Open-source AI projects built with Docker.
Run open models on your own machine with one command.
High-throughput serving built around PagedAttention.
A polished self-hosted chat front-end for local and remote models.
A visual platform for building and operating LLM apps.
The project that made autonomous agents a mainstream idea.
An agent that writes code, runs it, and fixes what breaks.
Fair-code workflow automation with AI steps built in.
A drop-in OpenAI replacement that runs on your hardware.
Turn any set of documents into a private chat workspace.
Microsoft Research framework for agents that solve tasks by conversing.
The embedding database that gets out of your way.
A Rust vector engine with genuinely good payload filtering.
Twelve build areas, from chatbots and agents to vector search and fine-tuning.
Retrieval-augmented generation — grounding a model in your own documents and data.
5 projectsThe scaffolding around a model: UI builders, experiment tracking and app frameworks.
5 projectsRunning models fast and cheaply: local runtimes, inference servers and OpenAI-compatible APIs.
4 projectsEmbedding stores and similarity search — the memory layer under most RAG systems.
3 projectsConversational apps you can actually ship — chat UIs, assistants and the plumbing behind them.
2 projectsProjects where the model plans, calls tools and works a task through to a result on its own.
2 projectsDiffusion pipelines, node graphs and browser front-ends for generating and editing images.
2 projectsSpeech recognition, text-to-speech and voice cloning you can run yourself.
2 projectsDetection, segmentation and tracking — the frameworks real vision products are built on.
2 projectsAdapting an existing model to your data — LoRA, full fine-tunes and the tooling around them.
2 projectsWiring models into multi-step processes that run without a human in the loop.
2 projectsSeveral specialised agents co-ordinating on one job — roles, hand-offs and shared state.
2 projects
