import streamlit as st
import pandas as pd
from recommender import load_movie_data, recommend_movies

# Load data
df = load_movie_data()

st.set_page_config(page_title="Movie Chatbot", layout="centered")
st.title("🎬 Movie Recommender Chatbot")
st.write("Answer a few quick questions and get personalized movie suggestions!")

# Step 1: Mood
mood = st.radio("What's your mood today?", ["Feel-good", "Intense", "Thought-provoking", "Funny"])

# Step 2: Genre
genre = st.selectbox("Pick a genre:", ["Any", "Sci-Fi", "Drama", "Romance", "Action", "Mystery", "Comedy", "Animation", "Thriller"])

# Step 3: Minimum rating
min_rating = st.slider("Minimum IMDb rating:", 1.0, 10.0, 7.0)

# Submit button
if st.button("🎥 Recommend Movies"):
    st.write("Here are some movies you might like:")

    results = recommend_movies(
        df,
        mood=None if mood == "Any" else mood,
        genre=None if genre == "Any" else genre,
        min_rating=min_rating
    )

    if not results.empty:
        for _, row in results.iterrows():
            if pd.notna(row["poster"]):
                st.image(row["poster"], width=200)

            st.markdown(f"**🎬 {row['title']}** ({row['year']}) — *{row['genre']}*")
            st.write(f"⭐ {row['rating']}")
            st.markdown("---")
    else:
        st.warning("No movies matched your filters. Try relaxing the criteria!")