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import streamlit as st
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import pandas as pd
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from recommender import load_movie_data, recommend_movies
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df = load_movie_data()
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st.set_page_config(page_title="Movie Chatbot", layout="centered")
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st.title("🎬 Movie Recommender Chatbot")
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st.write("Answer a few quick questions and get personalized movie suggestions!")
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mood = st.radio("What's your mood today?", ["Feel-good", "Intense", "Thought-provoking", "Funny"])
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genre = st.selectbox("Pick a genre:", ["Any", "Sci-Fi", "Drama", "Romance", "Action", "Mystery", "Comedy", "Animation", "Thriller"])
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min_rating = st.slider("Minimum IMDb rating:", 1.0, 10.0, 7.0)
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if st.button("🎥 Recommend Movies"):
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st.write("Here are some movies you might like:")
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results = recommend_movies(
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df,
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mood=None if mood == "Any" else mood,
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genre=None if genre == "Any" else genre,
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min_rating=min_rating
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)
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if not results.empty:
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for _, row in results.iterrows():
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if pd.notna(row["poster"]):
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st.image(row["poster"], width=200)
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st.markdown(f"**🎬 {row['title']}** ({row['year']}) — *{row['genre']}*")
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st.write(f"⭐ {row['rating']}")
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st.markdown("---")
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else:
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st.warning("No movies matched your filters. Try relaxing the criteria!")
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