Merge branch 'main' into refactor/model-manager-3

docs/features/PROMPTS.md

@@ -120,7 +120,7 @@ Generate an image with a given prompt, record the seed of the image, and then
 use the `prompt2prompt` syntax to substitute words in the original prompt for
 words in a new prompt. This works for `img2img` as well.
 
-For example, consider the prompt `a cat.swap(dog) playing with a ball in the forest`. Normally, because of the word words interact with each other when doing a stable diffusion image generation, these two prompts would generate different compositions:
+For example, consider the prompt `a cat.swap(dog) playing with a ball in the forest`. Normally, because the words interact with each other when doing a stable diffusion image generation, these two prompts would generate different compositions:
   - `a cat playing with a ball in the forest`
   - `a dog playing with a ball in the forest`
 

invokeai/app/api/routers/app_info.py

@@ -1,7 +1,11 @@
 import typing
 from enum import Enum
+from importlib.metadata import PackageNotFoundError, version
 from pathlib import Path
+from platform import python_version
+from typing import Optional
 
+import torch
 from fastapi import Body
 from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field
@@ -40,6 +44,24 @@ class AppVersion(BaseModel):
     version: str = Field(description="App version")
 
 
+class AppDependencyVersions(BaseModel):
+    """App depencency Versions Response"""
+
+    accelerate: str = Field(description="accelerate version")
+    compel: str = Field(description="compel version")
+    cuda: Optional[str] = Field(description="CUDA version")
+    diffusers: str = Field(description="diffusers version")
+    numpy: str = Field(description="Numpy version")
+    opencv: str = Field(description="OpenCV version")
+    onnx: str = Field(description="ONNX version")
+    pillow: str = Field(description="Pillow (PIL) version")
+    python: str = Field(description="Python version")
+    torch: str = Field(description="PyTorch version")
+    torchvision: str = Field(description="PyTorch Vision version")
+    transformers: str = Field(description="transformers version")
+    xformers: Optional[str] = Field(description="xformers version")
+
+
 class AppConfig(BaseModel):
     """App Config Response"""
 
@@ -54,6 +76,29 @@ async def get_version() -> AppVersion:
     return AppVersion(version=__version__)
 
 
+@app_router.get("/app_deps", operation_id="get_app_deps", status_code=200, response_model=AppDependencyVersions)
+async def get_app_deps() -> AppDependencyVersions:
+    try:
+        xformers = version("xformers")
+    except PackageNotFoundError:
+        xformers = None
+    return AppDependencyVersions(
+        accelerate=version("accelerate"),
+        compel=version("compel"),
+        cuda=torch.version.cuda,
+        diffusers=version("diffusers"),
+        numpy=version("numpy"),
+        opencv=version("opencv-python"),
+        onnx=version("onnx"),
+        pillow=version("pillow"),
+        python=python_version(),
+        torch=torch.version.__version__,
+        torchvision=version("torchvision"),
+        transformers=version("transformers"),
+        xformers=xformers,
+    )
+
+
 @app_router.get("/config", operation_id="get_config", status_code=200, response_model=AppConfig)
 async def get_config() -> AppConfig:
     infill_methods = ["tile", "lama", "cv2"]

invokeai/app/services/latents_storage/latents_storage_disk.py

@@ -5,6 +5,8 @@ from typing import Union
 
 import torch
 
+from invokeai.app.services.invoker import Invoker
+
 from .latents_storage_base import LatentsStorageBase
 
 
@@ -17,6 +19,10 @@ class DiskLatentsStorage(LatentsStorageBase):
         self.__output_folder = output_folder if isinstance(output_folder, Path) else Path(output_folder)
         self.__output_folder.mkdir(parents=True, exist_ok=True)
 
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        self._delete_all_latents()
+
     def get(self, name: str) -> torch.Tensor:
         latent_path = self.get_path(name)
         return torch.load(latent_path)
@@ -32,3 +38,21 @@ class DiskLatentsStorage(LatentsStorageBase):
 
     def get_path(self, name: str) -> Path:
         return self.__output_folder / name
+
+    def _delete_all_latents(self) -> None:
+        """
+        Deletes all latents from disk.
+        Must be called after we have access to `self._invoker` (e.g. in `start()`).
+        """
+        deleted_latents_count = 0
+        freed_space = 0
+        for latents_file in Path(self.__output_folder).glob("*"):
+            if latents_file.is_file():
+                freed_space += latents_file.stat().st_size
+                deleted_latents_count += 1
+                latents_file.unlink()
+        if deleted_latents_count > 0:
+            freed_space_in_mb = round(freed_space / 1024 / 1024, 2)
+            self._invoker.services.logger.info(
+                f"Deleted {deleted_latents_count} latents files (freed {freed_space_in_mb}MB)"
+            )

invokeai/app/services/latents_storage/latents_storage_forward_cache.py

@@ -5,6 +5,8 @@ from typing import Dict, Optional
 
 import torch
 
+from invokeai.app.services.invoker import Invoker
+
 from .latents_storage_base import LatentsStorageBase
 
