fix(jobs): harden ids filter per review

- parse_ids_filter: one shared parser/validator for the ids query param, used
  by the /api/jobs handler AND its tests (no more hand-copied wiring that can
  drift from — and silently outlive a regression in — the shipped handler)
- present-but-empty ids (?ids=, ?ids=,,) is now a zero-match filter, not a
  silent 'return the entire job history'
- bounded history lookup when an ids filter is present: a batch poll costs
  O(requested ids), not O(total history)
- dedupe ids so the max-count cap bounds distinct values, not repeats
- .get('id') instead of j['id'] so a job missing its id degrades to no-match
  rather than a 500

.github/workflows/ci-cursor-review.yml

@@ -0,0 +1,38 @@
+name: CI - Cursor Review
+
+# Thin caller for the shared reusable cursor-review workflow in
+# Comfy-Org/github-workflows. The review logic (panel matrix, judge
+# consolidation, prompts, extract/post/notify scripts) lives there as the
+# single source of truth, so this repo only carries the repo-specific diff
+# excludes.
+
+on:
+  pull_request:
+    types: [labeled, unlabeled]
+
+concurrency:
+  group: cursor-review-pr-${{ github.event.pull_request.number }}-${{ github.event.label.name }}
+  cancel-in-progress: true
+
+jobs:
+  cursor-review:
+    if: github.event.label.name == 'cursor-review'
+    permissions:
+      contents: read
+      pull-requests: write
+    # SHA-pinned per zizmor `unpinned-uses: hash-pin`. Bump this SHA to pick up
+    # upstream changes; keep `workflows_ref` matching so prompts/scripts load
+    # from the same commit as the workflow definition.
+    uses: Comfy-Org/github-workflows/.github/workflows/cursor-review.yml@047ca48febe3a6647608ed2e0c4331b491cb9d6a # github-workflows#9
+    with:
+      workflows_ref: 047ca48febe3a6647608ed2e0c4331b491cb9d6a
+      diff_excludes: >-
+        :!**/.claude/**
+        :!**/dist/**
+        :!**/vendor/**
+        :!**/*.generated.*
+        :!**/*.min.js
+        :!**/*.min.css
+    secrets:
+      CURSOR_API_KEY: ${{ secrets.CURSOR_API_KEY }}
+      SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}

AGENTS.md

@@ -0,0 +1,78 @@
+## Engineering Style
+
+- Keep changes small and direct. Most fixes should touch the narrowest code path
+  that explains the bug, performance issue, dtype issue, model-format issue, or
+  user-facing behavior.
+- Change the least amount of files possible. A change that touches many files is
+  more likely to be a bad change than a good one unless the broader scope is
+  directly required.
+- Prefer practical fixes over broad architecture work. Add abstractions only
+  when they remove real repeated logic or match an existing ComfyUI pattern.
+- Delete obsolete code aggressively when newer infrastructure makes it useless.
+  Remove dead fallbacks, migration paths, unused options, debug prints, and
+  compatibility branches that are no longer needed.
+- Revert or disable problematic behavior quickly when it breaks users. It is
+  better to remove a broken feature path than keep a complicated partial fix.
+- Preserve existing APIs, node names, model-loading behavior, file layout, and
+  workflow compatibility unless the change is explicitly about replacing them.
+- Code must look hand-written for this repository. Changes that read like
+  generic AI-generated code will be rejected automatically: unnecessary helper
+  layers, vague names, boilerplate comments, defensive branches without a real
+  failure mode, broad rewrites, or code that ignores the local style.
+
+## Python Style
+
+- Keep imports at module scope. Avoid inline imports unless they are already part
+  of an established optional-backend probe or are needed to avoid an import
+  cycle.
+- Do not add unnecessary `try`/`except` blocks. Use them for optional dependency,
+  platform, or backend capability detection only when the program has a useful
+  fallback. Prefer specific exception types when changing new code.
+- Let unsupported model formats, invalid quantization metadata, and bad states
+  fail with clear errors instead of silently producing lower quality output.
+- Match the existing local style in the file you edit. This codebase tolerates
+  long lines, simple helper functions, module-level state, and direct tensor
+  operations when they make the code easier to follow.
+- Keep comments sparse and useful. Short TODOs are fine when they name the
+  concrete missing follow-up.
+
+## Model, Device, and Memory Behavior
+
+- Treat dtype, device placement, VRAM usage, and offloading behavior as core
+  correctness concerns. Check CPU, CUDA, ROCm, MPS, DirectML, XPU, NPU, and low
+  VRAM implications when touching shared execution or loading code.
+- Prefer native ComfyUI formats and existing quantization/offload helpers over
+  adding parallel code paths. Use `comfy.quant_ops`, `comfy.model_management`,
+  `comfy.memory_management`, `comfy.pinned_memory`, `comfy_aimdo`, and
+  `comfy-kitchen` helpers where they already solve the problem.
+- Avoid unnecessary casts and transfers. Preserve the intended compute dtype,
+  storage dtype, bias dtype, and original tensor shape metadata.
+- When optimizing, favor small measurable changes: fewer allocations, fewer
+  device transfers, less peak memory, better batching, or use of a faster
+  existing backend op.
+
+## Nodes and User-Facing Behavior
+
+- Follow existing node conventions: `INPUT_TYPES`, `RETURN_TYPES`, `FUNCTION`,
+  `CATEGORY`, and registration through the local mapping used by that file.
+- Keep node changes backward compatible by default. Add inputs with sensible
+  defaults and avoid changing output types unless the request requires it.
+- The official mascot of ComfyUI is a very cute anime girl with massive fennec
+  ears, a big fluffy tail, long blonde wavy hair, and blue eyes. Feel free to
+  use her in ComfyUI materials, UI text, examples, tests, generated assets, or
+  comments, but do not disrespect her.
+- Warning and info messages should be short and actionable. Remove noisy or
+  misleading messages rather than adding more logging.
+- Documentation and README edits should be concise, factual, and tied to the
+  changed behavior.
+
+## Commit and Review Habits
+
+- If asked to write commit messages, use short direct subjects like the existing
+  history: `Fix ...`, `Add ...`, `Support ...`, `Remove ...`, `Update ...`,
+  `Make ...`, `Use ...`, `Disable ...`, `Bump ...`, or `Revert ...`.
+- Prefer one coherent behavioral change per commit. Dependency pins, tests, and
+  the code that needs them may be in the same commit when they are inseparable.
+- In reviews, prioritize real user impact: crashes, wrong dtype/device behavior,
+  memory regressions, broken model loading, workflow incompatibility, and noisy
+  or misleading user-facing output.

comfy/cli_args.py

@@ -240,6 +240,7 @@ database_default_path = os.path.abspath(
 )
 parser.add_argument("--database-url", type=str, default=f"sqlite:///{database_default_path}", help="Specify the database URL, e.g. for an in-memory database you can use 'sqlite:///:memory:'.")
 parser.add_argument("--enable-assets", action="store_true", help="Enable the assets system (API routes, database synchronization, and background scanning).")
+parser.add_argument("--enable-asset-hashing", action="store_true", help="Compute blake3 content hashes when scanning assets. Hashing enables future asset-portability features (deduplication, cross-machine model resolution) but adds startup cost and per-output cost on large models directories. Off by default; enable to opt in.")
 parser.add_argument("--feature-flag", type=str, action='append', default=[], metavar="KEY[=VALUE]", help="Set a server feature flag. Use KEY=VALUE to set an explicit value, or bare KEY to set it to true. Can be specified multiple times. Boolean values (true/false) and numbers are auto-converted. Examples: --feature-flag show_signin_button=true  or  --feature-flag show_signin_button")
 parser.add_argument("--list-feature-flags", action="store_true", help="Print the registry of known CLI-settable feature flags as JSON and exit.")
 

