refactor(langchain): migrate imports to canonical langchain-core paths

Migrate all imports from deprecated proxy paths to canonical
langchain-core paths
to ensure compatibility with LangChain 1.x. Changes include:
- Use `from langchain_core.language_models import BaseLLM,
BaseChatModel`
- Remove proxy imports from `langchain.chat_models.base`
- Standardize submodule imports to top-level
langchain_core.language_models

This ensures forward compatibility with LangChain 1.x where proxy
imports from the main langchain package will be removed.

Author: Pouyanpi

nemoguardrails/actions/llm/generation.py

@@ -28,8 +28,7 @@
 
 from jinja2 import meta
 from jinja2.sandbox import SandboxedEnvironment
-from langchain_core.language_models import BaseChatModel
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseChatModel, BaseLLM
 
 from nemoguardrails.actions.actions import ActionResult, action
 from nemoguardrails.actions.llm.utils import (

nemoguardrails/actions/v2_x/generation.py

@@ -21,8 +21,7 @@
 from ast import literal_eval
 from typing import Any, Dict, List, Optional, Tuple, Union, cast
 
-from langchain_core.language_models import BaseChatModel
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseChatModel, BaseLLM
 from rich.text import Text
 
 from nemoguardrails.actions.actions import action

nemoguardrails/library/content_safety/actions.py

@@ -16,7 +16,7 @@
 import logging
 from typing import Dict, Optional
 
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
 
 from nemoguardrails.actions.actions import action
 from nemoguardrails.actions.llm.utils import llm_call

nemoguardrails/library/factchecking/align_score/actions.py

@@ -16,7 +16,7 @@
 import logging
 from typing import Optional
 
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
 
 from nemoguardrails import RailsConfig
 from nemoguardrails.actions import action

nemoguardrails/library/hallucination/actions.py

@@ -16,9 +16,8 @@
 import logging
 from typing import Optional
 
-from langchain.chains import LLMChain
-from langchain.prompts import PromptTemplate
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
+from langchain_core.prompts import PromptTemplate
 
 from nemoguardrails import RailsConfig
 from nemoguardrails.actions import action
@@ -72,7 +71,7 @@ async def self_check_hallucination(
                 f"Current LLM engine is {type(llm).__name__}, which may not support all features."
             )
 
-            if "n" not in llm.__fields__:
+            if "n" not in llm.model_fields:
                 log.warning(
                     f"LLM engine {type(llm).__name__} does not support the 'n' parameter for generating multiple completion choices. "
                     f"Please use an OpenAI LLM engine or a model that supports the 'n' parameter for optimal performance."
@@ -81,16 +80,16 @@ async def self_check_hallucination(
 
         # Use the "generate" call from langchain to get all completions in the same response.
         last_bot_prompt = PromptTemplate(template="{text}", input_variables=["text"])
-        chain = LLMChain(prompt=last_bot_prompt, llm=llm)
+
+        # Format the prompt manually
+        formatted_prompt = last_bot_prompt.format(text=last_bot_prompt_string)
 
         # Generate multiple responses with temperature 1.
-        # Use chain.with_config for runtime parameters
-        configured_chain = chain.with_config(
-            configurable={"temperature": 1.0, "n": num_responses}
-        )
-        extra_llm_response = await configured_chain.agenerate(
-            [{"text": last_bot_prompt_string}],
-            run_manager=logging_callback_manager_for_chain,
+        # Bind the config parameters to the LLM for this call
+        llm_with_config = llm.bind(temperature=1.0, n=num_responses)
+        extra_llm_response = await llm_with_config.agenerate(
+            [formatted_prompt],
+            callbacks=[logging_callback_manager_for_chain],
         )
 
         extra_llm_completions = []

nemoguardrails/library/llama_guard/actions.py

@@ -16,7 +16,7 @@
 import logging
 from typing import List, Optional, Tuple
 
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
 
 from nemoguardrails.actions import action
 from nemoguardrails.actions.llm.utils import llm_call

nemoguardrails/library/patronusai/actions.py

@@ -19,7 +19,7 @@
 from typing import List, Literal, Optional, Tuple, Union
 
 import aiohttp
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
 
 from nemoguardrails.actions import action
 from nemoguardrails.actions.llm.utils import llm_call

nemoguardrails/library/self_check/facts/actions.py

@@ -16,7 +16,7 @@
 import logging
 from typing import Optional
 
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
 
 from nemoguardrails import RailsConfig
 from nemoguardrails.actions import action

nemoguardrails/library/self_check/input_check/actions.py

@@ -16,7 +16,7 @@
 import logging
 from typing import Optional
 
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
 
 from nemoguardrails import RailsConfig
 from nemoguardrails.actions.actions import ActionResult, action

nemoguardrails/library/self_check/output_check/actions.py

@@ -16,7 +16,7 @@
 import logging
 from typing import Optional
 
-from langchain_core.language_models.llms import BaseLLM
+from langchain_core.language_models import BaseLLM
 
 from nemoguardrails import RailsConfig
 from nemoguardrails.actions import action