InvokeAI/invokeai/app/api/routers/models.py

413 lines
18 KiB
Python

# Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654), 2023 Kent Keirsey (https://github.com/hipsterusername), 2023 Lincoln D. Stein
import pathlib
from typing import Literal, List, Optional, Union
from fastapi import Body, Path, Query, Response
from fastapi.routing import APIRouter
from pydantic import BaseModel, parse_obj_as
from starlette.exceptions import HTTPException
from invokeai.backend import BaseModelType, ModelType
from invokeai.backend.model_management.models import (
OPENAPI_MODEL_CONFIGS,
SchedulerPredictionType,
ModelNotFoundException,
)
from invokeai.backend.model_management import MergeInterpolationMethod
from ..dependencies import ApiDependencies
models_router = APIRouter(prefix="/v1/models", tags=["models"])
UpdateModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
ImportModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
ConvertModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
MergeModelResponse = Union[tuple(OPENAPI_MODEL_CONFIGS)]
ImportModelAttributes = Union[tuple(OPENAPI_MODEL_CONFIGS)]
class ModelsList(BaseModel):
models: list[Union[tuple(OPENAPI_MODEL_CONFIGS)]]
@models_router.get(
"/",
operation_id="list_models",
responses={200: {"model": ModelsList }},
)
async def list_models(
base_model: Optional[BaseModelType] = Query(default=None, description="Base model"),
model_type: Optional[ModelType] = Query(default=None, description="The type of model to get"),
) -> ModelsList:
"""Gets a list of models"""
models_raw = ApiDependencies.invoker.services.model_manager.list_models(base_model, model_type)
models = parse_obj_as(ModelsList, { "models": models_raw })
return models
@models_router.patch(
"/{base_model}/{model_type}/{model_name}",
operation_id="update_model",
responses={200: {"description" : "The model was updated successfully"},
400: {"description" : "Bad request"},
404: {"description" : "The model could not be found"},
409: {"description" : "There is already a model corresponding to the new name"},
},
status_code = 200,
response_model = UpdateModelResponse,
)
async def update_model(
base_model: BaseModelType = Path(description="Base model"),
model_type: ModelType = Path(description="The type of model"),
model_name: str = Path(description="model name"),
info: Union[tuple(OPENAPI_MODEL_CONFIGS)] = Body(description="Model configuration"),
) -> UpdateModelResponse:
""" Update model contents with a new config. If the model name or base fields are changed, then the model is renamed. """
logger = ApiDependencies.invoker.services.logger
try:
previous_info = ApiDependencies.invoker.services.model_manager.list_model(
model_name=model_name,
base_model=base_model,
model_type=model_type,
)
# rename operation requested
if info.model_name != model_name or info.base_model != base_model:
ApiDependencies.invoker.services.model_manager.rename_model(
base_model = base_model,
model_type = model_type,
model_name = model_name,
new_name = info.model_name,
new_base = info.base_model,
)
logger.info(f'Successfully renamed {base_model}/{model_name}=>{info.base_model}/{info.model_name}')
# update information to support an update of attributes
model_name = info.model_name
base_model = info.base_model
new_info = ApiDependencies.invoker.services.model_manager.list_model(
model_name=model_name,
base_model=base_model,
model_type=model_type,
)
if new_info.get('path') != previous_info.get('path'): # model manager moved model path during rename - don't overwrite it
info.path = new_info.get('path')
ApiDependencies.invoker.services.model_manager.update_model(
model_name=model_name,
base_model=base_model,
model_type=model_type,
model_attributes=info.dict()
)
model_raw = ApiDependencies.invoker.services.model_manager.list_model(
model_name=model_name,
base_model=base_model,
model_type=model_type,
)
model_response = parse_obj_as(UpdateModelResponse, model_raw)
except ModelNotFoundException as e:
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
logger.error(str(e))
raise HTTPException(status_code=409, detail=str(e))
except Exception as e:
logger.error(str(e))
raise HTTPException(status_code=400, detail=str(e))
return model_response
@models_router.post(
"/import",
operation_id="import_model",
responses= {
201: {"description" : "The model imported successfully"},
404: {"description" : "The model could not be found"},
424: {"description" : "The model appeared to import successfully, but could not be found in the model manager"},
409: {"description" : "There is already a model corresponding to this path or repo_id"},
},
status_code=201,
response_model=ImportModelResponse
)
async def import_model(
location: str = Body(description="A model path, repo_id or URL to import"),
prediction_type: Optional[Literal['v_prediction','epsilon','sample']] = \
Body(description='Prediction type for SDv2 checkpoint files', default="v_prediction"),
) -> ImportModelResponse:
""" Add a model using its local path, repo_id, or remote URL. Model characteristics will be probed and configured automatically """
items_to_import = {location}
prediction_types = { x.value: x for x in SchedulerPredictionType }
logger = ApiDependencies.invoker.services.logger
try:
installed_models = ApiDependencies.invoker.services.model_manager.heuristic_import(
items_to_import = items_to_import,