comfy/ops.py

@@ -256,7 +256,7 @@ def resolve_cast_module_with_vbar(s, dtype, device, bias_dtype, compute_dtype, w
             if (want_requant and len(fns) == 0 or update_weight):
                 seed = comfy.utils.string_to_seed(s.seed_key)
                 if isinstance(orig, QuantizedTensor):
-                    y = QuantizedTensor.from_float(x, s.layout_type, scale="recalculate", stochastic_rounding=seed)
+                    y = orig.requantize_from_float(x, scale="recalculate", stochastic_rounding=seed)
                 else:
                     y = comfy.float.stochastic_rounding(x, orig.dtype, seed=seed)
             if want_requant and len(fns) == 0:
@@ -1216,7 +1216,7 @@ def mixed_precision_ops(quant_config={}, compute_dtype=torch.bfloat16, full_prec
                         bias_dtype=input.dtype,
                         offloadable=True,
                         compute_dtype=compute_dtype,
-                        want_requant=want_requant,
+                        want_requant=True,
                     )
                     weight = weight.to(dtype=input.dtype)
                 else:
@@ -1306,8 +1306,7 @@ def mixed_precision_ops(quant_config={}, compute_dtype=torch.bfloat16, full_prec
 
             def set_weight(self, weight, inplace_update=False, seed=None, return_weight=False, **kwargs):
                 if getattr(self, 'layout_type', None) is not None:
-                    # dtype is now implicit in the layout class
-                    weight = QuantizedTensor.from_float(weight, self.layout_type, scale="recalculate", stochastic_rounding=seed, inplace_ops=True).to(self.weight.dtype)
+                    weight = self.weight.requantize_from_float(weight, scale="recalculate", stochastic_rounding=seed, inplace_ops=True).to(self.weight.dtype)
                 else:
                     weight = weight.to(self.weight.dtype)
                 if return_weight:

comfy_api_nodes/apis/gemini.py

@@ -121,6 +121,7 @@ class GeminiGenerationConfig(BaseModel):
     topK: int | None = Field(None, ge=1)
     topP: float | None = Field(None, ge=0.0, le=1.0)
     thinkingConfig: GeminiThinkingConfig | None = Field(None)
+    responseModalities: list[str] | None = Field(None)
 
 
 class GeminiImageOutputOptions(BaseModel):

comfy_api_nodes/nodes_gemini.py

@@ -13,7 +13,7 @@ import torch
 from typing_extensions import override
 
 import folder_paths
-from comfy_api.latest import IO, ComfyExtension, Input, Types
+from comfy_api.latest import IO, ComfyExtension, Input, InputImpl, Types
 from comfy_api_nodes.apis.gemini import (
     GeminiContent,
     GeminiFileData,
@@ -37,6 +37,7 @@ from comfy_api_nodes.util import (
     audio_to_base64_string,
     bytesio_to_image_tensor,
     download_url_to_image_tensor,
+    download_url_to_video_output,
     get_number_of_images,
     sync_op,
     tensor_to_base64_string,
@@ -45,6 +46,7 @@ from comfy_api_nodes.util import (
     upload_images_to_comfyapi,
     upload_video_to_comfyapi,
     validate_string,
+    validate_video_duration,
     video_to_base64_string,
 )
 
@@ -229,10 +231,29 @@ async def get_image_from_response(response: GeminiGenerateContentResponse, thoug
     return torch.cat(image_tensors, dim=0)
 
 
+async def get_video_from_response(
+    response: GeminiGenerateContentResponse, cls: type[IO.ComfyNode] | None = None
+) -> InputImpl.VideoFromFile:
+    parts = get_parts_by_type(response, "video/*")
+    for part in parts:
+        if part.inlineData and part.inlineData.data:
+            return InputImpl.VideoFromFile(BytesIO(base64.b64decode(part.inlineData.data)))
+        if part.fileData and part.fileData.fileUri:
+            return await download_url_to_video_output(part.fileData.fileUri, cls=cls)
+    model_message = get_text_from_response(response).strip()
+    if model_message:
+        raise ValueError(f"Gemini did not generate a video. Model response: {model_message}")
+    raise ValueError(
+        "Gemini did not generate a video. Try rephrasing your prompt, "
+        "shortening the requested duration, or reducing the number of input images/videos."
+    )
+
+
 def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | None:
     if not response.modelVersion:
         return None
     # Define prices (Cost per 1,000,000 tokens), see https://cloud.google.com/vertex-ai/generative-ai/pricing
+    output_video_tokens_price = 0.0
     if response.modelVersion == "gemini-2.5-pro":
         input_tokens_price = 1.25
         output_text_tokens_price = 10.0
@@ -249,18 +270,27 @@ def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | N
         input_tokens_price = 2
         output_text_tokens_price = 12.0
         output_image_tokens_price = 0.0
-    elif response.modelVersion == "gemini-3.1-flash-lite-preview":
+    elif response.modelVersion in ("gemini-3.1-flash-lite-preview", "gemini-3.1-flash-lite"):
         input_tokens_price = 0.25
         output_text_tokens_price = 1.50
         output_image_tokens_price = 0.0
-    elif response.modelVersion == "gemini-3-pro-image-preview":
+    elif response.modelVersion in ("gemini-3-pro-image-preview", "gemini-3-pro-image"):
         input_tokens_price = 2
         output_text_tokens_price = 12.0
         output_image_tokens_price = 120.0
-    elif response.modelVersion == "gemini-3.1-flash-image-preview":
+    elif response.modelVersion in ("gemini-3.1-flash-image-preview", "gemini-3.1-flash-image"):
         input_tokens_price = 0.5
         output_text_tokens_price = 3.0
         output_image_tokens_price = 60.0
+    elif response.modelVersion == "gemini-3.1-flash-lite-image":
+        input_tokens_price = 0.25
+        output_text_tokens_price = 1.50
+        output_image_tokens_price = 30.0
+    elif response.modelVersion == "gemini-omni-flash-preview":
+        input_tokens_price = 2.145
+        output_text_tokens_price = 12.87
+        output_image_tokens_price = 0.0
+        output_video_tokens_price = 25.025
     else:
         return None
     final_price = response.usageMetadata.promptTokenCount * input_tokens_price
@@ -268,6 +298,8 @@ def calculate_tokens_price(response: GeminiGenerateContentResponse) -> float | N
         for i in response.usageMetadata.candidatesTokensDetails:
             if i.modality == Modality.IMAGE:
                 final_price += output_image_tokens_price * i.tokenCount  # for Nano Banana models
+            elif i.modality == Modality.VIDEO:
+                final_price += output_video_tokens_price * i.tokenCount  # for Omni Flash
             else:
                 final_price += output_text_tokens_price * i.tokenCount
     if response.usageMetadata.thoughtsTokenCount:
@@ -1302,7 +1334,7 @@ class GeminiNanoBanana2(IO.ComfyNode):
         )
 
