RightNow-AI/openfang

Perfil de RightNow-AI

Última atividade de origem registrada: 30 de março de 2026 às 11:35

Catálogo do SkillsMP atualizado: 26 de outubro de 2026 às 11:37

skills coletadas: 70

Estrelas no GitHub: 18.227
Forks no GitHub: 2.286

README do repositório

Arquivo de origem do README: README.md

Ler o README original

Expandir README completo

<img src="public/assets/openfang-logo.png" width="160" alt="OpenFang Logo" /> <h1 align="center">OpenFang</h1> <h3 align="center">The Agent Operating System</h3> Open-source Agent OS built in Rust. 137K LOC. 14 crates. 1,767+ tests. Zero clippy warnings. One binary. Battle-tested. Agents that actually work for you. <a href="https://openfang.sh/docs">Documentation</a> • <a href="https://openfang.sh/docs/getting-started">Quick Start</a> • <a href="https://x.com/openfangg">Twitter / X</a> <img src="https://img.shields.io/badge/language-Rust-orange?style=flat-square" alt="Rust" /> <img src="https://img.shields.io/badge/license-MIT-blue?style=flat-square" alt="MIT" /> <img src="https://img.shields.io/badge/version-0.6.9-green?style=flat-square" alt="v0.6.9" /> <img src="https://img.shields.io/badge/tests-2,696%2B%20passing-brightgreen?style=flat-square" alt="Tests" /> <img src="https://img.shields.io/badge/clippy-0%20warnings-brightgreen?style=flat-square" alt="Clippy" /> <a href="https://www.buymeacoffee.com/openfang" target="_blank"><img src="https://img.shields.io/badge/Buy%20Me%20a%20Coffee-FFDD00?style=flat-square&logo=buy-me-a-coffee&logoColor=black" alt="Buy Me A Coffee" /></a> --- > **v0.5.10 (April 2026)** > > OpenFang is feature complete but still pre-1.0. Expect rough edges and breaking changes between minor versions. We ship fast and fix fast. Pin to a specific commit for production use until v1.0. [Report issues here.](https://github.com/RightNow-AI/openfang/issues) --- ## What is OpenFang? OpenFang is an **open-source Agent Operating System**. Not a chatbot framework. Not a Python wrapper around an LLM. Not a "multi-agent orchestrator." A full operating system for autonomous agents, built from scratch in Rust. Traditional agent frameworks wait for you to type something. OpenFang runs **autonomous agents that work for you**: on schedules, 24/7, building knowledge graphs, monitoring targets, generating leads, managing your social media, and reporting results to your dashboard. The entire system compiles to a **single ~32MB binary**. One install, one command, your agents are live. ```bash curl -fsSL https://openfang.sh/install | sh openfang init openfang start # Dashboard live at http://localhost:4200 ``` <details> <summary>Windows</summary> ```powershell irm https://openfang.sh/install.ps1 | iex openfang init openfang start ``` </details> --- ## Hands: Agents That Actually Do Things "Traditional agents wait for you to type. Hands work for you." **Hands** are OpenFang's core innovation. Pre-built autonomous capability packages that run independently, on schedules, without you having to prompt them. This is not a chatbot. This is an agent that wakes up at 6 AM, researches your competitors, builds a knowledge graph, scores the findings, and delivers a report to your Telegram before you've had coffee. Each Hand bundles: - **HAND.toml**: manifest declaring tools, settings, requirements, and dashboard metrics. - **System Prompt**: multi-phase operational playbook. Not a one-liner. These are 500+ word expert procedures. - **SKILL.md**: domain expertise reference injected into context at runtime. - **Guardrails**: approval gates for sensitive actions (e.g. Browser Hand requires approval before any purchase). All compiled into the binary. No downloading, no pip install, no Docker pull. ### The 7 Bundled Hands | Hand | What It Actually Does | |------|----------------------| | **Clip** | Takes a YouTube URL, downloads it, identifies the best moments, cuts them into vertical shorts with captions and thumbnails, optionally adds AI voice-over, and publishes to Telegram and WhatsApp. 