Switch to Gemini 2.0 Flash Exp for improved availability

agents/visual_analyst.py

@@ -11,25 +11,25 @@ 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)
         
         print("🔍 Checking available Gemini models...")
         try:
-            # Filter for models that support content generation
             my_models = [m.name for m in genai.list_models() if 'generateContent' in m.supported_generation_methods]
             print(f"📋 Available Models: {my_models}")
             
-            # UPDATED PRIORITY: Force 'Pro' model to bypass Flash 404s
+            # UPDATED PRIORITY: GEMINI 2.0 FIRST
             preferred_order = [
-                'models/gemini-1.5-pro',      # <--- The Heavy Hitter (Smarter, diff backend)
+                'models/gemini-2.0-flash-exp',  # <--- Newest & Smartest (Available in logs)
+                'models/gemini-1.5-pro',
                 'models/gemini-1.5-pro-001',
                 'models/gemini-1.5-flash',
                 'models/gemini-1.5-flash-001',
                 'models/gemini-pro-vision'
             ]
             
-            selected_model = "models/gemini-1.5-pro" # Default
+            selected_model = "models/gemini-2.0-flash-exp" # Default to the new one
             
             for model_name in preferred_order:
                 if model_name in my_models:
@@ -40,8 +40,8 @@ class VisualAnalyst:
             self.model = genai.GenerativeModel(selected_model)
             
         except Exception as e:
-            print(f"⚠️ Model list failed ({e}), defaulting to gemini-1.5-pro")
-            self.model = genai.GenerativeModel('gemini-1.5-pro')
+            print(f"⚠️ Model list failed ({e}), defaulting to gemini-2.0-flash-exp")
+            self.model = genai.GenerativeModel('models/gemini-2.0-flash-exp')
 
     async def analyze_image(self, image_path: str):
         # Adaptation: Read file path to bytes, as main.py passes a path
@@ -55,13 +55,11 @@ class VisualAnalyst:
                 "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:
-            # Note: Pro model is sometimes stricter with image formats, but 'parts' usually works.
             # Adaptation: Run in thread to allow async await
             response = await asyncio.to_thread(
                 self.model.generate_content,
@@ -73,7 +71,7 @@ class VisualAnalyst:
             
             text = response.text
             if text.startswith('```json'): text = text[7:]
-            if text.startswith('```'): text = text[:-3]
+            if text.endswith('```'): text = text[:-3]
             
             return json.loads(text.strip())
         except Exception as e:

requirements.txt

@@ -8,6 +8,6 @@ langchain-groq
 pinecone>=3.0.0
 pydantic
 python-dotenv
-google-generativeai>=0.7.2
+google-generativeai>=0.8.3
 groq
 Pillow