Merge branch 'main' into ace_plus_plus_patch-pr

Author: Attashe

docs/contributing/dev-environment.md

@@ -41,7 +41,7 @@ If you just want to use Invoke, you should use the [launcher][launcher link].
      With the modifications made, the install command should look something like this:
 
       ```sh
-      uv pip install -e ".[dev,test,docs,xformers]" --python 3.12 --python-preference only-managed --index=https://download.pytorch.org/whl/cu124 --reinstall
+      uv pip install -e ".[dev,test,docs,xformers]" --python 3.12 --python-preference only-managed --index=https://download.pytorch.org/whl/cu126 --reinstall
       ```
 
 6. At this point, you should have Invoke installed, a venv set up and activated, and the server running. But you will see a warning in the terminal that no UI was found. If you go to the URL for the server, you won't get a UI.

docs/installation/manual.md

@@ -71,7 +71,14 @@ The following commands vary depending on the version of Invoke being installed a
 
 7. Determine the `PyPI` index URL to use for installation, if any. This is necessary to get the right version of torch installed.
 
-    === "Invoke v5 or later"
+    === "Invoke v5.10.0 and later"
+
+        - If you are on Windows or Linux with an Nvidia GPU, use `https://download.pytorch.org/whl/cu126`.
+        - If you are on Linux with no GPU, use `https://download.pytorch.org/whl/cpu`.
+        - If you are on Linux with an AMD GPU, use `https://download.pytorch.org/whl/rocm6.2.4`.
+        - **In all other cases, do not use an index.**
+
+    === "Invoke v5.0.0 to v5.9.1"
 
         - If you are on Windows with an Nvidia GPU, use `https://download.pytorch.org/whl/cu124`.
         - If you are on Linux with no GPU, use `https://download.pytorch.org/whl/cpu`.

invokeai/app/api/dependencies.py

@@ -113,7 +113,6 @@ def initialize(
                 safe_globals=[torch.Tensor],
                 ephemeral=True,
             ),
-            max_cache_size=0,
         )
         conditioning = ObjectSerializerForwardCache(
             ObjectSerializerDisk[ConditioningFieldData](

invokeai/app/invocations/metadata_linked.py

@@ -39,7 +39,17 @@
     VAEField,
     VAEOutput,
 )
-from invokeai.app.invocations.primitives import BooleanOutput, FloatOutput, IntegerOutput, LatentsOutput, StringOutput
+from invokeai.app.invocations.primitives import (
+    BooleanCollectionOutput,
+    BooleanOutput,
+    FloatCollectionOutput,
+    FloatOutput,
+    IntegerCollectionOutput,
+    IntegerOutput,
+    LatentsOutput,
+    StringCollectionOutput,
+    StringOutput,
+)
 from invokeai.app.invocations.scheduler import SchedulerOutput
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField, T2IAdapterInvocation
 from invokeai.app.services.shared.invocation_context import InvocationContext
@@ -1162,3 +1172,133 @@ def invoke(self, context: InvocationContext) -> MDT2IAdapterListOutput:
             adapters = append_list(T2IAdapterField, i.t2i_adapter, adapters)
 
         return MDT2IAdapterListOutput(t2i_adapter_list=adapters)
+
+
+@invocation(
+    "metadata_to_string_collection",
+    title="Metadata To String Collection",
+    tags=["metadata"],
+    category="metadata",
+    version="1.0.0",
+    classification=Classification.Beta,
+)
+class MetadataToStringCollectionInvocation(BaseInvocation, WithMetadata):
+    """Extracts a string collection value of a label from metadata"""
+
+    label: CORE_LABELS_STRING = InputField(
+        default=CUSTOM_LABEL,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    custom_label: Optional[str] = InputField(
+        default=None,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    default_value: list[str] = InputField(
+        description="The default string collection to use if not found in the metadata"
+    )
+
+    _validate_custom_label = model_validator(mode="after")(validate_custom_label)
+
+    def invoke(self, context: InvocationContext) -> StringCollectionOutput:
+        data: Dict[str, Any] = {} if self.metadata is None else self.metadata.root
+        output = data.get(str(self.custom_label if self.label == CUSTOM_LABEL else self.label), self.default_value)
+
+        return StringCollectionOutput(collection=output)
+
+
+@invocation(
+    "metadata_to_integer_collection",
+    title="Metadata To Integer Collection",
+    tags=["metadata"],
+    category="metadata",
+    version="1.0.0",
+    classification=Classification.Beta,
+)
+class MetadataToIntegerCollectionInvocation(BaseInvocation, WithMetadata):
+    """Extracts an integer value Collection of a label from metadata"""
+
+    label: CORE_LABELS_INTEGER = InputField(
+        default=CUSTOM_LABEL,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    custom_label: Optional[str] = InputField(
+        default=None,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    default_value: list[int] = InputField(description="The default integer to use if not found in the metadata")
+
+    _validate_custom_label = model_validator(mode="after")(validate_custom_label)
+
+    def invoke(self, context: InvocationContext) -> IntegerCollectionOutput:
+        data: Dict[str, Any] = {} if self.metadata is None else self.metadata.root
+        output = data.get(str(self.custom_label if self.label == CUSTOM_LABEL else self.label), self.default_value)
+
+        return IntegerCollectionOutput(collection=output)
+
+
+@invocation(
+    "metadata_to_float_collection",
+    title="Metadata To Float Collection",
+    tags=["metadata"],
+    category="metadata",
+    version="1.0.0",
+    classification=Classification.Beta,
+)
+class MetadataToFloatCollectionInvocation(BaseInvocation, WithMetadata):
+    """Extracts a Float value Collection of a label from metadata"""
+
+    label: CORE_LABELS_FLOAT = InputField(
+        default=CUSTOM_LABEL,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    custom_label: Optional[str] = InputField(
+        default=None,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    default_value: list[float] = InputField(description="The default float to use if not found in the metadata")
+
+    _validate_custom_label = model_validator(mode="after")(validate_custom_label)
+
+    def invoke(self, context: InvocationContext) -> FloatCollectionOutput:
+        data: Dict[str, Any] = {} if self.metadata is None else self.metadata.root
+        output = data.get(str(self.custom_label if self.label == CUSTOM_LABEL else self.label), self.default_value)
+
+        return FloatCollectionOutput(collection=output)
+
+
+@invocation(
+    "metadata_to_bool_collection",
+    title="Metadata To Bool Collection",
+    tags=["metadata"],
+    category="metadata",
+    version="1.0.0",
+    classification=Classification.Beta,
+)
+class MetadataToBoolCollectionInvocation(BaseInvocation, WithMetadata):
+    """Extracts a Boolean value Collection of a label from metadata"""
+
+    label: CORE_LABELS_BOOL = InputField(
+        default=CUSTOM_LABEL,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    custom_label: Optional[str] = InputField(
+        default=None,
+        description=FieldDescriptions.metadata_item_label,
+        input=Input.Direct,
+    )
+    default_value: list[bool] = InputField(description="The default bool to use if not found in the metadata")
+
+    _validate_custom_label = model_validator(mode="after")(validate_custom_label)
+
+    def invoke(self, context: InvocationContext) -> BooleanCollectionOutput:
+        data: Dict[str, Any] = {} if self.metadata is None else self.metadata.root
+        output = data.get(str(self.custom_label if self.label == CUSTOM_LABEL else self.label), self.default_value)
+
+        return BooleanCollectionOutput(collection=output)