 
@@ -23,6 +25,18 @@ class ForwardCacheLatentsStorage(LatentsStorageBase):
         self.__cache_ids = Queue()
         self.__max_cache_size = max_cache_size
 
+    def start(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        start_op = getattr(self.__underlying_storage, "start", None)
+        if callable(start_op):
+            start_op(invoker)
+
+    def stop(self, invoker: Invoker) -> None:
+        self._invoker = invoker
+        stop_op = getattr(self.__underlying_storage, "stop", None)
+        if callable(stop_op):
+            stop_op(invoker)
+
     def get(self, name: str) -> torch.Tensor:
         cache_item = self.__get_cache(name)
         if cache_item is not None:

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -42,6 +42,7 @@ class SqliteSessionQueue(SessionQueueBase):
         self._set_in_progress_to_canceled()
         prune_result = self.prune(DEFAULT_QUEUE_ID)
         local_handler.register(event_name=EventServiceBase.queue_event, _func=self._on_session_event)
+        if prune_result.deleted > 0:
             self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items")
 
     def __init__(self, db: SqliteDatabase) -> None:

invokeai/app/services/shared/graph.py

@@ -207,10 +207,12 @@ class IterateInvocationOutput(BaseInvocationOutput):
     item: Any = OutputField(
         description="The item being iterated over", title="Collection Item", ui_type=UIType._CollectionItem
     )
+    index: int = OutputField(description="The index of the item", title="Index")
+    total: int = OutputField(description="The total number of items", title="Total")
 
 
 # TODO: Fill this out and move to invocations
-@invocation("iterate", version="1.0.0")
+@invocation("iterate", version="1.1.0")
 class IterateInvocation(BaseInvocation):
     """Iterates over a list of items"""
 
@@ -221,7 +223,7 @@ class IterateInvocation(BaseInvocation):
 
     def invoke(self, context: InvocationContext) -> IterateInvocationOutput:
         """Produces the outputs as values"""
-        return IterateInvocationOutput(item=self.collection[self.index])
+        return IterateInvocationOutput(item=self.collection[self.index], index=self.index, total=len(self.collection))
 
 
 @invocation_output("collect_output")

invokeai/app/services/shared/sqlite.py

@@ -1,6 +1,7 @@
 import sqlite3
 import threading
 from logging import Logger
+from pathlib import Path
 
 from invokeai.app.services.config import InvokeAIAppConfig
 
@@ -8,25 +9,20 @@ sqlite_memory = ":memory:"
 
 
 class SqliteDatabase:
-    conn: sqlite3.Connection
-    lock: threading.RLock
-    _logger: Logger
-    _config: InvokeAIAppConfig
-
     def __init__(self, config: InvokeAIAppConfig, logger: Logger):
         self._logger = logger
         self._config = config
 
         if self._config.use_memory_db:
-            location = sqlite_memory
+            self.db_path = sqlite_memory
             logger.info("Using in-memory database")
         else:
             db_path = self._config.db_path
             db_path.parent.mkdir(parents=True, exist_ok=True)
-            location = str(db_path)
+            self.db_path = str(db_path)
-            self._logger.info(f"Using database at {location}")
+            self._logger.info(f"Using database at {self.db_path}")
 
-        self.conn = sqlite3.connect(location, check_same_thread=False)
+        self.conn = sqlite3.connect(self.db_path, check_same_thread=False)
         self.lock = threading.RLock()
         self.conn.row_factory = sqlite3.Row
 
