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377 lines
9.3 KiB
Markdown
377 lines
9.3 KiB
Markdown
# Getting Started with OpenFang
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This guide walks you through installing OpenFang, configuring your first LLM provider, spawning an agent, and chatting with it.
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## Table of Contents
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- [Installation](#installation)
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- [Configuration](#configuration)
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- [Spawn Your First Agent](#spawn-your-first-agent)
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- [Chat with an Agent](#chat-with-an-agent)
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- [Start the Daemon](#start-the-daemon)
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- [Using the WebChat UI](#using-the-webchat-ui)
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- [Next Steps](#next-steps)
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---
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## Installation
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### Option 1: Desktop App (Windows / macOS / Linux)
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Download the installer for your platform from the [latest release](https://github.com/RightNow-AI/openfang/releases/latest):
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| Platform | File |
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|---|---|
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| Windows | `.msi` installer |
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| macOS | `.dmg` disk image |
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| Linux | `.AppImage` or `.deb` |
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The desktop app includes the full OpenFang system with a native window, system tray, auto-updates, and OS notifications. Updates are installed automatically in the background.
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### Option 2: Shell Installer (Linux / macOS)
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```bash
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curl -sSf https://openfang.sh | sh
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```
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This downloads the latest CLI binary and installs it to `~/.openfang/bin/`.
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### Option 3: PowerShell Installer (Windows)
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```powershell
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irm https://openfang.sh/install.ps1 | iex
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```
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Downloads the latest CLI binary, verifies its SHA256 checksum, and adds it to your user PATH.
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### Option 4: Cargo Install (Any Platform)
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Requires Rust 1.75+:
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```bash
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cargo install --git https://github.com/RightNow-AI/openfang openfang-cli
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```
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Or build from source:
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```bash
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git clone https://github.com/RightNow-AI/openfang.git
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cd openfang
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cargo install --path crates/openfang-cli
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```
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### Option 5: Docker
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```bash
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docker pull ghcr.io/RightNow-AI/openfang:latest
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docker run -d \
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--name openfang \
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-p 4200:4200 \
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-e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY \
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-v openfang-data:/data \
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ghcr.io/RightNow-AI/openfang:latest
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```
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Or use Docker Compose:
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```bash
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git clone https://github.com/RightNow-AI/openfang.git
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cd openfang
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# Set your API keys in environment or .env file
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docker compose up -d
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```
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### Verify Installation
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```bash
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openfang --version
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```
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---
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## Configuration
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### Initialize
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Run the init command to create the `~/.openfang/` directory and a default config file:
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```bash
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openfang init
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```
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This creates:
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```
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~/.openfang/
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config.toml # Main configuration
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data/ # Database and runtime data
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agents/ # Agent manifests (optional)
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```
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### Set Up an API Key
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OpenFang needs at least one LLM provider API key. Set it as an environment variable:
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```bash
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# Anthropic (Claude)
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export ANTHROPIC_API_KEY=sk-ant-...
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# Or OpenAI
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export OPENAI_API_KEY=sk-...
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# Or Groq (free tier available)
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export GROQ_API_KEY=gsk_...
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```
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Add the export to your shell profile (`~/.bashrc`, `~/.zshrc`, etc.) to persist it.
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### Edit the Config
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The default config uses Anthropic. To change the provider, edit `~/.openfang/config.toml`:
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```toml
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[default_model]
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provider = "groq" # anthropic, openai, groq, ollama, etc.
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model = "llama-3.3-70b-versatile" # Model identifier for the provider
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api_key_env = "GROQ_API_KEY" # Env var holding the API key
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[memory]
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decay_rate = 0.05 # Memory confidence decay rate
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[network]
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listen_addr = "127.0.0.1:4200" # OFP listen address
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```
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### Verify Your Setup
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```bash
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openfang doctor
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```
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This checks that your config exists, API keys are set, and the toolchain is available.
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---
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## Spawn Your First Agent
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### Using a Built-in Template
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OpenFang ships with 30 agent templates. Spawn the hello-world agent:
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```bash
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openfang agent spawn agents/hello-world/agent.toml
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```
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Output:
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```
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Agent spawned successfully!
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ID: a1b2c3d4-e5f6-...
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Name: hello-world
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```
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### Using a Custom Manifest
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Create your own `my-agent.toml`:
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```toml
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name = "my-assistant"
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version = "0.1.0"
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description = "A helpful assistant"
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author = "you"
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module = "builtin:chat"
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[model]
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provider = "groq"
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model = "llama-3.3-70b-versatile"
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[capabilities]
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tools = ["file_read", "file_list", "web_fetch"]
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memory_read = ["*"]
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memory_write = ["self.*"]
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```
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Then spawn it:
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```bash
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openfang agent spawn my-agent.toml
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```
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### List Running Agents
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```bash
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openfang agent list
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```
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Output:
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```
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ID NAME STATE PROVIDER MODEL
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-----------------------------------------------------------------------------------------------
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a1b2c3d4-e5f6-... hello-world Running groq llama-3.3-70b-versatile
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```
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---
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## Chat with an Agent
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Start an interactive chat session using the agent ID:
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```bash
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openfang agent chat a1b2c3d4-e5f6-...
