Git Out: A Local Voice Companion That Helps Developers Touch Grass

A developer has released Git Out, an open-source, local-first Android voice companion that lets developers ask technical questions out loud and receive spoken answers without sending audio to the cloud. The app runs Qwen2.5-1.5B-Instruct Q4_K_M GGUF on-device via llama.rn, uses Android on-device speech recognition and TextToSpeech, and includes an optional FastAPI-backed read-only GitHub workspace that keeps the token server-side.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass https://dev.to/challenges/hacktoberfest-week1-2026-10-05 Git Out is a local-first voice companion for developers who want to think through technical problems without staying glued to a screen. The idea is simple: take a walk, ask a question out loud, and get a useful answer without opening a laptop, sending your voice to a cloud service, or losing your train of thought to a dozen tabs. Git Out is built for developers who are walking, commuting, taking a break, or working away from their desk. It can help with questions such as: The app records one deliberate voice turn, transcribes it on the Android device, generates an answer with a local Qwen model, and reads the completed answer aloud with the installed Android voice. The screen is intentionally the shortest part of the experience. Pocket Mode has large, high-contrast controls and explicit states for Ready , Listening , Transcribing , Thinking , Speaking , and Error . There is no wake word, no always-on microphone, and no automatic microphone restart in the background. Git Out also includes an optional read-only GitHub workspace. When the backend is configured, the app can show the connected account, repositories, assigned issues, pull requests, and recent commits. The GitHub token stays on the server and is never bundled into the mobile app. Video demo: The demo should show: This is an Android development build, so a short screen recording is the most useful demo format. The project is designed to be tested on a physical Android device because installed speech packs, TTS voices, audio focus, headset events, and lock-screen behavior vary by device. The complete open-source project is available here: The repository contains the React Native/Expo mobile app, the FastAPI backend, the local AI abstraction, the Android speech and TTS integrations, GitHub API services, tests, and setup documentation. Git Out is an Android-first React Native app built with Expo and a small FastAPI backend for the optional GitHub workspace. The core model is Qwen2.5-1.5B-Instruct Q4 K M GGUF , loaded on the Android device with llama.rn https://github.com/mybigday/llama.rn . The model file is selected and stored locally by the user; it is not bundled into the repository or downloaded automatically by the app. The mobile conversation path is: Voice question ↓ Android on-device speech recognition ↓ Local transcript ↓ Qwen GGUF through llama.rn ↓ Readable answer + optional Android TTS playback expo-speech-recognition checks for an installed Android on-device language pack before recording. GitOutTts Expo module wraps Android TextToSpeech . Pocket Mode is a one-shot voice workflow rather than a continuous assistant. Each tap starts one question, and the lifecycle is guarded so stale recognition or TTS callbacks cannot submit an accidental second turn. The state machine makes the interaction understandable while the user is moving: Ready → Listening → Transcribing → Thinking → Speaking ↘ Error The FastAPI service uses a server-only GITHUB TOKEN and GitHub's REST API. It exposes sanitized read endpoints for the authenticated user, repositories, assigned issues, pull requests, and commits. The mobile app only receives whitelisted response fields; it never receives the token. GitHub is intentionally separate from local inference. Local conversation keeps working when the backend or network is unavailable. The app uses a dark, minimal skeuomorphic interface: raised cards, recessed input wells, tactile buttons, subtle shadows, and clear status pills. This gives the controls a physical-device feel without adding a heavy UI library or image assets. Open innovation is what makes Git Out fit the Touch Grass theme instead of becoming another cloud chat interface. The open-weight Qwen model lets the main conversation run locally on the phone. That makes several important things possible: llama.rn , Expo modules, native Android speech APIs, and a local-first state machine in a way that can be inspected and changed. A closed hosted API could make a quick prototype, but it would move the central conversation onto a remote service and make a no-signal walking workflow much less reliable. Open components gave me the control needed to make privacy and offline behavior product features rather than marketing claims. The trade-off is honest: a small on-device model has less capacity than a large cloud model, and loading a GGUF requires enough memory on the Android phone. Git Out chooses that trade-off because a private, available answer while walking is more useful here than a larger answer that requires a network connection. I am entering the overall Hacktoberfest Open-Source AI Challenge. I am not claiming a partner category because Git Out does not currently use partner-specific technology. The repository includes automated checks for the local AI guards, speech recognition behavior, TTS lifecycle, voice-conversation transitions, Pocket Mode state changes, and duplicate media-command handling. The final frontend checks passed: npm run typecheck ✓ npm test ✓ 50 tests passed npx expo export --platform android ✓ git diff --check ✓ For the final device demo, I will report the phone model, Android version, speech service, and TTS engine used. Device-specific speech, headset, background playback, and lock-screen behavior can vary by device, so those details are part of the demo notes rather than assumptions about every Android phone. Git Out is a small experiment in making developer tooling less desk-bound. The goal is not to keep people in an AI chat window. The goal is to let them ask one useful question, hear a practical next step, and get back to the world outside the screen.