[FR]: How to configure pydantic-ai with langgraph + LogFire so all LLM traces are unified in a single trace?

[lucasboscatti]

Proposal summary

I’m experimenting with langgraph and tracing via Opik. Here’s the behavior I’m seeing:

• With langgraph + langchain:
  When I trace execution using Opik, all LLM-related information (inputs, outputs, tokens, pricing, timing) is captured in a single trace, distributed across the nodes of the graph.

• With langgraph + pydantic-ai (tracing enabled via LogFire with capture_all=True):
  Instead of one unified trace, I get multiple separate traces, which makes it harder to visualize the entire flow in a single execution graph.

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Question:
How can I configure pydantic-ai so that all LLM-related traces are logged within a single trace and distributed across the nodes of the graph, similar to how langgraph handles it with langchain?

The reason I’m exploring pydantic-ai is because langchain feels too complex for my use case.

Motivation

No response