feat(ui, nodes): metadata wip

2026-04-23 03:00:31 -04:00 · 2023-04-14 12:52:07 +10:00
parent 49612d69d0
commit 65f2a7ea31
43 changed files with 600 additions and 305 deletions
--- a/invokeai/app/api/routers/images.py
+++ b/invokeai/app/api/routers/images.py
@@ -1,6 +1,8 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 import io
 from datetime import datetime, timezone
+import json
+import os
 import uuid

 from fastapi import Path, Query, Request, UploadFile
@@ -8,6 +10,7 @@ from fastapi.responses import FileResponse, Response
 from fastapi.routing import APIRouter
 from PIL import Image
 from invokeai.app.api.models.images import ImageResponse
+from invokeai.app.models.metadata import ImageMetadata
 from invokeai.app.services.item_storage import PaginatedResults

 from ...services.image_storage import ImageType
@@ -40,32 +43,47 @@ async def get_thumbnail(
    "/uploads/",
    operation_id="upload_image",
    responses={
-        201: {"description": "The image was uploaded successfully"},
+        201: {"description": "The image was uploaded successfully", "model": ImageResponse},
        404: {"description": "Session not found"},
    },
+    status_code=201
 )
-async def upload_image(file: UploadFile, request: Request):
+async def upload_image(file: UploadFile, request: Request, response: Response) -> ImageResponse:
    if not file.content_type.startswith("image"):
        return Response(status_code=415)

    contents = await file.read()
    try:
-        im = Image.open(io.BytesIO(contents))
+        img = Image.open(io.BytesIO(contents))
    except:
        # Error opening the image
        return Response(status_code=415)

    filename = f"{uuid.uuid4()}_{str(int(datetime.now(timezone.utc).timestamp()))}.png"
-    ApiDependencies.invoker.services.images.save(ImageType.UPLOAD, filename, im)
+    image_path = ApiDependencies.invoker.services.images.save(ImageType.UPLOAD, filename, img)
+    invokeai_metadata = json.loads(img.info.get("invokeai", "{}"))

-    return Response(
-        status_code=201,
-        headers={
-            "Location": request.url_for(
+    res = ImageResponse(
+        image_type=ImageType.UPLOAD,
+        image_name=filename,
+        # TODO: DiskImageStorage should not be building URLs...?
+        image_url=f"api/v1/images/{ImageType.UPLOAD.value}/{filename}",
+        thumbnail_url=f"api/v1/images/{ImageType.UPLOAD.value}/thumbnails/{os.path.splitext(filename)[0]}.webp",
+        # TODO: Creation of this object should happen elsewhere, just making it fit here so it works
+        metadata=ImageMetadata(
+            created=int(os.path.getctime(image_path)),
+            width=img.width,
+            height=img.height,
+            invokeai=invokeai_metadata
+        ),
+    )
+
+    response.status_code = 201
+    response.headers["Location"] = request.url_for(
                "get_image", image_type=ImageType.UPLOAD.value, image_name=filename
            )
-        },
-    )
+
+    return res

@images_router.get(
    "/",
--- a/invokeai/app/invocations/cv.py
+++ b/invokeai/app/invocations/cv.py
@@ -9,7 +9,7 @@ from pydantic import BaseModel, Field

 from invokeai.app.models.image import ImageField, ImageType
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output


 class CvInvocationConfig(BaseModel):
@@ -56,7 +56,9 @@ class CvInpaintInvocation(BaseInvocation, CvInvocationConfig):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, image_inpainted)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, image_inpainted, self.dict())
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=image_inpainted,
        )
--- a/invokeai/app/invocations/generate.py
+++ b/invokeai/app/invocations/generate.py
@@ -9,9 +9,9 @@ from torch import Tensor
 from pydantic import BaseModel, Field

 from invokeai.app.models.image import ImageField, ImageType
-from invokeai.app.invocations.util.get_model import choose_model
+from invokeai.app.invocations.util.choose_model import choose_model
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output
 from ...backend.generator import Txt2Img, Img2Img, Inpaint, InvokeAIGenerator
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ..models.exceptions import CanceledException
@@ -76,6 +76,7 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
    def invoke(self, context: InvocationContext) -> ImageOutput:
        # Handle invalid model parameter
        model = choose_model(context.services.model_manager, self.model)
+        self.model_name = model["model_name"]

        outputs = Txt2Img(model).generate(
            prompt=self.prompt,
@@ -95,9 +96,22 @@ class TextToImageInvocation(BaseInvocation, SDImageInvocation):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, generate_output.image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+
+        graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
+        source_id = graph_execution_state.prepared_source_mapping[self.id]
+        invocation = graph_execution_state.execution_graph.get_node(self.id)
+        
+        metadata = {
+          "session": context.graph_execution_state_id,
+          "source_id": source_id,
+          "invocation": invocation.dict()
+        }
+
+        context.services.images.save(image_type, image_name, generate_output.image, metadata)
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=generate_output.image
        )


@@ -144,6 +158,7 @@ class ImageToImageInvocation(TextToImageInvocation):

        # Handle invalid model parameter
        model = choose_model(context.services.model_manager, self.model)
+        self.model = model["model_name"]

        outputs = Img2Img(model).generate(
                prompt=self.prompt,
@@ -168,9 +183,11 @@ class ImageToImageInvocation(TextToImageInvocation):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, result_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, result_image, self.dict())
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=result_image
        )

 class InpaintInvocation(ImageToImageInvocation):
@@ -218,7 +235,8 @@ class InpaintInvocation(ImageToImageInvocation):
        )

        # Handle invalid model parameter
-        model = choose_model(context.services.model_manager, self.model)   
+        model = choose_model(context.services.model_manager, self.model)
+        self.model = model["model_name"]

        outputs = Inpaint(model).generate(
                prompt=self.prompt,
@@ -243,7 +261,9 @@ class InpaintInvocation(ImageToImageInvocation):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, result_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, result_image, self.dict())
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=result_image
        )
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -9,7 +9,12 @@ from pydantic import BaseModel, Field

 from ..models.image import ImageField, ImageType
 from ..services.invocation_services import InvocationServices
-from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext, InvocationConfig
+from .baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    InvocationContext,
+    InvocationConfig,
+)


 class PILInvocationConfig(BaseModel):
@@ -22,51 +27,70 @@ class PILInvocationConfig(BaseModel):
            },
        }

+
 class ImageOutput(BaseInvocationOutput):
    """Base class for invocations that output an image"""
-    #fmt: off
+
+    # fmt: off
    type: Literal["image"] = "image"
    image:      ImageField = Field(default=None, description="The output image")
-    #fmt: on
+    width:             int = Field(description="The width of the image in pixels")
+    height:            int = Field(description="The height of the image in pixels")
+    # fmt: on

    class Config:
        schema_extra = {
-            'required': [
-                'type',
-                'image',
+            "required": [
+                "type",
+                "image",
+                "width",
+                "height",
            ]
        }

+
+def build_image_output(
+    image_type: ImageType, image_name: str, image: Image.Image
+) -> ImageOutput:
+    image_field = ImageField(image_name=image_name, image_type=image_type)
+
+    return ImageOutput(image=image_field, width=image.width, height=image.height)
+
+
 class MaskOutput(BaseInvocationOutput):
    """Base class for invocations that output a mask"""
-    #fmt: off
+
+    # fmt: off
    type: Literal["mask"] = "mask"
    mask:      ImageField = Field(default=None, description="The output mask")
-    #fmt: on
+    # fmt: on

    class Config:
        schema_extra = {
-            'required': [
-                'type',
-                'mask',
+            "required": [
+                "type",
+                "mask",
            ]
        }

-# TODO: this isn't really necessary anymore
-class LoadImageInvocation(BaseInvocation):
-    """Load an image from a filename and provide it as output."""
-    #fmt: off
-    type: Literal["load_image"] = "load_image"

-    # Inputs
-    image_type: ImageType = Field(description="The type of the image")
-    image_name:       str = Field(description="The name of the image")
-    #fmt: on
+# # TODO: this isn't really necessary anymore
+# class LoadImageInvocation(BaseInvocation):
+#     """Load an image from a filename and provide it as output."""
+#     #fmt: off
+#     type: Literal["load_image"] = "load_image"

