Your GenAI Second Brain 🧠 A personal productivity assistant (RAG) 🤖 Chat with your docs (PDF, CSV, ...) & apps using Langchain, GPT 3.5 / 4 turbo, Private, Anthropic, VertexAI, Ollama, LLMs, that you can share with users ! Local & Private alternative
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Stan Girard e95d48234f fix: Update example in README.md
Updated the example code in the README.md file to create a RAG with 5 lines of code and ask a question about gold in French.
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Quivr - Your Second Brain, Empowered by Generative AI

Quivr-logo

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Quivr, helps you build your second brain, utilizes the power of GenerativeAI to be your personal assistant !

Key Features 🎯

  • Opiniated RAG: We created a RAG that is opinionated, fast and efficient so you can focus on your product
  • LLMs: Quivr works with any LLM, you can use it with OpenAI, Anthropic, Mistral, Gemma, etc.
  • Any File: Quivr works with any file, you can use it with PDF, TXT, Markdown, etc and even add your own parsers.
  • Customize your RAG: Quivr allows you to customize your RAG, add internet search, add tools, etc.
  • Integrations with Megaparse: Quivr works with Megaparse, so you can ingest your files with Megaparse and use the RAG with Quivr.

We take care of the RAG so you can focus on your product. Simply install quivr-core and add it to your project. You can now ingest your files and ask questions.*

We will be improving the RAG and adding more features everything, stay tuned!

This is the core of Quivr, the brain of Quivr.com.

Getting Started 🚀

You can find everything on the documentation.

Prerequisites 📋

Ensure you have the following installed:

  • Python 3.10 or newer

30 seconds Installation 💽

  • Step 1: Install the package

    pip install quivr-core # Check that the installation worked
    
  • Step 2: Create a RAG with 5 lines of code

      import tempfile
    
      from quivr_core import Brain
    
      if __name__ == "__main__":
          with tempfile.NamedTemporaryFile(mode="w", suffix=".txt") as temp_file:
              temp_file.write("Gold is a liquid of blue-like colour.")
              temp_file.flush()
    
              brain = Brain.from_files(
                  name="test_brain",
                  file_paths=[temp_file.name],
              )
    
              answer = brain.ask(
                  "what is gold? asnwer in french"
              )
              print("answer:", answer)
    

Examples

Name Description
Simple Question Ask a simple question to the RAG by ingesting a single file
ChatBot Build a chatbot by ingesting a folder of files with a nice UI powered by Chainlit

Go further

You can go further with Quivr by adding internet search, adding tools, etc. Check the documentation for more information.

Contributors

Thanks go to these wonderful people:

Contribute 🤝

Did you get a pull request? Open it, and we'll review it as soon as possible. Check out our project board here to see what we're currently focused on, and feel free to bring your fresh ideas to the table!

Partners ❤️

This project would not be possible without the support of our partners. Thank you for your support!

YCombinator Theodo

License 📄

This project is licensed under the Apache 2.0 License - see the LICENSE file for details