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LlamaIndex

Data framework for RAG; ingest, index and query your own corpus.

LlamaIndex is a data framework for connecting large language models to private or domain-specific data, with a focus on retrieval-augmented generation (RAG). It provides data loaders, indexing structures, retrievers, and query engines to ingest documents and serve grounded answers. It is widely used for building question-answering systems and knowledge assistants over custom corpora.

Repository

run-llama/llama_index

Language

Python

What you'd build with it

  • Building a RAG pipeline that answers questions over internal documents
  • Ingesting and indexing PDFs, databases, and APIs for LLM retrieval
  • Creating query engines and agents that route across multiple data sources

Tags

ragretrievalindexing