prediction_type_helper = lambda x: prediction_types.get(prediction_type)
)
info = installed_models.get(location)
if not info:
logger.error("Import failed")
raise HTTPException(status_code=424)
logger.info(f'Successfully imported {location}, got {info}')
model_raw = ApiDependencies.invoker.services.model_manager.list_model(
model_name=info.name,
base_model=info.base_model,
model_type=info.model_type
)
return parse_obj_as(ImportModelResponse, model_raw)
except ModelNotFoundException as e:
logger.error(str(e))
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
logger.error(str(e))
raise HTTPException(status_code=409, detail=str(e))
@models_router.post(
"/add",
operation_id="add_model",
responses= {
201: {"description" : "The model added successfully"},
404: {"description" : "The model could not be found"},
424: {"description" : "The model appeared to add successfully, but could not be found in the model manager"},
409: {"description" : "There is already a model corresponding to this path or repo_id"},
},
status_code=201,
response_model=ImportModelResponse
)
async def add_model(
info: Union[tuple(OPENAPI_MODEL_CONFIGS)] = Body(description="Model configuration"),
) -> ImportModelResponse:
""" Add a model using the configuration information appropriate for its type. Only local models can be added by path"""
logger = ApiDependencies.invoker.services.logger
try:
ApiDependencies.invoker.services.model_manager.add_model(
info.model_name,
info.base_model,
info.model_type,
model_attributes = info.dict()
)
logger.info(f'Successfully added {info.model_name}')
model_raw = ApiDependencies.invoker.services.model_manager.list_model(
model_name=info.model_name,
base_model=info.base_model,
model_type=info.model_type
)
return parse_obj_as(ImportModelResponse, model_raw)
except ModelNotFoundException as e:
logger.error(str(e))
raise HTTPException(status_code=404, detail=str(e))
except ValueError as e:
logger.error(str(e))
raise HTTPException(status_code=409, detail=str(e))
@models_router.delete(
"/{base_model}/{model_type}/{model_name}",
operation_id="del_model",
responses={
204: { "description": "Model deleted successfully" },
404: { "description": "Model not found" }
},
status_code = 204,
response_model = None,
)
async def delete_model(
base_model: BaseModelType = Path(description="Base model"),
model_type: ModelType = Path(description="The type of model"),
model_name: str = Path(description="model name"),
) -> Response:
"""Delete Model"""
logger = ApiDependencies.invoker.services.logger
try:
ApiDependencies.invoker.services.model_manager.del_model(model_name,
base_model = base_model,
model_type = model_type
)
logger.info(f"Deleted model: {model_name}")
return Response(status_code=204)
except ModelNotFoundException as e:
logger.error(str(e))
raise HTTPException(status_code=404, detail=str(e))
@models_router.put(
"/convert/{base_model}/{model_type}/{model_name}",
operation_id="convert_model",
responses={
200: { "description": "Model converted successfully" },
400: {"description" : "Bad request" },
404: { "description": "Model not found" },
},
status_code = 200,
response_model = ConvertModelResponse,
)
async def convert_model(
base_model: BaseModelType = Path(description="Base model"),
model_type: ModelType = Path(description="The type of model"),
model_name: str = Path(description="model name"),
convert_dest_directory: Optional[str] = Query(default=None, description="Save the converted model to the designated directory"),
) -> ConvertModelResponse:
"""Convert a checkpoint model into a diffusers model, optionally saving to the indicated destination directory, or `models` if none."""
logger = ApiDependencies.invoker.services.logger
try:
logger.info(f"Converting model: {model_name}")
dest = pathlib.Path(convert_dest_directory) if convert_dest_directory else None
ApiDependencies.invoker.services.model_manager.convert_model(model_name,
base_model = base_model,
model_type = model_type,
convert_dest_directory = dest,
)
model_raw = ApiDependencies.invoker.services.model_manager.list_model(model_name,
base_model = base_model,
model_type = model_type)
response = parse_obj_as(ConvertModelResponse, model_raw)
except ModelNotFoundException as e:
raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found: {str(e)}")
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
return response
@models_router.get(
"/search",
operation_id="search_for_models",
responses={
200: { "description": "Directory searched successfully" },
404: { "description": "Invalid directory path" },
},
status_code = 200,
response_model = List[pathlib.Path]
)
async def search_for_models(
search_path: pathlib.Path = Query(description="Directory path to search for models")
)->List[pathlib.Path]:
if not search_path.is_dir():
raise HTTPException(status_code=404, detail=f"The search path '{search_path}' does not exist or is not directory")
return ApiDependencies.invoker.services.model_manager.search_for_models([search_path])
@models_router.get(
"/ckpt_confs",
operation_id="list_ckpt_configs",
responses={
200: { "description" : "paths retrieved successfully" },
},
status_code = 200,
response_model = List[pathlib.Path]
)
async def list_ckpt_configs(
)->List[pathlib.Path]:
"""Return a list of the legacy checkpoint configuration files stored in `ROOT/configs/stable-diffusion`, relative to ROOT."""
