Show HN: Cognee – Open-Source AI Memory Layer That Remembers Context

1 day ago 5

Interconnect and retrieve your past conversations, documents, images and audio transcriptions
Replaces RAG systems and reduces 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 quickly with a Google Colab notebook or starter repo

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.

You can install Cognee using either pip, poetry, uv or any other python package manager. Cognee supports Python 3.8 to 3.12

Local Cognee installation

You can install the local Cognee repo using pip, poetry and uv. For local pip installation please make sure your pip version is above version 21.3.

with UV with all optional dependencies

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("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.

You can also cognify your files and query using cognee UI.