🦅 ravenbot Documentation

Welcome to the official documentation for ravenbot, a high-performance, self-hosted autonomous AI agent built in Go.

🚀 Quick Links

Getting Started: Jump right in with our Docker or local setup guides.
Web UI: Access the browser-based chat, reports, agents, and missions dashboard.
Enhanced Features: Workflow pipelines, Insight Vault, Visual Intelligence, and Active Sentinel.
Configuration: Environment variables and config.json options.
Security & Privacy: How ravenbot protects your data and network.
Troubleshooting: Common solutions for setup and runtime issues.
FAQ: Frequently asked questions.

Web Interface: Browser-based chat, research reports browser, tool launcher, agent registry, and missions dashboard — all powered by HTMX + templ.
Autonomous Research: Deep-dives into technical topics with web search, weather, memory, and sequential-thinking tools.
Workflow Pipelines: Structured agent chains (e.g., ResearchAssistant → ResearchSynthesizer) executed as tracked missions.
Agent Orchestration: Launch, monitor, and review workflow pipelines from the web UI.
Multi-Agent Architecture: Specialized sub-agents for research, system diagnostics, and software engineering (Jules).
Insight Vault: Integrated access to your personal Markdown knowledge base.
Visual Intelligence: Ability to analyze and debug via images and screenshots.
Active Sentinel: Proactive monitoring and alerting on your favorite topics.

Agent Persona & Memory: Understanding the bot's personality and long-term recall.
MCP Architecture: How ravenbot integrates with the Model Context Protocol.