cognee-integration-langgraph 0.1.1

A powerful integration between LangGraph and Cognee providing intelligent knowledge management and retrieval capabilities for AI agents

Cognee-Integration-LangGraph

A powerful integration between Cognee and LangGraph that provides intelligent knowledge management and retrieval capabilities for AI agents.

Overview

cognee-integration-langgraph combines Cognee's advanced knowledge storage and retrieval system with LangGraph's workflow orchestration capabilities. This integration allows you to build AI agents that can efficiently store, search, and retrieve information from a persistent knowledge base.

Features

• Smart Knowledge Storage: Add and persist information using Cognee's advanced indexing
• Semantic Search: Retrieve relevant information using natural language queries
• Session Management: Support for user-specific data isolation
• LangGraph Integration: Seamless integration with LangGraph's agent framework
• Async Support: Built with async/await for high-performance applications

Installation

# Using uv
uv add cognee-integration-langgraph

# Using pip
pip install cognee-integration-langgraph

Available Tools

get_sessionized_cognee_tools(session_id: str = None)

Returns sessionized cognee tools for isolated data management.

Returns: (add_tool, search_tool) - A tuple of tools for storing and searching data

Individual Tools

• add_tool: Store information in the knowledge base
• search_tool: Search and retrieve previously stored information

Session Management

cognee-integration-langgraph supports user-specific sessions to isolate data between different users or contexts:

from cognee_integration_langgraph import get_sessionized_cognee_tools

user1_tools = get_sessionized_cognee_tools("user-123")
user2_tools = get_sessionized_cognee_tools("user-456")

Configuration

Copy the .env.template file to .env and fill out the required API keys:

cp .env.template .env

Then edit the .env file and set both keys using your OpenAI API key:

OPENAI_API_KEY=your-openai-api-key-here
LLM_API_KEY=your-openai-api-key-here

Examples

Check out the examples/ directory for more comprehensive usage examples:

• examples/example.py: Complete workflow with contract management
• examples/guide.ipynb: Jupyter notebook tutorial with step-by-step guidance

Requirements

• Python 3.12+
• OpenAI API key
• Dependencies automatically managed via pyproject.toml