<div align="center">
  <a href="https://github.com/topoteretes/cognee">
    <img src="https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/dev/assets/cognee-logo-transparent.png" alt="Cognee Logo" height="60">
  </a>

  <br />

  cognee - Memory for AI Agents in 6 lines of code

  <p align="center">
  <a href="https://www.youtube.com/watch?v=1bezuvLwJmw&t=2s">Demo</a>
  .
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  .
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Build dynamic memory for Agents and replace RAG using scalable, modular ECL (Extract, Cognify, Load) pipelines.

  <p align="center">
  🌐 Available Languages
  :
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<div style="text-align: center">
  <img src="https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/main/assets/cognee_benefits.png" alt="Why cognee?" width="50%" />
</div>
</div>



## Get Started

Get started quickly with a Google Colab  <a href="https://colab.research.google.com/drive/1jHbWVypDgCLwjE71GSXhRL3YxYhCZzG1?usp=sharing">notebook</a> , <a href="https://deepnote.com/workspace/cognee-382213d0-0444-4c89-8265-13770e333c02/project/cognee-demo-78ffacb9-5832-4611-bb1a-560386068b30/notebook/Notebook-1-75b24cda566d4c24ab348f7150792601?utm_source=share-modal&utm_medium=product-shared-content&utm_campaign=notebook&utm_content=78ffacb9-5832-4611-bb1a-560386068b30">Deepnote notebook</a> or  <a href="https://github.com/topoteretes/cognee/tree/main/cognee-starter-kit">starter repo</a>


## About cognee

cognee works locally and stores your data on your device.
Our hosted solution is just our deployment of OSS cognee on Modal, with the goal of making development and productionization easier.

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](https://www.cognee.ai)



## 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

```bash
uv pip install cognee
```

Detailed instructions can be found in our [docs](https://docs.cognee.ai/getting-started/installation#environment-configuration)

### 💻 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 <a href="https://github.com/topoteretes/cognee/blob/main/.env.template">template.</a>
To use different LLM providers, for more info check out our <a href="https://docs.cognee.ai/setup-configuration/llm-providers">documentation</a>


#### Simple example



##### Python

This script will run the default pipeline:

```python
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
```


</div>


### Hosted Platform

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

1. Sign up on [cogwit](https://www.cognee.ai)
2. Add your API key to local UI and sync your data to Cogwit




## Demos

1. Cogwit Beta demo:

[Cogwit Beta](https://github.com/user-attachments/assets/fa520cd2-2913-4246-a444-902ea5242cb0)

2. Simple GraphRAG demo

[Simple GraphRAG demo](https://github.com/user-attachments/assets/d80b0776-4eb9-4b8e-aa22-3691e2d44b8f)

3. cognee with Ollama

[cognee with local models](https://github.com/user-attachments/assets/8621d3e8-ecb8-4860-afb2-5594f2ee17db)


## 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`](CONTRIBUTING.md) for more information.


## Code of Conduct

We are committed to making open source an enjoyable and respectful experience for our community. See <a href="https://github.com/topoteretes/cognee/blob/main/CODE_OF_CONDUCT.md"><code>CODE_OF_CONDUCT</code></a> for more information.

## Citation

We now have a paper you can cite:

```bibtex
@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}, 
}
```
