topoteretes/cognee

Get Started

Get started quickly with a Google Colab notebook , Deepnote notebook or starter repo

About cognee

Self-hosted package:

• Interconnects any kind of documents: past conversations, files, images, and audio transcriptions
• Replaces RAG systems with a memory layer based on graphs and vectors
• Reduces developer effort and cost, while increasing quality and precision
• Provides Pythonic data pipelines that manage data ingestion from 30+ data sources
• Is highly customizable with custom tasks, pipelines, and a set of built-in search endpoints

Hosted platform:

• Includes a managed UI and a hosted solution

Self-Hosted (Open Source)

📦 Installation

You can install Cognee using either pip, poetry, uv or any other python package manager.

Cognee supports Python 3.10 to 3.12

With uv

uv pip install cognee

Detailed instructions can be found in our docs

💻 Basic Usage

Setup

import os
os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY"

You can also set the variables by creating .env file, using our template. To use different LLM providers, for more info check out our documentation

Simple example

Python

This script will run the default pipeline:

import cognee
import asyncio


async def main():
    # Add text to cognee
    await cognee.add("Cognee turns documents into AI memory.")

    # Generate the knowledge graph
    await cognee.cognify()

    # Add memory algorithms to the graph
    await cognee.memify()

    # Query the knowledge graph
    results = await cognee.search("What does cognee do?")

    # Display the results
    for result in results:
        print(result)


if __name__ == '__main__':
    asyncio.run(main())

Example output:

  Cognee turns documents into AI memory.

Via CLI

Let's get the basics covered

cognee-cli add "Cognee turns documents into AI memory."

cognee-cli cognify

cognee-cli search "What does cognee do?"
cognee-cli delete --all

or run

cognee-cli -ui

Hosted Platform

Get up and running in minutes with automatic updates, analytics, and enterprise security.

1. Sign up on cogwit
2. Add your API key to local UI and sync your data to Cogwit

Demos

1. Cogwit Beta demo:

Cogwit Beta

2. Simple GraphRAG demo

Simple GraphRAG demo

3. cognee with Ollama

cognee with local models

Contributing

Your contributions are at the core of making this a true open source project. Any contributions you make are greatly appreciated. See CONTRIBUTING.md for more information.

Code of Conduct

We are committed to making open source an enjoyable and respectful experience for our community. See CODE_OF_CONDUCT for more information.

Citation

We now have a paper you can cite:

@misc{markovic2025optimizinginterfaceknowledgegraphs,
      title={Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning}, 
      author={Vasilije Markovic and Lazar Obradovic and Laszlo Hajdu and Jovan Pavlovic},
      year={2025},
      eprint={2505.24478},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2505.24478}, 
}