Open source: RAG and vector databases
Store your documents as searchable embeddings and let a model answer from them (retrieval-augmented generation).
- RAGFlowinfiniflow/ragflow
A self-hosted knowledge base over company documents, with answers that cite their source.
- LlamaIndexrun-llama/llama_index
Developers building document Q&A or data agents in Python or TypeScript.
- Milvusmilvus-io/milvus
Vector search that may need to grow to very large collections.
- Qdrantqdrant/qdrant
The search layer behind a "chat with your documents" app.
- Chromachroma-core/chroma
Adding document search to a prototype or small app with very little setup.
- Weaviateweaviate/weaviate
Search over your own content that mixes keyword matching with meaning-based matching.
Other categories
Agents and frameworks · Local LLMs · Workflow automation · Voice and TTS · Image and video · Dev tools
Stars, licences and commit dates come from the GitHub API, checked 16 Oct 2026. "Last commit" is the last push to the repo. Star counts are a rough popularity signal, not a quality score. There are no affiliate links in this section: links go straight to each project.