Manages environment variables for secure storage of the Hugging Face token needed for API authentication.
Facilitates deployment of the MCP server to Hugging Face Spaces through version control.
Provides a user interface for interacting with the sentiment analysis and sarcasm detection models, allowing for text input and displaying structured results.
Enables deployment to Hugging Face Spaces and utilizes Hugging Face Transformers models for sentiment analysis and sarcasm detection.
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. The app is fully compatible with the Hugging Face MCP server architecture.
Live Demo
š Launch the app on Hugging Face Spaces
Related MCP server: Grumpy Senior Developer MCP
Architecture Overview
Models (CPU-only):
distilbert-base-uncased-finetuned-sst-2-english: Sentiment analysishelinivan/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:
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
2. Create a virtual environment
3. Install dependencies
Make sure gradio[mcp] is included for MCP compatibility.
4. Add Hugging Face token
Create a .env file:
5. Run the app locally
Deploy to Hugging Face Spaces
Once pushed, the MCP server endpoint will be live at:
Credits
Hugging Face MCP Course