8-phase pipeline. FFmpeg + yt-dlp + 5 STT backends. | | **Lead** | Runs daily. Discovers prospects matching your ICP, enriches them with web research, scores 0-100, deduplicates against your existing database, and delivers qualified leads in CSV/JSON/Markdown. Builds ICP profiles over time. | | **Collector** | OSINT grade intelligence. You give it a target (company, person, topic). It monitors continuously: change detection, sentiment tracking, knowledge graph construction, and critical alerts when something important shifts. | | **Predictor** | Superforecasting engine. Collects signals from multiple sources, builds calibrated reasoning chains, makes predictions with confidence intervals, and tracks its own accuracy using Brier scores. Has a contrarian mode that deliberately argues against consensus. | | **Researcher** | Deep autonomous researcher. Cross-references multiple sources, evaluates credibility using CRAAP criteria (Currency, Relevance, Authority, Accuracy, Purpose), generates cited reports with APA formatting, supports multiple languages. | | **Twitter** | Autonomous Twitter/X account manager. Creates content in 7 rotating formats, schedules posts for optimal engagement, responds to mentions, tracks performance metrics. Has an approval queue, so nothing posts without your OK. | | **Browser** | Web automation agent. Navigates sites, fills forms, clicks buttons, handles multi-step workflows. Uses Playwright bridge with session persistence. **Mandatory purchase approval gate**: it will never spend your money without explicit confirmation. | ```bash # Activate the Researcher Hand. It starts working immediately. openfang hand activate researcher # Check its progress anytime openfang hand status researcher # Activate lead generation on a daily schedule openfang hand activate lead # Pause without losing state openfang hand pause lead # See all available Hands openfang hand list ``` **Build your own.** Define a `HAND.toml` with tools, settings, and a system prompt. Publish to FangHub. --- ## OpenFang vs The Landscape <img src="public/assets/openfang-vs-claws.png" width="600" alt="OpenFang vs OpenClaw vs ZeroClaw" /> ### Benchmarks: Measured, Not Marketed All data from official documentation and public repositories, February 2026. #### Cold Start Time (lower is better) ``` ZeroClaw ██░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 10 ms OpenFang ██████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 180 ms ★ LangGraph █████████████████░░░░░░░░░░░░░░░░░░░░░░░░░ 2.5 sec CrewAI ████████████████████░░░░░░░░░░░░░░░░░░░░░░ 3.0 sec AutoGen ██████████████████████████░░░░░░░░░░░░░░░░░ 4.0 sec OpenClaw █████████████████████████████████████████░░ 5.98 sec ``` #### Idle Memory Usage (lower is better) ``` ZeroClaw █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 5 MB OpenFang ████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 40 MB ★ LangGraph ██████████████████░░░░░░░░░░░░░░░░░░░░░░░░░ 180 MB CrewAI ████████████████████░░░░░░░░░░░░░░░░░░░░░░░ 200 MB AutoGen █████████████████████████░░░░░░░░░░░░░░░░░░ 250 MB OpenClaw ████████████████████████████████████████░░░░ 394 MB ``` #### Install Size (lower is better) ``` ZeroClaw █░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 8.8 MB OpenFang ███░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 32 MB ★ CrewAI ████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 100 MB LangGraph ████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 150 MB AutoGen ████████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░ 200 MB OpenClaw ████████████████████████████████████████░░░░ 500 MB ``` #### Security Systems (higher is better) ``` OpenFang ████████████████████████████████████████████ 16 ★ ZeroClaw ███████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 6 OpenClaw ████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 3 AutoGen █████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 2 LangGraph █████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 2 CrewAI ███░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 1 ``` #### Channel Adapters (higher is better) ``` OpenFang ████████████████████████████████████████████ 40 ★ ZeroClaw ███████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 15 OpenClaw █████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 13 CrewAI ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0 AutoGen ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0 LangGraph ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 0 ``` #### LLM Providers (higher is better) ``` ZeroClaw ████████████████████████████████████████████ 28 OpenFang ██████████████████████████████████████████░░ 27 ★ LangGraph ██████████████████████░░░░░░░░░░░░░░░░░░░░░ 15 CrewAI ██████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 10 OpenClaw ██████████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 10 AutoGen ███████████░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 8 ``` ### Feature-by-Feature Comparison | Feature | OpenFang | OpenClaw | ZeroClaw | CrewAI | AutoGen | LangGraph | |---------|----------|----------|----------|--------|---------|-----------| | **Language** | **Rust** | TypeScript | **Rust** | Python | Python | Python | | **Autonomous Hands** | **7 built-in** | None | None | None | None | None | | **Security Layers** | **16 discrete** | 3 basic | 6 layers | 1 basic | Docker | AES enc. | | **Agent Sandbox** | **WASM dual-metered** | None | Allowlists | None | Docker | None | | **Channel Adapters** | **40** | 13 | 15 | 0 | 0 | 0 | | **Built-in Tools** | **53 + MCP + A2A** | 50+ | 12 | Plugins | MCP | LC tools | | **Memory** | **SQLite + vector** | File-based | SQLite FTS5 | 4-layer | External | Checkpoints | | **Desktop App** | **Tauri 2.0** | None | None | None | Studio | None | | **Audit Trail** | **Merkle hash-chain** | Logs | Logs | Tracing | Logs | Checkpoints | | **Cold Start** | **<200ms** | ~6s | ~10ms | ~3s | ~4s | ~2.5s | | **Install Size** | **~32 MB** | ~500 MB | ~8.8 MB | ~100 MB | ~200 MB | ~150 MB | | **License** | MIT | MIT | MIT | MIT | Apache 2.0 | MIT | --- ## 16 Security Systems: Defense in Depth OpenFang doesn't bolt security on after the fact. Every layer is independently testable and operates without a single point of failure. | # | System | What It Does | |---|--------|-------------| | 1 | **WASM Dual-Metered Sandbox** | Tool code runs in WebAssembly with fuel metering + epoch interruption. A watchdog thread kills runaway code. | | 2 | **Merkle Hash-Chain Audit Trail** | Every action is cryptographically linked to the previous one. Tamper with one entry and the entire chain breaks. | | 3 | **Information Flow Taint Tracking** | Labels propagate through execution. Secrets are tracked from source to sink. | | 4 | **Ed25519 Signed Agent Manifests** | Every agent identity and capability set is cryptographically signed. | | 5 | **SSRF Protection** | Blocks private IPs, cloud metadata endpoints, and DNS rebinding attacks. | | 6 | **Secret Zeroization** | `Zeroizing<String>` auto-wipes API keys from memory the instant they're no longer needed. | | 7 | **OFP Mutual Authentication** | HMAC-SHA256 nonce-based, constant-time verification for P2P networking. | | 8 | **Capability Gates** | Role based access control. Agents declare required tools, the kernel enforces it. | | 9 | **Security Headers** | CSP, X-Frame-Options, HSTS, X-Content-Type-Options on every response. | | 10 | **Health Endpoint Redaction** | Public health check returns minimal info. Full diagnostics require authentication. | | 11 | **Subprocess Sandbox** | `env_clear()` + selective variable passthrough. Process tree isolation with cross-platform kill. | | 12 | **Prompt Injection Scanner** | Detects override attempts, data exfiltration patterns, and shell reference injection in skills. | | 13 | **Loop Guard** | SHA256-based tool call loop detection with circuit breaker. Handles ping-pong patterns. | | 14 | **Session Repair** | 7-phase message history validation and automatic recovery from corruption. | | 15 | **Path Traversal Prevention** | Canonicalization with symlink escape prevention. ``../`` doesn't work here. | | 16 | **GCRA Rate Limiter** | Cost-aware token bucket rate limiting with per-IP tracking and stale cleanup. | --- ## Architecture 14 Rust crates. 