
cognee - Memory for AI Agents in 6 lines of code
Demo . Learn more · Join Discord · Join r/AIMemory . Docs . cognee community repo
Build dynamic memory for Agents and replace RAG using scalable, modular ECL (Extract, Cognify, Load) pipelines.
🌐 Available Languages : Deutsch | Español | français | 日本語 | 한국어 | Português | Русский | 中文
Get started quickly with a Google Colab notebook , Deepnote notebook or starter repo
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
You can install Cognee using either pip, poetry, uv or any other python package manager.
Cognee supports Python 3.10 to 3.12
uv pip install cognee
Detailed instructions can be found in our docs
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
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.
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
Get up and running in minutes with automatic updates, analytics, and enterprise security.
- Sign up on cogwit
- Add your API key to local UI and sync your data to Cogwit
- Cogwit Beta demo:
cogwit_beta_demo.mp4
- Simple GraphRAG demo
cognee_graphrag.mp4
- cognee with Ollama
cognee_with_ollama.mp4
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.
We are committed to making open source an enjoyable and respectful experience for our community. See CODE_OF_CONDUCT
for more information.
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},
}