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

@@ -2393,9 +2393,8 @@
     "whatsNew": {
         "whatsNewInInvoke": "What's New in Invoke",
         "items": [
-            "Workflows: Support for custom string drop-downs in Workflow Builder.",
-            "FLUX: Support for FLUX Fill in Workflows and Canvas.",
-            "LLaVA OneVision VLLM: Beta support in Workflows."
+            "CogView4: Support for CogView4 models in Canvas and Workflows.",
+            "Updated Dependencies: Invoke now runs on the latest version of its dependencies, including Python 3.12 and Pytorch 2.6.0."
         ],
         "readReleaseNotes": "Read Release Notes",
         "watchRecentReleaseVideos": "Watch Recent Release Videos",

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

@@ -636,7 +636,8 @@
         "urlUnauthorizedErrorMessage2": "Scopri come qui.",
         "urlForbidden": "Non hai accesso a questo modello",
         "urlForbiddenErrorMessage": "Potrebbe essere necessario richiedere l'autorizzazione al sito che distribuisce il modello.",
-        "urlUnauthorizedErrorMessage": "Potrebbe essere necessario configurare un gettone API per accedere a questo modello."
+        "urlUnauthorizedErrorMessage": "Potrebbe essere necessario configurare un gettone API per accedere a questo modello.",
+        "fileSize": "Dimensione del file"
     },
     "parameters": {
         "images": "Immagini",
@@ -717,7 +718,8 @@
             "collectionNumberGTExclusiveMax": "{{value}} >= {{exclusiveMaximum}} (excl max)",
             "collectionNumberLTExclusiveMin": "{{value}} <= {{exclusiveMinimum}} (excl min)",
             "collectionEmpty": "raccolta vuota",
-            "batchNodeCollectionSizeMismatchNoGroupId": "Dimensione della raccolta di gruppo nel Lotto non corrisponde"
+            "batchNodeCollectionSizeMismatchNoGroupId": "Dimensione della raccolta di gruppo nel Lotto non corrisponde",
+            "modelIncompatibleBboxWidth": "La larghezza del riquadro di delimitazione è {{width}} ma {{model}} richiede multipli di {{multiple}}"
         },
         "useCpuNoise": "Usa la CPU per generare rumore",
         "iterations": "Iterazioni",
@@ -1807,7 +1809,6 @@
             "unpublishableInputs": "Questi input non pubblicabili verranno omessi",
             "publishWarnings": "Avvertenze",
             "errorWorkflowHasUnsavedChanges": "Il flusso di lavoro presenta modifiche non salvate",
-            "errorWorkflowHasBatchOrGeneratorNodes": "Il flusso di lavoro ha nodi lotto e/o generatori",
             "errorWorkflowHasInvalidGraph": "Grafico del flusso di lavoro non valido (passare il mouse sul pulsante Invoke per i dettagli)",
             "errorWorkflowHasNoOutputNode": "Nessun nodo di uscita selezionato",
             "warningWorkflowHasUnpublishableInputFields": "Il flusso di lavoro presenta alcuni ingressi non pubblicabili: questi verranno omessi dal flusso di lavoro pubblicato",
@@ -2399,8 +2400,7 @@
         "watchUiUpdatesOverview": "Guarda le novità dell'interfaccia",
         "items": [
             "Flussi di lavoro: supporto per menu a discesa di stringhe personalizzate nel Generatore di Flussi di lavoro.",
-            "FLUX: supporto per FLUX Fill in Flussi di lavoro e Tela.",
-            "LLaVA OneVision VLLM: supporto beta nei flussi di lavoro."
+            "FLUX: supporto per FLUX Fill in Flussi di lavoro e Tela."
         ]
     },
     "system": {