-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        return ImageOutput(
-            image=ImageField(image_type=self.image_type, image_name=self.image_name)
-        )
+#     # Inputs
+#     image_type: ImageType = Field(description="The type of the image")
+#     image_name:       str = Field(description="The name of the image")
+#     #fmt: on
+
+#     def invoke(self, context: InvocationContext) -> ImageOutput:
+#         return ImageOutput(
+#             image_type=self.image_type,
+#             image_name=self.image_name,
+#             image=result_image
+#         )


 class ShowImageInvocation(BaseInvocation):
@@ -86,16 +110,17 @@ class ShowImageInvocation(BaseInvocation):

        # TODO: how to handle failure?

-        return ImageOutput(
-            image=ImageField(
-                image_type=self.image.image_type, image_name=self.image.image_name
-            )
+        return build_image_output(
+            image_type=self.image.image_type,
+            image_name=self.image.image_name,
+            image=image,
        )


 class CropImageInvocation(BaseInvocation, PILInvocationConfig):
    """Crops an image to a specified box. The box can be outside of the image."""
-    #fmt: off
+
+    # fmt: off
    type: Literal["crop"] = "crop"

    # Inputs
@@ -104,7 +129,7 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
    y:      int = Field(default=0, description="The top y coordinate of the crop rectangle")
    width:  int = Field(default=512, gt=0, description="The width of the crop rectangle")
    height: int = Field(default=512, gt=0, description="The height of the crop rectangle")
-    #fmt: on
+    # fmt: on

    def invoke(self, context: InvocationContext) -> ImageOutput:
        image = context.services.images.get(
@@ -120,15 +145,16 @@ class CropImageInvocation(BaseInvocation, PILInvocationConfig):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, image_crop)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, image_crop, self.dict())
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=image_crop
        )


 class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
    """Pastes an image into another image."""
-    #fmt: off
+
+    # fmt: off
    type: Literal["paste"] = "paste"

    # Inputs
@@ -137,7 +163,7 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
    mask: Optional[ImageField] = Field(default=None, description="The mask to use when pasting")
    x:                     int = Field(default=0, description="The left x coordinate at which to paste the image")
    y:                     int = Field(default=0, description="The top y coordinate at which to paste the image")
-    #fmt: on
+    # fmt: on

    def invoke(self, context: InvocationContext) -> ImageOutput:
        base_image = context.services.images.get(
@@ -170,21 +196,22 @@ class PasteImageInvocation(BaseInvocation, PILInvocationConfig):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, new_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, new_image, self.dict())
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=new_image
        )


 class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
    """Extracts the alpha channel of an image as a mask."""
-    #fmt: off
+
+    # fmt: off
    type: Literal["tomask"] = "tomask"

    # Inputs
    image: ImageField = Field(default=None, description="The image to create the mask from")
    invert:      bool = Field(default=False, description="Whether or not to invert the mask")
-    #fmt: on
+    # fmt: on

    def invoke(self, context: InvocationContext) -> MaskOutput:
        image = context.services.images.get(
@@ -199,22 +226,22 @@ class MaskFromAlphaInvocation(BaseInvocation, PILInvocationConfig):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, image_mask)
+        context.services.images.save(image_type, image_name, image_mask, self.dict())
        return MaskOutput(mask=ImageField(image_type=image_type, image_name=image_name))


 class BlurInvocation(BaseInvocation, PILInvocationConfig):
    """Blurs an image"""

-    #fmt: off
+    # fmt: off
    type: Literal["blur"] = "blur"

    # Inputs
    image: ImageField = Field(default=None, description="The image to blur")
    radius:     float = Field(default=8.0, ge=0, description="The blur radius")
    blur_type: Literal["gaussian", "box"] = Field(default="gaussian", description="The type of blur")
-    #fmt: on
-    
+    # fmt: on
+
    def invoke(self, context: InvocationContext) -> ImageOutput:
        image = context.services.images.get(
            self.image.image_type, self.image.image_name
@@ -231,22 +258,23 @@ class BlurInvocation(BaseInvocation, PILInvocationConfig):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, blur_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, blur_image, self.dict())
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=blur_image
        )


 class LerpInvocation(BaseInvocation, PILInvocationConfig):
    """Linear interpolation of all pixels of an image"""
-    #fmt: off
+
+    # fmt: off
    type: Literal["lerp"] = "lerp"

    # Inputs
    image: ImageField = Field(default=None, description="The image to lerp")
    min: int = Field(default=0, ge=0, le=255, description="The minimum output value")
    max: int = Field(default=255, ge=0, le=255, description="The maximum output value")
-    #fmt: on
+    # fmt: on

    def invoke(self, context: InvocationContext) -> ImageOutput:
        image = context.services.images.get(
@@ -262,23 +290,24 @@ class LerpInvocation(BaseInvocation, PILInvocationConfig):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, lerp_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, lerp_image, self.dict())
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=lerp_image
        )


 class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
    """Inverse linear interpolation of all pixels of an image"""
-    #fmt: off
+
+    # fmt: off
    type: Literal["ilerp"] = "ilerp"

    # Inputs
    image: ImageField = Field(default=None, description="The image to lerp")
    min: int = Field(default=0, ge=0, le=255, description="The minimum input value")
    max: int = Field(default=255, ge=0, le=255, description="The maximum input value")
-    #fmt: on
-    
+    # fmt: on
+
    def invoke(self, context: InvocationContext) -> ImageOutput:
        image = context.services.images.get(
            self.image.image_type, self.image.image_name
@@ -298,7 +327,7 @@ class InverseLerpInvocation(BaseInvocation, PILInvocationConfig):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, ilerp_image)
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
+        context.services.images.save(image_type, image_name, ilerp_image, self.dict())
+        return build_image_output(
+            image_type=image_type, image_name=image_name, image=ilerp_image
        )
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -6,7 +6,7 @@ from pydantic import BaseModel, Field
 import torch

 from invokeai.app.models.exceptions import CanceledException
-from invokeai.app.invocations.util.get_model import choose_model
+from invokeai.app.invocations.util.choose_model import choose_model
 from invokeai.app.util.step_callback import diffusers_step_callback_adapter

 from ...backend.model_management.model_manager import ModelManager
@@ -19,7 +19,7 @@ from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationCont
 import numpy as np
 from ..services.image_storage import ImageType
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput
+from .image import ImageField, ImageOutput, build_image_output
 from ...backend.stable_diffusion import PipelineIntermediateState
 from diffusers.schedulers import SchedulerMixin as Scheduler
 import diffusers
@@ -405,7 +405,9 @@ class LatentsToImageInvocation(BaseInvocation):
            image_name = context.services.images.create_name(
                context.graph_execution_state_id, self.id
            )
-            context.services.images.save(image_type, image_name, image)
-            return ImageOutput(
-                image=ImageField(image_type=image_type, image_name=image_name)
+            context.services.images.save(image_type, image_name, image, self.dict())
+            return build_image_output(
+                image_type=image_type,
+                image_name=image_name,
+                image=image
            )
--- a/invokeai/app/invocations/reconstruct.py
+++ b/invokeai/app/invocations/reconstruct.py
@@ -6,7 +6,7 @@ from pydantic import Field
 from invokeai.app.models.image import ImageField, ImageType
 from ..services.invocation_services import InvocationServices
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output

 class RestoreFaceInvocation(BaseInvocation):
    """Restores faces in an image."""
@@ -44,7 +44,9 @@ class RestoreFaceInvocation(BaseInvocation):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, results[0][0])
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
-        )
+        context.services.images.save(image_type, image_name, results[0][0], self.dict())
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=results[0][0]
+        )
--- a/invokeai/app/invocations/upscale.py
+++ b/invokeai/app/invocations/upscale.py
@@ -8,7 +8,7 @@ from pydantic import Field
 from invokeai.app.models.image import ImageField, ImageType
 from ..services.invocation_services import InvocationServices
 from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from .image import ImageOutput
+from .image import ImageOutput, build_image_output


 class UpscaleInvocation(BaseInvocation):
@@ -49,7 +49,9 @@ class UpscaleInvocation(BaseInvocation):
        image_name = context.services.images.create_name(
            context.graph_execution_state_id, self.id
        )
-        context.services.images.save(image_type, image_name, results[0][0])
-        return ImageOutput(
-            image=ImageField(image_type=image_type, image_name=image_name)
-        )
+        context.services.images.save(image_type, image_name, results[0][0], self.dict())
+        return build_image_output(
+            image_type=image_type,
+            image_name=image_name,
+            image=results[0][0]
+        )
--- a/invokeai/app/invocations/util/choose_model.py
+++ b/invokeai/app/invocations/util/choose_model.py
@@ -1,11 +1,14 @@
-from invokeai.app.invocations.baseinvocation import InvocationContext
 from invokeai.backend.model_management.model_manager import ModelManager


 def choose_model(model_manager: ModelManager, model_name: str):
    """Returns the default model if the `model_name` not a valid model, else returns the selected model."""
    if model_manager.valid_model(model_name):
-        return model_manager.get_model(model_name)
+        model = model_manager.get_model(model_name)
    else:
-        print(f"* Warning: '{model_name}' is not a valid model name. Using default model instead.")
-        return model_manager.get_model()
+        model = model_manager.get_model()
+        print(
+            f"* Warning: '{model_name}' is not a valid model name. Using default model \'{model['model_name']}\' instead."
+        )
+
+    return model
--- a/invokeai/app/models/metadata.py
+++ b/invokeai/app/models/metadata.py
@@ -1,11 +1,26 @@
-from typing import Optional
+from typing import Any, Optional, Dict
 from pydantic import BaseModel, Field

