feat(db,nodes,api): refactor metadata

Metadata for the Linear UI is now sneakily provided via a `MetadataAccumulator` node, which the client populates / hooks up while building the graph.

Additionally, we provide the unexpanded graph with the metadata API response.

Both of these are embedded into the PNGs.

- Remove `metadata` from `ImageDTO`
- Split up the `images/` routes to accomodate this; metadata is only retrieved per-image
- `images/{image_name}` now gets the DTO
- `images/{image_name}/metadata` gets the new metadata
- `images/{image_name}/full` gets the full-sized image file
- Remove old metadata service
- Add `MetadataAccumulator` node, `CoreMetadataField`, hook up to `LatentsToImage` node
- Add `get_raw()` method to `ItemStorage`, retrieves the row from DB as a string, no pydantic parsing
- Update `images`related services to handle storing and retrieving the new metadata
- Add `get_metadata_graph_from_raw_session` which extracts the `graph` from `session` without needing to hydrate the session in pydantic, in preparation for providing it as metadata; also removes all references to the `MetadataAccumulator` node

invokeai/app/api/dependencies.py

@@ -13,7 +13,6 @@ from invokeai.app.services.board_record_storage import SqliteBoardRecordStorage
 from invokeai.app.services.boards import BoardService, BoardServiceDependencies
 from invokeai.app.services.image_record_storage import SqliteImageRecordStorage
 from invokeai.app.services.images import ImageService, ImageServiceDependencies
-from invokeai.app.services.metadata import CoreMetadataService
 from invokeai.app.services.resource_name import SimpleNameService
 from invokeai.app.services.urls import LocalUrlService
 from invokeai.backend.util.logging import InvokeAILogger
@@ -75,7 +74,6 @@ class ApiDependencies:
         )
 
         urls = LocalUrlService()
-        metadata = CoreMetadataService()
         image_record_storage = SqliteImageRecordStorage(db_location)
         image_file_storage = DiskImageFileStorage(f"{output_folder}/images")
         names = SimpleNameService()
@@ -111,7 +109,6 @@ class ApiDependencies:
                 board_image_record_storage=board_image_record_storage,
                 image_record_storage=image_record_storage,
                 image_file_storage=image_file_storage,
-                metadata=metadata,
                 url=urls,
                 logger=logger,
                 names=names,

invokeai/app/api/routers/images.py

@@ -1,20 +1,19 @@
 import io
 from typing import Optional
-from fastapi import Body, HTTPException, Path, Query, Request, Response, UploadFile
+
-from fastapi.routing import APIRouter
+from fastapi import (Body, HTTPException, Path, Query, Request, Response,
+                     UploadFile)
 from fastapi.responses import FileResponse
+from fastapi.routing import APIRouter
 from PIL import Image
-from invokeai.app.models.image import (
+
-    ImageCategory,
+from invokeai.app.invocations.metadata import ImageMetadata
-    ResourceOrigin,
+from invokeai.app.models.image import ImageCategory, ResourceOrigin
-)
 from invokeai.app.services.image_record_storage import OffsetPaginatedResults
-from invokeai.app.services.models.image_record import (
-    ImageDTO,
-    ImageRecordChanges,
-    ImageUrlsDTO,
-)
 from invokeai.app.services.item_storage import PaginatedResults
+from invokeai.app.services.models.image_record import (ImageDTO,
+                                                       ImageRecordChanges,
+                                                       ImageUrlsDTO)
 
 from ..dependencies import ApiDependencies
 
@@ -103,23 +102,38 @@ async def update_image(
 
 
 @images_router.get(
-    "/{image_name}/metadata",
+    "/{image_name}",
-    operation_id="get_image_metadata",
+    operation_id="get_image_dto",
     response_model=ImageDTO,
 )
-async def get_image_metadata(
+async def get_image_dto(
     image_name: str = Path(description="The name of image to get"),
 ) -> ImageDTO:
-    """Gets an image's metadata"""
+    """Gets an image's DTO"""
 
     try:
         return ApiDependencies.invoker.services.images.get_dto(image_name)
     except Exception as e:
         raise HTTPException(status_code=404)
 
+@images_router.get(
+    "/{image_name}/metadata",
+    operation_id="get_image_metadata",
+    response_model=ImageMetadata,
+)
+async def get_image_metadata(
+    image_name: str = Path(description="The name of image to get"),
+) -> ImageMetadata:
+    """Gets an image's metadata"""
+
+    try:
+        return ApiDependencies.invoker.services.images.get_metadata(image_name)
+    except Exception as e:
+        raise HTTPException(status_code=404)
+
 
 @images_router.get(
-    "/{image_name}",
+    "/{image_name}/full",
     operation_id="get_image_full",
     response_class=Response,
     responses={
@@ -208,10 +222,10 @@ async def get_image_urls(
 
