InvokeAI/ldm/invoke/config/model_install.py

#!/usr/bin/env python
# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
# Before running stable-diffusion on an internet-isolated machine,
# run this script from one with internet connectivity. The
# two machines must share a common .cache directory.

"""
This is the npyscreen frontend to the model installation application.
The work is actually done in backend code in model_install_backend.py.
"""

import argparse
import os
import sys
from argparse import Namespace
from pathlib import Path
from typing import List

import npyscreen
import torch
from npyscreen import widget
from omegaconf import OmegaConf
from shutil import get_terminal_size

from invokeai.backend.devices import choose_precision, choose_torch_device
from ..globals import Globals, global_config_dir
from .model_install_backend import (Dataset_path, default_config_file,
                                    default_dataset, get_root,
                                    install_requested_models,
                                    recommended_datasets,
                                    )
from .widgets import (MultiSelectColumns, TextBox,
                      OffsetButtonPress, CenteredTitleText,
                      set_min_terminal_size,
                      )

# minimum size for the UI
MIN_COLS = 120
MIN_LINES = 45

class addModelsForm(npyscreen.FormMultiPage):
    # for responsive resizing - disabled
    #FIX_MINIMUM_SIZE_WHEN_CREATED = False
    
    def __init__(self, parentApp, name, multipage=False, *args, **keywords):
        self.multipage = multipage
        self.initial_models = OmegaConf.load(Dataset_path)
        try:
            self.existing_models = OmegaConf.load(default_config_file())
        except:
            self.existing_models = dict()
        self.starter_model_list = [
            x for x in list(self.initial_models.keys()) if x not in self.existing_models
        ]
        self.installed_models = dict()
        super().__init__(parentApp=parentApp, name=name, *args, **keywords)

    def create(self):
        window_width, window_height = get_terminal_size()
        starter_model_labels = self._get_starter_model_labels()
        recommended_models = [
            x
            for x in self.starter_model_list
            if self.initial_models[x].get("recommended", False)
        ]
        self.installed_models = sorted(
            [x for x in list(self.initial_models.keys()) if x in self.existing_models]
        )
        self.nextrely -= 1
        self.add_widget_intelligent(
            npyscreen.FixedText,
            value="Use ctrl-N and ctrl-P to move to the <N>ext and <P>revious fields,",
            editable=False,
            color='CAUTION',
        )
        self.add_widget_intelligent(
            npyscreen.FixedText,
            value="Use cursor arrows to make a selection, and space to toggle checkboxes.",
            editable=False,
            color='CAUTION'
        )
        self.nextrely += 1
        if len(self.installed_models) > 0:
            self.add_widget_intelligent(
                CenteredTitleText,
                name="== INSTALLED STARTER MODELS ==",
                editable=False,
                color="CONTROL",
            )
            self.nextrely -= 1
            self.add_widget_intelligent(
                CenteredTitleText,
                name="Currently installed starter models. Uncheck to delete:",
                editable=False,
                labelColor="CAUTION",
            )
            self.nextrely -= 1
            columns = self._get_columns()
            self.previously_installed_models = self.add_widget_intelligent(
                MultiSelectColumns,
                columns=columns,
                values=self.installed_models,
                value=[x for x in range(0, len(self.installed_models))],
                max_height=1 + len(self.installed_models) // columns,
                relx=4,
                slow_scroll=True,
                scroll_exit=True,
            )
            self.purge_deleted = self.add_widget_intelligent(
                npyscreen.Checkbox,
                name="Purge deleted models from disk",
                value=False,
                scroll_exit=True,
                relx=4,
            )
        self.nextrely += 1
        if len(self.starter_model_list) > 0:
            self.add_widget_intelligent(
                CenteredTitleText,
                name="== STARTER MODELS (recommended ones selected) ==",
                editable=False,
                color="CONTROL",
            )
            self.nextrely -= 1
            self.add_widget_intelligent(
                CenteredTitleText,
                name="Select from a starter set of Stable Diffusion models from HuggingFace.",
                editable=False,
                labelColor="CAUTION",
            )
            self.nextrely -= 1
            # if user has already installed some initial models, then don't patronize them
            # by showing more recommendations
            show_recommended = not self.existing_models
            self.models_selected = self.add_widget_intelligent(
                npyscreen.MultiSelect,
                name="Install Starter Models",
                values=starter_model_labels,
                value=[
                    self.starter_model_list.index(x)
                    for x in self.starter_model_list
                    if show_recommended and x in recommended_models
                ],
                max_height=len(starter_model_labels) + 1,
                relx=4,
                scroll_exit=True,
            )
        self.add_widget_intelligent(
            CenteredTitleText,
            name='== IMPORT LOCAL AND REMOTE MODELS ==',
            editable=False,
            color="CONTROL",
        )
        self.nextrely -= 1

