Update app.py

app.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 """
 Gemini Vision Pro Medical Image Analysis - Gradio Interface
-Lightweight alternative using Google's Gemini Vision Pro API
+Fixed version with HuggingFace Secrets support and better error handling
 """
 
 import gradio as gr
@@ -20,36 +20,127 @@ warnings.filterwarnings("ignore")
 GEMINI_MODEL = None
 API_KEY = None
 
+def get_api_key_from_secrets():
+    """Try to get API key from HuggingFace secrets or environment variables"""
+    # Try multiple possible secret names
+    possible_keys = [
+        'GOOGLE_API_KEY',
+        'GEMINI_API_KEY', 
+        'GOOGLE_GEMINI_API_KEY',
+        'GOOGLE_AI_API_KEY'
+    ]
+    
+    for key_name in possible_keys:
+        # First try HuggingFace secrets (if running on HF Spaces)
+        try:
+            from huggingface_hub import HfFolder
+            token = HfFolder.get_token()
+            if token:
+                # This is a simplified approach - in HF Spaces, secrets are usually available as env vars
+                api_key = os.getenv(key_name)
+                if api_key:
+                    return api_key
+        except:
+            pass
+        
+        # Try regular environment variables
+        api_key = os.getenv(key_name)
+        if api_key:
+            return api_key
+    
+    return None
+
 def setup_gemini(api_key: str = None):
     """Setup Gemini Vision Pro with API key"""
     global GEMINI_MODEL, API_KEY
     
-    # Try to get API key from environment or parameter
-    if api_key:
-        API_KEY = api_key
+    # Try to get API key from various sources
+    if api_key and api_key.strip():
+        API_KEY = api_key.strip()
     else:
-        API_KEY = os.getenv('GOOGLE_API_KEY') or os.getenv('GEMINI_API_KEY')
+        API_KEY = get_api_key_from_secrets()
     
     if not API_KEY:
-        return False, "❌ No API key provided. Please set GOOGLE_API_KEY environment variable or enter it in the interface."
+        return False, "❌ No API key found. Please:\n1. Set GOOGLE_API_KEY in HuggingFace Spaces secrets, or\n2. Enter your API key in the interface below\n\n🔗 Get your API key from: https://makersuite.google.com/app/apikey"
     
     try:
         # Configure the API
         genai.configure(api_key=API_KEY)
         
-        # Initialize the model
-        GEMINI_MODEL = genai.GenerativeModel('gemini-1.5-pro')
+        # Initialize the model with safety settings
+        safety_settings = [
+            {
+                "category": "HARM_CATEGORY_MEDICAL",
+                "threshold": "BLOCK_NONE"
+            },
+            {
+                "category": "HARM_CATEGORY_HARASSMENT",
+                "threshold": "BLOCK_ONLY_HIGH"
+            },
+            {
+                "category": "HARM_CATEGORY_HATE_SPEECH", 
+                "threshold": "BLOCK_ONLY_HIGH"
+            },
+            {
+                "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+                "threshold": "BLOCK_ONLY_HIGH"
+            },
+            {
+                "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+                "threshold": "BLOCK_ONLY_HIGH"
+            }
+        ]
         
-        # Test the connection
-        test_response = GEMINI_MODEL.generate_content("Hello, can you help with medical image analysis?")
+        GEMINI_MODEL = genai.GenerativeModel(
+            'gemini-1.5-pro',
+            safety_settings=safety_settings
+        )
+        
+        # Test the connection with a simple query
+        test_response = GEMINI_MODEL.generate_content(
+            "Respond with just 'OK' to confirm you can analyze medical images.",
+            generation_config=genai.types.GenerationConfig(
+                temperature=0.1,
+                max_output_tokens=10
+            )
+        )
         
         if test_response and test_response.text:
             return True, "✅ Gemini Vision Pro connected successfully!"
         else:
-            return False, "❌ Failed to connect to Gemini API"
+            return False, "❌ Failed to get response from Gemini API"
             