-class ImageMetadata(BaseModel):
-    """An image's metadata"""

-    timestamp: float = Field(description="The creation timestamp of the image")
+class InvokeAIMetadata(BaseModel):
+    """An image's InvokeAI-specific metadata"""
+
+    session: Optional[str] = Field(description="The session that generated this image")
+    source_id: Optional[str] = Field(
+        description="The source id of the invocation that generated this image"
+    )
+    # TODO: figure out metadata
+    invocation: Optional[Dict[str, Any]] = Field(
+        default={}, description="The prepared invocation that generated this image"
+    )
+
+
+class ImageMetadata(BaseModel):
+    """An image's general metadata"""
+
+    created: int = Field(description="The creation timestamp of the image")
    width: int = Field(description="The width of the image in pixels")
    height: int = Field(description="The height of the image in pixels")
-    # TODO: figure out metadata
-    sd_metadata: Optional[dict] = Field(default={}, description="The image's SD-specific metadata")
+    invokeai: Optional[InvokeAIMetadata] = Field(
+        default={}, description="The image's InvokeAI-specific metadata"
+    )
--- a/invokeai/app/services/events.py
+++ b/invokeai/app/services/events.py
@@ -25,7 +25,8 @@ class EventServiceBase:
    def emit_generator_progress(
        self,
        graph_execution_state_id: str,
-        invocation_id: str,
+        invocation_dict: dict,
+        source_id: str,
        progress_image: ProgressImage | None,
        step: int,
        total_steps: int,
@@ -35,7 +36,8 @@ class EventServiceBase:
            event_name="generator_progress",
            payload=dict(
                graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                invocation=invocation_dict,
+                source_id=source_id,
                progress_image=progress_image,
                step=step,
                total_steps=total_steps,
@@ -43,40 +45,43 @@ class EventServiceBase:
        )

    def emit_invocation_complete(
-        self, graph_execution_state_id: str, invocation_id: str, result: Dict
+        self, graph_execution_state_id: str, result: Dict, invocation_dict: Dict, source_id: str,
    ) -> None:
        """Emitted when an invocation has completed"""
        self.__emit_session_event(
            event_name="invocation_complete",
            payload=dict(
                graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                invocation=invocation_dict,
+                source_id=source_id,
                result=result,
            ),
        )

    def emit_invocation_error(
-        self, graph_execution_state_id: str, invocation_id: str, error: str
+        self, graph_execution_state_id: str, invocation_dict: Dict, source_id: str, error: str
    ) -> None:
        """Emitted when an invocation has completed"""
        self.__emit_session_event(
            event_name="invocation_error",
            payload=dict(
                graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                invocation=invocation_dict,
+                source_id=source_id,
                error=error,
            ),
        )

    def emit_invocation_started(
-        self, graph_execution_state_id: str, invocation_id: str
+        self, graph_execution_state_id: str, invocation_dict: Dict, source_id: str
    ) -> None:
        """Emitted when an invocation has started"""
        self.__emit_session_event(
            event_name="invocation_started",
            payload=dict(
                graph_execution_state_id=graph_execution_state_id,
-                invocation_id=invocation_id,
+                invocation=invocation_dict,
+                source_id=source_id,
            ),
        )

--- a/invokeai/app/services/image_storage.py
+++ b/invokeai/app/services/image_storage.py
@@ -2,16 +2,17 @@

 import datetime
 import os
+import json
 from glob import glob
 from abc import ABC, abstractmethod
 from enum import Enum
 from pathlib import Path
 from queue import Queue
-from typing import Callable, Dict, List
+from typing import Any, Callable, Dict, List, Union

 from PIL.Image import Image
 import PIL.Image as PILImage
-from pydantic import BaseModel
+from pydantic import BaseModel, Json
 from invokeai.app.api.models.images import ImageResponse
 from invokeai.app.models.image import ImageField, ImageType
 from invokeai.app.models.metadata import ImageMetadata
@@ -42,7 +43,7 @@ class ImageStorageBase(ABC):
        pass

    @abstractmethod
-    def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
+    def save(self, image_type: ImageType, image_name: str, image: Image, metadata: Dict[str, Any] | None = None) -> str:
        pass

    @abstractmethod
@@ -100,6 +101,8 @@ class DiskImageStorage(ImageStorageBase):
        for path in page_of_image_paths:
            filename = os.path.basename(path)
            img = PILImage.open(path)
+            invokeai_metadata = json.loads(img.info.get("invokeai", "{}"))
+
            page_of_images.append(
                ImageResponse(
                    image_type=image_type.value,
@@ -109,9 +112,10 @@ class DiskImageStorage(ImageStorageBase):
                    thumbnail_url=f"api/v1/images/{image_type.value}/thumbnails/{os.path.splitext(filename)[0]}.webp",
                    # TODO: Creation of this object should happen elsewhere, just making it fit here so it works
                    metadata=ImageMetadata(
-                        timestamp=os.path.getctime(path),
+                        created=int(os.path.getctime(path)),
                        width=img.width,
                        height=img.height,
+                        invokeai=invokeai_metadata
                    ),
                )
            )
@@ -150,10 +154,11 @@ class DiskImageStorage(ImageStorageBase):
            path = os.path.join(self.__output_folder, image_type, image_name)
        return path

-    def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
+    def save(self, image_type: ImageType, image_name: str, image: Image, metadata: Dict[str, Any] | None = None) -> str:
+        print(metadata)
        image_subpath = os.path.join(image_type, image_name)
        self.__pngWriter.save_image_and_prompt_to_png(
-            image, "", image_subpath, None
+            image, "", image_subpath, metadata
        )  # TODO: just pass full path to png writer
        save_thumbnail(
            image=image,
@@ -162,6 +167,7 @@ class DiskImageStorage(ImageStorageBase):
        )
        image_path = self.get_path(image_type, image_name)
        self.__set_cache(image_path, image)
+        return image_path

    def delete(self, image_type: ImageType, image_name: str) -> None:
        image_path = self.get_path(image_type, image_name)
--- a/invokeai/app/services/processor.py
+++ b/invokeai/app/services/processor.py
@@ -43,10 +43,14 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                    queue_item.invocation_id
                )

+                # get the source node to provide to cliepnts (the prepared node is not as useful)
+                source_id = graph_execution_state.prepared_source_mapping[invocation.id]
+
                # Send starting event
                self.__invoker.services.events.emit_invocation_started(
                    graph_execution_state_id=graph_execution_state.id,
-                    invocation_id=invocation.id,
+                    invocation_dict=invocation.dict(),
+                    source_id=source_id
                )

                # Invoke
@@ -75,7 +79,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                    # Send complete event
                    self.__invoker.services.events.emit_invocation_complete(
                        graph_execution_state_id=graph_execution_state.id,
-                        invocation_id=invocation.id,
+                        invocation_dict=invocation.dict(),
+                        source_id=source_id,
                        result=outputs.dict(),
                    )

@@ -99,7 +104,8 @@ class DefaultInvocationProcessor(InvocationProcessorABC):
                    # Send error event
                    self.__invoker.services.events.emit_invocation_error(
                        graph_execution_state_id=graph_execution_state.id,
-                        invocation_id=invocation.id,
+                        invocation_dict=invocation.dict(),
+                        source_id=source_id,
                        error=error,
                    )

