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<!-- .github/pull_request_template.md --> ## Description Add info about installing Cognee locally ## DCO Affirmation I affirm that all code in every commit of this pull request conforms to the terms of the Topoteretes Developer Certificate of Origin.
188 lines
6.4 KiB
Markdown
188 lines
6.4 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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</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://www.producthunt.com/posts/cognee?embed=true&utm_source=badge-top-post-badge&utm_medium=badge&utm_souce=badge-cognee" target="_blank"><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" style="width: 250px; height: 54px;" width="250" height="54" /></a>
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Build dynamic Agent memory 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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<a href="assets/community/README.pt.md">🇵🇹 Português</a>
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<a href="assets/community/README.zh.md">🇨🇳 [中文]</a>
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·
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<a href="assets/community/README.ru.md">🇷🇺 Русский</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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- Reduce hallucinations, 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> or <a href="https://github.com/topoteretes/cognee-starter">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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## 📦 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 3.8 to 3.12
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### With pip
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```bash
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pip install cognee
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```
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## Local Cognee installation
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You can install the local Cognee repo using **pip**, **poetry** and **uv**.
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For local pip installation please make sure your pip version is above version 21.3.
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### with UV with all optional dependencies
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```bash
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uv sync --all-extras
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```
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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">documentation</a>
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### Simple example
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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("Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval.")
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# Generate the knowledge graph
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await cognee.cognify()
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# Query the knowledge graph
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results = await cognee.search("Tell me about NLP")
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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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Natural Language Processing (NLP) is a cross-disciplinary and interdisciplinary field that involves computer science and information retrieval. It focuses on the interaction between computers and human language, enabling machines to understand and process natural language.
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```
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### cognee UI
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You can also cognify your files and query using cognee UI.
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<img src="assets/cognee-ui-2.webp" width="100%" alt="Cognee UI 2"></a>
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Try cognee UI out locally [here](https://docs.cognee.ai/how-to-guides/cognee-ui).
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## Understand our architecture
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<div style="text-align: center">
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<img src="assets/cognee_diagram.png" alt="cognee concept diagram" width="100%" />
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</div>
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## Demos
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1. What is AI memory:
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[Learn about cognee](https://github.com/user-attachments/assets/8b2a0050-5ec4-424c-b417-8269971503f0)
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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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## 💫 Contributors
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<a href="https://github.com/topoteretes/cognee/graphs/contributors">
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<img alt="contributors" src="https://contrib.rocks/image?repo=topoteretes/cognee"/>
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</a>
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## Star History
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[](https://star-history.com/#topoteretes/cognee&Date)
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