Add nodes to support OpenAPI and similar backend workflows

.github/workflows/test-ui.yaml

@@ -1,25 +1,25 @@
 name: Tests CI
 
-on: [push, pull_request]
+on: [ push, pull_request ]
 
 jobs:
   test:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v4
-    - uses: actions/setup-node@v3
-      with:
-        node-version: 18
-    - uses: actions/setup-python@v4
-      with:
-        python-version: '3.11'
-    - name: Install requirements
-      run: |
-        python -m pip install --upgrade pip
-        pip install .
-    - name: Run Tests
-      run: | 
-        npm ci
-        npm run test:generate
-        npm test -- --verbose
-      working-directory: ./tests-ui
+      - uses: actions/checkout@v4
+      - uses: actions/setup-node@v3
+        with:
+          node-version: 18
+      - uses: actions/setup-python@v4
+        with:
+          python-version: '3.11'
+      - name: Install requirements
+        run: |
+          python -m pip install --upgrade pip
+          pip install .[dev]
+      - name: Run Tests
+        run: |
+          npm ci
+          npm run test:generate
+          npm test -- --verbose
+        working-directory: ./tests-ui

.github/workflows/test.yml

@@ -5,11 +5,7 @@ name: Build package
 # Install Python dependencies across different Python versions.
 #
 
-on:
-  push:
-    paths:
-      - "requirements.txt"
-      - ".github/workflows/test-build.yml"
+on: [ push ]
 
 jobs:
   build:
@@ -18,7 +14,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        python-version: [ "3.9", "3.10", "3.11", "3.12" ]
     steps:
       - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python-version }}
@@ -28,7 +24,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install .
-      - name: Run distributed tests
+          pip install .[dev]
+      - name: Run tests
         run: |
-          pytest tests/distributed
+          pytest tests/

comfy/cli_args.py

@@ -141,7 +141,7 @@ def create_parser() -> argparse.ArgumentParser:
                         help="Make pytorch use slower deterministic algorithms when it can. Note that this might not make images deterministic in all cases.")
 
     parser.add_argument("--dont-print-server", action="store_true", help="Don't print server output.")
-    parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI.")
+    parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI. Raises an error if nodes cannot be imported,")
     parser.add_argument("--windows-standalone-build", default=hasattr(sys, 'frozen') and getattr(sys, 'frozen'),
                         action="store_true",
                         help="Windows standalone build: Enable convenient things that most people using the standalone windows build will probably enjoy (like auto opening the page on startup).")

comfy/cmd/main.py

@@ -196,6 +196,8 @@ async def main():
         folder_paths.set_input_directory(input_dir)
 
     if args.quick_test_for_ci:
+        # for CI purposes, try importing all the nodes
+        import_all_nodes_in_workspace()
         exit(0)
 
     call_on_start = None

comfy/model_downloader.py

@@ -40,11 +40,20 @@ def get_or_download(folder_name: str, filename: str, known_files: List[HuggingFi
                 return path
             with comfy_tqdm():
                 if isinstance(known_file, HuggingFile):
-                    save_filename = known_file.save_with_filename or known_file.filename
                     path = hf_hub_download(repo_id=known_file.repo_id,
-                                           filename=save_filename,
+                                           filename=known_file.filename,
                                            local_dir=destination,
                                            resume_download=True)
+                    if known_file.save_with_filename is not None:
+                        linked_filename = known_file.save_with_filename
+                    elif os.path.basename(known_file.filename) != known_file.filename:
+                        linked_filename = os.path.basename(known_file.filename)
+                    else:
+                        linked_filename = None
+                    try:
+                        os.symlink(os.path.join(destination,known_file.filename), linked_filename)
+                    except Exception as exc_info:
+                        logging.error(f"Failed to link file with alternative download save name in a way that is compatible with Hugging Face caching {repr(known_file)}", exc_info=exc_info)
                 else:
                     url: Optional[str] = None
                     save_filename = known_file.save_with_filename or known_file.filename

comfy/nodes/package.py

@@ -12,7 +12,6 @@ from importlib.metadata import entry_points
 from pkg_resources import resource_filename
 from .package_typing import ExportedNodes
 
-
 _comfy_nodes: ExportedNodes = ExportedNodes()
 
 
@@ -35,10 +34,13 @@ def _import_nodes_in_module(exported_nodes: ExportedNodes, module: types.ModuleT
     return node_class_mappings and len(node_class_mappings) > 0 or web_directory
 
 
-def _import_and_enumerate_nodes_in_module(module: types.ModuleType, print_import_times=False,
+def _import_and_enumerate_nodes_in_module(module: types.ModuleType,
+                                          print_import_times=False,
+                                          raise_on_failure=False,
                                           depth=100) -> ExportedNodes:
     exported_nodes = ExportedNodes()
     timings = []
+    exceptions = []
     if _import_nodes_in_module(exported_nodes, module):
         pass
     else:
@@ -65,15 +67,21 @@ def _import_and_enumerate_nodes_in_module(module: types.ModuleType, print_import
                         continue
                 logging.error(f"{full_name} import failed", exc_info=x)
                 success = False
+                exceptions.append(x)
             timings.append((time.perf_counter() - time_before, full_name, success))
 
     if print_import_times and len(timings) > 0 or any(not success for (_, _, success) in timings):
         for (duration, module_name, success) in sorted(timings):
             print(f"{duration:6.1f} seconds{'' if success else ' (IMPORT FAILED)'}, {module_name}")
+    if raise_on_failure and len(exceptions) > 0:
+        try:
+            raise ExceptionGroup("Node import failed", exceptions)
+        except NameError:
+            raise exceptions[0]
     return exported_nodes
 