     except Exception as e:
-        return False, f"❌ Gemini setup failed: {str(e)}"
+        error_msg = f"❌ Gemini setup failed: {str(e)}"
+        
+        # Provide specific guidance based on error type
+        if "429" in str(e) or "quota" in str(e).lower():
+            error_msg += "\n\n💡 **Quota Exceeded Solutions:**\n"
+            error_msg += "• Check your Google Cloud Console billing\n"
+            error_msg += "• Verify your API key has sufficient quota\n"
+            error_msg += "• Try again in a few minutes (rate limiting)\n"
+            error_msg += "• Consider upgrading your Google AI plan\n"
+            error_msg += "🔗 Check usage: https://console.cloud.google.com/"
+            
+        elif "403" in str(e) or "permission" in str(e).lower():
+            error_msg += "\n\n💡 **Permission Error Solutions:**\n"
+            error_msg += "• Ensure Gemini API is enabled in your project\n"
+            error_msg += "• Check if your API key has proper permissions\n"
+            error_msg += "• Verify your Google Cloud project settings"
+            
+        elif "401" in str(e) or "unauthorized" in str(e).lower():
+            error_msg += "\n\n💡 **Authentication Error:**\n"
+            error_msg += "• Double-check your API key is correct\n"
+            error_msg += "• Ensure no extra spaces in the API key\n"
+            error_msg += "• Generate a new API key if needed"
+            
+        elif "safety" in str(e).lower() or "blocked" in str(e).lower():
+            error_msg += "\n\n💡 **Content Safety Issue:**\n"
+            error_msg += "• The image may have triggered safety filters\n"
+            error_msg += "• Try a different medical image\n"
+            error_msg += "• Ensure the image is clearly medical in nature"
+        
+        return False, error_msg
 
 def create_medical_prompt(clinical_data: Dict, analysis_type: str, focus_areas: str) -> str:
     """Create optimized medical analysis prompt for Gemini"""
@@ -59,10 +150,11 @@ def create_medical_prompt(clinical_data: Dict, analysis_type: str, focus_areas:
 **ANALYSIS INSTRUCTIONS:**
 Analyze this medical image systematically and professionally:
 - Use clear medical terminology with explanations for complex terms
-- Structure your response with clear sections and headers
+- Structure your response with clear sections and headers  
 - Be thorough but concise
 - Always mention limitations and emphasize the need for professional medical consultation
 - Focus on observable findings rather than definitive diagnoses
+- This is for educational and research purposes only
 """
     
     # Add clinical context if provided
@@ -185,11 +277,11 @@ def analyze_medical_image_gemini(
         
         # Prepare clinical data
         clinical_data = {
-            "age": age.strip(),
-            "gender": gender,
-            "symptoms": symptoms.strip(),
-            "history": history.strip(),
-            "medications": medications.strip()
+            "age": age.strip() if age else "",
+            "gender": gender if gender else "",
+            "symptoms": symptoms.strip() if symptoms else "",
+            "history": history.strip() if history else "",
+            "medications": medications.strip() if medications else ""
         }
         
         # Create prompt
@@ -197,11 +289,22 @@ def analyze_medical_image_gemini(
         
         progress(0.5, desc="Analyzing image with Gemini...")
         
+        # Configure generation parameters for better results
+        generation_config = genai.types.GenerationConfig(
+            temperature=0.3,  # Lower temperature for more consistent medical analysis
+            max_output_tokens=2048,  # Sufficient for detailed analysis
+            top_p=0.8,
+            top_k=40
+        )
+        
         # Generate analysis using Gemini Vision Pro
-        response = GEMINI_MODEL.generate_content([prompt, image])
+        response = GEMINI_MODEL.generate_content(
+            [prompt, image],
+            generation_config=generation_config
+        )
         
         if not response or not response.text:
-            return "❌ No response received from Gemini API", "", "❌ Analysis failed"
+            return "❌ No response received from Gemini API. The image may have been blocked by safety filters or there was a processing error.", "", "❌ Analysis failed"
         
         progress(0.9, desc="Preparing results...")
         
