From a3cb5da130280d380cbb7bf4492f8cf50ebd060b Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lincoln.stein@gmail.com>
Date: Thu, 13 Jun 2024 13:10:03 -0400
Subject: [PATCH 01/24] Improve RAM<->VRAM memory copy performance in LoRA
 patching and elsewhere (#6490)

* allow model patcher to optimize away the unpatching step when feasible

* remove lazy_offloading functionality

* allow model patcher to optimize away the unpatching step when feasible

* remove lazy_offloading functionality

* do not save original weights if there is a CPU copy of state dict

* Update invokeai/backend/model_manager/load/load_base.py

Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>

* documentation fixes requested during penultimate review

* add non-blocking=True parameters to several torch.nn.Module.to() calls, for slight performance increases

* fix ruff errors

* prevent crash on non-cuda-enabled systems

---------

Co-authored-by: Lincoln Stein <lstein@gmail.com>
Co-authored-by: Kent Keirsey <31807370+hipsterusername@users.noreply.github.com>
Co-authored-by: Ryan Dick <ryanjdick3@gmail.com>
---
 invokeai/backend/ip_adapter/ip_adapter.py     | 11 ++--
 invokeai/backend/lora.py                      | 51 +++++++++++--------
 .../load/model_cache/model_cache_default.py   |  4 +-
 invokeai/backend/model_patcher.py             | 16 +++---
 invokeai/backend/onnx/onnx_runtime.py         | 10 ++++
 invokeai/backend/raw_model.py                 | 18 ++++++-
 invokeai/backend/textual_inversion.py         | 12 +++++
 7 files changed, 84 insertions(+), 38 deletions(-)

diff --git a/invokeai/backend/ip_adapter/ip_adapter.py b/invokeai/backend/ip_adapter/ip_adapter.py
index f3be042146..c33cb3f4ab 100644
--- a/invokeai/backend/ip_adapter/ip_adapter.py
+++ b/invokeai/backend/ip_adapter/ip_adapter.py
@@ -125,13 +125,16 @@ class IPAdapter(RawModel):
             self.device, dtype=self.dtype
         )
 
-    def to(self, device: torch.device, dtype: Optional[torch.dtype] = None):
-        self.device = device
+    def to(
+        self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None, non_blocking: bool = False
+    ):
+        if device is not None:
+            self.device = device
         if dtype is not None:
             self.dtype = dtype
 
-        self._image_proj_model.to(device=self.device, dtype=self.dtype)
-        self.attn_weights.to(device=self.device, dtype=self.dtype)
+        self._image_proj_model.to(device=self.device, dtype=self.dtype, non_blocking=non_blocking)
+        self.attn_weights.to(device=self.device, dtype=self.dtype, non_blocking=non_blocking)
 
     def calc_size(self):
         # workaround for circular import
diff --git a/invokeai/backend/lora.py b/invokeai/backend/lora.py
index 0b7128034a..f7c3863a6a 100644
--- a/invokeai/backend/lora.py
+++ b/invokeai/backend/lora.py
@@ -61,9 +61,10 @@ class LoRALayerBase:
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
     ) -> None:
         if self.bias is not None:
-            self.bias = self.bias.to(device=device, dtype=dtype)
+            self.bias = self.bias.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
 
 # TODO: find and debug lora/locon with bias
@@ -109,14 +110,15 @@ class LoRALayer(LoRALayerBase):
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
     ) -> None:
-        super().to(device=device, dtype=dtype)
+        super().to(device=device, dtype=dtype, non_blocking=non_blocking)
 
-        self.up = self.up.to(device=device, dtype=dtype)
-        self.down = self.down.to(device=device, dtype=dtype)
+        self.up = self.up.to(device=device, dtype=dtype, non_blocking=non_blocking)
+        self.down = self.down.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
         if self.mid is not None:
-            self.mid = self.mid.to(device=device, dtype=dtype)
+            self.mid = self.mid.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
 
 class LoHALayer(LoRALayerBase):
@@ -169,18 +171,19 @@ class LoHALayer(LoRALayerBase):
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
     ) -> None:
         super().to(device=device, dtype=dtype)
 
-        self.w1_a = self.w1_a.to(device=device, dtype=dtype)
-        self.w1_b = self.w1_b.to(device=device, dtype=dtype)
+        self.w1_a = self.w1_a.to(device=device, dtype=dtype, non_blocking=non_blocking)
+        self.w1_b = self.w1_b.to(device=device, dtype=dtype, non_blocking=non_blocking)
         if self.t1 is not None:
-            self.t1 = self.t1.to(device=device, dtype=dtype)
+            self.t1 = self.t1.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
-        self.w2_a = self.w2_a.to(device=device, dtype=dtype)
-        self.w2_b = self.w2_b.to(device=device, dtype=dtype)
+        self.w2_a = self.w2_a.to(device=device, dtype=dtype, non_blocking=non_blocking)
+        self.w2_b = self.w2_b.to(device=device, dtype=dtype, non_blocking=non_blocking)
         if self.t2 is not None:
-            self.t2 = self.t2.to(device=device, dtype=dtype)
+            self.t2 = self.t2.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
 
 class LoKRLayer(LoRALayerBase):
@@ -265,6 +268,7 @@ class LoKRLayer(LoRALayerBase):
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
     ) -> None:
         super().to(device=device, dtype=dtype)
 
@@ -273,19 +277,19 @@ class LoKRLayer(LoRALayerBase):
         else:
             assert self.w1_a is not None
             assert self.w1_b is not None
-            self.w1_a = self.w1_a.to(device=device, dtype=dtype)
-            self.w1_b = self.w1_b.to(device=device, dtype=dtype)
+            self.w1_a = self.w1_a.to(device=device, dtype=dtype, non_blocking=non_blocking)
+            self.w1_b = self.w1_b.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
         if self.w2 is not None:
-            self.w2 = self.w2.to(device=device, dtype=dtype)
+            self.w2 = self.w2.to(device=device, dtype=dtype, non_blocking=non_blocking)
         else:
             assert self.w2_a is not None
             assert self.w2_b is not None
-            self.w2_a = self.w2_a.to(device=device, dtype=dtype)
-            self.w2_b = self.w2_b.to(device=device, dtype=dtype)
+            self.w2_a = self.w2_a.to(device=device, dtype=dtype, non_blocking=non_blocking)
+            self.w2_b = self.w2_b.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
         if self.t2 is not None:
-            self.t2 = self.t2.to(device=device, dtype=dtype)
+            self.t2 = self.t2.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
 
 class FullLayer(LoRALayerBase):
@@ -319,10 +323,11 @@ class FullLayer(LoRALayerBase):
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
     ) -> None:
         super().to(device=device, dtype=dtype)
 
-        self.weight = self.weight.to(device=device, dtype=dtype)
+        self.weight = self.weight.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
 
 class IA3Layer(LoRALayerBase):
@@ -358,11 +363,12 @@ class IA3Layer(LoRALayerBase):
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
     ):
         super().to(device=device, dtype=dtype)
 
-        self.weight = self.weight.to(device=device, dtype=dtype)
-        self.on_input = self.on_input.to(device=device, dtype=dtype)
+        self.weight = self.weight.to(device=device, dtype=dtype, non_blocking=non_blocking)
+        self.on_input = self.on_input.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
 
 AnyLoRALayer = Union[LoRALayer, LoHALayer, LoKRLayer, FullLayer, IA3Layer]
@@ -388,10 +394,11 @@ class LoRAModelRaw(RawModel):  # (torch.nn.Module):
         self,
         device: Optional[torch.device] = None,
         dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
     ) -> None:
         # TODO: try revert if exception?
         for _key, layer in self.layers.items():
-            layer.to(device=device, dtype=dtype)
+            layer.to(device=device, dtype=dtype, non_blocking=non_blocking)
 
     def calc_size(self) -> int:
         model_size = 0
@@ -514,7 +521,7 @@ class LoRAModelRaw(RawModel):  # (torch.nn.Module):
             # lower memory consumption by removing already parsed layer values
             state_dict[layer_key].clear()
 
-            layer.to(device=device, dtype=dtype)
+            layer.to(device=device, dtype=dtype, non_blocking=True)
             model.layers[layer_key] = layer
 
         return model
diff --git a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
index 335a15a5c8..d48e45426e 100644
--- a/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
+++ b/invokeai/backend/model_manager/load/model_cache/model_cache_default.py
@@ -285,9 +285,9 @@ class ModelCache(ModelCacheBase[AnyModel]):
                 else:
                     new_dict: Dict[str, torch.Tensor] = {}
                     for k, v in cache_entry.state_dict.items():
-                        new_dict[k] = v.to(torch.device(target_device), copy=True)
+                        new_dict[k] = v.to(torch.device(target_device), copy=True, non_blocking=True)
                     cache_entry.model.load_state_dict(new_dict, assign=True)
-            cache_entry.model.to(target_device)
+            cache_entry.model.to(target_device, non_blocking=True)
             cache_entry.device = target_device
         except Exception as e:  # blow away cache entry
             self._delete_cache_entry(cache_entry)
diff --git a/invokeai/backend/model_patcher.py b/invokeai/backend/model_patcher.py
index c407cd8472..fdc79539ae 100644
--- a/invokeai/backend/model_patcher.py
+++ b/invokeai/backend/model_patcher.py
@@ -67,7 +67,7 @@ class ModelPatcher:
         unet: UNet2DConditionModel,
         loras: Iterator[Tuple[LoRAModelRaw, float]],
         model_state_dict: Optional[Dict[str, torch.Tensor]] = None,
-    ) -> None:
+    ) -> Generator[None, None, None]:
         with cls.apply_lora(
             unet,
             loras=loras,
@@ -83,7 +83,7 @@ class ModelPatcher:
         text_encoder: CLIPTextModel,
         loras: Iterator[Tuple[LoRAModelRaw, float]],
         model_state_dict: Optional[Dict[str, torch.Tensor]] = None,
-    ) -> None:
+    ) -> Generator[None, None, None]:
         with cls.apply_lora(text_encoder, loras=loras, prefix="lora_te_", model_state_dict=model_state_dict):
             yield
 
@@ -95,7 +95,7 @@ class ModelPatcher:
         loras: Iterator[Tuple[LoRAModelRaw, float]],
         prefix: str,
         model_state_dict: Optional[Dict[str, torch.Tensor]] = None,
-    ) -> Generator[Any, None, None]:
+    ) -> Generator[None, None, None]:
         """
         Apply one or more LoRAs to a model.
 
@@ -139,12 +139,12 @@ class ModelPatcher:
                         # We intentionally move to the target device first, then cast. Experimentally, this was found to
                         # be significantly faster for 16-bit CPU tensors being moved to a CUDA device than doing the
                         # same thing in a single call to '.to(...)'.
-                        layer.to(device=device)
-                        layer.to(dtype=torch.float32)
+                        layer.to(device=device, non_blocking=True)
+                        layer.to(dtype=torch.float32, non_blocking=True)
                         # TODO(ryand): Using torch.autocast(...) over explicit casting may offer a speed benefit on CUDA
                         # devices here. Experimentally, it was found to be very slow on CPU. More investigation needed.
                         layer_weight = layer.get_weight(module.weight) * (lora_weight * layer_scale)
-                        layer.to(device=torch.device("cpu"))
+                        layer.to(device=torch.device("cpu"), non_blocking=True)
 
                         assert isinstance(layer_weight, torch.Tensor)  # mypy thinks layer_weight is a float|Any ??!
                         if module.weight.shape != layer_weight.shape:
@@ -153,7 +153,7 @@ class ModelPatcher:
                             layer_weight = layer_weight.reshape(module.weight.shape)
 
                         assert isinstance(layer_weight, torch.Tensor)  # mypy thinks layer_weight is a float|Any ??!
-                        module.weight += layer_weight.to(dtype=dtype)
+                        module.weight += layer_weight.to(dtype=dtype, non_blocking=True)
 
             yield  # wait for context manager exit
 
@@ -161,7 +161,7 @@ class ModelPatcher:
             assert hasattr(model, "get_submodule")  # mypy not picking up fact that torch.nn.Module has get_submodule()
             with torch.no_grad():
                 for module_key, weight in original_weights.items():
-                    model.get_submodule(module_key).weight.copy_(weight)
+                    model.get_submodule(module_key).weight.copy_(weight, non_blocking=True)
 
     @classmethod
     @contextmanager
diff --git a/invokeai/backend/onnx/onnx_runtime.py b/invokeai/backend/onnx/onnx_runtime.py
index 8916865dd5..9fcd4d093f 100644
--- a/invokeai/backend/onnx/onnx_runtime.py
+++ b/invokeai/backend/onnx/onnx_runtime.py
@@ -6,6 +6,7 @@ from typing import Any, List, Optional, Tuple, Union
 
 import numpy as np
 import onnx
+import torch
 from onnx import numpy_helper
 from onnxruntime import InferenceSession, SessionOptions, get_available_providers
 
@@ -188,6 +189,15 @@ class IAIOnnxRuntimeModel(RawModel):
         # return self.io_binding.copy_outputs_to_cpu()
         return self.session.run(None, inputs)
 
+    # compatability with RawModel ABC
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
+    ) -> None:
+        pass
+
     # compatability with diffusers load code
     @classmethod
     def from_pretrained(
diff --git a/invokeai/backend/raw_model.py b/invokeai/backend/raw_model.py
index d0dc50c456..7bca6945d9 100644
--- a/invokeai/backend/raw_model.py
+++ b/invokeai/backend/raw_model.py
@@ -10,6 +10,20 @@ The term 'raw' was introduced to describe a wrapper around a torch.nn.Module
 that adds additional methods and attributes.
 """
 
+from abc import ABC, abstractmethod
+from typing import Optional
 
-class RawModel:
-    """Base class for 'Raw' model wrappers."""
+import torch
+
+
+class RawModel(ABC):
+    """Abstract base class for 'Raw' model wrappers."""
+
+    @abstractmethod
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
+    ) -> None:
+        pass
diff --git a/invokeai/backend/textual_inversion.py b/invokeai/backend/textual_inversion.py
index 98104f769e..0408176edb 100644
--- a/invokeai/backend/textual_inversion.py
+++ b/invokeai/backend/textual_inversion.py
@@ -65,6 +65,18 @@ class TextualInversionModelRaw(RawModel):
 
         return result
 
+    def to(
+        self,
+        device: Optional[torch.device] = None,
+        dtype: Optional[torch.dtype] = None,
+        non_blocking: bool = False,
+    ) -> None:
+        if not torch.cuda.is_available():
+            return
+        for emb in [self.embedding, self.embedding_2]:
+            if emb is not None:
+                emb.to(device=device, dtype=dtype, non_blocking=non_blocking)
+
 
 class TextualInversionManager(BaseTextualInversionManager):
     """TextualInversionManager implements the BaseTextualInversionManager ABC from the compel library."""

