import gradio as gr
from product_recommender import ProductRecommender
import urllib.parse

def get_recommendations(text: str) -> dict:
    try:
        recommender = ProductRecommender()
        recs = recommender.get_recommendations(text, [])
        
        # Add shopping links
        for rec in recs:
            query = urllib.parse.quote(rec['name'])
            rec['links'] = {
                "Amazon": f"https://www.amazon.in/s?k={query}",
                "Flipkart": f"https://www.flipkart.com/search?q={query}",
                "IGP": f"https://www.igp.com/search?q={query}"
            }
        
        return {"recommendations": recs}
    except Exception as e:
        return {"error": str(e)}

demo = gr.Interface(
    fn=get_recommendations,
    inputs=gr.Textbox(lines=3),
    outputs=gr.JSON(),
    title="🎁 Smart Gift Recommender",
    description="Get personalized gift suggestions with shopping links!"
)

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)
else:
    app = demo.app