        for line in [
                "In the box below, enter URLs, file paths, or HuggingFace repository IDs.",
                "Separate model names by lines or whitespace (Use shift-control-V to paste):",
        ]:
            self.add_widget_intelligent(
                CenteredTitleText,
                name=line,
                editable=False,
                labelColor="CONTROL",
                relx = 4,
            )
            self.nextrely -= 1
        self.import_model_paths = self.add_widget_intelligent(
            TextBox,
            max_height=7,
            scroll_exit=True,
            editable=True,
            relx=4
        )
        self.nextrely += 1
        self.show_directory_fields = self.add_widget_intelligent(
            npyscreen.FormControlCheckbox,
            name="Select a directory for models to import",
            value=False,
        )
        self.autoload_directory = self.add_widget_intelligent(
            npyscreen.TitleFilename,
            name="Directory (<tab> autocompletes):",
            select_dir=True,
            must_exist=True,
            use_two_lines=False,
            labelColor="DANGER",
            begin_entry_at=34,
            scroll_exit=True,
        )
        self.autoscan_on_startup = self.add_widget_intelligent(
            npyscreen.Checkbox,
            name="Scan this directory each time InvokeAI starts for new models to import",
            value=False,
            relx=4,
            scroll_exit=True,
        )
        self.nextrely += 1
        self.convert_models = self.add_widget_intelligent(
            npyscreen.TitleSelectOne,
            name="== CONVERT IMPORTED MODELS INTO DIFFUSERS==",
            values=["Keep original format", "Convert to diffusers"],
            value=0,
            begin_entry_at=4,
            max_height=4,
            hidden=True,  # will appear when imported models box is edited
            scroll_exit=True,
        )
        self.cancel = self.add_widget_intelligent(
            npyscreen.ButtonPress,
            name="CANCEL",
            rely=-3,
            when_pressed_function=self.on_cancel,
        )
        done_label = "DONE"
        back_label = "BACK"
        button_length = len(done_label)
        button_offset = 0
        if self.multipage:
            button_length += len(back_label) + 1
            button_offset += len(back_label) + 1
            self.back_button = self.add_widget_intelligent(
                OffsetButtonPress,
                name=back_label,
                relx=(window_width - button_length) // 2,
                offset=-3,
                rely=-3,
                when_pressed_function=self.on_back,
            )
        self.ok_button = self.add_widget_intelligent(
            OffsetButtonPress,
            name=done_label,
            offset=+3,
            relx=button_offset + 1 + (window_width - button_length) // 2,
            rely=-3,
            when_pressed_function=self.on_ok,
        )

        for i in [self.autoload_directory, self.autoscan_on_startup]:
            self.show_directory_fields.addVisibleWhenSelected(i)

        self.show_directory_fields.when_value_edited = self._clear_scan_directory
        self.import_model_paths.when_value_edited = self._show_hide_convert
        self.autoload_directory.when_value_edited = self._show_hide_convert

