Remove Langchain Dependency

pyproject.toml

@@ -34,7 +34,6 @@ dependencies = [
     "browsergym>=0.7.1",
     "joblib>=1.2.0",
     "openai>=1.7,<2",
-    "langchain_community",
     "tiktoken",
     "huggingface_hub",
     "contexttimer",

src/agentlab/llm/llm_utils.py

@@ -1,5 +1,6 @@
 import base64
 import collections
+import importlib
 import io
 import json
 import logging
@@ -16,11 +17,17 @@
 import openai
 import tiktoken
 import yaml
-from langchain.schema import BaseMessage as LangchainBaseMessage
-from langchain_community.adapters.openai import convert_message_to_dict
 from PIL import Image
 from transformers import AutoModel, AutoTokenizer
 
+langchain_community = importlib.util.find_spec("langchain_community")
+if langchain_community is not None:
+    from langchain.schema import BaseMessage as LangchainBaseMessage
+    from langchain_community.adapters.openai import convert_message_to_dict
+else:
+    LangchainBaseMessage = None
+    convert_message_to_dict = None
+
 if TYPE_CHECKING:
     from agentlab.llm.chat_api import ChatModel
 
@@ -32,7 +39,7 @@ def messages_to_dict(messages: list[dict] | list[LangchainBaseMessage]) -> dict:
             new_messages.add_message(m)
         elif isinstance(m, str):
             new_messages.add_message({"role": "<unknown role>", "content": m})
-        elif isinstance(m, LangchainBaseMessage):
+        elif LangchainBaseMessage is not None and isinstance(m, LangchainBaseMessage):
             new_messages.add_message(convert_message_to_dict(m))
         else:
             raise ValueError(f"Unknown message type: {type(m)}")

src/agentlab/llm/tracking.py

@@ -1,3 +1,4 @@
+import importlib
 import logging
 import os
 import re
@@ -9,7 +10,13 @@
 from typing import Optional
 
 import requests
-from langchain_community.callbacks import bedrock_anthropic_callback, openai_info
+
+langchain_community = importlib.util.find_spec("langchain_community")
+if langchain_community is not None:
+    from langchain_community.callbacks import bedrock_anthropic_callback, openai_info
+else:
+    bedrock_anthropic_callback = None
+    openai_info = None
 from litellm import completion_cost, get_model_info
 
 TRACKER = threading.local()
@@ -103,7 +110,14 @@ def get_pricing_openrouter():
 
 def get_pricing_openai():
     """Returns a dictionary of model pricing for OpenAI models."""
-    cost_dict = openai_info.MODEL_COST_PER_1K_TOKENS
+    try:
+        cost_dict = openai_info.MODEL_COST_PER_1K_TOKENS
+    except Exception as e:
+        logging.warning(
+            f"Failed to get OpenAI pricing: {e}. "
+            "Please install langchain-community or use LiteLLM API for pricing information."
+        )
+        return {}
     cost_dict = {k: v / 1000 for k, v in cost_dict.items()}
     res = {}
     for k in cost_dict:
@@ -126,8 +140,15 @@ def _remove_version_suffix(model_name):
 
 def get_pricing_anthropic():
     """Returns a dictionary of model pricing for Anthropic models."""
-    input_cost_dict = bedrock_anthropic_callback.MODEL_COST_PER_1K_INPUT_TOKENS
-    output_cost_dict = bedrock_anthropic_callback.MODEL_COST_PER_1K_OUTPUT_TOKENS
+    try:
+        input_cost_dict = bedrock_anthropic_callback.MODEL_COST_PER_1K_INPUT_TOKENS
+        output_cost_dict = bedrock_anthropic_callback.MODEL_COST_PER_1K_OUTPUT_TOKENS
+    except Exception as e:
+        logging.warning(
+            f"Failed to get Anthropic pricing: {e}. "
+            "Please install langchain-community or use LiteLLM API for pricing information."
+        )
+        return {}
 
     res = {}
     for k, v in input_cost_dict.items():