# Copyright (c) 2023 Lincoln D. Stein """FastAPI route for model configuration records.""" import io import pathlib import traceback from copy import deepcopy from tempfile import TemporaryDirectory from typing import Any, Dict, List, Optional, Type from fastapi import Body, Path, Query, Response, UploadFile from fastapi.responses import FileResponse, HTMLResponse from fastapi.routing import APIRouter from PIL import Image from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field from starlette.exceptions import HTTPException from typing_extensions import Annotated from invokeai.app.services.model_images.model_images_common import ModelImageFileNotFoundException from invokeai.app.services.model_install.model_install_common import ModelInstallJob from invokeai.app.services.model_records import ( InvalidModelException, ModelRecordChanges, UnknownModelException, ) from invokeai.backend.model_manager.config import ( AnyModelConfig, BaseModelType, MainCheckpointConfig, ModelFormat, ModelType, ) from invokeai.backend.model_manager.metadata.fetch.huggingface import HuggingFaceMetadataFetch from invokeai.backend.model_manager.metadata.metadata_base import ModelMetadataWithFiles, UnknownMetadataException from invokeai.backend.model_manager.search import ModelSearch from invokeai.backend.model_manager.starter_models import STARTER_MODELS, StarterModel, StarterModelWithoutDependencies from ..dependencies import ApiDependencies model_manager_router = APIRouter(prefix="/v2/models", tags=["model_manager"]) # images are immutable; set a high max-age IMAGE_MAX_AGE = 31536000 class ModelsList(BaseModel): """Return list of configs.""" models: List[AnyModelConfig] model_config = ConfigDict(use_enum_values=True) def add_cover_image_to_model_config(config: AnyModelConfig, dependencies: Type[ApiDependencies]) -> AnyModelConfig: """Add a cover image URL to a model configuration.""" cover_image = dependencies.invoker.services.model_images.get_url(config.key) config.cover_image = cover_image return config ############################################################################## # These are example inputs and outputs that are used in places where Swagger # is unable to generate a correct example. ############################################################################## example_model_config = { "path": "string", "name": "string", "base": "sd-1", "type": "main", "format": "checkpoint", "config_path": "string", "key": "string", "hash": "string", "description": "string", "source": "string", "converted_at": 0, "variant": "normal", "prediction_type": "epsilon", "repo_variant": "fp16", "upcast_attention": False, } example_model_input = { "path": "/path/to/model", "name": "model_name", "base": "sd-1", "type": "main", "format": "checkpoint", "config_path": "configs/stable-diffusion/v1-inference.yaml", "description": "Model description", "vae": None, "variant": "normal", } ############################################################################## # ROUTES ############################################################################## @model_manager_router.get( "/", operation_id="list_model_records", ) async def list_model_records( base_models: Optional[List[BaseModelType]] = Query(default=None, description="Base models to include"), model_type: Optional[ModelType] = Query(default=None, description="The type of model to get"), model_name: Optional[str] = Query(default=None, description="Exact match on the name of the model"), model_format: Optional[ModelFormat] = Query( default=None, description="Exact match on the format of the model (e.g. 'diffusers')" ), ) -> ModelsList: """Get a list of models.""" record_store = ApiDependencies.invoker.services.model_manager.store found_models: list[AnyModelConfig] = [] if base_models: for base_model in base_models: found_models.extend( record_store.search_by_attr( base_model=base_model, model_type=model_type, model_name=model_name, model_format=model_format ) ) else: found_models.extend( record_store.search_by_attr(model_type=model_type, model_name=model_name, model_format=model_format) ) for model in found_models: model = add_cover_image_to_model_config(model, ApiDependencies) return ModelsList(models=found_models) @model_manager_router.get( "/get_by_attrs", operation_id="get_model_records_by_attrs", response_model=AnyModelConfig, ) async def get_model_records_by_attrs( name: str = Query(description="The name of the model"), type: ModelType = Query(description="The type of the model"), base: BaseModelType = Query(description="The base model of the model"), ) -> AnyModelConfig: """Gets a model by its attributes. The main use of this route is to provide backwards compatibility with the old model manager, which identified models by a combination of name, base and type.""" configs = ApiDependencies.invoker.services.model_manager.store.search_by_attr( base_model=base, model_type=type, model_name=name ) if not configs: raise HTTPException(status_code=404, detail="No model found with these attributes") return configs[0] @model_manager_router.get( "/i/{key}", operation_id="get_model_record", responses={ 200: { "description": "The model configuration was retrieved successfully", "content": {"application/json": {"example": example_model_config}}, }, 400: {"description": "Bad request"}, 404: {"description": "The model