import json
from APIs.aichat import generate

DISH_SAFETY_SCHEMA = {
    "type": "object",
    "properties": {
        "is_safe": {
            "type": "boolean",
            "description": "True if no microwave hazards (metal, foil, sealed packaging) are present."
        },
        "warning_message": {
            "type": "string",
            "description": "Explanation of any hazard found, or an empty string if safe."
        },
        "detected_hazards": {
            "type": "array",
            "items": {
                "type": "string"
            },
            "description": "List of specific hazard items detected."
        }
    },
    "required": ["is_safe", "warning_message", "detected_hazards"]
}

def check_dish_safety(image_path: str) -> dict:
    prompt = (
        "Analyze this top-down photo of a dish prepared for microwave cooking. "
        "Inspect the area for metal utensils, aluminum foil, metallic dish patterns, or unvented plastic wraps."
    )

    # Pass the schema directly to the generation call
    response_raw = generate(
        prompt=prompt,
        images=[image_path],
        output_format=DISH_SAFETY_SCHEMA  # Passed as Ollama's `format` parameter
    )
    print(f"[Debug] Raw response from AI generator: {response_raw}")

    # 1. If response_raw is already a dict, return it directly
    if isinstance(response_raw, dict):
        return response_raw

    # 2. If it's a string or bytes, parse it
    if isinstance(response_raw, (str, bytes, bytearray)):
        return json.loads(response_raw)

    raise ValueError(f"Unexpected response type from AI generator: {type(response_raw)}")