---
license: mit
task_categories:
- text-generation
language:
- si
- en
tags:
- recommendation-system
- emotions
- sinhala
- singlish
size_categories:
- 1K<n<10K
---

# emoBooks Dataset 📚✨

## Overview
The **emoBooks** dataset is a curated collection of conversational samples designed to train AI models for **emotion-aware book recommendations**. It focuses on understanding user emotions and providing relevant book suggestions in "Singlish" (transliterated Sinhala).

The dataset follows a **Match/Switch** logic:
- **Match**: Recommend books that align with the user's current emotional state.
- **Switch**: Recommend books that help transition the user to a more positive emotional state (e.g., from Sadness to Joy).

## Dataset Structure
The dataset is provided in a standard **ChatML/OpenAI format**, making it ideal for instruction fine-tuning of models like Llama-3, Mistral, or Gemma.

### Format
Each entry is a JSON object with a `messages` list:
```json
{
  "messages": [
    { "role": "user", "content": "I feel very lonely and sad today." },
    { "role": "assistant", "content": "I can sense you're feeling that way. Would you like a book that matches your current mood, or something to help you switch to a more positive state?" },
    { "role": "user", "content": "I'd like something that matches how I feel." },
    { "role": "assistant", "content": "I understand. Since you're looking for something that matches your mood, I recommend 'Maha Nidagala Saha Abirahasa' by 'Dhigala'. It's a deep 'Translations' book that resonates with those feelings." }
  ]
}
```

## Emotion Categories
The dataset covers 8 primary emotional states:
1.  **Sadness** (0)
2.  **Joy** (1)
3.  **Love** (2)
4.  **Anger** (3)
5.  **Fear** (4)
6.  **Surprise** (5)
7.  **Disgust** (6)
8.  **Calm** (7)

## Book Categories
The recommendations include various genres:
- Children's Stories (ළමා කතා)
- Novels (නවකතා)
- Translations (පරිවර්තන)
- Biographies (චරිතාපදාන)
- Short Stories (කෙටි කතා)

## Data Generation
This dataset was synthetically generated using a custom pipeline that:
1.  Transliterated Sinhala book titles and authors into Singlish.
2.  Mapped book categories to primary emotions.
3.  Generated conversational templates for various user-assistant interactions.

## Intended Use
This dataset is intended for:
- Fine-tuning Large Language Models (LLMs) for recommendation systems.
- Research in emotion-aware conversational AI.
- Developing bilingual (Sinhala/English) literary assistants.

## Licensing
[MIT License] - Free to use for research and development.