app.py

import gradio as gr
import joblib

# Load trained model and vectorizer
try:
    model = joblib.load("positivity_model.pkl")
    vectorizer = joblib.load("vectorizer.pkl")
    print("✅ Model and vectorizer loaded successfully.")
except Exception as e:
    raise RuntimeError(f"Error loading model: {e}")

# Define the prediction function
def predict_sentiment(text):
    """Predicts positivity score based on input text."""
    features = vectorizer.transform([text])
    score = model.predict(features)[0]
    return f"Positivity Score: {round(float(score), 2)}"

# Gradio Interface
with gr.Blocks() as app:
    gr.Markdown("# 😊 Sentiment Analysis Model")
    gr.Markdown("Enter text and get a positivity score!")

    text_input = gr.Textbox(label="Input Text")
    output_label = gr.Label(label="Positivity Score")

    btn = gr.Button("Predict")
    btn.click(predict_sentiment, inputs=text_input, outputs=output_label)

    gr.Markdown("🚀 Powered by a Machine Learning Model")

# Launch app
if __name__ == "__main__":
    app.launch()