@@ -211,7 +314,7 @@ def analyze_medical_image_gemini(
             "model": "Google Gemini-1.5-Pro Vision",
             "analysis_type": analysis_type,
             "clinical_data": clinical_data,
-            "focus_areas": focus_areas,
+            "focus_areas": focus_areas if focus_areas else "None specified",
             "analysis": response.text
         }
         
@@ -223,12 +326,22 @@ def analyze_medical_image_gemini(
         
     except Exception as e:
         error_msg = f"❌ Analysis failed: {str(e)}"
-        if "API_KEY" in str(e):
-            error_msg += "\n\n💡 Tip: Make sure your Google API key is valid and has access to Gemini API"
-        elif "quota" in str(e).lower():
-            error_msg += "\n\n💡 Tip: You may have exceeded your API quota. Check your Google Cloud Console"
-        elif "safety" in str(e).lower():
-            error_msg += "\n\n💡 Tip: The image may have been blocked by safety filters. Try a different medical image"
+        
+        # Provide specific error guidance
+        if "429" in str(e) or "quota" in str(e).lower():
+            error_msg += "\n\n💡 **Quota Issue:** You've exceeded your API limits. Please:\n"
+            error_msg += "• Check your Google Cloud Console billing\n"
+            error_msg += "• Wait a few minutes and try again\n"
+            error_msg += "• Consider upgrading your plan"
+            
+        elif "safety" in str(e).lower() or "blocked" in str(e).lower():
+            error_msg += "\n\n💡 **Safety Filter:** The image was blocked. Try:\n"
+            error_msg += "• A different medical image\n"
+            error_msg += "• Ensuring the image is clearly medical\n"
+            error_msg += "• Removing any potentially sensitive content"
+            
+        elif "401" in str(e) or "403" in str(e):
+            error_msg += "\n\n💡 **Authentication Error:** Check your API key"
         
         return error_msg, "", error_msg
 
@@ -260,6 +373,13 @@ def create_interface():
         color: #d93025;
         font-weight: 500;
     }
+    .quota-info {
+        background-color: #fff3cd;
+        padding: 10px;
+        border-radius: 5px;
+        margin: 10px 0;
+        border-left: 3px solid #ffc107;
+    }
     """
     
     with gr.Blocks(css=css, theme=gr.themes.Soft(), title="Gemini Medical AI") as interface:
@@ -273,23 +393,45 @@ def create_interface():
         </div>
         """)
         
+        # Check for existing API key on startup
+        initial_api_key = get_api_key_from_secrets()
+        
         # API Configuration Section
-        with gr.Accordion("🔑 API Configuration", open=True):
-            gr.Markdown("""
-            ### Google Gemini API Setup
-            You need a Google API key to use Gemini Vision Pro. Get one from [Google AI Studio](https://makersuite.google.com/app/apikey).
+        with gr.Accordion("🔑 API Configuration", open=not bool(initial_api_key)):
+            if initial_api_key:
+                gr.Markdown("""
+                ### ✅ API Key Found in Secrets
+                An API key was found in the environment/secrets. You can still override it below if needed.
+                """)
+            else:
+                gr.Markdown("""
+                ### 🔐 Google Gemini API Setup Required
+                You need a Google API key to use Gemini Vision Pro. 
+                
+                **For HuggingFace Spaces:** Add your API key as a secret named `GOOGLE_API_KEY`
+                **For local use:** Set the `GOOGLE_API_KEY` environment variable or enter it below
+                
+                🔗 Get your API key from: [Google AI Studio](https://makersuite.google.com/app/apikey)
+                """)
+            
+            gr.HTML("""
+            <div class="quota-info">
+                <strong>💰 Important:</strong> Make sure your Google API key has sufficient quota and billing is set up.
+                The 429 error indicates quota limits have been exceeded.
+            </div>
             """)
             
             api_key_input = gr.Textbox(
-                label="Google API Key",
+                label="Google API Key (Optional Override)",
                 type="password",
-                placeholder="Enter your Google API key here...",
-                info="Your API key is not stored and only used for this session"
+                placeholder="Enter your Google API key here to override secrets...",
+                info="Leave empty to use API key from secrets/environment",
+                value=""
             )
             
             status_display = gr.Textbox(
                 label="Connection Status",
-                value="⏳ Enter API key to connect",
+                value="⏳ Testing connection..." if initial_api_key else "⏳ Enter API key to connect",
                 interactive=False
             )
         
