Run a local, offline AI assistant that keeps its reasoning and data entirely on your own machine.
Inspect an AI assistant's internal reasoning trace and routing decisions using built-in debug commands.
Study a neuro-symbolic architecture that combines exact math tools with a compact learned model.
| jacksonjp0311-gif/perci | bbalabs/athanor-lite | adysec/clawbot | |
|---|---|---|---|
| Stars | 38 | 38 | 37 |
| Language | Rust | Rust | Rust |
| Setup difficulty | hard | easy | moderate |
| Complexity | 5/5 | 2/5 | 3/5 |
| Audience | researcher | vibe coder | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Git LFS to pull a ~200MB model package and running verification scripts before first use.
Perci is an experimental AI assistant written in Rust that is meant to run entirely on your own machine instead of relying on a cloud AI service. The project describes itself as a small operating system for thinking, built by separating different jobs that most chat assistants hide inside one large model. It has a compact binary knowledge structure called Bitwork, about 200 megabytes in size, that handles routing and pattern matching. It has named procedures called operators that handle things like deciding whether to trust an instruction, planning a response, or writing code. It also has exact tools for math and geometry that calculate real answers instead of guessing, and a governance layer that checks results before anything is allowed to change the system permanently. When you send Perci a message, it first checks for quick reflex style responses or exact calculations, then routes the message through its Bitwork field, applies the relevant operators, and if needed builds a longer chain of reasoning that gets rewritten into plain, conversational language before being shown to you. You can inspect what happened behind a response using special commands that reveal its internal reasoning trace, and you can adjust how concise or detailed its answers are. The project places heavy emphasis on testing and measurement, publishing tables of pass and fail results from its own internal test suites that check reasoning correctness, dialogue behavior, and security boundaries, along with scripts you can run yourself to reproduce those results. Importantly, the underlying model weights can never update automatically. Any permanent change requires a human to explicitly authorize it. The full runtime package, including the Bitwork model files, is distributed through Git LFS and must be pulled down separately after cloning the repository. Perci is dual licensed under MIT or Apache 2.0.
Perci is a local-first, Rust-built AI assistant that separates reasoning into a compact binary model, named operators, and exact math tools, with all weight changes requiring human approval.
Mainly Rust. The stack also includes Rust, Git LFS, Python.
Dual-licensed MIT or Apache 2.0, use freely for any purpose including commercial use.
Setup difficulty is rated hard, with roughly 1day+ to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Don't trust strangers blindly. Verify against the repo.