agi-core Demo

Use this page only when you intentionally want the notebook path first.

If you want the main AGILAB product path first, use Quick-Start and run the built-in flight_telemetry_project from the web UI. This page shows how to run the built-in Minimal App example in a notebook using published packages.

Start here

Use the Kaggle launcher first:

Open In Kaggle

This launcher installs the published AGILAB runtime packages into an isolated Kaggle venv under /kaggle/working and runs the built-in Minimal App example app (minimal_app_project) without mutating the base notebook kernel packages.

Kaggle note: enable Internet in the notebook settings for the first install.

What will happen

The first notebook does only one thing:

  • it prepares an isolated runtime environment from published packages

  • it loads the built-in Minimal App example app

  • it runs one local AGI.run(...) call

  • it shows you where the run artifacts were written

What success looks like

Your first notebook run is complete when:

  • the notebook run finishes without error

  • you can inspect fresh output under ~/log/execute/minimal_app

Local PyPI fallback

If you want local Jupyter instead of Kaggle, use the published packages in a clean environment:

mkdir ~/agi-core-demo && cd ~/agi-core-demo
uv venv
source .venv/bin/activate
uv pip install "agilab[examples]"
jupyter lab

Then use the minimal notebook cells below in a blank notebook.

Minimal notebook cells

Cell 1: select the built-in Minimal App example app and create the local request.

from agi_cluster.agi_distributor import AGI
from agilab.notebook_demo import notebook_agi_core_context

APP = "minimal_app_project"  # built-in Minimal App example app
context = notebook_agi_core_context(APP, verbose=1)
app_env = context.app_env
request = context.request
print("App:", context.app)
print("Log root:", context.log_root)

Cell 2: install the worker if needed, then run the visible AGI.run(...) call.

from agilab.notebook_demo import install_if_needed

await install_if_needed(app_env, request=request)
result = await AGI.run(app_env, request=request)
result

Cell 3: inspect the run artifacts.

from agilab.notebook_demo import notebook_log_root

log_root = notebook_log_root(app_env)
print(log_root)

How this maps back to the web UI

  • Notebook notebook_app_env(\"minimal_app_project\") is the compact form of AgiEnv(...) and corresponds to choosing the built-in Minimal App example app in PROJECT.

  • Notebook notebook_local_request() creates the small local RunRequest that ORCHESTRATE would generate for a one-worker run.

  • Notebook AGI.run(...) corresponds to the generated snippet from ORCHESTRATE.

  • The output path under ~/log/execute/minimal_app is the same family of artifacts the UI writes and reuses.

Advanced notebook routes

If you want source-checkout launchers, benchmark notebooks, Data + DAG, worker path inspection, or the source-checkout local notebook flow, use Advanced Notebook Routes.