--- title: cognee --- # cognee [cognee](https://www.cognee.ai) is a memory management tool for AI Apps and Agents Qdrant is available as a native built-in vector database to store and retrieve embeddings. ## 📦 Installation You can install Cognee using either **pip**, **poetry**, **uv** or any other python package manager. Cognee supports Python 3.8 to 3.12 ### With pip ```bash pip install cognee ``` ## 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 ```bash uv sync --all-extras ``` ## 💻 Basic Usage ### Setup ``` import os os.environ["LLM_API_KEY"] = "YOUR OPENAI_API_KEY" VECTOR_DB_PROVIDER="qdrant" VECTOR_DB_URL=https://url-to-your-qdrant-cloud-instance.cloud.qdrant.io:6333 VECTOR_DB_KEY=your-qdrant-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: ```python 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. ```