# Sentiment Checker (Docker + Hugging Face Spaces)

A minimal interactive web app that performs sentiment analysis using a Hugging Face model.  
Users can type text, click a button, and instantly receive a prediction.

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## 🚀 Live Concept

- Type text into a box  
- Click **Check**  
- Get sentiment (POSITIVE / NEGATIVE)

---

## 🧠 Why This Project Exists

Machine learning apps often fail to run across different environments due to:
- dependency conflicts  
- mismatched library versions  
- complex setup requirements  

This project demonstrates how Docker solves these issues and enables seamless deployment on Hugging Face Spaces.

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## 🧰 Tech Stack

- Python  
- FastAPI  
- Transformers (by Hugging Face)  
- Docker  

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## 📁 Project Structure

```

.
├── app.py
├── requirements.txt
└── Dockerfile

````

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## ⚙️ How It Works

1. The frontend is a simple HTML page served by FastAPI  
2. User input is sent to the `/predict` endpoint  
3. A pre-trained sentiment model processes the text  
4. The result is returned and displayed instantly  

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## 🐳 Docker Setup

### Build the image
```bash
docker build -t sentiment-app .
````

### Run the container

```bash
docker run -p 7860:7860 sentiment-app
```

Then open: [http://localhost:7860](http://localhost:7860)

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## 🤗 Deployment (Hugging Face Spaces)

This app is designed to run on Hugging Face Spaces using Docker.

Steps:

1. Create a new Space
2. Select **Docker** as the SDK
3. Upload project files
4. The app will automatically build and deploy

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## 💡 Why Docker Matters

Without Docker:

* Manual installation of dependencies
* Version conflicts (e.g., Torch, Transformers)
* Inconsistent results across machines

With Docker:

* Reproducible environment
* One-step deployment
* Works the same everywhere

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## ⚠️ Notes

* The first run may take longer due to model download
* Subsequent requests are much faster

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## ✅ Key Takeaway

Docker enables reliable, reproducible deployment of machine learning applications, making it easy to share and run apps on platforms like Hugging Face Spaces without additional setup.

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