 @images_router.get(
     "/",
-    operation_id="list_images_with_metadata",
+    operation_id="list_image_dtos",
     response_model=OffsetPaginatedResults[ImageDTO],
 )
-async def list_images_with_metadata(
+async def list_image_dtos(
     image_origin: Optional[ResourceOrigin] = Query(
         default=None, description="The origin of images to list"
     ),
@@ -227,7 +241,7 @@ async def list_images_with_metadata(
     offset: int = Query(default=0, description="The page offset"),
     limit: int = Query(default=10, description="The number of images per page"),
 ) -> OffsetPaginatedResults[ImageDTO]:
-    """Gets a list of images"""
+    """Gets a list of image DTOs"""
 
     image_dtos = ApiDependencies.invoker.services.images.get_many(
         offset,

invokeai/app/cli_app.py

@@ -34,7 +34,6 @@ from invokeai.app.services.board_record_storage import SqliteBoardRecordStorage
 from invokeai.app.services.boards import BoardService, BoardServiceDependencies
 from invokeai.app.services.image_record_storage import SqliteImageRecordStorage
 from invokeai.app.services.images import ImageService, ImageServiceDependencies
-from invokeai.app.services.metadata import CoreMetadataService
 from invokeai.app.services.resource_name import SimpleNameService
 from invokeai.app.services.urls import LocalUrlService
 from .services.default_graphs import (default_text_to_image_graph_id,
@@ -244,7 +243,6 @@ def invoke_cli():
         )
 
     urls = LocalUrlService()
-    metadata = CoreMetadataService()
     image_record_storage = SqliteImageRecordStorage(db_location)
     image_file_storage = DiskImageFileStorage(f"{output_folder}/images")
     names = SimpleNameService()
@@ -277,7 +275,6 @@ def invoke_cli():
             board_image_record_storage=board_image_record_storage,
             image_record_storage=image_record_storage,
             image_file_storage=image_file_storage,
-            metadata=metadata,
             url=urls,
             logger=logger,
             names=names,

invokeai/app/invocations/latent.py

@@ -9,9 +9,9 @@ from diffusers.image_processor import VaeImageProcessor
 from diffusers.schedulers import SchedulerMixin as Scheduler
 from pydantic import BaseModel, Field, validator
 
+from invokeai.app.invocations.metadata import CoreMetadata
 from invokeai.app.util.step_callback import stable_diffusion_step_callback
 
-from ..models.image import ImageCategory, ImageField, ResourceOrigin
 from ...backend.model_management.lora import ModelPatcher
 from ...backend.stable_diffusion import PipelineIntermediateState
 from ...backend.stable_diffusion.diffusers_pipeline import (
@@ -21,6 +21,7 @@ from ...backend.stable_diffusion.diffusion.shared_invokeai_diffusion import \
     PostprocessingSettings
 from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP
 from ...backend.util.devices import torch_dtype
+from ..models.image import ImageCategory, ImageField, ResourceOrigin
 from .baseinvocation import (BaseInvocation, BaseInvocationOutput,
                              InvocationConfig, InvocationContext)
 from .compel import ConditioningField
@@ -449,6 +450,8 @@ class LatentsToImageInvocation(BaseInvocation):
     tiled: bool = Field(
         default=False,
         description="Decode latents by overlaping tiles(less memory consumption)")
+    metadata: Optional[CoreMetadata] = Field(default=None, description="Optional core metadata to be written to the image")
+    
 
     # Schema customisation
     class Config(InvocationConfig):
@@ -493,7 +496,8 @@ class LatentsToImageInvocation(BaseInvocation):
             image_category=ImageCategory.GENERAL,
             node_id=self.id,
             session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate
+            is_intermediate=self.is_intermediate,
+            metadata=self.metadata.dict() if self.metadata else None,
         )
 