@@ -37,10 +33,16 @@ class SqliteDatabase:
 
     def clean(self) -> None:
         try:
+            if self.db_path == sqlite_memory:
+                return
+            initial_db_size = Path(self.db_path).stat().st_size
             self.lock.acquire()
             self.conn.execute("VACUUM;")
             self.conn.commit()
-            self._logger.info("Cleaned database")
+            final_db_size = Path(self.db_path).stat().st_size
+            freed_space_in_mb = round((initial_db_size - final_db_size) / 1024 / 1024, 2)
+            if freed_space_in_mb > 0:
+                self._logger.info(f"Cleaned database (freed {freed_space_in_mb}MB)")
         except Exception as e:
             self._logger.error(f"Error cleaning database: {e}")
             raise e

invokeai/frontend/web/public/locales/it.json

@@ -91,7 +91,19 @@
         "controlNet": "ControlNet",
         "auto": "Automatico",
         "simple": "Semplice",
-        "details": "Dettagli"
+        "details": "Dettagli",
+        "format": "formato",
+        "unknown": "Sconosciuto",
+        "folder": "Cartella",
+        "error": "Errore",
+        "installed": "Installato",
+        "template": "Schema",
+        "outputs": "Uscite",
+        "data": "Dati",
+        "somethingWentWrong": "Qualcosa è andato storto",
+        "copyError": "$t(gallery.copy) Errore",
+        "input": "Ingresso",
+        "notInstalled": "Non $t(common.installed)"
     },
     "gallery": {
         "generations": "Generazioni",
@@ -122,7 +134,14 @@
         "preparingDownload": "Preparazione del download",
         "preparingDownloadFailed": "Problema durante la preparazione del download",
         "downloadSelection": "Scarica gli elementi selezionati",
-        "noImageSelected": "Nessuna immagine selezionata"
+        "noImageSelected": "Nessuna immagine selezionata",
+        "deleteSelection": "Elimina la selezione",
+        "image": "immagine",
+        "drop": "Rilascia",
+        "unstarImage": "Rimuovi preferenza immagine",
+        "dropOrUpload": "$t(gallery.drop) o carica",
+        "starImage": "Immagine preferita",
+        "dropToUpload": "$t(gallery.drop) per aggiornare"
     },
     "hotkeys": {
         "keyboardShortcuts": "Tasti rapidi",
@@ -477,7 +496,8 @@
         "modelType": "Tipo di modello",
         "customConfigFileLocation": "Posizione del file di configurazione personalizzato",
         "vaePrecision": "Precisione VAE",
-        "noModelSelected": "Nessun modello selezionato"
+        "noModelSelected": "Nessun modello selezionato",
+        "conversionNotSupported": "Conversione non supportata"
     },
     "parameters": {
         "images": "Immagini",
@@ -838,7 +858,8 @@
         "menu": "Menu",
         "showGalleryPanel": "Mostra il pannello Galleria",
         "loadMore": "Carica altro",
-        "mode": "Modalità"
+        "mode": "Modalità",
+        "resetUI": "$t(accessibility.reset) l'Interfaccia Utente"
     },
     "ui": {
         "hideProgressImages": "Nascondi avanzamento immagini",
@@ -1040,7 +1061,15 @@
         "updateAllNodes": "Aggiorna tutti i nodi",
         "unableToUpdateNodes_one": "Impossibile aggiornare {{count}} nodo",
         "unableToUpdateNodes_many": "Impossibile aggiornare {{count}} nodi",
-        "unableToUpdateNodes_other": "Impossibile aggiornare {{count}} nodi"
+        "unableToUpdateNodes_other": "Impossibile aggiornare {{count}} nodi",
+        "addLinearView": "Aggiungi alla vista Lineare",
+        "outputFieldInInput": "Campo di uscita in ingresso",
+        "unableToMigrateWorkflow": "Impossibile migrare il flusso di lavoro",
+        "unableToUpdateNode": "Impossibile aggiornare nodo",
+        "unknownErrorValidatingWorkflow": "Errore sconosciuto durante la convalida del flusso di lavoro",
+        "collectionFieldType": "{{name}} Raccolta",
+        "collectionOrScalarFieldType": "{{name}} Raccolta|Scalare",
+        "nodeVersion": "Versione Nodo"
     },
     "boards": {
         "autoAddBoard": "Aggiungi automaticamente bacheca",
@@ -1062,7 +1091,10 @@
         "deleteBoardOnly": "Elimina solo la Bacheca",
         "deleteBoard": "Elimina Bacheca",
         "deleteBoardAndImages": "Elimina Bacheca e Immagini",
-        "deletedBoardsCannotbeRestored": "Le bacheche eliminate non possono essere ripristinate"
+        "deletedBoardsCannotbeRestored": "Le bacheche eliminate non possono essere ripristinate",
+        "movingImagesToBoard_one": "Spostare {{count}} immagine nella bacheca:",
+        "movingImagesToBoard_many": "Spostare {{count}} immagini nella bacheca:",
+        "movingImagesToBoard_other": "Spostare {{count}} immagini nella bacheca:"
     },
     "controlnet": {
         "contentShuffleDescription": "Rimescola il contenuto di un'immagine",
@@ -1136,7 +1168,8 @@
         "megaControl": "Mega ControlNet",
         "minConfidence": "Confidenza minima",
         "scribble": "Scribble",
-        "amult": "Angolo di illuminazione"
+        "amult": "Angolo di illuminazione",
+        "coarse": "Approssimativo"
     },
     "queue": {
         "queueFront": "Aggiungi all'inizio della coda",
@@ -1204,7 +1237,8 @@
     "embedding": {
         "noMatchingEmbedding": "Nessun Incorporamento corrispondente",
         "addEmbedding": "Aggiungi Incorporamento",
-        "incompatibleModel": "Modello base incompatibile:"
+        "incompatibleModel": "Modello base incompatibile:",
+        "noEmbeddingsLoaded": "Nessun incorporamento caricato"
     },
     "models": {
         "noMatchingModels": "Nessun modello corrispondente",
@@ -1217,7 +1251,8 @@
         "noRefinerModelsInstalled": "Nessun modello SDXL Refiner installato",
         "noLoRAsInstalled": "Nessun LoRA installato",
         "esrganModel": "Modello ESRGAN",
-        "addLora": "Aggiungi LoRA"
+        "addLora": "Aggiungi LoRA",
+        "noLoRAsLoaded": "Nessuna LoRA caricata"
     },
     "invocationCache": {
         "disable": "Disabilita",
@@ -1233,7 +1268,8 @@
         "enable": "Abilita",
         "clear": "Svuota",
         "maxCacheSize": "Dimensione max cache",
-        "cacheSize": "Dimensione cache"
+        "cacheSize": "Dimensione cache",
+        "useCache": "Usa Cache"
     },
     "dynamicPrompts": {
         "seedBehaviour": {

