LlamaIndex
Data framework for connecting LLMs to external data sources and knowledge bases
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About
LlamaIndex (formerly GPT Index) is an open-source data framework that solves one of the most critical challenges in building LLM applications: connecting AI models to your private data. While LLMs are powerful, they have a knowledge cutoff and no access to proprietary documents, databases, or APIs. LlamaIndex bridges this gap by providing tools to ingest, index, and query any external data source.
The framework supports over 160 data connectors for loading data from sources like Notion, Slack, Google Drive, Salesforce, databases, PDFs, and websites. Once loaded, data is indexed into a vector store and made retrievable through sophisticated query engines that can handle complex multi-step questions requiring reasoning over large document collections.
LlamaIndex is widely used for building enterprise knowledge assistants, legal document analysis tools, code documentation search, and any application where an LLM needs to reliably answer questions from a large, constantly-updated body of knowledge. It works with all major LLM providers and vector stores.
The framework supports over 160 data connectors for loading data from sources like Notion, Slack, Google Drive, Salesforce, databases, PDFs, and websites. Once loaded, data is indexed into a vector store and made retrievable through sophisticated query engines that can handle complex multi-step questions requiring reasoning over large document collections.
LlamaIndex is widely used for building enterprise knowledge assistants, legal document analysis tools, code documentation search, and any application where an LLM needs to reliably answer questions from a large, constantly-updated body of knowledge. It works with all major LLM providers and vector stores.
Product Features
- 160+ data connectors (Notion, Slack, Google Drive, databases, PDFs)
- Multiple index types: vector, keyword, knowledge graph, SQL
- Advanced query engines for multi-step reasoning
- Sub-question decomposition for complex queries
- Response synthesis strategies for accurate answers
- Integration with all major vector stores (Pinecone, Chroma, Weaviate)
- LlamaHub: community library of data loaders and tools
- Streaming and async support for production use
- Evaluation modules for measuring retrieval quality
- Multiple index types: vector, keyword, knowledge graph, SQL
- Advanced query engines for multi-step reasoning
- Sub-question decomposition for complex queries
- Response synthesis strategies for accurate answers
- Integration with all major vector stores (Pinecone, Chroma, Weaviate)
- LlamaHub: community library of data loaders and tools
- Streaming and async support for production use
- Evaluation modules for measuring retrieval quality
About the Publisher
LlamaIndex was created by Jerry Liu and Simon Suo in late 2022 as a personal project to improve GPT-3 applications. It quickly gained massive adoption in the AI developer community. LlamaIndex Inc. was founded in 2023 and raised $8.5 million in seed funding led by Greylock Partners. The project has over 30,000 GitHub stars and thousands of contributors worldwide. LlamaCloud, the company's managed service, offers enterprise-grade data pipelines and deployment infrastructure.