 
-def import_all_nodes_in_workspace(vanilla_custom_nodes=True) -> ExportedNodes:
+def import_all_nodes_in_workspace(vanilla_custom_nodes=True, raise_on_failure=False) -> ExportedNodes:
     # now actually import the nodes, to improve control of node loading order
     from comfy_extras import nodes as comfy_extras_nodes
     from . import base_nodes
@@ -81,7 +89,7 @@ def import_all_nodes_in_workspace(vanilla_custom_nodes=True) -> ExportedNodes:
     # only load these nodes once
     if len(_comfy_nodes) == 0:
         base_and_extra = reduce(lambda x, y: x.update(y),
-                                map(_import_and_enumerate_nodes_in_module, [
+                                map(lambda module_inner: _import_and_enumerate_nodes_in_module(module_inner, raise_on_failure=raise_on_failure), [
                                     # this is the list of default nodes to import
                                     base_nodes,
                                     comfy_extras_nodes

comfy/nodes/package_typing.py

@@ -63,6 +63,7 @@ ValidateInputsMethod = Optional[Callable[..., Union[bool, str]]]
 
 class FunctionReturnsUIVariables(TypedDict):
     ui: dict
+    result: NotRequired[Sequence[Any]]
 
 
 class SaveNodeResult(TypedDict, total=True):
@@ -78,6 +79,7 @@ class UIImagesImagesResult(TypedDict, total=True):
 
 class UIImagesResult(TypedDict, total=True):
     ui: UIImagesImagesResult
+    result: NotRequired[Sequence[Any]]
 
 
 class UILatentsLatentsResult(TypedDict, total=True):
@@ -86,6 +88,7 @@ class UILatentsLatentsResult(TypedDict, total=True):
 
 class UILatentsResult(TypedDict, total=True):
     ui: UILatentsLatentsResult
+    result: NotRequired[Sequence[Any]]
 
 
 ValidatedNodeResult = Union[Tuple, UIImagesResult, UILatentsResult, FunctionReturnsUIVariables]

