InvokeAI/invokeai/backend/install/install_helper.py
Lincoln Stein cc41e8912c several small model install enhancements
- Support extended HF repoid syntax in TUI. This allows
  installation of subfolders and safetensors files, as in
  `XpucT/Deliberate::Deliberate_v5.safetensors`

- Add `error` and `error_traceback` properties to the install
  job objects.

- Rename the `heuristic_import` route to `heuristic_install`.

- Fix the example `config` input in the `heuristic_install` route.
2024-03-01 10:42:33 +11:00

268 lines
11 KiB
Python

"""Utility (backend) functions used by model_install.py"""
from logging import Logger
from pathlib import Path
from typing import Any, Dict, List, Optional
import omegaconf
from pydantic import BaseModel, Field
from pydantic.dataclasses import dataclass
from requests import HTTPError
from tqdm import tqdm
import invokeai.configs as configs
from invokeai.app.services.config import InvokeAIAppConfig
from invokeai.app.services.download import DownloadQueueService
from invokeai.app.services.events.events_base import EventServiceBase
from invokeai.app.services.image_files.image_files_disk import DiskImageFileStorage
from invokeai.app.services.model_install import (
ModelInstallService,
ModelInstallServiceBase,
)
from invokeai.app.services.model_metadata import ModelMetadataStoreSQL
from invokeai.app.services.model_records import ModelRecordServiceBase, ModelRecordServiceSQL
from invokeai.app.services.shared.sqlite.sqlite_util import init_db
from invokeai.backend.model_manager import (
BaseModelType,
InvalidModelConfigException,
ModelType,
)
from invokeai.backend.model_manager.metadata import UnknownMetadataException
from invokeai.backend.util.logging import InvokeAILogger
# name of the starter models file
INITIAL_MODELS = "INITIAL_MODELS.yaml"
def initialize_record_store(app_config: InvokeAIAppConfig) -> ModelRecordServiceBase:
"""Return an initialized ModelConfigRecordServiceBase object."""
logger = InvokeAILogger.get_logger(config=app_config)
image_files = DiskImageFileStorage(f"{app_config.output_path}/images")
db = init_db(config=app_config, logger=logger, image_files=image_files)
obj: ModelRecordServiceBase = ModelRecordServiceSQL(db, ModelMetadataStoreSQL(db))
return obj
def initialize_installer(
app_config: InvokeAIAppConfig, event_bus: Optional[EventServiceBase] = None
) -> ModelInstallServiceBase:
"""Return an initialized ModelInstallService object."""
record_store = initialize_record_store(app_config)
download_queue = DownloadQueueService()
installer = ModelInstallService(
app_config=app_config,
record_store=record_store,
download_queue=download_queue,
event_bus=event_bus,
)
download_queue.start()
installer.start()
return installer
class UnifiedModelInfo(BaseModel):
"""Catchall class for information in INITIAL_MODELS2.yaml."""
name: Optional[str] = None
base: Optional[BaseModelType] = None
type: Optional[ModelType] = None
source: Optional[str] = None
subfolder: Optional[str] = None
description: Optional[str] = None
recommended: bool = False
installed: bool = False
default: bool = False
requires: List[str] = Field(default_factory=list)
@dataclass
class InstallSelections:
"""Lists of models to install and remove."""
install_models: List[UnifiedModelInfo] = Field(default_factory=list)
remove_models: List[str] = Field(default_factory=list)
class TqdmEventService(EventServiceBase):
"""An event service to track downloads."""
def __init__(self) -> None:
"""Create a new TqdmEventService object."""
super().__init__()
self._bars: Dict[str, tqdm] = {}
self._last: Dict[str, int] = {}
self._logger = InvokeAILogger.get_logger(__name__)
def dispatch(self, event_name: str, payload: Any) -> None:
"""Dispatch an event by appending it to self.events."""
data = payload["data"]
source = data["source"]
if payload["event"] == "model_install_downloading":
dest = data["local_path"]
total_bytes = data["total_bytes"]
bytes = data["bytes"]
if dest not in self._bars:
self._bars[dest] = tqdm(desc=Path(dest).name, initial=0, total=total_bytes, unit="iB", unit_scale=True)
self._last[dest] = 0
self._bars[dest].update(bytes - self._last[dest])
self._last[dest] = bytes
elif payload["event"] == "model_install_completed":
self._logger.info(f"{source}: installed successfully.")
elif payload["event"] == "model_install_error":
self._logger.warning(f"{source}: installation failed with error {data['error']}")
elif payload["event"] == "model_install_cancelled":
self._logger.warning(f"{source}: installation cancelled")
class InstallHelper(object):
"""Capture information stored jointly in INITIAL_MODELS.yaml and the installed models db."""
def __init__(self, app_config: InvokeAIAppConfig, logger: Logger):
"""Create new InstallHelper object."""
self._app_config = app_config
self.all_models: Dict[str, UnifiedModelInfo] = {}
omega = omegaconf.OmegaConf.load(Path(configs.__path__[0]) / INITIAL_MODELS)