From 785bb1d9e446987b64a41491a1517e207793655c Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Thu, 6 Jun 2024 09:16:45 -0400
Subject: [PATCH 02/24] Fix all comparisons against the DEFAULT_PRECISION
 constant. DEFAULT_PRECISION is a torch.dtype. Previously, it was compared to
 a str in a number of places where it would always resolve to False. This is a
 bugfix that results in a change to the default behavior. In practice, this
 will not change the behavior for many users, because it only causes a change
 in behavior if a users has configured float32 as their default precision.

---
 invokeai/app/invocations/constants.py            | 3 +++
 invokeai/app/invocations/create_denoise_mask.py  | 4 ++--
 invokeai/app/invocations/create_gradient_mask.py | 4 ++--
 invokeai/app/invocations/denoise_latents.py      | 2 --
 invokeai/app/invocations/image_to_latents.py     | 4 ++--
 invokeai/app/invocations/latents_to_image.py     | 4 ++--
 6 files changed, 11 insertions(+), 10 deletions(-)

diff --git a/invokeai/app/invocations/constants.py b/invokeai/app/invocations/constants.py
index cebe0eb30f..e01589be81 100644
--- a/invokeai/app/invocations/constants.py
+++ b/invokeai/app/invocations/constants.py
@@ -1,6 +1,7 @@
 from typing import Literal
 
 from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
+from invokeai.backend.util.devices import TorchDevice
 
 LATENT_SCALE_FACTOR = 8
 """
@@ -15,3 +16,5 @@ SCHEDULER_NAME_VALUES = Literal[tuple(SCHEDULER_MAP.keys())]
 
 IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
 """A literal type for PIL image modes supported by Invoke"""
+
+DEFAULT_PRECISION = TorchDevice.choose_torch_dtype()
diff --git a/invokeai/app/invocations/create_denoise_mask.py b/invokeai/app/invocations/create_denoise_mask.py
index d128e0efec..2d66c20dbd 100644
--- a/invokeai/app/invocations/create_denoise_mask.py
+++ b/invokeai/app/invocations/create_denoise_mask.py
@@ -6,7 +6,7 @@ from PIL import Image
 from torchvision.transforms.functional import resize as tv_resize
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION
+from invokeai.app.invocations.constants import DEFAULT_PRECISION
 from invokeai.app.invocations.fields import FieldDescriptions, ImageField, Input, InputField
 from invokeai.app.invocations.image_to_latents import ImageToLatentsInvocation
 from invokeai.app.invocations.model import VAEField
@@ -30,7 +30,7 @@ class CreateDenoiseMaskInvocation(BaseInvocation):
     mask: ImageField = InputField(description="The mask to use when pasting", ui_order=2)
     tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=3)
     fp32: bool = InputField(
-        default=DEFAULT_PRECISION == "float32",
+        default=DEFAULT_PRECISION == torch.float32,
         description=FieldDescriptions.fp32,
         ui_order=4,
     )
diff --git a/invokeai/app/invocations/create_gradient_mask.py b/invokeai/app/invocations/create_gradient_mask.py
index 2d2b13fdcc..089313463b 100644
--- a/invokeai/app/invocations/create_gradient_mask.py
+++ b/invokeai/app/invocations/create_gradient_mask.py
@@ -7,7 +7,7 @@ from PIL import Image, ImageFilter
 from torchvision.transforms.functional import resize as tv_resize
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, invocation, invocation_output
-from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION
+from invokeai.app.invocations.constants import DEFAULT_PRECISION
 from invokeai.app.invocations.fields import (
     DenoiseMaskField,
     FieldDescriptions,
@@ -74,7 +74,7 @@ class CreateGradientMaskInvocation(BaseInvocation):
     )
     tiled: bool = InputField(default=False, description=FieldDescriptions.tiled, ui_order=8)
     fp32: bool = InputField(
-        default=DEFAULT_PRECISION == "float32",
+        default=DEFAULT_PRECISION == torch.float32,
         description=FieldDescriptions.fp32,
         ui_order=9,
     )
diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py
index 3851caa647..7260fcb168 100644
--- a/invokeai/app/invocations/denoise_latents.py
+++ b/invokeai/app/invocations/denoise_latents.py
@@ -59,8 +59,6 @@ from .baseinvocation import BaseInvocation, invocation
 from .controlnet_image_processors import ControlField
 from .model import ModelIdentifierField, UNetField
 
-DEFAULT_PRECISION = TorchDevice.choose_torch_dtype()
-
 
 def get_scheduler(
     context: InvocationContext,
diff --git a/invokeai/app/invocations/image_to_latents.py b/invokeai/app/invocations/image_to_latents.py
index bf2eb414e1..06de530154 100644
--- a/invokeai/app/invocations/image_to_latents.py
+++ b/invokeai/app/invocations/image_to_latents.py
@@ -12,7 +12,7 @@ from diffusers.models.autoencoders.autoencoder_kl import AutoencoderKL
 from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION
+from invokeai.app.invocations.constants import DEFAULT_PRECISION
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     ImageField,
@@ -44,7 +44,7 @@ class ImageToLatentsInvocation(BaseInvocation):
         input=Input.Connection,
     )
     tiled: bool = InputField(default=False, description=FieldDescriptions.tiled)
-    fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32)
+    fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32)
 
     @staticmethod
     def vae_encode(vae_info: LoadedModel, upcast: bool, tiled: bool, image_tensor: torch.Tensor) -> torch.Tensor:
diff --git a/invokeai/app/invocations/latents_to_image.py b/invokeai/app/invocations/latents_to_image.py
index 648ee7ac68..202e8bfa1b 100644
--- a/invokeai/app/invocations/latents_to_image.py
+++ b/invokeai/app/invocations/latents_to_image.py
@@ -11,7 +11,7 @@ from diffusers.models.autoencoders.autoencoder_tiny import AutoencoderTiny
 from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
-from invokeai.app.invocations.denoise_latents import DEFAULT_PRECISION
+from invokeai.app.invocations.constants import DEFAULT_PRECISION
 from invokeai.app.invocations.fields import (
     FieldDescriptions,
     Input,
@@ -46,7 +46,7 @@ class LatentsToImageInvocation(BaseInvocation, WithMetadata, WithBoard):
         input=Input.Connection,
     )
     tiled: bool = InputField(default=False, description=FieldDescriptions.tiled)
-    fp32: bool = InputField(default=DEFAULT_PRECISION == "float32", description=FieldDescriptions.fp32)
+    fp32: bool = InputField(default=DEFAULT_PRECISION == torch.float32, description=FieldDescriptions.fp32)
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ImageOutput:

From aae318425d52af7a573f3fb4c0a6a00576ce2db2 Mon Sep 17 00:00:00 2001
From: chainchompa <chainchompa@gmail.com>
Date: Fri, 14 Jun 2024 17:08:39 -0400
Subject: [PATCH 03/24] added route for installing huggingface model from model
 marketplace

---
 invokeai/app/api/routers/model_manager.py | 76 ++++++++++++++++++++++-
 1 file changed, 75 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index b1221f7a34..01590b21be 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -9,7 +9,7 @@ from copy import deepcopy
 from typing import Any, Dict, List, Optional, Type
 
 from fastapi import Body, Path, Query, Response, UploadFile
-from fastapi.responses import FileResponse
+from fastapi.responses import FileResponse, HTMLResponse
 from fastapi.routing import APIRouter
 from PIL import Image
 from pydantic import AnyHttpUrl, BaseModel, ConfigDict, Field
@@ -501,6 +501,80 @@ async def install_model(
         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="Hugging Face repo_id to install"),
+) -> HTMLResponse:
+    """Install a Hugging Face model using a string identifier."""
+
+    def generate_html(message: str) -> str:
+        return f"""
+        <html>
+        <head>
+            <style>
+                body {{
+                    text-align: center;
+                    margin-top: 50px;
+                }}
+                .message-box {{
+                    display: inline-block;
+                    padding: 20px;
+                    border: 1px solid #ccc;
+                    border-radius: 5px;
+                    background-color: #f9f9f9;
+                    box-shadow: 0px 0px 10px rgba(0, 0, 0, 0.1);
+                }}
+            </style>
+        </head>
+        <body>
+            <div class="message-box">
+                <p>{message}</p>
+            </div>
+        </body>
+        </html>
+        """
+
+    try:
+        metadata = HuggingFaceMetadataFetch().from_id(source)
+        assert isinstance(metadata, ModelMetadataWithFiles)
+        message = "Your Hugging Face model is installing now. You can close this tab and check the Model Manager for installation progress."
+    except UnknownMetadataException:
+        message = "No HuggingFace repository found with that repo id."
+        return HTMLResponse(content=generate_html(message), status_code=400)
+
+    logger = ApiDependencies.invoker.services.logger
+
+    try:
+        installer = ApiDependencies.invoker.services.model_manager.install
+
+        if metadata.is_diffusers:
+            installer.heuristic_import(
+                source=source,
+                inplace=False,
+            )
+        elif metadata.ckpt_urls is not None and len(metadata.ckpt_urls) == 1:
+            installer.heuristic_import(
+                source=str(metadata.ckpt_urls[0]),
+                inplace=False,
+            )
+        else:
+            message = "This HuggingFace repo has multiple models. Please use the Model Manager to install this."
+    except Exception as e:
+        logger.error(str(e))
+        message = "There was an error with installing this model. Please use the Model Manager to install this."
+
+    return HTMLResponse(content=generate_html(message), status_code=201)
+
 
 @model_manager_router.get(
     "/install",

From 328f160e88b403b193f3a0708ffce4f878084ec5 Mon Sep 17 00:00:00 2001
From: chainchompa <chainchompa@gmail.com>
Date: Fri, 14 Jun 2024 17:09:07 -0400
Subject: [PATCH 04/24] refetch model installs when a new model install starts

---
 .../listeners/socketio/socketModelInstall.ts              | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index 7fafb8302c..adfa7edd06 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -6,9 +6,17 @@ import {
   socketModelInstallComplete,
   socketModelInstallDownloadProgress,
   socketModelInstallError,
+  socketModelInstallStarted,
 } from 'services/events/actions';
 
 export const addModelInstallEventListener = (startAppListening: AppStartListening) => {
+  startAppListening({
+    actionCreator: socketModelInstallStarted,
+    effect: async (action, { dispatch }) => {
+      dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+    },
+  });
+
   startAppListening({
     actionCreator: socketModelInstallDownloadProgress,
     effect: async (action, { dispatch }) => {

From 40299725304e3fa3271b2d6d746512b7c448e1cd Mon Sep 17 00:00:00 2001
From: chainchompa <chainchompa@gmail.com>
Date: Fri, 14 Jun 2024 17:15:55 -0400
Subject: [PATCH 05/24] formatting

---
 invokeai/app/api/routers/model_manager.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index 01590b21be..f2fb0932e5 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -501,6 +501,7 @@ async def install_model(
         raise HTTPException(status_code=409, detail=str(e))
     return result
 
+
 @model_manager_router.get(
     "/install/huggingface",
     operation_id="install_hugging_face_model",
@@ -510,7 +511,7 @@ async def install_model(
         409: {"description": "There is already a model corresponding to this path or repo_id"},
     },
     status_code=201,
-    response_class=HTMLResponse
+    response_class=HTMLResponse,
 )
 async def install_hugging_face_model(
     source: str = Query(description="Hugging Face repo_id to install"),

From 1bc98abc7626690b4f850b80a72dd4d4573190dc Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 17 Jun 2024 09:33:46 +1000
Subject: [PATCH 06/24] docs(ui): explain model install events

---
 .../listeners/socketio/socketModelInstall.ts      | 15 +++++++++++++++
 1 file changed, 15 insertions(+)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index adfa7edd06..113d2cbd66 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -9,6 +9,21 @@ import {
   socketModelInstallStarted,
 } from 'services/events/actions';
 
+/**
+ * A model install has two main stages - downloading and installing. All these events are namespaced under `model_install_`
+ * which is a bit misleading. For example, a `model_install_started` event is actually fired _after_ the model has fully
+ * downloaded and is being "physically" installed.
+ *
+ * Here's the expected flow:
+ * - Model manager does some prep
+ * - `model_install_download_progress` fired when the download starts and continually until the download is complete
+ * - `model_install_download_complete` fired when the download is complete
+ * - `model_install_started` fired when the "physical" installation starts
+ * - `model_install_complete` fired when the installation is complete
+ * - `model_install_cancelled` fired if the installation is cancelled
+ * - `model_install_error` fired if the installation has an error
+ */
+
 export const addModelInstallEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketModelInstallStarted,

From fb694b3e179733400676c8cc7bcbb1c7ae7ba60e Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 17 Jun 2024 09:50:25 +1000
Subject: [PATCH 07/24] feat(app): add `model_install_download_started` event

Previously, we used `model_install_download_progress` for both download starting and progressing. When handling this event, we don't know which actual thing it represents.

