Update app.py

app.py

@@ -1,6 +1,5 @@
 import gradio as gr
 import os
-import requests
 from groq import Groq
 
 # Set up Groq API client
@@ -8,97 +7,120 @@ client = Groq(
     api_key=os.getenv("GROQ_API_KEY"),  # Ensure you add this key to your environment variables
 )
 
+# Supported languages
+LANGUAGES = {
+    "English": "en",
+    "Spanish": "es",
+    "Japanese": "ja",
+    "Urdu": "ur",
+}
+
+# Function to translate text
+def translate_text(text, language_code):
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {"role": "user", "content": f"Translate this text to {language_code}: {text}"}
+        ],
+        model="llama-3.3-70b-versatile",
+    )
+    return chat_completion.choices[0].message.content.strip()
+
 # Function to fetch team overview
-def get_team_overview(team):
+def get_team_overview(team, language):
     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",
     )
-    return chat_completion.choices[0].message.content.strip()
+    result = chat_completion.choices[0].message.content.strip()
+    return translate_text(result, LANGUAGES[language])
 
 # Function to predict season outcomes
-def predict_season_outcomes(team):
+def predict_season_outcomes(team, language):
     chat_completion = client.chat.completions.create(
         messages=[
             {"role": "user", "content": f"Predict the potential season outcomes for the {team} based on their current performance."}
         ],
         model="llama-3.3-70b-versatile",
     )
-    return chat_completion.choices[0].message.content.strip()
+    result = chat_completion.choices[0].message.content.strip()
+    return translate_text(result, LANGUAGES[language])
 
 # Function for player wildcards
-def get_player_wildcards(player):
+def get_player_wildcards(player, language):
     chat_completion = client.chat.completions.create(
         messages=[
             {"role": "user", "content": f"Describe any standout performances or recent achievements for the player {player} in MLB."}
         ],
         model="llama-3.3-70b-versatile",
     )
-    return chat_completion.choices[0].message.content.strip()
+    result = chat_completion.choices[0].message.content.strip()
+    return translate_text(result, LANGUAGES[language])
 
 # Function for real-time strategy insights
-def real_time_tooltips(game_event):
+def real_time_tooltips(game_event, language):
     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 chat_completion.choices[0].message.content.strip()
-
-# Function to fetch images or news for a team/player
-def fetch_news_images(query):
-    url = "https://www.searchapi.io/api/v1/search"
-    params = {
-        "engine": "google",
-        "q": query,
-        "api_key": "PMjgK27a8Lyb6uMXP2jnSNnB",  # Replace with your API key
-    }
-    try:
-        response = requests.get(url, params=params)
-        data = response.json()
-        if "items" in data:
-            news = "\n".join([f"{item['title']}: {item['link']}" for item in data["items"][:5]])
-            return news
-        else:
-            return "No news or images found for this query."
-    except Exception as e:
-        return f"Error fetching data: {e}"
+    result = chat_completion.choices[0].message.content.strip()
+    return translate_text(result, LANGUAGES[language])
 
 # Gradio app interface
 def create_gradio_interface():
     with gr.Blocks() as demo:
-        gr.Markdown("# Enhanced MLB Fan Engagement App")
+        gr.Markdown("#MLB Fantasy World")
         
         with gr.Tab("Team Overview"):
             team_input = gr.Textbox(label="Enter Team Name")
+            language_selector = gr.Dropdown(
+                label="Select Language", choices=list(LANGUAGES.keys()), value="English"
+            )
             team_output = gr.Textbox(label="Team Overview")
-            team_news_output = gr.Textbox(label="Team News and Images")
-            team_input.submit(get_team_overview, inputs=team_input, outputs=team_output)
-            team_input.submit(fetch_news_images, inputs=team_input, outputs=team_news_output)
+            team_input.submit(
+                get_team_overview, inputs=[team_input, language_selector], outputs=team_output
+            )
         
         with gr.Tab("Season Predictions"):
             team_input_pred = gr.Textbox(label="Enter Team Name")
+            language_selector_pred = gr.Dropdown(
+                label="Select Language", choices=list(LANGUAGES.keys()), value="English"
+            )
             predictions_output = gr.Textbox(label="Season Predictions")
-            team_news_output_pred = gr.Textbox(label="Team News and Images")
-            team_input_pred.submit(predict_season_outcomes, inputs=team_input_pred, outputs=predictions_output)
-            team_input_pred.submit(fetch_news_images, inputs=team_input_pred, outputs=team_news_output_pred)
+            team_input_pred.submit(
+                predict_season_outcomes,
+                inputs=[team_input_pred, language_selector_pred],
+                outputs=predictions_output,
+            )
         
         with gr.Tab("Player Wildcards"):
             player_input = gr.Textbox(label="Enter Player Name")
+            language_selector_player = gr.Dropdown(
+                label="Select Language", choices=list(LANGUAGES.keys()), value="English"
+            )
             player_output = gr.Textbox(label="Player Highlights")
-            player_news_output = gr.Textbox(label="Player News and Images")
-            player_input.submit(get_player_wildcards, inputs=player_input, outputs=player_output)
-            player_input.submit(fetch_news_images, inputs=player_input, outputs=player_news_output)
+            player_input.submit(
+                get_player_wildcards,
+                inputs=[player_input, language_selector_player],
+                outputs=player_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?')"
             )
+            language_selector_event = gr.Dropdown(
+                label="Select Language", choices=list(LANGUAGES.keys()), value="English"
+            )
             strategy_output = gr.Textbox(label="Strategy Explanation")
-            game_event_input.submit(real_time_tooltips, inputs=game_event_input, outputs=strategy_output)
+            game_event_input.submit(
+                real_time_tooltips,
+                inputs=[game_event_input, language_selector_event],
+                outputs=strategy_output,
+            )
         
         demo.launch()