 
-def _nano_banana_2_v2_model_inputs():
+def _nano_banana_2_v2_model_inputs(resolutions: list[str]):
     return [
         IO.Combo.Input(
             "aspect_ratio",
@@ -1329,8 +1361,8 @@ def _nano_banana_2_v2_model_inputs():
         ),
         IO.Combo.Input(
             "resolution",
-            options=["1K", "2K", "4K"],
-            tooltip="Target output resolution. For 2K/4K the native Gemini upscaler is used.",
+            options=resolutions,
+            tooltip="Target output resolution.",
         ),
         IO.Combo.Input(
             "thinking_level",
@@ -1376,7 +1408,11 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
                     options=[
                         IO.DynamicCombo.Option(
                             "Nano Banana 2 (Gemini 3.1 Flash Image)",
-                            _nano_banana_2_v2_model_inputs(),
+                            _nano_banana_2_v2_model_inputs(resolutions=["1K", "2K", "4K"]),
+                        ),
+                        IO.DynamicCombo.Option(
+                            "Nano Banana 2 Lite",
+                            _nano_banana_2_v2_model_inputs(resolutions=["1K"]),
                         ),
                     ],
                 ),
@@ -1445,9 +1481,13 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
                 depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution"]),
                 expr="""
                 (
-                  $r := $lookup(widgets, "model.resolution");
-                  $prices := {"1k": 0.0696, "2k": 0.1014, "4k": 0.154};
-                  {"type":"usd","usd": $lookup($prices, $r), "format":{"suffix":"/Image","approximate":true}}
+                  $contains(widgets.model, "lite")
+                    ? {"type":"usd","usd": 0.034, "format":{"suffix":"/Image","approximate":true}}
+                    : (
+                        $r := $lookup(widgets, "model.resolution");
+                        $prices := {"1k": 0.0696, "2k": 0.1014, "4k": 0.154};
+                        {"type":"usd","usd": $lookup($prices, $r), "format":{"suffix":"/Image","approximate":true}}
+                      )
                 )
                 """,
             ),
@@ -1468,6 +1508,8 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
         model_choice = model["model"]
         if model_choice == "Nano Banana 2 (Gemini 3.1 Flash Image)":
             model_id = "gemini-3.1-flash-image-preview"
+        elif model_choice == "Nano Banana 2 Lite":
+            model_id = "gemini-3.1-flash-lite-image"
         else:
             model_id = model_choice
 
@@ -1517,6 +1559,149 @@ class GeminiNanoBanana2V2(IO.ComfyNode):
         )
 
 
+OMNI_MAX_IMAGES = 14
+OMNI_MAX_VIDEOS = 3
+
+OMNI_MODELS: dict[str, str] = {
+    "Omni Flash": "gemini-omni-flash-preview",
+}
+
+
+def _omni_flash_inputs() -> list[Input]:
+    """Per-model inputs for the Omni video DynamicCombo (prompt + reference media + sampling)."""
+    return [
+        IO.String.Input(
+            "prompt",
+            multiline=True,
+            default="",
+            tooltip="Describe the video to generate. Specify the length and aspect ratio directly in the "
+            'prompt, e.g. "a 6-second clip in 16:9". Length may be 3-10 seconds; the aspect ratio must be '
+            "16:9 (landscape) or 9:16 (portrait). The output is 720p, 24 FPS, with audio.",
+        ),
+        IO.Autogrow.Input(
+            "images",
+            template=IO.Autogrow.TemplateNames(
+                IO.Image.Input("image"),
+                names=[f"image_{i}" for i in range(1, OMNI_MAX_IMAGES + 1)],
+                min=0,
+            ),
+            tooltip=f"Optional reference image(s) to guide or animate the video. Up to {OMNI_MAX_IMAGES} images.",
+        ),
+        IO.Autogrow.Input(
+            "videos",
+            template=IO.Autogrow.TemplateNames(
+                IO.Video.Input("video"),
+                names=[f"video_{i}" for i in range(1, OMNI_MAX_VIDEOS + 1)],
+                min=0,
+            ),
+            tooltip=f"Optional reference video(s) to guide or edit. Up to {OMNI_MAX_VIDEOS} videos, "
+            f"each up to 10 seconds long.",
+        ),
+        IO.Float.Input(
+            "temperature",
+            default=1.0,
+            min=0.0,
+            max=2.0,
+            step=0.01,
+            tooltip="Controls randomness. Lower is more focused/deterministic, higher is more varied.",
+            advanced=True,
+        ),
+        IO.Float.Input(
+            "top_p",
+            default=0.95,
+            min=0.0,
+            max=1.0,
+            step=0.01,
+            tooltip="Nucleus sampling: sample from the smallest token set whose cumulative probability reaches top_p.",
+            advanced=True,
+        ),
+    ]
+
+
+class GeminiVideoOmni(IO.ComfyNode):
+
+    @classmethod
+    def define_schema(cls):
+        return IO.Schema(
+            node_id="GeminiVideoOmni",
+            display_name="Google Gemini Omni (Video)",
+            category="partner/video/Gemini",
+            essentials_category="Video Generation",
+            description="Generate a video with audio from a text prompt using Google's Gemini Omni Flash model. "
+            "Optionally provide reference images and/or videos to guide or edit the result. Describe the desired "
+            "length (3-10s) and aspect ratio (16:9 or 9:16) directly in the prompt.",
+            inputs=[
+                IO.DynamicCombo.Input(
+                    "model",
+                    options=[
+                        IO.DynamicCombo.Option("Omni Flash", _omni_flash_inputs()),
+                    ],
+                    tooltip="The Gemini video model used to generate the video.",
+                ),
+                IO.Int.Input(
+                    "seed",
+                    default=42,
+                    min=0,
+                    max=2147483647,
+                    control_after_generate=True,
+                    tooltip="Seed controls whether the node should re-run; "
+                    "results are non-deterministic regardless of seed.",
+                ),
+            ],
+            outputs=[
+                IO.Video.Output(),
+                IO.String.Output(),
+            ],
+            hidden=[
+                IO.Hidden.auth_token_comfy_org,
+                IO.Hidden.api_key_comfy_org,
+                IO.Hidden.unique_id,
+            ],
+            is_api_node=True,
+            price_badge=IO.PriceBadge(
+                expr='{"type":"usd","usd":0.146,"format":{"suffix":"/second","approximate":true}}'
+            ),
+        )
+
+    @classmethod
+    async def execute(cls, model: dict, seed: int) -> IO.NodeOutput:
+        prompt = model.get("prompt") or ""
+        validate_string(prompt, strip_whitespace=True, min_length=1)
+        model_id = OMNI_MODELS[model["model"]]
+
+        images = [t for t in (model.get("images") or {}).values() if t is not None]
+        videos = [v for v in (model.get("videos") or {}).values() if v is not None]
+        if sum(get_number_of_images(t) for t in images) > OMNI_MAX_IMAGES:
+            raise ValueError(f"The current maximum number of supported images is {OMNI_MAX_IMAGES}.")
+        if len(videos) > OMNI_MAX_VIDEOS:
+            raise ValueError(f"The current maximum number of supported videos is {OMNI_MAX_VIDEOS}.")
+        for video in videos:
+            validate_video_duration(video, max_duration=10)
+
+        parts: list[GeminiPart] = []
+        if images or videos:
+            parts.extend(await build_gemini_media_parts(cls, images, [], videos))
+        parts.append(GeminiPart(text=prompt))
+        response = await sync_op(
+            cls,
+            ApiEndpoint(path=f"{GEMINI_BASE_ENDPOINT}/{model_id}", method="POST"),
+            data=GeminiGenerateContentRequest(
+                contents=[GeminiContent(role=GeminiRole.user, parts=parts)],
+                generationConfig=GeminiGenerationConfig(
+                    responseModalities=["TEXT", "VIDEO"],
+                    temperature=model.get("temperature", 1.0),
+                    topP=model.get("top_p", 0.95),
+                ),
+            ),
+            response_model=GeminiGenerateContentResponse,
+            price_extractor=calculate_tokens_price,
+        )
+        return IO.NodeOutput(
+            await get_video_from_response(response, cls=cls),
+            get_text_from_response(response),
+        )
+
+
 class GeminiExtension(ComfyExtension):
     @override
     async def get_node_list(self) -> list[type[IO.ComfyNode]]:
@@ -1527,6 +1712,7 @@ class GeminiExtension(ComfyExtension):
             GeminiImage2,
             GeminiNanoBanana2,
             GeminiNanoBanana2V2,
+            GeminiVideoOmni,
             GeminiInputFiles,
         ]
 