return ApiDependencies.invoker.services.model_manager.list_checkpoint_configs()
@models_router.get(
"/sync",
operation_id="sync_to_config",
responses={
201: { "description": "synchronization successful" },
},
status_code = 201,
response_model = None
)
async def sync_to_config(
)->None:
"""Call after making changes to models.yaml, autoimport directories or models directory to synchronize
in-memory data structures with disk data structures."""
return ApiDependencies.invoker.services.model_manager.sync_to_config()
@models_router.put(
"/merge/{base_model}",
operation_id="merge_models",
responses={
200: { "description": "Model converted successfully" },
400: { "description": "Incompatible models" },
404: { "description": "One or more models not found" },
},
status_code = 200,
response_model = MergeModelResponse,
)
async def merge_models(
base_model: BaseModelType = Path(description="Base model"),
model_names: List[str] = Body(description="model name", min_items=2, max_items=3),
merged_model_name: Optional[str] = Body(description="Name of destination model"),
alpha: Optional[float] = Body(description="Alpha weighting strength to apply to 2d and 3d models", default=0.5),
interp: Optional[MergeInterpolationMethod] = Body(description="Interpolation method"),
force: Optional[bool] = Body(description="Force merging of models created with different versions of diffusers", default=False),
merge_dest_directory: Optional[str] = Body(description="Save the merged model to the designated directory (with 'merged_model_name' appended)", default=None)
) -> MergeModelResponse:
"""Convert a checkpoint model into a diffusers model"""
logger = ApiDependencies.invoker.services.logger
try:
logger.info(f"Merging models: {model_names} into {merge_dest_directory or '<MODELS>'}/{merged_model_name}")
dest = pathlib.Path(merge_dest_directory) if merge_dest_directory else None
result = ApiDependencies.invoker.services.model_manager.merge_models(model_names,
base_model,
merged_model_name=merged_model_name or "+".join(model_names),
alpha=alpha,
interp=interp,
force=force,
merge_dest_directory = dest
)
model_raw = ApiDependencies.invoker.services.model_manager.list_model(result.name,
base_model = base_model,
model_type = ModelType.Main,
)
response = parse_obj_as(ConvertModelResponse, model_raw)
except ModelNotFoundException:
raise HTTPException(status_code=404, detail=f"One or more of the models '{model_names}' not found")
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
return response
# The rename operation is now supported by update_model and no longer needs to be
# a standalone route.
# @models_router.post(
# "/rename/{base_model}/{model_type}/{model_name}",
# operation_id="rename_model",
# responses= {
# 201: {"description" : "The model was renamed successfully"},
# 404: {"description" : "The model could not be found"},
# 409: {"description" : "There is already a model corresponding to the new name"},
# },
# status_code=201,
# response_model=ImportModelResponse
# )
# async def rename_model(
# base_model: BaseModelType = Path(description="Base model"),
# model_type: ModelType = Path(description="The type of model"),
# model_name: str = Path(description="current model name"),
# new_name: Optional[str] = Query(description="new model name", default=None),
# new_base: Optional[BaseModelType] = Query(description="new model base", default=None),
# ) -> ImportModelResponse:
# """ Rename a model"""
# logger = ApiDependencies.invoker.services.logger
# try:
# result = ApiDependencies.invoker.services.model_manager.rename_model(
# base_model = base_model,
# model_type = model_type,
# model_name = model_name,
# new_name = new_name,
# new_base = new_base,
# )
# logger.debug(result)
# logger.info(f'Successfully renamed {model_name}=>{new_name}')
# model_raw = ApiDependencies.invoker.services.model_manager.list_model(
# model_name=new_name or model_name,
# base_model=new_base or base_model,
# model_type=model_type
# )
# return parse_obj_as(ImportModelResponse, model_raw)
# except ModelNotFoundException as e:
# logger.error(str(e))
# raise HTTPException(status_code=404, detail=str(e))
# except ValueError as e:
# logger.error(str(e))
# raise HTTPException(status_code=409, detail=str(e))