137,728 lines of code. Modular kernel design. ``` openfang-kernel Orchestration, workflows, metering, RBAC, scheduler, budget tracking openfang-runtime Agent loop, 3 LLM drivers, 53 tools, WASM sandbox, MCP, A2A openfang-api 140+ REST/WS/SSE endpoints, OpenAI-compatible API, dashboard openfang-channels 40 messaging adapters with rate limiting, DM/group policies openfang-memory SQLite persistence, vector embeddings, canonical sessions, compaction openfang-types Core types, taint tracking, Ed25519 manifest signing, model catalog openfang-skills 60 bundled skills, SKILL.md parser, FangHub marketplace openfang-hands 7 autonomous Hands, HAND.toml parser, lifecycle management openfang-extensions 25 MCP templates, AES-256-GCM credential vault, OAuth2 PKCE openfang-wire OFP P2P protocol with HMAC-SHA256 mutual authentication openfang-cli CLI with daemon management, TUI dashboard, MCP server mode openfang-desktop Tauri 2.0 native app (system tray, notifications, global shortcuts) openfang-migrate OpenClaw, LangChain, AutoGPT migration engine xtask Build automation ``` --- ## 40 Channel Adapters Connect your agents to every platform your users are on. **Core:** Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email (IMAP/SMTP) **Enterprise:** Microsoft Teams, Mattermost, Google Chat, Webex, Feishu/Lark, Zulip **Social:** LINE, Viber, Facebook Messenger, Mastodon, Bluesky, Reddit, LinkedIn, Twitch **Community:** IRC, XMPP, Guilded, Revolt, Keybase, Discourse, Gitter **Privacy:** Threema, Nostr, Mumble, Nextcloud Talk, Rocket.Chat, Ntfy, Gotify **Workplace:** Pumble, Flock, Twist, DingTalk, Zalo, Webhooks Each adapter supports per-channel model overrides, DM/group policies, rate limiting, and output formatting. --- ## WhatsApp Web Gateway (QR Code) Connect your personal WhatsApp account to OpenFang via QR code, just like WhatsApp Web. No Meta Business account required. ### Prerequisites - **Node.js >= 18** installed ([download](https://nodejs.org/)) - OpenFang installed and initialized ### Setup **1. Install the gateway dependencies:** ```bash cd packages/whatsapp-gateway npm install ``` **2. Configure `config.toml`:** ```toml [channels.whatsapp] mode = "web" default_agent = "assistant" ``` **3. Set the gateway URL (choose one):** Add to your shell profile for persistence: ```bash # macOS / Linux echo 'export WHATSAPP_WEB_GATEWAY_URL="http://127.0.0.1:3009"' >> ~/.zshrc source ~/.zshrc ``` Or set it inline when starting the gateway: ```bash export WHATSAPP_WEB_GATEWAY_URL="http://127.0.0.1:3009" ``` **4. Start the gateway:** ```bash node packages/whatsapp-gateway/index.js ``` The gateway listens on port `3009` by default. Override with `WHATSAPP_GATEWAY_PORT`. **5. Start OpenFang:** ```bash openfang start # Dashboard at http://localhost:4200 ``` **6. Scan the QR code:** Open the dashboard → **Channels** → **WhatsApp**. A QR code will appear. Scan it with your phone: > **WhatsApp** → **Settings** → **Linked Devices** → **Link a Device** Once scanned, the status changes to `connected` and incoming messages are routed to your configured agent. ### Gateway Environment Variables | Variable | Description | Default | |----------|-------------|---------| | `WHATSAPP_WEB_GATEWAY_URL` | Gateway URL for OpenFang to connect to | _(empty = disabled)_ | | `WHATSAPP_GATEWAY_PORT` | Port the gateway listens on | `3009` | | `OPENFANG_URL` | OpenFang API URL the gateway reports to | `http://127.0.0.1:4200` | | `OPENFANG_DEFAULT_AGENT` | Agent that handles incoming messages | `assistant` | ### Gateway API Endpoints | Method | Route | Description | |--------|-------|-------------| | `POST` | `/login/start` | Generate QR code (returns base64 PNG) | | `GET` | `/login/status` | Connection status (`disconnected`, `qr_ready`, `connected`) | | `POST` | `/message/send` | Send a message (`{ "to": "5511999999999", "text": "Hello" }`) | | `GET` | `/health` | Health check | ### Alternative: WhatsApp Cloud API For production workloads, use the [WhatsApp Cloud API](https://developers.facebook.com/docs/whatsapp/cloud-api) with a Meta Business account. See the [Cloud API configuration docs](https://openfang.sh/docs/channels/whatsapp). --- ## 27 LLM Providers, 123+ Models 3 native drivers (Anthropic, Gemini, OpenAI-compatible) route