chore: replaced needed stuff

app.py

@@ -198,7 +198,7 @@ Return format: [card1_data, card2_data, card3_data, ...]
         logger.debug("Adding metadata to extracted data")
         for i, data in enumerate(response_data):
             # Use user-friendly model name for Excel
-            data['method'] = "Speed-Optimized AI" if "flash" in model_name else "Accuracy-Optimized AI"
+            data['method'] = "Speed-Optimized model" if "flash" in model_name else "Accuracy-Optimized model"
             if i < len(filenames):
                 data['filename'] = filenames[i]
                 logger.debug(f"Added metadata to card {i+1}: {filenames[i]}")
@@ -232,7 +232,7 @@ Return format: [card1_data, card2_data, card3_data, ...]
             logger.debug("Adding metadata to cleaned extracted data")
             for i, data in enumerate(response_data):
                 # Use user-friendly model name for Excel
-                data['method'] = "Speed-Optimized AI" if "flash" in model_name else "Accuracy-Optimized AI"
+                data['method'] = "Speed-Optimized model" if "flash" in model_name else "Accuracy-Optimized model"
                 if i < len(filenames):
                     data['filename'] = filenames[i]
                     logger.debug(f"Added metadata to cleaned card {i+1}: {filenames[i]}")
@@ -580,7 +580,7 @@ def process_business_cards(images, model_name="gemini-2.5-flash", save_images=Tr
     logger.info("Creating summary message")
     num_batches = len(image_batches) if 'image_batches' in locals() else 1
     summary = f"Successfully processed {len(all_data)} business card(s) in {num_batches} batch(es) of up to 5 cards.\n"
-    model_display = "Speed-Optimized AI" if "flash" in model_name else "Accuracy-Optimized AI"
+    model_display = "Speed-Optimized model" if "flash" in model_name else "Accuracy-Optimized model"
     summary += f"🤖 AI Model used: {model_display}\n"
     summary += f"⚡ API calls made: {num_batches} (instead of {len(all_data)})\n"
     
@@ -670,7 +670,7 @@ with gr.Blocks(title="Business Card Data Extractor") as demo:
             )
             
             model_selector = gr.Dropdown(
-                choices=[("Accuracy-Optimized AI", "gemini-2.5-pro"), ("Speed-Optimized AI", "gemini-2.5-flash")],
+                choices=[("Accuracy-Optimized model", "gemini-2.5-pro"), ("Speed-Optimized model", "gemini-2.5-flash")],
                 value="gemini-2.5-pro",
                 label="AI Model Selection"
             )
@@ -711,7 +711,7 @@ with gr.Blocks(title="Business Card Data Extractor") as demo:
     gr.Markdown(
         """
         ## Features:
-        - 🤖 **Model Selection**: Choose between Speed-Optimized AI (fast) or Accuracy-Optimized AI (accurate)
+        - 🤖 **Model Selection**: Choose between Speed-Optimized model (fast) or Accuracy-Optimized model (accurate)
         - ⚡ **Batch Processing**: Processes 5 cards per API call for efficiency
         - 📄 **Data Extraction**: Names, emails, phone numbers, addresses, and more
         - 📞 **Smart Combination**: Multiple emails/phones combined with commas