Welcome to Quivr Documentation#

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)