         return ImageOutput(

invokeai/app/invocations/metadata.py

@@ -0,0 +1,124 @@
+from typing import Literal, Optional, Union
+
+from pydantic import BaseModel, Field
+
+from invokeai.app.invocations.baseinvocation import (BaseInvocation,
+                                                     BaseInvocationOutput,
+                                                     InvocationContext)
+from invokeai.app.invocations.controlnet_image_processors import ControlField
+from invokeai.app.invocations.model import (LoRAModelField, MainModelField,
+                                            VAEModelField)
+
+
+class LoRAMetadataField(BaseModel):
+    """LoRA metadata for an image generated in InvokeAI."""
+    lora: LoRAModelField = Field(description="The LoRA model")
+    weight: float = Field(description="The weight of the LoRA model")
+
+
+class CoreMetadata(BaseModel):
+    """Core generation metadata for an image generated in InvokeAI."""
+
+    generation_mode: str = Field(description="The generation mode that output this image",)
+    positive_prompt: str = Field(description="The positive prompt parameter")
+    negative_prompt: str = Field(description="The negative prompt parameter")
+    width: int = Field(description="The width parameter")
+    height: int = Field(description="The height parameter")
+    seed: int = Field(description="The seed used for noise generation")
+    rand_device: str = Field(description="The device used for random number generation")
+    cfg_scale: float = Field(description="The classifier-free guidance scale parameter")
+    steps: int = Field(description="The number of steps used for inference")
+    scheduler: str = Field(description="The scheduler used for inference")
+    clip_skip: int = Field(description="The number of skipped CLIP layers",)
+    model: MainModelField = Field(description="The main model used for inference")
+    controlnets: list[ControlField]= Field(description="The ControlNets used for inference")
+    loras: list[LoRAMetadataField] = Field(description="The LoRAs used for inference")
+    strength: Union[float, None] = Field(
+        default=None,
+        description="The strength used for latents-to-latents",
+    )
+    init_image: Union[str, None] = Field(
+        default=None, description="The name of the initial image"
+    )
+    vae: Union[VAEModelField, None] = Field(
+        default=None,
+        description="The VAE used for decoding, if the main model's default was not used",
+    )
+
+
+class ImageMetadata(BaseModel):
+    """An image's generation metadata"""
+
+    metadata: Optional[dict] = Field(
+        default=None,
+        description="The image's core metadata, if it was created in the Linear or Canvas UI",
+    )
+    graph: Optional[dict] = Field(
+        default=None, description="The graph that created the image"
+    )
+
+
+class MetadataAccumulatorOutput(BaseInvocationOutput):
+    """The output of the MetadataAccumulator node"""
+
+    type: Literal["metadata_accumulator_output"] = "metadata_accumulator_output"
+
+    metadata: CoreMetadata = Field(description="The core metadata for the image")
+
+
+class MetadataAccumulatorInvocation(BaseInvocation):
+    """Outputs a Core Metadata Object"""
+
+    type: Literal["metadata_accumulator"] = "metadata_accumulator"
+
+    generation_mode: str = Field(description="The generation mode that output this image",)
+    positive_prompt: str = Field(description="The positive prompt parameter")
+    negative_prompt: str = Field(description="The negative prompt parameter")
+    width: int = Field(description="The width parameter")
+    height: int = Field(description="The height parameter")
+    seed: int = Field(description="The seed used for noise generation")
+    rand_device: str = Field(description="The device used for random number generation")
+    cfg_scale: float = Field(description="The classifier-free guidance scale parameter")
+    steps: int = Field(description="The number of steps used for inference")
+    scheduler: str = Field(description="The scheduler used for inference")
+    clip_skip: int = Field(description="The number of skipped CLIP layers",)
+    model: MainModelField = Field(description="The main model used for inference")
+    controlnets: list[ControlField]= Field(description="The ControlNets used for inference")
+    loras: list[LoRAMetadataField] = Field(description="The LoRAs used for inference")
+    strength: Union[float, None] = Field(
+        default=None,
+        description="The strength used for latents-to-latents",
+    )
+    init_image: Union[str, None] = Field(
+        default=None, description="The name of the initial image"
+    )
+    vae: Union[VAEModelField, None] = Field(
+        default=None,
+        description="The VAE used for decoding, if the main model's default was not used",
+    )
+
+
+    def invoke(self, context: InvocationContext) -> MetadataAccumulatorOutput:
+        """Collects and outputs a CoreMetadata object"""
+
+        return MetadataAccumulatorOutput(
+            metadata=CoreMetadata(
+                generation_mode=self.generation_mode,
+                positive_prompt=self.positive_prompt,
+                negative_prompt=self.negative_prompt,
+                width=self.width,
+                height=self.height,
+                seed=self.seed,
+                rand_device=self.rand_device,
+                cfg_scale=self.cfg_scale,
+                steps=self.steps,
+                scheduler=self.scheduler,
+                model=self.model,
+                strength=self.strength,
+                init_image=self.init_image,
+                vae=self.vae,
+                controlnets=self.controlnets,
+                loras=self.loras,
+                clip_skip=self.clip_skip,
+            )
+        )

invokeai/app/models/metadata.py

@@ -1,93 +0,0 @@
-from typing import Optional, Union, List
-from pydantic import BaseModel, Extra, Field, StrictFloat, StrictInt, StrictStr
-
-
-class ImageMetadata(BaseModel):
-    """
-    Core generation metadata for an image/tensor generated in InvokeAI.
-
-    Also includes any metadata from the image's PNG tEXt chunks.
-
-    Generated by traversing the execution graph, collecting the parameters of the nearest ancestors
-    of a given node.
-
-    Full metadata may be accessed by querying for the session in the `graph_executions` table.
-    """
-
-    class Config:
-        extra = Extra.allow
-        """
-        This lets the ImageMetadata class accept arbitrary additional fields. The CoreMetadataService
-        won't add any fields that are not already defined, but other a different metadata service
-        implementation might.
-        """
-
-    type: Optional[StrictStr] = Field(
-        default=None,
-        description="The type of the ancestor node of the image output node.",
-    )
-    """The type of the ancestor node of the image output node."""
-    positive_conditioning: Optional[StrictStr] = Field(
-        default=None, description="The positive conditioning."
-    )
-    """The positive conditioning"""
-    negative_conditioning: Optional[StrictStr] = Field(
-        default=None, description="The negative conditioning."
-    )
-    """The negative conditioning"""
-    width: Optional[StrictInt] = Field(
-        default=None, description="Width of the image/latents in pixels."
-    )
-    """Width of the image/latents in pixels"""
-    height: Optional[StrictInt] = Field(
-        default=None, description="Height of the image/latents in pixels."
-    )
-    """Height of the image/latents in pixels"""
-    seed: Optional[StrictInt] = Field(
-        default=None, description="The seed used for noise generation."
-    )
-    """The seed used for noise generation"""
-    # cfg_scale: Optional[StrictFloat] = Field(
-    # cfg_scale: Union[float, list[float]] = Field(
-    cfg_scale: Union[StrictFloat, List[StrictFloat]] = Field(
-        default=None, description="The classifier-free guidance scale."
-    )
-    """The classifier-free guidance scale"""
-    steps: Optional[StrictInt] = Field(
-        default=None, description="The number of steps used for inference."
-    )
-    """The number of steps used for inference"""
-    scheduler: Optional[StrictStr] = Field(
-        default=None, description="The scheduler used for inference."
-    )
-    """The scheduler used for inference"""
-    model: Optional[StrictStr] = Field(
-        default=None, description="The model used for inference."
-    )
-    """The model used for inference"""
-    strength: Optional[StrictFloat] = Field(
-        default=None,
-        description="The strength used for image-to-image/latents-to-latents.",
-    )
-    """The strength used for image-to-image/latents-to-latents."""
-    latents: Optional[StrictStr] = Field(
-        default=None, description="The ID of the initial latents."
-    )
-    """The ID of the initial latents"""
-    vae: Optional[StrictStr] = Field(
-        default=None, description="The VAE used for decoding."
-    )
-    """The VAE used for decoding"""
-    unet: Optional[StrictStr] = Field(
-        default=None, description="The UNet used dor inference."
-    )
-    """The UNet used dor inference"""
-    clip: Optional[StrictStr] = Field(
-        default=None, description="The CLIP Encoder used for conditioning."
-    )
-    """The CLIP Encoder used for conditioning"""
-    extra: Optional[StrictStr] = Field(
-        default=None,
-        description="Uploaded image metadata, extracted from the PNG tEXt chunk.",
-    )
-    """Uploaded image metadata, extracted from the PNG tEXt chunk."""

