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OpenLit is the recommended path: it auto-instruments CrewAI plus the underlying LLM provider.
CrewAI/OpenLit traces can include prompts, completions, tool inputs, and tool outputs. Review Data Governance before enabling production traffic.

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Install

pip install crewai openlit

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Setup

import os, openlit
from crewai import Agent, Crew, Task
from openinference.instrumentation import using_attributes

os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"] = "https://otel.agnost.ai"
os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = "X-Agnost-Org-ID=<your-org-id>"

openlit.init(application_name="my-crew", environment="production")

with using_attributes(session_id="sess-123", user_id="u-42"):
    Crew(agents=[...], tasks=[...]).kickoff()
Spans use OTel GenAI semconv (gen_ai.prompt.{n}.content, gen_ai.completion.{n}.content, gen_ai.usage.*) plus gen_ai.agent.name and gen_ai.operation.name on agent/task spans.

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Caveats

  • Call openlit.init() before constructing any Crew / Agent objects.
  • CrewAI’s own anonymized telemetry (sent to CrewAI’s servers) is unrelated and can be left enabled.

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Verify

Run one Crew(...).kickoff() call, then open Raw logs in Agnost. Confirm CrewAI and provider spans are present.

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Troubleshooting

  • Call openlit.init() before constructing crews or agents.
  • Confirm OTEL_EXPORTER_OTLP_HEADERS contains X-Agnost-Org-ID=<your-org-id>.
  • Wrap runs with using_attributes if you need explicit user/session grouping.

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References