    def resize(self):
        super().resize()
        if hasattr(self,'models_selected'):
            self.models_selected.values = self._get_starter_model_labels()

    def _clear_scan_directory(self):
        if not self.show_directory_fields.value:
            self.autoload_directory.value = ""

    def _show_hide_convert(self):
        model_paths = self.import_model_paths.value or ""
        autoload_directory = self.autoload_directory.value or ""
        self.convert_models.hidden = (
            len(model_paths) == 0 and len(autoload_directory) == 0
        )

    def _get_starter_model_labels(self) -> List[str]:
        window_width, window_height = get_terminal_size()
        label_width = 25
        checkbox_width = 4
        spacing_width = 2
        description_width = window_width - label_width - checkbox_width - spacing_width
        im = self.initial_models
        names = self.starter_model_list
        descriptions = [
            im[x].description[0 : description_width - 3] + "..."
            if len(im[x].description) > description_width
            else im[x].description
            for x in names
        ]
        return [
            f"%-{label_width}s %s" % (names[x], descriptions[x])
            for x in range(0, len(names))
        ]

    def _get_columns(self) -> int:
        window_width, window_height = get_terminal_size()
        cols = (
            4
            if window_width > 240
            else 3
            if window_width > 160
            else 2
            if window_width > 80
            else 1
        )
        return min(cols, len(self.installed_models))

    def on_ok(self):
        self.parentApp.setNextForm(None)
        self.editing = False
        self.parentApp.user_cancelled = False
        self.marshall_arguments()

    def on_back(self):
        self.parentApp.switchFormPrevious()
        self.editing = False

    def on_cancel(self):
        if npyscreen.notify_yes_no(
            "Are you sure you want to cancel?\nYou may re-run this script later using the invoke.sh or invoke.bat command.\n"
        ):
            self.parentApp.setNextForm(None)
            self.parentApp.user_cancelled = True
            self.editing = False

    def marshall_arguments(self):
        """
        Assemble arguments and store as attributes of the application:
        .starter_models: dict of model names to install from INITIAL_CONFIGURE.yaml
                         True  => Install
                         False => Remove
        .scan_directory: Path to a directory of models to scan and import
        .autoscan_on_startup:  True if invokeai should scan and import at startup time
        .import_model_paths:   list of URLs, repo_ids and file paths to import
        .convert_to_diffusers: if True, convert legacy checkpoints into diffusers
        """
        # we're using a global here rather than storing the result in the parentapp
        # due to some bug in npyscreen that is causing attributes to be lost
        selections = self.parentApp.user_selections

        # starter models to install/remove
        if hasattr(self,'models_selected'):
            starter_models = dict(
                map(
                    lambda x: (self.starter_model_list[x], True), self.models_selected.value
                )
            )
        else:
            starter_models = dict()
        selections.purge_deleted_models = False
        if hasattr(self, "previously_installed_models"):
            unchecked = [
                self.previously_installed_models.values[x]
                for x in range(0, len(self.previously_installed_models.values))
                if x not in self.previously_installed_models.value
            ]
            starter_models.update(map(lambda x: (x, False), unchecked))
            selections.purge_deleted_models = self.purge_deleted.value
        selections.starter_models = starter_models

        # load directory and whether to scan on startup
        if self.show_directory_fields.value:
            selections.scan_directory = self.autoload_directory.value
            selections.autoscan_on_startup = self.autoscan_on_startup.value
        else:
            selections.scan_directory = None
            selections.autoscan_on_startup = False

        # URLs and the like
        selections.import_model_paths = self.import_model_paths.value.split()
        selections.convert_to_diffusers = self.convert_models.value[0] == 1


class AddModelApplication(npyscreen.NPSAppManaged):
    def __init__(self):
        super().__init__()
        self.user_cancelled = False
        self.user_selections = Namespace(
            starter_models=None,
            purge_deleted_models=False,
            scan_directory=None,
            autoscan_on_startup=None,
            import_model_paths=None,
            convert_to_diffusers=None,
        )

    def onStart(self):
        npyscreen.setTheme(npyscreen.Themes.DefaultTheme)
        self.main_form = self.addForm(
            "MAIN", addModelsForm, name="Install Stable Diffusion Models"
        )

