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After completing the installation steps successfully, run your first Cognee example to see AI memory in action.

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Basic Usage

This minimal example shows how to store content and retrieve it: 
import cognee
import asyncio

async def main():

    # Create a clean slate for cognee -- reset data and system state
    await cognee.prune.prune_data()
    await cognee.prune.prune_system(metadata=True)
    
    # Store content in memory (ingests, builds knowledge graph, enriches)
    text = "Cognee turns documents into AI memory."
    await cognee.remember(text)
    
    # Retrieve from memory
    results = await cognee.recall(
        query_text="What does Cognee do?"
    )
    
    # Print
    for result in results:
        print(result)

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

Interactive knowledge graph visualization — drag nodes, zoom, and hover for details. Create your own visualization with 2 additional lines of code here.

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What just happened

The code demonstrates Cognee’s two primary v1.0 operations:
  • .remember — Stores data in memory. Under the hood it runs ingestion, chunking, entity extraction, graph building, and a follow-up enrichment pass. The result is a fully queryable knowledge graph.
  • .recall — Retrieves from memory. It auto-routes the query to the best retrieval strategy and returns contextual results from the knowledge graph.
If you need direct control over each pipeline step, the lower-level add, cognify, and search operations are still available.

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About async / await in Cognee

Cognee uses asynchronous code extensively. That means many of its functions are defined with async and must be called with await. This lets Python handle waiting (e.g. for I/O or network calls) without blocking the rest of your program.
This example uses async / await, Python’s way of doing asynchronous programming. Asynchronous programming is used when functions may block because they are waiting for something (for example, a reply from an API call). By writing async def, you define a function that can pause at certain points. The await keyword marks those calls that may need to pause. To run such functions, Python provides the asyncio library. It uses a loop, called the event loop, which executes your code in order but, whenever a function is waiting, can temporarily run another one. From inside your function, though, everything still runs top-to-bottom: each line after an await only executes once the awaited call has finished.
  • A good starting point is this guide.
  • Official documentation is available here.

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Next Steps

Cognee core concepts

Learn about Cognee’s core concepts, architecture, building blocks, and main operations.

Improve and enrich memory

Enrich an existing graph and bridge session memory into permanent memory.