Add `model_install_download_started` event to explicitly represent a model download started event.
---
 invokeai/app/services/events/events_base.py   |  5 +++
 invokeai/app/services/events/events_common.py | 36 +++++++++++++++++++
 .../model_install/model_install_default.py    |  9 ++++-
 3 files changed, 49 insertions(+), 1 deletion(-)

diff --git a/invokeai/app/services/events/events_base.py b/invokeai/app/services/events/events_base.py
index cf49cc0626..bb578c23e8 100644
--- a/invokeai/app/services/events/events_base.py
+++ b/invokeai/app/services/events/events_base.py
@@ -22,6 +22,7 @@ from invokeai.app.services.events.events_common import (
     ModelInstallCompleteEvent,
     ModelInstallDownloadProgressEvent,
     ModelInstallDownloadsCompleteEvent,
+    ModelInstallDownloadStartedEvent,
     ModelInstallErrorEvent,
     ModelInstallStartedEvent,
     ModelLoadCompleteEvent,
@@ -144,6 +145,10 @@ class EventServiceBase:
 
     # region Model install
 
+    def emit_model_install_download_started(self, job: "ModelInstallJob") -> None:
+        """Emitted at intervals while the install job is started (remote models only)."""
+        self.dispatch(ModelInstallDownloadStartedEvent.build(job))
+
     def emit_model_install_download_progress(self, job: "ModelInstallJob") -> None:
         """Emitted at intervals while the install job is in progress (remote models only)."""
         self.dispatch(ModelInstallDownloadProgressEvent.build(job))
diff --git a/invokeai/app/services/events/events_common.py b/invokeai/app/services/events/events_common.py
index 0adcaa2ab1..c6a867fb08 100644
--- a/invokeai/app/services/events/events_common.py
+++ b/invokeai/app/services/events/events_common.py
@@ -417,6 +417,42 @@ class ModelLoadCompleteEvent(ModelEventBase):
         return cls(config=config, submodel_type=submodel_type)
 
 
+@payload_schema.register
+class ModelInstallDownloadStartedEvent(ModelEventBase):
+    """Event model for model_install_download_started"""
+
+    __event_name__ = "model_install_download_started"
+
+    id: int = Field(description="The ID of the install job")
+    source: str = Field(description="Source of the model; local path, repo_id or url")
+    local_path: str = Field(description="Where model is downloading to")
+    bytes: int = Field(description="Number of bytes downloaded so far")
+    total_bytes: int = Field(description="Total size of download, including all files")
+    parts: list[dict[str, int | str]] = Field(
+        description="Progress of downloading URLs that comprise the model, if any"
+    )
+
+    @classmethod
+    def build(cls, job: "ModelInstallJob") -> "ModelInstallDownloadStartedEvent":
+        parts: list[dict[str, str | int]] = [
+            {
+                "url": str(x.source),
+                "local_path": str(x.download_path),
+                "bytes": x.bytes,
+                "total_bytes": x.total_bytes,
+            }
+            for x in job.download_parts
+        ]
+        return cls(
+            id=job.id,
+            source=str(job.source),
+            local_path=job.local_path.as_posix(),
+            parts=parts,
+            bytes=job.bytes,
+            total_bytes=job.total_bytes,
+        )
+
+
 @payload_schema.register
 class ModelInstallDownloadProgressEvent(ModelEventBase):
     """Event model for model_install_download_progress"""
diff --git a/invokeai/app/services/model_install/model_install_default.py b/invokeai/app/services/model_install/model_install_default.py
index 0a2e2d798a..dd1b44d899 100644
--- a/invokeai/app/services/model_install/model_install_default.py
+++ b/invokeai/app/services/model_install/model_install_default.py
@@ -822,7 +822,7 @@ class ModelInstallService(ModelInstallServiceBase):
                 install_job.download_parts = download_job.download_parts
                 install_job.bytes = sum(x.bytes for x in download_job.download_parts)
                 install_job.total_bytes = download_job.total_bytes
-                self._signal_job_downloading(install_job)
+                self._signal_job_download_started(install_job)
 
     def _download_progress_callback(self, download_job: MultiFileDownloadJob) -> None:
         with self._lock:
@@ -874,6 +874,13 @@ class ModelInstallService(ModelInstallServiceBase):
         if self._event_bus:
             self._event_bus.emit_model_install_started(job)
 
+    def _signal_job_download_started(self, job: ModelInstallJob) -> None:
+        if self._event_bus:
+            assert job._multifile_job is not None
+            assert job.bytes is not None
+            assert job.total_bytes is not None
+            self._event_bus.emit_model_install_download_started(job)
+
     def _signal_job_downloading(self, job: ModelInstallJob) -> None:
         if self._event_bus:
             assert job._multifile_job is not None

From c11478a94ac53e9f61ff57ff69e75fb45d6504f2 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 17 Jun 2024 09:51:18 +1000
Subject: [PATCH 08/24] chore(ui): typegen

---
 .../frontend/web/src/services/api/schema.ts   | 435 +++++++++++-------
 1 file changed, 260 insertions(+), 175 deletions(-)