comfy_extras/nodes/nodes_open_api.py

@@ -0,0 +1,592 @@
+from __future__ import annotations
+
+import json
+import logging
+import os
+import posixpath
+import re
+import sys
+import uuid
+from datetime import datetime
+from typing import Sequence, Optional, TypedDict, Dict, List, Literal, Callable, Tuple
+
+import PIL
+import fsspec
+import numpy as np
+from PIL import Image
+from PIL.PngImagePlugin import PngInfo
+from fsspec.core import OpenFiles, OpenFile
+from fsspec.generic import GenericFileSystem
+from fsspec.implementations.local import LocalFileSystem
+from joblib import Parallel, delayed
+from torch import Tensor
+from natsort import natsorted
+
+from comfy.cmd import folder_paths
+from comfy.digest import digest
+from comfy.nodes.package_typing import CustomNode, InputTypes, FunctionReturnsUIVariables, SaveNodeResult, \
+    InputTypeSpec, ValidatedNodeResult
+
+_open_api_common_schema: Dict[str, InputTypeSpec] = {
+    "name": ("STRING", {}),
+    "title": ("STRING", {"default": ""}),
+    "description": ("STRING", {"default": "", "multiline": True}),
+    "__required": ("BOOLEAN", {"default": True})
+}
+
+_common_image_metadatas = {
+    "CreationDate": ("STRING", {"default": ""}),
+    "Title": ("STRING", {"default": ""}),
+    "Description": ("STRING", {"default": ""}),
+    "Artist": ("STRING", {"default": ""}),
+    "ImageNumber": ("STRING", {"default": ""}),
+    "Rating": ("STRING", {"default": ""}),
+    "UserComment": ("STRING", {"default": "", "multiline": True}),
+}
+
+_null_uri = "/dev/null"
+
+
+def is_null_uri(local_uri):
+    return local_uri == _null_uri or local_uri == "NUL"
+
+
+class FsSpecComfyMetadata(TypedDict, total=True):
+    prompt_json_str: str
+    batch_number_str: str
+
+
+class SaveNodeResultWithName(SaveNodeResult):
+    name: str
+
+
+class IntRequestParameter(CustomNode):
+
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                **_open_api_common_schema,
+                "value": ("INT", {"default": 0, "min": -sys.maxsize, "max": sys.maxsize})
+            }
+        }
+
+    RETURN_TYPES = ("INT",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, value=0, *args, **kwargs):
+        return (value,)
+
+
+class FloatRequestParameter(CustomNode):
+
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                **_open_api_common_schema,
+                "value": ("FLOAT", {"default": 0})
+            }
+        }
+
+    RETURN_TYPES = ("FLOAT",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, value=0.0, *args, **kwargs):
+        return (value,)
+
+
+class StringRequestParameter(CustomNode):
+
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                **_open_api_common_schema,
+                "value": ("STRING", {"multiline": True})
+            }
+        }
+
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, value="", *args, **kwargs):
+        return (value,)
+
+
+class HashImage(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "images": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("IMAGE_HASHES",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, images: Sequence[Tensor]) -> Sequence[str]:
+        def process_image(image: Tensor) -> str:
+            image_as_numpy_array: np.ndarray = 255. * image.cpu().numpy()
+            image_as_numpy_array = np.ascontiguousarray(np.clip(image_as_numpy_array, 0, 255).astype(np.uint8))
+            data = image_as_numpy_array.data
+            try:
+                image_bytes_digest = digest(data)
+            finally:
+                data.release()
+            return image_bytes_digest
+
+        hashes = Parallel(n_jobs=-1)(delayed(process_image)(image) for image in images)
+        return hashes
+
+
+class StringPosixPathJoin(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                f"value{i}": ("STRING", {"default": "", "multiline": True}) for i in range(5)
+            }
+        }
+
+    RETURN_TYPES = ("STRING",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, *args: str, **kwargs):
+        return posixpath.join(*[kwargs[key] for key in natsorted(kwargs.keys())])
+
+
+class LegacyOutputURIs(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                "prefix": ("STRING", {"default": "ComfyUI_"}),
+                "suffix": ("STRING", {"default": "_.png"}),
+            }
+        }
+
+    RETURN_TYPES = ("URIS",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, images: Sequence[Tensor], prefix: str = "ComfyUI_", suffix: str = "_.png") -> List[str]:
+        output_directory = folder_paths.get_output_directory()
+        pattern = rf'^{prefix}([\d]+){suffix}$'
+        compiled_pattern = re.compile(pattern)
+        matched_values = ["0"]
+
+        # todo: use fcntl to lock a pattern while executing a job
+        with os.scandir(output_directory) as entries:
+            for entry in entries:
+                match = compiled_pattern.match(entry.name)
+                if entry.is_file() and match is not None:
+                    matched_values.append(match.group(1))
+
+        # find the highest value in the matched files
+        highest_value = max(int(v, 10) for v in matched_values)
+        # substitute batch number string
+        # this is not going to produce exactly the same path names as SaveImage, but there's no reason to for %batch_num%
+        return [os.path.join(output_directory, f'{prefix.replace("%batch_num%", str(i))}{highest_value + i + 1:05d}{suffix}') for i in range(len(images))]
+
+
+class DevNullUris(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "images": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("URIS",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, images: Sequence[Tensor]):
+        return [_null_uri] * len(images)
+
+
+class StringJoin(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        required = {f"value{i}": ("STRING", {"default": "", "multiline": True}) for i in range(5)}
+        required["separator"] = ("STRING", {"default": "_"})
+        return {
+            "required": required
+        }
+
+    RETURN_TYPES = ("STRING",)
+    CATEGORY = "openapi"
+
+    def execute(self, separator: str = "_", *args: str, **kwargs):
+        return separator.join([kwargs[key] for key in natsorted(kwargs.keys())])
+
+
+class StringToUri(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "value": ("STRING", {"default": "", "multiline": True}),
+                "batch": ("INT", {"default": 1})
+            }
+        }
+