comfy_execution/jobs.py

@@ -31,6 +31,12 @@ class JobStatus:
     ALL = [PENDING, IN_PROGRESS, COMPLETED, FAILED, CANCELLED]
 
 
+# Maximum number of (distinct) ids accepted by the `ids` filter on the jobs
+# listing. Caps request size; the bounded id-lookup in get_all_jobs then keeps
+# a batch-poll request at O(requested ids), not O(total history).
+MAX_JOB_IDS_FILTER = 100
+
+
 def validate_job_id(value) -> str:
     """Validate a client-supplied job (prompt) id.
 
@@ -50,6 +56,56 @@ def validate_job_id(value) -> str:
     return value
 
 
+class JobIdsFilterError(ValueError):
+    """Raised when the ``ids`` query-param value is malformed.
+
+    Carries an HTTP-ready ``payload`` dict so the caller can return it verbatim
+    with a 400 without re-deriving the message.
+    """
+
+    def __init__(self, payload: dict):
+        self.payload = payload
+        super().__init__(payload.get("error", "invalid ids"))
+
+
+def parse_ids_filter(ids_param: Optional[str]) -> Optional[list[str]]:
+    """Parse the ``ids`` query-param value into a filter list.
+
+    Single source of truth for ``ids`` parsing/validation, shared by the HTTP
+    handler and its tests so the two cannot drift.
+
+    Returns:
+        - ``None`` when the param is absent (``ids_param is None``) -> no filter.
+        - A de-duplicated list when present. An empty/blank value (``?ids=``,
+          ``?ids=,,``) yields ``[]``, which ``get_all_jobs`` treats as a
+          zero-match filter -- NOT "return everything".
+
+    Raises:
+        JobIdsFilterError: more than ``MAX_JOB_IDS_FILTER`` distinct ids, or any
+            id not in canonical UUID form. ``.payload`` is a 400-ready dict.
+    """
+    if ids_param is None:
+        return None
+    # De-dupe up front: a repeated id must not count toward the cap or be
+    # looked up twice. dict.fromkeys keeps first-seen order.
+    ids_filter = list(dict.fromkeys(i.strip() for i in ids_param.split(',') if i.strip()))
+    if len(ids_filter) > MAX_JOB_IDS_FILTER:
+        raise JobIdsFilterError(
+            {"error": f"ids must contain at most {MAX_JOB_IDS_FILTER} values"}
+        )
+    invalid_ids = []
+    for jid in ids_filter:
+        try:
+            validate_job_id(jid)
+        except (ValueError, AttributeError):
+            invalid_ids.append(jid)
+    if invalid_ids:
+        raise JobIdsFilterError(
+            {"error": "ids contains invalid id(s)", "invalid_ids": invalid_ids}
+        )
+    return ids_filter
+
+
 # Media types that can be previewed in the frontend
 PREVIEWABLE_MEDIA_TYPES = frozenset({'images', 'video', 'audio', '3d', 'text'})
 
@@ -362,6 +418,7 @@ def get_all_jobs(
     history: dict,
     status_filter: Optional[list[str]] = None,
     workflow_id: Optional[str] = None,
+    ids: Optional[list[str]] = None,
     sort_by: str = "created_at",
     sort_order: str = "desc",
     limit: Optional[int] = None,
@@ -376,6 +433,8 @@ def get_all_jobs(
         history: Dict of history items keyed by prompt_id
         status_filter: List of statuses to include (from JobStatus.ALL)
         workflow_id: Filter by workflow ID
+        ids: Restrict the result to these job ids. None = no filter; a present
+            list (including empty) restricts to that set, so [] = zero matches
         sort_by: Field to sort by ('created_at', 'execution_duration')
         sort_order: 'asc' or 'desc'
         limit: Maximum number of items to return
@@ -389,6 +448,10 @@ def get_all_jobs(
     if status_filter is None:
         status_filter = JobStatus.ALL
 
+    # None => no id filter; a present list (including empty) restricts to that
+    # set (empty => zero matches).
+    id_set = set(ids) if ids is not None else None
+
     if JobStatus.IN_PROGRESS in status_filter:
         for item in running:
             jobs.append(normalize_queue_item(item, JobStatus.IN_PROGRESS))
@@ -400,14 +463,30 @@ def get_all_jobs(
     history_statuses = {JobStatus.COMPLETED, JobStatus.FAILED, JobStatus.CANCELLED}
     requested_history_statuses = history_statuses & set(status_filter)
     if requested_history_statuses:
-        for prompt_id, history_item in history.items():
-            job = normalize_history_item(prompt_id, history_item)
-            if job.get('status') in requested_history_statuses:
-                jobs.append(job)
+        if id_set is not None:
+            # Batch-poll fast path: history is keyed by id, so look up only the
+            # requested ids instead of normalizing the whole (unbounded) history.
+            for prompt_id in id_set:
+                history_item = history.get(prompt_id)
+                if history_item is None:
+                    continue
+                job = normalize_history_item(prompt_id, history_item)
+                if job.get('status') in requested_history_statuses:
+                    jobs.append(job)
+        else:
+            for prompt_id, history_item in history.items():
+                job = normalize_history_item(prompt_id, history_item)
+                if job.get('status') in requested_history_statuses:
+                    jobs.append(job)
 
     if workflow_id:
         jobs = [j for j in jobs if j.get('workflow_id') == workflow_id]
 