--- a/invokeai/app/services/sqlite.py
+++ b/invokeai/app/services/sqlite.py
@@ -1,4 +1,4 @@
-from typing import Generic, TypeVar, Union, get_args, get_origin
+from typing import Generic, TypeVar, Union, get_args
 from pydantic import BaseModel, parse_raw_as

 from .item_storage import ItemStorageABC, PaginatedResults
--- a/invokeai/app/util/step_callback.py
+++ b/invokeai/app/util/step_callback.py
@@ -1,3 +1,4 @@
+from re import S
 import torch
 from ..invocations.baseinvocation import InvocationContext
 from ...backend.util.util import image_to_dataURL
@@ -20,12 +21,18 @@ def fast_latents_step_callback(

    dataURL = image_to_dataURL(image, image_format="JPEG")

+    graph_execution_state = context.services.graph_execution_manager.get(context.graph_execution_state_id)
+    source_id = graph_execution_state.prepared_source_mapping[id]
+
+    invocation = graph_execution_state.execution_graph.get_node(id)
+
    context.services.events.emit_generator_progress(
-        context.graph_execution_state_id,
-        id,
-        {"width": width, "height": height, "dataURL": dataURL},
-        step,
-        steps,
+        graph_execution_state_id=context.graph_execution_state_id,
+        invocation_dict=invocation.dict(),
+        source_id=source_id,
+        progress_image={"width": width, "height": height, "dataURL": dataURL},
+        step=step,
+        total_steps=steps,
    )


--- a/invokeai/backend/image_util/pngwriter.py
+++ b/invokeai/backend/image_util/pngwriter.py
@@ -41,7 +41,7 @@ class PngWriter:
        info = PngImagePlugin.PngInfo()
        info.add_text("Dream", dream_prompt)
        if metadata:
-            info.add_text("sd-metadata", json.dumps(metadata))
+            info.add_text("invokeai", json.dumps(metadata))
        image.save(path, "PNG", pnginfo=info, compress_level=compress_level)
        return path

--- a/invokeai/frontend/web/src/app/invokeai.d.ts
+++ b/invokeai/frontend/web/src/app/invokeai.d.ts
@@ -15,6 +15,7 @@
 import { InvokeTabName } from 'features/ui/store/tabMap';
 import { IRect } from 'konva/lib/types';
 import { ImageMetadata, ImageType } from 'services/api';
+import { AnyInvocation } from 'services/events/types';

 /**
 * TODO:
--- a/invokeai/frontend/web/src/app/store.ts
+++ b/invokeai/frontend/web/src/app/store.ts
@@ -6,19 +6,31 @@ import dynamicMiddlewares from 'redux-dynamic-middlewares';
 import { getPersistConfig } from 'redux-deep-persist';

 import canvasReducer from 'features/canvas/store/canvasSlice';
-import galleryReducer from 'features/gallery/store/gallerySlice';
-import resultsReducer from 'features/gallery/store/resultsSlice';
+import galleryReducer, {
+  GalleryState,
+} from 'features/gallery/store/gallerySlice';
+import resultsReducer, {
+  resultsAdapter,
+  ResultsState,
+} from 'features/gallery/store/resultsSlice';
 import uploadsReducer from 'features/gallery/store/uploadsSlice';
-import lightboxReducer from 'features/lightbox/store/lightboxSlice';
-import generationReducer from 'features/parameters/store/generationSlice';
-import postprocessingReducer from 'features/parameters/store/postprocessingSlice';
-import systemReducer from 'features/system/store/systemSlice';
+import lightboxReducer, {
+  LightboxState,
+} from 'features/lightbox/store/lightboxSlice';
+import generationReducer, {
+  GenerationState,
+} from 'features/parameters/store/generationSlice';
+import postprocessingReducer, {
+  PostprocessingState,
+} from 'features/parameters/store/postprocessingSlice';
+import systemReducer, { SystemState } from 'features/system/store/systemSlice';
 import uiReducer from 'features/ui/store/uiSlice';
 import modelsReducer from 'features/system/store/modelSlice';
-import nodesReducer from 'features/nodes/store/nodesSlice';
+import nodesReducer, { NodesState } from 'features/nodes/store/nodesSlice';

 import { socketioMiddleware } from './socketio/middleware';
 import { socketMiddleware } from 'services/events/middleware';
+import { CanvasState } from 'features/canvas/store/canvasTypes';

 /**
 * redux-persist provides an easy and reliable way to persist state across reloads.
@@ -34,13 +46,21 @@ import { socketMiddleware } from 'services/events/middleware';
 * The necesssary nested persistors with blacklists are configured below.
 */

-const canvasBlacklist = [
+/**
+ * Canvas slice persist blacklist
+ */
+const canvasBlacklist: (keyof CanvasState)[] = [
  'cursorPosition',
  'isCanvasInitialized',
  'doesCanvasNeedScaling',
-].map((blacklistItem) => `canvas.${blacklistItem}`);
+];

-const systemBlacklist = [
+canvasBlacklist.map((blacklistItem) => `canvas.${blacklistItem}`);
+
+/**
+ * System slice persist blacklist
+ */
+const systemBlacklist: (keyof SystemState)[] = [
  'currentIteration',
  'currentStatus',
  'currentStep',
@@ -53,40 +73,101 @@ const systemBlacklist = [
  'totalIterations',
  'totalSteps',
  'openModel',
-  'cancelOptions.cancelAfter',
  'isCancelScheduled',
  'sessionId',
-].map((blacklistItem) => `system.${blacklistItem}`);
+  'progressImage',
+];

-const galleryBlacklist = [
+systemBlacklist.map((blacklistItem) => `system.${blacklistItem}`);
+
+/**
+ * Gallery slice persist blacklist
+ */
+const galleryBlacklist: (keyof GalleryState)[] = [
  'categories',
  'currentCategory',
  'currentImage',
  'currentImageUuid',
  'shouldAutoSwitchToNewImages',
  'intermediateImage',
-].map((blacklistItem) => `gallery.${blacklistItem}`);
+];

-const lightboxBlacklist = ['isLightboxOpen'].map(
-  (blacklistItem) => `lightbox.${blacklistItem}`
+galleryBlacklist.map((blacklistItem) => `gallery.${blacklistItem}`);
+
+/**
+ * Lightbox slice persist blacklist
+ */
+const lightboxBlacklist: (keyof LightboxState)[] = ['isLightboxOpen'];
+
+lightboxBlacklist.map((blacklistItem) => `lightbox.${blacklistItem}`);
+
+/**
+ * Nodes slice persist blacklist
+ */
+const nodesBlacklist: (keyof NodesState)[] = ['schema', 'invocations'];
+
+nodesBlacklist.map((blacklistItem) => `nodes.${blacklistItem}`);
+
+/**
+ * Generation slice persist blacklist
+ */
+const generationBlacklist: (keyof GenerationState)[] = [];
+
+generationBlacklist.map((blacklistItem) => `generation.${blacklistItem}`);
+
+/**
+ * Postprocessing slice persist blacklist
+ */
+const postprocessingBlacklist: (keyof PostprocessingState)[] = [];
+
+postprocessingBlacklist.map(
+  (blacklistItem) => `postprocessing.${blacklistItem}`
 );

-const nodesBlacklist = ['schema', 'invocations'].map(
-  (blacklistItem) => `nodes.${blacklistItem}`
-);
+/**
+ * Results slice persist blacklist
+ *
+ * Currently blacklisting results slice entirely, see persist config below
+ */
+const resultsBlacklist: (keyof ResultsState)[] = [];
+
+resultsBlacklist.map((blacklistItem) => `results.${blacklistItem}`);
+
+/**
+ * Uploads slice persist blacklist
+ *
+ * Currently blacklisting uploads slice entirely, see persist config below
+ */
+const uploadsBlacklist: (keyof NodesState)[] = [];
+
+uploadsBlacklist.map((blacklistItem) => `uploads.${blacklistItem}`);
+
+/**
+ * Models slice persist blacklist
+ */
+const modelsBlacklist: (keyof NodesState)[] = [];
+
+modelsBlacklist.map((blacklistItem) => `models.${blacklistItem}`);
+
+/**
+ * UI slice persist blacklist
+ */
+const uiBlacklist: (keyof NodesState)[] = [];
+
+uiBlacklist.map((blacklistItem) => `ui.${blacklistItem}`);

 const rootReducer = combineReducers({
-  generation: generationReducer,
-  postprocessing: postprocessingReducer,
-  gallery: galleryReducer,
-  system: systemReducer,
  canvas: canvasReducer,
-  ui: uiReducer,
+  gallery: galleryReducer,
+  generation: generationReducer,
  lightbox: lightboxReducer,
-  results: resultsReducer,
-  uploads: uploadsReducer,
  models: modelsReducer,
  nodes: nodesReducer,
+  postprocessing: postprocessingReducer,
+  results: resultsReducer,
+  system: systemReducer,
+  ui: uiReducer,
+  uploads: uploadsReducer,
 });

