app.py

import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
from pathlib import Path

# Load model
MODEL_PATH = "outputs/final_model"

if Path(MODEL_PATH).exists():
    tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
    model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)
    model.eval()
    MODEL_LOADED = True
else:
    MODEL_LOADED = False
    model = None
    tokenizer = None

def predict_genre(track_name):
    """Predict genre for a track name"""
    if not MODEL_LOADED:
        return "Model not found. Please train first."
    
    if not track_name:
        return "Please enter a track name"
    
    # Tokenize
    inputs = tokenizer(track_name, return_tensors='pt', padding=True, truncation=True, max_length=256)
    
    # Predict
    with torch.no_grad():
        outputs = model(**inputs)
        probs = torch.softmax(outputs.logits, dim=-1)
        pred_id = torch.argmax(probs, dim=-1).item()
        confidence = probs[0, pred_id].item()
    
    # Get label
    pred_label = model.config.id2label.get(pred_id, f"Class_{pred_id}")
    
    return f"**Genre:** {pred_label}\n\n**Confidence:** {confidence:.2%}"

# Create Gradio interface
with gr.Blocks(title="Spotify Genre Classifier", theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🎵 Spotify Genre Classifier")
    gr.Markdown("Enter a song track name to predict its genre using a fine-tuned GPT-2 model.")
    
    with gr.Row():
        with gr.Column():
            track_input = gr.Textbox(
                label="Track Name",
                placeholder="e.g., Bohemian Rhapsody",
                lines=1
            )
            predict_btn = gr.Button("🔮 Predict Genre", variant="primary")
        
        with gr.Column():
            output = gr.Textbox(label="Prediction")
    
    # Examples
    gr.Examples(
        examples=[
            "Bohemian Rhapsody",
            "Shape of You",
            "Old Town Road",
            "Blinding Lights",
            "Bad Guy",
            "Stairway to Heaven",
            "Smells Like Teen Spirit",
            "Billie Jean",
        ],
        inputs=track_input
    )
    
    predict_btn.click(fn=predict_genre, inputs=track_input, outputs=output)
    track_input.submit(fn=predict_genre, inputs=track_input, outputs=output)

if __name__ == "__main__":
    demo.launch()