+    if id_set is not None:
+        # `.get('id')` (not `j['id']`): prune_dict can drop a None id, and a
+        # job missing its id should degrade to "no match", not raise KeyError.
+        jobs = [j for j in jobs if j.get('id') in id_set]
+
     jobs = apply_sorting(jobs, sort_by, sort_order)
 
     total_count = len(jobs)

comfy_extras/nodes_cond.py

@@ -8,7 +8,8 @@ class CLIPTextEncodeControlnet(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="CLIPTextEncodeControlnet",
-            category="experimental/conditioning",
+            display_name="CLIP Text Encode (Controlnet)",
+            category="model/conditioning",
             inputs=[
                 io.Clip.Input("clip"),
                 io.Conditioning.Input("conditioning"),
@@ -35,11 +36,12 @@ class T5TokenizerOptions(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="T5TokenizerOptions",
-            category="experimental/conditioning",
+            display_name="T5 Tokenizer Options",
+            category="model/conditioning",
             inputs=[
                 io.Clip.Input("clip"),
-                io.Int.Input("min_padding", default=0, min=0, max=10000, step=1, advanced=True),
-                io.Int.Input("min_length", default=0, min=0, max=10000, step=1, advanced=True),
+                io.Int.Input("min_padding", default=0, min=0, max=10000, step=1),
+                io.Int.Input("min_length", default=0, min=0, max=10000, step=1),
             ],
             outputs=[io.Clip.Output()],
             is_experimental=True,

comfy_extras/nodes_custom_sampler.py

@@ -1070,7 +1070,7 @@ class AddNoise(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="AddNoise",
-            category="experimental/custom_sampling/noise",
+            category="model/sampling/noise",
             is_experimental=True,
             inputs=[
                 io.Model.Input("model"),
@@ -1120,7 +1120,7 @@ class ManualSigmas(io.ComfyNode):
         return io.Schema(
             node_id="ManualSigmas",
             search_aliases=["custom noise schedule", "define sigmas"],
-            category="experimental/custom_sampling",
+            category="model/sampling/sigmas",
             is_experimental=True,
             inputs=[
                 io.String.Input("sigmas", default="1, 0.5", multiline=False)

comfy_extras/nodes_glsl.py

@@ -1,85 +1,68 @@
 import os
 import sys
 import re
+import ctypes
 import logging
-import ctypes.util
-import importlib.util
 from typing import TypedDict
 
 import numpy as np
 import torch
 
 import nodes
+import comfy_angle
 from comfy_api.latest import ComfyExtension, io, ui
 from typing_extensions import override
-from utils.install_util import get_missing_requirements_message
 
 logger = logging.getLogger(__name__)
 
 
-def _check_opengl_availability():
-    """Early check for OpenGL availability. Raises RuntimeError if unlikely to work."""
-    logger.debug("_check_opengl_availability: starting")
-    missing = []
+def _preload_angle():
+    egl_path = comfy_angle.get_egl_path()
+    gles_path = comfy_angle.get_glesv2_path()
 
-    # Check Python packages (using find_spec to avoid importing)
-    logger.debug("_check_opengl_availability: checking for glfw package")
-    if importlib.util.find_spec("glfw") is None:
-        missing.append("glfw")
+    if sys.platform == "win32":
+        angle_dir = comfy_angle.get_lib_dir()
+        os.add_dll_directory(angle_dir)
+        os.environ["PATH"] = angle_dir + os.pathsep + os.environ.get("PATH", "")
 
-    logger.debug("_check_opengl_availability: checking for OpenGL package")
-    if importlib.util.find_spec("OpenGL") is None:
-        missing.append("PyOpenGL")
-
-    if missing:
-        raise RuntimeError(
-            f"OpenGL dependencies not available.\n{get_missing_requirements_message()}\n"
-        )
-
-    # On Linux without display, check if headless backends are available
-    logger.debug(f"_check_opengl_availability: platform={sys.platform}")
-    if sys.platform.startswith("linux"):
-        has_display = os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY")
-        logger.debug(f"_check_opengl_availability: has_display={bool(has_display)}")
-        if not has_display:
-            # Check for EGL or OSMesa libraries
-            logger.debug("_check_opengl_availability: checking for EGL library")
-            has_egl = ctypes.util.find_library("EGL")
-            logger.debug("_check_opengl_availability: checking for OSMesa library")
-            has_osmesa = ctypes.util.find_library("OSMesa")
-
-            # Error disabled for CI as it fails this check
-            # if not has_egl and not has_osmesa:
-            #     raise RuntimeError(
-            #         "GLSL Shader node: No display and no headless backend (EGL/OSMesa) found.\n"
-            #         "See error below for installation instructions."
-            #     )
-            logger.debug(f"Headless mode: EGL={'yes' if has_egl else 'no'}, OSMesa={'yes' if has_osmesa else 'no'}")
-
-    logger.debug("_check_opengl_availability: completed")
+    mode = 0 if sys.platform == "win32" else ctypes.RTLD_GLOBAL
+    ctypes.CDLL(str(egl_path), mode=mode)
+    ctypes.CDLL(str(gles_path), mode=mode)
 
 
-# Run early check at import time
-logger.debug("nodes_glsl: running _check_opengl_availability at import time")
-_check_opengl_availability()
-
-# OpenGL modules - initialized lazily when context is created
-gl = None
-glfw = None
-EGL = None
+# Pre-load ANGLE *before* any PyOpenGL import so that the EGL platform
+# plugin picks up ANGLE's libEGL / libGLESv2 instead of system libs.
+_preload_angle()
+os.environ.setdefault("PYOPENGL_PLATFORM", "egl")
 
 
-def _import_opengl():
-    """Import OpenGL module. Called after context is created."""
-    global gl
-    if gl is None:
-        logger.debug("_import_opengl: importing OpenGL.GL")
-        import OpenGL.GL as _gl
-        gl = _gl
-        logger.debug("_import_opengl: import completed")
-    return gl
+import OpenGL
+OpenGL.USE_ACCELERATE = False
 
 
+def _patch_find_library():
+    """PyOpenGL's EGL platform looks for 'EGL' and 'GLESv2' by short name
+    via ctypes.util.find_library, but ANGLE ships as 'libEGL' and
+    'libGLESv2'.  Patch find_library to return the full ANGLE paths so
+    PyOpenGL loads the same libraries we pre-loaded."""
+    if sys.platform == "linux":
+        return
+    import ctypes.util
+    _orig = ctypes.util.find_library
+    def _patched(name):
+        if name == 'EGL':
+            return comfy_angle.get_egl_path()
+        if name == 'GLESv2':
+            return comfy_angle.get_glesv2_path()
+        return _orig(name)
+    ctypes.util.find_library = _patched
+
+
+_patch_find_library()
+
+from OpenGL import EGL
+from OpenGL import GLES3 as gl
+
 class SizeModeInput(TypedDict):
     size_mode: str
     width: int
@@ -102,7 +85,7 @@ MAX_OUTPUTS = 4     # fragColor0-3 (MRT)
 # (-1,-1)---(3,-1)
 #
 # v_texCoord is computed from clip space: * 0.5 + 0.5 maps (-1,1) -> (0,1)
-VERTEX_SHADER = """#version 330 core
+VERTEX_SHADER = """#version 300 es
 out vec2 v_texCoord;
 void main() {
     vec2 verts[3] = vec2[](vec2(-1, -1), vec2(3, -1), vec2(-1, 3));
@@ -126,14 +109,99 @@ void main() {
 """
 
