import logging

import helpers.datastore as datastore

logger = logging.getLogger(__name__)


def validate_answer(
    question_id: int, answer: str, answer_type: str | int | list
) -> str:
    """Validate the user's answer against an expected answer type.

        question_id (int): The identifier of the question being validated
        answer (str): The user's provided answer to validate
        answer_type (type): The expected python type that the answer should match (e.g. str, int, list)

        str: Returns "Answer is valid" if answer matches expected type, raises ValueError otherwise

    Raises:
        ValueError: If the answer's type does not match the expected answer_type

    Example:
        >>> validate_answer(1, "42", str)
        True
        >>> validate_answer(1, 42, str)
        ValueError: Invalid answer type
    """

    logging.info(
        {
            "question_id": question_id,
            "answer": answer,
            "answer_type": answer_type,
        }
    )
    if type(answer) is answer_type:
        raise ValueError("Invalid answer type")

    datastore.DATA_STORE["answers"].append(
        {"question_id": question_id, "answer": answer}
    )

    return "Answer is valid"


validate_answer_tool = {
    "name": "validate_answer",
    "description": "Validate the user's answer against an expected answer type",
    "parameters": {
        "type": "OBJECT",
        "properties": {
            "question_id": {
                "type": "INTEGER",
                "description": "The identifier of the question being validated",
            },
            "answer": {
                "type": "STRING",
                "description": "The user's provided answer to validate",
            },
            "answer_type": {
                "type": "STRING",
                "description": "The expected python type that the answer should match (e.g. str, int, list)",
            },
        },
        "required": ["question_id", "answer", "answer_type"],
    },
}


def store_input(role: str, input: str) -> str:
    """Store conversation input in a JSON file.

    Args:
        role (str): The role of the speaker (user or assistant)
        input (str): The text input to store

    Returns:
        str: Confirmation message
    """
    print(datastore.DATA_STORE)
    conversation = datastore.DATA_STORE.get("conversation")
    if conversation is None:
        datastore.DATA_STORE["conversation"] = [{"role": role, "input": input}]
    else:
        datastore.DATA_STORE["conversation"].append({"role": role, "input": input})

    return "Input stored successfully"


store_input_tool = {
    "name": "store_input",
    "description": "Store user input in conversation history",
    "parameters": {
        "type": "OBJECT",
        "properties": {
            "role": {
                "type": "STRING",
                "description": "The role of the speaker (user or assistant)",
            },
            "input": {"type": "STRING", "description": "The text input to store"},
        },
    },
}