Implement smart model selection for Visual Analyst

agents/visual_analyst.py

@@ -11,30 +11,57 @@ class VisualAnalyst:
         self.api_key = os.getenv("GEMINI_API_KEY")
         if not self.api_key:
             raise ValueError("GEMINI_API_KEY not found")
+
         genai.configure(api_key=self.api_key)
-        # UPDATED: Using specific version ID to avoid 404s
-        self.model = genai.GenerativeModel('gemini-1.5-flash-001')
+        
+        # --- SMART MODEL SELECTION ---
+        print("🔍 Checking available Gemini models for this key...")
+        try:
+            my_models = [m.name for m in genai.list_models() if 'generateContent' in m.supported_generation_methods]
+            print(f"📋 Available Models: {my_models}")
+            
+            # Priority list (Newest -> Oldest)
+            preferred_order = [
+                'models/gemini-1.5-flash',
+                'models/gemini-1.5-flash-001',
+                'models/gemini-1.5-pro',
+                'models/gemini-1.5-pro-001',
+                'models/gemini-pro-vision'  # Legacy fallback
+            ]
+            
+            selected_model = "models/gemini-1.5-flash" # Default
+            
+            for model_name in preferred_order:
+                if model_name in my_models:
+                    selected_model = model_name
+                    break
+            
+            print(f"✅ Selected Vision Model: {selected_model}")
+            self.model = genai.GenerativeModel(selected_model)
+            
+        except Exception as e:
+            print(f"⚠️ Model list failed ({e}), defaulting to gemini-1.5-flash")
+            self.model = genai.GenerativeModel('gemini-1.5-flash')
 
     async def analyze_image(self, image_path: str):
-        # Read file as bytes to match the user's logic requirements
+        # Adaptation: Read file path to bytes, as main.py passes a path
         try:
             with open(image_path, "rb") as f:
                 image_bytes = f.read()
         except Exception as e:
-             return {
-                "main_color": "Error",
-                "product_type": "File Read Error",
-                "design_style": "Error",
-                "visual_features": [f"Could not read file: {str(e)}"]
+            print(f"❌ File Read Error: {e}")
+            return {
+                "main_color": "Unknown",
+                "visual_features": [f"Error reading file: {str(e)}"]
             }
 
+        # Prompt for analysis
         prompt = (
             "Analyze this product image for an e-commerce listing. "
             "Return a JSON object with keys: main_color, product_type, design_style, visual_features."
         )
-        
         try:
-            # Run blocking call in thread
+            # Adaptation: Run in thread to allow async await
             response = await asyncio.to_thread(
                 self.model.generate_content,
                 [
@@ -44,12 +71,12 @@ class VisualAnalyst:
             )
             
             text = response.text
-            # Clean markdown
             if text.startswith('```json'): text = text[7:]
-            if text.endswith('```'): text = text[:-3]
+            if text.startswith('```'): text = text[:-3]
             
             return json.loads(text.strip())
         except Exception as e:
+            print(f"❌ Analysis Failed: {e}")
             return {
                 "main_color": "Unknown",
                 "visual_features": [f"Error: {str(e)}"]