 
-def _convert_es_to_desktop(source: str) -> str:
-    """Convert GLSL ES (WebGL) shader source to desktop GLSL 330 core."""
-    # Remove any existing #version directive
-    source = re.sub(r"#version\s+\d+(\s+es)?\s*\n?", "", source, flags=re.IGNORECASE)
-    # Remove precision qualifiers (not needed in desktop GLSL)
-    source = re.sub(r"precision\s+(lowp|mediump|highp)\s+\w+\s*;\s*\n?", "", source)
-    # Prepend desktop GLSL version
-    return "#version 330 core\n" + source
+
+def _egl_attribs(*values):
+    """Build an EGL_NONE-terminated EGLint attribute array."""
+    vals = list(values) + [EGL.EGL_NONE]
+    return (ctypes.c_int32 * len(vals))(*vals)
+
+
+# EGL platform extension constants
+EGL_PLATFORM_ANGLE_ANGLE = 0x3202
+EGL_PLATFORM_ANGLE_TYPE_ANGLE = 0x3203
+EGL_PLATFORM_ANGLE_TYPE_VULKAN_ANGLE = 0x3450
+EGL_MESA_PLATFORM_SURFACELESS = 0x31DD
+
+
+_eglGetPlatformDisplayEXT = None
+
+def _get_egl_platform_display_ext(platform, native_display, attribs):
+    """Call eglGetPlatformDisplayEXT via ctypes (extension, not in PyOpenGL)."""
+    global _eglGetPlatformDisplayEXT
+    if _eglGetPlatformDisplayEXT is None:
+        from OpenGL import platform as _plat
+        egl_lib = _plat.PLATFORM.EGL
+        _get_proc = egl_lib.eglGetProcAddress
+        _get_proc.restype = ctypes.c_void_p
+        _get_proc.argtypes = [ctypes.c_char_p]
+        ptr = _get_proc(b"eglGetPlatformDisplayEXT")
+        if not ptr:
+            return None
+        func_type = ctypes.CFUNCTYPE(ctypes.c_void_p, ctypes.c_uint32, ctypes.c_void_p, ctypes.c_void_p)
+        _eglGetPlatformDisplayEXT = func_type(ptr)
+
+    raw = _eglGetPlatformDisplayEXT(platform, native_display, attribs)
+    if not raw:
+        return None
+    return ctypes.cast(raw, EGL.EGLDisplay)
+
+
+def _get_egl_display():
+    """Get an EGL display, trying the default first then ANGLE's Vulkan
+    platform for headless environments without a display server."""
+    failures = []
+
+    # Try the default display first (works when X11/Wayland is available)
+    display = EGL.eglGetDisplay(EGL.EGL_DEFAULT_DISPLAY)
+    if display:
+        major, minor = ctypes.c_int32(0), ctypes.c_int32(0)
+        try:
+            if EGL.eglInitialize(display, ctypes.byref(major), ctypes.byref(minor)):
+                return display, major.value, minor.value
+        except Exception as e:
+            failures.append(f"default: {e}")
+
+    logger.info("Default EGL display unavailable, trying headless fallbacks")
+
+    # Headless fallback strategies, tried in order:
+    headless_strategies = [
+        ("surfaceless", EGL_MESA_PLATFORM_SURFACELESS, None, None),
+        ("ANGLE Vulkan", EGL_PLATFORM_ANGLE_ANGLE, None,
+         _egl_attribs(EGL_PLATFORM_ANGLE_TYPE_ANGLE, EGL_PLATFORM_ANGLE_TYPE_VULKAN_ANGLE)),
+    ]
+
+    for name, platform, native_display, attribs in headless_strategies:
+        display = _get_egl_platform_display_ext(platform, native_display, attribs)
+        if not display:
+            failures.append(f"{name}: eglGetPlatformDisplayEXT returned no display")
+            continue
+        major, minor = ctypes.c_int32(0), ctypes.c_int32(0)
+        try:
+            if EGL.eglInitialize(display, ctypes.byref(major), ctypes.byref(minor)):
+                logger.info(f"Using EGL {name} platform (headless)")
+                return display, major.value, minor.value
+            failures.append(f"{name}: eglInitialize returned false")
+        except Exception as e:
+            failures.append(f"{name}: {e}")
+            continue
+
+    details = "\n".join(f"  - {f}" for f in failures)
+    raise RuntimeError(
+        "Failed to initialize EGL display.\n"
+        "No display server and no headless EGL platform available.\n"
+        f"Tried:\n{details}\n"
+        "Ensure GPU drivers are installed or set DISPLAY for a virtual framebuffer."
+    )
+
+
+def _gl_str(name):
+    """Get an OpenGL string parameter."""
+    v = gl.glGetString(name)
+    if not v:
+        return "Unknown"
+    if isinstance(v, bytes):
+        return v.decode(errors="replace")
+    return ctypes.string_at(v).decode(errors="replace")
 
 
 def _detect_output_count(source: str) -> int:
@@ -159,163 +227,8 @@ def _detect_pass_count(source: str) -> int:
     return 1
 
