app.py

import gradio as gr
import openai
import requests
from deep_translator import GoogleTranslator
import os

# Set up OpenAI API key from environment variables
openai.api_key = os.getenv("OPENAI_API_KEY")

# MLB API endpoint (mocked, replace with actual MLB API endpoint)
MLB_API_URL = "https://api.mlb.com/v1/games/"  # Example; replace with actual URL

def get_highlight_summary(team, player, lang='en'):
    # Fetch game data from MLB API (this is a mockup)
    highlight = f"Highlight of {player} from {team} in the latest game..."
    
    # Generate a summary with OpenAI API
    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=f"Generate a highlight summary for: {highlight}",
        max_tokens=100
    )
    summary = response.choices[0].text.strip()

    # Translate summary if necessary
    if lang != 'en':
        summary = GoogleTranslator(source='auto', target=lang).translate(summary)
    
    return summary

# Create Gradio Interface
def create_gradio_interface():
    with gr.Blocks() as demo:
        gr.Markdown("### Personalized MLB Highlights System")
        
        team_input = gr.Textbox(label="Enter your favorite team", placeholder="e.g., New York Yankees")
        player_input = gr.Textbox(label="Enter your favorite player", placeholder="e.g., Aaron Judge")
        lang_input = gr.Dropdown(choices=["en", "es", "ja"], label="Select language", value="en")
        
        output = gr.Textbox(label="Your Highlight Summary")
        
        submit_button = gr.Button("Generate Highlight")
        submit_button.click(get_highlight_summary, inputs=[team_input, player_input, lang_input], outputs=output)
    
    demo.launch()

# Start the Gradio interface
create_gradio_interface()