app.py

import gradio as gr
import pandas as pd 
from ScriptMatcher import ScriptMatcher
# Initialize the ScriptMatcher instance
scriptmatcher = ScriptMatcher()

def classify_movie_genre(description, genres):
    """
    Given a description (synopsis) and genres, return similar series predictions.
    """
    # Split the genres string into a list of keywords
    genre_keywords = genres.split(",")  # Assuming genres are comma-separated
    # Get the predictions using the ScriptMatcher
    predictions = scriptmatcher.find_similar_series(description, genre_keywords)
    
    return pd.DataFrame(predictions)

# Create the Gradio interface
iface = gr.Interface(
    fn=classify_movie_genre,
    inputs=[
        gr.Textbox(lines=5, label="Synopsis (Description)"),
        gr.Textbox(label="Genres (Comma-separated)")
    ],
    outputs=gr.Dataframe(label="Similar Series Predictions"),
    live=False,  # No need for live updates as the processing will be based on submission
    title="Genre Prediction",
    description="Provide a movie synopsis and genres to get predictions for similar scripts.",
)

# Launch the Gradio interface
iface.launch(inline=False)