import json
from pydantic import BaseModel, Field
from APIs.aichat import generate
import shared.config as config


class DishSafetyResult(BaseModel):
    visible_objects: list[str] = Field(
        description="List physical container items and utensils visible in the image."
    )
    material_analysis: str = Field(
        description="Brief description of container material (e.g., standard plastic tray, glass bowl)."
    )
    detected_hazards: list[str] = Field(
        description="List of visually confirmed metal or foil hazards. MUST be empty [] if no metal or foil is present."
    )
    is_safe: bool = Field(
        description="Set to True if detected_hazards is empty. Set to False ONLY if metal or aluminum foil is present."
    )
    warning_message: str = Field(
        description="Short warning if is_safe is False, otherwise an empty string."
    )


def check_dish_safety(image_path: str) -> dict:
    prompt = (
        "Analyze this food image for microwave safety.\n\n"
        "DEFAULT ASSUMPTION:\n"
        "- Assume the dish is SAFE (is_safe = True, detected_hazards = []).\n"
        "- Standard food (meat, vegetables, potatoes) and standard containers (black plastic meal trays, plastic bowls, ceramic, glass) are 100% SAFE for microwaves.\n\n"
        "STRICT HAZARD RULE:\n"
        "- 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"
        "- Do NOT invent or hallucinate hazards. If you do not see shiny metal or aluminum foil, detected_hazards MUST be an empty list []."
    )

    response_raw = generate(
        prompt=prompt,
        images=[image_path],
        output_format=DishSafetyResult,
        should_think=False,
    )
    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)}")