233 lines
8.1 KiB
Markdown
233 lines
8.1 KiB
Markdown
<div align="center">
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<a href="https://github.com/topoteretes/cognee">
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<img src="https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/dev/assets/cognee-logo-transparent.png" alt="Cognee Logo" height="60">
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</a>
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<br />
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cognee - Memory for AI Agents in 5 lines of code
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<p align="center">
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<a href="https://www.youtube.com/watch?v=1bezuvLwJmw&t=2s">Demo</a>
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.
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<a href="https://cognee.ai">Learn more</a>
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·
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<a href="https://discord.gg/NQPKmU5CCg">Join Discord</a>
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·
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<a href="https://www.reddit.com/r/AIMemory/">Join r/AIMemory</a>
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.
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<a href="https://docs.cognee.ai/">Docs</a>
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.
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<a href="https://github.com/topoteretes/cognee-community">cognee community repo</a>
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</p>
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[](https://GitHub.com/topoteretes/cognee/network/)
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[](https://GitHub.com/topoteretes/cognee/stargazers/)
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[](https://GitHub.com/topoteretes/cognee/commit/)
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[](https://github.com/topoteretes/cognee/tags/)
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[](https://pepy.tech/project/cognee)
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[](https://github.com/topoteretes/cognee/blob/main/LICENSE)
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[](https://github.com/topoteretes/cognee/graphs/contributors)
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<a href="https://github.com/sponsors/topoteretes"><img src="https://img.shields.io/badge/Sponsor-❤️-ff69b4.svg" alt="Sponsor"></a>
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<p>
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<a href="https://www.producthunt.com/posts/cognee?embed=true&utm_source=badge-top-post-badge&utm_medium=badge&utm_souce=badge-cognee" target="_blank" style="display:inline-block; margin-right:10px;">
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<img src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=946346&theme=light&period=daily&t=1744472480704" alt="cognee - Memory for AI Agents  in 5 lines of code | Product Hunt" width="250" height="54" />
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</a>
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<a href="https://trendshift.io/repositories/13955" target="_blank" style="display:inline-block;">
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<img src="https://trendshift.io/api/badge/repositories/13955" alt="topoteretes%2Fcognee | Trendshift" width="250" height="55" />
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</a>
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</p>
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**🚀 We launched Cogwit beta (Fully-hosted AI Memory): Sign up [here](https://platform.cognee.ai/)! 🚀**
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Build dynamic memory for Agents and replace RAG using scalable, modular ECL (Extract, Cognify, Load) pipelines.
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More on [use-cases](https://docs.cognee.ai/use-cases) and [evals](https://github.com/topoteretes/cognee/tree/main/evals)
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<p align="center">
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🌐 Available Languages
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:
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<!-- Keep these links. Translations will automatically update with the README. -->
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=de">Deutsch</a> |
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=es">Español</a> |
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=fr">français</a> |
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=ja">日本語</a> |
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=ko">한국어</a> |
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=pt">Português</a> |
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=ru">Русский</a> |
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<a href="https://www.readme-i18n.com/topoteretes/cognee?lang=zh">中文</a>
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</p>
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<div style="text-align: center">
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<img src="https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/main/assets/cognee_benefits.png" alt="Why cognee?" width="50%" />
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</div>
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</div>
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## Features
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- Interconnect and retrieve your past conversations, documents, images and audio transcriptions
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- Replaces RAG systems and reduces developer effort, and cost.
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- Load data to graph and vector databases using only Pydantic
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- Manipulate your data while ingesting from 30+ data sources
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## Get Started
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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>
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## Contributing
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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.
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## Using cognee
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Start with our self-hosted package and UI.
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Deploy your data to our hosted solution with one click once you want to move to production.
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## Self-Hosted (Open Source)
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### 📦 Installation
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You can install Cognee using either **pip**, **poetry**, **uv** or any other python package manager.
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Cognee supports Python 3.10 to 3.12
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#### With uv
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```bash
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uv pip install cognee
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```
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Detailed instructions can be found in our [docs](https://docs.cognee.ai/getting-started/installation#environment-configuration)
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### 💻 Basic Usage
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#### Setup
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```
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import os
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os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY"
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```
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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>
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To use different LLM providers, for more info check out our <a href="https://docs.cognee.ai/setup-configuration/llm-providers">documentation</a>
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#### Simple example
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##### Via CLI
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These commands will show you the basics of cognee CLI
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```
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cognee-cli add "Cognee turns documents into AI memory."
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cognee-cli cognify
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cognee-cli search "What does cognee do?"
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cognee-cli delete --all
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```
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or run
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```
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cognee-cli -ui
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```
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##### Python
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This script will run the default pipeline:
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```python
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import cognee
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import asyncio
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async def main():
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# Add text to cognee
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await cognee.add("Cognee turns documents into AI memory.")
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# Generate the knowledge graph
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await cognee.cognify()
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# Add memory algorithms to the graph
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await cognee.memify()
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# Query the knowledge graph
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results = await cognee.search("What does cognee do?")
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# Display the results
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for result in results:
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print(result)
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if __name__ == '__main__':
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asyncio.run(main())
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```
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Example output:
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```
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Cognee turns documents into AI memory.
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```
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</div>
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### Hosted Platform
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Get up and running in minutes with automatic updates, analytics, and enterprise security.
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1. Sign up on [cogwit](https://www.cognee.ai)
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2. Add your API key to local UI and sync your data or send your data to Cogwit API
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## Demos
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1. Cogwit Beta demo:
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[Cogwit Beta](https://github.com/user-attachments/assets/fa520cd2-2913-4246-a444-902ea5242cb0)
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2. Simple GraphRAG demo
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[Simple GraphRAG demo](https://github.com/user-attachments/assets/d80b0776-4eb9-4b8e-aa22-3691e2d44b8f)
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3. cognee with Ollama
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[cognee with local models](https://github.com/user-attachments/assets/8621d3e8-ecb8-4860-afb2-5594f2ee17db)
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## Code of Conduct
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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.
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## Citation
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We now have a paper you can cite:
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```bibtex
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@misc{markovic2025optimizinginterfaceknowledgegraphs,
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title={Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning},
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author={Vasilije Markovic and Lazar Obradovic and Laszlo Hajdu and Jovan Pavlovic},
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year={2025},
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eprint={2505.24478},
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archivePrefix={arXiv},
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primaryClass={cs.AI},
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url={https://arxiv.org/abs/2505.24478},
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}
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```
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