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```
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Or use the quick chat command (picks the first available agent):
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```bash
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openfang chat
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```
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Or specify an agent by name:
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```bash
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openfang chat hello-world
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```
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Example session:
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```
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Chat session started (daemon mode). Type 'exit' or Ctrl+C to quit.
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you> Hello! What can you do?
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agent> I'm the hello-world agent running on OpenFang. I can:
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- Read files from the filesystem
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- List directory contents
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- Fetch web pages
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Try asking me to read a file or look up something on the web!
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[tokens: 142 in / 87 out | iterations: 1]
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you> List the files in the current directory
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agent> Here are the files in the current directory:
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- Cargo.toml
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- Cargo.lock
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- README.md
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- agents/
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- crates/
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- docs/
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...
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you> exit
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Chat session ended.
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```
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---
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## Start the Daemon
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For persistent agents, multi-user access, and the WebChat UI, start the daemon:
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```bash
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openfang start
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```
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Output:
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```
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Starting OpenFang daemon...
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OpenFang daemon running on http://127.0.0.1:4200
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Press Ctrl+C to stop.
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```
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The daemon provides:
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- **REST API** at `http://127.0.0.1:4200/api/`
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- **WebSocket** endpoint at `ws://127.0.0.1:4200/api/agents/{id}/ws`
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- **WebChat UI** at `http://127.0.0.1:4200/`
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- **OFP networking** on port 4200
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### Check Status
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```bash
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openfang status
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```
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### Stop the Daemon
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Press `Ctrl+C` in the terminal running the daemon, or:
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```bash
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curl -X POST http://127.0.0.1:4200/api/shutdown
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```
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---
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## Using the WebChat UI
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With the daemon running, open your browser to:
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```
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http://127.0.0.1:4200/
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```
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The embedded WebChat UI allows you to:
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- View all running agents
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- Chat with any agent in real-time (via WebSocket)
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- See streaming responses as they are generated
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- View token usage per message
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---
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## Next Steps
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Now that you have OpenFang running:
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- **Explore agent templates**: Browse the `agents/` directory for 30 pre-built agents (coder, researcher, writer, ops, analyst, security-auditor, and more).
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- **Create custom agents**: Write your own `agent.toml` manifests. See the [Architecture guide](architecture.md) for details on capabilities and scheduling.
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- **Set up channels**: Connect any of 40 messaging platforms (Telegram, Discord, Slack, WhatsApp, LINE, Mastodon, and 34 more). See [Channel Adapters](channel-adapters.md).
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- **Use bundled skills**: 60 expert knowledge skills are pre-installed (GitHub, Docker, Kubernetes, security audit, prompt engineering, etc.). See [Skill Development](skill-development.md).
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- **Build custom skills**: Extend agents with Python, WASM, or prompt-only skills. See [Skill Development](skill-development.md).
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- **Use the API**: 76 REST/WS/SSE endpoints, including an OpenAI-compatible `/v1/chat/completions`. See [API Reference](api-reference.md).
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- **Switch LLM providers**: 20 providers supported (Anthropic, OpenAI, Gemini, Groq, DeepSeek, xAI, Ollama, and more). Per-agent model overrides.
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- **Set up workflows**: Chain multiple agents together. Use `openfang workflow create` with a TOML workflow definition.
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- **Use MCP**: Connect to external tools via Model Context Protocol. Configure in `config.toml` under `[[mcp_servers]]`.
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- **Migrate from OpenClaw**: Run `openfang migrate --from openclaw`. See [MIGRATION.md](../MIGRATION.md).
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- **Desktop app**: Run `cargo tauri dev` for a native desktop experience with system tray.
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- **Run diagnostics**: `openfang doctor` checks your entire setup.
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### Useful Commands Reference
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```bash
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openfang init # Initialize ~/.openfang/
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openfang start # Start the daemon
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openfang status # Check daemon status
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openfang doctor # Run diagnostic checks
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openfang agent spawn <manifest.toml> # Spawn an agent
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openfang agent list # List all agents
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openfang agent chat <id> # Chat with an agent
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openfang agent kill <id> # Kill an agent
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openfang workflow list # List workflows
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openfang workflow create <file.json> # Create a workflow
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openfang workflow run <id> <input> # Run a workflow
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openfang trigger list # List event triggers
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openfang trigger create <args> # Create a trigger
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openfang trigger delete <id> # Delete a trigger
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openfang skill install <source> # Install a skill
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openfang skill list # List installed skills
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openfang skill search <query> # Search FangHub
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openfang skill create # Scaffold a new skill
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openfang channel list # List channel status
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openfang channel setup <channel> # Interactive setup wizard
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openfang config show # Show current config
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openfang config edit # Open config in editor
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openfang chat [agent] # Quick chat (alias)
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openfang migrate --from openclaw # Migrate from OpenClaw
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openfang mcp # Start MCP server (stdio)
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```
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