57 lines
2.3 KiB
Python
57 lines
2.3 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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class DishSafetyResult(BaseModel):
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visible_objects: list[str] = Field(
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description="List physical container items and utensils visible in the image."
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)
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material_analysis: str = Field(
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description="Brief description of container material (e.g., standard plastic tray, glass bowl)."
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)
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detected_hazards: list[str] = Field(
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description="List of visually confirmed metal or foil hazards. MUST be empty [] if no metal or foil is present."
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)
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is_safe: bool = Field(
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description="Set to True if detected_hazards is empty. Set to False ONLY if metal or aluminum foil is present."
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)
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warning_message: str = Field(
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description="Short warning if is_safe is False, 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 microwave safety.\n\n"
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"DEFAULT ASSUMPTION:\n"
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"- Assume the dish is SAFE (is_safe = True, detected_hazards = []).\n"
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"- Standard food (meat, vegetables, potatoes) and standard containers (black plastic meal trays, plastic bowls, ceramic, glass) are 100% SAFE for microwaves.\n\n"
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"STRICT HAZARD RULE:\n"
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"- Flag as UNSAFE ONLY if you can literally see actual metal cutlery (metal spoon/fork/knife), aluminum foil packaging, or metal foil trim in the image.\n"
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"- Do NOT invent or hallucinate hazards. If you do not see shiny metal or aluminum foil, detected_hazards MUST be an empty list []."
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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)}") |