@@ -382,6 +524,30 @@ def create_interface():
                 download_content = gr.Textbox(visible=False)
         
         # Information sections
+        with gr.Accordion("🔧 Troubleshooting Common Issues", open=False):
+            gr.Markdown("""
+            ### 🚨 **Error 429 - Quota Exceeded:**
+            - **Check billing:** Ensure your Google Cloud project has billing enabled
+            - **API limits:** You may have hit free tier limits - consider upgrading
+            - **Rate limiting:** Wait a few minutes and try again
+            - **Multiple keys:** Try generating a new API key
+            
+            ### 🔐 **For HuggingFace Spaces Users:**
+            1. Go to your Space settings
+            2. Add a new secret: `GOOGLE_API_KEY` 
+            3. Paste your Google API key as the value
+            4. Restart your Space
+            
+            ### 📊 **Monitor Usage:**
+            - [Google AI Studio Usage](https://makersuite.google.com/)
+            - [Google Cloud Console](https://console.cloud.google.com/)
+            
+            ### 🔄 **If Still Having Issues:**
+            - Try a different API key
+            - Check if Gemini API is enabled in your project
+            - Verify your Google Cloud project settings
+            """)
+        
         with gr.Accordion("💡 About Gemini Vision Pro", open=False):
             gr.Markdown("""
             ### 🚀 **Advantages of Gemini Vision Pro:**
@@ -405,21 +571,6 @@ def create_interface():
             - Check [Google AI Pricing](https://ai.google.dev/pricing) for current rates
             """)
         
-        with gr.Accordion("📝 Tips for Better Results", open=False):
-            gr.Markdown("""
-            ### 🎯 **Optimization Tips:**
-            - **Provide clinical context**: Age, symptoms, and history significantly improve accuracy
-            - **Use specific focus areas**: "cardiac silhouette, pulmonary vessels" vs just "chest"
-            - **High-quality images**: Clear, well-lit, properly oriented images work best
-            - **Appropriate image size**: Gemini works well with various image sizes
-            - **Choose right analysis type**: Comprehensive for complex cases, Quick for screening
-            
-            ### 🔐 **API Key Security:**
-            - Your API key is only used for this session and not stored
-            - Consider using environment variables for production deployments
-            - Monitor your API usage in Google Cloud Console
-            """)
-        
         # Footer
         gr.HTML("""
         <div style="text-align: center; margin-top: 20px; padding: 15px; background-color: #fff3cd; border-radius: 8px;">
@@ -438,12 +589,22 @@ def create_interface():
                 return gr.File(value=filename, visible=True)
             return gr.File(visible=False)
         
-        def test_api_connection(api_key):
-            if not api_key:
-                return "⏳ Enter API key to connect"
-            success, status = setup_gemini(api_key)
+        def test_api_connection(api_key_override):
+            # Use override if provided, otherwise use secrets
+            test_key = api_key_override if api_key_override.strip() else None
+            success, status = setup_gemini(test_key)
             return status
         
+        # Test connection on startup if we have an API key
+        if initial_api_key:
+            def initial_connection_test():
+                return test_api_connection("")
+            
+            interface.load(
+                fn=initial_connection_test,
+                outputs=[status_display]
+            )
+        
         # API key testing
         api_key_input.change(
             fn=test_api_connection,
@@ -469,6 +630,15 @@ def create_interface():
 
 if __name__ == "__main__":
     print("🏥 Initializing Gemini Medical AI Analyzer...")
+    print("🔍 Checking for API keys in secrets/environment...")
+    
+    # Check for API key
+    api_key_found = get_api_key_from_secrets()
+    if api_key_found:
+        print("✅ API key found in environment/secrets")
+    else:
+        print("⚠️  No API key found - user will need to provide one")
+    
     print("🚀 No local model loading required - using Google Gemini Vision Pro API")
     
     # Create and launch interface