A continuously-updated, categorized self-hosting guide that catalogs tools, deployment notes and resources for containers, networking, home automation and running LLMs/chatbots locally; provided as a long, structured README with links and quick setup tips.
Runs a local AI assistant across WeChat/Feishu/DingTalk/WeCom/QQ/MP/Web, with an Agent mode for task planning, long-term memory, Skills, and tool calling so it can keep working toward goals rather than just chat.
Framework for building multi-channel AI assistants that autonomously plan tasks, invoke tools/skills, and keep long-term memory; supports many LLM providers and channels (WeChat, Feishu, QQ, web) for local or server 24/7 deployment.
Smart model router for personal AI agents that sends each request to the cheapest model capable of handling it — cutting API costs by up to ~70%. Uses a fast 23-dimension scorer, automatic fallbacks, per-tier controls, and supports local Docker self-hosting or a cloud app; ideal for cost-sensitive personal agents.
Rust-and-Python toolkit that serves open-source LLMs (Llama, Falcon, Mixtral, StarCoder) over HTTP/gRPC with tensor parallelism, continuous batching, Flash/Paged Attention and quantization. Now in maintenance mode, pointing users toward vLLM and SGLang.
Connect LLMs to major chat platforms so teams can build, deploy, and operate multi-platform AI chatbots and agents. Provides multi-platform adapters, a plugin marketplace, an MCP server and built-in RAG plus production features like access control, rate limiting and monitoring.
Connects one LLM agent to 15+ chat platforms — QQ, WeChat Work, Feishu, Telegram, Discord, Slack — from a single self-hosted backend. Routes to OpenAI, Anthropic, Gemini, DeepSeek or Ollama, and adds a WebUI, MCP tools, and a 1000+ plugin marketplace.
Web and desktop/mobile WebUI for generating, editing, captioning and processing images and videos with Stable Diffusion and many diffusion models. Key features include automatic model download, SDNQ on-the-fly quantization for VRAM savings, balanced CPU/GPU offload, multi-backend GPU support, and built-in captioning/tagging/upscaling workflows.
Centralizes logs, metrics, traces, frontend RUM and LLM observability into one self-hostable platform, using Parquet + S3-native storage and SQL/PromQL querying to reduce long‑term storage costs and unify telemetry analysis.
Turns documents, web pages and audio into a private, searchable knowledge base and builder for AI assistants and agents — supports wide-format ingestion, multi-model (cloud or local) execution, retrieval-augmented responses, and enterprise deployment features like RBAC and SSO.
Provides a minimal, Zig-written headless browser tailored for AI agents and automation — runs JavaScript, supports key Web APIs, exposes the Chrome DevTools Protocol for Puppeteer/Playwright, and targets low memory usage and fast startup for large-scale scraping and agent workflows.