LangGraph

Give your LangGraph agents persistent semantic memory that survives across sessions. Store data in cognee’s knowledge graph and retrieve it via natural language—no manual state management required.

Why Use This Integration

Cross-Session Memory: Context persists across agent instances and conversation sessions
Semantic Recall: Retrieve information using natural language queries
Session Isolation: Multi-tenant support with per-user data separation
Drop-in tools: add_tool and search_tool work with LangGraph agents out of the box

Installation

pip install cognee-integration-langgraph

Quick Start

Before using the integration, configure your environment variables:

export OPENAI_API_KEY="your-openai-api-key-here"    # for LangGraph
export LLM_API_KEY="your-openai-api-key-here"       # for cognee
export LLM_MODEL="gpt-4o-mini"

Add memory tools to your LangGraph agent. Tools are built per session and the agent must be invoked asynchronously with ainvoke():

import asyncio
from langchain.agents import create_agent
from langchain_core.messages import HumanMessage
from cognee_integration_langgraph import get_sessionized_cognee_tools

async def main():
    # Build sessionized memory tools (omit the arg to auto-generate a session ID)
    add_tool, search_tool = get_sessionized_cognee_tools("user-123")

    # Create an agent with memory
    agent = create_agent(
        "openai:gpt-4o-mini",
        tools=[add_tool, search_tool],
    )

    # Store and retrieve information (note: must use await with .ainvoke())
    response = await agent.ainvoke({
        "messages": [
            HumanMessage(content="Remember: I like pizza and coding in Python")
        ]
    })
    print(response["messages"][-1].content)

if __name__ == "__main__":
    asyncio.run(main())

Tools

get_sessionized_cognee_tools(session_id=None, include_persist_tool=False, user=None) returns the memory tools:

Tool	Description
`add_tool`	Stores data in the knowledge base (`data`, optional `node_set`)
`search_tool`	Retrieves stored information with natural language (`query_text`, optional `session_id`, `query_type`); defaults to `SearchType.GRAPH_COMPLETION`
`persist_sessions_tool`	Promotes conversation sessions into the permanent graph (`session_ids`); returned only when `include_persist_tool=True`

Session Management

Pass a session_id to isolate memory per user or organization:

# User-specific memory
user_tools = get_sessionized_cognee_tools(session_id="user_123")

# Org-specific memory
org_tools = get_sessionized_cognee_tools(session_id="org_acme")

# Generate a unique session automatically
auto_tools = get_sessionized_cognee_tools()  # Uses a UUID-based session ID

Session isolation is implemented by scoping data with node_set=[session_id] for add_tool, and injecting the session_id into search_tool. Data added outside a session forms separate clusters.

How It Works

Add Tool: Stores data in cognee’s knowledge graph with embeddings
Search Tool: Retrieves relevant information via cognee’s recall pipeline
Auto-Processing: cognee extracts entities, relationships, and context automatically
Session Scoping: Data is organized by session clusters but globally accessible

Use Cases

Knowledge Accumulation

Build domain knowledge incrementally over multiple sessions:

# Add knowledge from sessions
for doc in knowledge_base:
    await agent.ainvoke({"messages": [HumanMessage(content=f"Learn: {doc}")]})

# Query across all
response = await agent.ainvoke({
    "messages": [HumanMessage(content="Find information about contract terms")]
})

Context-Aware Assistance

Maintain user context across work sessions:

# Monday
await agent.ainvoke({"messages": [HumanMessage(content="Debugging payment flow")]})

# Wednesday
await agent.ainvoke({"messages": [HumanMessage(content="What was I debugging?")]})

Multi-Tenant Applications

Isolate data per user/organization while sharing global knowledge:

# Per-user isolation
add_tool, search_tool = get_sessionized_cognee_tools(session_id=user_id)
agent = create_agent("openai:gpt-4o-mini", tools=[add_tool, search_tool])

GitHub Repository

View source code and examples

Examples

Runnable example scripts

Overview

Cloud LLM Providers

Observability

Evaluation

Data Ingestion

Agent Frameworks

Coding Agents

No-Code & Low-Code

Why Use This Integration

Installation

Quick Start

Tools

Session Management

How It Works

Use Cases

GitHub Repository

Examples

​Why Use This Integration

​Installation

​Quick Start

​Tools

​Session Management

​How It Works

​Use Cases

GitHub Repository

Examples

Why Use This Integration

Installation

Quick Start

Tools

Session Management

How It Works

Use Cases