diff --git a/invokeai/frontend/web/src/services/api/schema.ts b/invokeai/frontend/web/src/services/api/schema.ts
index 5482b57c0b..fe2732d06b 100644
--- a/invokeai/frontend/web/src/services/api/schema.ts
+++ b/invokeai/frontend/web/src/services/api/schema.ts
@@ -123,6 +123,13 @@ export type paths = {
      */
     delete: operations["prune_model_install_jobs"];
   };
+  "/api/v2/models/install/huggingface": {
+    /**
+     * Install Hugging Face Model
+     * @description Install a Hugging Face model using a string identifier.
+     */
+    get: operations["install_hugging_face_model"];
+  };
   "/api/v2/models/install/{id}": {
     /**
      * Get Model Install Job
@@ -3788,23 +3795,6 @@ export type components = {
      * @description Class to monitor and control a model download request.
      */
     DownloadJob: {
-      /**
-       * Source
-       * Format: uri
-       * @description Where to download from. Specific types specified in child classes.
-       */
-      source: string;
-      /**
-       * Dest
-       * Format: path
-       * @description Destination of downloaded model on local disk; a directory or file path
-       */
-      dest: string;
-      /**
-       * Access Token
-       * @description authorization token for protected resources
-       */
-      access_token?: string | null;
       /**
        * Id
        * @description Numeric ID of this job
@@ -3812,36 +3802,21 @@ export type components = {
        */
       id?: number;
       /**
-       * Priority
-       * @description Queue priority; lower values are higher priority
-       * @default 10
+       * Dest
+       * Format: path
+       * @description Initial destination of downloaded model on local disk; a directory or file path
        */
-      priority?: number;
+      dest: string;
+      /**
+       * Download Path
+       * @description Final location of downloaded file or directory
+       */
+      download_path?: string | null;
       /**
        * @description Status of the download
        * @default waiting
        */
       status?: components["schemas"]["DownloadJobStatus"];
-      /**
-       * Download Path
-       * @description Final location of downloaded file
-       */
-      download_path?: string | null;
-      /**
-       * Job Started
-       * @description Timestamp for when the download job started
-       */
-      job_started?: string | null;
-      /**
-       * Job Ended
-       * @description Timestamp for when the download job ende1d (completed or errored)
-       */
-      job_ended?: string | null;
-      /**
-       * Content Type
-       * @description Content type of downloaded file
-       */
-      content_type?: string | null;
       /**
        * Bytes
        * @description Bytes downloaded so far
@@ -3864,6 +3839,38 @@ export type components = {
        * @description Traceback of the exception that caused an error
        */
       error?: string | null;
+      /**
+       * Source
+       * Format: uri
+       * @description Where to download from. Specific types specified in child classes.
+       */
+      source: string;
+      /**
+       * Access Token
+       * @description authorization token for protected resources
+       */
+      access_token?: string | null;
+      /**
+       * Priority
+       * @description Queue priority; lower values are higher priority
+       * @default 10
+       */
+      priority?: number;
+      /**
+       * Job Started
+       * @description Timestamp for when the download job started
+       */
+      job_started?: string | null;
+      /**
+       * Job Ended
+       * @description Timestamp for when the download job ende1d (completed or errored)
+       */
+      job_ended?: string | null;
+      /**
+       * Content Type
+       * @description Content type of downloaded file
+       */
+      content_type?: string | null;
     };
     /**
      * DownloadJobStatus
@@ -7276,144 +7283,144 @@ export type components = {
       project_id: string | null;
     };
     InvocationOutputMap: {
-      pidi_image_processor: components["schemas"]["ImageOutput"];
-      image_mask_to_tensor: components["schemas"]["MaskOutput"];
-      vae_loader: components["schemas"]["VAEOutput"];
-      collect: components["schemas"]["CollectInvocationOutput"];
-      string_join_three: components["schemas"]["StringOutput"];
-      content_shuffle_image_processor: components["schemas"]["ImageOutput"];
-      random_range: components["schemas"]["IntegerCollectionOutput"];
-      ip_adapter: components["schemas"]["IPAdapterOutput"];
-      step_param_easing: components["schemas"]["FloatCollectionOutput"];
-      core_metadata: components["schemas"]["MetadataOutput"];
-      main_model_loader: components["schemas"]["ModelLoaderOutput"];
-      leres_image_processor: components["schemas"]["ImageOutput"];
-      calculate_image_tiles_even_split: components["schemas"]["CalculateImageTilesOutput"];
-      color_correct: components["schemas"]["ImageOutput"];
-      calculate_image_tiles: components["schemas"]["CalculateImageTilesOutput"];
-      float_range: components["schemas"]["FloatCollectionOutput"];
-      infill_cv2: components["schemas"]["ImageOutput"];
-      img_channel_multiply: components["schemas"]["ImageOutput"];
-      img_pad_crop: components["schemas"]["ImageOutput"];
-      sdxl_refiner_compel_prompt: components["schemas"]["ConditioningOutput"];
-      face_mask_detection: components["schemas"]["FaceMaskOutput"];
-      infill_lama: components["schemas"]["ImageOutput"];
-      mask_combine: components["schemas"]["ImageOutput"];
-      sdxl_compel_prompt: components["schemas"]["ConditioningOutput"];
-      segment_anything_processor: components["schemas"]["ImageOutput"];
-      merge_metadata: components["schemas"]["MetadataOutput"];
-      img_ilerp: components["schemas"]["ImageOutput"];
-      heuristic_resize: components["schemas"]["ImageOutput"];
-      cv_inpaint: components["schemas"]["ImageOutput"];
-      div: components["schemas"]["IntegerOutput"];
-      pair_tile_image: components["schemas"]["PairTileImageOutput"];
-      float_math: components["schemas"]["FloatOutput"];
-      img_channel_offset: components["schemas"]["ImageOutput"];
-      canvas_paste_back: components["schemas"]["ImageOutput"];
-      canny_image_processor: components["schemas"]["ImageOutput"];
-      integer_collection: components["schemas"]["IntegerCollectionOutput"];
-      freeu: components["schemas"]["UNetOutput"];
-      lresize: components["schemas"]["LatentsOutput"];
-      range_of_size: components["schemas"]["IntegerCollectionOutput"];
-      depth_anything_image_processor: components["schemas"]["ImageOutput"];
-      float_to_int: components["schemas"]["IntegerOutput"];
-      rand_int: components["schemas"]["IntegerOutput"];
-      lineart_anime_image_processor: components["schemas"]["ImageOutput"];
-      string_split: components["schemas"]["String2Output"];
-      img_nsfw: components["schemas"]["ImageOutput"];
-      string: components["schemas"]["StringOutput"];
-      mask_edge: components["schemas"]["ImageOutput"];
-      i2l: components["schemas"]["LatentsOutput"];
-      face_identifier: components["schemas"]["ImageOutput"];
-      compel: components["schemas"]["ConditioningOutput"];
-      esrgan: components["schemas"]["ImageOutput"];
-      seamless: components["schemas"]["SeamlessModeOutput"];
-      mask_from_id: components["schemas"]["ImageOutput"];
-      invert_tensor_mask: components["schemas"]["MaskOutput"];
-      rectangle_mask: components["schemas"]["MaskOutput"];
-      conditioning: components["schemas"]["ConditioningOutput"];
-      t2i_adapter: components["schemas"]["T2IAdapterOutput"];
-      string_collection: components["schemas"]["StringCollectionOutput"];
-      show_image: components["schemas"]["ImageOutput"];
-      dw_openpose_image_processor: components["schemas"]["ImageOutput"];
-      string_split_neg: components["schemas"]["StringPosNegOutput"];
-      conditioning_collection: components["schemas"]["ConditioningCollectionOutput"];
-      infill_patchmatch: components["schemas"]["ImageOutput"];
-      img_conv: components["schemas"]["ImageOutput"];
-      unsharp_mask: components["schemas"]["ImageOutput"];
-      metadata_item: components["schemas"]["MetadataItemOutput"];
-      image: components["schemas"]["ImageOutput"];
-      image_collection: components["schemas"]["ImageCollectionOutput"];
-      tile_to_properties: components["schemas"]["TileToPropertiesOutput"];
-      lblend: components["schemas"]["LatentsOutput"];
-      float: components["schemas"]["FloatOutput"];
-      boolean_collection: components["schemas"]["BooleanCollectionOutput"];
-      color: components["schemas"]["ColorOutput"];
       midas_depth_image_processor: components["schemas"]["ImageOutput"];
-      zoe_depth_image_processor: components["schemas"]["ImageOutput"];
-      infill_rgba: components["schemas"]["ImageOutput"];
-      mlsd_image_processor: components["schemas"]["ImageOutput"];
+      lscale: components["schemas"]["LatentsOutput"];
+      string_split: components["schemas"]["String2Output"];
+      mask_edge: components["schemas"]["ImageOutput"];
+      content_shuffle_image_processor: components["schemas"]["ImageOutput"];
+      color_correct: components["schemas"]["ImageOutput"];
+      save_image: components["schemas"]["ImageOutput"];
+      show_image: components["schemas"]["ImageOutput"];
+      segment_anything_processor: components["schemas"]["ImageOutput"];
+      latents: components["schemas"]["LatentsOutput"];
+      lineart_image_processor: components["schemas"]["ImageOutput"];
+      hed_image_processor: components["schemas"]["ImageOutput"];
+      infill_lama: components["schemas"]["ImageOutput"];
+      infill_patchmatch: components["schemas"]["ImageOutput"];
+      float_collection: components["schemas"]["FloatCollectionOutput"];
+      denoise_latents: components["schemas"]["LatentsOutput"];
+      metadata: components["schemas"]["MetadataOutput"];
+      compel: components["schemas"]["ConditioningOutput"];
+      img_blur: components["schemas"]["ImageOutput"];
+      img_crop: components["schemas"]["ImageOutput"];
+      sdxl_lora_collection_loader: components["schemas"]["SDXLLoRALoaderOutput"];
+      img_ilerp: components["schemas"]["ImageOutput"];
+      img_paste: components["schemas"]["ImageOutput"];
+      core_metadata: components["schemas"]["MetadataOutput"];
+      lora_collection_loader: components["schemas"]["LoRALoaderOutput"];
+      lora_selector: components["schemas"]["LoRASelectorOutput"];
+      create_denoise_mask: components["schemas"]["DenoiseMaskOutput"];
+      rectangle_mask: components["schemas"]["MaskOutput"];
+      noise: components["schemas"]["NoiseOutput"];
+      float_to_int: components["schemas"]["IntegerOutput"];
+      esrgan: components["schemas"]["ImageOutput"];
       merge_tiles_to_image: components["schemas"]["ImageOutput"];
       prompt_from_file: components["schemas"]["StringCollectionOutput"];
-      boolean: components["schemas"]["BooleanOutput"];
-      create_gradient_mask: components["schemas"]["GradientMaskOutput"];
-      rand_float: components["schemas"]["FloatOutput"];
-      img_mul: components["schemas"]["ImageOutput"];
-      controlnet: components["schemas"]["ControlOutput"];
-      latents_collection: components["schemas"]["LatentsCollectionOutput"];
-      img_lerp: components["schemas"]["ImageOutput"];
-      noise: components["schemas"]["NoiseOutput"];
-      iterate: components["schemas"]["IterateInvocationOutput"];
-      lineart_image_processor: components["schemas"]["ImageOutput"];
-      tomask: components["schemas"]["ImageOutput"];
-      integer: components["schemas"]["IntegerOutput"];
-      create_denoise_mask: components["schemas"]["DenoiseMaskOutput"];
-      clip_skip: components["schemas"]["CLIPSkipInvocationOutput"];
-      denoise_latents: components["schemas"]["LatentsOutput"];
-      string_join: components["schemas"]["StringOutput"];
-      scheduler: components["schemas"]["SchedulerOutput"];
-      model_identifier: components["schemas"]["ModelIdentifierOutput"];
-      normalbae_image_processor: components["schemas"]["ImageOutput"];
-      face_off: components["schemas"]["FaceOffOutput"];
-      hed_image_processor: components["schemas"]["ImageOutput"];
-      img_paste: components["schemas"]["ImageOutput"];
-      img_chan: components["schemas"]["ImageOutput"];
-      img_watermark: components["schemas"]["ImageOutput"];
-      l2i: components["schemas"]["ImageOutput"];
-      string_replace: components["schemas"]["StringOutput"];
-      color_map_image_processor: components["schemas"]["ImageOutput"];
-      tile_image_processor: components["schemas"]["ImageOutput"];
-      crop_latents: components["schemas"]["LatentsOutput"];
-      sdxl_lora_collection_loader: components["schemas"]["SDXLLoRALoaderOutput"];
-      add: components["schemas"]["IntegerOutput"];
-      sub: components["schemas"]["IntegerOutput"];
-      img_scale: components["schemas"]["ImageOutput"];
-      range: components["schemas"]["IntegerCollectionOutput"];
-      dynamic_prompt: components["schemas"]["StringCollectionOutput"];
-      img_crop: components["schemas"]["ImageOutput"];
-      infill_tile: components["schemas"]["ImageOutput"];
-      img_resize: components["schemas"]["ImageOutput"];
-      mediapipe_face_processor: components["schemas"]["ImageOutput"];
-      sdxl_model_loader: components["schemas"]["SDXLModelLoaderOutput"];
-      lora_selector: components["schemas"]["LoRASelectorOutput"];
-      img_hue_adjust: components["schemas"]["ImageOutput"];
-      latents: components["schemas"]["LatentsOutput"];
-      lora_collection_loader: components["schemas"]["LoRALoaderOutput"];
-      img_blur: components["schemas"]["ImageOutput"];
-      ideal_size: components["schemas"]["IdealSizeOutput"];
-      float_collection: components["schemas"]["FloatCollectionOutput"];
-      blank_image: components["schemas"]["ImageOutput"];
-      integer_math: components["schemas"]["IntegerOutput"];
-      lora_loader: components["schemas"]["LoRALoaderOutput"];
-      metadata: components["schemas"]["MetadataOutput"];
+      infill_rgba: components["schemas"]["ImageOutput"];
       sdxl_lora_loader: components["schemas"]["SDXLLoRALoaderOutput"];
-      round_float: components["schemas"]["FloatOutput"];
-      sdxl_refiner_model_loader: components["schemas"]["SDXLRefinerModelLoaderOutput"];
-      mul: components["schemas"]["IntegerOutput"];
-      alpha_mask_to_tensor: components["schemas"]["MaskOutput"];
-      lscale: components["schemas"]["LatentsOutput"];
-      save_image: components["schemas"]["ImageOutput"];
+      lora_loader: components["schemas"]["LoRALoaderOutput"];
+      iterate: components["schemas"]["IterateInvocationOutput"];
+      t2i_adapter: components["schemas"]["T2IAdapterOutput"];
+      color_map_image_processor: components["schemas"]["ImageOutput"];
+      blank_image: components["schemas"]["ImageOutput"];
+      normalbae_image_processor: components["schemas"]["ImageOutput"];
+      canvas_paste_back: components["schemas"]["ImageOutput"];
+      string_split_neg: components["schemas"]["StringPosNegOutput"];
+      img_channel_offset: components["schemas"]["ImageOutput"];
+      face_mask_detection: components["schemas"]["FaceMaskOutput"];
+      cv_inpaint: components["schemas"]["ImageOutput"];
+      clip_skip: components["schemas"]["CLIPSkipInvocationOutput"];
+      invert_tensor_mask: components["schemas"]["MaskOutput"];
+      tomask: components["schemas"]["ImageOutput"];
+      main_model_loader: components["schemas"]["ModelLoaderOutput"];
+      img_watermark: components["schemas"]["ImageOutput"];
+      img_pad_crop: components["schemas"]["ImageOutput"];
+      random_range: components["schemas"]["IntegerCollectionOutput"];
+      mlsd_image_processor: components["schemas"]["ImageOutput"];
+      merge_metadata: components["schemas"]["MetadataOutput"];
+      string_join: components["schemas"]["StringOutput"];
+      vae_loader: components["schemas"]["VAEOutput"];
+      calculate_image_tiles_even_split: components["schemas"]["CalculateImageTilesOutput"];
       calculate_image_tiles_min_overlap: components["schemas"]["CalculateImageTilesOutput"];
+      mask_from_id: components["schemas"]["ImageOutput"];
+      zoe_depth_image_processor: components["schemas"]["ImageOutput"];
+      img_resize: components["schemas"]["ImageOutput"];
+      string_replace: components["schemas"]["StringOutput"];
+      face_identifier: components["schemas"]["ImageOutput"];
+      canny_image_processor: components["schemas"]["ImageOutput"];
+      collect: components["schemas"]["CollectInvocationOutput"];
+      infill_tile: components["schemas"]["ImageOutput"];
+      integer_collection: components["schemas"]["IntegerCollectionOutput"];
+      img_lerp: components["schemas"]["ImageOutput"];
+      step_param_easing: components["schemas"]["FloatCollectionOutput"];
+      lresize: components["schemas"]["LatentsOutput"];
+      img_mul: components["schemas"]["ImageOutput"];
+      create_gradient_mask: components["schemas"]["GradientMaskOutput"];
+      img_scale: components["schemas"]["ImageOutput"];
+      rand_float: components["schemas"]["FloatOutput"];
+      tile_to_properties: components["schemas"]["TileToPropertiesOutput"];
+      calculate_image_tiles: components["schemas"]["CalculateImageTilesOutput"];
+      range_of_size: components["schemas"]["IntegerCollectionOutput"];
+      sdxl_refiner_model_loader: components["schemas"]["SDXLRefinerModelLoaderOutput"];
+      heuristic_resize: components["schemas"]["ImageOutput"];
+      controlnet: components["schemas"]["ControlOutput"];
+      string: components["schemas"]["StringOutput"];
+      tile_image_processor: components["schemas"]["ImageOutput"];
+      metadata_item: components["schemas"]["MetadataItemOutput"];
+      freeu: components["schemas"]["UNetOutput"];
+      round_float: components["schemas"]["FloatOutput"];
+      conditioning: components["schemas"]["ConditioningOutput"];
+      ideal_size: components["schemas"]["IdealSizeOutput"];
+      float: components["schemas"]["FloatOutput"];
+      conditioning_collection: components["schemas"]["ConditioningCollectionOutput"];
+      alpha_mask_to_tensor: components["schemas"]["MaskOutput"];
+      integer_math: components["schemas"]["IntegerOutput"];
+      string_collection: components["schemas"]["StringCollectionOutput"];
+      img_conv: components["schemas"]["ImageOutput"];
+      img_channel_multiply: components["schemas"]["ImageOutput"];
+      lblend: components["schemas"]["LatentsOutput"];
+      color: components["schemas"]["ColorOutput"];
+      image: components["schemas"]["ImageOutput"];
+      sdxl_model_loader: components["schemas"]["SDXLModelLoaderOutput"];
+      image_collection: components["schemas"]["ImageCollectionOutput"];
+      model_identifier: components["schemas"]["ModelIdentifierOutput"];
+      l2i: components["schemas"]["ImageOutput"];
+      seamless: components["schemas"]["SeamlessModeOutput"];
+      boolean_collection: components["schemas"]["BooleanCollectionOutput"];
+      string_join_three: components["schemas"]["StringOutput"];
+      ip_adapter: components["schemas"]["IPAdapterOutput"];
+      add: components["schemas"]["IntegerOutput"];
+      crop_latents: components["schemas"]["LatentsOutput"];
+      float_range: components["schemas"]["FloatCollectionOutput"];
+      mul: components["schemas"]["IntegerOutput"];
+      dw_openpose_image_processor: components["schemas"]["ImageOutput"];
+      boolean: components["schemas"]["BooleanOutput"];
+      dynamic_prompt: components["schemas"]["StringCollectionOutput"];
+      mediapipe_face_processor: components["schemas"]["ImageOutput"];
+      i2l: components["schemas"]["LatentsOutput"];
+      latents_collection: components["schemas"]["LatentsCollectionOutput"];
+      integer: components["schemas"]["IntegerOutput"];
+      img_chan: components["schemas"]["ImageOutput"];
+      pair_tile_image: components["schemas"]["PairTileImageOutput"];
+      unsharp_mask: components["schemas"]["ImageOutput"];
+      img_hue_adjust: components["schemas"]["ImageOutput"];
+      lineart_anime_image_processor: components["schemas"]["ImageOutput"];
+      face_off: components["schemas"]["FaceOffOutput"];
+      mask_combine: components["schemas"]["ImageOutput"];
+      leres_image_processor: components["schemas"]["ImageOutput"];
+      image_mask_to_tensor: components["schemas"]["MaskOutput"];
+      sdxl_refiner_compel_prompt: components["schemas"]["ConditioningOutput"];
+      scheduler: components["schemas"]["SchedulerOutput"];
+      sub: components["schemas"]["IntegerOutput"];
+      pidi_image_processor: components["schemas"]["ImageOutput"];
+      infill_cv2: components["schemas"]["ImageOutput"];
+      div: components["schemas"]["IntegerOutput"];
+      img_nsfw: components["schemas"]["ImageOutput"];
+      depth_anything_image_processor: components["schemas"]["ImageOutput"];
+      sdxl_compel_prompt: components["schemas"]["ConditioningOutput"];
+      range: components["schemas"]["IntegerCollectionOutput"];
+      rand_int: components["schemas"]["IntegerOutput"];
+      float_math: components["schemas"]["FloatOutput"];
     };
     /**
      * InvocationStartedEvent
@@ -9443,6 +9450,49 @@ export type components = {
           [key: string]: number | string;
         })[];
     };
+    /**
+     * ModelInstallDownloadStartedEvent
+     * @description Event model for model_install_download_started
+     */
+    ModelInstallDownloadStartedEvent: {
+      /**
+       * Timestamp
+       * @description The timestamp of the event
+       */
+      timestamp: number;
+      /**
+       * Id
+       * @description The ID of the install job
+       */
+      id: number;
+      /**
+       * Source
+       * @description Source of the model; local path, repo_id or url
+       */
+      source: string;
+      /**
+       * Local Path
+       * @description Where model is downloading to
+       */
+      local_path: string;
+      /**
+       * Bytes
+       * @description Number of bytes downloaded so far
+       */
+      bytes: number;
+      /**
+       * Total Bytes
+       * @description Total size of download, including all files
+       */
+      total_bytes: number;
+      /**
+       * Parts
+       * @description Progress of downloading URLs that comprise the model, if any
+       */
+      parts: ({
+          [key: string]: number | string;
+        })[];
+    };
     /**
      * ModelInstallDownloadsCompleteEvent
      * @description Emitted once when an install job becomes active.
@@ -10671,8 +10721,9 @@ export type components = {
       /**
        * Size
        * @description The size of this file, in bytes
+       * @default 0
        */
-      size: number;
+      size?: number | null;
       /**
        * Sha256
        * @description SHA256 hash of this model (not always available)
@@ -14050,6 +14101,40 @@ export type operations = {
       };
     };
   };
+  /**
+   * Install Hugging Face Model
+   * @description Install a Hugging Face model using a string identifier.
+   */
+  install_hugging_face_model: {
+    parameters: {
+      query: {
+        /** @description Hugging Face repo_id to install */
+        source: string;
+      };
+    };
+    responses: {
+      /** @description The model is being installed */
+      201: {
+        content: {
+          "text/html": string;
+        };
+      };
+      /** @description Bad request */
+      400: {
+        content: never;
+      };
+      /** @description There is already a model corresponding to this path or repo_id */
+      409: {
+        content: never;
+      };
+      /** @description Validation Error */
+      422: {
+        content: {
+          "application/json": components["schemas"]["HTTPValidationError"];
+        };
+      };
+    };
+  };
   /**
    * Get Model Install Job
    * @description Return model install job corresponding to the given source. See the documentation for 'List Model Install Jobs'