invokeai/app/services/image_file_storage.py

@@ -1,14 +1,14 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
+import json
 from abc import ABC, abstractmethod
 from pathlib import Path
 from queue import Queue
 from typing import Dict, Optional, Union
 
-from PIL.Image import Image as PILImageType
 from PIL import Image, PngImagePlugin
+from PIL.Image import Image as PILImageType
 from send2trash import send2trash
 
-from invokeai.app.models.metadata import ImageMetadata
 from invokeai.app.util.thumbnails import get_thumbnail_name, make_thumbnail
 
 
@@ -59,7 +59,8 @@ class ImageFileStorageBase(ABC):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[ImageMetadata] = None,
+        metadata: Optional[dict] = None,
+        graph: Optional[dict] = None,
         thumbnail_size: int = 256,
     ) -> None:
         """Saves an image and a 256x256 WEBP thumbnail. Returns a tuple of the image name, thumbnail name, and created timestamp."""
@@ -110,20 +111,22 @@ class DiskImageFileStorage(ImageFileStorageBase):
         self,
         image: PILImageType,
         image_name: str,
-        metadata: Optional[ImageMetadata] = None,
+        metadata: Optional[dict] = None,
+        graph: Optional[dict] = None,
         thumbnail_size: int = 256,
     ) -> None:
         try:
             self.__validate_storage_folders()
             image_path = self.get_path(image_name)
 
+            pnginfo = PngImagePlugin.PngInfo()
+            
             if metadata is not None:
-                pnginfo = PngImagePlugin.PngInfo()
+                pnginfo.add_text("metadata", json.dumps(metadata))
-                pnginfo.add_text("invokeai", metadata.json())
+            if graph is not None:
-                image.save(image_path, "PNG", pnginfo=pnginfo)
+                pnginfo.add_text("graph", json.dumps(graph))
-            else:
-                image.save(image_path, "PNG")
 
+            image.save(image_path, "PNG", pnginfo=pnginfo)
             thumbnail_name = get_thumbnail_name(image_name)
             thumbnail_path = self.get_path(thumbnail_name, thumbnail=True)
             thumbnail_image = make_thumbnail(image, thumbnail_size)

invokeai/app/services/image_record_storage.py

@@ -1,3 +1,4 @@
+import json
 import sqlite3
 import threading
 from abc import ABC, abstractmethod
@@ -8,7 +9,6 @@ from pydantic import BaseModel, Field
 from pydantic.generics import GenericModel
 
 from invokeai.app.models.image import ImageCategory, ResourceOrigin
-from invokeai.app.models.metadata import ImageMetadata
 from invokeai.app.services.models.image_record import (
     ImageRecord, ImageRecordChanges, deserialize_image_record)
 
@@ -48,6 +48,28 @@ class ImageRecordDeleteException(Exception):
         super().__init__(message)
 
 
+IMAGE_DTO_COLS = ", ".join(
+    list(
+        map(
+            lambda c: "images." + c,
+            [
+                "image_name",
+                "image_origin",
+                "image_category",
+                "width",
+                "height",
+                "session_id",
+                "node_id",
+                "is_intermediate",
+                "created_at",
+                "updated_at",
+                "deleted_at",
+            ],
+        )
+    )
+)
+
+
 class ImageRecordStorageBase(ABC):
     """Low-level service responsible for interfacing with the image record store."""
 
