Overview

Title

Cognee - Memory for AI Agents in 5 lines of code

How to Use

1. Install via pip install cognee.
2. Set up your API key (e.g., OpenAI).
3. Use simple Python functions (add(), cognify(), search()) to store, process, and retrieve AI memory.
4. Run queries to extract structured knowledge from stored data.

Key Features

• Dynamic AI Memory: Store and retrieve conversations, documents, images, and audio transcriptions.
• Reduced Hallucinations: Improves response accuracy by grounding AI in structured knowledge.
• Modular Pipelines: Scalable ECL (Extract, Cognify, Load) architecture.
• Multi-Source Support: Ingest and manipulate data from 30+ sources.
• Graph & Vector DBs: Store and query data using Pydantic models.

Use Cases

• AI Agents: Persistent memory for chatbots and autonomous agents.
• Knowledge Graphs: Structured representation of interconnected data.
• RAG (Retrieval-Augmented Generation): Enhance LLM outputs with contextual knowledge.
• Multimodal AI: Process text, images, and audio in a unified memory system.

For demos, tutorials, and advanced usage, explore the documentation.