cognee

Reliable LLM Memory for AI Applications and AI Agents

Databases

vector-database

cognitive-architecture

chatgpt

cognee - Memory for AI Agents in 5 lines of code

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Build dynamic Agent memory using scalable, modular ECL (Extract, Cognify, Load) pipelines.

Features

Interconnect and retrieve your past conversations, documents, images and audio transcriptions
Reduce hallucinations, developer effort, and cost.
Load data to graph and vector databases using only Pydantic
Manipulate your data while ingesting from 30+ data sources

Get Started

Get started quickly with a Google Colab notebook or starter repo

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.

📦 Installation

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

With pip

pip install cognee

💻 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

This script will run the default pipeline:

import cognee
import asyncio


async def main():
    # Add text to cognee
    await cognee.add("Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval.")

    # Generate the knowledge graph
    await cognee.cognify()

    # Query the knowledge graph
    results = await cognee.search("Tell me about NLP")

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


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

Example output:

  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.

Graph visualization: Open in browser.