# Quivr — Opinionated RAG Framework for Any LLM

> Quivr is an opinionated RAG framework supporting any LLM, multiple file types, and customizable retrieval. 39.1K+ stars. Apache 2.0.

## Install

Save as a script file and run:

## Quick Use

```bash
pip install quivr-core

python -c "
from quivr_core import Brain
brain = Brain.from_files(name=\"my-brain\", file_paths=[\"./doc.pdf\"])
answer = brain.ask(\"What is this document about?\")  
print(answer.answer)
"
```

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## Intro

Quivr is an opinionated RAG framework that simplifies integrating generative AI into applications. With 39,100+ GitHub stars and Apache 2.0 license, it works with any LLM (OpenAI, Anthropic, Mistral, Groq), supports multiple file types (PDF, TXT, Markdown, custom parsers), provides customizable RAG workflows with reranking and history management, and configures via YAML.

**Best for**: Developers building RAG applications with minimal setup
**Works with**: Claude Code, OpenAI Codex, Cursor, Gemini CLI, Windsurf

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## Key Features

- Any LLM (OpenAI, Anthropic, Mistral, Groq)
- Multiple file types (PDF, TXT, Markdown)
- Customizable retrieval with reranking
- YAML configuration
- Megaparse for advanced file processing
- History management

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### FAQ

**Q: What is Quivr?**
A: Opinionated RAG framework with 39.1K+ stars. Any LLM, multiple file types, customizable retrieval. Apache 2.0.

**Q: How do I install Quivr?**
A: pip install quivr-core. Brain.from_files() to start.

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## Source & Thanks

> [QuivrHQ/quivr](https://github.com/QuivrHQ/quivr) — 39,100+ GitHub stars

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Source: https://tokrepo.com/en/workflows/96223597-08c2-4e60-b84e-0c4779641933
Author: Script Depot