51 lines
2.0 KiB
Python
51 lines
2.0 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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class DishSafetyResult(BaseModel):
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visible_objects: list[str] = Field(
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description="List EVERY distinct item visible in the frame (e.g., ['ceramic bowl', 'rice', 'metal spoon handle', 'stew'])."
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)
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is_safe: bool = Field(
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description="Is the microwave dish safe to microwave? True if safe, False if unsafe."
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)
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detected_hazards: list[str] = Field(
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description="List ONLY physical hazard items found. Empty list [] if safe."
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)
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warning_message: str = Field(
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description="Warning statement if unsafe, otherwise 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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"You are an expert microwave safety quality inspector analyzing a top-down camera frame.\n\n"
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"INSPECTION STEPS:\n"
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"Describe what you see in the image, identify any potential hazards, and determine if the dish is safe to microwave.\n"
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"Alert only if the cooking of the dish will cause damage to the microwave or the dish itself.\n"
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"NOTES:\n"
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"The camera focus is wrongly setup, so the image may be blurry. Please do not take the blurriness into account when analyzing the dish.\n"
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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)}") |