# --------------------------------------------------------
def process_and_execute(opt: Namespace, selections: Namespace):
    models_to_remove = [
        x for x in selections.starter_models if not selections.starter_models[x]
    ]
    models_to_install = [
        x for x in selections.starter_models if selections.starter_models[x]
    ]
    directory_to_scan = selections.scan_directory
    scan_at_startup = selections.autoscan_on_startup
    potential_models_to_install = selections.import_model_paths
    convert_to_diffusers = selections.convert_to_diffusers

    install_requested_models(
        install_initial_models=models_to_install,
        remove_models=models_to_remove,
        scan_directory=Path(directory_to_scan) if directory_to_scan else None,
        external_models=potential_models_to_install,
        scan_at_startup=scan_at_startup,
        convert_to_diffusers=convert_to_diffusers,
        precision="float32"
        if opt.full_precision
        else choose_precision(torch.device(choose_torch_device())),
        purge_deleted=selections.purge_deleted_models,
        config_file_path=Path(opt.config_file) if opt.config_file else None,
    )


# --------------------------------------------------------
def select_and_download_models(opt: Namespace):
    precision = (
        "float32"
        if opt.full_precision
        else choose_precision(torch.device(choose_torch_device()))
    )
    if opt.default_only:
        install_requested_models(
            install_initial_models=default_dataset(),
            precision=precision,
        )
    elif opt.yes_to_all:
        install_requested_models(
            install_initial_models=recommended_datasets(),
            precision=precision,
        )
    else:
        set_min_terminal_size(MIN_COLS, MIN_LINES)
        installApp = AddModelApplication()
        installApp.run()

        if not installApp.user_cancelled:
            process_and_execute(opt, installApp.user_selections)


# -------------------------------------
def main():
    parser = argparse.ArgumentParser(description="InvokeAI model downloader")
    parser.add_argument(
        "--full-precision",
        dest="full_precision",
        action=argparse.BooleanOptionalAction,
        type=bool,
        default=False,
        help="use 32-bit weights instead of faster 16-bit weights",
    )
    parser.add_argument(
        "--yes",
        "-y",
        dest="yes_to_all",
        action="store_true",
        help='answer "yes" to all prompts',
    )
    parser.add_argument(
        "--default_only",
        action="store_true",
        help="only install the default model",
    )
    parser.add_argument(
        "--config_file",
        "-c",
        dest="config_file",
        type=str,
        default=None,
        help="path to configuration file to create",
    )
    parser.add_argument(
        "--root_dir",
        dest="root",
        type=str,
        default=None,
        help="path to root of install directory",
    )
    opt = parser.parse_args()

    # setting a global here
    Globals.root = os.path.expanduser(get_root(opt.root) or "")

    if not global_config_dir().exists():
        print(
            ">> Your InvokeAI root directory is not set up. Calling invokeai-configure."
        )
        import ldm.invoke.config.invokeai_configure

        ldm.invoke.config.invokeai_configure.main()
        sys.exit(0)

    try:
        select_and_download_models(opt)
    except AssertionError as e:
        print(str(e))
        sys.exit(-1)
    except KeyboardInterrupt:
        print("\nGoodbye! Come back soon.")
    except widget.NotEnoughSpaceForWidget as e:
        if str(e).startswith("Height of 1 allocated"):
            print(
                "** Insufficient vertical space for the interface. Please make your window taller and try again"
            )
        elif str(e).startswith("addwstr"):
            print(
                "** Insufficient horizontal space for the interface. Please make your window wider and try again."
            )

# -------------------------------------
if __name__ == "__main__":
    main()