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OpenCircuitDev/opencircuitmodel

OpenCircuitModel (OCM)

A free, open-source personal AI agent that lives on your machine, remembers everything, and grows in capability as the mesh grows. Apache 2.0 licensed.

Status: v1 mostly built, not yet released. The daemon (Tauri + Rust) compiles end-to-end with HTTP + MCP API surfaces, library-driven Mem0 retrieval, llama.cpp / vLLM inference adapters, a SvelteKit chat UI, settings panel, and curated model registry. The release workflow is wired but no v0.1.0 tag has been cut yet. See "What's built" below for the per-crate state.

Website (planned): ocm.shortcircuit.bot — under the shortcircuit.bot ecosystem.


What OCM is

A peer-to-peer mesh that gives every participant access to AI agent compute by sharing the idle GPU/NPU cycles of their own machine. SETI@home-style volunteer compute, bidirectional, AI-agent-focused.

The user pitch: "Your personal AI agent — lives on your machine, persistent memory, OpenAI-compatible API, free, private. Give compute when you're idle, draw compute when you need it."

The contributor pitch: "Run OCM on your Mac Mini or gaming PC. Other users access AI through your idle GPU; you get cloud-tier agent capability through theirs."

OCM is built as a stack of borrowed open-source frameworks plus a thin original orchestration layer — vLLM/SGLang for inference, llama.cpp for Apple Silicon, Mem0 for persistent memory, libp2p/iroh for mesh transport, MCP + OpenAI-compat for the client API. The novel work is the orchestration and reciprocity ledger.

What ships when

Version What Effort Status
v1 Single-node personal agent — works standalone, no mesh required 8-12 wks Mostly built; pre-release
v2 Two-node mesh via iroh / libp2p 6-8 wks Trait scaffold landed; impl pending
v3 Reciprocity ledger (give-to-get accounting) 4-6 wks After v2
v4 Public bootnet + codesigned daemon 4-6 wks After v3
v5 Sandboxing + Sybil resistance 6-10 wks After v4
v6 Sharded inference for frontier models (Exo / Prima.cpp patterns) 8-12 wks After v5

v1 is a useful product on its own — a free, local, persistent AI agent with an OpenAI-compatible API and an MCP server. The mesh comes later.

Why this might work

  • Open foundation models (Llama 3.1, Qwen3, DeepSeek V3, Mistral) have closed the quality gap with closed cloud APIs
  • The frameworks for distributed inference, efficient serving, mesh transport, and persistent agent memory all exist as mature OSS — OCM is mostly orchestration
  • MCP and OpenAI-compatible APIs let any client (Claude Code, Cursor, Cline, Continue.dev, ChatGPT Connectors, Gemini, etc.) plug in immediately
  • Consumer hardware — especially Apple Silicon Mac Mini class — is now genuinely capable of useful agent workloads
  • Stacking efficiency multipliers (Q4 quantization × continuous batching × RadixAttention prefix-caching × EAGLE-3 speculative decoding × Qwen3-30B-A3B MoE) gets ~20-30× aggregate throughput per node, ~80× quality-adjusted, vs naive single-stream FP16 serving. Fewer machines deliver more aggregate compute than the naive math suggests.

Why this might not work

OCM is a hard project, and we want to be honest about that.

  • Petals — the closest prior art for "BitTorrent-style LLM inference" — is functionally dead as of 2026. Working tech, never crossed escape velocity.
  • Folding@home only mobilized millions during a galvanizing event (COVID) and lost 99% of capacity post-event.
  • 60% of solo OSS maintainers are unpaid; 60% are considering quitting; 44% cite burnout (Tidelift 2024 survey).
  • Median GitHub Sponsors monthly income: $50. Caleb Porzio's $100K/yr is exceptional.
  • The realistic best-case OSS exit is the llama.cpp pattern — acquired by Hugging Face (Feb 2026) with team retained and full autonomy. Not IPO.