From 56771de8565d2ff6d435fc6f234c0ee5254ca433 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 17 Jun 2024 09:52:46 +1000
Subject: [PATCH 09/24] feat(ui): add redux actions for
 `model_install_download_started` event

---
 invokeai/frontend/web/src/services/events/actions.ts | 4 ++++
 invokeai/frontend/web/src/services/events/types.ts   | 2 ++
 2 files changed, 6 insertions(+)

diff --git a/invokeai/frontend/web/src/services/events/actions.ts b/invokeai/frontend/web/src/services/events/actions.ts
index 257819b4c8..a97bdcbf8b 100644
--- a/invokeai/frontend/web/src/services/events/actions.ts
+++ b/invokeai/frontend/web/src/services/events/actions.ts
@@ -16,6 +16,7 @@ import type {
   ModelInstallCompleteEvent,
   ModelInstallDownloadProgressEvent,
   ModelInstallDownloadsCompleteEvent,
+  ModelInstallDownloadStartedEvent,
   ModelInstallErrorEvent,
   ModelInstallStartedEvent,
   ModelLoadCompleteEvent,
@@ -45,6 +46,9 @@ export const socketModelInstallStarted = createSocketAction<ModelInstallStartedE
 export const socketModelInstallDownloadProgress = createSocketAction<ModelInstallDownloadProgressEvent>(
   'ModelInstallDownloadProgressEvent'
 );
+export const socketModelInstallDownloadStarted = createSocketAction<ModelInstallDownloadStartedEvent>(
+  'ModelInstallDownloadStartedEvent'
+);
 export const socketModelInstallDownloadsComplete = createSocketAction<ModelInstallDownloadsCompleteEvent>(
   'ModelInstallDownloadsCompleteEvent'
 );
diff --git a/invokeai/frontend/web/src/services/events/types.ts b/invokeai/frontend/web/src/services/events/types.ts
index a84049cc28..2d3725394d 100644
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -9,6 +9,7 @@ export type InvocationCompleteEvent = S['InvocationCompleteEvent'];
 export type InvocationErrorEvent = S['InvocationErrorEvent'];
 export type ProgressImage = InvocationDenoiseProgressEvent['progress_image'];
 
+export type ModelInstallDownloadStartedEvent = S['ModelInstallDownloadStartedEvent'];
 export type ModelInstallDownloadProgressEvent = S['ModelInstallDownloadProgressEvent'];
 export type ModelInstallDownloadsCompleteEvent = S['ModelInstallDownloadsCompleteEvent'];
 export type ModelInstallCompleteEvent = S['ModelInstallCompleteEvent'];
@@ -49,6 +50,7 @@ export type ServerToClientEvents = {
   download_error: (payload: DownloadErrorEvent) => void;
   model_load_started: (payload: ModelLoadStartedEvent) => void;
   model_install_started: (payload: ModelInstallStartedEvent) => void;
+  model_install_download_started: (payload: ModelInstallDownloadStartedEvent) => void;
   model_install_download_progress: (payload: ModelInstallDownloadProgressEvent) => void;
   model_install_downloads_complete: (payload: ModelInstallDownloadsCompleteEvent) => void;
   model_install_complete: (payload: ModelInstallCompleteEvent) => void;

From f002bca2fa057aa9dcb997fc3520a3b31a12578a Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 17 Jun 2024 10:07:10 +1000
Subject: [PATCH 10/24] feat(ui): handle new `model_install_download_started`
 event

When a model install is initiated from outside the client, we now trigger the model manager tab's model install list to update.

- Handle new `model_install_download_started` event
- Handle `model_install_download_complete` event (this event is not new but was never handled)
- Update optimistic updates/cache invalidation logic to efficiently update the model install list
---
 .../listeners/socketio/socketModelInstall.ts  | 184 +++++++++++++-----
 1 file changed, 136 insertions(+), 48 deletions(-)

diff --git a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
index 113d2cbd66..22ad87fbe9 100644
--- a/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
+++ b/invokeai/frontend/web/src/app/store/middleware/listenerMiddleware/listeners/socketio/socketModelInstall.ts
@@ -5,6 +5,8 @@ import {
   socketModelInstallCancelled,
   socketModelInstallComplete,
   socketModelInstallDownloadProgress,
+  socketModelInstallDownloadsComplete,
+  socketModelInstallDownloadStarted,
   socketModelInstallError,
   socketModelInstallStarted,
 } from 'services/events/actions';
@@ -14,9 +16,12 @@ import {
  * which is a bit misleading. For example, a `model_install_started` event is actually fired _after_ the model has fully
  * downloaded and is being "physically" installed.
  *
+ * Note: the download events are only fired for remote model installs, not local.
+ *
  * Here's the expected flow:
- * - Model manager does some prep
- * - `model_install_download_progress` fired when the download starts and continually until the download is complete
+ * - API receives install request, model manager preps the install
+ * - `model_install_download_started` fired when the download starts
+ * - `model_install_download_progress` fired continually until the download is complete
  * - `model_install_download_complete` fired when the download is complete
  * - `model_install_started` fired when the "physical" installation starts
  * - `model_install_complete` fired when the installation is complete
@@ -24,47 +29,98 @@ import {
  * - `model_install_error` fired if the installation has an error
  */
 
+const selectModelInstalls = modelsApi.endpoints.listModelInstalls.select();
+
 export const addModelInstallEventListener = (startAppListening: AppStartListening) => {
+  startAppListening({
+    actionCreator: socketModelInstallDownloadStarted,
+    effect: async (action, { dispatch, getState }) => {
+      const { id } = action.payload.data;
+      const { data } = selectModelInstalls(getState());
+
+      if (!data || !data.find((m) => m.id === id)) {
+        dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+      } else {
+        dispatch(
+          modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
+            const modelImport = draft.find((m) => m.id === id);
+            if (modelImport) {
+              modelImport.status = 'downloading';
+            }
+            return draft;
+          })
+        );
+      }
+    },
+  });
+
   startAppListening({
     actionCreator: socketModelInstallStarted,
-    effect: async (action, { dispatch }) => {
-      dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+    effect: async (action, { dispatch, getState }) => {
+      const { id } = action.payload.data;
+      const { data } = selectModelInstalls(getState());
+
+      if (!data || !data.find((m) => m.id === id)) {
+        dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+      } else {
+        dispatch(
+          modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
+            const modelImport = draft.find((m) => m.id === id);
+            if (modelImport) {
+              modelImport.status = 'running';
+            }
+            return draft;
+          })
+        );
+      }
     },
   });
 
   startAppListening({
     actionCreator: socketModelInstallDownloadProgress,
-    effect: async (action, { dispatch }) => {
+    effect: async (action, { dispatch, getState }) => {
       const { bytes, total_bytes, id } = action.payload.data;
+      const { data } = selectModelInstalls(getState());
 
-      dispatch(
-        modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
-          const modelImport = draft.find((m) => m.id === id);
-          if (modelImport) {
-            modelImport.bytes = bytes;
-            modelImport.total_bytes = total_bytes;
-            modelImport.status = 'downloading';
-          }
-          return draft;
-        })
-      );
+      if (!data || !data.find((m) => m.id === id)) {
+        dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+      } else {
+        dispatch(
+          modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
+            const modelImport = draft.find((m) => m.id === id);
+            if (modelImport) {
+              modelImport.bytes = bytes;
+              modelImport.total_bytes = total_bytes;
+              modelImport.status = 'downloading';
+            }
+            return draft;
+          })
+        );
+      }
     },
   });
 
   startAppListening({
     actionCreator: socketModelInstallComplete,
-    effect: (action, { dispatch }) => {
+    effect: (action, { dispatch, getState }) => {
       const { id } = action.payload.data;
 
-      dispatch(
-        modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
-          const modelImport = draft.find((m) => m.id === id);
-          if (modelImport) {
-            modelImport.status = 'completed';
-          }
-          return draft;
-        })
-      );
+      const { data } = selectModelInstalls(getState());
+
+      if (!data || !data.find((m) => m.id === id)) {
+        dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+      } else {
+        dispatch(
+          modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
+            const modelImport = draft.find((m) => m.id === id);
+            if (modelImport) {
+              modelImport.status = 'completed';
+            }
+            return draft;
+          })
+        );
+      }
+
       dispatch(api.util.invalidateTags([{ type: 'ModelConfig', id: LIST_TAG }]));
       dispatch(api.util.invalidateTags([{ type: 'ModelScanFolderResults', id: LIST_TAG }]));
     },
@@ -72,37 +128,69 @@ export const addModelInstallEventListener = (startAppListening: AppStartListenin
 
   startAppListening({
     actionCreator: socketModelInstallError,
-    effect: (action, { dispatch }) => {
+    effect: (action, { dispatch, getState }) => {
       const { id, error, error_type } = action.payload.data;
+      const { data } = selectModelInstalls(getState());
 
-      dispatch(
-        modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
-          const modelImport = draft.find((m) => m.id === id);
-          if (modelImport) {
-            modelImport.status = 'error';
-            modelImport.error_reason = error_type;
-            modelImport.error = error;
-          }
-          return draft;
-        })
-      );
+      if (!data || !data.find((m) => m.id === id)) {
+        dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+      } else {
+        dispatch(
+          modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
+            const modelImport = draft.find((m) => m.id === id);
+            if (modelImport) {
+              modelImport.status = 'error';
+              modelImport.error_reason = error_type;
+              modelImport.error = error;
+            }
+            return draft;
+          })
+        );
+      }
     },
   });
 
   startAppListening({
     actionCreator: socketModelInstallCancelled,
-    effect: (action, { dispatch }) => {
+    effect: (action, { dispatch, getState }) => {
       const { id } = action.payload.data;
+      const { data } = selectModelInstalls(getState());
 
-      dispatch(
-        modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
-          const modelImport = draft.find((m) => m.id === id);
-          if (modelImport) {
-            modelImport.status = 'cancelled';
-          }
-          return draft;
-        })
-      );
+      if (!data || !data.find((m) => m.id === id)) {
+        dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+      } else {
+        dispatch(
+          modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
+            const modelImport = draft.find((m) => m.id === id);
+            if (modelImport) {
+              modelImport.status = 'cancelled';
+            }
+            return draft;
+          })
+        );
+      }
+    },
+  });
+
+  startAppListening({
+    actionCreator: socketModelInstallDownloadsComplete,
+    effect: (action, { dispatch, getState }) => {
+      const { id } = action.payload.data;
+      const { data } = selectModelInstalls(getState());
+
+      if (!data || !data.find((m) => m.id === id)) {
+        dispatch(api.util.invalidateTags([{ type: 'ModelInstalls' }]));
+      } else {
+        dispatch(
+          modelsApi.util.updateQueryData('listModelInstalls', undefined, (draft) => {
+            const modelImport = draft.find((m) => m.id === id);
+            if (modelImport) {
+              modelImport.status = 'downloads_done';
+            }
+            return draft;
+          })
+        );
+      }
     },
   });
 };

From cd70937b7f3a44669f6c011376bbb44fb8201045 Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 17 Jun 2024 10:51:08 +1000
Subject: [PATCH 11/24] feat(api): improved model install confirmation page
 styling & messaging

---
 invokeai/app/api/routers/model_manager.py | 118 ++++++++++++++++------
 1 file changed, 85 insertions(+), 33 deletions(-)

diff --git a/invokeai/app/api/routers/model_manager.py b/invokeai/app/api/routers/model_manager.py
index f2fb0932e5..99f00423c6 100644
--- a/invokeai/app/api/routers/model_manager.py
+++ b/invokeai/app/api/routers/model_manager.py
@@ -514,50 +514,93 @@ async def install_model(
     response_class=HTMLResponse,
 )
 async def install_hugging_face_model(
-    source: str = Query(description="Hugging Face repo_id to install"),
+    source: str = Query(description="HuggingFace repo_id to install"),
 ) -> HTMLResponse:
     """Install a Hugging Face model using a string identifier."""
 