could not be found"}, }, ) async def get_model_record( key: str = Path(description="Key of the model record to fetch."), ) -> AnyModelConfig: """Get a model record""" try: config = ApiDependencies.invoker.services.model_manager.store.get_model(key) return add_cover_image_to_model_config(config, ApiDependencies) except UnknownModelException as e: raise HTTPException(status_code=404, detail=str(e)) class FoundModel(BaseModel): path: str = Field(description="Path to the model") is_installed: bool = Field(description="Whether or not the model is already installed") @model_manager_router.get( "/scan_folder", operation_id="scan_for_models", responses={ 200: {"description": "Directory scanned successfully"}, 400: {"description": "Invalid directory path"}, }, status_code=200, response_model=List[FoundModel], ) async def scan_for_models( scan_path: str = Query(description="Directory path to search for models", default=None), ) -> List[FoundModel]: path = pathlib.Path(scan_path) if not scan_path or not path.is_dir(): raise HTTPException( status_code=400, detail=f"The search path '{scan_path}' does not exist or is not directory", ) search = ModelSearch() try: found_model_paths = search.search(path) models_path = ApiDependencies.invoker.services.configuration.models_path # If the search path includes the main models directory, we need to exclude core models from the list. # TODO(MM2): Core models should be handled by the model manager so we can determine if they are installed # without needing to crawl the filesystem. core_models_path = pathlib.Path(models_path, "core").resolve() non_core_model_paths = [p for p in found_model_paths if not p.is_relative_to(core_models_path)] installed_models = ApiDependencies.invoker.services.model_manager.store.search_by_attr() scan_results: list[FoundModel] = [] # Check if the model is installed by comparing paths, appending to the scan result. for p in non_core_model_paths: path = str(p) is_installed = any(str(models_path / m.path) == path for m in installed_models) found_model = FoundModel(path=path, is_installed=is_installed) scan_results.append(found_model) except Exception as e: raise HTTPException( status_code=500, detail=f"An error occurred while searching the directory: {e}", ) return scan_results class HuggingFaceModels(BaseModel): urls: List[AnyHttpUrl] | None = Field(description="URLs for all checkpoint format models in the metadata") is_diffusers: bool = Field(description="Whether the metadata is for a Diffusers format model") @model_manager_router.get( "/hugging_face", operation_id="get_hugging_face_models", responses={ 200: {"description": "Hugging Face repo scanned successfully"}, 400: {"description": "Invalid hugging face repo"}, }, status_code=200, response_model=HuggingFaceModels, ) async def get_hugging_face_models( hugging_face_repo: str = Query(description="Hugging face repo to search for models", default=None), ) -> HuggingFaceModels: try: metadata = HuggingFaceMetadataFetch().from_id(hugging_face_repo) except UnknownMetadataException: raise HTTPException( status_code=400, detail="No HuggingFace repository found", ) assert isinstance(metadata, ModelMetadataWithFiles) return HuggingFaceModels( urls=metadata.ckpt_urls, is_diffusers=metadata.is_diffusers, ) @model_manager_router.patch( "/i/{key}", operation_id="update_model_record", responses={ 200: { "description": "The model was updated successfully", "content": {"application/json": {"example": example_model_config}}, }, 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, ) async def update_model_record( key: Annotated[str, Path(description="Unique key of model")], changes: Annotated[ModelRecordChanges, Body(description="Model config", example=example_model_input)], ) -> AnyModelConfig: """Update a model's config.""" logger = ApiDependencies.invoker.services.logger record_store = ApiDependencies.invoker.services.model_manager.store installer = ApiDependencies.invoker.services.model_manager.install try: record_store.update_model(key, changes=changes) config = installer.sync_model_path(key) config = add_cover_image_to_model_config(config, ApiDependencies) logger.info(f"Updated model: {key}") except UnknownModelException 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)) return config @model_manager_router.get( "/i/{key}/image", operation_id="get_model_image", responses={ 200: { "description": "The model image was fetched successfully", }, 400: {"description": "Bad request"}, 404: {"description": "The model image could not be found"}, }, status_code=200, ) async def get_model_image( key: str = Path(description="The name of model image file to get"), ) -> FileResponse: """Gets an image file that previews the model""" try: path = ApiDependencies.invoker.services.model_images.get_path(key) response = FileResponse( path, media_type="image/png", filename=key + ".png", content_disposition_type="inline", ) response.headers["Cache-Control"] = f"max-age={IMAGE_MAX_AGE}" return response except Exception: raise HTTPException(status_code=404) @model_manager_router.patch( "/i/{key}/image", operation_id="update_model_image", responses={ 200: { "description": "The model image was updated successfully", }, 400: {"description": "Bad request"}, }, status_code=200, ) async def update_model_image( key: Annotated[str, Path(description="Unique key of