OCM-as-described is a 24-month bet on mission + learning + optionality. The realistic financial outcome distribution:

Outcome Probability
Burnout / archive at month 14 50-60%
Niche subsistence ($5-10K/mo blended income, real users) 25-30%
Acquired/folded with team retained (llama.cpp pattern) 10-15%
Foundation / open-core breakout ($200K-$2M ARR, small team) 5-10%

If you're considering contributing or running a node, do so because you believe in the mission. Not because you expect financial return.

License

Apache 2.0 — see LICENSE. Choose your own license for derivative works as Apache permits.

What's built

Daemon + API (Rust workspace)

Crate Role State
ocm-daemon Tauri desktop shell — system tray, settings, app paths, supervises subprocesses, hosts the API server. Tauri commands for settings (get/save) and model downloads (list/download). Built
ocm-api OpenAI-compat HTTP server (/v1/models, /v1/chat/completions with SSE streaming, /v1/registry/models). Library-driven Mem0 retrieval before every chat turn. Localhost-only auth middleware. Built
ocm-inference InferenceBackend trait + llama.cpp + vLLM adapters + supervisor. Auto-selects backend by platform. Built
ocm-memory Mem0 client (search before generation, persist after). Built
ocm-mcp MCP stdio JSON-RPC bridge. Lets Claude Code / Cursor / Cline / Continue.dev connect via standard MCP. Built
ocm-models Curated registry (3 GGUFs across tiny / default tiers, all SHA256-verified; canonical tier returns in v0.1.1) + streaming verified downloader. Refuses unverified hashes. Built
ocm-mesh Mesh transport trait + iroh / libp2p stubs. Real implementations land in v2. Scaffolded

Frontend (frontend/, SvelteKit 2 + Svelte 5 + adapter-static)

Route What State
/ Chat UI with SSE streaming, model picker, abort-to-stop Built
/models/ Browse the curated registry, download with status feedback (Tauri-only) Built
/settings/ Edit all 7 settings.toml fields, save via Tauri command Built

Built with Tailwind v4, TypeScript strict mode, svelte-check 0 errors / 0 warnings.

Bench framework (bench/)

Hypothesis-based sandbox runner. First isolation sandbox (vllm-q4-llama8b on RTX 4090) wired with expected.json. Multipass-fleet mesh-discovery sandbox stub committed for v2 activation.

Release pipeline

.github/workflows/release.yml builds .dmg (mac aarch64 + x86_64), .msi (windows), .deb + .AppImage (linux) on tag push. Drafts a GitHub Release with auto-generated notes. Codesigning + auto-update deferred to v4 per spec. See docs/release-process.md.

Design + research artifacts

Everything in docs/superpowers/ informed the architecture:

What's NOT built yet

  • Real iroh/libp2p mesh transport (v2)
  • Reciprocity ledger (v3)
  • Codesigning + auto-update (v4)
  • Sandboxing + Sybil resistance (v5)
  • Sharded inference (v6)
  • Qwen3 canonical-tier registry entries (dropped pending verified hashes; return in v0.1.1 — the shipping 3-model registry is fully SHA256-verified)
  • Live deployment on ocm.shortcircuit.bot — domain reserved, site not yet up

Contributing

Code contributions are welcome. Per-area:

  • Daemon / API — Rust 1.78+, cargo test --workspace runs the suite locally. CI verifies fmt + clippy + tests across ubuntu / macos / windows.
  • Frontend — Node 20+, cd frontend && npm install && npm run dev for HMR. npm run check for svelte-check + tsc.
  • Spec / research — critical reading is still a high-leverage contribution. Flag where the analysis is wrong, the assumptions are off, or the architecture has a hidden flaw.

File issues at github.com/OpenCircuitDev/opencircuitmodel/issues.

Acknowledgments

OCM stands on the shoulders of every project named in the research synthesis: vLLM, SGLang, llama.cpp, MLX-LM, MLC-LLM, Mem0, Smolagents, DSPy, libp2p, iroh, Exo, Prima.cpp, Hivemind, Letta, Outlines, Instructor, Tauri, the MCP working group, and the Folding@home / BitTorrent / IPFS / Storj / Filecoin / Tor projects whose patterns inform the mesh and reciprocity design.

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A free, open-source personal AI agent with persistent memory. Apache 2.0. Pre-v1 — design + research phase.

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