import gzip
import pickle
import gradio as gr

# Load model
with gzip.open("pivot.pkl.gz", "rb") as f:
    pivot = pickle.load(f)

with gzip.open("knn_model.pkl.gz", "rb") as f:
    model = pickle.load(f)


def recommend(anime_name):
    if not anime_name or len(anime_name.strip()) < 2:
        return ["❌ Anime not found"]

    anime_name = anime_name.lower().strip()

    matches = [anime for anime in pivot.index if anime_name in anime.lower()]

    if not matches:
        return ["❌ Anime not found"]

    anime_name = matches[0]

    index = pivot.index.get_loc(anime_name)

    distances, indices = model.kneighbors(
        pivot.iloc[index, :].values.reshape(1, -1),
        n_neighbors=6
    )

    recommendations = [pivot.index[i] for i in indices[0][1:]]

    return recommendations


# 🎨 Better UI
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 🎌 Anime Recommendation System")
    gr.Markdown("Enter an anime name and get similar recommendations")

    inp = gr.Textbox(placeholder="Type anime name (e.g., Naruto)")
    btn = gr.Button("Get Recommendations")

    output = gr.Textbox(label="Recommendations")

    def run(x):
        result = recommend(x)
        return "\n".join(result)

    btn.click(fn=run, inputs=inp, outputs=output)

demo.launch()