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ScriptsMar 29, 2026·1 min de lecture

LlamaIndex — Data Framework for LLM Applications

Connect your data to large language models. The leading framework for RAG, document indexing, knowledge graphs, and structured data extraction.

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Introduction

LlamaIndex (formerly GPT Index) is the go-to framework for connecting custom data to LLMs. Ingest data from 160+ sources, build indexes for fast retrieval, and create production-ready RAG pipelines.

Best for: Document Q&A, knowledge base search, data extraction, enterprise RAG Works with: OpenAI, Anthropic, Google, Ollama, HuggingFace

Key Features

Data Connectors

Ingest from PDFs, databases, APIs, Notion, Slack, Google Drive, and 160+ sources:

from llama_index.core import SimpleDirectoryReader
documents = SimpleDirectoryReader("./data").load_data()

Indexing & Retrieval

from llama_index.core import VectorStoreIndex
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("What is the revenue trend?")

Agents

Build data-aware agents that can query multiple data sources, use tools, and maintain conversation state.

FAQ

Q: What is LlamaIndex? A: Connect your data to large language models. The leading framework for RAG, document indexing, knowledge graphs, and structured data extraction.

Q: How do I install LlamaIndex? A: Check the Quick Use section above for step-by-step installation instructions. Most assets can be set up in under 2 minutes.

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Source et remerciements

Created by LlamaIndex. Licensed under MIT. run-llama/llama_index — 38K+ GitHub stars

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