README.md

---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: system
    dtype: string
  - name: user
    dtype: string
  - name: summary
    dtype: string
  splits:
  - name: train
    num_bytes: 15849
    num_examples: 27
  download_size: 14229
  dataset_size: 15849
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
license: agpl-3.0
language:
- en
- fr
pretty_name: AI Outlook prompts
---

# AI Prompts Dataset

A collection of carefully crafted AI prompts used in the AI Outlook Add-in, designed to enhance email communication and assist in software development tasks.

## Overview

This dataset contains a variety of AI prompts originally developed for the [AI Outlook Add-in](https://github.com/sctg-development/ai-outlook). These prompts are intended to guide AI language models in tasks such as improving email drafts, translating text, summarizing content, drafting professional correspondence, and assisting with code review and optimization.

## Contents

The dataset includes prompts covering the following categories:

- **Email Enhancement**: Improve the language, tone, and clarity of email drafts in English and French.
- **Translation**: Accurately translate text while maintaining the original meaning, tone, and context.
- **Summarization**: Summarize complex emails or web pages into clear, concise bullet-point formats.
- **Professional Correspondence**: Draft polite and professional emails for various scenarios, including declining invitations, requesting meetings, and following up on communications.
- **Code Assistance**: Review code for quality, performance optimization, and security vulnerabilities; add meaningful comments; and create clear documentation.

## Dataset Structure

Each prompt in the dataset includes the following fields:

- `id`: A unique identifier for the prompt.
- `system`: Instructions provided to the AI model to set the context and specify the task.
- `user`: A template or example of user input that accompanies the system prompt.
- `summary`: A brief summary of the prompt's purpose.

## Usage

You can load the dataset using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

dataset = load_dataset("eltorio/ai-prompts")
```

## License

This dataset is licensed under the [GNU Affero General Public License v3.0 (AGPLv3)](https://www.gnu.org/licenses/agpl-3.0.en.html), the same license as the AI Outlook Add-in.

## Author

- **Ronan Le Meillat**
- Company: SCTG Development
- GitHub: [sctg-development](https://github.com/sctg-development/)

## Acknowledgments

- [AI Outlook Add-in](https://github.com/sctg-development/ai-outlook): The source of the prompts in this dataset.

## Citation

If you use this dataset, please cite it as follows:

```bibtex
@dataset{le_meillat_ai_prompts_2024,
  author       = {Le Meillat, Ronan},
  title        = {AI Prompts Dataset},
  year         = {2024},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/eltorio/ai-prompts},
  note         = {Dataset of AI prompts for enhancing email communication and software development tasks},
}
```