+    RETURN_TYPES = ("URIS",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, value: str = "", batch: int = 1):
+        return [value] * batch
+
+
+class UriFormat(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "uri_template": ("STRING", {"default": "{output}/{uuid4}_{batch_index}.png"}),
+                "metadata_uri_extension": ("STRING", {"default": ".json"}),
+                "image_hash_format_name": ("STRING", {"default": "image_hash"}),
+                "uuid_format_name": ("STRING", {"default": "uuid4"}),
+                "batch_index_format_name": ("STRING", {"default": "batch_index"}),
+                "output_dir_format_name": ("STRING", {"default": "output"}),
+            },
+            "optional": {
+                "images": ("IMAGE",),
+                "image_hashes": ("IMAGE_HASHES",),
+            },
+            "hidden": {
+                "prompt": "PROMPT",
+                "extra_pnginfo": "EXTRA_PNGINFO"
+            },
+        }
+
+    RETURN_TYPES = ("URIS", "URIS")
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self,
+                uri_template: str = "{output}/{uuid}_{batch_index:05d}.png",
+                metadata_uri_extension: str = ".json",
+                images: Optional[Sequence[Tensor]] | List[Literal[None]] = None,
+                image_hashes: Optional[Sequence[str]] = None,
+                output_dir_format_name: str = "output",
+                image_hash_format_name: str = "image_hash",
+                batch_index_format_name: str = "batch_index",
+                uuid_format_name: str = "uuid",
+                *args, **kwargs) -> Tuple[Sequence[str], Sequence[str]]:
+        batch_indices = [0]
+        if images is not None:
+            batch_indices = list(range(len(images)))
+        if image_hashes is None:
+            image_hashes = [""] * len(batch_indices)
+        if len(image_hashes) > len(batch_indices):
+            batch_indices = list(range(len(image_hashes)))
+
+        # trusted but not verified
+        output_directory = folder_paths.get_output_directory()
+
+        uris = []
+        metadata_uris = []
+        without_ext, ext = os.path.splitext(uri_template)
+        metadata_uri_template = f"{without_ext}{metadata_uri_extension}"
+        for batch_index, image_hash in zip(batch_indices, image_hashes):
+            uuid_val = str(uuid.uuid4())
+            format_vars = {
+                image_hash_format_name: image_hash,
+                uuid_format_name: uuid_val,
+                batch_index_format_name: batch_index,
+                output_dir_format_name: output_directory
+            }
+            uri = uri_template.format(**format_vars)
+            metadata_uri = metadata_uri_template.format(**format_vars)
+
+            uris.append(uri)
+            metadata_uris.append(metadata_uri)
+
+        return uris, metadata_uris
+
+
+class ImageExifMerge(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                f"value{i}": ("EXIF",) for i in range(5)
+            }
+        }
+
+    RETURN_TYPES = ("EXIF",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, **kwargs):
+        merges = [kwargs[key] for key in natsorted(kwargs.keys())]
+        exifs_per_image = [list(group) for group in zip(*[pair for pair in merges])]
+        result = []
+        for exifs in exifs_per_image:
+            new_exif = {}
+            for exif in exifs:
+                new_exif.update({k: v for k,v in exif.items() if v != ""})
+
+            result.append(new_exif)
+        return result
+
+class ImageExifCreationDateAndBatchNumber(CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "images": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("EXIF",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+    def execute(self, images: Sequence[Tensor]):
+        return [{
+            "ImageNumber": str(i),
+            "CreationDate": datetime.now().strftime("%Y:%m:%d %H:%M:%S%z")
+        } for i in range(len(images))]
+
+
+class ImageExifBase:
+    def execute(self, images: Sequence[Tensor] = (), *args, **metadata):
+        metadata = {k: v for k, v in metadata.items() if v != ""}
+        return [{**metadata} for _ in images]
+
+
+class ImageExif(ImageExifBase, CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                **_common_image_metadatas
+            }
+        }
+
+    RETURN_TYPES = ("EXIF",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+
+class ImageExifUncommon(ImageExifBase, CustomNode):
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                "images": ("IMAGE",),
+                **_common_image_metadatas,
+                "Make": ("STRING", {"default": ""}),
+                "Model": ("STRING", {"default": ""}),
+                "ExposureTime": ("STRING", {"default": ""}),
+                "FNumber": ("STRING", {"default": ""}),
+                "ISO": ("STRING", {"default": ""}),
+                "DateTimeOriginal": ("STRING", {"default": ""}),
+                "ShutterSpeedValue": ("STRING", {"default": ""}),
+                "ApertureValue": ("STRING", {"default": ""}),
+                "BrightnessValue": ("STRING", {"default": ""}),
+                "FocalLength": ("STRING", {"default": ""}),
+                "MeteringMode": ("STRING", {"default": ""}),
+                "Flash": ("STRING", {"default": ""}),
+                "WhiteBalance": ("STRING", {"default": ""}),
+                "ExposureMode": ("STRING", {"default": ""}),
+                "DigitalZoomRatio": ("STRING", {"default": ""}),
+                "FocalLengthIn35mmFilm": ("STRING", {"default": ""}),
+                "SceneCaptureType": ("STRING", {"default": ""}),
+                "GPSLatitude": ("STRING", {"default": ""}),
+                "GPSLongitude": ("STRING", {"default": ""}),
+                "GPSTimeStamp": ("STRING", {"default": ""}),
+                "GPSAltitude": ("STRING", {"default": ""}),
+                "LensMake": ("STRING", {"default": ""}),
+                "LensModel": ("STRING", {"default": ""}),
+            }
+        }
+
+    RETURN_TYPES = ("EXIF",)
+    FUNCTION = "execute"
+    CATEGORY = "openapi"
+
+
+class SaveImagesResponse(CustomNode):
+
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypes:
+        return {
+            "required": {
+                **_open_api_common_schema,
+                "images": ("IMAGE",),
+                "uris": ("URIS",),
+                "pil_save_format": ("STRING", {"default": "png"}),
+            },
+            "optional": {
