import json
import os
import typing
import warnings
from pathlib import Path

import fastapi

from source import model, api


class ModelManager:
    def __init__(self, application: api.Application, model_library: os.PathLike | str):
        self.application: api.Application = application
        self.model_library: Path = Path(model_library)

        # the model types
        self.model_types: dict[str, typing.Type[model.base.BaseModel]] = {}
        # the models
        self.models: dict[str, model.base.BaseModel] = {}

        # the currently loaded model
        # TODO(Faraphel): load more than one model at a time ? require a way more complex manager to handle memory issue
        self.current_loaded_model: typing.Optional[model.base.BaseModel] = None

        # lock to avoid concurrent inference and concurrent model loading and unloading
        self.inference_lock = asyncio.Lock()

        @self.application.get("/models")
        async def get_models() -> list[str]:
            """
            Get the list of models available
            :return: the list of models available
            """

            # list the models found
            return list(self.models.keys())

        @self.application.get("/models/{model_name}")
        async def get_model(model_name: str) -> dict:
            """
            Get information about a specific model
            :param model_name: the name of the model
            :return: the information about the corresponding model
            """

            # get the corresponding model
            model = self.models.get(model_name)
            if model is None:
                raise fastapi.HTTPException(status_code=404, detail="Model not found")

            # return the model information
            return model.get_information()


    def register_model_type(self, name: str, model_type: "typing.Type[model.base.BaseModel]"):
        self.model_types[name] = model_type

    def reload(self):
        # reset the model list
        for model in self.models.values():
            model.unload()
        self.models.clear()

        # load all the models in the library
        for model_path in self.model_library.iterdir():
            model_name: str = model_path.name
            model_configuration_path: Path = model_path / "config.json"

            # check if the configuration file exists
            if not model_configuration_path.exists():
                warnings.warn(f"Model {model_name!r} is missing a config.json file.")
                continue

            # load the configuration file
            model_configuration = json.loads(model_configuration_path.read_text())

            # get the model type for this model
            model_type_name: str = model_configuration.get("type")
            if model_type_name not in self.model_types:
                warnings.warn("Field 'type' missing from the model configuration file.")
                continue

            # get the class of this model type
            model_type = self.model_types.get(model_type_name)
            if model_type is None:
                warnings.warn(f"Model type {model_type_name!r} does not exists. Has it been registered ?")
                continue

            # load the model
            self.models[model_name] = model_type(self, model_configuration, model_path)