Installation

Set up your environment and install Cognee

Set up your environment and install Cognee to start building AI memory.

Python 3.9 – 3.12 is required to run Cognee.

Prerequisites

Environment Configuration

• We recommend creating a .env file in your project root
• Cognee supports many configuration options, and a .env file keeps them organized

API Keys & Models

You have two main options for configuring LLM and embedding providers:

Option 1: OpenAI (Simplest)

• Single API key handles both LLM and embeddings
• Uses gpt-4o-mini for LLM and text-embedding-3-small for embeddings by default
• Works out of the box with minimal configuration

Option 2: Other Providers

• Configure both LLM and embedding providers separately
• Supports Gemini, Anthropic, Ollama, and more
• Requires setting both LLM_* and EMBEDDING_* variables

By default, Cognee uses OpenAI for both LLMs and embeddings. If you change the LLM provider but don’t configure embeddings, it will still default to OpenAI.

Virtual Environment

• We recommend using uv for virtual environment management
• Run the following commands to create and activate a virtual environment:

uv venv && source .venv/bin/activate

Optional

Database

• PostgreSQL database is required if you plan to use PostgreSQL as your relational database (requires postgres extra)

Setup

OpenAI (Recommended)

Environment: Add your OpenAI API key to your .env file:

LLM_API_KEY="your_openai_api_key"

Installation: Install Cognee with all extras:

uv pip install cognee

What this gives you: Cognee installed with default local databases (SQLite, LanceDB, Kuzu) — no external servers required.

This single API key handles both LLM and embeddings. We use gpt-4o-mini for the LLM model and text-embedding-3-small for embeddings by default.

Other Providers (Gemini, Anthropic, etc.)

Environment: Configure both LLM and embedding providers in your .env file. Here is an example for Gemini:

# LLM
LLM_PROVIDER="gemini"
LLM_MODEL="gemini/gemini-flash-latest"
LLM_API_KEY="your_gemini_api_key"

# Embeddings
EMBEDDING_PROVIDER="gemini"
EMBEDDING_MODEL="gemini/gemini-embedding-001"
EMBEDDING_API_KEY="your_gemini_api_key"

Make sure to configure both LLM and embedding settings. If you only set one, the other will default to OpenAI.

Installation: Install Cognee with provider-specific extras (gemini, anthropic, ollama, mistral, huggingface, or groq) for example:

uv pip install cognee[gemini]

What this gives you: Cognee installed with your chosen providers and default local databases.

For detailed configuration options, see our LLM and Embeddings guides.

Next Steps

Run Your First Example

Quickstart Tutorial

Get started with Cognee by running your first knowledge graph example.

Explore Advanced Features

Core Concepts

Dive deeper into Cognee’s powerful features and capabilities.