app.py

import gradio as gr
from transformers import pipeline

# Load a pre-trained sentiment analysis model
model = pipeline("sentiment-analysis")

# Define the function to be called by Gradio
def predict(text):
    result = model(text)[0]  # e.g., {'label': 'POSITIVE', 'score': 0.999}
    return f"{result['label']} (score: {result['score']:.2f})"

# Build Gradio interface
demo = gr.Interface(
    fn=predict,
    inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
    outputs="text",
    title="Sentiment Analysis",
    description="This app uses a Hugging Face model to predict sentiment (positive/negative)."
)

# Launch the app
demo.launch()