invokeai/frontend/web/src/app/hooks/useSocketIO.ts

@@ -3,8 +3,8 @@ import { $authToken } from 'app/store/nanostores/authToken';
 import { $baseUrl } from 'app/store/nanostores/baseUrl';
 import { $isDebugging } from 'app/store/nanostores/isDebugging';
 import { useAppDispatch } from 'app/store/storeHooks';
-import { MapStore, WritableAtom, atom, map } from 'nanostores';
+import { MapStore, atom, map } from 'nanostores';
-import { useEffect } from 'react';
+import { useEffect, useMemo } from 'react';
 import {
   ClientToServerEvents,
   ServerToClientEvents,
@@ -16,57 +16,10 @@ import { ManagerOptions, Socket, SocketOptions, io } from 'socket.io-client';
 declare global {
   interface Window {
     $socketOptions?: MapStore<Partial<ManagerOptions & SocketOptions>>;
-    $socketUrl?: WritableAtom<string>;
   }
 }
 
-const makeSocketOptions = (): Partial<ManagerOptions & SocketOptions> => {
-  const socketOptions: Parameters<typeof io>[0] = {
-    timeout: 60000,
-    path: '/ws/socket.io',
-    autoConnect: false, // achtung! removing this breaks the dynamic middleware
-    forceNew: true,
-  };
-
-  // if building in package mode, replace socket url with open api base url minus the http protocol
-  if (['nodes', 'package'].includes(import.meta.env.MODE)) {
-    const authToken = $authToken.get();
-    if (authToken) {
-      // TODO: handle providing jwt to socket.io
-      socketOptions.auth = { token: authToken };
-    }
-
-    socketOptions.transports = ['websocket', 'polling'];
-  }
-
-  return socketOptions;
-};
-
-const makeSocketUrl = (): string => {
-  const wsProtocol = window.location.protocol === 'https:' ? 'wss' : 'ws';
-  let socketUrl = `${wsProtocol}://${window.location.host}`;
-  if (['nodes', 'package'].includes(import.meta.env.MODE)) {
-    const baseUrl = $baseUrl.get();
-    if (baseUrl) {
-      //eslint-disable-next-line
-      socketUrl = baseUrl.replace(/^https?\:\/\//i, '');
-    }
-  }
-  return socketUrl;
-};
-
-const makeSocket = (): Socket<ServerToClientEvents, ClientToServerEvents> => {
-  const socketOptions = makeSocketOptions();
-  const socketUrl = $socketUrl.get();
-  const socket: Socket<ServerToClientEvents, ClientToServerEvents> = io(
-    socketUrl,
-    { ...socketOptions, ...$socketOptions.get() }
-  );
-  return socket;
-};
-
 export const $socketOptions = map<Partial<ManagerOptions & SocketOptions>>({});
-export const $socketUrl = atom<string>(makeSocketUrl());
 export const $isSocketInitialized = atom<boolean>(false);
 
