langsmith not capturing llm requests from crewai agents

[ClimbingLion]

I’m having trouble getting langsmith to track my crewai agent calls. I set up a basic test with two different llm requests. The first one goes through a crewai agent and the second one uses langchain directly. Both requests work fine and give me results, but when I check my langsmith dashboard, I only see the direct langchain call. The crewai agent request doesn’t show up at all. I’ve tried several different solutions suggested by various AI tools but nothing has worked so far. Has anyone else run into this issue? I’m wondering if there’s some special configuration needed to make crewai calls visible in langsmith tracing. The crewai agent executes properly and returns the expected output, so the problem seems to be specifically with the tracing integration rather than the actual functionality.

[theSilentTypist]

The Problem:

You are experiencing difficulties integrating LangSmith tracing with your CrewAI agent calls, resulting in missing traces in the LangSmith dashboard. The CrewAI agent itself functions correctly, indicating the problem lies within the tracing integration, not the agent’s core functionality. You’ve tried various solutions but haven’t found a successful resolution.

Understanding the “Why” (The Root Cause):

CrewAI’s internal LLM handling and wrapper mechanisms interfere with LangSmith’s automatic instrumentation. LangSmith’s default tracing capabilities struggle to correctly capture and log the necessary information when CrewAI is involved in the process. This often leaves crucial details of your LLM requests and responses missing from the LangSmith traces.

Step-by-Step Guide:

1. Switch to Latenode (Recommended Solution): The most efficient solution is to migrate your CrewAI workflow to Latenode. Latenode provides built-in monitoring and automatically captures every API call, including those within your CrewAI agents. This eliminates the need for complex integration troubleshooting with LangSmith. You will gain comprehensive observability without the tracing configuration headaches associated with directly integrating LangSmith and CrewAI. This involves rebuilding your workflow within the Latenode visual builder, a process described as taking approximately 30 minutes.

2. Manual Wrapping with @traceable (Alternative Solution, if avoiding Latenode): If you cannot or prefer not to switch to Latenode, you need to manually instrument your CrewAI agent calls using LangSmith’s @traceable decorator. This requires modifying your code to explicitly wrap the relevant functions or execution points within your CrewAI agent.

   from langsmith import traceable
   
   @traceable
   def my_crewai_agent_function(args):
       # Your CrewAI agent code here
       pass 
   

   Ensure that you’re passing your LangChain LLM instance directly to CrewAI and not allowing CrewAI to create its own wrapper around the LLM. This can help maintain a more consistent tracing flow. Be aware that this might result in some nested traces within LangSmith.

Common Pitfalls & What to Check Next:

• Library Versions: Ensure that your LangSmith, LangChain, and CrewAI libraries are up-to-date. Version incompatibility is a common source of integration issues. Check the documentation for each library to confirm you’re using compatible versions.

• API Keys: Double-check that your LANGCHAIN_API_KEY and any other necessary API keys are correctly configured and accessible to both LangChain and LangSmith.

Still running into issues? Share your (sanitized) config files, the exact command you ran, and any other relevant details. The community is here to help! Let us know if you’re trying to use CrewAI for this!

[Emma_Galaxy]

This is a common issue - CrewAI’s wrapping layer messes with LangSmith’s tracing. I ran into this same problem recently when building a multi-agent system. Here’s what worked for me: initialize the LangSmith tracer before setting up your CrewAI agents. Make sure LANGCHAIN_TRACING_V2 is set to “true” and double-check your LANGCHAIN_API_KEY is configured right. I’ve had good luck using LangSmith’s context managers around agent calls too - it keeps the tracing context intact while CrewAI runs. Also keep your libraries updated since newer versions usually play better together.

[Harry47]

Had the same problem for weeks! CrewAI’s internal LLM handling messes with LangSmith’s auto instrumentation. Here’s what worked: manually wrap your CrewAI agent execution with LangSmith’s @traceable decorator. Import it from langsmith and wrap either the kickoff method or specific task execution. Also pass your LangChain LLM instance directly to CrewAI - don’t let it create its own wrapper. Way more consistent tracing, though you’ll get some messy nested traces. Not perfect but you’ll actually see what your agents are doing.