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It uses a Large Language Model (LLM) to parse your SQL `CREATE` statements, extracting both upstream and downstream relationships at the table and column level.\n\n---\n\n## Features\n\n- **LLM-powered parsing** of SQL DDL to extract dependencies  \n- Tracks **both upstream and downstream** lineage  \n- Captures **table-level and column-level** dependencies, including column transformations  \n- Stores extracted data for each DDL into `json` files\n- Uses **Neo4j graph database** to store the lineage data that can be queried\n- Provides a frontend to **visualize data lineage maps** for easier understanding and debugging\n\n## Frontend \n### View Dependencies\nSelect a datamodel to view its upstream and downstream dependencies.\n![Select Datamodel](resources/zoom_lineage.gif)\n\n### Show Datamodel Lineage\nIsolate the lineage to only display the datamodels upstream and downstream dependencies.\n![Show Datamodel Lineage](resources/datamodel_lineage.gif)\n\n### Search\nSearch for a datamodel by name.\n![Search Datamodel](resources/search.gif)\n\n### Show Column Lineage\nSelect a column to view the columns upstream and downstream dependencies and transformations.\n![Show Column Lineage](resources/column_lineage.gif)\n\n---\n\n## Why “WashedUp Lineage”?\n\nData warehouses often become messy, complex, and hard to navigate — basically, “washed up.” This tool aims to be a **half-decent**, practical way to bring some clarity and order by mapping out all those tangled dependencies with the help of AI.\n\n---\n\n## Getting Started\n\n### Prerequisites\n\n- Python 3.12+  \n- Neo4j database instance  \n- Access to your data warehouse DDL SQL scripts  \n\n### Setup\n\n#### 1. Neo4j Setup\n\n1. Install and start Neo4j on your system\n   - You can download Neo4j from [https://neo4j.com/deployment-center/?desktop-gdb](https://neo4j.com/deployment-center/?desktop-gdb)\n   - After installation, start the Neo4j service\n   - Neo4j Browser interface is typically available at: `http://localhost:7474/browser/`\n\n2. Configure Neo4j credentials\n   - Make note of your Neo4j URL, username and password\n   - You'll need to update these in the `.env` file in both the `llm_to_graph` and `backend` modules\n\n#### 2. LLM to Graph Module\n\n1. Navigate to the `llm_to_graph` directory:\n   ```\n   cd llm_to_graph\n   ```\n\n2. Install dependencies:\n   ```\n   pip install -r requirements.txt\n   ```\n   Note: Using a virtual environment is recommended but optional\n\n3. Configure the module:\n   - Refer to `llm_to_graph/README.md` for detailed configuration instructions\n   - Make sure to update the `.env` file with your Neo4j credentials\n\n4. Run the module:\n   ```\n   python main.py\n   ```\n\n#### 3. Backend Module\n\n1. Navigate to the backend directory:\n   ```\n   cd backend\n   ```\n\n2. Install dependencies:\n   ```\n   pip install -r requirements.txt\n   ```\n\n3. Update the `.env` file with your Neo4j credentials\n\n4. Run the backend server:\n   ```\n   python app.py\n   ```\n   - The API documentation will be available at: `http://localhost:8000/docs`\n\n#### 4. Frontend Module\n\n1. Navigate to the frontend directory:\n   ```\n   cd frontend\n   ```\n\n2. Install dependencies:\n   ```\n   npm install\n   ```\n\n3. Start the development server:\n   ```\n   ng serve\n   ```\n   - The frontend will be available at: `http://localhost:4200/`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgitgut01%2Fwashed-up-lineage","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgitgut01%2Fwashed-up-lineage","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgitgut01%2Fwashed-up-lineage/lists"}