-    def generate_html(message: str) -> str:
+    def generate_html(title: str, heading: str, repo_id: str, is_error: bool, message: str | None = "") -> str:
+        if message:
+            message = f"<p>{message}</p>"
+        title_class = "error" if is_error else "success"
         return f"""
-        <html>
-        <head>
-            <style>
-                body {{
-                    text-align: center;
-                    margin-top: 50px;
-                }}
-                .message-box {{
-                    display: inline-block;
-                    padding: 20px;
-                    border: 1px solid #ccc;
-                    border-radius: 5px;
-                    background-color: #f9f9f9;
-                    box-shadow: 0px 0px 10px rgba(0, 0, 0, 0.1);
-                }}
-            </style>
-        </head>
-        <body>
-            <div class="message-box">
-                <p>{message}</p>
-            </div>
-        </body>
-        </html>
+            <html>
+
+            <head>
+                <title>{title}</title>
+                <style>
+                    body {{
+                        text-align: center;
+                        background-color: hsl(220 12% 10% / 1);
+                        font-family: Helvetica, sans-serif;
+                        color: hsl(220 12% 86% / 1);
+                    }}
+
+                    .repo-id {{
+                        color: hsl(220 12% 68% / 1);
+                    }}
+
+                    .error {{
+                        color: hsl(0 42% 68% / 1)
+                    }}
+
+                    .message-box {{
+                        display: inline-block;
+                        border-radius: 5px;
+                        background-color: hsl(220 12% 20% / 1);
+                        padding-inline-end: 30px;
+                        padding: 20px;
+                        padding-inline-start: 30px;
+                        padding-inline-end: 30px;
+                    }}
+
+                    .container {{
+                        display: flex;
+                        width: 100%;
+                        height: 100%;
+                        align-items: center;
+                        justify-content: center;
+                    }}
+
+                    a {{
+                        color: inherit
+                    }}
+
+                    a:visited {{
+                        color: inherit
+                    }}
+
+                    a:active {{
+                        color: inherit
+                    }}
+                </style>
+            </head>
+
+            <body style="background-color: hsl(220 12% 10% / 1);">
+                <div class="container">
+                    <div class="message-box">
+                        <h2 class="{title_class}">{heading}</h2>
+                        {message}
+                        <p class="repo-id">Repo ID: {repo_id}</p>
+                    </div>
+                </div>
+            </body>
+
+            </html>
         """
 
     try:
         metadata = HuggingFaceMetadataFetch().from_id(source)
         assert isinstance(metadata, ModelMetadataWithFiles)
-        message = "Your Hugging Face model is installing now. You can close this tab and check the Model Manager for installation progress."
     except UnknownMetadataException:
-        message = "No HuggingFace repository found with that repo id."
-        return HTMLResponse(content=generate_html(message), status_code=400)
+        title = "Unable to Install Model"
+        heading = "No HuggingFace repository found with that repo ID."
+        message = "Ensure the repo ID is correct and try again."
+        return HTMLResponse(content=generate_html(title, heading, source, True, message), status_code=400)
 
     logger = ApiDependencies.invoker.services.logger
 
     try:
         installer = ApiDependencies.invoker.services.model_manager.install
-
         if metadata.is_diffusers:
             installer.heuristic_import(
                 source=source,
@@ -569,12 +612,21 @@ async def install_hugging_face_model(
                 inplace=False,
             )
         else:
-            message = "This HuggingFace repo has multiple models. Please use the Model Manager to install this."
+            title = "Unable to Install Model"
+            heading = "This HuggingFace repo has multiple models."
+            message = "Please use the Model Manager to install this model."
+            return HTMLResponse(content=generate_html(title, heading, source, True, message), status_code=200)
+
+        title = "Model Install Started"
+        heading = "Your HuggingFace model is installing now."
+        message = "You can close this tab and check the Model Manager for installation progress."
+        return HTMLResponse(content=generate_html(title, heading, source, False, message), status_code=201)
     except Exception as e:
         logger.error(str(e))
-        message = "There was an error with installing this model. Please use the Model Manager to install this."
-
-    return HTMLResponse(content=generate_html(message), status_code=201)
+        title = "Unable to Install Model"
+        heading = "There was an problem installing this model."
+        message = 'Please use the Model Manager directly to install this model. If the issue persists, ask for help on <a href="https://discord.gg/ZmtBAhwWhy">discord</a>.'
+        return HTMLResponse(content=generate_html(title, heading, source, True, message), status_code=500)
 
 
 @model_manager_router.get(

From e26125b734be2bcfb3188c1a0e29ccd3b6f474ba Mon Sep 17 00:00:00 2001
From: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Date: Mon, 17 Jun 2024 10:57:11 +1000
Subject: [PATCH 12/24] tests: fix test_model_install.py

---
 tests/app/services/model_install/test_model_install.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/tests/app/services/model_install/test_model_install.py b/tests/app/services/model_install/test_model_install.py
index 9602a79a27..0c212cca76 100644
--- a/tests/app/services/model_install/test_model_install.py
+++ b/tests/app/services/model_install/test_model_install.py
@@ -17,6 +17,7 @@ from invokeai.app.services.events.events_common import (
     ModelInstallCompleteEvent,
     ModelInstallDownloadProgressEvent,
     ModelInstallDownloadsCompleteEvent,
+    ModelInstallDownloadStartedEvent,
     ModelInstallStartedEvent,
 )
 from invokeai.app.services.model_install import (
@@ -252,7 +253,7 @@ def test_simple_download(mm2_installer: ModelInstallServiceBase, mm2_app_config:
     assert (mm2_app_config.models_path / model_record.path).exists()
 
     assert len(bus.events) == 5
-    assert isinstance(bus.events[0], ModelInstallDownloadProgressEvent)  # download starts
+    assert isinstance(bus.events[0], ModelInstallDownloadStartedEvent)  # download starts
     assert isinstance(bus.events[1], ModelInstallDownloadProgressEvent)  # download progresses
     assert isinstance(bus.events[2], ModelInstallDownloadsCompleteEvent)  # download completed
     assert isinstance(bus.events[3], ModelInstallStartedEvent)  # install started

From 41a6bb45f3018040089338c1e98a6024a9229cf0 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Thu, 13 Jun 2024 16:34:27 -0400
Subject: [PATCH 13/24] Initial functionality

---
 invokeai/backend/model_hash/hash_validator.py | 16 ++++++++++++++++
 invokeai/backend/model_manager/config.py      |  3 +++
 2 files changed, 19 insertions(+)
 create mode 100644 invokeai/backend/model_hash/hash_validator.py

diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py
new file mode 100644
index 0000000000..0a1bdf6ea9
--- /dev/null
+++ b/invokeai/backend/model_hash/hash_validator.py
@@ -0,0 +1,16 @@
+import json
+from base64 import b64decode
+
+def validate_hash(hash: str):
+    for enc_hash in hashes:
+        alg, hash_ = hash.split(":")
+        if alg == "blake3":
+            alg = "blake3_single"
+        map = json.loads(b64decode(enc_hash))
+        if alg in map:
+            if hash_ == map[alg]:
+                raise Exception("Unrecoverable Model Error")
+
+hashes: list[str]=[
+    "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",
+]
diff --git a/invokeai/backend/model_manager/config.py b/invokeai/backend/model_manager/config.py
index e3c99c5644..7ed12a7674 100644
--- a/invokeai/backend/model_manager/config.py
+++ b/invokeai/backend/model_manager/config.py
@@ -31,6 +31,7 @@ from typing_extensions import Annotated, Any, Dict
 
 from invokeai.app.invocations.constants import SCHEDULER_NAME_VALUES
 from invokeai.app.util.misc import uuid_string
+from invokeai.backend.model_hash.hash_validator import validate_hash
 
 from ..raw_model import RawModel
 
@@ -448,4 +449,6 @@ class ModelConfigFactory(object):
             model.key = key
         if isinstance(model, CheckpointConfigBase) and timestamp is not None:
             model.converted_at = timestamp
+        if model:
+            validate_hash(model.hash)
         return model  # type: ignore

From 3a5ad6d11299e1c9fa2dbd1008faec8fd150fab5 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Fri, 14 Jun 2024 12:34:45 -0400
Subject: [PATCH 14/24] Update validator list

---
 invokeai/backend/model_hash/hash_validator.py | 26 ++++++++++++++++++-
 1 file changed, 25 insertions(+), 1 deletion(-)

diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py
index 0a1bdf6ea9..08fff62f27 100644
--- a/invokeai/backend/model_hash/hash_validator.py
+++ b/invokeai/backend/model_hash/hash_validator.py
@@ -12,5 +12,29 @@ def validate_hash(hash: str):
                 raise Exception("Unrecoverable Model Error")
 
 hashes: list[str]=[
-    "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",
+    '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',
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 ]

From 1925f83f5ed3bd1519d94ab4db2b9690fd34aa5b Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Fri, 14 Jun 2024 13:09:20 -0400
Subject: [PATCH 15/24] Update validator list

---
 invokeai/backend/model_hash/hash_validator.py | 21 -------------------
 1 file changed, 21 deletions(-)

diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py
index 08fff62f27..73b5feb654 100644
--- a/invokeai/backend/model_hash/hash_validator.py
+++ b/invokeai/backend/model_hash/hash_validator.py
@@ -12,29 +12,8 @@ def validate_hash(hash: str):
                 raise Exception("Unrecoverable Model Error")
 
 hashes: list[str]=[
-    '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',
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 ]

From f14f377ede5da9a22ba9e440469799ff6ce9783c Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Fri, 14 Jun 2024 13:13:01 -0400
Subject: [PATCH 16/24] Update validator list

---
 invokeai/backend/model_hash/hash_validator.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py
index 73b5feb654..b0d54ef7c6 100644
--- a/invokeai/backend/model_hash/hash_validator.py
+++ b/invokeai/backend/model_hash/hash_validator.py
@@ -16,4 +16,5 @@ hashes: list[str]=[
     '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',
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     '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',
+    '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',
 ]

From 8ce6e4540e2ecf88d4d8b6c021de7d9bfc27812d Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Tue, 18 Jun 2024 09:14:05 -0400
Subject: [PATCH 17/24] Run ruff

---
 invokeai/backend/model_hash/hash_validator.py | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py
index b0d54ef7c6..f0580e00dd 100644
--- a/invokeai/backend/model_hash/hash_validator.py
+++ b/invokeai/backend/model_hash/hash_validator.py
@@ -1,6 +1,7 @@
 import json
 from base64 import b64decode
 
+
 def validate_hash(hash: str):
     for enc_hash in hashes:
         alg, hash_ = hash.split(":")
@@ -11,10 +12,11 @@ def validate_hash(hash: str):
             if hash_ == map[alg]:
                 raise Exception("Unrecoverable Model Error")
 
-hashes: list[str]=[
-    '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',
-    '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',
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+    "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",
+    "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",
 ]

From fbc5a8ec6554ff9b5c375122e1e99777bc4d3f47 Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Tue, 18 Jun 2024 09:38:22 -0400
Subject: [PATCH 18/24] Ignore validation on improperly formatted hashes
 (pytest)

---
 invokeai/backend/model_hash/hash_validator.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py
index f0580e00dd..2064b74a92 100644
--- a/invokeai/backend/model_hash/hash_validator.py
+++ b/invokeai/backend/model_hash/hash_validator.py
@@ -3,6 +3,8 @@ from base64 import b64decode
 
 
 def validate_hash(hash: str):
+    if not ":" in hash:
+        return
     for enc_hash in hashes:
         alg, hash_ = hash.split(":")
         if alg == "blake3":

From 63a7e19dbfd2d74a5939e7e9b077cf3051d63cec Mon Sep 17 00:00:00 2001
From: Brandon Rising <brandon@invoke.ai>
Date: Tue, 18 Jun 2024 09:40:01 -0400
Subject: [PATCH 19/24] Run ruff

---
 invokeai/backend/model_hash/hash_validator.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/invokeai/backend/model_hash/hash_validator.py b/invokeai/backend/model_hash/hash_validator.py
index 2064b74a92..8c38788514 100644
--- a/invokeai/backend/model_hash/hash_validator.py
+++ b/invokeai/backend/model_hash/hash_validator.py
@@ -3,7 +3,7 @@ from base64 import b64decode
 
 
 def validate_hash(hash: str):
-    if not ":" in hash:
+    if ":" not in hash:
         return
     for enc_hash in hashes:
         alg, hash_ = hash.split(":")

From d13aafb5146781539bd88e96f9b883d86da12dff Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Thu, 6 Jun 2024 09:30:49 -0400
Subject: [PATCH 20/24] Tidy denoise_latents.py imports to all use absolute
 import paths.

