66 lines
3.0 KiB
Python
66 lines
3.0 KiB
Python
import json
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from pydantic import BaseModel, Field
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from APIs.aichat import generate
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import shared.config as config
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# 1. Output schema with strict anti-hallucination descriptions
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class DishSafetyResult(BaseModel):
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visible_objects: list[str] = Field(
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description="Objective list of physical items visible (e.g., 'black plastic tray', 'stew', 'plastic fork'). Do NOT categorize them as safe or hazards here."
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)
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material_analysis: str = Field(
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description="Describe physical materials based strictly on visual cues. Note: Smooth, rigid black plastic meal trays are Polypropylene/CPET plastic (safe), NOT foam/styrofoam."
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)
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detected_hazards: list[str] = Field(
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description=(
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"List ONLY explicit physical hazards: metal utensils/cutlery, aluminum foil/wrappers, "
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"metallic foil trim, spongy white foam/styrofoam containers, or airtight unvented plastic wrap. "
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"Rigid black or clear plastic meal trays are NOT hazards. Empty if none."
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)
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)
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is_safe: bool = Field(
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description="Set to True if detected_hazards is completely empty. Otherwise set to False."
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)
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warning_message: str = Field(
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description="One brief sentence warning if detected_hazards is non-empty, otherwise an empty string."
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)
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def check_dish_safety(image_path: str) -> dict:
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prompt = (
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"Analyze this food image for critical microwave safety hazards.\n\n"
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"MATERIAL IDENTIFICATION RULES:\n"
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"- Black plastic meal trays / TV dinner containers = Smooth, rigid Polypropylene (PP) or CPET plastic. These are STANDARD MICROWAVE MEAL TRAYS and are SAFE.\n"
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"- Styrofoam / EPS = White or light-colored spongy, cellular foam. (Do NOT misclassify smooth black plastic as styrofoam!).\n\n"
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"STRICT HAZARDS TO LOOK FOR:\n"
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"1. Metal objects (metal forks, spoons, knives, metal bowls).\n"
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"2. Aluminum foil or foil packaging.\n"
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"3. Metallic gold/silver decorative trim on ceramic dishes.\n"
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"4. White spongy foam / Styrofoam packaging.\n"
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"5. Tightly sealed, unvented plastic film or foil lids.\n\n"
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"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)."
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)
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response_raw = generate(
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prompt=prompt,
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images=[image_path],
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output_format=DishSafetyResult,
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should_think=False,
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)
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print(f"[Debug] Raw response from AI generator: {response_raw}")
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if isinstance(response_raw, str):
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try:
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validated_result = DishSafetyResult.model_validate_json(response_raw)
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return validated_result.model_dump()
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except Exception:
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return json.loads(response_raw)
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if isinstance(response_raw, DishSafetyResult):
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return response_raw.model_dump()
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if isinstance(response_raw, dict):
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return response_raw
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raise ValueError(f"Unexpected response type from AI generator: {type(response_raw)}") |