@@ -58,6 +80,11 @@ class ImageRecordStorageBase(ABC):
         """Gets an image record."""
         pass
 
+    @abstractmethod
+    def get_metadata(self, image_name: str) -> Optional[dict]:
+        """Gets an image's metadata'."""
+        pass
+
     @abstractmethod
     def update(
         self,
@@ -102,7 +129,7 @@ class ImageRecordStorageBase(ABC):
         height: int,
         session_id: Optional[str],
         node_id: Optional[str],
-        metadata: Optional[ImageMetadata],
+        metadata: Optional[dict],
         is_intermediate: bool = False,
     ) -> datetime:
         """Saves an image record."""
@@ -206,7 +233,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
 
             self._cursor.execute(
                 f"""--sql
-                SELECT * FROM images
+                SELECT {IMAGE_DTO_COLS} FROM images
                 WHERE image_name = ?;
                 """,
                 (image_name,),
@@ -224,6 +251,28 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
 
         return deserialize_image_record(dict(result))
 
+    def get_metadata(self, image_name: str) -> Optional[dict]:
+        try:
+            self._lock.acquire()
+
+            self._cursor.execute(
+                f"""--sql
+                SELECT images.metadata FROM images
+                WHERE image_name = ?;
+                """,
+                (image_name,),
+            )
+
+            result = cast(Optional[sqlite3.Row], self._cursor.fetchone())
+            if not result or not result[0]:
+                return None
+            return json.loads(result[0])
+        except sqlite3.Error as e:
+            self._conn.rollback()
+            raise ImageRecordNotFoundException from e
+        finally:
+            self._lock.release()
+
     def update(
         self,
         image_name: str,
@@ -291,8 +340,8 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
             WHERE 1=1
             """
 
-            images_query = """--sql
+            images_query = f"""--sql
-            SELECT images.*
+            SELECT {IMAGE_DTO_COLS}
             FROM images
             LEFT JOIN board_images ON board_images.image_name = images.image_name
             WHERE 1=1
@@ -410,12 +459,12 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
         width: int,
         height: int,
         node_id: Optional[str],
-        metadata: Optional[ImageMetadata],
+        metadata: Optional[dict],
         is_intermediate: bool = False,
     ) -> datetime:
         try:
             metadata_json = (
-                None if metadata is None else metadata.json(exclude_none=True)
+                None if metadata is None else json.dumps(metadata)
             )
             self._lock.acquire()
             self._cursor.execute(
@@ -465,9 +514,7 @@ class SqliteImageRecordStorage(ImageRecordStorageBase):
         finally:
             self._lock.release()
 
-    def get_most_recent_image_for_board(
+    def get_most_recent_image_for_board(self, board_id: str) -> Optional[ImageRecord]:
-        self, board_id: str
-    ) -> Optional[ImageRecord]:
         try:
             self._lock.acquire()
             self._cursor.execute(

invokeai/app/services/images.py

@@ -1,39 +1,30 @@
+import json
 from abc import ABC, abstractmethod
 from logging import Logger
-from typing import Optional, TYPE_CHECKING, Union
+from typing import TYPE_CHECKING, Optional
+
 from PIL.Image import Image as PILImageType
 
-from invokeai.app.models.image import (
+from invokeai.app.invocations.metadata import ImageMetadata
-    ImageCategory,
+from invokeai.app.models.image import (ImageCategory,
-    ResourceOrigin,
+                                       InvalidImageCategoryException,
-    InvalidImageCategoryException,
+                                       InvalidOriginException, ResourceOrigin)
-    InvalidOriginException,
+from invokeai.app.services.board_image_record_storage import \
-)
+    BoardImageRecordStorageBase
-from invokeai.app.models.metadata import ImageMetadata
+from invokeai.app.services.graph import Graph
-from invokeai.app.services.board_image_record_storage import BoardImageRecordStorageBase
-from invokeai.app.services.image_record_storage import (
-    ImageRecordDeleteException,
-    ImageRecordNotFoundException,
-    ImageRecordSaveException,
-    ImageRecordStorageBase,
-    OffsetPaginatedResults,
-)
-from invokeai.app.services.models.image_record import (
-    ImageRecord,
-    ImageDTO,
-    ImageRecordChanges,
-    image_record_to_dto,
-)
 from invokeai.app.services.image_file_storage import (
-    ImageFileDeleteException,
+    ImageFileDeleteException, ImageFileNotFoundException,
-    ImageFileNotFoundException,
+    ImageFileSaveException, ImageFileStorageBase)
-    ImageFileSaveException,
+from invokeai.app.services.image_record_storage import (
-    ImageFileStorageBase,
+    ImageRecordDeleteException, ImageRecordNotFoundException,
-)
+    ImageRecordSaveException, ImageRecordStorageBase, OffsetPaginatedResults)
-from invokeai.app.services.item_storage import ItemStorageABC, PaginatedResults
+from invokeai.app.services.item_storage import ItemStorageABC
-from invokeai.app.services.metadata import MetadataServiceBase
+from invokeai.app.services.models.image_record import (ImageDTO, ImageRecord,
+                                                       ImageRecordChanges,
+                                                       image_record_to_dto)
 from invokeai.app.services.resource_name import NameServiceBase
 from invokeai.app.services.urls import UrlServiceBase
+from invokeai.app.util.metadata import get_metadata_graph_from_raw_session
 
 if TYPE_CHECKING:
     from invokeai.app.services.graph import GraphExecutionState
@@ -51,6 +42,7 @@ class ImageServiceABC(ABC):
         node_id: Optional[str] = None,
         session_id: Optional[str] = None,
         is_intermediate: bool = False,
+        metadata: Optional[dict] = None,
     ) -> ImageDTO:
         """Creates an image, storing the file and its metadata."""
         pass
@@ -79,6 +71,11 @@ class ImageServiceABC(ABC):
         """Gets an image DTO."""
         pass
 
