# Sentiment + Sarcasm Analyzer (Gradio + MCP)

This project is a lightweight Gradio application that performs **sentiment analysis** and **sarcasm detection** using Hugging Face Transformers. It is designed to run on CPU and was developed as part of the [Hugging Face MCP Course](https://huggingface.co/learn/mcp-course). The app is fully compatible with the Hugging Face MCP server architecture.

## Live Demo

👉 [Launch the app on Hugging Face Spaces](https://huggingface.co/spaces/igorpavlov-mgr/mcp-sentiment)

## Architecture Overview

- **Models (CPU-only):**
  - `distilbert-base-uncased-finetuned-sst-2-english`: Sentiment analysis
  - `helinivan/english-sarcasm-detector`: Sarcasm detection

- **Frontend**: Gradio UI  
- **Backend**: Python with Hugging Face Transformers  
- **MCP Integration**: Hugging Face MCP-compatible (`gradio[mcp]`)

## Features

- Sentiment classification: "positive" or "negative"
- Sarcasm detection with a probability score
- CPU-compatible (no GPU required)
- Simple and clean Gradio interface

## Output Format

The app returns a structured JSON response with four fields:

```json
{
  "assessment": "positive",
  "confidence": 1.0,
  "sarcasm_detected": true,
  "sarcasm_confidence": 0.97
}
```

## Gradio Interface

The interface provides the following controls:

| Element       | Description |
|---------------|-------------|
| **Textbox**   | Enter text to be analyzed |
| **Submit**    | Run the sentiment and sarcasm analysis |
| **Clear**     | Reset the input/output |

## Setup Instructions

### 1. Clone the repository

```bash
git clone https://github.com/YOUR_USERNAME/mcp-sentiment
cd mcp-sentiment
```

### 2. Create a virtual environment

```bash
python -m venv .venv
# Then activate:
.venv\Scripts\activate      # Windows
source .venv/bin/activate     # macOS/Linux
```

### 3. Install dependencies

```bash
pip install -r requirements.txt
```

Make sure `gradio[mcp]` is included for MCP compatibility.

### 4. Add Hugging Face token

Create a `.env` file:

```ini
HF_TOKEN=your_token_here
```

### 5. Run the app locally

```bash
python app.py
```

## Deploy to Hugging Face Spaces

```bash
git init
git remote add origin https://huggingface.co/spaces/YOUR_USERNAME/mcp-sentiment
git add .
git commit -m "Deploy MCP app"
git push -u origin main
```

Once pushed, the MCP server endpoint will be live at:

```
https://YOUR_USERNAME-mcp-sentiment.hf.space/gradio_api/mcp/sse
```

## Credits

- Hugging Face MCP Course  
- Model: [`distilbert-base-uncased-finetuned-sst-2-english`](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english)  
- Model: [`helinivan/english-sarcasm-detector`](https://huggingface.co/helinivan/english-sarcasm-detector)  
- [Gradio](https://gradio.app/)