README.md

README.md

@@ -44,62 +44,3 @@ You can use **Streamlit** to interactively generate datasets through a web-based
 
 ```bash
 streamlit run app.py
-
-This will launch a web application that lets you configure the dataset parameters, such as project types, task complexity, resources, and risks, through an easy-to-use UI.
-
-Dataset Generation (CLI)
-For users preferring a command-line interface, datasets can also be generated via:
-
-Configure the dataset parameters in config.json. Set the number of projects, types of tasks, milestones, resource allocation strategies, risks, etc.
-
-Run the generator script:
-python generate_dataset.py --config config.json
-
-This will generate a dataset based on the parameters set in the config.json file.
-
-Example Configuration (config.json)
-
-{
-  "project_count": 100,
-  "methodologies": ["Agile", "Waterfall", "Hybrid"],
-  "task_types": ["Development", "Testing", "Deployment", "Documentation"],
-  "resources": {
-    "developers": 10,
-    "testers": 5,
-    "project_managers": 3
-  },
-  "risk_levels": ["low", "medium", "high"],
-  "output_format": "csv"
-}
-
-Output Example
-After running the generator, you will find the output dataset in the output/ directory (or your specified directory). The dataset will contain information like:
-
-Project Names
-Task Lists
-Start and End Dates
-Resource Allocations
-Risk Analysis
-Command-Line Options
-The script supports the following command-line options:
-
---config: Path to the configuration file (default: config.json)
---output_dir: Directory to store the generated dataset (default: output/)
-
-python generate_dataset.py --config config.json --output_dir /my/output/dir
-
-Customization
-Adding Custom Project Management Scenarios
-You can add more scenarios to the dataset generation by modifying the scenarios.py file. This allows you to introduce new types of tasks, risks, or methodologies specific to your use case.
-
-Extending Dataset Formats
-If you need the dataset in a specific format that is not yet supported (e.g., XML or SQL), you can extend the export logic by editing the exporter.py file.
-
-Contributing
-Contributions are welcome! To contribute:
-
-Fork the repository
-Create a new branch (git checkout -b feature/your-feature)
-Commit your changes (git commit -am 'Add new feature')
-Push to the branch (git push origin feature/your-feature)
-Create a new Pull Request