This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady
What I Built
When I return to a repository after a break, I need to reconstruct more than the latest diff. What was I trying to do? Did a PR merge? What did a reviewer ask for? Where did my coding-agent conversation stop?
While I Was Away turns that scattered context into one briefing. I select a local repository and, optionally, specific agent sessions. The app reads Git history and working-tree changes, syncs my GitHub PRs on request, and uses a local Gemma model to explain the evidence. It puts “Your next step” first, links claims to their sources, and gives me an editable handoff prompt to copy into my coding agent.
The benefit is less manual context reconstruction. I have not measured time saved, so I am not claiming a speedup.
Demo
Watch the 20-second demo. It shows a briefing, source evidence, PR states, an agent conversation, and the editable handoff.
The recording is synthetic and silent. Its briefing is precomputed; watching it does not run Gemma or contact GitHub. The installed local application supports real inference and explicit authenticated GitHub sync.
Code
RishavRajSingh44
/
while-i-was-away
Local-first developer briefings from Git, GitHub PRs, selected agent sessions, and Gemma
While I Was Away
Close your laptop. Lose the context. Get it back in one briefing.
While I Was Away is a local developer app that combines read-only Git state, your GitHub PRs, selected coding-agent sessions and a real local Gemma briefing. A briefing shows where you stopped, what changed, what needs attention and one next action. Every source can be opened from its citation. It produces an editable, secret-redacted handoff prompt and Markdown export.
The synthetic demo needs no GitHub account, repository or model. It is explicitly labeled and never substitutes for a real briefing. A separate public static demo contains only synthetic precomputed data and cannot access files, GitHub or Ollama.
Setup (macOS first)
Requirements: Python 3.11+, Node 20.19+ or 22.12+, npm, Git, GitHub CLI for PR sync, and Ollama for real briefing synthesis. The app works offline with local Git and cached GitHub data. GitHub sync and…
The public repository contains the application, setup instructions, tests, synthetic demo data, and third-party notices. The application code is MIT-licensed; Gemma weights are obtained separately under Gemma’s terms.
How I Built It
The interface uses React, TypeScript, and Vite. A loopback-only FastAPI backend reads local Git state without changing the worktree. GitHub CLI supplies authenticated PR data while retaining its own credentials. SQLite stores snapshots, acknowledged checkpoints, cached PR facts, selected session imports, and a recoverable briefing queue.
The app supports manual transcript imports and selected Codex and Claude sessions. It also has a read-only Entire checkpoint adapter, though compatibility with the current Entire CLI remains experimental: I tested synthetic checkpoint refs, not a checkpoint produced by that tool.
For synthesis, gemma3:4b runs locally through Ollama. The app bounds the evidence, asks for structured output, and validates every cited evidence ID. Deterministic Git and PR facts remain separate from the model’s interpretation. One real inference run over a temporary synthetic repository, four synthetic PRs, and a synthetic conversation took 39.605 seconds on an Apple arm64 machine with 48 GiB RAM. The suggested next action followed the latest user direction. The model also placed a historical goal under “What changed,” showing that a valid citation does not guarantee perfect interpretation.
Local checks passed 73 backend tests, 11 frontend tests, lint, type checks, builds, and browser flows. Authenticated read-only sync handled 23 real merged PRs; open, draft, and closed-without-merge states were fixture-tested. The corrected GitHub Actions run passed its configured checks.
Why Does Open Innovation Matter?
The model is replaceable, and the prompts and evidence rules are inspectable. Local Git and cached GitHub data remain useful offline. With a compatible installed model, briefing synthesis can run without sending code or conversations to a cloud inference API by default.
That does not make the app cost-free or guarantee perfect privacy: local hardware, electricity, redaction limits, and export choices still matter. Gemma is an open-weight model under its own terms; the application is MIT-licensed software.
My Agent Session
The Lazy Payoff
Prize Categories
Best Use of Gemma
Best Use of GitHub Copilot
Top comments (0)