import streamlit as st
import pandas as pd
import torch  # Ensure PyTorch is imported
from transformers import AutoTokenizer, AutoModelForCausalLM

# Load the Netflix dataset from CSV
@st.cache_data
def load_data():
    df = pd.read_csv("https://huggingface.co/spaces/mfraz/Netflix-data/resolve/main/netflix_titles.csv")
    df.fillna("N/A", inplace=True)  # Replace NaN values with "N/A"
    return df

# Load DialoGPT model and tokenizer
@st.cache_resource
def load_model():
    tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
    model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
    return tokenizer, model

# Function to search the dataset for movie details
def search_movie_details(query, data):
    query = query.lower()
    
    # Filtering: Ensure column names exist and search query is in title, cast, or director
    results = data[
        data["title"].str.lower().str.contains(query, na=False) |
        data["cast"].str.lower().str.contains(query, na=False) |
        data["director"].str.lower().str.contains(query, na=False)
    ]
    
    return results

# Streamlit App
st.title("Netflix Movies 🎬")

# Load dataset and model
data = load_data()
tokenizer, model = load_model()

# User Input (Only Text)
user_input = st.text_input("Enter the movie name, director, or cast:")

# Generate response
if user_input:
    movie_results = search_movie_details(user_input, data)
    
    if not movie_results.empty:
        st.write("Here are the matching results:")
        for _, row in movie_results.iterrows():
            st.write(f"**Title:** {row['title']}")
            st.write(f"**Type:** {row['type']}")
            st.write(f"**Director:** {row['director']}")
            st.write(f"**Cast:** {row['cast']}")
            st.write(f"**Release Year:** {row['release_year']}")
            st.write(f"**Country:** {row['country']}")  # ✅ Now displays Country correctly
            st.write(f"**Rating:** {row['rating']}")
            st.write(f"**Description:** {row['description']}")
            st.write("---")
    else:
        st.write("**I have no data about this movie. Please search another movie.**")