 
-def _init_glfw():
-    """Initialize GLFW. Returns (window, glfw_module). Raises RuntimeError on failure."""
-    logger.debug("_init_glfw: starting")
-    # On macOS, glfw.init() must be called from main thread or it hangs forever
-    if sys.platform == "darwin":
-        logger.debug("_init_glfw: skipping on macOS")
-        raise RuntimeError("GLFW backend not supported on macOS")
-
-    logger.debug("_init_glfw: importing glfw module")
-    import glfw as _glfw
-
-    logger.debug("_init_glfw: calling glfw.init()")
-    if not _glfw.init():
-        raise RuntimeError("glfw.init() failed")
-
-    try:
-        logger.debug("_init_glfw: setting window hints")
-        _glfw.window_hint(_glfw.VISIBLE, _glfw.FALSE)
-        _glfw.window_hint(_glfw.CONTEXT_VERSION_MAJOR, 3)
-        _glfw.window_hint(_glfw.CONTEXT_VERSION_MINOR, 3)
-        _glfw.window_hint(_glfw.OPENGL_PROFILE, _glfw.OPENGL_CORE_PROFILE)
-
-        logger.debug("_init_glfw: calling create_window()")
-        window = _glfw.create_window(64, 64, "ComfyUI GLSL", None, None)
-        if not window:
-            raise RuntimeError("glfw.create_window() failed")
-
-        logger.debug("_init_glfw: calling make_context_current()")
-        _glfw.make_context_current(window)
-        logger.debug("_init_glfw: completed successfully")
-        return window, _glfw
-    except Exception:
-        logger.debug("_init_glfw: failed, terminating glfw")
-        _glfw.terminate()
-        raise
-
-
-def _init_egl():
-    """Initialize EGL for headless rendering. Returns (display, context, surface, EGL_module). Raises RuntimeError on failure."""
-    logger.debug("_init_egl: starting")
-    from OpenGL import EGL as _EGL
-    from OpenGL.EGL import (
-        eglGetDisplay, eglInitialize, eglChooseConfig, eglCreateContext,
-        eglMakeCurrent, eglCreatePbufferSurface, eglBindAPI,
-        eglTerminate, eglDestroyContext, eglDestroySurface,
-        EGL_DEFAULT_DISPLAY, EGL_NO_CONTEXT, EGL_NONE,
-        EGL_SURFACE_TYPE, EGL_PBUFFER_BIT, EGL_RENDERABLE_TYPE, EGL_OPENGL_BIT,
-        EGL_RED_SIZE, EGL_GREEN_SIZE, EGL_BLUE_SIZE, EGL_ALPHA_SIZE, EGL_DEPTH_SIZE,
-        EGL_WIDTH, EGL_HEIGHT, EGL_OPENGL_API,
-    )
-    logger.debug("_init_egl: imports completed")
-
-    display = None
-    context = None
-    surface = None
-
-    try:
-        logger.debug("_init_egl: calling eglGetDisplay()")
-        display = eglGetDisplay(EGL_DEFAULT_DISPLAY)
-        if display == _EGL.EGL_NO_DISPLAY:
-            raise RuntimeError("eglGetDisplay() failed")
-
-        logger.debug("_init_egl: calling eglInitialize()")
-        major, minor = _EGL.EGLint(), _EGL.EGLint()
-        if not eglInitialize(display, major, minor):
-            display = None  # Not initialized, don't terminate
-            raise RuntimeError("eglInitialize() failed")
-        logger.debug(f"_init_egl: EGL version {major.value}.{minor.value}")
-
-        config_attribs = [
-            EGL_SURFACE_TYPE, EGL_PBUFFER_BIT,
-            EGL_RENDERABLE_TYPE, EGL_OPENGL_BIT,
-            EGL_RED_SIZE, 8, EGL_GREEN_SIZE, 8, EGL_BLUE_SIZE, 8, EGL_ALPHA_SIZE, 8,
-            EGL_DEPTH_SIZE, 0, EGL_NONE
-        ]
-        configs = (_EGL.EGLConfig * 1)()
-        num_configs = _EGL.EGLint()
-        if not eglChooseConfig(display, config_attribs, configs, 1, num_configs) or num_configs.value == 0:
-            raise RuntimeError("eglChooseConfig() failed")
-        config = configs[0]
-        logger.debug(f"_init_egl: config chosen, num_configs={num_configs.value}")
-
-        if not eglBindAPI(EGL_OPENGL_API):
-            raise RuntimeError("eglBindAPI() failed")
-
-        logger.debug("_init_egl: calling eglCreateContext()")
-        context_attribs = [
-            _EGL.EGL_CONTEXT_MAJOR_VERSION, 3,
-            _EGL.EGL_CONTEXT_MINOR_VERSION, 3,
-            _EGL.EGL_CONTEXT_OPENGL_PROFILE_MASK, _EGL.EGL_CONTEXT_OPENGL_CORE_PROFILE_BIT,
-            EGL_NONE
-        ]
-        context = eglCreateContext(display, config, EGL_NO_CONTEXT, context_attribs)
-        if context == EGL_NO_CONTEXT:
-            raise RuntimeError("eglCreateContext() failed")
-
-        logger.debug("_init_egl: calling eglCreatePbufferSurface()")
-        pbuffer_attribs = [EGL_WIDTH, 64, EGL_HEIGHT, 64, EGL_NONE]
-        surface = eglCreatePbufferSurface(display, config, pbuffer_attribs)
-        if surface == _EGL.EGL_NO_SURFACE:
-            raise RuntimeError("eglCreatePbufferSurface() failed")
-
-        logger.debug("_init_egl: calling eglMakeCurrent()")
-        if not eglMakeCurrent(display, surface, surface, context):
-            raise RuntimeError("eglMakeCurrent() failed")
-
-        logger.debug("_init_egl: completed successfully")
-        return display, context, surface, _EGL
-
-    except Exception:
-        logger.debug("_init_egl: failed, cleaning up")
-        # Clean up any resources on failure
-        if surface is not None:
-            eglDestroySurface(display, surface)
-        if context is not None:
-            eglDestroyContext(display, context)
-        if display is not None:
-            eglTerminate(display)
-        raise
-
-
-def _init_osmesa():
-    """Initialize OSMesa for software rendering. Returns (context, buffer). Raises RuntimeError on failure."""
-    import ctypes
-
-    logger.debug("_init_osmesa: starting")
-    os.environ["PYOPENGL_PLATFORM"] = "osmesa"
-
-    logger.debug("_init_osmesa: importing OpenGL.osmesa")
-    from OpenGL import GL as _gl
-    from OpenGL.osmesa import (
-        OSMesaCreateContextExt, OSMesaMakeCurrent, OSMesaDestroyContext,
-        OSMESA_RGBA,
-    )
-    logger.debug("_init_osmesa: imports completed")
-
-    ctx = OSMesaCreateContextExt(OSMESA_RGBA, 24, 0, 0, None)
-    if not ctx:
-        raise RuntimeError("OSMesaCreateContextExt() failed")
-
-    width, height = 64, 64
-    buffer = (ctypes.c_ubyte * (width * height * 4))()
-
-    logger.debug("_init_osmesa: calling OSMesaMakeCurrent()")
-    if not OSMesaMakeCurrent(ctx, buffer, _gl.GL_UNSIGNED_BYTE, width, height):
-        OSMesaDestroyContext(ctx)
-        raise RuntimeError("OSMesaMakeCurrent() failed")
-
-    logger.debug("_init_osmesa: completed successfully")
-    return ctx, buffer
-
-
 class GLContext:
-    """Manages OpenGL context and resources for shader execution.
-
-    Tries backends in order: GLFW (desktop) → EGL (headless GPU) → OSMesa (software).
-    """
+    """Manages an OpenGL ES 3.0 context via EGL/ANGLE (singleton)."""
 
     _instance = None
     _initialized = False
@@ -327,131 +240,105 @@ class GLContext:
 
     def __init__(self):
         if GLContext._initialized:
-            logger.debug("GLContext.__init__: already initialized, skipping")
             return
 
-        logger.debug("GLContext.__init__: starting initialization")
-
-        global glfw, EGL
-
         import time
         start = time.perf_counter()
 
-        self._backend = None
-        self._window = None
-        self._egl_display = None
-        self._egl_context = None
-        self._egl_surface = None
-        self._osmesa_ctx = None
-        self._osmesa_buffer = None
+        self._display = None
+        self._surface = None
+        self._context = None
         self._vao = None
 
-        # Try backends in order: GLFW → EGL → OSMesa
-        errors = []
-
-        logger.debug("GLContext.__init__: trying GLFW backend")
         try:
-            self._window, glfw = _init_glfw()
-            self._backend = "glfw"
-            logger.debug("GLContext.__init__: GLFW backend succeeded")
-        except Exception as e:
-            logger.debug(f"GLContext.__init__: GLFW backend failed: {e}")
-            errors.append(("GLFW", e))
+            self._display, self._egl_major, self._egl_minor = _get_egl_display()
 
-        if self._backend is None:
-            logger.debug("GLContext.__init__: trying EGL backend")
-            try:
-                self._egl_display, self._egl_context, self._egl_surface, EGL = _init_egl()
-                self._backend = "egl"
-                logger.debug("GLContext.__init__: EGL backend succeeded")
-            except Exception as e:
-                logger.debug(f"GLContext.__init__: EGL backend failed: {e}")
-                errors.append(("EGL", e))
+            if not EGL.eglBindAPI(EGL.EGL_OPENGL_ES_API):
+                raise RuntimeError("eglBindAPI(EGL_OPENGL_ES_API) failed")
 
-        if self._backend is None:
-            logger.debug("GLContext.__init__: trying OSMesa backend")
-            try:
-                self._osmesa_ctx, self._osmesa_buffer = _init_osmesa()
-                self._backend = "osmesa"
-                logger.debug("GLContext.__init__: OSMesa backend succeeded")
-            except Exception as e:
-                logger.debug(f"GLContext.__init__: OSMesa backend failed: {e}")
-                errors.append(("OSMesa", e))
+            config = EGL.EGLConfig()
+            n_configs = ctypes.c_int32(0)
+            if not EGL.eglChooseConfig(
+                self._display,
+                _egl_attribs(
+                    EGL.EGL_RENDERABLE_TYPE, EGL.EGL_OPENGL_ES3_BIT,
+                    EGL.EGL_SURFACE_TYPE, EGL.EGL_PBUFFER_BIT,
+                    EGL.EGL_RED_SIZE, 8, EGL.EGL_GREEN_SIZE, 8,
+                    EGL.EGL_BLUE_SIZE, 8, EGL.EGL_ALPHA_SIZE, 8,
+                ),
+                ctypes.byref(config), 1, ctypes.byref(n_configs),
+            ) or n_configs.value == 0:
+                raise RuntimeError("eglChooseConfig() failed")
 