+    @abstractmethod
+    def get_metadata(self, image_name: str) -> ImageMetadata:
+        """Gets an image's metadata."""
+        pass
+
     @abstractmethod
     def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         """Gets an image's path."""
@@ -124,7 +121,6 @@ class ImageServiceDependencies:
     image_records: ImageRecordStorageBase
     image_files: ImageFileStorageBase
     board_image_records: BoardImageRecordStorageBase
-    metadata: MetadataServiceBase
     urls: UrlServiceBase
     logger: Logger
     names: NameServiceBase
@@ -135,7 +131,6 @@ class ImageServiceDependencies:
         image_record_storage: ImageRecordStorageBase,
         image_file_storage: ImageFileStorageBase,
         board_image_record_storage: BoardImageRecordStorageBase,
-        metadata: MetadataServiceBase,
         url: UrlServiceBase,
         logger: Logger,
         names: NameServiceBase,
@@ -144,7 +139,6 @@ class ImageServiceDependencies:
         self.image_records = image_record_storage
         self.image_files = image_file_storage
         self.board_image_records = board_image_record_storage
-        self.metadata = metadata
         self.urls = url
         self.logger = logger
         self.names = names
@@ -165,6 +159,7 @@ class ImageService(ImageServiceABC):
         node_id: Optional[str] = None,
         session_id: Optional[str] = None,
         is_intermediate: bool = False,
+        metadata: Optional[dict] = None,
     ) -> ImageDTO:
         if image_origin not in ResourceOrigin:
             raise InvalidOriginException
@@ -174,7 +169,16 @@ class ImageService(ImageServiceABC):
 
         image_name = self._services.names.create_image_name()
 
-        metadata = self._get_metadata(session_id, node_id)
+        graph = None
+
+        if session_id is not None:
+            session_raw = self._services.graph_execution_manager.get_raw(session_id)
+            if session_raw is not None:
+                try:
+                    graph = get_metadata_graph_from_raw_session(session_raw)
+                except Exception as e:
+                    self._services.logger.warn(f"Failed to parse session graph: {e}")
+                    graph = None
 
         (width, height) = image.size
 
@@ -191,14 +195,12 @@ class ImageService(ImageServiceABC):
                 is_intermediate=is_intermediate,
                 # Nullable fields
                 node_id=node_id,
-                session_id=session_id,
                 metadata=metadata,
+                session_id=session_id,
             )
 
             self._services.image_files.save(
-                image_name=image_name,
+                image_name=image_name, image=image, metadata=metadata, graph=graph
-                image=image,
-                metadata=metadata,
             )
 
             image_dto = self.get_dto(image_name)
@@ -268,6 +270,34 @@ class ImageService(ImageServiceABC):
             self._services.logger.error("Problem getting image DTO")
             raise e
 
+    def get_metadata(self, image_name: str) -> Optional[ImageMetadata]:
+        try:
+            image_record = self._services.image_records.get(image_name)
+
+            if not image_record.session_id:
+                return ImageMetadata()
+
+            session_raw = self._services.graph_execution_manager.get_raw(
+                image_record.session_id
+            )
+            graph = None
+
+            if session_raw:
+                try:
+                    graph = get_metadata_graph_from_raw_session(session_raw)
+                except Exception as e:
+                    self._services.logger.warn(f"Failed to parse session graph: {e}")
+                    graph = None
+
+            metadata = self._services.image_records.get_metadata(image_name)
+            return ImageMetadata(graph=graph, metadata=metadata)
+        except ImageRecordNotFoundException:
+            self._services.logger.error("Image record not found")
+            raise
+        except Exception as e:
+            self._services.logger.error("Problem getting image DTO")
+            raise e
+
     def get_path(self, image_name: str, thumbnail: bool = False) -> str:
         try:
             return self._services.image_files.get_path(image_name, thumbnail)
@@ -367,15 +397,3 @@ class ImageService(ImageServiceABC):
         except Exception as e:
             self._services.logger.error("Problem deleting image records and files")
             raise e
-
-    def _get_metadata(
-        self, session_id: Optional[str] = None, node_id: Optional[str] = None
-    ) -> Optional[ImageMetadata]:
-        """Get the metadata for a node."""
-        metadata = None
-
-        if node_id is not None and session_id is not None:
-            session = self._services.graph_execution_manager.get(session_id)
-            metadata = self._services.metadata.create_image_metadata(session, node_id)
-
-        return metadata

invokeai/app/services/item_storage.py

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Callable, Generic, TypeVar
+from typing import Callable, Generic, Optional, TypeVar
 
 from pydantic import BaseModel, Field
 from pydantic.generics import GenericModel
@@ -29,14 +29,22 @@ class ItemStorageABC(ABC, Generic[T]):
 
     @abstractmethod
     def get(self, item_id: str) -> T:
+        """Gets the item, parsing it into a Pydantic model"""
+        pass
+
+    @abstractmethod
+    def get_raw(self, item_id: str) -> Optional[str]:
+        """Gets the raw item as a string, skipping Pydantic parsing"""
         pass
 
