211 lines
7.6 KiB
Markdown
211 lines
7.6 KiB
Markdown
# OpenFang Project Research
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**Date**: 2026-02-26
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**Scope**: GitHub projects using the "OpenFang" name
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---
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## Summary
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There are three distinct projects on GitHub that share the "OpenFang" name:
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| Project | Domain | Language | License | Stars | Status |
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|---------|--------|----------|---------|-------|--------|
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| [RightNow-AI/openfang](https://github.com/RightNow-AI/openfang) | Agent Operating System | Rust | MIT / Apache 2.0 | ~979 | Active (v0.1.0, Feb 2026) |
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| [anmaped/openfang](https://github.com/anmaped/openfang) | Camera firmware (Ingenic T20) | PHP/Shell | GPL-3.0 | ~188 | Dormant (last release 2018) |
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| [danshorstein/OpenFang](https://github.com/danshorstein/OpenFang) | Python AI assistant | Python | Unknown | Low | Fork of OpenClaw |
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---
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## 1. RightNow-AI/openfang — Agent Operating System (Primary)
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**Website**: [openfang.sh](https://www.openfang.sh/)
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**Repo**: [github.com/RightNow-AI/openfang](https://github.com/RightNow-AI/openfang)
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**Built by**: Jaber (RightNow AI)
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### What It Is
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OpenFang is a **production-grade Agent Operating System** built from scratch in Rust. It is not a chatbot framework or a Python wrapper around an LLM — it is a full operating system for autonomous agents that run 24/7, building knowledge graphs, monitoring targets, generating leads, and managing social media.
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The entire system compiles to a **single ~32 MB binary**.
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### Key Numbers
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- **137,728** lines of Rust code across **14 crates**
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- **1,767+** passing tests, **0** clippy warnings
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- **30** pre-built agents across 4 performance tiers
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- **40** channel adapters (Telegram, Discord, Slack, WhatsApp, Signal, Matrix, etc.)
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- **38** built-in tools + MCP integration
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- **27** LLM providers supporting **123+** models
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- **16** security systems
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- **v0.1.0** — first public release (February 2026)
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### Performance Benchmarks
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| Metric | OpenFang | OpenClaw | CrewAI | AutoGen |
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|--------|----------|----------|--------|---------|
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| Cold Start | 180ms | 5.98s | 3s | — |
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| Idle Memory | 40MB | 394MB | 250MB | — |
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| Install Size | 32MB | 500MB | — | 200MB |
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### The 7 "Hands" (Autonomous Agents)
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1. **Clip** — Video processing: downloads YouTube content, creates vertical shorts with captions
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2. **Lead** — Daily prospect discovery with ICP matching and qualification scoring
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3. **Collector** — OSINT intelligence with continuous monitoring and change detection
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4. **Predictor** — Superforecasting engine with calibrated reasoning and accuracy tracking
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5. **Researcher** — Cross-references sources using CRAAP criteria with APA citations
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6. **Twitter** — Account management across 7 content formats with approval gates
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7. **Browser** — Web automation with mandatory purchase approval safeguards
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### 14 Core Rust Crates
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| Crate | Purpose |
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|-------|---------|
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| `openfang-kernel` | Orchestration, workflows, RBAC |
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| `openfang-runtime` | Agent loop, 53 tools, WASM sandbox |
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| `openfang-api` | 140+ REST/WS/SSE endpoints |
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| `openfang-channels` | 40 messaging adapters |
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| `openfang-memory` | SQLite persistence, vector embeddings |
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| `openfang-skills` | 60 bundled skills |
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| `openfang-hands` | Lifecycle management for autonomous agents |
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| `openfang-extensions` | 25 MCP templates |
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| `openfang-wire` | P2P protocol |
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| `openfang-cli` | Daemon management |
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| `openfang-desktop` | Tauri 2.0 native app |
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| `openfang-migrate` | OpenClaw/LangChain migration |
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### 16 Security Systems
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1. WASM dual-metered sandbox (fuel + epoch interruption)
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2. Merkle hash-chain audit trails
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3. Information flow taint tracking
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4. Ed25519 signed agent manifests
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5. SSRF protection
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6. Secret zeroization
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7. OFP mutual authentication (HMAC-SHA256)
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8. Capability gates (role-based access)
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9. Security headers (CSP, HSTS, X-Frame-Options)
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10. Health endpoint redaction
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11. Subprocess sandbox with environment isolation
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12. Prompt injection scanner
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13. Loop guard with circuit breaker
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14. Session repair (7-phase validation)
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15. Path traversal prevention
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16. GCRA rate limiter
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### Protocol Support
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- **MCP** (Model Context Protocol)
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- **A2A** (Agent-to-Agent)
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- **OFP** (OpenFang Protocol — proprietary P2P with HMAC-SHA256 mutual auth)
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### LLM Providers (27)
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Anthropic, OpenAI, Google Gemini, Groq, DeepSeek, Mistral, xAI, Ollama, AWS Bedrock, and 18+ others — supporting 123+ models total.
