langinsight-langchain

LangInsight callback handler for LangChain. Sends input/output traces to LangInsight in parallel on each LLM end and supports feedback (thumbs up/down) via score(). TypeScript の @langinsight/langchain と同じ仕様です。

Installation

pip install langinsight-langchain

Or with Poetry:

poetry add langinsight-langchain

Usage

Basic usage

from langchain_anthropic import ChatAnthropic
from langinsight_langchain import CallbackHandler

import os

model = ChatAnthropic(model="claude-3-7-sonnet-20250219")

handler = CallbackHandler(
    api_key=os.environ["LANGINSIGHT_API_KEY"],
    endpoint=os.environ["LANGINSIGHT_ENDPOINT"],
    metadata={"userId": "admin", "sessionId": "admin"},
    on_success=lambda input_trace, output_trace: print("Trace sent:", output_trace.get("id")),
    on_failure=lambda err: print("Trace failed:", err),
)

response = model.invoke("hi!", config={"callbacks": [handler]})

Feedback (score)

Trace ID は handler.result.result() で取得し、その output_trace["id"] を score() に渡してフィードバックを送信する。DB 永続化などは on_success コールバックでも行える。

from langinsight_langchain import CallbackHandler

handler = CallbackHandler(
    api_key=os.environ["LANGINSIGHT_API_KEY"],
    endpoint=os.environ["LANGINSIGHT_ENDPOINT"],
    metadata={"userId": "admin", "sessionId": "admin"},
)

response = model.invoke("hi!", config={"callbacks": [handler]})

input_trace, output_trace = handler.result.result(timeout=10)
handler.score(trace_id=output_trace["id"], value=1)   # 👍
handler.score(trace_id=output_trace["id"], value=-1)  # 👎

Options

API

• score(trace_id, value) — Submits feedback (1 = thumbs up, -1 = thumbs down) for the given trace. Use (handler.result.result())[1]["id"] as trace_id.
• result — A concurrent.futures.Future that resolves to (input_trace, output_trace) when both traces are sent. Use handler.result.result(timeout=10) to block and get the traces.

Development

poetry install
poetry run python examples/basic_usage.py

License

MIT