 const rootPersistConfig = getPersistConfig({
@@ -95,13 +176,18 @@ const rootPersistConfig = getPersistConfig({
  rootReducer,
  blacklist: [
    ...canvasBlacklist,
-    ...systemBlacklist,
    ...galleryBlacklist,
+    ...generationBlacklist,
    ...lightboxBlacklist,
+    ...modelsBlacklist,
    ...nodesBlacklist,
+    ...postprocessingBlacklist,
+    // ...resultsBlacklist,
    'results',
+    ...systemBlacklist,
+    ...uiBlacklist,
+    // ...uploadsBlacklist,
    'uploads',
-    // 'nodes',
  ],
  debounce: 300,
 });
--- a/invokeai/frontend/web/src/common/util/buildGraph.ts
+++ b/invokeai/frontend/web/src/common/util/buildGraph.ts
@@ -66,5 +66,7 @@ export const buildGraph = (state: RootState): BuildGraphOutput => {
    nodeIdsToSubscribe.push(Object.keys(node)[0]);
  }

+  console.log('buildGraph: ', graph);
+
  return { graph, nodeIdsToSubscribe };
 };
--- a/invokeai/frontend/web/src/common/util/getUrl.ts
+++ b/invokeai/frontend/web/src/common/util/getUrl.ts
@@ -2,6 +2,14 @@ import { RootState } from 'app/store';
 import { useAppSelector } from 'app/storeHooks';
 import { OpenAPI } from 'services/api';

+export const getUrlAlt = (url: string, shouldTransformUrls: boolean) => {
+  if (OpenAPI.BASE && shouldTransformUrls) {
+    return [OpenAPI.BASE, url].join('/');
+  }
+
+  return url;
+};
+
 export const useGetUrl = () => {
  const shouldTransformUrls = useAppSelector(
    (state: RootState) => state.system.shouldTransformUrls
@@ -11,11 +19,9 @@ export const useGetUrl = () => {
    shouldTransformUrls,
    getUrl: (url: string) => {
      if (OpenAPI.BASE && shouldTransformUrls) {
-        console.log('transformed');
        return [OpenAPI.BASE, url].join('/');
      }

-      console.log('didnt transform');
      return url;
    },
  };
--- a/invokeai/frontend/web/src/features/gallery/components/CurrentImagePreview.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/CurrentImagePreview.tsx
@@ -5,6 +5,7 @@ import { useGetUrl } from 'common/util/getUrl';
 import { systemSelector } from 'features/system/store/systemSelectors';
 import { uiSelector } from 'features/ui/store/uiSelectors';
 import { isEqual } from 'lodash';
+import { ReactEventHandler } from 'react';
 import { APP_METADATA_HEIGHT } from 'theme/util/constants';

 import { selectedImageSelector } from '../store/gallerySelectors';
--- a/invokeai/frontend/web/src/features/gallery/components/ImageMetaDataViewer/ImageMetadataViewer.tsx
+++ b/invokeai/frontend/web/src/features/gallery/components/ImageMetaDataViewer/ImageMetadataViewer.tsx
@@ -46,6 +46,7 @@ import { useHotkeys } from 'react-hotkeys-hook';
 import { useTranslation } from 'react-i18next';
 import { FaCopy } from 'react-icons/fa';
 import { IoArrowUndoCircleOutline } from 'react-icons/io5';
+import * as png from '@stevebel/png';

 type MetadataItemProps = {
  isLink?: boolean;
@@ -167,7 +168,17 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
  const { t } = useTranslation();
  const { getUrl } = useGetUrl();

-  const metadataJSON = JSON.stringify(image.metadata, null, 2);
+  const metadataJSON = JSON.stringify(image, null, 2);
+
+  // fetch(getUrl(image.url))
+  //   .then((r) => r.arrayBuffer())
+  //   .then((buffer) => {
+  //     const { text } = png.decode(buffer);
+  //     const metadata = text?.['sd-metadata']
+  //       ? JSON.parse(text['sd-metadata'] ?? {})
+  //       : {};
+  //     console.log(metadata);
+  //   });

  return (
    <Flex
@@ -193,6 +204,37 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
          <ExternalLinkIcon mx="2px" />
        </Link>
      </Flex>
+      <Flex gap={2} direction="column">
+        <Flex gap={2}>
+          <Tooltip label="Copy metadata JSON">
+            <IconButton
+              aria-label={t('accessibility.copyMetadataJson')}
+              icon={<FaCopy />}
+              size="xs"
+              variant="ghost"
+              fontSize={14}
+              onClick={() => navigator.clipboard.writeText(metadataJSON)}
+            />
+          </Tooltip>
+          <Text fontWeight="semibold">Metadata JSON:</Text>
+        </Flex>
+        <Box
+          sx={{
+            mt: 0,
+            mr: 2,
+            mb: 4,
+            ml: 2,
+            padding: 4,
+            borderRadius: 'base',
+            overflowX: 'scroll',
+            wordBreak: 'break-all',
+            bg: 'whiteAlpha.500',
+            _dark: { bg: 'blackAlpha.500' },
+          }}
+        >
+          <pre>{metadataJSON}</pre>
+        </Box>
+      </Flex>
      {Object.keys(metadata).length > 0 ? (
        <>
          {type && <MetadataItem label="Generation type" value={type} />}
@@ -411,37 +453,6 @@ const ImageMetadataViewer = memo(({ image }: ImageMetadataViewerProps) => {
          {dreamPrompt && (
            <MetadataItem withCopy label="Dream Prompt" value={dreamPrompt} />
          )}
-          <Flex gap={2} direction="column">
-            <Flex gap={2}>
-              <Tooltip label="Copy metadata JSON">
-                <IconButton
-                  aria-label={t('accessibility.copyMetadataJson')}
-                  icon={<FaCopy />}
-                  size="xs"
-                  variant="ghost"
-                  fontSize={14}
-                  onClick={() => navigator.clipboard.writeText(metadataJSON)}
-                />
-              </Tooltip>
-              <Text fontWeight="semibold">Metadata JSON:</Text>
-            </Flex>
-            <Box
-              sx={{
-                mt: 0,
-                mr: 2,
-                mb: 4,
-                ml: 2,
-                padding: 4,
-                borderRadius: 'base',
-                overflowX: 'scroll',
-                wordBreak: 'break-all',
-                bg: 'whiteAlpha.500',
-                _dark: { bg: 'blackAlpha.500' },
-              }}
-            >
-              <pre>{metadataJSON}</pre>
-            </Box>
-          </Flex>
        </>
      ) : (
        <Center width="100%" pt={10}>
--- a/invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts
+++ b/invokeai/frontend/web/src/features/gallery/store/gallerySlice.ts
@@ -295,7 +295,7 @@ export const gallerySlice = createSlice({
     * Upload Image - FULFILLED
     */
    builder.addCase(imageUploaded.fulfilled, (state, action) => {
-      const location = action.payload;
+      const { location } = action.payload;
      const imageName = location.split('/').pop() || '';
      state.selectedImageName = imageName;
    });
--- a/invokeai/frontend/web/src/features/gallery/store/resultsSlice.ts
+++ b/invokeai/frontend/web/src/features/gallery/store/resultsSlice.ts
@@ -8,8 +8,14 @@ import {
  IMAGES_PER_PAGE,
 } from 'services/thunks/gallery';
 import { isImageOutput } from 'services/types/guards';
-import { deserializeImageField } from 'services/util/deserializeImageField';
+import {
+  buildImageUrls,
+  deserializeImageField,
+  extractTimestampFromImageName,
+} from 'services/util/deserializeImageField';
 import { deserializeImageResponse } from 'services/util/deserializeImageResponse';
+import { getUrlAlt } from 'common/util/getUrl';
+import { ImageMetadata } from 'services/api';
 // import { deserializeImageField } from 'services/util/deserializeImageField';

 // use `createEntityAdapter` to create a slice for results images
@@ -21,7 +27,7 @@ export const resultsAdapter = createEntityAdapter<Image>({
  // `(item) => item.id`, but for our result images, the `name` is the unique identifier.
  selectId: (image) => image.name,
  // Order all images by their time (in descending order)
-  sortComparer: (a, b) => b.metadata.timestamp - a.metadata.timestamp,
+  sortComparer: (a, b) => b.metadata.created - a.metadata.created,
 });

