LlamaIndex
Open source · RAG and vector databases · run-llama/llama_index
What it does
LlamaIndex is a code library for connecting language models to your own data. It handles loading documents, splitting them, indexing them and querying them, and works with most vector databases.
Good for: Developers building document Q&A or data agents in Python or TypeScript.
LlamaIndex on GitHub (opens in a new tab) Project homepage (opens in a new tab)
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The signals we checked
- Licence
- MIT (OSI-approved open-source licence)
- Popularity
- Stars: 52,515 (checked 16 Oct 2026)
- Last commit
- 14 Oct 2026
- Open issues and PRs
- 939
- Status
- Active (not archived)
- Self-host
- ModerateA code library; you write Python or TypeScript.
- GitHub topics
- agents
- application
- data
- fine-tuning
- framework
- llamaindex
- llm
- multi-agents
- rag
- vector-database
More in rag and vector databases
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- Milvus Vector search that may need to grow to very large collections.
- Qdrant The search layer behind a "chat with your documents" app.
- Chroma Adding document search to a prototype or small app with very little setup.
- Weaviate Search over your own content that mixes keyword matching with meaning-based matching.
No affiliate links on this page, and we are not paid by this project. The summary is our own plain-English description; check the repo for current features before you rely on it.
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.