+                "exif": ("EXIF",),
+                "metadata_uris": ("URIS",),
+                "local_uris": ("URIS",)
+            },
+            "hidden": {
+                "prompt": "PROMPT",
+                "extra_pnginfo": "EXTRA_PNGINFO"
+            },
+        }
+
+    FUNCTION = "execute"
+    OUTPUT_NODE = True
+    RETURN_TYPES = ("IMAGE_RESULT",)
+    CATEGORY = "openapi"
+
+    def execute(self,
+                name: str = "",
+                images: Sequence[Tensor] = tuple(),
+                uris: Sequence[str] = ("",),
+                exif: Sequence[dict] = None,
+                metadata_uris: Optional[Sequence[str | None]] = None,
+                local_uris: Optional[Sequence[Optional[str]]] = None,
+                pil_save_format="png",
+                # from comfyui
+                prompt: Optional[dict] = None,
+                extra_pnginfo=None,
+                *args,
+                **kwargs,
+                ) -> FunctionReturnsUIVariables:
+
+        ui_images_result: ValidatedNodeResult = {"ui": {
+            "images": []
+        }}
+
+        if metadata_uris is None:
+            metadata_uris = [None] * len(images)
+        if local_uris is None:
+            local_uris = [None] * len(images)
+        if exif is None:
+            exif = [dict() for _ in range(len(images))]
+
+        assert len(uris) == len(images) == len(metadata_uris) == len(local_uris) == len(exif), f"len(uris)={len(uris)} == len(images)={len(images)} == len(metadata_uris)={len(metadata_uris)} == len(local_uris)={len(local_uris)} == len(exif)={len(exif)}"
+
+        image: Tensor
+        uri: str
+        metadata_uri: str | None
+        local_uri: str | Callable[[bytearray | memoryview], str]
+
+        images_ = ui_images_result["ui"]["images"]
+
+        for batch_number, (image, uri, metadata_uri, local_uri, exif_inst) in enumerate(zip(images, uris, metadata_uris, local_uris, exif)):
+            image_as_numpy_array: np.ndarray = 255. * image.cpu().numpy()
+            image_as_numpy_array = np.ascontiguousarray(np.clip(image_as_numpy_array, 0, 255).astype(np.uint8))
+            image_as_pil: PIL.Image = Image.fromarray(image_as_numpy_array)
+
+            if prompt is not None and "prompt" not in exif_inst:
+                exif_inst["prompt"] = json.dumps(prompt)
+            if extra_pnginfo is not None:
+                for x in extra_pnginfo:
+                    exif_inst[x] = json.dumps(extra_pnginfo[x])
+
+            png_metadata = PngInfo()
+            for tag, value in exif_inst.items():
+                png_metadata.add_text(tag, value)
+
+            fsspec_metadata: FsSpecComfyMetadata = {
+                "prompt_json_str": json.dumps(prompt, separators=(',', ':')),
+                "batch_number_str": str(batch_number),
+            }
+
+            _, file_ext = os.path.splitext(uri)
+
+            additional_args = {}
+            if pil_save_format.lower() == "png":
+                additional_args = {"pnginfo": png_metadata, "compress_level": 9}
+
+            # save it to the local directory when None is passed with a random name
+            output_directory = folder_paths.get_output_directory()
+            test_open: OpenFile = fsspec.open(uri)
+            fs: GenericFileSystem = test_open.fs
+            uri_is_remote = not isinstance(fs, LocalFileSystem)
+
+            local_uri: str
+            if uri_is_remote and local_uri is None:
+                filename_for_ui = f"{uuid.uuid4()}.png"
+                local_uri = os.path.join(output_directory, filename_for_ui)
+                subfolder = ""
+            elif uri_is_remote and local_uri is not None:
+                filename_for_ui = os.path.basename(local_uri)
+                subfolder = self.subfolder_of(local_uri, output_directory)
+            else:
+                filename_for_ui = os.path.basename(uri)
+                subfolder = self.subfolder_of(uri, output_directory) if os.path.isabs(uri) else os.path.dirname(uri)
+
+            if not uri_is_remote and not os.path.isabs(uri):
+                uri = os.path.join(output_directory, uri)
+            abs_path = uri
+            try:
+                with fsspec.open(uri, mode="wb", auto_mkdir=True) as f:
+                    image_as_pil.save(f, format=pil_save_format, **additional_args)
+                if metadata_uri is not None:
+                    # all values are stringified for the metadata
+                    # in case these are going to be used as S3, google blob storage key-value tags
+                    fsspec_metadata_img = {k: v for k, v in fsspec_metadata.items()}
+                    fsspec_metadata_img.update(exif)
+
+                    with fsspec.open(metadata_uri, mode="wt") as f:
+                        json.dump(fsspec_metadata, f)
+            except Exception as e:
+                logging.error(f"Error while trying to save file with fsspec_url {uri}", exc_info=e)
+                abs_path = os.path.abspath(local_uri)
+
+            if is_null_uri(local_uri):
+                filename_for_ui = ""
+                subfolder = ""
+            elif uri_is_remote:
+                logging.debug(f"saving this uri locally: {local_uri}")
+                os.makedirs(os.path.dirname(local_uri), exist_ok=True)
+                image_as_pil.save(local_uri, format=pil_save_format, **additional_args)
+
+            img_item: SaveNodeResultWithName = {
+                "abs_path": str(abs_path),
+                "filename": filename_for_ui,
+                "subfolder": subfolder,
+                "type": "output",
+                "name": name
+            }
+
+            images_.append(img_item)
+        if "ui" in ui_images_result and "images" in ui_images_result["ui"]:
+            ui_images_result["result"] = images_
+
+        return ui_images_result
+
+    def subfolder_of(self, local_uri, output_directory):
+        return os.path.dirname(os.path.relpath(os.path.abspath(local_uri), os.path.abspath(output_directory)))
+
+
+NODE_CLASS_MAPPINGS = {}
+for cls in (
+        IntRequestParameter,
+        FloatRequestParameter,
+        StringRequestParameter,
+        HashImage,
+        StringPosixPathJoin,
+        LegacyOutputURIs,
+        DevNullUris,
+        StringJoin,
+        StringToUri,
+        UriFormat,
+        ImageExif,
+        ImageExifMerge,
+        ImageExifUncommon,
+        ImageExifCreationDateAndBatchNumber,
+        SaveImagesResponse,
+
+):
+    NODE_CLASS_MAPPINGS[cls.__name__] = cls

