open-source-ai

Distribute and run LLMs with a single file.

Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.

50+ open-source generative AI apps you can clone, deploy, and monetize — image generators, video tools, virtual try-ons, AI SaaS templates, and platform integrations. One-click Vercel deploy on every template.

Ouroboros — self-creating AI agent. Born Feb 16, 2026.

A curated list of OpenClaw resources, tools, skills, tutorials & articles. OpenClaw (formerly Moltbot / Clawdbot) — open-source self-hosted AI agent for WhatsApp, Telegram, Discord & 50+ integrations.

A list of open-source AI projects you can use to generate income easily.

Open-source local AI SDK - run AI on-device with no cloud, no API keys. Supports GGUF, RAG, image, music, and video generation, speech-to-text, P2P inference, and more. Cross-platform: Linux, macOS, Windows, Android, iOS.

GEO 领域 AI 员工开源方案 · Open-source GEO AI-employee solution (MIT). GEO Skills package + curated lists of agents and office CLIs that make up the AI-employee stack.

Open-source realtime voice agent server in Go with WebRTC (WHIP), barge-in, streaming STT/LLM/TTS pipelines, plugin system, multi-language SDKs, SIP telephony, ESP32 support & fully local mode.

Your SDK solves all of this. One interface. Unified logic. Local + hosted models. Fine-tuning. Agent tools. Enterprise-ready. Hybrid RAG.Star 🌟 if you like it!

Predictive memory layer for AI agents. MongoDB + Qdrant + Neo4j with multi-tier caching, custom schema support & GraphQL. 91% Stanford STARK accuracy, <100ms on-device retrieval

Metronix Memory is self-hosted memory infrastructure for AI agents: MCP-native, local-model friendly, with hybrid RAG, a temporal knowledge graph and ontology layer, durable memory, freshness checks, and agent-scoped context

An interactive educational game built for the Google Gemma 3n Impact Challenge.

Open-source AI assistant with voice control, browser automation, desktop overlay, and 109+ tools. Built with Python, Next.js, and Three.js.

Apache-2.0, model-agnostic macOS agent: bring your own model to deliver verified code, docs, slides, and computer actions.

⚡ Vectro: Lightning-fast embedding quantization. Hit 12M+ vec/s throughput (4.85× faster than FAISS C++) while drastically cutting memory footprint for vector databases and local AI research.