Update app.py

app.py

@@ -7,6 +7,9 @@ matplotlib.use('Agg') # Set backend for Matplotlib to avoid GUI conflicts with G
 import matplotlib.pyplot as plt
 import time # For profiling if needed
 
+# --- Add Gemini Import ---
+import google.generativeai as genai
+
 # --- Module Imports ---
 from gradio_utils import get_url_user_token
 
@@ -160,6 +163,47 @@ def update_analytics_plots_figures(token_state_value, date_filter_option, custom
         return [error_msg] + placeholder_figs
 
 
+# --- Gemini Test Function (simple as requested, with prompt input) ---
+def call_gemini_api_direct_with_prompt(user_prompt):
+    """
+    Calls the Gemini API with the provided prompt and API key.
+    This function performs a direct API call without explicit try-except blocks
+    for the API interaction itself, as per the request.
+    """
+    # WARNING: Hardcoding API keys is not recommended for production. 
+    # Consider using environment variables or a secure config management system.
+    api_key = "AIzaSyCSfIw2kWWO1c_oa7WQ33h11O6N8egNoqk" # User provided API key
+    
+    if not user_prompt:
+        logging.warning("Gemini API call: Prompt is empty.")
+        return "Per favore, inserisci un prompt."
+
+    try:
+        # Configure the genai library with the API key
+        # This needs to be done once, but doing it per call is fine for this simple test
+        genai.configure(api_key=api_key)
+        
+        # Specify the model name as requested
+        model_name = "gemini-2.5-flash-preview-05-20" 
+        
+        # Create a GenerativeModel instance
+        model = genai.GenerativeModel(model_name)
+        
+        # Generate content based on the user's prompt
+        # Direct execution of the API call
+        response = model.generate_content(user_prompt)
+        
+        # Log the response text (optional, for server-side debugging)
+        logging.info(f"Gemini API call successful. Prompt: '{user_prompt}'. Response: '{response.text[:100]}...'")
+        
+        return response.text
+    except Exception as e:
+        # Catching exceptions here to provide a user-friendly message in the UI
+        # instead of letting the Gradio app crash or show a raw error.
+        logging.error(f"Error calling Gemini API: {e}", exc_info=True)
+        return f"Errore durante la chiamata API Gemini: {str(e)}"
+
+
 # --- Gradio UI Blocks ---
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
                title="LinkedIn Organization Dashboard") as app:
@@ -193,6 +237,37 @@ with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
             sync_status_html_output = gr.HTML("<p style='text-align:center;'>Stato sincronizzazione...</p>")
             dashboard_display_html = gr.HTML("<p style='text-align:center;'>Caricamento dashboard...</p>")
 
+            # --- Gemini API Test Section ---
+            gr.Markdown("---") # Visual separator
+            gr.Markdown("## 🧪 Test Gemini API (Semplice)")
+            gr.Markdown("Inserisci un prompt e clicca il pulsante per testare la chiamata all'API Gemini.")
+            
+            with gr.Row():
+                gemini_test_prompt_input = gr.Textbox(
+                    label="Prompt per Gemini:", 
+                    value="Explain how AI works in a few words", 
+                    lines=2,
+                    scale=3
+                )
+                gemini_test_btn = gr.Button("🚀 Esegui Test Gemini", scale=1, variant="secondary")
+            
+            gemini_output_textbox = gr.Textbox(
+                label="Risposta da Gemini:", 
+                interactive=False, 
+                lines=5, 
+                show_label=True,
+                placeholder="La risposta di Gemini apparirà qui..."
+            )
+
+            # Connect the button to the Gemini API call function
+            gemini_test_btn.click(
+                fn=call_gemini_api_direct_with_prompt,
+                inputs=[gemini_test_prompt_input],
+                outputs=[gemini_output_textbox],
+                api_name="test_gemini_simple" # Optional: for API access if needed by Gradio client
+            )
+            # --- End Gemini API Test Section ---
+
             org_urn_display.change(
                 fn=initial_load_sequence,
                 inputs=[url_user_token_display, org_urn_display, token_state],
@@ -543,5 +618,6 @@ if __name__ == "__main__":
     except ImportError:
         logging.error("Matplotlib non è installato. I grafici non verranno generati.")
 
+    # Ensure you have the google-generativeai library installed:
+    # pip install google-generativeai
     app.launch(server_name="0.0.0.0", server_port=7860, debug=True)
-