Cognee Starter Kit

Welcome to the cognee Starter Repo! This repository is designed to help you get started quickly by providing a structured dataset and pre-built data pipelines using cognee to build powerful knowledge graphs.

You can use this repo to ingest, process, and visualize data in minutes.

By following this guide, you will:

• Load structured company and employee data
• Utilize pre-built pipelines for data processing
• Perform graph-based search and query operations
• Visualize entity relationships effortlessly on a graph

How to Use This Repo 🛠

Install dependencies

uv sync

Setup LLM

Add environment variables to .env file. In case you choose to use OpenAI provider, add just the model and api_key.

LLM_PROVIDER=""
LLM_MODEL=""
LLM_ENDPOINT=""
LLM_API_KEY=""
LLM_API_VERSION=""

EMBEDDING_PROVIDER=""
EMBEDDING_MODEL=""
EMBEDDING_ENDPOINT=""
EMBEDDING_API_KEY=""
EMBEDDING_API_VERSION=""

Activate the Python environment:

source .venv/bin/activate

Run the Default Pipeline

This script runs the cognify pipeline with default settings. It ingests text data, builds a knowledge graph, and allows you to run search queries.

python src/pipelines/default.py

Run the Low-Level Pipeline

This script implements its own pipeline with custom ingestion task. It processes the given JSON data about companies and employees, making it searchable via a graph.

python src/pipelines/low_level.py

Run the Custom Model Pipeline

Custom model uses custom pydantic model for graph extraction. This script categorizes programming languages as an example and visualizes relationships.

python src/pipelines/custom-model.py

Graph preview

cognee provides a visualize_graph function that will render the graph for you.

    graph_file_path = str(
        pathlib.Path(
            os.path.join(pathlib.Path(__file__).parent, ".artifacts/graph_visualization.html")
        ).resolve()
    )
    await visualize_graph(graph_file_path)

If you want to use tools like Graphistry for graph visualization:

• create an account and API key from https://www.graphistry.com
• add the following environment variables to .env file:

GRAPHISTRY_USERNAME=""
GRAPHISTRY_PASSWORD=""

Note: GRAPHISTRY_PASSWORD is API key.

What will you build with cognee?

• Expand the dataset by adding more structured/unstructured data
• Customize the data model to fit your use case
• Use the search API to build an intelligent assistant
• Visualize knowledge graphs for better insights