import gradio as gr
from api import MovieRecommender

recommender = MovieRecommender()

def recommend_movies(prompt, topk):
    df = recommender.recommend(prompt, topk=int(topk))
    return df

demo = gr.Interface(
    fn=recommend_movies,
    inputs=[
        gr.Textbox(label="Movie prompt", placeholder="action thriller with robots"),
        gr.Slider(1, 20, value=5, step=1, label="Top K")
    ],
    outputs=gr.Dataframe(label="Recommendations"),
    title="🎬 Movie Nerd",
    description="Prompt-based movie recommendations using embeddings"
)

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