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Move historical Langfuse observations into Arize AX so past traces are available next to the AX workflows your team uses for debugging and evaluation. Importing history is different from pointing your app at AX for the first time. Instrumentation alone only captures new traffic. The migration skill copies existing Langfuse observations into an AX project with OpenInference attributes your AX UI expects.

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What you can migrate

The skill maps observation output to plain-text output.value, keeps parent/child links, and copies Langfuse session and user IDs onto AX spans. If your Langfuse project also has unrelated experiment traffic, you can limit the import with a Langfuse tag.

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Migrate existing Langfuse data

1

Install the migration skill

See Install skills if you need the full Arize Skills setup.
2

Ask your coding agent to start

Use the Arize Langfuse migration skill. I want to import historical Langfuse traces into AX.
Tell the agent your Langfuse region or host, optional tag filter, and the AX space and destination project you want. Prefer a new AX project name so you can review the import cleanly.
3

Provide connection details privately

Give the agent credentials through a local env file path you control, or let it generate a secure command you run in a separate terminal. Do not paste API keys into agent chat.
  • Langfuse: LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, and LANGFUSE_BASE_URL
    • EU Cloud: https://cloud.langfuse.com
    • US Cloud: https://us.cloud.langfuse.com
    • Self-hosted: your Langfuse origin
  • Create or find an AX API key and space ID for OTLP ingest
Use the same region (or host) that issued your Langfuse keys. A US key against the EU host returns auth errors.
4

Review the plan and import

The agent confirms the Langfuse host, optional tag filter, destination AX project, and import scope. Approve before it writes to AX.It exports observations from the Langfuse public API and ingests them into AX over OTLP. Small windows finish quickly; larger histories take longer while AX indexes spans.
5

Verify in Arize AX

In the destination project, open a few traces and check:
  1. Output — agent and generation spans show readable final text (not a raw message/parts dump)
  2. Tree — tools and generations nest under the parent observation
  3. Sessions — traces that had a Langfuse sessionId share an AX session
  4. Kinds — generations look like LLM spans, tools like TOOL, agents like AGENT when Langfuse typed them that way
If something looks wrong, re-import into a fresh project after the agent adjusts filters or mapping.
6

Migrate prompts (optional)

Ask the agent to import Langfuse prompts (GET /api/public/v2/prompts) into the AX Prompt Hub. You can choose latest / production label only or all versions.The agent fetches each version, maps text or chat prompts into AX messages, creates the prompt, then adds versions in order and applies Langfuse labels (for example production, staging) with set_labels.

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What good imported traces look like

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After you migrate

Historical import does not change where your running app sends new spans. When you are ready for new traffic in AX, follow Set up tracing and Configure your tracer.
Keep Langfuse available until you have verified the import, because the skill reads from the Langfuse API. See the arize-migrate-langfuse skill source for current behavior and limits.