 /**
@@ -74,23 +27,50 @@ export const $isSocketInitialized = atom<boolean>(false);
  */
 export const useSocketIO = () => {
   const dispatch = useAppDispatch();
-  const socketOptions = useStore($socketOptions);
-  const socketUrl = useStore($socketUrl);
   const baseUrl = useStore($baseUrl);
   const authToken = useStore($authToken);
+  const addlSocketOptions = useStore($socketOptions);
+
+  const socketUrl = useMemo(() => {
+    const wsProtocol = window.location.protocol === 'https:' ? 'wss' : 'ws';
+    if (baseUrl) {
+      return baseUrl.replace(/^https?:\/\//i, '');
+    }
+
+    return `${wsProtocol}://${window.location.host}`;
+  }, [baseUrl]);
+
+  const socketOptions = useMemo(() => {
+    const options: Parameters<typeof io>[0] = {
+      timeout: 60000,
+      path: '/ws/socket.io',
+      autoConnect: false, // achtung! removing this breaks the dynamic middleware
+      forceNew: true,
+    };
+
+    if (authToken) {
+      options.auth = { token: authToken };
+      options.transports = ['websocket', 'polling'];
+    }
+
+    return { ...options, ...addlSocketOptions };
+  }, [authToken, addlSocketOptions]);
 
   useEffect(() => {
     if ($isSocketInitialized.get()) {
       // Singleton!
       return;
     }
-    const socket = makeSocket();
+
+    const socket: Socket<ServerToClientEvents, ClientToServerEvents> = io(
+      socketUrl,
+      socketOptions
+    );
     setEventListeners({ dispatch, socket });
     socket.connect();
 
     if ($isDebugging.get()) {
       window.$socketOptions = $socketOptions;
-      window.$socketUrl = $socketUrl;
       console.log('Socket initialized', socket);
     }
 
@@ -99,11 +79,10 @@ export const useSocketIO = () => {
     return () => {
       if ($isDebugging.get()) {
         window.$socketOptions = undefined;
-        window.$socketUrl = undefined;
         console.log('Socket teardown', socket);
       }
       socket.disconnect();
       $isSocketInitialized.set(false);
     };
-  }, [dispatch, socketOptions, socketUrl, baseUrl, authToken]);
+  }, [dispatch, socketOptions, socketUrl]);
 };

invokeai/frontend/web/src/features/gallery/components/Boards/BoardContextMenu.tsx

@@ -73,7 +73,13 @@ const BoardContextMenu = ({
         addToast({
           title: t('gallery.preparingDownload'),
           status: 'success',
-          ...(response.response ? { description: response.response } : {}),
+          ...(response.response
+            ? {
+                description: response.response,
+                duration: null,
+                isClosable: true,
+              }
+            : {}),
         })
       );
     } catch {

invokeai/frontend/web/src/features/gallery/components/ImageContextMenu/MultipleSelectionMenuItems.tsx

@@ -59,7 +59,13 @@ const MultipleSelectionMenuItems = () => {
         addToast({
           title: t('gallery.preparingDownload'),
           status: 'success',
-          ...(response.response ? { description: response.response } : {}),
+          ...(response.response
+            ? {
+                description: response.response,
+                duration: null,
+                isClosable: true,
+              }
+            : {}),
         })
       );
     } catch {

pyproject.toml

@@ -54,7 +54,8 @@ dependencies = [
   "invisible-watermark~=0.2.0",            # needed to install SDXL base and refiner using their repo_ids
   "matplotlib",                            # needed for plotting of Penner easing functions
   "mediapipe",                             # needed for "mediapipeface" controlnet model
-  "numpy",
+  # Minimum numpy version of 1.24.0 is needed to use the 'strict' argument to np.testing.assert_array_equal().
+  "numpy>=1.24.0",
   "npyscreen",
   "omegaconf",
   "onnx",