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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 uv if you don't have it on your system
pip install uv
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
.envfile:
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