Update app.py

app.py

@@ -8,42 +8,92 @@ client = Groq(
     api_key=os.getenv("GROQ_API_KEY"),  # Ensure you add this key to your environment variables
 )
 
-def get_highlight_summary(team, player, lang='en'):
-    # Generate the highlight content
-    highlight = f"Highlight of {player} from {team} in the latest game..."
+# Function to fetch team and player list from LLM (using Groq API)
+def get_team_and_players():
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {"role": "user", "content": "List all MLB teams and their top players."}
+        ],
+        model="llama-3.3-70b-versatile",  # You can adjust the model here
+    )
+    
+    return chat_completion.choices[0].message.content.strip()
+
+# Function to generate team overview
+def get_team_overview(team):
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {"role": "user", "content": f"Provide an overview of the {team} MLB team, including recent performance and standings."}
+        ],
+        model="llama-3.3-70b-versatile",
+    )
     
-    # Call Groq API for chat completions
+    return chat_completion.choices[0].message.content.strip()
+
+# Function for season predictions
+def predict_season_outcomes(team):
     chat_completion = client.chat.completions.create(
         messages=[
-            {"role": "user", "content": f"Generate a highlight summary for: {highlight}"}
+            {"role": "user", "content": f"Predict the potential season outcomes for the {team} based on their current performance."}
         ],
-        model="llama-3.3-70b-versatile",  # Specify the model to use
+        model="llama-3.3-70b-versatile",
     )
     
-    # Extract the generated summary
-    summary = chat_completion.choices[0].message.content.strip()
+    return chat_completion.choices[0].message.content.strip()
 
-    # Translate summary if necessary
-    if lang != 'en':
-        summary = GoogleTranslator(source='auto', target=lang).translate(summary)
+# Function for real-time strategy insights
+def real_time_tooltips(game_event):
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {"role": "user", "content": f"Explain the strategy behind the following baseball play: {game_event}"}
+        ],
+        model="llama-3.3-70b-versatile",
+    )
     
-    return summary
+    return chat_completion.choices[0].message.content.strip()
 
-# Create Gradio Interface
+# Gradio app interface
 def create_gradio_interface():
     with gr.Blocks() as demo:
-        gr.Markdown("### Personalized MLB Highlights System")
+        gr.Markdown("# MLB Fan Engagement App")
         
-        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")
+        with gr.Tab("Team and Player Selection"):
+            team_dropdown = gr.Dropdown(choices=[], label="Select Team")
+            player_dropdown = gr.Dropdown(choices=[], label="Select Player")
+            
+            # Update teams and players dynamically using LLM
+            def update_teams_and_players():
+                team_and_players = get_team_and_players()
+                teams = team_and_players.split("\n")  # Assuming each team is on a new line
+                team_dropdown.update(choices=teams)
+                return team_dropdown, player_dropdown
+            
+            # Load teams and players when app starts
+            update_teams_and_players_button = gr.Button("Load Teams and Players")
+            update_teams_and_players_button.click(update_teams_and_players, inputs=[], outputs=[team_dropdown, player_dropdown])
         
-        output = gr.Textbox(label="Your Highlight Summary")
+        with gr.Tab("Team Overview"):
+            team_dropdown_overview = gr.Dropdown(choices=[], label="Select Team")
+            overview_output = gr.Textbox(label="Team Overview")
+            team_dropdown_overview.change(
+                get_team_overview, inputs=team_dropdown_overview, outputs=overview_output
+            )
         
-        submit_button = gr.Button("Generate Highlight")
-        submit_button.click(get_highlight_summary, inputs=[team_input, player_input, lang_input], outputs=output)
-    
-    demo.launch()
+        with gr.Tab("Season Predictions"):
+            team_dropdown_predictions = gr.Dropdown(choices=[], label="Select Team")
+            predictions_output = gr.Textbox(label="Season Predictions")
+            team_dropdown_predictions.change(
+                predict_season_outcomes, inputs=team_dropdown_predictions, outputs=predictions_output
+            )
+        
+        with gr.Tab("Real-Time Strategy Insights"):
+            game_event_input = gr.Textbox(
+                label="Describe the game event (e.g., 'Why did the batter bunt in the 8th inning?')"
+            )
+            strategy_output = gr.Textbox(label="Strategy Explanation")
+            game_event_input.submit(real_time_tooltips, inputs=game_event_input, outputs=strategy_output)
+        
+        demo.launch()
 
-# Start the Gradio interface
+# Run the app
 create_gradio_interface()