requirements-dev.txt

@@ -3,4 +3,5 @@ pytest-asyncio
 websocket-client==1.6.1
 PyInstaller
 testcontainers-rabbitmq
-mypy>=1.6.0
+mypy>=1.6.0
+freezegun

requirements.txt

@@ -15,7 +15,7 @@ jsonmerge>=1.9.0
 clean-fid>=0.1.35
 clip @ git+https://github.com/openai/CLIP.git@main#egg=clip
 resize-right>=0.0.2
-opencv-python>=4.7.0.72
+opencv-python-headless>=4.9.0.80
 albumentations>=1.3.0
 aiofiles>=23.1.0
 frozendict>=2.3.6
@@ -33,4 +33,6 @@ kornia>=0.7.1
 mpmath>=1.0,!=1.4.0a0
 huggingface_hub
 lazy-object-proxy
-can_ada
+can_ada
+fsspec
+natsort

tests/compare/conftest.py

@@ -29,6 +29,8 @@ def args_pytest(pytestconfig):
 
 def gather_file_basenames(directory: str):
     files = []
+    if not os.path.isdir(directory):
+        return files
     for file in os.listdir(directory):
         if file.endswith(".png"):
             files.append(file)

tests/compare/test_quality.py

@@ -1,6 +1,8 @@
 import datetime
 import numpy as np
 import os
+
+import torch
 from PIL import Image
 import pytest
 from pytest import fixture
@@ -9,12 +11,13 @@ from typing import Tuple, List
 from cv2 import imread, cvtColor, COLOR_BGR2RGB
 from skimage.metrics import structural_similarity as ssim
 