model")], image: UploadFile, ) -> None: if not image.content_type or not image.content_type.startswith("image"): raise HTTPException(status_code=415, detail="Not an image") contents = await image.read() try: pil_image = Image.open(io.BytesIO(contents)) except Exception: ApiDependencies.invoker.services.logger.error(traceback.format_exc()) raise HTTPException(status_code=415, detail="Failed to read image") logger = ApiDependencies.invoker.services.logger model_images = ApiDependencies.invoker.services.model_images try: model_images.save(pil_image, key) logger.info(f"Updated image for model: {key}") except ValueError as e: logger.error(str(e)) raise HTTPException(status_code=409, detail=str(e)) return @model_manager_router.delete( "/i/{key}", operation_id="delete_model", responses={ 204: {"description": "Model deleted successfully"}, 404: {"description": "Model not found"}, }, status_code=204, ) async def delete_model( key: str = Path(description="Unique key of model to remove from model registry."), ) -> Response: """ Delete model record from database. The configuration record will be removed. The corresponding weights files will be deleted as well if they reside within the InvokeAI "models" directory. """ logger = ApiDependencies.invoker.services.logger try: installer = ApiDependencies.invoker.services.model_manager.install installer.delete(key) logger.info(f"Deleted model: {key}") return Response(status_code=204) except UnknownModelException as e: logger.error(str(e)) raise HTTPException(status_code=404, detail=str(e)) @model_manager_router.delete( "/i/{key}/image", operation_id="delete_model_image", responses={ 204: {"description": "Model image deleted successfully"}, 404: {"description": "Model image not found"}, }, status_code=204, ) async def delete_model_image( key: str = Path(description="Unique key of model image to remove from model_images directory."), ) -> None: logger = ApiDependencies.invoker.services.logger model_images = ApiDependencies.invoker.services.model_images try: model_images.delete(key) logger.info(f"Deleted model image: {key}") return except UnknownModelException as e: logger.error(str(e)) raise HTTPException(status_code=404, detail=str(e)) @model_manager_router.post( "/install", operation_id="install_model", responses={ 201: {"description": "The model imported successfully"}, 415: {"description": "Unrecognized file/folder format"}, 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, ) async def install_model( source: str = Query(description="Model source to install, can be a local path, repo_id, or remote URL"), inplace: Optional[bool] = Query(description="Whether or not to install a local model in place", default=False), # TODO(MM2): Can we type this? config: Optional[Dict[str, Any]] = Body( description="Dict of fields that override auto-probed values in the model config record, such as name, description and prediction_type ", default=None, example={"name": "string", "description": "string"}, ), access_token: Optional[str] = None, ) -> ModelInstallJob: """Install a model using a string identifier. `source` can be any of the following. 1. A path on the local filesystem ('C:\\users\\fred\\model.safetensors') 2. A Url pointing to a single downloadable model file 3. A HuggingFace repo_id with any of the following formats: - model/name - model/name:fp16:vae - model/name::vae -- use default precision - model/name:fp16:path/to/model.safetensors - model/name::path/to/model.safetensors `config` is an optional dict containing model configuration values that will override the ones that are probed automatically. `access_token` is an optional access token for use with Urls that require authentication. Models will be downloaded, probed, configured and installed in a series of background threads. The return object has `status` attribute that can be used to monitor progress. See the documentation for `import_model_record` for more information on interpreting the job information returned by this route. """ logger = ApiDependencies.invoker.services.logger try: installer = ApiDependencies.invoker.services.model_manager.install result: ModelInstallJob = installer.heuristic_import( source=source, config=config, access_token=access_token, inplace=bool(inplace), ) logger.info(f"Started installation of {source}") except UnknownModelException as e: logger.error(str(e)) raise HTTPException(status_code=424, detail=str(e)) except InvalidModelException as e: logger.error(str(e)) raise HTTPException(status_code=415) except ValueError as e: logger.error(str(e)) raise HTTPException(status_code=409, detail=str(e)) return result @model_manager_router.get( "/install/huggingface", operation_id="install_hugging_face_model", responses={ 201: {"description": "The model is being installed"}, 400: {"description": "Bad request"}, 409: {"description": "There is already a model corresponding to this path or repo_id"}, }, status_code=201, response_class=HTMLResponse, ) async def install_hugging_face_model( source: str = Query(description="HuggingFace repo_id to install"), ) -> HTMLResponse: """Install a Hugging Face model using a string identifier.""" def generate_html(title: str, heading: str, repo_id: str, is_error: bool, message: str | None = "") -> str: if message: message = f"
{message}
" title_class = "error" if is_error else "success" return f"""