to 27 providers: Anthropic, Gemini, OpenAI, Groq, DeepSeek, OpenRouter, Together, Mistral, Fireworks, Cohere, Perplexity, xAI, AI21, Cerebras, SambaNova, HuggingFace, Replicate, Ollama, vLLM, LM Studio, Qwen, MiniMax, Zhipu, Moonshot, Qianfan, Bedrock, and more. Intelligent routing with task complexity scoring, automatic fallback, cost tracking, and per-model pricing. --- ## Migrate from OpenClaw Already running OpenClaw? One command: ```bash # Migrate everything: agents, memory, skills, configs. openfang migrate --from openclaw # Migrate from a specific path openfang migrate --from openclaw --path ~/.openclaw # Dry run first to see what would change openfang migrate --from openclaw --dry-run ``` The migration engine imports your agents, conversation history, skills, and configuration. OpenFang reads SKILL.md natively and is compatible with the ClawHub marketplace. --- ## OpenAI-Compatible API Drop-in replacement. Point your existing tools at OpenFang: ```bash curl -X POST localhost:4200/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "researcher", "messages": [{"role": "user", "content": "Analyze Q4 market trends"}], "stream": true }' ``` 140+ REST/WS/SSE endpoints covering agents, memory, workflows, channels, models, skills, A2A, Hands, and more. --- ## Quick Start ```bash # 1. Install (macOS/Linux) curl -fsSL https://openfang.sh/install | sh # 2. Initialize. Walks you through provider setup. openfang init # 3. Start the daemon openfang start # 4. Dashboard is live at http://localhost:4200 # 5. Activate a Hand. It starts working for you. openfang hand activate researcher # 6. Chat with an agent openfang chat researcher > "What are the emerging trends in AI agent frameworks?" # 7. Spawn a pre-built agent openfang agent spawn coder ``` <details> <summary>Windows (PowerShell)</summary> ```powershell irm https://openfang.sh/install.ps1 | iex openfang init openfang start ``` </details> --- ## Development ```bash # Build the workspace cargo build --workspace --lib # Run all tests (1,767+) cargo test --workspace # Lint (must be 0 warnings) cargo clippy --workspace --all-targets -- -D warnings # Format cargo fmt --all -- --check ``` --- ## Stability Notice OpenFang v0.5.10 is pre-1.0. The architecture is solid, the test suite is comprehensive, and the security model is deep. That said: - **Breaking changes** may occur between minor versions until v1.0. - **Some Hands** are more mature than others. Browser and Researcher are the most battle tested. - **Edge cases** exist. If you find one, [open an issue](https://github.com/RightNow-AI/openfang/issues). - **Pin to a specific commit** for production deployments until v1.0. We ship fast and fix fast. The goal is a rock solid v1.0 by mid 2026. --- ## Security To report a security vulnerability, email **jaber@rightnowai.co**. We take all reports seriously and will respond within 48 hours. --- ## License MIT. Use it however you want. --- ## Links - [Website & Documentation](https://openfang.sh) - [Quick Start Guide](https://openfang.sh/docs/getting-started) - [GitHub](https://github.com/RightNow-AI/openfang) - [Discord](https://discord.gg/sSJqgNnq6X) - [Twitter / X](https://x.com/openfangg) --- ## Built by RightNow <a href="https://www.rightnowai.co/"> <img src="public/assets/rightnow-logo.webp" width="60" alt="RightNow Logo" /> </a> OpenFang is built and maintained by <a href="https://x.com/Akashi203">Jaber</a>, Founder of <a href="https://www.rightnowai.co/">RightNow</a>. <a href="https://www.rightnowai.co/">Website</a> • <a href="https://x.com/Akashi203">Twitter / X</a> • <a href="https://www.buymeacoffee.com/openfang" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" style="height: 60px !important;width: 217px !important;" ></a> --- Built with Rust. Secured with 16 layers. Agents that actually work for you.

Carregando o README do repositório…

Skills neste repositório

Desenvolvedores de software Administradores de redes e sistemas de computador Analistas de pesquisa de mercado e especialistas em marketing Cientistas de dados

19 categorias ocupacionais · 100% classificado

skill

ocupação

descrição

atualizado