forgesight-adapters-langgraph 0.1.1

ForgeSight LangGraph adapter — auto-instrument LangGraph/LangChain agents via callbacks.

forgesight-adapters-langgraph

The LangGraph / LangChain adapter for ForgeSight. An unchanged LangGraph graph emits a correct ForgeSight span tree — with cost and metrics — by subscribing to LangChain's callbacks.

pip install forgesight-adapters-langgraph

import forgesight
from forgesight_adapters_langgraph import LangGraphAdapter

forgesight.configure()
LangGraphAdapter().instrument()          # subscribe to LangChain/LangGraph callbacks

# Unchanged graph — now fully instrumented:
result = await my_compiled_graph.ainvoke({"task": "review PR #42"})

What it maps

LangChain callback	ForgeSight
root chain (graph invoke)	agent_run
nested chain (graph node)	step
on_chat_model_start / on_llm_*	llm_call (+ token usage from the LLMResult)
on_tool_*	tool_call (execute_tool)
*_error	span ERROR + error.type

Because every adapter targets the same domain model, a LangGraph agent and (say) a CrewAI agent produce comparable agent_runs_total / cost views. Cost is derived by the runtime from the extracted token usage — the adapter never computes cost.

No double-instrument. When a tool call is already covered by an inner span (an MCP tools/call, feat-016), the adapter defers and does not open a second execute_tool.

Explicit handler

Auto-subscription uses LangChain's inheritable-callback hook. You can also pass the handler per-invocation: graph.ainvoke(..., config={"callbacks": [LangGraphAdapter().handler]}).

License

Apache-2.0