Create app.py

app.py

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+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()