 // This type is intersected with the Entity type to create the shape of the state
@@ -34,22 +40,31 @@ type AdditionalResultsState = {
  nextPage: number; // the next page to request
 };

-const resultsSlice = createSlice({
-  name: 'results',
-  initialState: resultsAdapter.getInitialState<AdditionalResultsState>({
+// export type ResultsState = ReturnType<
+//   typeof resultsAdapter.getInitialState<AdditionalResultsState>
+// >;
+
+export const initialResultsState =
+  resultsAdapter.getInitialState<AdditionalResultsState>({
    // provide the additional initial state
    page: 0,
    pages: 0,
    isLoading: false,
    nextPage: 0,
-  }),
+  });
+
+export type ResultsState = typeof initialResultsState;
+
+const resultsSlice = createSlice({
+  name: 'results',
+  initialState: initialResultsState,
  reducers: {
    // the adapter provides some helper reducers; see the docs for all of them
    // can use them as helper functions within a reducer, or use the function itself as a reducer

    // here we just use the function itself as the reducer. we'll call this on `invocation_complete`
    // to add a single result
-    resultAdded: resultsAdapter.addOne,
+    resultAdded: resultsAdapter.upsertOne,
  },
  extraReducers: (builder) => {
    // here we can respond to a fulfilled call of the `getNextResultsPage` thunk
@@ -86,10 +101,34 @@ const resultsSlice = createSlice({
     */
    builder.addCase(invocationComplete, (state, action) => {
      const { data } = action.payload;
+      const { result, invocation, graph_execution_state_id, source_id } = data;

-      if (isImageOutput(data.result)) {
-        const resultImage = deserializeImageField(data.result.image);
-        resultsAdapter.addOne(state, resultImage);
+      if (isImageOutput(result)) {
+        const name = result.image.image_name;
+        const type = result.image.image_type;
+        const { url, thumbnail } = buildImageUrls(type, name);
+
+        const timestamp = extractTimestampFromImageName(name);
+
+        const image: Image = {
+          name,
+          type,
+          url,
+          thumbnail,
+          metadata: {
+            created: timestamp,
+            width: result.width, // TODO: add tese dimensions
+            height: result.height,
+            invokeai: {
+              session: graph_execution_state_id,
+              source_id,
+              invocation,
+            },
+          },
+        };
+
+        // const resultImage = deserializeImageField(result.image, invocation);
+        resultsAdapter.addOne(state, image);
      }
    });
  },
--- a/invokeai/frontend/web/src/features/gallery/store/uploadsSlice.ts
+++ b/invokeai/frontend/web/src/features/gallery/store/uploadsSlice.ts
@@ -12,7 +12,7 @@ import { deserializeImageResponse } from 'services/util/deserializeImageResponse

 export const uploadsAdapter = createEntityAdapter<Image>({
  selectId: (image) => image.name,
-  sortComparer: (a, b) => b.metadata.timestamp - a.metadata.timestamp,
+  sortComparer: (a, b) => b.metadata.created - a.metadata.created,
 });

 type AdditionalUploadsState = {
@@ -22,6 +22,10 @@ type AdditionalUploadsState = {
  nextPage: number;
 };

+export type UploadssState = ReturnType<
+  typeof uploadsAdapter.getInitialState<AdditionalUploadsState>
+>;
+
 const uploadsSlice = createSlice({
  name: 'uploads',
  initialState: uploadsAdapter.getInitialState<AdditionalUploadsState>({
@@ -61,12 +65,17 @@ const uploadsSlice = createSlice({
     * Upload Image - FULFILLED
     */
    builder.addCase(imageUploaded.fulfilled, (state, action) => {
-      const location = action.payload;
+      const { location, response } = action.payload;
+      const { image_name, image_url, image_type, metadata, thumbnail_url } =
+        response;

-      const uploadedImage = deserializeImageField({
-        image_name: location.split('/').pop() || '',
-        image_type: 'uploads',
-      });
+      const uploadedImage: Image = {
+        name: image_name,
+        url: image_url,
+        thumbnail: thumbnail_url,
+        type: 'uploads',
+        metadata,
+      };

      uploadsAdapter.addOne(state, uploadedImage);
    });
--- a/invokeai/frontend/web/src/features/system/store/systemSlice.ts
+++ b/invokeai/frontend/web/src/features/system/store/systemSlice.ts
@@ -413,7 +413,13 @@ export const systemSlice = createSlice({
     * Generator Progress
     */
    builder.addCase(generatorProgress, (state, action) => {
-      const { step, total_steps, progress_image } = action.payload.data;
+      const {
+        step,
+        total_steps,
+        progress_image,
+        invocation,
+        graph_execution_state_id,
+      } = action.payload.data;

      state.currentStatusHasSteps = true;
      state.currentStep = step + 1; // TODO: step starts at -1, think this is a bug
--- a/invokeai/frontend/web/src/services/api/index.ts
+++ b/invokeai/frontend/web/src/services/api/index.ts
@@ -34,6 +34,7 @@ export type { InpaintInvocation } from './models/InpaintInvocation';
 export type { IntCollectionOutput } from './models/IntCollectionOutput';
 export type { IntOutput } from './models/IntOutput';
 export type { InverseLerpInvocation } from './models/InverseLerpInvocation';
+export type { InvokeAIMetadata } from './models/InvokeAIMetadata';
 export type { IterateInvocation } from './models/IterateInvocation';
 export type { IterateInvocationOutput } from './models/IterateInvocationOutput';
 export type { LatentsField } from './models/LatentsField';
@@ -41,7 +42,6 @@ export type { LatentsOutput } from './models/LatentsOutput';
 export type { LatentsToImageInvocation } from './models/LatentsToImageInvocation';
 export type { LatentsToLatentsInvocation } from './models/LatentsToLatentsInvocation';
 export type { LerpInvocation } from './models/LerpInvocation';
-export type { LoadImageInvocation } from './models/LoadImageInvocation';
 export type { MaskFromAlphaInvocation } from './models/MaskFromAlphaInvocation';
 export type { MaskOutput } from './models/MaskOutput';
 export type { ModelsList } from './models/ModelsList';
@@ -91,6 +91,7 @@ export { $InpaintInvocation } from './schemas/$InpaintInvocation';
 export { $IntCollectionOutput } from './schemas/$IntCollectionOutput';
 export { $IntOutput } from './schemas/$IntOutput';
 export { $InverseLerpInvocation } from './schemas/$InverseLerpInvocation';
+export { $InvokeAIMetadata } from './schemas/$InvokeAIMetadata';
 export { $IterateInvocation } from './schemas/$IterateInvocation';
 export { $IterateInvocationOutput } from './schemas/$IterateInvocationOutput';
 export { $LatentsField } from './schemas/$LatentsField';
@@ -98,7 +99,6 @@ export { $LatentsOutput } from './schemas/$LatentsOutput';
 export { $LatentsToImageInvocation } from './schemas/$LatentsToImageInvocation';
 export { $LatentsToLatentsInvocation } from './schemas/$LatentsToLatentsInvocation';
 export { $LerpInvocation } from './schemas/$LerpInvocation';
-export { $LoadImageInvocation } from './schemas/$LoadImageInvocation';
 export { $MaskFromAlphaInvocation } from './schemas/$MaskFromAlphaInvocation';
 export { $MaskOutput } from './schemas/$MaskOutput';
 export { $ModelsList } from './schemas/$ModelsList';
--- a/invokeai/frontend/web/src/services/api/models/Graph.ts
+++ b/invokeai/frontend/web/src/services/api/models/Graph.ts
@@ -17,7 +17,6 @@ import type { IterateInvocation } from './IterateInvocation';
 import type { LatentsToImageInvocation } from './LatentsToImageInvocation';
 import type { LatentsToLatentsInvocation } from './LatentsToLatentsInvocation';
 import type { LerpInvocation } from './LerpInvocation';
-import type { LoadImageInvocation } from './LoadImageInvocation';
 import type { MaskFromAlphaInvocation } from './MaskFromAlphaInvocation';
 import type { MultiplyInvocation } from './MultiplyInvocation';
 import type { NoiseInvocation } from './NoiseInvocation';
@@ -39,7 +38,7 @@ export type Graph = {
  /**
   * The nodes in this graph
   */
-  nodes?: Record<string, (LoadImageInvocation | ShowImageInvocation | CropImageInvocation | PasteImageInvocation | MaskFromAlphaInvocation | BlurInvocation | LerpInvocation | InverseLerpInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | CvInpaintInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RangeInvocation | RandomRangeInvocation | UpscaleInvocation | RestoreFaceInvocation | TextToImageInvocation | GraphInvocation | IterateInvocation | CollectInvocation | LatentsToLatentsInvocation | ImageToImageInvocation | InpaintInvocation)>;
+  nodes?: Record<string, (ShowImageInvocation | CropImageInvocation | PasteImageInvocation | MaskFromAlphaInvocation | BlurInvocation | LerpInvocation | InverseLerpInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | CvInpaintInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RangeInvocation | RandomRangeInvocation | UpscaleInvocation | RestoreFaceInvocation | TextToImageInvocation | GraphInvocation | IterateInvocation | CollectInvocation | LatentsToLatentsInvocation | ImageToImageInvocation | InpaintInvocation)>;
  /**
   * The connections between nodes and their fields in this graph
   */
--- a/invokeai/frontend/web/src/services/api/models/ImageMetadata.ts
+++ b/invokeai/frontend/web/src/services/api/models/ImageMetadata.ts
@@ -2,14 +2,16 @@
 /* tslint:disable */
 /* eslint-disable */

