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[BEZALEL][DEMO] Notebook Workflow: Jupytext + Papermill for Agent Tasks (#157)
2026-04-07 02:02:49 +00:00

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Notebook Workflow for Agent Tasks

This directory demonstrates a sovereign, version-controlled workflow for LLM agent tasks using Jupyter notebooks.

Philosophy

  • **.py files are the source of truth** — authored and reviewed as plain Python with # %%` cell markers (via Jupytext)
  • .ipynb files are generated artifacts — auto-created from .py for execution and rich viewing
  • Papermill parameterizes and executes — each run produces an output notebook with code, narrative, and results preserved
  • Output notebooks are audit artifacts — every execution leaves a permanent, replayable record

File Layout

notebooks/
  agent_task_system_health.py      # Source of truth (Jupytext)
  agent_task_system_health.ipynb   # Generated from .py
docs/
  NOTEBOOK_WORKFLOW.md             # This document
.gitea/workflows/
  notebook-ci.yml                  # CI gate: executes notebooks on PR/push

How Agents Work With Notebooks

  1. Create — Agent generates a .py notebook using # %% [markdown] and # %% code blocks
  2. Review — PR reviewers see clean diffs in Gitea (no JSON noise)
  3. Generatejupytext --to ipynb produces the .ipynb before merge
  4. Execute — Papermill runs the notebook with injected parameters
  5. Archive — Output notebook is committed to a reports/ branch or artifact store

Converting Between Formats

# .py -> .ipynb
jupytext --to ipynb notebooks/agent_task_system_health.py

# .ipynb -> .py
jupytext --to py notebooks/agent_task_system_health.ipynb

# Execute with parameters
papermill notebooks/agent_task_system_health.ipynb output.ipynb \
  -p threshold 1.0 -p hostname forge-vps-01

CI Gate

The notebook-ci.yml workflow executes all notebooks in notebooks/ on every PR and push, ensuring that checked-in notebooks still run and produce outputs.

Why This Matters

Problem Notebook Solution
Ephemeral agent reasoning Markdown cells narrate the thought process
Stateless single-turn tools Stateful cells persist variables across steps
Unreviewable binary artifacts .py source is diffable and PR-friendly
No execution audit trail Output notebook preserves code + outputs + metadata