-
 """
 This test suite compares images in 2 directories by file name
 The directories are specified by the command line arguments --baseline_dir and --test_dir
 
 """
+
+
 # ssim: Structural Similarity Index
 # Returns a tuple of (ssim, diff_image)
 def ssim_score(img0: np.ndarray, img1: np.ndarray) -> Tuple[float, np.ndarray]:
@@ -22,7 +25,8 @@ def ssim_score(img0: np.ndarray, img1: np.ndarray) -> Tuple[float, np.ndarray]:
     # rescale the difference image to 0-255 range
     diff = (diff * 255).astype("uint8")
     return score, diff
-    
+
+
 # Metrics must return a tuple of (score, diff_image)
 METRICS = {"ssim": ssim_score}
 METRICS_PASS_THRESHOLD = {"ssim": 0.95}
@@ -32,7 +36,7 @@ class TestCompareImageMetrics:
     @fixture(scope="class")
     def test_file_names(self, args_pytest):
         test_dir = args_pytest['test_dir']
-        fnames = self.gather_file_basenames(test_dir)  
+        fnames = self.gather_file_basenames(test_dir)
         yield fnames
         del fnames
 
@@ -56,50 +60,53 @@ class TestCompareImageMetrics:
                     score = self.lookup_score_from_fname(file, metrics_file)
                     image_file_list = []
                     image_file_list.append([
-                                            os.path.join(baseline_dir, file),
-                                            os.path.join(test_dir, file),
-                                            os.path.join(metric_path, file)
-                                            ])
+                        os.path.join(baseline_dir, file),
+                        os.path.join(test_dir, file),
+                        os.path.join(metric_path, file)
+                    ])
                     # Create grid
                     image_list = [[Image.open(file) for file in files] for files in image_file_list]
                     grid = self.image_grid(image_list)
                     grid.save(os.path.join(grid_dir, f"{metric_dir}_{score:.3f}_{file}"))
-    
+
     # Tests run for each baseline file name
     @fixture()
     def fname(self, baseline_fname, teardown):
         yield baseline_fname
         del baseline_fname
-    
-    def test_directories_not_empty(self, args_pytest, teardown):
-        baseline_dir = args_pytest['baseline_dir']
-        test_dir = args_pytest['test_dir']
-        assert len(os.listdir(baseline_dir)) != 0, f"Baseline directory {baseline_dir} is empty"
-        assert len(os.listdir(test_dir)) != 0, f"Test directory {test_dir} is empty"
 
-    def test_dir_has_all_matching_metadata(self, fname, test_file_names, args_pytest, teardown):
+    # For a baseline image file, finds the corresponding file name in test_dir and 
+    # compares the images using the metrics in METRICS
+    @pytest.mark.parametrize("metric", METRICS.keys())
+    @pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA is not available")
+    def test_pipeline_compare(
+            self,
+            args_pytest,
+            fname,
+            test_file_names,
+            metric,
+            teardown,
+    ):
+        baseline_dir = args_pytest['baseline_dir']
+
+        test_dir = args_pytest['test_dir']
+        metrics_output_file = args_pytest['metrics_file']
+        img_output_dir = args_pytest['img_output_dir']
+
+        if not os.path.isdir(baseline_dir):
+            pytest.skip("Baseline directory does not exist")
+            return
+
+        if not os.path.isdir(test_dir):
+            pytest.skip("Test directory does not exist")
+            return
+
         # Check that all files in baseline_dir have a file in test_dir with matching metadata
         baseline_file_path = os.path.join(args_pytest['baseline_dir'], fname)
         file_paths = [os.path.join(args_pytest['test_dir'], f) for f in test_file_names]
         file_match = self.find_file_match(baseline_file_path, file_paths)
         assert file_match is not None, f"Could not find a file in {args_pytest['test_dir']} with matching metadata to {baseline_file_path}"
 
-    # For a baseline image file, finds the corresponding file name in test_dir and 
-    # compares the images using the metrics in METRICS
-    @pytest.mark.parametrize("metric", METRICS.keys())
-    def test_pipeline_compare(
-        self,
-        args_pytest,
-        fname,
-        test_file_names,
-        metric,
-        teardown,
-    ):
-        baseline_dir = args_pytest['baseline_dir']
-        test_dir = args_pytest['test_dir']
-        metrics_output_file = args_pytest['metrics_file']
-        img_output_dir = args_pytest['img_output_dir']
-        
         baseline_file_path = os.path.join(baseline_dir, fname)
 
         # Find file match
@@ -109,7 +116,7 @@ class TestCompareImageMetrics:
         # Run metrics
         sample_baseline = self.read_img(baseline_file_path)
         sample_secondary = self.read_img(test_file)
-        
+
         score, metric_img = METRICS[metric](sample_baseline, sample_secondary)
         metric_status = score > METRICS_PASS_THRESHOLD[metric]
 
@@ -140,17 +147,17 @@ class TestCompareImageMetrics:
         cols = len(img_list[0])
 
         w, h = img_list[0][0].size
-        grid = Image.new('RGB', size=(cols*w, rows*h))
-        
+        grid = Image.new('RGB', size=(cols * w, rows * h))
+
         for i, row in enumerate(img_list):
             for j, img in enumerate(row):
-                grid.paste(img, box=(j*w, i*h))
+                grid.paste(img, box=(j * w, i * h))
         return grid
 
     def lookup_score_from_fname(self,
                                 fname: str,
                                 metrics_output_file: str
-        ) -> float:
+                                ) -> float:
         fname_basestr = os.path.splitext(fname)[0]
         with open(metrics_output_file, 'r') as f:
             for line in f:
@@ -166,12 +173,12 @@ class TestCompareImageMetrics:
                 files.append(file)
         return files
 