---
 invokeai/app/invocations/denoise_latents.py | 21 ++++++++++-----------
 1 file changed, 10 insertions(+), 11 deletions(-)

diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py
index 7260fcb168..41e57ec63e 100644
--- a/invokeai/app/invocations/denoise_latents.py
+++ b/invokeai/app/invocations/denoise_latents.py
@@ -16,7 +16,9 @@ from pydantic import field_validator
 from torchvision.transforms.functional import resize as tv_resize
 from transformers import CLIPVisionModelWithProjection
 
+from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
 from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR, SCHEDULER_NAME_VALUES
+from invokeai.app.invocations.controlnet_image_processors import ControlField
 from invokeai.app.invocations.fields import (
     ConditioningField,
     DenoiseMaskField,
@@ -27,6 +29,7 @@ from invokeai.app.invocations.fields import (
     UIType,
 )
 from invokeai.app.invocations.ip_adapter import IPAdapterField
+from invokeai.app.invocations.model import ModelIdentifierField, UNetField
 from invokeai.app.invocations.primitives import LatentsOutput
 from invokeai.app.invocations.t2i_adapter import T2IAdapterField
 from invokeai.app.services.shared.invocation_context import InvocationContext
@@ -36,6 +39,11 @@ from invokeai.backend.lora import LoRAModelRaw
 from invokeai.backend.model_manager import BaseModelType
 from invokeai.backend.model_patcher import ModelPatcher
 from invokeai.backend.stable_diffusion import PipelineIntermediateState, set_seamless
+from invokeai.backend.stable_diffusion.diffusers_pipeline import (
+    ControlNetData,
+    StableDiffusionGeneratorPipeline,
+    T2IAdapterData,
+)
 from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     BasicConditioningInfo,
     IPAdapterConditioningInfo,
@@ -45,20 +53,11 @@ from invokeai.backend.stable_diffusion.diffusion.conditioning_data import (
     TextConditioningData,
     TextConditioningRegions,
 )
+from invokeai.backend.stable_diffusion.schedulers import SCHEDULER_MAP
+from invokeai.backend.util.devices import TorchDevice
 from invokeai.backend.util.mask import to_standard_float_mask
 from invokeai.backend.util.silence_warnings import SilenceWarnings
 
-from ...backend.stable_diffusion.diffusers_pipeline import (
-    ControlNetData,
-    StableDiffusionGeneratorPipeline,
-    T2IAdapterData,
-)
-from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP
-from ...backend.util.devices import TorchDevice
-from .baseinvocation import BaseInvocation, invocation
-from .controlnet_image_processors import ControlField
-from .model import ModelIdentifierField, UNetField
-
 
 def get_scheduler(
     context: InvocationContext,

From 8e47e005a7e2cd404656558b2a27d3f3b14d7f08 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Thu, 6 Jun 2024 10:28:00 -0400
Subject: [PATCH 21/24] Tidy SilenceWarnings context manager:

- Fix type errors
- Enable SilenceWarnings to be used as both a context manager and a decorator
- Remove duplicate implementation
- Check the initial verbosity on __enter__() rather than __init__()
---
 invokeai/backend/model_manager/probe.py   |  2 +-
 invokeai/backend/util/silence_warnings.py | 33 ++++++++++++++---------
 invokeai/backend/util/util.py             | 21 ---------------
 3 files changed, 21 insertions(+), 35 deletions(-)

diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index 8f33e4b49f..4aef281bac 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -10,7 +10,7 @@ from picklescan.scanner import scan_file_path
 import invokeai.backend.util.logging as logger
 from invokeai.app.util.misc import uuid_string
 from invokeai.backend.model_hash.model_hash import HASHING_ALGORITHMS, ModelHash
-from invokeai.backend.util.util import SilenceWarnings
+from invokeai.backend.util.silence_warnings import SilenceWarnings
 
 from .config import (
     AnyModelConfig,
diff --git a/invokeai/backend/util/silence_warnings.py b/invokeai/backend/util/silence_warnings.py
index 4c566ba759..0cd6d0738d 100644
--- a/invokeai/backend/util/silence_warnings.py
+++ b/invokeai/backend/util/silence_warnings.py
@@ -1,29 +1,36 @@
-"""Context class to silence transformers and diffusers warnings."""
-
 import warnings
-from typing import Any
+from contextlib import ContextDecorator
 
-from diffusers import logging as diffusers_logging
+from diffusers.utils import logging as diffusers_logging
 from transformers import logging as transformers_logging
 
 
-class SilenceWarnings(object):
-    """Use in context to temporarily turn off warnings from transformers & diffusers modules.
+# Inherit from ContextDecorator to allow using SilenceWarnings as both a context manager and a decorator.
+class SilenceWarnings(ContextDecorator):
+    """A context manager that disables warnings from transformers & diffusers modules while active.
 
+    As context manager:
+    ```
     with SilenceWarnings():
         # do something
+    ```
+
+    As decorator:
+    ```
+    @SilenceWarnings()
+    def some_function():
+        # do something
+    ```
     """
 
-    def __init__(self) -> None:
-        self.transformers_verbosity = transformers_logging.get_verbosity()
-        self.diffusers_verbosity = diffusers_logging.get_verbosity()
-
     def __enter__(self) -> None:
+        self._transformers_verbosity = transformers_logging.get_verbosity()
+        self._diffusers_verbosity = diffusers_logging.get_verbosity()
         transformers_logging.set_verbosity_error()
         diffusers_logging.set_verbosity_error()
         warnings.simplefilter("ignore")
 
-    def __exit__(self, *args: Any) -> None:
-        transformers_logging.set_verbosity(self.transformers_verbosity)
-        diffusers_logging.set_verbosity(self.diffusers_verbosity)
+    def __exit__(self, *args) -> None:
+        transformers_logging.set_verbosity(self._transformers_verbosity)
+        diffusers_logging.set_verbosity(self._diffusers_verbosity)
         warnings.simplefilter("default")
diff --git a/invokeai/backend/util/util.py b/invokeai/backend/util/util.py
index 1ee89dcc66..b3466ddba9 100644
--- a/invokeai/backend/util/util.py
+++ b/invokeai/backend/util/util.py
@@ -3,12 +3,9 @@ import io
 import os
 import re
 import unicodedata
-import warnings
 from pathlib import Path
 
-from diffusers import logging as diffusers_logging
 from PIL import Image
-from transformers import logging as transformers_logging
 
 # actual size of a gig
 GIG = 1073741824
@@ -80,21 +77,3 @@ class Chdir(object):
 
     def __exit__(self, *args):
         os.chdir(self.original)
-
-
-class SilenceWarnings(object):
-    """Context manager to temporarily lower verbosity of diffusers & transformers warning messages."""
-
-    def __enter__(self):
-        """Set verbosity to error."""
-        self.transformers_verbosity = transformers_logging.get_verbosity()
-        self.diffusers_verbosity = diffusers_logging.get_verbosity()
-        transformers_logging.set_verbosity_error()
-        diffusers_logging.set_verbosity_error()
-        warnings.simplefilter("ignore")
-
-    def __exit__(self, type, value, traceback):
-        """Restore logger verbosity to state before context was entered."""
-        transformers_logging.set_verbosity(self.transformers_verbosity)
-        diffusers_logging.set_verbosity(self.diffusers_verbosity)
-        warnings.simplefilter("default")

From 79ceac2f828e9410be6d2ed0681d9a681eba5d77 Mon Sep 17 00:00:00 2001
From: Ryan Dick <ryanjdick3@gmail.com>
Date: Thu, 6 Jun 2024 10:40:19 -0400
Subject: [PATCH 22/24] (minor) Use SilenceWarnings as a decorator rather than
 a context manager to save an indentation level.

---
 invokeai/app/invocations/denoise_latents.py | 274 ++++++++++----------
 1 file changed, 137 insertions(+), 137 deletions(-)

diff --git a/invokeai/app/invocations/denoise_latents.py b/invokeai/app/invocations/denoise_latents.py
index 41e57ec63e..e94daf70bd 100644
--- a/invokeai/app/invocations/denoise_latents.py
+++ b/invokeai/app/invocations/denoise_latents.py
@@ -657,155 +657,155 @@ class DenoiseLatentsInvocation(BaseInvocation):
         return 1 - mask, masked_latents, self.denoise_mask.gradient
 
     @torch.no_grad()
+    @SilenceWarnings()  # This quenches the NSFW nag from diffusers.
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        with SilenceWarnings():  # this quenches NSFW nag from diffusers
-            seed = None
-            noise = None
-            if self.noise is not None:
-                noise = context.tensors.load(self.noise.latents_name)
-                seed = self.noise.seed
-
-            if self.latents is not None:
-                latents = context.tensors.load(self.latents.latents_name)
-                if seed is None:
-                    seed = self.latents.seed
-
-                if noise is not None and noise.shape[1:] != latents.shape[1:]:
-                    raise Exception(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}")
-
-            elif noise is not None:
-                latents = torch.zeros_like(noise)
-            else:
-                raise Exception("'latents' or 'noise' must be provided!")
+        seed = None
+        noise = None
+        if self.noise is not None:
+            noise = context.tensors.load(self.noise.latents_name)
+            seed = self.noise.seed
 
+        if self.latents is not None:
+            latents = context.tensors.load(self.latents.latents_name)
             if seed is None:
-                seed = 0
+                seed = self.latents.seed
 
-            mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents)
+            if noise is not None and noise.shape[1:] != latents.shape[1:]:
+                raise Exception(f"Incompatable 'noise' and 'latents' shapes: {latents.shape=} {noise.shape=}")
 
-            # TODO(ryand): I have hard-coded `do_classifier_free_guidance=True` to mirror the behaviour of ControlNets,
-            # below. Investigate whether this is appropriate.
-            t2i_adapter_data = self.run_t2i_adapters(
-                context,
-                self.t2i_adapter,
-                latents.shape,
-                do_classifier_free_guidance=True,
+        elif noise is not None:
+            latents = torch.zeros_like(noise)
+        else:
+            raise Exception("'latents' or 'noise' must be provided!")
+
+        if seed is None:
+            seed = 0
+
+        mask, masked_latents, gradient_mask = self.prep_inpaint_mask(context, latents)
+
+        # TODO(ryand): I have hard-coded `do_classifier_free_guidance=True` to mirror the behaviour of ControlNets,
+        # below. Investigate whether this is appropriate.
+        t2i_adapter_data = self.run_t2i_adapters(
+            context,
+            self.t2i_adapter,
+            latents.shape,
+            do_classifier_free_guidance=True,
+        )
+
+        ip_adapters: List[IPAdapterField] = []
+        if self.ip_adapter is not None:
+            # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here.
+            if isinstance(self.ip_adapter, list):
+                ip_adapters = self.ip_adapter
+            else:
+                ip_adapters = [self.ip_adapter]
+
+        # If there are IP adapters, the following line runs the adapters' CLIPVision image encoders to return
+        # a series of image conditioning embeddings. This is being done here rather than in the
+        # big model context below in order to use less VRAM on low-VRAM systems.
+        # The image prompts are then passed to prep_ip_adapter_data().
+        image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapters=ip_adapters)
+
+        # get the unet's config so that we can pass the base to dispatch_progress()
+        unet_config = context.models.get_config(self.unet.unet.key)
+
+        def step_callback(state: PipelineIntermediateState) -> None:
+            context.util.sd_step_callback(state, unet_config.base)
+
+        def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
+            for lora in self.unet.loras:
+                lora_info = context.models.load(lora.lora)
+                assert isinstance(lora_info.model, LoRAModelRaw)
+                yield (lora_info.model, lora.weight)
+                del lora_info
+            return
+
+        unet_info = context.models.load(self.unet.unet)
+        assert isinstance(unet_info.model, UNet2DConditionModel)
+        with (
+            ExitStack() as exit_stack,
+            unet_info.model_on_device() as (model_state_dict, unet),
+            ModelPatcher.apply_freeu(unet, self.unet.freeu_config),
+            set_seamless(unet, self.unet.seamless_axes),  # FIXME
+            # Apply the LoRA after unet has been moved to its target device for faster patching.
+            ModelPatcher.apply_lora_unet(
+                unet,
+                loras=_lora_loader(),
+                model_state_dict=model_state_dict,
+            ),
+        ):
+            assert isinstance(unet, UNet2DConditionModel)
+            latents = latents.to(device=unet.device, dtype=unet.dtype)
+            if noise is not None:
+                noise = noise.to(device=unet.device, dtype=unet.dtype)
+            if mask is not None:
+                mask = mask.to(device=unet.device, dtype=unet.dtype)
+            if masked_latents is not None:
+                masked_latents = masked_latents.to(device=unet.device, dtype=unet.dtype)
+
+            scheduler = get_scheduler(
+                context=context,
+                scheduler_info=self.unet.scheduler,
+                scheduler_name=self.scheduler,
+                seed=seed,
             )
 