     @abstractmethod
     def set(self, item: T) -> None:
+        """Sets the item"""
         pass
 
     @abstractmethod
     def list(self, page: int = 0, per_page: int = 10) -> PaginatedResults[T]:
+        """Gets a paginated list of items"""
         pass
 
     @abstractmethod

invokeai/app/services/metadata.py

@@ -1,142 +0,0 @@
-from abc import ABC, abstractmethod
-from typing import Any, Optional
-import networkx as nx
-
-from invokeai.app.models.metadata import ImageMetadata
-from invokeai.app.services.graph import Graph, GraphExecutionState
-
-
-class MetadataServiceBase(ABC):
-    """Handles building metadata for nodes, images, and outputs."""
-
-    @abstractmethod
-    def create_image_metadata(
-        self, session: GraphExecutionState, node_id: str
-    ) -> ImageMetadata:
-        """Builds an ImageMetadata object for a node."""
-        pass
-
-
-class CoreMetadataService(MetadataServiceBase):
-    _ANCESTOR_TYPES = ["t2l", "l2l"]
-    """The ancestor types that contain the core metadata"""
-
-    _ANCESTOR_PARAMS = ["type", "steps", "model", "cfg_scale", "scheduler", "strength"]
-    """The core metadata parameters in the ancestor types"""
-
-    _NOISE_FIELDS = ["seed", "width", "height"]
-    """The core metadata parameters in the noise node"""
-
-    def create_image_metadata(
-        self, session: GraphExecutionState, node_id: str
-    ) -> ImageMetadata:
-        metadata = self._build_metadata_from_graph(session, node_id)
-
-        return metadata
-
-    def _find_nearest_ancestor(self, G: nx.DiGraph, node_id: str) -> Optional[str]:
-        """
-        Finds the id of the nearest ancestor (of a valid type) of a given node.
-
-        Parameters:
-        G (nx.DiGraph): The execution graph, converted in to a networkx DiGraph. Its nodes must
-        have the same data as the execution graph.
-        node_id (str): The ID of the node.
-
-        Returns:
-        str | None: The ID of the nearest ancestor, or None if there are no valid ancestors.
-        """
-
-        # Retrieve the node from the graph
-        node = G.nodes[node_id]
-
-        # If the node type is one of the core metadata node types, return its id
-        if node.get("type") in self._ANCESTOR_TYPES:
-            return node.get("id")
-
-        # Else, look for the ancestor in the predecessor nodes
-        for predecessor in G.predecessors(node_id):
-            result = self._find_nearest_ancestor(G, predecessor)
-            if result:
-                return result
-
-        # If there are no valid ancestors, return None
-        return None
-
-    def _get_additional_metadata(
-        self, graph: Graph, node_id: str
-    ) -> Optional[dict[str, Any]]:
-        """
-        Returns additional metadata for a given node.
-
-        Parameters:
-        graph (Graph): The execution graph.
-        node_id (str): The ID of the node.
-
-        Returns:
-        dict[str, Any] | None: A dictionary of additional metadata.
-        """
-
-        metadata = {}
-
-        # Iterate over all edges in the graph
-        for edge in graph.edges:
-            dest_node_id = edge.destination.node_id
-            dest_field = edge.destination.field
-            source_node_dict = graph.nodes[edge.source.node_id].dict()
-
-            # If the destination node ID matches the given node ID, gather necessary metadata
-            if dest_node_id == node_id:
-                # Prompt
-                if dest_field == "positive_conditioning":
-                    metadata["positive_conditioning"] = source_node_dict.get("prompt")
-                # Negative prompt
-                if dest_field == "negative_conditioning":
-                    metadata["negative_conditioning"] = source_node_dict.get("prompt")
-                # Seed, width and height
-                if dest_field == "noise":
-                    for field in self._NOISE_FIELDS:
-                        metadata[field] = source_node_dict.get(field)
-        return metadata
-
-    def _build_metadata_from_graph(
-        self, session: GraphExecutionState, node_id: str
-    ) -> ImageMetadata:
-        """
-        Builds an ImageMetadata object for a node.
-
-        Parameters:
-        session (GraphExecutionState): The session.
-        node_id (str): The ID of the node.
-
-        Returns:
-        ImageMetadata: The metadata for the node.
-        """
-
-        # We need to do all the traversal on the execution graph
-        graph = session.execution_graph
-
-        # Find the nearest `t2l`/`l2l` ancestor of the given node
-        ancestor_id = self._find_nearest_ancestor(graph.nx_graph_with_data(), node_id)
-
-        # If no ancestor was found, return an empty ImageMetadata object
-        if ancestor_id is None:
-            return ImageMetadata()
-
-        ancestor_node = graph.get_node(ancestor_id)
-
-        # Grab all the core metadata from the ancestor node
-        ancestor_metadata = {
-            param: val
-            for param, val in ancestor_node.dict().items()
-            if param in self._ANCESTOR_PARAMS
-        }
-
-        # Get this image's prompts and noise parameters
-        addl_metadata = self._get_additional_metadata(graph, ancestor_id)
-
-        # If additional metadata was found, add it to the main metadata
-        if addl_metadata is not None:
-            ancestor_metadata.update(addl_metadata)
-
-        return ImageMetadata(**ancestor_metadata)

invokeai/app/services/models/image_record.py

@@ -1,13 +1,14 @@
 import datetime
 from typing import Optional, Union
+
 from pydantic import BaseModel, Extra, Field, StrictBool, StrictStr
+
 from invokeai.app.models.image import ImageCategory, ResourceOrigin
-from invokeai.app.models.metadata import ImageMetadata
 from invokeai.app.util.misc import get_iso_timestamp
 
 
 class ImageRecord(BaseModel):
-    """Deserialized image record."""
+    """Deserialized image record without metadata."""
 