+import type { InvokeAIMetadata } from './InvokeAIMetadata';
+
 /**
- * An image's metadata
+ * An image's general metadata
 */
 export type ImageMetadata = {
  /**
   * The creation timestamp of the image
   */
-  timestamp: number;
+  created: number;
  /**
   * The width of the image in pixels
   */
@@ -19,8 +21,8 @@ export type ImageMetadata = {
   */
  height: number;
  /**
-   * The image's SD-specific metadata
+   * The image's InvokeAI-specific metadata
   */
-  sd_metadata?: any;
+  invokeai?: InvokeAIMetadata;
 };

--- a/invokeai/frontend/web/src/services/api/models/ImageOutput.ts
+++ b/invokeai/frontend/web/src/services/api/models/ImageOutput.ts
@@ -13,5 +13,13 @@ export type ImageOutput = {
   * The output image
   */
  image: ImageField;
+  /**
+   * The width of the image in pixels
+   */
+  width: number;
+  /**
+   * The height of the image in pixels
+   */
+  height: number;
 };

--- a/invokeai/frontend/web/src/services/api/models/InvokeAIMetadata.ts
+++ b/invokeai/frontend/web/src/services/api/models/InvokeAIMetadata.ts
@@ -0,0 +1,22 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * An image's InvokeAI-specific metadata
+ */
+export type InvokeAIMetadata = {
+  /**
+   * The session that generated this image
+   */
+  session?: string;
+  /**
+   * The source id of the invocation that generated this image
+   */
+  source_id?: string;
+  /**
+   * The prepared invocation that generated this image
+   */
+  invocation?: any;
+};
+
--- a/invokeai/frontend/web/src/services/api/models/LoadImageInvocation.ts
+++ b/invokeai/frontend/web/src/services/api/models/LoadImageInvocation.ts
@@ -1,25 +0,0 @@
-/* istanbul ignore file */
-/* tslint:disable */
-/* eslint-disable */
-
-import type { ImageType } from './ImageType';
-
-/**
- * Load an image from a filename and provide it as output.
- */
-export type LoadImageInvocation = {
-  /**
-   * The id of this node. Must be unique among all nodes.
-   */
-  id: string;
-  type?: 'load_image';
-  /**
-   * The type of the image
-   */
-  image_type: ImageType;
-  /**
-   * The name of the image
-   */
-  image_name: string;
-};
-
--- a/invokeai/frontend/web/src/services/api/schemas/$Graph.ts
+++ b/invokeai/frontend/web/src/services/api/schemas/$Graph.ts
@@ -12,8 +12,6 @@ export const $Graph = {
      contains: {
        type: 'one-of',
        contains: [{
-          type: 'LoadImageInvocation',
-        }, {
          type: 'ShowImageInvocation',
        }, {
          type: 'CropImageInvocation',
--- a/invokeai/frontend/web/src/services/api/schemas/$ImageMetadata.ts
+++ b/invokeai/frontend/web/src/services/api/schemas/$ImageMetadata.ts
@@ -2,9 +2,9 @@
 /* tslint:disable */
 /* eslint-disable */
 export const $ImageMetadata = {
-  description: `An image's metadata`,
+  description: `An image's general metadata`,
  properties: {
-    timestamp: {
+    created: {
      type: 'number',
      description: `The creation timestamp of the image`,
      isRequired: true,
@@ -19,10 +19,12 @@ export const $ImageMetadata = {
      description: `The height of the image in pixels`,
      isRequired: true,
    },
-    sd_metadata: {
-      description: `The image's SD-specific metadata`,
-      properties: {
-      },
+    invokeai: {
+      type: 'all-of',
+      description: `The image's InvokeAI-specific metadata`,
+      contains: [{
+        type: 'InvokeAIMetadata',
+      }],
    },
  },
 } as const;
--- a/invokeai/frontend/web/src/services/api/schemas/$ImageOutput.ts
+++ b/invokeai/frontend/web/src/services/api/schemas/$ImageOutput.ts
@@ -16,5 +16,15 @@ export const $ImageOutput = {
      }],
      isRequired: true,
    },
+    width: {
+      type: 'number',
+      description: `The width of the image in pixels`,
+      isRequired: true,
+    },
+    height: {
+      type: 'number',
+      description: `The height of the image in pixels`,
+      isRequired: true,
+    },
  },
 } as const;
--- a/invokeai/frontend/web/src/services/api/schemas/$InvokeAIMetadata.ts
+++ b/invokeai/frontend/web/src/services/api/schemas/$InvokeAIMetadata.ts
@@ -0,0 +1,21 @@
+/* istanbul ignore file */
+/* tslint:disable */
+/* eslint-disable */
+export const $InvokeAIMetadata = {
+  description: `An image's InvokeAI-specific metadata`,
+  properties: {
+    session: {
+      type: 'string',
+      description: `The session that generated this image`,
+    },
+    source_id: {
+      type: 'string',
+      description: `The source id of the invocation that generated this image`,
+    },
+    invocation: {
+      description: `The prepared invocation that generated this image`,
+      properties: {
+      },
+    },
+  },
+} as const;
--- a/invokeai/frontend/web/src/services/api/schemas/$LoadImageInvocation.ts
+++ b/invokeai/frontend/web/src/services/api/schemas/$LoadImageInvocation.ts
@@ -1,29 +0,0 @@
-/* istanbul ignore file */
-/* tslint:disable */
-/* eslint-disable */
-export const $LoadImageInvocation = {
-  description: `Load an image from a filename and provide it as output.`,
-  properties: {
-    id: {
-      type: 'string',
-      description: `The id of this node. Must be unique among all nodes.`,
-      isRequired: true,
-    },
-    type: {
-      type: 'Enum',
-    },
-    image_type: {
-      type: 'all-of',
-      description: `The type of the image`,
-      contains: [{
-        type: 'ImageType',
-      }],
-      isRequired: true,
-    },
-    image_name: {
-      type: 'string',
-      description: `The name of the image`,
-      isRequired: true,
-    },
-  },
-} as const;
--- a/invokeai/frontend/web/src/services/api/services/ImagesService.ts
+++ b/invokeai/frontend/web/src/services/api/services/ImagesService.ts
@@ -2,6 +2,7 @@
 /* tslint:disable */
 /* eslint-disable */
 import type { Body_upload_image } from '../models/Body_upload_image';
+import type { ImageResponse } from '../models/ImageResponse';
 import type { ImageType } from '../models/ImageType';
 import type { PaginatedResults_ImageResponse_ } from '../models/PaginatedResults_ImageResponse_';

