Faber
AI coding agent with code-graph search and lower token cost
What it does
Faber is an open-source AI coding agent for the terminal that uses a code graph to find relevant files and symbols before loading context. It reduces unnecessary context and repeated API cost through code-graph-guided search, prompt caching, and concise output. It supports Claude, OpenAI Codex, and local models, plus Git-aware workflows, undo/redo, memory, and detailed token and cost tracking.
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Launched alongside, September 2026
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