-            elif isinstance(fn, Chain):
-                # If we're dealing with a chain, we list the annotations
-                # TODO: make some additional type checking here
-                parameters = fn.input_keys
-                action_type = "chain"
-
             # For every parameter that start with "__context__", we pass the value
             for parameter_name in parameters:
                 if parameter_name.startswith("__context__"):
@@ -677,11 +670,9 @@ async def _process_start_action(self, events: List[dict]) -> List[dict]:
                     if var_name in context:
                         kwargs[k] = context[var_name]
 
-            # If we have an action server, we use it for non-system/non-chain actions
-            if (
-                self.config.actions_server_url
-                and not action_meta.get("is_system_action")
-                and action_type != "chain"
+            # If we have an action server, we use it for non-system actions
+            if self.config.actions_server_url and not action_meta.get(
+                "is_system_action"
             ):
                 result, status = await self._get_action_resp(
                     action_meta, action_name, kwargs

nemoguardrails/colang/v2_x/runtime/runtime.py

@@ -20,8 +20,6 @@
 from urllib.parse import urljoin
 
 import aiohttp
-import langchain
-from langchain.chains.base import Chain
 
 from nemoguardrails.actions.actions import ActionResult
 from nemoguardrails.colang import parse_colang_file
@@ -45,8 +43,6 @@
 from nemoguardrails.rails.llm.config import RailsConfig
 from nemoguardrails.utils import new_event_dict, new_readable_uuid
 
-langchain.debug = False
-
 log = logging.getLogger(__name__)
 
 
@@ -202,12 +198,6 @@ async def _process_start_action(
                 parameters = inspect.signature(fn).parameters
                 action_type = "function"
 
-            elif isinstance(fn, Chain):
-                # If we're dealing with a chain, we list the annotations
-                # TODO: make some additional type checking here
-                parameters = fn.input_keys
-                action_type = "chain"
-
             # For every parameter that start with "__context__", we pass the value
             for parameter_name in parameters:
                 if parameter_name.startswith("__context__"):
@@ -221,11 +211,9 @@ async def _process_start_action(
                     if var_name in context:
                         kwargs[k] = context[var_name]
 
-            # If we have an action server, we use it for non-system/non-chain actions
-            if (
-                self.config.actions_server_url
-                and not action_meta.get("is_system_action")
-                and action_type != "chain"
+            # If we have an action server, we use it for non-system actions
+            if self.config.actions_server_url and not action_meta.get(
+                "is_system_action"
             ):
                 result, status = await self._get_action_resp(
                     action_meta, action_name, kwargs

nemoguardrails/evaluate/evaluate_factcheck.py

@@ -20,8 +20,7 @@
 
 import tqdm
 import typer
-from langchain.chains import LLMChain
-from langchain.prompts import PromptTemplate
+from langchain_core.prompts import PromptTemplate
 
 from nemoguardrails import LLMRails
 from nemoguardrails.actions.llm.utils import llm_call
@@ -94,19 +93,23 @@ def create_negative_samples(self, dataset):
             template=create_negatives_template,
             input_variables=["evidence", "answer"],
         )
-        create_negatives_chain = LLMChain(prompt=create_negatives_prompt, llm=self.llm)
+
+        # Bind config parameters to the LLM for generating negative samples
+        llm_with_config = self.llm.bind(temperature=0.8, max_tokens=300)
 
         print("Creating negative samples...")
         for data in tqdm.tqdm(dataset):
             assert "evidence" in data and "question" in data and "answer" in data
             evidence = data["evidence"]
             answer = data["answer"]
-            negative_answer_result = create_negatives_chain.invoke(
-                {"evidence": evidence, "answer": answer},
-                config={"temperature": 0.8, "max_tokens": 300},
+
+            # Format the prompt and invoke the LLM directly
+            formatted_prompt = create_negatives_prompt.format(
+                evidence=evidence, answer=answer
             )
-            negative_answer = negative_answer_result["text"]
-            data["incorrect_answer"] = negative_answer.strip()
+            negative_answer = llm_with_config.invoke(formatted_prompt)
+            negative_answer_content = negative_answer.content
+            data["incorrect_answer"] = negative_answer_content.strip()
 
         return dataset
 
@@ -186,14 +189,16 @@ def run(self):
             split="negative"
         )
 
-        print(f"Positive Accuracy: {pos_num_correct/len(self.dataset) * 100}")
-        print(f"Negative Accuracy: {neg_num_correct/len(self.dataset) * 100}")
+        print(f"Positive Accuracy: {pos_num_correct / len(self.dataset) * 100}")
+        print(f"Negative Accuracy: {neg_num_correct / len(self.dataset) * 100}")
         print(
-            f"Overall Accuracy: {(pos_num_correct + neg_num_correct)/(2*len(self.dataset))* 100}"
+            f"Overall Accuracy: {(pos_num_correct + neg_num_correct) / (2 * len(self.dataset)) * 100}"
         )
 
         print("---Time taken per sample:---")
-        print(f"Ask LLM:\t{(pos_time+neg_time)*1000/(2*len(self.dataset)):.1f}ms")
+        print(
+            f"Ask LLM:\t{(pos_time + neg_time) * 1000 / (2 * len(self.dataset)):.1f}ms"
+        )
 
         if self.write_outputs:
             dataset_name = os.path.basename(self.dataset_path).split(".")[0]

nemoguardrails/llm/providers/huggingface/pipeline.py

@@ -15,12 +15,12 @@
 
 from typing import Any, List, Optional
 
-from langchain.callbacks.manager import (
+from langchain_community.llms import HuggingFacePipeline
+from langchain_core.callbacks.manager import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
-from langchain.schema.output import GenerationChunk
-from langchain_community.llms import HuggingFacePipeline
+from langchain_core.outputs import GenerationChunk
 
 
 class HuggingFacePipelineCompatible(HuggingFacePipeline):

nemoguardrails/logging/callbacks.py

@@ -18,15 +18,15 @@
 from typing import Any, Dict, List, Optional, Union, cast
 from uuid import UUID
 
-from langchain.callbacks import StdOutCallbackHandler
-from langchain.callbacks.base import (
+from langchain_core.agents import AgentAction, AgentFinish
+from langchain_core.callbacks.base import (
     AsyncCallbackHandler,
     BaseCallbackHandler,
     BaseCallbackManager,
 )
-from langchain.callbacks.manager import AsyncCallbackManagerForChainRun
-from langchain.schema import AgentAction, AgentFinish, AIMessage, BaseMessage, LLMResult
-from langchain_core.outputs import ChatGeneration
+from langchain_core.callbacks.manager import AsyncCallbackManagerForChainRun
+from langchain_core.messages import AIMessage, BaseMessage
+from langchain_core.outputs import ChatGeneration, LLMResult
 
 from nemoguardrails.context import explain_info_var, llm_call_info_var, llm_stats_var
 from nemoguardrails.logging.explain import LLMCallInfo

nemoguardrails/streaming.py

@@ -18,10 +18,9 @@
 from typing import Any, AsyncIterator, Dict, List, Optional, Union
 from uuid import UUID
 
-from langchain.callbacks.base import AsyncCallbackHandler
-from langchain.schema import BaseMessage
-from langchain.schema.messages import AIMessageChunk
-from langchain.schema.output import ChatGenerationChunk, GenerationChunk, LLMResult
+from langchain_core.callbacks.base import AsyncCallbackHandler
+from langchain_core.messages import AIMessageChunk, BaseMessage
+from langchain_core.outputs import ChatGenerationChunk, GenerationChunk, LLMResult
 
 from nemoguardrails.utils import new_uuid
 

tests/rails/llm/test_config.py

@@ -13,11 +13,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import json
 from unittest.mock import MagicMock
 
 import pytest
-from langchain.llms.base import BaseLLM
+from langchain_core.language_models import BaseLLM
 from pydantic import ValidationError
 
 from nemoguardrails.rails.llm.config import Model, RailsConfig, TaskPrompt

tests/test_callbacks.py

@@ -17,15 +17,14 @@
 from uuid import uuid4
 
 import pytest
-from langchain.schema import Generation, LLMResult
 from langchain_core.messages import (
     AIMessage,
     BaseMessage,
     HumanMessage,
     SystemMessage,
     ToolMessage,
 )
-from langchain_core.outputs import ChatGeneration
+from langchain_core.outputs import ChatGeneration, Generation, LLMResult
 
 from nemoguardrails.context import explain_info_var, llm_call_info_var, llm_stats_var
 from nemoguardrails.logging.callbacks import LoggingCallbackHandler

tests/test_streaming_handler.py

@@ -21,8 +21,8 @@
 from uuid import UUID
 
 import pytest
-from langchain.schema.messages import AIMessageChunk
-from langchain.schema.output import ChatGenerationChunk, GenerationChunk
+from langchain_core.messages import AIMessageChunk
+from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
 
 from nemoguardrails.streaming import END_OF_STREAM, StreamingHandler