app.py

import gradio as gr
import joblib

# Load model and vectorizer
model = joblib.load("final_emotion_model.pkl")
vectorizer = joblib.load("final_vectorizer.pkl")

# Define accuracy (hardcoded or loaded from a file)
model_accuracy = 0.9974

# Define prediction function
def predict_emotion(text):
    text_vec = vectorizer.transform([text])
    prediction = model.predict(text_vec)[0]
    return f"Prediction: {prediction}"

# Add accuracy info in the description or title
iface = gr.Interface(
    fn=predict_emotion,
    inputs="text",
    outputs="text",
    title="Emotional Manipulation Detector",
    description=f"Detects manipulative intent in messages. Model accuracy: {model_accuracy*100:.2f}%"
)

iface.launch()