Update main.py

main.py

@@ -1,11 +1,12 @@
 """
-main.py — Pricelyst Shopping Advisor (Jessica Edition 2026 - Upgrade v2.2)
+main.py — Pricelyst Shopping Advisor (Jessica Edition 2026 - Upgrade v2.3)
 
-✅ Fixed: Vision SDK Crash (Part.from_text removed)
-✅ Fixed: "Clingy" Memory (Topic Reset Rule added)
-✅ "Analyst Engine": Enhanced Basket Math, Category Context, ZESA Logic
-✅ "Visual Engine": Lists, Products, & Meal-to-Recipe recognition
-✅ Memory Logic: Short-Term Sliding Window (Last 6 messages)
+✅ Fixed: Image Endpoint now auto-resolves prices (Simulated Intent).
+✅ Fixed: Vision SDK Crash (Part.from_text removed).
+✅ Fixed: "Clingy" Memory (Topic Reset Rule added).
+✅ "Analyst Engine": Enhanced Basket Math, Category Context, ZESA Logic.
+✅ "Visual Engine": Lists, Products, & Meal-to-Recipe recognition.
+✅ Memory Logic: Short-Term Sliding Window (Last 6 messages).
 
 ENV VARS:
 - GOOGLE_API_KEY=...
@@ -469,12 +470,11 @@ def gemini_analyze_image(image_b64: str, caption: str = "") -> Dict[str, Any]:
     }}
     """
     try:
-        # FIX: Remove types.Part.from_text wrapping. Pass string directly.
         image_bytes = base64.b64decode(image_b64)
         resp = _gemini_client.models.generate_content(
             model=GEMINI_MODEL,
             contents=[
-                PROMPT, # Pass text as string directly
+                PROMPT, 
                 types.Part.from_bytes(data=image_bytes, mime_type="image/jpeg")
             ],
             config=types.GenerateContentConfig(response_mime_type="application/json")
@@ -561,7 +561,7 @@ def health():
         "ok": True,
         "offers_indexed": len(df),
         "api_source": PRICE_API_BASE,
-        "persona": "Jessica v2.2"
+        "persona": "Jessica v2.3"
     })
 
 @app.post("/chat")
@@ -633,6 +633,7 @@ def chat():
 def analyze_image():
     """
     Handles Image -> List/Product/Meal -> Shopping Data
+    AUTO-RESOLVES intent to give prices immediately.
     """
     body = request.get_json(silent=True) or {}
     image_b64 = body.get("image_data") # Base64 string
@@ -654,15 +655,20 @@ def analyze_image():
         response_text = "I see the image, but I can't find any shopping items or meals in it. Try a receipt, a product, or a plate of food!"
         
     elif items:
-        # Run the Analyst Engine
+        # Run the Analyst Engine immediately
         analyst_data = calculate_basket_optimization(items)
         
-        # Craft a specific prompt for image results (No history needed here usually)
-        intent_sim = {"intent": "SHOPPING_BASKET"}
+        # 3. SIMULATE INTENT
+        # Instead of asking "Do you want to search?", we simulate a user asking "Where is [item] cheapest?"
+        # This forces the Persona to look at the analyst_data and reply with the solution.
+        simulated_user_msg = f"I have a photo of {', '.join(items)}. Which store has the cheapest price for this right now?"
+        intent_sim = {"intent": "STORE_DECISION"}
+        
         response_text = gemini_chat_response(
-            f"User uploaded image of {img_type}: {vision_result.get('description')}. Items found: {items}", 
+            simulated_user_msg, 
             intent_sim, 
-            analyst_data
+            analyst_data,
+            chat_history="" # No history needed for fresh lookup
         )
     
     return jsonify({