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Documentation Index

Fetch the complete documentation index at: https://docs.trulayer.ai/llms.txt

Use this file to discover all available pages before exploring further.

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Install

pip install trulayer haystack-ai

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Instrument

instrument_haystack wraps a single Pipeline instance. Call it after the pipeline is built, before run(). 
import os
import trulayer
from haystack import Pipeline
from haystack.components.generators import OpenAIGenerator
from trulayer.instruments.haystack import instrument_haystack

trulayer.init(api_key=os.environ["TRULAYER_API_KEY"], project_name="my-app")

pipe = Pipeline()
pipe.add_component("llm", OpenAIGenerator(model="gpt-4o-mini"))

with trulayer.trace("haystack-run") as trace:
    instrument_haystack(pipe, trace)
    result = pipe.run({"llm": {"prompt": "What is the capital of France?"}})
    print(result["llm"]["replies"][0])

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What gets captured

  • A pipeline root span around every Pipeline.run() call, with data as input and the final result dict as output.
  • One child span per component in the pipeline (retrievers, generators, rankers, converters) with that component’s input and output attached.
  • Generator components’ LLM calls appear as llm spans with token counts and model metadata.

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Known gotchas

  • Haystack v2 only. The legacy Haystack v1 API (BaseComponent) is not supported.
  • Component names matter. Span names come from the name passed to pipe.add_component(...) — use descriptive names (retriever, reranker) to make the waterfall readable.
  • run_async works. The async pipeline path is instrumented via the same function — one call covers both.