Better prompt

cloud/safety_checker.py

@@ -4,45 +4,44 @@ from APIs.aichat import generate
 import shared.config as config
 
 
-# Output schema as a Pydantic model
+# 1. Output schema with strict anti-hallucination descriptions
 class DishSafetyResult(BaseModel):
     visible_objects: list[str] = Field(
-        description="List all distinct physical objects visible in or around the dish (e.g., bowl, plastic tray, liquid, spoon, cover)."
+        description="Objective list of physical items visible (e.g., 'black plastic tray', 'stew', 'plastic fork'). Do NOT categorize them as safe or hazards here."
     )
     material_analysis: str = Field(
-        description="Analyze the physical material of each visible object (e.g., ceramic, polypropylene plastic, stainless steel, aluminum foil)."
+        description="Describe physical materials based strictly on visual cues. Note: Smooth, rigid black plastic meal trays are Polypropylene/CPET plastic (safe), NOT foam/styrofoam."
     )
     detected_hazards: list[str] = Field(
         description=(
-            "List ONLY explicit, high-risk microwave hazards: metal items, cutlery, aluminum foil, "
+            "List ONLY explicit physical hazards: metal utensils/cutlery, aluminum foil/wrappers, "
-            "metallic trim/gilding, Styrofoam (expanded polystyrene), or tightly sealed/unvented foil lids. "
+            "metallic foil trim, spongy white foam/styrofoam containers, or airtight unvented plastic wrap. "
-            "Do NOT include standard plastic containers, TV dinner trays, polypropylene (#5), or Tupperware as hazards. Empty if none."
+            "Rigid black or clear plastic meal trays are NOT hazards. Empty if none."
         )
     )
     is_safe: bool = Field(
-        description="Must be set to True if detected_hazards is empty. Otherwise False."
+        description="Set to True if detected_hazards is completely empty. Otherwise set to False."
     )
     warning_message: str = Field(
-        description="One short sentence explaining the hazard if detected_hazards is not empty, otherwise an empty string."
+        description="One brief sentence warning if detected_hazards is non-empty, otherwise an empty string."
     )
 
 
 def check_dish_safety(image_path: str) -> dict:
     prompt = (
-        "Examine this photo of a meal intended for microwave heating.\n\n"
+        "Analyze this food image for critical microwave safety hazards.\n\n"
-        "Inspect all objects to determine if any CRITICAL microwave hazards exist.\n\n"
+        "MATERIAL IDENTIFICATION RULES:\n"
-        "STRICT HAZARDS TO DETECT:\n"
+        "- Black plastic meal trays / TV dinner containers = Smooth, rigid Polypropylene (PP) or CPET plastic. These are STANDARD MICROWAVE MEAL TRAYS and are SAFE.\n"
-        "- Metal utensils, cutlery, or metal objects.\n"
+        "- Styrofoam / EPS = White or light-colored spongy, cellular foam. (Do NOT misclassify smooth black plastic as styrofoam!).\n\n"
-        "- Aluminum foil, metallic packaging, or decorative metallic trim.\n"
+        "STRICT HAZARDS TO LOOK FOR:\n"
-        "- Expanded Polystyrene / Styrofoam containers.\n"
+        "1. Metal objects (metal forks, spoons, knives, metal bowls).\n"
-        "- Completely sealed non-vented foil or plastic film lids (explosion risk).\n\n"
+        "2. Aluminum foil or foil packaging.\n"
-        "SAFE MATERIALS (DO NOT FLAG AS HAZARDS):\n"
+        "3. Metallic gold/silver decorative trim on ceramic dishes.\n"
-        "- Standard microwavable food containers, plastic meal prep trays, black plastic TV dinner trays, and polypropylene (PP / #5) plastics.\n"
+        "4. White spongy foam / Styrofoam packaging.\n"
-        "- Glass, ceramic, or paper containers.\n\n"
+        "5. Tightly sealed, unvented plastic film or foil lids.\n\n"
-        "Only mark is_safe as False if a clear, high-risk hazard from the strictly dangerous list above is present."
+        "If the meal is simply inside a standard black plastic tray or ceramic/glass dish without any metal/foil/foam present, flag it as SAFE (is_safe = True)."
     )
 
-    # 2. Pass the Pydantic class directly to generate()
     response_raw = generate(
         prompt=prompt,
         images=[image_path],
@@ -51,14 +50,11 @@ def check_dish_safety(image_path: str) -> dict:
     )
     print(f"[Debug] Raw response from AI generator: {response_raw}")
 
-    # 3. Handle response parsing
     if isinstance(response_raw, str):
-        # Parse and validate the JSON string into the Pydantic model, then return as a dict
         try:
             validated_result = DishSafetyResult.model_validate_json(response_raw)
             return validated_result.model_dump()
         except Exception:
-            # Fallback to standard json.loads if raw parsing is needed
             return json.loads(response_raw)
 
     if isinstance(response_raw, DishSafetyResult):