@@ -77,14 +78,14 @@ export class ImagesService {

  /**
   * Upload Image
-   * @returns any Successful Response
+   * @returns ImageResponse The image was uploaded successfully
   * @throws ApiError
   */
  public static uploadImage({
    formData,
  }: {
    formData: Body_upload_image,
-  }): CancelablePromise<any> {
+  }): CancelablePromise<ImageResponse> {
    return __request(OpenAPI, {
      method: 'POST',
      url: '/api/v1/images/uploads/',
--- a/invokeai/frontend/web/src/services/api/services/SessionsService.ts
+++ b/invokeai/frontend/web/src/services/api/services/SessionsService.ts
@@ -18,7 +18,6 @@ import type { IterateInvocation } from '../models/IterateInvocation';
 import type { LatentsToImageInvocation } from '../models/LatentsToImageInvocation';
 import type { LatentsToLatentsInvocation } from '../models/LatentsToLatentsInvocation';
 import type { LerpInvocation } from '../models/LerpInvocation';
-import type { LoadImageInvocation } from '../models/LoadImageInvocation';
 import type { MaskFromAlphaInvocation } from '../models/MaskFromAlphaInvocation';
 import type { MultiplyInvocation } from '../models/MultiplyInvocation';
 import type { NoiseInvocation } from '../models/NoiseInvocation';
@@ -141,7 +140,7 @@ export class SessionsService {
     * The id of the session
     */
    sessionId: string,
-    requestBody: (LoadImageInvocation | ShowImageInvocation | CropImageInvocation | PasteImageInvocation | MaskFromAlphaInvocation | BlurInvocation | LerpInvocation | InverseLerpInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | CvInpaintInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RangeInvocation | RandomRangeInvocation | UpscaleInvocation | RestoreFaceInvocation | TextToImageInvocation | GraphInvocation | IterateInvocation | CollectInvocation | LatentsToLatentsInvocation | ImageToImageInvocation | InpaintInvocation),
+    requestBody: (ShowImageInvocation | CropImageInvocation | PasteImageInvocation | MaskFromAlphaInvocation | BlurInvocation | LerpInvocation | InverseLerpInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | CvInpaintInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RangeInvocation | RandomRangeInvocation | UpscaleInvocation | RestoreFaceInvocation | TextToImageInvocation | GraphInvocation | IterateInvocation | CollectInvocation | LatentsToLatentsInvocation | ImageToImageInvocation | InpaintInvocation),
  }): CancelablePromise<string> {
    return __request(OpenAPI, {
      method: 'POST',
@@ -178,7 +177,7 @@ export class SessionsService {
     * The path to the node in the graph
     */
    nodePath: string,
-    requestBody: (LoadImageInvocation | ShowImageInvocation | CropImageInvocation | PasteImageInvocation | MaskFromAlphaInvocation | BlurInvocation | LerpInvocation | InverseLerpInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | CvInpaintInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RangeInvocation | RandomRangeInvocation | UpscaleInvocation | RestoreFaceInvocation | TextToImageInvocation | GraphInvocation | IterateInvocation | CollectInvocation | LatentsToLatentsInvocation | ImageToImageInvocation | InpaintInvocation),
+    requestBody: (ShowImageInvocation | CropImageInvocation | PasteImageInvocation | MaskFromAlphaInvocation | BlurInvocation | LerpInvocation | InverseLerpInvocation | NoiseInvocation | TextToLatentsInvocation | LatentsToImageInvocation | CvInpaintInvocation | AddInvocation | SubtractInvocation | MultiplyInvocation | DivideInvocation | RangeInvocation | RandomRangeInvocation | UpscaleInvocation | RestoreFaceInvocation | TextToImageInvocation | GraphInvocation | IterateInvocation | CollectInvocation | LatentsToLatentsInvocation | ImageToImageInvocation | InpaintInvocation),
  }): CancelablePromise<GraphExecutionState> {
    return __request(OpenAPI, {
      method: 'PUT',
--- a/invokeai/frontend/web/src/services/events/middleware.ts
+++ b/invokeai/frontend/web/src/services/events/middleware.ts
@@ -177,25 +177,25 @@ export const socketMiddleware = () => {

        // Set up listeners for the present subscription
        socket.on('invocation_started', (data) => {
-          if (shouldHandleEvent(data.source_id)) {
+          if (shouldHandleEvent(data.invocation.id)) {
            dispatch(invocationStarted({ data, timestamp: getTimestamp() }));
          }
        });

        socket.on('generator_progress', (data) => {
-          if (shouldHandleEvent(data.source_id)) {
+          if (shouldHandleEvent(data.invocation.id)) {
            dispatch(generatorProgress({ data, timestamp: getTimestamp() }));
          }
        });

        socket.on('invocation_error', (data) => {
-          if (shouldHandleEvent(data.source_id)) {
+          if (shouldHandleEvent(data.invocation.id)) {
            dispatch(invocationError({ data, timestamp: getTimestamp() }));
          }
        });

        socket.on('invocation_complete', (data) => {
-          if (shouldHandleEvent(data.source_id)) {
+          if (shouldHandleEvent(data.invocation.id)) {
            const sessionId = data.graph_execution_state_id;

            const { cancelType, isCancelScheduled } = getState().system;
--- a/invokeai/frontend/web/src/services/events/types.ts
+++ b/invokeai/frontend/web/src/services/events/types.ts
@@ -13,6 +13,12 @@ export type AnyInvocationType = NonNullable<
  NonNullable<Graph['nodes']>[string]['type']
 >;

+export type AnyInvocation = {
+  id: string;
+  type: AnyInvocationType | string;
+  [key: string]: any;
+};
+
 export type AnyResult = GraphExecutionState['results'][string];

 /**
@@ -22,7 +28,7 @@ export type AnyResult = GraphExecutionState['results'][string];
 */
 export type GeneratorProgressEvent = {
  graph_execution_state_id: string;
-  invocation: AnyInvocationType;
+  invocation: AnyInvocation;
  source_id: string;
  progress_image?: ProgressImage;
  step: number;
@@ -38,6 +44,7 @@ export type GeneratorProgressEvent = {
 */
 export type InvocationCompleteEvent = {
  graph_execution_state_id: string;
+  invocation: AnyInvocation;
  source_id: string;
  result: AnyResult;
 };
@@ -49,7 +56,7 @@ export type InvocationCompleteEvent = {
 */
 export type InvocationErrorEvent = {
  graph_execution_state_id: string;
-  invocation: AnyInvocationType;
+  invocation: AnyInvocation;
  source_id: string;
  error: string;
 };
@@ -61,8 +68,8 @@ export type InvocationErrorEvent = {
 */
 export type InvocationStartedEvent = {
  graph_execution_state_id: string;
-  invocation: AnyInvocationType;
  source_id: string;
+  invocation: AnyInvocation;
 };

 /**
--- a/invokeai/frontend/web/src/services/thunks/image.ts
+++ b/invokeai/frontend/web/src/services/thunks/image.ts
@@ -26,7 +26,7 @@ export const imageUploaded = createAppAsyncThunk(
  async (arg: ImageUploadedArg, _thunkApi) => {
    const response = await ImagesService.uploadImage(arg);
    const { location } = getHeaders(response);
-    return location;
+    return { response, location };
  }
 );

--- a/invokeai/frontend/web/src/services/util/deserializeImageField.ts
+++ b/invokeai/frontend/web/src/services/util/deserializeImageField.ts
@@ -1,5 +1,6 @@
 import { Image } from 'app/invokeai';
 import { ImageField, ImageType } from 'services/api';
+import { AnyInvocation } from 'services/events/types';

 export const buildImageUrls = (
  imageType: ImageType,
@@ -34,23 +35,21 @@ export const extractTimestampFromImageName = (imageName: string) => {
 * TODO: do some more janky stuff here to get image dimensions instead of defaulting to 512x512?
 * TODO: better yet, improve the nodes server (wip)
 */
-export const deserializeImageField = (image: ImageField): Image => {
+export const deserializeImageField = (
+  image: ImageField,
+  invocation: AnyInvocation
+): Image => {
  const name = image.image_name;
  const type = image.image_type;

  const { url, thumbnail } = buildImageUrls(type, name);

-  const timestamp = extractTimestampFromImageName(name);
-
  return {
    name,
    type,
    url,
    thumbnail,
-    metadata: {
-      timestamp,
-      height: 512,
-      width: 512,
-    },
+    timestamp,
+    metadata: invocation,
  };
 };
--- a/invokeai/frontend/web/src/services/util/deserializeImageResponse.ts
+++ b/invokeai/frontend/web/src/services/util/deserializeImageResponse.ts
@@ -10,6 +10,8 @@ export const deserializeImageResponse = (
  const { image_name, image_type, image_url, metadata, thumbnail_url } =
    imageResponse;

+  const { width, height, timestamp, invokeai } = metadata;
+
  // TODO: parse metadata - just leaving it as-is for now

  return {
@@ -17,6 +19,7 @@ export const deserializeImageResponse = (
    type: image_type,
    url: image_url,
    thumbnail: thumbnail_url,
-    metadata,
+    timestamp,
+    metadata: invokeai,
  };
 };