mirror of
https://git.isriupjv.fr/ISRI/ai-server
synced 2025-04-24 18:18:11 +02:00
faraphel
7bd84c8570
Models are now loaded in separate endpoints for the inputs to be easier to recognise
88 lines
3.1 KiB
Python
88 lines
3.1 KiB
Python
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
|
|
|
|
@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)
|