LlamaIndex
Data framework for LLM apps with document parsing capabilities
Large language modelsDocument ingestionData parsing
Introduction
LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs). It offers industry-leading document ingestion, parsing, retrieval, indexing, querying, and evaluation capabilities. Developers can build LLM applications quickly using Python and Typescript.
Key Features
Connect custom data sources to LLMs
Industry-leading document ingestion and parsing
Store, index, query, and evaluate data
Build LLM applications using Python and Typescript
Frequently Asked Questions
What is LlamaIndex?
How to use LlamaIndex?
What types of data can be loaded into LlamaIndex?
How can developers integrate with the LlamaIndex community?
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Use Cases
- Build production-ready LLM applications
- Connect data to generative AI for enterprises
- Orchestrate production LLM workflows over data with advanced features
How to Use
To use LlamaIndex, developers can load data from 160+ sources, store, index, query, and evaluate the data. Integrate with various services, access community-contributed tools, and engage in a developer network to build innovative LLM applications.