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Prepare and deploy hackathon submission: Gradio Space, GitHub repo, docs, trace dataset

Session from lost-found-desk-codex-traces on Hugging Face by build-small-hackathon · MIT · condensed by Coders Talk

1h 45msession
1interventions
by library · 20h
PythongradiohuggingfacepydanticPyTorchuv
GOAL

Get the Lost & Found Desk project fully ready for a hackathon submission: check it against the official field guide, deploy it as a Hugging Face Space, publish a public GitHub repo, write submission docs/article/social post, and set up a Codex trace dataset and collection.

  1. Prompt · +0
    Check the project against the hackathon submit guide, check applicable quests, and fully prepare it for submission: deployment, public GitHub repo, README/docs, article and social post drafts, quest checks, commits with co-author.
  2. Agent did · +0m
    Read the official submit guide, audited the repo (gitignore, README, pyproject, remotes), checked HF/GitHub CLI auth, ran the test suite (27 passing) and identified what still needed to be added for submission.
  3. Agent did · +4m
    Removed legacy Gradio compatibility shims and disabled the silent mock-model fallback by default, wrote docs/article.md, social-post.md and submission-notes.md, added README submission metadata/tags, squashed everything into one Codex co-authored commit, then created the public GitHub repo and the official build-small-hackathon HF Space.
  4. Fail · +12m
    HF Space build rejected the README's colorTo value, then failed on a pydantic version conflict with the Gradio builder's mcp extra, then failed again on a torchvision/torch version mismatch.
  5. Fail · +20m
    After fixing dependencies, the ZeroGPU startup detector reported no @spaces.GPU function; fixing the decorator condition still crashed because the model was eager-loading before the spaces package patched CUDA. Fixed import order so spaces loads before ModelHub, then the Space finally reached RUNNING with healthy /health checks.
  6. Prompt · +31m
    Use this YouTube link for the demo video instead of the local mp4.
  7. Break · 40m away, not counted
  8. Prompt · +1h 25m
    Create a trace dataset from our Codex session logs, and a collection grouping the Space, article, model, and dataset.
  9. Intervention · +1h 44m
    Developer pointed out the dataset should use the officially supported Hugging Face agent trace format instead of the custom derived JSONL schema the agent had built.
    Why: I saw the agent had invented its own schema for the trace dataset instead of checking whether Hugging Face already had a standard viewer/format, so I pointed them at the actual changelog entry.
  10. Outcome · +1h 45m
    Rebuilt the dataset generator to emit official Codex-compatible session JSONL under traces/ with metadata/ sidecars, added dict-key and path/secret redaction, re-ran safety scans clean, and re-synced README/submission-notes to reference the official Agent Traces format before final upload.
VERDICT

Next time I'd tell the agent up front to check for an officially supported artifact format (like HF's agent-trace-viewer) before inventing a custom schema for things like the trace dataset — that would have saved a whole extra redaction/rebuild cycle at the end. The correction that actually mattered was catching the ZeroGPU import-order bug and the dependency pins the HF builder silently overrides; without those the Space never would have gone from BUILD_ERROR to RUNNING. Otherwise the agent was thorough about not leaking secrets or local paths and kept everything in a single clean co-authored commit.'

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