from fastapi import Query, Depends, HTTPException
from pydantic import BaseModel, model_validator
from typing import Dict, Any
import json, os, logging

from app.utils import (
    is_safe_path,
    _prompt_base_path,
    _prompt_path,
)


# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Prompt(BaseModel):
    name: str = ''
    prompt: str = ''
    params: Dict[str, Any] = {}
    source: str = ''

    @model_validator(mode="after")
    def prompt_validate(self) -> "Prompt":
        # If name is provided, validate it and prefer it over prompt
        if self.name:
            if is_safe_path(_prompt_base_path(), _prompt_path(self.name)):
                if os.path.isfile(_prompt_path(self.name)):
                    self.source = 'name'
                    return self
                else:
                    logger.error(f"The specified prompt file at '{_prompt_path(self.name)}' was not found.")
                    raise HTTPException(status_code=400, detail=f"The specified prompt file at '{_prompt_path(self.name)}' was not found.")
            else:
                logger.error("Unsafe path access detected; Got path: " + _prompt_path(self.name))
                raise HTTPException(status_code=400, detail="Unsafe path access detected; Got path: " + _prompt_path(self.name))
        # If prompt is provided (and name is not valid), use prompt
        if self.prompt:
            self.source = 'prompt'
            return self
        # If neither is valid, raise error
        logger.error("At least one parameter is required: 'prompt_name' or 'prompt_prompt'")
        raise HTTPException(status_code=400, detail="At least one parameter is required: 'prompt_name' or 'prompt_prompt'")

class RequestModel(BaseModel):
    prompt: Prompt
    # AI_model: AIModel    # AI_model.name, AI_model.params

class QueryParams(BaseModel):
    prompt_name: str = Query('')
    prompt_prompt: str = Query('')
    prompt_params: str = Query('{}')

def parse_query(query: QueryParams = Depends()) -> RequestModel:
    #  Transform prompt_params (JSON string -> dict)
    if query.prompt_params:
        try:
            prompt_params = json.loads(query.prompt_params)
        except Exception as e:
            logger.exception(f"Invalid JSON for prompt_params: {e}")
            raise HTTPException(status_code=400, detail=f"Invalid JSON for prompt_params: {e}")
    # Make Prompt model
    prompt = Prompt(
        name = query.prompt_name,
        prompt=query.prompt_prompt,
        params=prompt_params
    )
    logger.info(f"RequestModel has been created and verified")
    return RequestModel(prompt=prompt)