Topics / #llama-index

Llama-index projects on GitHub

Data framework for connecting documents to language models for retrieval augmented generation.

As of , the most-starred Llama-index projects on GitHub are langfuse (35.9K stars), RAG_Techniques (29.9K stars) and opik (22.7K stars). GitHub.Locker tracks 6 Llama-index repositories with 130K stars combined. The fastest-growing on October 16 was langfuse, with +54 stars in a day.

6Projects
130KStars in total
+163Stars in a day

Hot right now

Most stars gained in a day · Oct 16

The all-time top

6 projects · by stars

  1. #1 · langfuse/langfuse

    langfuse

    Langfuse is an open source LLM engineering platform for tracing, evaluating, and debugging LLM and agent applications, with prompt management and a playground built in.

    35.9K
  2. #2 · NirDiamant/RAG_Techniques

    RAG_Techniques

    A community-driven hub of advanced techniques for Retrieval-Augmented Generation (RAG) — grounding LLM answers in retrieved documents, distilled into runnable notebook tutorials.

    29.9K
  3. #3 · comet-ml/opik

    opik

    Opik is an open-source platform for debugging, evaluating, and monitoring LLM applications, RAG systems, and agentic workflows, with tracing, automated evaluation, and production dashboards.

    22.7K
  1. 4

    awesome-ai-apps

    16.2KArindam200/awesome-ai-apps · Python

    A curated collection of 132 projects, tutorials, and recipes for building LLM-powered applications - covering text agents, voice assistants, RAG apps, and MCP-backed tools.

  2. 5

    LEANN

    13KStarTrail-org/LEANN · Python

    LEANN is a vector database that lets you run retrieval-augmented generation (RAG) over millions of personal documents on your own laptop using 97% less storage than traditional vector databases, with no accuracy loss.

  3. 6

    all-in-rag

    12.2Kdatawhalechina/all-in-rag · Python

    This is a full-stack tutorial on Retrieval-Augmented Generation (RAG) for developers building LLM applications, covering theory and hands-on practice from basic concepts to production-ready RAG systems.

Often tagged together