     image_name: str = Field(description="The unique name of the image.")
     """The unique name of the image."""
@@ -43,11 +44,6 @@ class ImageRecord(BaseModel):
         description="The node ID that generated this image, if it is a generated image.",
     )
     """The node ID that generated this image, if it is a generated image."""
-    metadata: Optional[ImageMetadata] = Field(
-        default=None,
-        description="A limited subset of the image's generation metadata. Retrieve the image's session for full metadata.",
-    )
-    """A limited subset of the image's generation metadata. Retrieve the image's session for full metadata."""
 
 
 class ImageRecordChanges(BaseModel, extra=Extra.forbid):
@@ -112,6 +108,7 @@ def deserialize_image_record(image_dict: dict) -> ImageRecord:
 
     # Retrieve all the values, setting "reasonable" defaults if they are not present.
 
+    # TODO: do we really need to handle default values here? ideally the data is the correct shape...
     image_name = image_dict.get("image_name", "unknown")
     image_origin = ResourceOrigin(
         image_dict.get("image_origin", ResourceOrigin.INTERNAL.value)
@@ -128,13 +125,6 @@ def deserialize_image_record(image_dict: dict) -> ImageRecord:
     deleted_at = image_dict.get("deleted_at", get_iso_timestamp())
     is_intermediate = image_dict.get("is_intermediate", False)
 
-    raw_metadata = image_dict.get("metadata")
-
-    if raw_metadata is not None:
-        metadata = ImageMetadata.parse_raw(raw_metadata)
-    else:
-        metadata = None
-
     return ImageRecord(
         image_name=image_name,
         image_origin=image_origin,
@@ -143,7 +133,6 @@ def deserialize_image_record(image_dict: dict) -> ImageRecord:
         height=height,
         session_id=session_id,
         node_id=node_id,
-        metadata=metadata,
         created_at=created_at,
         updated_at=updated_at,
         deleted_at=deleted_at,

invokeai/app/services/sqlite.py

@@ -1,6 +1,6 @@
 import sqlite3
 from threading import Lock
-from typing import Generic, TypeVar, Optional, Union, get_args
+from typing import Generic, Optional, TypeVar, get_args
 
 from pydantic import BaseModel, parse_raw_as
 
@@ -78,6 +78,21 @@ class SqliteItemStorage(ItemStorageABC, Generic[T]):
 
         return self._parse_item(result[0])
 
+    def get_raw(self, id: str) -> Optional[str]:
+        try:
+            self._lock.acquire()
+            self._cursor.execute(
+                f"""SELECT item FROM {self._table_name} WHERE id = ?;""", (str(id),)
+            )
+            result = self._cursor.fetchone()
+        finally:
+            self._lock.release()
+
+        if not result:
+            return None
+
+        return result[0]
+
     def delete(self, id: str):
         try:
             self._lock.acquire()

invokeai/app/services/urls.py

@@ -22,4 +22,4 @@ class LocalUrlService(UrlServiceBase):
         if thumbnail:
             return f"{self._base_url}/images/{image_basename}/thumbnail"
 
-        return f"{self._base_url}/images/{image_basename}"
+        return f"{self._base_url}/images/{image_basename}/full"

invokeai/app/util/metadata.py

@@ -0,0 +1,55 @@
+import json
+from typing import Optional
+
+from pydantic import ValidationError
+
+from invokeai.app.services.graph import Edge
+
+
+def get_metadata_graph_from_raw_session(session_raw: str) -> Optional[dict]:
+    """
+    Parses raw session string, returning a dict of the graph.
+
+    Only the general graph shape is validated; none of the fields are validated.
+
+    Any `metadata_accumulator` nodes and edges are removed.
+
+    Any validation failure will return None.
+    """
+
+    graph = json.loads(session_raw).get("graph", None)
+
+    # sanity check make sure the graph is at least reasonably shaped
+    if (
+        type(graph) is not dict
+        or "nodes" not in graph
+        or type(graph["nodes"]) is not dict
+        or "edges" not in graph
+        or type(graph["edges"]) is not list
+    ):
+        # something has gone terribly awry, return an empty dict
+        return None
+
+    try:
+        # delete the `metadata_accumulator` node
+        del graph["nodes"]["metadata_accumulator"]
+    except KeyError:
+        # no accumulator node, all good
+        pass
+
+    # delete any edges to or from it
+    for i, edge in enumerate(graph["edges"]):
+        try:
+            # try to parse the edge
+            Edge(**edge)
+        except ValidationError:
+            # something has gone terribly awry, return an empty dict
+            return None
+
+        if (
+            edge["source"]["node_id"] == "metadata_accumulator"
+            or edge["destination"]["node_id"] == "metadata_accumulator"
+        ):
+            del graph["edges"][i]
+
+    return graph