AGILab Documentation

AGILAB turns experimental AI/ML notebooks and scripts into executable, portable, evidence-backed applications that can run locally or on distributed workers. Workflows stay portable: export them back to runnable agi-core notebooks, keep reproducibility evidence, and hand off tracking evidence to MLflow when that integration is enabled. The notebook export is an agi-core runtime handoff: you can continue to run the saved project and stage contract with only the stable core runtime, without depending on the AGILAB UI or distributed worker layer. That stable, production-grade core technology remains the smallest supported handoff surface.

If you are new to AGILab, choose one route first:

  • See the UI now: open AGILAB Demo for the public Hugging Face Space.

  • Prove it locally: follow Quick-Start with the built-in flight_telemetry_project or start from a notebook through PROJECT. Default target: pass the flight first proof in 10 minutes.

  • Use the API/notebook: follow agi-core Demo for the smaller AgiEnv / AGI.run(...) surface.

The fastest adoption ladder is browser preview, one local first-proof lane, evidence manifest, then expansion into package mode, external apps, or cluster work.

AGILAB is not locked to one web frontend. App projects can declare app-owned UI surfaces so the same runtime, artifacts, and evidence contract can be opened through the local Streamlit UI, a hosted Hugging Face backend, or browser-native agi-web UI islands with React-ready component contracts. See Page Bundles for the [app_surface] contract and the generic agilab app surface launcher.

If the local first proof fails, use Newcomer First-Failure Recovery before branching into cluster mode, external app repositories, or broader workflows.

For release-level evidence, use Release Proof; it points to the latest public GitHub release, package proof, CI guardrails, and hosted demo status.

This documentation then expands into architecture, service mode, API references, and example projects.

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