-            ip_adapters: List[IPAdapterField] = []
-            if self.ip_adapter is not None:
-                # ip_adapter could be a list or a single IPAdapterField. Normalize to a list here.
-                if isinstance(self.ip_adapter, list):
-                    ip_adapters = self.ip_adapter
-                else:
-                    ip_adapters = [self.ip_adapter]
+            pipeline = self.create_pipeline(unet, scheduler)
 
-            # If there are IP adapters, the following line runs the adapters' CLIPVision image encoders to return
-            # a series of image conditioning embeddings. This is being done here rather than in the
-            # big model context below in order to use less VRAM on low-VRAM systems.
-            # The image prompts are then passed to prep_ip_adapter_data().
-            image_prompts = self.prep_ip_adapter_image_prompts(context=context, ip_adapters=ip_adapters)
+            _, _, latent_height, latent_width = latents.shape
+            conditioning_data = self.get_conditioning_data(
+                context=context, unet=unet, latent_height=latent_height, latent_width=latent_width
+            )
 
-            # get the unet's config so that we can pass the base to dispatch_progress()
-            unet_config = context.models.get_config(self.unet.unet.key)
+            controlnet_data = self.prep_control_data(
+                context=context,
+                control_input=self.control,
+                latents_shape=latents.shape,
+                # do_classifier_free_guidance=(self.cfg_scale >= 1.0))
+                do_classifier_free_guidance=True,
+                exit_stack=exit_stack,
+            )
 
-            def step_callback(state: PipelineIntermediateState) -> None:
-                context.util.sd_step_callback(state, unet_config.base)
+            ip_adapter_data = self.prep_ip_adapter_data(
+                context=context,
+                ip_adapters=ip_adapters,
+                image_prompts=image_prompts,
+                exit_stack=exit_stack,
+                latent_height=latent_height,
+                latent_width=latent_width,
+                dtype=unet.dtype,
+            )
 
-            def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
-                for lora in self.unet.loras:
-                    lora_info = context.models.load(lora.lora)
-                    assert isinstance(lora_info.model, LoRAModelRaw)
-                    yield (lora_info.model, lora.weight)
-                    del lora_info
-                return
+            num_inference_steps, timesteps, init_timestep, scheduler_step_kwargs = self.init_scheduler(
+                scheduler,
+                device=unet.device,
+                steps=self.steps,
+                denoising_start=self.denoising_start,
+                denoising_end=self.denoising_end,
+                seed=seed,
+            )
 
-            unet_info = context.models.load(self.unet.unet)
-            assert isinstance(unet_info.model, UNet2DConditionModel)
-            with (
-                ExitStack() as exit_stack,
-                unet_info.model_on_device() as (model_state_dict, unet),
-                ModelPatcher.apply_freeu(unet, self.unet.freeu_config),
-                set_seamless(unet, self.unet.seamless_axes),  # FIXME
-                # Apply the LoRA after unet has been moved to its target device for faster patching.
-                ModelPatcher.apply_lora_unet(
-                    unet,
-                    loras=_lora_loader(),
-                    model_state_dict=model_state_dict,
-                ),
-            ):
-                assert isinstance(unet, UNet2DConditionModel)
-                latents = latents.to(device=unet.device, dtype=unet.dtype)
-                if noise is not None:
-                    noise = noise.to(device=unet.device, dtype=unet.dtype)
-                if mask is not None:
-                    mask = mask.to(device=unet.device, dtype=unet.dtype)
-                if masked_latents is not None:
-                    masked_latents = masked_latents.to(device=unet.device, dtype=unet.dtype)
+            result_latents = pipeline.latents_from_embeddings(
+                latents=latents,
+                timesteps=timesteps,
+                init_timestep=init_timestep,
+                noise=noise,
+                seed=seed,
+                mask=mask,
+                masked_latents=masked_latents,
+                gradient_mask=gradient_mask,
+                num_inference_steps=num_inference_steps,
+                scheduler_step_kwargs=scheduler_step_kwargs,
+                conditioning_data=conditioning_data,
+                control_data=controlnet_data,
+                ip_adapter_data=ip_adapter_data,
+                t2i_adapter_data=t2i_adapter_data,
+                callback=step_callback,
+            )
 
-                scheduler = get_scheduler(
-                    context=context,
-                    scheduler_info=self.unet.scheduler,
-                    scheduler_name=self.scheduler,
-                    seed=seed,
-                )
+        # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
+        result_latents = result_latents.to("cpu")
+        TorchDevice.empty_cache()
 
-                pipeline = self.create_pipeline(unet, scheduler)
-
-                _, _, latent_height, latent_width = latents.shape
-                conditioning_data = self.get_conditioning_data(
-                    context=context, unet=unet, latent_height=latent_height, latent_width=latent_width
-                )
-
-                controlnet_data = self.prep_control_data(
-                    context=context,
-                    control_input=self.control,
-                    latents_shape=latents.shape,
-                    # do_classifier_free_guidance=(self.cfg_scale >= 1.0))
-                    do_classifier_free_guidance=True,
-                    exit_stack=exit_stack,
-                )
-
-                ip_adapter_data = self.prep_ip_adapter_data(
-                    context=context,
-                    ip_adapters=ip_adapters,
-                    image_prompts=image_prompts,
-                    exit_stack=exit_stack,
-                    latent_height=latent_height,
-                    latent_width=latent_width,
-                    dtype=unet.dtype,
-                )
-
-                num_inference_steps, timesteps, init_timestep, scheduler_step_kwargs = self.init_scheduler(
-                    scheduler,
-                    device=unet.device,
-                    steps=self.steps,
-                    denoising_start=self.denoising_start,
-                    denoising_end=self.denoising_end,
-                    seed=seed,
-                )
-
-                result_latents = pipeline.latents_from_embeddings(
-                    latents=latents,
-                    timesteps=timesteps,
-                    init_timestep=init_timestep,
-                    noise=noise,
-                    seed=seed,
-                    mask=mask,
-                    masked_latents=masked_latents,
-                    gradient_mask=gradient_mask,
-                    num_inference_steps=num_inference_steps,
-                    scheduler_step_kwargs=scheduler_step_kwargs,
-                    conditioning_data=conditioning_data,
-                    control_data=controlnet_data,
-                    ip_adapter_data=ip_adapter_data,
-                    t2i_adapter_data=t2i_adapter_data,
-                    callback=step_callback,
-                )
-
-            # https://discuss.huggingface.co/t/memory-usage-by-later-pipeline-stages/23699
-            result_latents = result_latents.to("cpu")
-            TorchDevice.empty_cache()
-
-            name = context.tensors.save(tensor=result_latents)
+        name = context.tensors.save(tensor=result_latents)
         return LatentsOutput.build(latents_name=name, latents=result_latents, seed=None)

From a43d602f16b41c3023fa9556205af8173345f58b Mon Sep 17 00:00:00 2001
From: steffylo <steffy-lo@hotmail.com>
Date: Wed, 19 Jun 2024 05:32:13 +0800
Subject: [PATCH 23/24] fix(queue): add clear_queue_on_startup config to clear
 problematic queues

---
 invokeai/app/services/config/config_default.py       |  2 ++
 .../services/session_queue/session_queue_sqlite.py   | 12 ++++++++----
 2 files changed, 10 insertions(+), 4 deletions(-)

diff --git a/invokeai/app/services/config/config_default.py b/invokeai/app/services/config/config_default.py
index 496988e853..1dc75add1d 100644
--- a/invokeai/app/services/config/config_default.py
+++ b/invokeai/app/services/config/config_default.py
@@ -113,6 +113,7 @@ class InvokeAIAppConfig(BaseSettings):
         force_tiled_decode: Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty).
         pil_compress_level: The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.
         max_queue_size: Maximum number of items in the session queue.
+        clear_queue_on_startup: Empties session queue on startup.
         allow_nodes: List of nodes to allow. Omit to allow all.
         deny_nodes: List of nodes to deny. Omit to deny none.
         node_cache_size: How many cached nodes to keep in memory.
@@ -186,6 +187,7 @@ class InvokeAIAppConfig(BaseSettings):
     force_tiled_decode:            bool = Field(default=False,              description="Whether to enable tiled VAE decode (reduces memory consumption with some performance penalty).")
     pil_compress_level:             int = Field(default=1,                  description="The compress_level setting of PIL.Image.save(), used for PNG encoding. All settings are lossless. 0 = no compression, 1 = fastest with slightly larger filesize, 9 = slowest with smallest filesize. 1 is typically the best setting.")
     max_queue_size:                 int = Field(default=10000, gt=0,        description="Maximum number of items in the session queue.")
+    clear_queue_on_startup:        bool = Field(default=False,              description="Empties session queue on startup.")
 
     # NODES
     allow_nodes:    Optional[list[str]] = Field(default=None,               description="List of nodes to allow. Omit to allow all.")
diff --git a/invokeai/app/services/session_queue/session_queue_sqlite.py b/invokeai/app/services/session_queue/session_queue_sqlite.py
index 467853aae4..a3a7004c94 100644
--- a/invokeai/app/services/session_queue/session_queue_sqlite.py
+++ b/invokeai/app/services/session_queue/session_queue_sqlite.py
@@ -37,10 +37,14 @@ class SqliteSessionQueue(SessionQueueBase):
     def start(self, invoker: Invoker) -> None:
         self.__invoker = invoker
         self._set_in_progress_to_canceled()
-        prune_result = self.prune(DEFAULT_QUEUE_ID)
-
-        if prune_result.deleted > 0:
-            self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items")
+        if self.__invoker.services.configuration.clear_queue_on_startup:
+            clear_result = self.clear(DEFAULT_QUEUE_ID)
+            if clear_result.deleted > 0:
+                self.__invoker.services.logger.info(f"Cleared all {clear_result.deleted} queue items")
+        else:
+            prune_result = self.prune(DEFAULT_QUEUE_ID)
+            if prune_result.deleted > 0:
+                self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items")
 
     def __init__(self, db: SqliteDatabase) -> None:
         super().__init__()

From b03073d888b5f8cd77a119a4d8612c235c480859 Mon Sep 17 00:00:00 2001
From: Lincoln Stein <lincoln.stein@gmail.com>
Date: Wed, 19 Jun 2024 22:57:27 -0400
Subject: [PATCH 24/24] [MM] Add support for probing and loading SDXL VAE
 checkpoint files (#6524)

* add support for probing and loading SDXL VAE checkpoint files

* broaden regexp probe for SDXL VAEs

---------

Co-authored-by: Lincoln Stein <lstein@gmail.com>
---
 .../backend/model_manager/load/model_loaders/vae.py  | 11 +++--------
 invokeai/backend/model_manager/probe.py              | 12 ++++++++++--
 2 files changed, 13 insertions(+), 10 deletions(-)

diff --git a/invokeai/backend/model_manager/load/model_loaders/vae.py b/invokeai/backend/model_manager/load/model_loaders/vae.py
index 122b2f0797..f51c551f09 100644
--- a/invokeai/backend/model_manager/load/model_loaders/vae.py
+++ b/invokeai/backend/model_manager/load/model_loaders/vae.py
@@ -22,8 +22,7 @@ from .generic_diffusers import GenericDiffusersLoader
 
 
 @ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.VAE, format=ModelFormat.Diffusers)
-@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion1, type=ModelType.VAE, format=ModelFormat.Checkpoint)
-@ModelLoaderRegistry.register(base=BaseModelType.StableDiffusion2, type=ModelType.VAE, format=ModelFormat.Checkpoint)
+@ModelLoaderRegistry.register(base=BaseModelType.Any, type=ModelType.VAE, format=ModelFormat.Checkpoint)
 class VAELoader(GenericDiffusersLoader):
     """Class to load VAE models."""
 
@@ -40,12 +39,8 @@ class VAELoader(GenericDiffusersLoader):
             return True
 
     def _convert_model(self, config: AnyModelConfig, model_path: Path, output_path: Optional[Path] = None) -> AnyModel:
-        # TODO(MM2): check whether sdxl VAE models convert.
-        if config.base not in {BaseModelType.StableDiffusion1, BaseModelType.StableDiffusion2}:
-            raise Exception(f"VAE conversion not supported for model type: {config.base}")
-        else:
-            assert isinstance(config, CheckpointConfigBase)
-            config_file = self._app_config.legacy_conf_path / config.config_path
+        assert isinstance(config, CheckpointConfigBase)
+        config_file = self._app_config.legacy_conf_path / config.config_path
 
         if model_path.suffix == ".safetensors":
             checkpoint = safetensors_load_file(model_path, device="cpu")
diff --git a/invokeai/backend/model_manager/probe.py b/invokeai/backend/model_manager/probe.py
index 4aef281bac..a19a772764 100644
--- a/invokeai/backend/model_manager/probe.py
+++ b/invokeai/backend/model_manager/probe.py
@@ -451,8 +451,16 @@ class PipelineCheckpointProbe(CheckpointProbeBase):
 
 class VaeCheckpointProbe(CheckpointProbeBase):
     def get_base_type(self) -> BaseModelType:
-        # I can't find any standalone 2.X VAEs to test with!
-        return BaseModelType.StableDiffusion1
+        # VAEs of all base types have the same structure, so we wimp out and
+        # guess using the name.
+        for regexp, basetype in [
+            (r"xl", BaseModelType.StableDiffusionXL),
+            (r"sd2", BaseModelType.StableDiffusion2),
+            (r"vae", BaseModelType.StableDiffusion1),
+        ]:
+            if re.search(regexp, self.model_path.name, re.IGNORECASE):
+                return basetype
+        raise InvalidModelConfigException("Cannot determine base type")
 
 
 class LoRACheckpointProbe(CheckpointProbeBase):