Files
Smartwave/cloud/safety_checker.py
T
Ninluc eb80d13300
Build, push image, and notify Watchtower / build-image (push) Successful in 39s
Build, push image, and notify Watchtower / notify (push) Successful in 12s
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2026-08-23 18:43:16 +02:00

52 lines
1.9 KiB
Python

import json
from pydantic import BaseModel, Field
from APIs.aichat import generate
import shared.config as config
class DishSafetyResult(BaseModel):
image_description: str = Field(
description="Describe the food and container in 1 simple sentence."
)
is_safe: bool = Field(
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 ''."
)
def check_dish_safety(image_path: str) -> dict:
prompt = (
"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(
prompt=prompt,
images=[image_path],
output_format=DishSafetyResult,
should_think=False,
)
if config.DEBUG_MESSAGES:
print(f"[Debug] Raw response from AI generator: {response_raw}")
if isinstance(response_raw, str):
try:
validated_result = DishSafetyResult.model_validate_json(response_raw)
return validated_result.model_dump()
except Exception:
return json.loads(response_raw)
if isinstance(response_raw, DishSafetyResult):
return response_raw.model_dump()
if isinstance(response_raw, dict):
return response_raw
raise ValueError(f"Unexpected response type from AI generator: {type(response_raw)}")