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thinking-dataset

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Creating a Thinking Dataset: Leveraging Real-World Data for Strategic Business Insights and STaR Case Study Generation.

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# Thinking Dataset: Leveraging Real-World Data for Strategic Business Insights

[![License](https://img.shields.io/github/license/MultiTonic/thinking-dataset)](https://raw.githubusercontent.com/MultiTonic/thinking-dataset/main/LICENSE)
[![Python Version](https://img.shields.io/badge/python-3.12%2B-blue)](https://www.python.org/downloads/)
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## Table of Contents
- [Overview](#overview)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Quick Start](#quick-start)
- [Project Structure](#project-structure)
- [Contributing](#contributing)
- [Resources](#resources)
- [License](#license)
- [Citations](#citations)
- [Acknowledgements](#acknowledgements)
- [Contact](#contact)

## Overview
Thinking Dataset leverages real-world data and efficient pipelines for business insights. We integrate robust data workflows (PDF to SQL ingestion), tactical TDD ([details](docs/02c_TESTING.md)), and a streamlined SQLite design ([details](docs/02b_DATABASE.md)). Multi-stage AI generates STaR case studies for actionable strategies.

## Features
- 🔄 **End-to-End Pipeline**: Download, process, transform, and store large datasets.
- 💾 **SQLite Backend**: Lightweight, fast, and easy to manage, with optional Parquet.
- ✅ **Comprehensive Testing**: Thorough TDD coverage and validation checks.
- 🖥️ **Flexible CLI**: Modular Click commands for quick execution of tasks.
- 🔀 **Data Transformation**: Granular pipes for cleaning, merging, and deriving data.
- 📚 **STaR Case Studies**: Generate synthetic scenarios alongside real data for deeper insights.
- ⚡ **Parallel Execution**: Efficiently process big data with optional concurrency.
- 🔒 **Secure Config**: Manage environment variables discretely with .env files.

## Quick Start

### Prerequisites

- [**Python 3.12**](https://www.python.org/downloads/release/python-3128/) or later
- [**Git**](https://git-scm.com/)
- A **cloud-based account** (e.g., ***Huggingface***) or a **GPU** (***RTX 3090*** or greater) for processing, or both

### Setup

1. **Clone the [repository](https://github.com/MultiTonic/thinking-dataset.git):**

```bash
    git clone https://github.com/MultiTonic/thinking-dataset.git
    cd thinking-dataset
    ```

2. **Install [`uv`](https://docs.astral.sh/uv/) package manager:**

First add the package into the global environment:
    ```bash
    pip install uv
    ```

Then add uv tools directory to PATH*:
    ```bash
    uv tool update-shell
    ```

3. **Set up the project:**
    ```bash
    uv run setup
    ```

>___*You may need to restart your terminal session for the changes to update.___

This will create a virtual environment, install the project dependencies, and activate the virtual environment.

4. **Set up environment variables:**

Copy the `.env.sample` file to `.env` and change the values as needed:
    ```bash
    cp .env.sample .env
    ```

Update the `.env` file with your credentials:
    ```ini
    # Required settings
    HF_ORG="my_huggingface_organization"
    HF_USER="my_huggingface_username"
    HF_READ_TOKEN="my_huggingface_read_access_token"
    HF_WRITE_TOKEN="my_huggingface_write_access_token"

# Required configuration
    CONFIG_PATH="config/config.yaml"

# One or more providers
    OLLAMA_SERVER_URL="http://localhost:11434"
    OPENAI_API_TOKEN="your_openai_api_token"
    RUNPOD_API_TOKEN="your_runpod_api_token"
    ```

## Usage

For complete usage instructions and examples, see the [**Usage Guide**](docs/05_USAGE.md).

### Running the Download Command

To download all parquet files from the Cablegate dataset using Hugging Face CLI:
```bash
thinking-dataset download
```

### Running All CLI Commands

To execute all CLI commands for the project:
```bash
python assets/scripts/run_cli_commands.py
```

## Project Structure

The following directory structure provides an overview of how the project is organized:

```
thinking-dataset/
├── config/                 # Configuration files
├── assets/                 # Assets directory for external resources
│   ├── prompts/            # Prompt templates
│   ├── scripts/            # Utility scripts
│   ├── resources/          # External project data
│   ├── templates/          # JSON prompt templates
├── data/                   # Data directory
├── docs/                   # Project documentation
├── reports/                # Generated reports
├── tests/                  # Test files
├── thinking_dataset/       # Core project code
│   ├── commands/           # CLI command implementations
│   ├── connectors/         # Data connectors
│   ├── config/             # Configuration loaders and management
│   ├── datasets/           # Dataset definitions and processing
│   │   ├── operations/     # Data operations and transformations
│   ├── db/                 # Database support
│   │   ├── operations/     # Database operations and transactions
│   ├── dto/                # Data Transfer Objects (DTO)
│   ├── io/                 # File I/O operations
│   ├── pipeworks/          # Pipelines and pipes for data processing
│   │   ├── pipelines/      # Pipeline management and control
│   │   ├── pipes/          # Pipes used for data frame processing
│   ├── providers/          # AI data providers
│   ├── tonics/             # Data utility functions and helpers
│   ├── utils/              # General-purpose utility helpers
│   ├── main.py             # Main execution file
└── setup.py                # Project setup
└── .env                    # Private environment variables file
```

## Contributing

Contributions are welcome! Fork the repository, make your changes, and create a pull request. Ensure your code follows the project's standards and includes tests. See [**Contributing**](CONTRIBUTING.md) for guidelines.

## Resources

- **[GitHub Repository](https://github.com/MultiTonic/thinking-dataset)**
- **[Python](https://www.python.org/downloads/)**
- **[Ollama](https://ollama.com/)**
- **[Discord: 🌟Tonic's Better Prompts](https://discord.gg/RgxcdVFjpz)**

## License

This dataset is licensed under the MIT License.

## Citations

Please use the following BibTeX entry to cite this dataset:

```bibtex
@software{thinking-dataset,
  author = {Kara Rawson, Joseph Pollack, and et al.},
  title = {Thinking-Dataset: Leveraging Real-World Data for Strategic Business Insights and STaR Case Study Generation},
  year = {2025},
  howpublished = {\url{https://github.com/MultiTonic/thinking-dataset}},
  note = {Accessed: 2025-01-25}
}
```

## Acknowledgements

Special thanks to our contributors:

- **Kara Rawson** - Lead Engineer
- **Joseph Pollack** - Creator & Business Leader
- **MultiTonic Team** - Support and Collaboration
- **Hugging Face** - Robust tools and infrastructure for dataset management

## Contact

For questions or support, please contact us at:

- **Email**: info@multitonics.ai
- **Discord**: [Join our Discord](https://discord.gg/RgxcdVFjpz)

thinking-dataset

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