# Team Loci

- **Event:** [Google DeepMind Bangalore Hackathon](https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon)
- **When:** Sat, Jul 11 at 9:00 AM – 10:00 PM (GMT+5:30)
- **Where:** Marathahalli, Marathahalli Main Road
- **Team:** [Panendra Jadav](https://cerebralvalley.ai/u/panendrajadav)
- **GitHub:** https://github.com/panendrajadav/Loci
- **Demo video:** https://www.loom.com/share/4a4215688e6742cebe27cb6d07db958f
- **Gallery:** https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon/hackathon/gallery/158

Loci — a local, offline coding agent
Loci is a fully offline coding agent built on Gemma 4 (E2B). Describe an app you want — say, tic-tac-toe — and Loci asks the minimum clarifying questions needed, then writes a complete, working single-file app.
Unlike a typical code-generation chatbot, Loci closes the loop itself: it runs the generated code in a real headless browser, checks for errors, and if something's broken, feeds the failure back into the model and rewrites it — no user intervention required. If it can't resolve an issue after two attempts, it stops and explicitly hands the decision back to the user (simplify the feature, or inspect the code directly) rather than looping indefinitely.
Every part of this — generation, execution, testing, and retry — runs entirely on-device, with zero network calls at any point. That makes Loci viable in offline environments, on unreliable connections, or wherever sending code or data to a cloud service isn't acceptable.
Built with Flask, vanilla JS, Selenium for self-testing, and Ollama running Gemma 4 E2B locally, leveraging the model's native speculative decoding for faster on-device inference.

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Markdown version of https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon/hackathon/gallery/158. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt