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LLAMAINDEX
Turn your data into a queryable knowledge base for any LLM
MIT
ABOUT
Connecting LLMs to your own data — PDFs, databases, APIs, Notion pages — requires writing custom parsers, chunking strategies, embedding pipelines, and retrieval logic. LlamaIndex abstracts all of this with 160+ data connectors, smart chunking, query engines, and agent orchestration. It's the fastest way to go from "I have documents" to "I have a smart Q&A system."
INSTALL
npm install llamaindexINTEGRATION GUIDE
1. Build a document Q&A system over PDFs, Word docs, and spreadsheets in under 10 lines of code
2. Create a structured analytics agent that queries SQL databases using natural language
3. Build a multi-document summarization pipeline that synthesizes insights across 1000+ files
4. Connect your LLM to live APIs (Notion, Slack, GitHub) with pre-built data loaders
5. Implement a conversational interface over a large knowledge base with conversation memory
TAGS
pythontypescriptragknowledge-basedata-ingestionembeddingsagents