assert isinstance(omega, omegaconf.dictconfig.DictConfig)
self._installer = initialize_installer(app_config, TqdmEventService())
self._initial_models = omega
self._installed_models: List[str] = []
self._starter_models: List[str] = []
self._default_model: Optional[str] = None
self._logger = logger
self._initialize_model_lists()
@property
def installer(self) -> ModelInstallServiceBase:
"""Return the installer object used internally."""
return self._installer
def _initialize_model_lists(self) -> None:
"""
Initialize our model slots.
Set up the following:
installed_models -- list of installed model keys
starter_models -- list of starter model keys from INITIAL_MODELS
all_models -- dict of key => UnifiedModelInfo
default_model -- key to default model
"""
# previously-installed models
for model in self._installer.record_store.all_models():
info = UnifiedModelInfo.parse_obj(model.dict())
info.installed = True
model_key = f"{model.base.value}/{model.type.value}/{model.name}"
self.all_models[model_key] = info
self._installed_models.append(model_key)
for key in self._initial_models.keys():
assert isinstance(key, str)
if key in self.all_models:
# we want to preserve the description
description = self.all_models[key].description or self._initial_models[key].get("description")
self.all_models[key].description = description
else:
base_model, model_type, model_name = key.split("/")
info = UnifiedModelInfo(
name=model_name,
type=ModelType(model_type),
base=BaseModelType(base_model),
source=self._initial_models[key].source,
description=self._initial_models[key].get("description"),
recommended=self._initial_models[key].get("recommended", False),
default=self._initial_models[key].get("default", False),
subfolder=self._initial_models[key].get("subfolder"),
requires=list(self._initial_models[key].get("requires", [])),
)
self.all_models[key] = info
if not self.default_model():
self._default_model = key
elif self._initial_models[key].get("default", False):
self._default_model = key
self._starter_models.append(key)
# previously-installed models
for model in self._installer.record_store.all_models():
info = UnifiedModelInfo.parse_obj(model.dict())
info.installed = True
model_key = f"{model.base.value}/{model.type.value}/{model.name}"
self.all_models[model_key] = info
self._installed_models.append(model_key)
def recommended_models(self) -> List[UnifiedModelInfo]:
"""List of the models recommended in INITIAL_MODELS.yaml."""
return [self._to_model(x) for x in self._starter_models if self._to_model(x).recommended]
def installed_models(self) -> List[UnifiedModelInfo]:
"""List of models already installed."""
return [self._to_model(x) for x in self._installed_models]
def starter_models(self) -> List[UnifiedModelInfo]:
"""List of starter models."""
return [self._to_model(x) for x in self._starter_models]
def default_model(self) -> Optional[UnifiedModelInfo]:
"""Return the default model."""
return self._to_model(self._default_model) if self._default_model else None
def _to_model(self, key: str) -> UnifiedModelInfo:
return self.all_models[key]
def _add_required_models(self, model_list: List[UnifiedModelInfo]) -> None:
installed = {x.source for x in self.installed_models()}
reverse_source = {x.source: x for x in self.all_models.values()}
additional_models: List[UnifiedModelInfo] = []
for model_info in model_list:
for requirement in model_info.requires:
if requirement not in installed and reverse_source.get(requirement):
additional_models.append(reverse_source[requirement])
model_list.extend(additional_models)
def add_or_delete(self, selections: InstallSelections) -> None:
"""Add or delete selected models."""
installer = self._installer
self._add_required_models(selections.install_models)
for model in selections.install_models:
assert model.source
model_path_id_or_url = model.source.strip("\"' ")
config = (
{
"description": model.description,
"name": model.name,
}
if model.name
else None
)
try:
installer.heuristic_import(
source=model_path_id_or_url,
config=config,
)
except (UnknownMetadataException, InvalidModelConfigException, HTTPError, OSError) as e:
self._logger.warning(f"{model.source}: {e}")
for model_to_remove in selections.remove_models:
parts = model_to_remove.split("/")
if len(parts) == 1:
base_model, model_type, model_name = (None, None, model_to_remove)
else:
base_model, model_type, model_name = parts
matches = installer.record_store.search_by_attr(
base_model=BaseModelType(base_model) if base_model else None,
model_type=ModelType(model_type) if model_type else None,
model_name=model_name,
)
if len(matches) > 1:
self._logger.error(
"{model_to_remove} is ambiguous. Please use model_base/model_type/model_name (e.g. sd-1/main/my_model) to disambiguate"
)
elif not matches:
self._logger.error(f"{model_to_remove}: unknown model")
else:
for m in matches:
self._logger.info(f"Deleting {m.type}:{m.name}")
installer.delete(m.key)
installer.wait_for_installs()