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### Installation
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```bash
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# macOS/Linux
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curl -fsSL https://openfang.sh/install | sh
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openfang init
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openfang start
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# Dashboard: http://localhost:4200
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# Windows
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irm https://openfang.sh/install.ps1 | iex
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```
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### Key Differentiators
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- Single binary deployment — no Python, no Node, no Docker required
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- OpenAI-compatible API — drop-in replacement capability
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- Migration engine — imports from OpenClaw, LangChain, AutoGPT
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- Dashboard-first — web UI at localhost:4200
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- Desktop app — native Tauri 2.0 application with system tray
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---
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## 2. anmaped/openfang — Camera Firmware
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**Repo**: [github.com/anmaped/openfang](https://github.com/anmaped/openfang)
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### What It Is
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An open-source bootloader, kernel, and toolchain for IP cameras using **Ingenic T10 and T20 SoCs**. This was one of the early community firmware projects for cheap Chinese IP cameras.
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### Supported Devices
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| SoC | RAM | Cameras |
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|-----|-----|---------|
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| Ingenic T20L | 64MB DDR | Xiaomi Mijia 2018, Xiaomi Xiaofang 1S |
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| Ingenic T20N | 64MB DDR + SIMD128 | DIGOO DG W30 |
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| Ingenic T20X | 128MB DDR | Wyze Cam V2, Xiaomi Dafang, Wyze Cam Pan |
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### Technical Details
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- Kernel version 3.10.14
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- U-Boot bootloader v2013.07
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- Buildroot-based toolchain
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- Docker support for compilation
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- GPL-3.0 license
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### Status
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- **Last release**: RC5 (November 2018) — **dormant**
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- 188 stars, 43 forks, 10 contributors
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- Largely superseded by [OpenMiko](https://github.com/openmiko/openmiko), [OpenIPC](https://github.com/OpenIPC), and [Thingino](https://thingino.com/)
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---
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## 3. danshorstein/OpenFang — Python AI Assistant
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**Repo**: [github.com/danshorstein/OpenFang](https://github.com/danshorstein/OpenFang)
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### What It Is
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An open-source fork of **OpenClaw** that rethinks personal AI agents. Built on the principle that "LLMs should write automations, not be automations."
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### Key Claims
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- 90%+ reduction in token costs
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- Faster execution and more reliable automations
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- System gets cheaper over time as workflows graduate from LLM-orchestrated to Python-automated
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### Status
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Low activity, small community. Positioned as a philosophical alternative to the mainstream agent frameworks.
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---
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## Analysis & Relevance
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### Most Notable: RightNow-AI/openfang
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The **RightNow-AI** variant is by far the most significant project:
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- **Active development** with a February 2026 v0.1.0 release
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- **Rust-based architecture** — high performance, single binary, low memory
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- **Comprehensive agent ecosystem** — 30 agents, 40 channels, 38 tools
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- **Strong security posture** — 16 dedicated security systems
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- **Production-oriented** — not a research project or toy framework
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### Potential Relevance to RuVector
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- The Rust architecture and WASM sandbox approach could inform solver optimization strategies
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- The 14-crate modular design demonstrates a scalable Rust workspace pattern
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- The security systems (especially taint tracking, prompt injection scanning) are relevant to any AI-adjacent system
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- The performance benchmarks (180ms cold start, 40MB idle) set a useful reference point
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---
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## Sources
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- [RightNow-AI/openfang (GitHub)](https://github.com/RightNow-AI/openfang)
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- [OpenFang.sh (Website)](https://www.openfang.sh/)
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- [anmaped/openfang (GitHub)](https://github.com/anmaped/openfang)
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- [danshorstein/OpenFang (GitHub)](https://github.com/danshorstein/OpenFang)
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- [OpenMiko (GitHub)](https://github.com/openmiko/openmiko)
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- [OpenIPC (GitHub)](https://github.com/OpenIPC)
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