-    def read_file_prompt(self, fname:str) -> str:
+    def read_file_prompt(self, fname: str) -> str:
         # Read prompt from image file metadata
         img = Image.open(fname)
         img.load()
         return img.info['prompt']
-    
+
     def find_file_match(self, baseline_file: str, file_paths: List[str]):
         # Find a file in file_paths with matching metadata to baseline_file
         baseline_prompt = self.read_file_prompt(baseline_file)
@@ -193,4 +200,4 @@ class TestCompareImageMetrics:
         for f in file_paths:
             test_file_prompt = self.read_file_prompt(f)
             if baseline_prompt == test_file_prompt:
-                return f
+                return f

tests/inference/test_inference.py

@@ -148,12 +148,12 @@ scheduler_list = SCHEDULER_NAMES[:]
 @pytest.mark.parametrize("sampler", sampler_list)
 @pytest.mark.parametrize("scheduler", scheduler_list)
 @pytest.mark.parametrize("prompt", prompt_list)
+@pytest.mark.skipif(not torch.cuda.is_available(), reason="CUDA is not available")
 class TestInference:
     #
     # Initialize server and client
     #
 
-
     def start_client(self, listen: str, port: int):
         # Start client
         comfy_client = ComfyClient()

tests/nodes/test_openapi_unit.py

@@ -0,0 +1,218 @@
+import os
+import pathlib
+import re
+import uuid
+from datetime import datetime
+
+import pytest
+import torch
+from PIL import Image
+from freezegun import freeze_time
+from comfy.cmd import folder_paths
+from comfy_extras.nodes.nodes_open_api import SaveImagesResponse, IntRequestParameter, FloatRequestParameter, StringRequestParameter, HashImage, StringPosixPathJoin, LegacyOutputURIs, DevNullUris, StringJoin, StringToUri, UriFormat, ImageExifMerge, ImageExifCreationDateAndBatchNumber, ImageExif, ImageExifUncommon
+
+_image_1x1 = torch.zeros((1, 1, 3), dtype=torch.float32, device="cpu")
+
+
+@pytest.fixture(scope="function", autouse=True)
+def use_tmp_path(tmp_path: pathlib.Path):
+    orig_dir = folder_paths.get_output_directory()
+    folder_paths.set_output_directory(tmp_path)
+    yield tmp_path
+    folder_paths.set_output_directory(orig_dir)
+
+
+def test_save_image_response():
+    assert SaveImagesResponse.INPUT_TYPES() is not None
+    n = SaveImagesResponse()
+    result = n.execute(images=[_image_1x1], uris=["with_prefix/1.png"], name="test")
+    assert os.path.isfile(os.path.join(folder_paths.get_output_directory(), "with_prefix/1.png"))
+    assert len(result["result"]) == 1
+    assert len(result["ui"]["images"]) == 1
+    assert result["result"][0]["filename"] == "1.png"
+    assert result["result"][0]["subfolder"] == "with_prefix"
+    assert result["result"][0]["name"] == "test"
+
+
+def test_save_image_response_abs_local_uris():
+    assert SaveImagesResponse.INPUT_TYPES() is not None
+    n = SaveImagesResponse()
+    result = n.execute(images=[_image_1x1], uris=[os.path.join(folder_paths.get_output_directory(), "with_prefix/1.png")], name="test")
+    assert os.path.isfile(os.path.join(folder_paths.get_output_directory(), "with_prefix/1.png"))
+    assert len(result["result"]) == 1
+    assert len(result["ui"]["images"]) == 1
+    assert result["result"][0]["filename"] == "1.png"
+    assert result["result"][0]["subfolder"] == "with_prefix"
+    assert result["result"][0]["name"] == "test"
+
+
+def test_save_image_response_remote_uris():
+    n = SaveImagesResponse()
+    uri = "memory://some_folder/1.png"
+    result = n.execute(images=[_image_1x1], uris=[uri])
+    assert len(result["result"]) == 1
+    assert len(result["ui"]["images"]) == 1
+    filename_ = result["result"][0]["filename"]
+    assert filename_ != "1.png"
+    assert filename_ != ""
+    assert uuid.UUID(filename_.replace(".png", "")) is not None
+    assert os.path.isfile(os.path.join(folder_paths.get_output_directory(), filename_))
+    assert result["result"][0]["abs_path"] == uri
+    assert result["result"][0]["subfolder"] == ""
+
+
+def test_save_exif():
+    n = SaveImagesResponse()
+    filename = "with_prefix/2.png"
+    result = n.execute(images=[_image_1x1], uris=[filename], name="test", exif=[{
+        "Title": "test title"
+    }])
+    filepath = os.path.join(folder_paths.get_output_directory(), filename)
+    assert os.path.isfile(filepath)
+    with Image.open(filepath) as img:
+        assert img.info['Title'] == "test title"
+
+
+def test_no_local_file():
+    n = SaveImagesResponse()
+    uri = "memory://some_folder/2.png"
+    result = n.execute(images=[_image_1x1], uris=[uri], local_uris=["/dev/null"])
+    assert len(result["result"]) == 1
+    assert len(result["ui"]["images"]) == 1
+    assert result["result"][0]["filename"] == ""
+    assert not os.path.isfile(os.path.join(folder_paths.get_output_directory(), result["result"][0]["filename"]))
+    assert result["result"][0]["abs_path"] == uri
+    assert result["result"][0]["subfolder"] == ""
+
+
+def test_int_request_parameter():
+    nt = IntRequestParameter.INPUT_TYPES()
+    assert nt is not None
+    n = IntRequestParameter()
+    v, = n.execute(value=1, name="test")
+    assert v == 1
+
+
+def test_float_request_parameter():
+    nt = FloatRequestParameter.INPUT_TYPES()
+    assert nt is not None
+    n = FloatRequestParameter()
+    v, = n.execute(value=3.5, name="test", description="")
+    assert v == 3.5
+
+
+def test_string_request_parameter():
+    nt = StringRequestParameter.INPUT_TYPES()
+    assert nt is not None
+    n = StringRequestParameter()
+    v, = n.execute(value="test", name="test")
+    assert v == "test"
+
+
+def test_hash_images():
+    nt = HashImage.INPUT_TYPES()
+    assert nt is not None
+    n = HashImage()
+    hashes = n.execute(images=[_image_1x1.clone(), _image_1x1.clone()])
+    # same image, same hash
+    assert hashes[0] == hashes[1]
+    # hash should be a valid sha256 hash
+    p = re.compile(r'^[0-9a-fA-F]{64}$')
+    for hash in hashes:
+        assert p.match(hash)
+
+
+def test_string_posix_path_join():
+    nt = StringPosixPathJoin.INPUT_TYPES()
+    assert nt is not None
+    n = StringPosixPathJoin()
+    joined_path = n.execute(value2="c", value0="a", value1="b")
+    assert joined_path == "a/b/c"
+
+
+def test_legacy_output_uris(use_tmp_path):
+    nt = LegacyOutputURIs.INPUT_TYPES()
+    assert nt is not None
+    n = LegacyOutputURIs()
+    images_ = [_image_1x1, _image_1x1]
+    output_paths = n.execute(images=images_)
+    # from SaveImage node
+    full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path("ComfyUI", str(use_tmp_path), images_[0].shape[1], images_[0].shape[0])
+    file1 = f"{filename}_{counter:05}_.png"
+    file2 = f"{filename}_{counter + 1:05}_.png"
+    files = [file1, file2]
+    assert os.path.basename(output_paths[0]) == files[0]
+    assert os.path.basename(output_paths[1]) == files[1]
+
+
+def test_null_uris():
+    nt = DevNullUris.INPUT_TYPES()
+    assert nt is not None
+    n = DevNullUris()
+    res = n.execute([_image_1x1, _image_1x1])
+    assert all(x == "/dev/null" for x in res)
+
+
+def test_string_join():
+    assert StringJoin.INPUT_TYPES() is not None
+    n = StringJoin()
+    assert n.execute(separator="*", value1="b", value3="c", value0="a") == "a*b*c"
+
+
+def test_string_to_uri():
+    assert StringToUri.INPUT_TYPES() is not None
+    n = StringToUri()
+    assert n.execute("x", batch=3) == ["x"] * 3
+
+
+def test_uri_format(use_tmp_path):
+    assert UriFormat.INPUT_TYPES() is not None
+    n = UriFormat()
+    images = [_image_1x1, _image_1x1]
+    # with defaults
+    uris, metadata_uris = n.execute(images=images, uri_template="{output}/{uuid}_{batch_index:05d}.png")
+    for uri in uris:
+        assert os.path.isabs(uri), "uri format returns absolute URIs when output appears"
+        assert os.path.commonpath([uri, use_tmp_path]) == str(use_tmp_path), "should be under output dir"
+    uris, metadata_uris = n.execute(images=images, uri_template="{output}/{uuid}.png")
+    for uri in uris:
+        assert os.path.isabs(uri)
+        assert os.path.commonpath([uri, use_tmp_path]) == str(use_tmp_path), "should be under output dir"
+
+    with pytest.raises(KeyError):
+        n.execute(images=images, uri_template="{xyz}.png")
+
+
+def test_image_exif_merge():
+    assert ImageExifMerge.INPUT_TYPES() is not None
+    n = ImageExifMerge()
+    res = n.execute(value0=[{"a": "1"}, {"a": "1"}], value1=[{"b": "2"}, {"a": "1"}], value2=[{"a": 3}, {}], value4=[{"a": ""}, {}])
+    assert res[0]["a"] == 3
+    assert res[0]["b"] == "2"
+    assert res[1]["a"] == "1"
+
+
+@freeze_time("2012-01-14 03:21:34", tz_offset=-4)
+def test_image_exif_creation_date_and_batch_number():
+    assert ImageExifCreationDateAndBatchNumber.INPUT_TYPES() is not None
+    n = ImageExifCreationDateAndBatchNumber()
+    res = n.execute(images=[_image_1x1, _image_1x1])
+    mock_now = datetime(2012, 1, 13, 23, 21, 34)
+
+    now_formatted = mock_now.strftime("%Y:%m:%d %H:%M:%S%z")
+    assert res[0]["ImageNumber"] == "0"
+    assert res[1]["ImageNumber"] == "1"
+    assert res[0]["CreationDate"] == res[1]["CreationDate"] == now_formatted
+
+
+def test_image_exif():
+    assert ImageExif.INPUT_TYPES() is not None
+    n = ImageExif()
+    res = n.execute(images=[_image_1x1], Title="test", Artist="test2")
+    assert res[0]["Title"] == "test"
+    assert res[0]["Artist"] == "test2"
+
+
+def test_image_exif_uncommon():
+    assert "DigitalZoomRatio" in ImageExifUncommon.INPUT_TYPES()
+    ImageExifUncommon().execute(images=[_image_1x1])