OpenMonoAgent.ai

--- OpenMono is a coding agent that runs **entirely on your hardware** — no subscriptions, no data leaving your network, no per-token billing. It pairs a .NET 10 CLI with its own llama.cpp inference server, giving you a full agentic loop with **20 built-in tools**, Docker sandboxing, and deep code intelligence. NVIDIA GPU, CPU, or Apple Silicon (Metal) — **it auto-configures itself**. You own the model, the compute, and the data. --- ## Free Course — Get Started with OMA --- ## Quickstart One command. Auto-detects GPU · CPU · Apple Silicon. Installs model, runtime, and Docker containers. ```bash bash <(curl -fsSL https://raw.githubusercontent.com/StartupHakk/OpenMonoAgent.ai/refs/heads/main/get-openmono.sh) ``` Then from any project: ```bash openmono agent # TUI mode (default) openmono agent --classic # classic scrolling terminal ``` → Full command reference — daily commands, setup flags, GPU/CPU options
--- ## What's shipping Get them: openmono setup search · OPENMONO_VISION_ENABLED=1 · App Store · Google Play · VS Code Marketplace --- ## How it compares Most coding agents are cloud products wearing an open-source label. Your prompts, your code, and your context hit someone else's servers on every keystroke. OpenMono runs the model on your hardware — after the one-time setup, **inference costs nothing**. Your code never leaves the machine. No account. No usage dashboard. No API key. → [Full architecture + diagram](docs/ARCHITECTURE.md) · [4 providers](docs/MODELS.md) · runs at **~45 tok/s on GPU**, ~20 tok/s on CPU --- ## What's inside 01 · **Bundled inference — zero config, zero cost** llama.cpp ships inside Docker. Installer detects your hardware and picks the right model. After setup, every token is free. `GPU` Qwen3.8-27B dense · ~60 tok/s `CPU` Qwen3.6-35B-A3B MoE · ~20 tok/s `Mac` Qwen3.6-35B-A3B MoE · Metal · ~45–48 tok/s → [Models & reasoning mode](docs/MODELS.md) 02 · **Agentic loop that earns its name** 25 iterations per turn. Doom-loop detection aborts if the same tool sequence repeats 3×. Checkpoints at 65% context fill, compacts at 80%. Runs until done — then stops. 03 · **[20 tools](docs/ARCHITECTURE.md), 12-step pipeline** Every call: parse → schema validate → path sanity → plan-mode guard → capability check → cache → pre-hook → execute → post-hook → artifact store. Read-only tools run in parallel. Nothing bypasses the pipeline. 04 · **5 specialist sub-agents** Isolated sessions with locked tool sets and turn budgets: `Explore` · read-only discovery · 15 turns `Plan` · architecture, no writes · 10 turns `Coder` · full file access · 30 turns `Verify` · adversarial + Roslyn · 20 turns `general-purpose` · everything · 25 turns 05 · **Docker sandbox** Project mounts as `/workspace`. The agent reads and writes your real files — that's the blast radius. Nothing outside that mount is visible or reachable. 06 · **Deep code intelligence** Roslyn: type hierarchy, blast-radius, cross-file symbol search, callers, diagnostics — 5-min compilation cache. LSP for TypeScript, Python, Go, Rust, lazy-started on first use. Auto-detects [graphify](docs/graphify.md) (semantic concept graph, 25+ languages) and [code-review-graph](docs/code-review-graph.md) (structural call graph via MCP, ~22 tools) if installed — no config needed. 07 · **[Playbooks](docs/PLAYBOOKS.md)** YAML workflows with typed parameters, conditional gates, and checkpoint/resume. Composable — one playbook can call another. 08 · **[4 providers](docs/MODELS.md), hot-swappable** Local llama.cpp is the default and fully supported. OpenAI, Anthropic, and Ollama are available but WIP — see [Models](docs/MODELS.md) for details. 09 · **Distributed inference** Agent on your laptop, inference on a separate GPU machine. No port forwarding — tunnel is established outbound from the inference box. Free relay at [app.openmonoagent.ai](https://app.openmonoagent.ai). → [Dual-box setup guide](docs/SETUP.md#dual-box-setup) 10 · **Vision** Attach images in chat with `@screenshot.png` or ask the agent to read any image file. The multimodal projector (mmproj) is downloaded automatically at setup. Supported formats: PNG, JPG, GIF, WebP. Large images are auto-resized to fit within VRAM budget. Enable with `OPENMONO_VISION_ENABLED=1`. → [Vision setup & usage](docs/SETUP.md#vision) 11 · **Private web search & scraping** Self-hosted search via SearXNG — your queries never leave the machine. Anti-bot scraping via Scrapling + Camoufox (real browser, Cloudflare bypass). Single Caddy gateway, auto-detected. Falls back to DuckDuckGo / direct fetch when the gateway is absent. `openmono setup search` · `openmono setup scraper` → [Web services architecture](docs/ARCHITECTURE.md#inference-side-web-services-caddy-gateway) 12 · **VS Code extension** The full agent loop in your editor sidebar — streaming responses, live Markdown, file edits, bash, and permission prompts without leaving VS Code. Connects to the local agent over ACP on port `7475`. Also works in Cursor. `code --install-extension StartupHakk.openmono-agent` → [Extension docs](docs/SETUP.md#vs-code--cursor-extension) · [Marketplace](https://marketplace.visualstudio.com/items?itemName=StartupHakk.openmono-agent) --- ## Supported Hardware
Auto-detects GPU · CPU · no config needed. On Linux, 12 GB and 16 GB cards run lower-accuracy models; use a 24 GB card for best results. Requires Ubuntu 26.04 LTS (recommended) or 25.10. On macOS, the full and inference roles require Apple Silicon (M1+); 64 GB+ unified memory is the recommended, tested configuration. Less than 64 GB is not encouraged — smaller model, much tighter context window. Intel Macs: agent-only mode. macOS 14+ (Sonoma/Sequoia) recommended. --- ## Docs Roadmap What's next Setup & commands Daily commands, TUI vs classic, flags Architecture .NET CLI + llama.cpp + Docker, full diagram Models & reasoning Model tiers, reasoning mode, provider config Configuration settings.json, providers, permissions, MCP servers Playbooks YAML workflows, typed params, checkpoint/resume graphify Semantic code graph, 25+ languages code-review-graph Structural call graph via MCP VS Code extension Chat panel for VS Code 1.85+ · also works in Cursor · Marketplace Contributing How to contribute
PUBLIC BETA  Early access is open — we're shipping updates fast. Try it out and tell us what you'd like to see next. --- ## Contributing OpenMono is early and moving fast. Contributions are welcome — new tools, providers, LSP servers, playbooks, bug fixes, or docs. → Read the contributing guide before opening a PR ---