:(

cloud/safety_checker.py

@@ -4,17 +4,14 @@ from APIs.aichat import generate
 import shared.config as config
 
 class DishSafetyResult(BaseModel):
-    step_1_visible_items: list[str] = Field(
-        description="List ONLY 2-3 broad visible items (e.g., ['ceramic bowl', 'brown stew']). Do NOT guess objects if blurry."
-    )
-    step_2_has_metal_or_cutlery: bool = Field(
-        description="Is a metal spoon, fork, knife, or foil clearly visible? True ONLY if distinct metal is seen, otherwise False."
-    )
-    detected_hazards: list[str] = Field(
-        description="List ONLY physical metal items (e.g. ['metal spoon']). MUST be an empty list [] if step_2 is False."
+    image_description: str = Field(
+        description="Describe the food and container in 1 simple sentence."
     )
     is_safe: bool = Field(
-        description="MUST be True if step_2 is False. Set to False ONLY if metal cutlery/foil is present."
+        description="Set to True if safe. Set to False ONLY if a physical metallic utensil or aluminum foil is clearly visible."
+    )
+    detected_hazards: list[str] = Field(
+        description="List any metallic objects found (e.g. ['metal utensil']). If is_safe is True, this MUST be empty []."
     )
     warning_message: str = Field(
         description="Short warning if unsafe, otherwise empty string ''."
@@ -22,12 +19,11 @@ class DishSafetyResult(BaseModel):
 
 def check_dish_safety(image_path: str) -> dict:
     prompt = (
-        "You are a strict microwave safety vision inspector analyzing a top-down frame.\n\n"
-        "RULES:\n"
-        "1. First, list basic items in `step_1_visible_items`.\n"
-        "2. Examine the dish for shiny metallic cutlery, forks, spoons, or aluminum foil.\n"
-        "3. Set `step_2_has_metal_or_cutlery` to True ONLY if clear metallic cutlery is visible.\n"
-        "4. If the image is blurry and no metal is clearly identified, assume NO metal is present (step_2 = False, is_safe = True)."
+        "Analyze this top-down photo inside a microwave.\n\n"
+        "TASK:\n"
+        "1. Describe what is visible in `image_description`.\n"
+        "2. If the container holds strictly food with no physical metal objects, set `is_safe` to True and `detected_hazards` to [].\n"
+        "3. Mark `is_safe` as False ONLY if an actual metal object or metallic handle is present in the container."
     )
 
     response_raw = generate(
@@ -36,11 +32,10 @@ def check_dish_safety(image_path: str) -> dict:
         output_format=DishSafetyResult,
         should_think=False,
     )
-    
+
     if config.DEBUG_MESSAGES:
         print(f"[Debug] Raw response from AI generator: {response_raw}")
 
-    # Handling response mapping...
     if isinstance(response_raw, str):
         try:
             validated_result = DishSafetyResult.model_validate_json(response_raw)