-        if self._backend is None:
-            if sys.platform == "win32":
-                platform_help = (
-                    "Windows: Ensure GPU drivers are installed and display is available.\n"
-                    "         CPU-only/headless mode is not supported on Windows."
-                )
-            elif sys.platform == "darwin":
-                platform_help = (
-                    "macOS: GLFW is not supported.\n"
-                    "  Install OSMesa via Homebrew: brew install mesa\n"
-                    "  Then: pip install PyOpenGL PyOpenGL-accelerate"
-                )
-            else:
-                platform_help = (
-                    "Linux: Install one of these backends:\n"
-                    "  Desktop:           sudo apt install libgl1-mesa-glx libglfw3\n"
-                    "  Headless with GPU: sudo apt install libegl1-mesa libgl1-mesa-dri\n"
-                    "  Headless (CPU):    sudo apt install libosmesa6"
-                )
-
-            error_details = "\n".join(f"  {name}: {err}" for name, err in errors)
-            raise RuntimeError(
-                f"Failed to create OpenGL context.\n\n"
-                f"Backend errors:\n{error_details}\n\n"
-                f"{platform_help}"
+            self._surface = EGL.eglCreatePbufferSurface(
+                self._display, config,
+                _egl_attribs(EGL.EGL_WIDTH, 64, EGL.EGL_HEIGHT, 64),
             )
+            if not self._surface:
+                raise RuntimeError("eglCreatePbufferSurface() failed")
 
-        # Now import OpenGL.GL (after context is current)
-        logger.debug("GLContext.__init__: importing OpenGL.GL")
-        _import_opengl()
+            self._context = EGL.eglCreateContext(
+                self._display, config, EGL.EGL_NO_CONTEXT,
+                _egl_attribs(EGL.EGL_CONTEXT_CLIENT_VERSION, 3),
+            )
+            if not self._context:
+                raise RuntimeError("eglCreateContext() failed")
 
-        # Create VAO (required for core profile, but OSMesa may use compat profile)
-        logger.debug("GLContext.__init__: creating VAO")
-        try:
-            vao = gl.glGenVertexArrays(1)
-            gl.glBindVertexArray(vao)
-            self._vao = vao  # Only store after successful bind
-            logger.debug("GLContext.__init__: VAO created successfully")
-        except Exception as e:
-            logger.debug(f"GLContext.__init__: VAO creation failed (may be expected for OSMesa): {e}")
-            # OSMesa with older Mesa may not support VAOs
-            # Clean up if we created but couldn't bind
-            if vao:
-                try:
-                    gl.glDeleteVertexArrays(1, [vao])
-                except Exception:
-                    pass
+            if not EGL.eglMakeCurrent(self._display, self._surface, self._surface, self._context):
+                raise RuntimeError("eglMakeCurrent() failed")
+
+            self._vao = gl.glGenVertexArrays(1)
+            gl.glBindVertexArray(self._vao)
+
+        except Exception:
+            self._cleanup()
+            raise
 
         elapsed = (time.perf_counter() - start) * 1000
 
-        # Log device info
-        renderer = gl.glGetString(gl.GL_RENDERER)
-        vendor = gl.glGetString(gl.GL_VENDOR)
-        version = gl.glGetString(gl.GL_VERSION)
-        renderer = renderer.decode() if renderer else "Unknown"
-        vendor = vendor.decode() if vendor else "Unknown"
-        version = version.decode() if version else "Unknown"
+        renderer = _gl_str(gl.GL_RENDERER)
+        vendor = _gl_str(gl.GL_VENDOR)
+        version = _gl_str(gl.GL_VERSION)
 
         GLContext._initialized = True
-        logger.info(f"GLSL context initialized in {elapsed:.1f}ms ({self._backend}) - {renderer} ({vendor}), GL {version}")
+        logger.info(f"GLSL context initialized in {elapsed:.1f}ms - EGL {self._egl_major}.{self._egl_minor}, {renderer} ({vendor}), GL {version}")
 
     def make_current(self):
-        if self._backend == "glfw":
-            glfw.make_context_current(self._window)
-        elif self._backend == "egl":
-            from OpenGL.EGL import eglMakeCurrent
-            eglMakeCurrent(self._egl_display, self._egl_surface, self._egl_surface, self._egl_context)
-        elif self._backend == "osmesa":
-            from OpenGL.osmesa import OSMesaMakeCurrent
-            OSMesaMakeCurrent(self._osmesa_ctx, self._osmesa_buffer, gl.GL_UNSIGNED_BYTE, 64, 64)
-
+        if not EGL.eglMakeCurrent(self._display, self._surface, self._surface, self._context):
+            err = EGL.eglGetError()
+            raise RuntimeError(f"eglMakeCurrent() failed (EGL error: 0x{err:04X})")
         if self._vao is not None:
             gl.glBindVertexArray(self._vao)
 
+    def _cleanup(self):
+        if not self._display:
+            return
+        try:
+            if self._vao is not None:
+                gl.glDeleteVertexArrays(1, [self._vao])
+                self._vao = None
+        except Exception:
+            pass
+        try:
+            EGL.eglMakeCurrent(self._display, EGL.EGL_NO_SURFACE, EGL.EGL_NO_SURFACE, EGL.EGL_NO_CONTEXT)
+        except Exception:
+            pass
+        try:
+            if self._context:
+                EGL.eglDestroyContext(self._display, self._context)
+        except Exception:
+            pass
+        try:
+            if self._surface:
+                EGL.eglDestroySurface(self._display, self._surface)
+        except Exception:
+            pass
+        try:
+            EGL.eglTerminate(self._display)
+        except Exception:
+            pass
+        self._display = None
+
 
 def _compile_shader(source: str, shader_type: int) -> int:
     """Compile a shader and return its ID."""
@@ -459,8 +346,10 @@ def _compile_shader(source: str, shader_type: int) -> int:
     gl.glShaderSource(shader, source)
     gl.glCompileShader(shader)
 
-    if gl.glGetShaderiv(shader, gl.GL_COMPILE_STATUS) != gl.GL_TRUE:
-        error = gl.glGetShaderInfoLog(shader).decode()
+    if not gl.glGetShaderiv(shader, gl.GL_COMPILE_STATUS):
+        error = gl.glGetShaderInfoLog(shader)
+        if isinstance(error, bytes):
+            error = error.decode(errors="replace")
         gl.glDeleteShader(shader)
         raise RuntimeError(f"Shader compilation failed:\n{error}")
 
@@ -484,8 +373,10 @@ def _create_program(vertex_source: str, fragment_source: str) -> int:
     gl.glDeleteShader(vertex_shader)
     gl.glDeleteShader(fragment_shader)
 
-    if gl.glGetProgramiv(program, gl.GL_LINK_STATUS) != gl.GL_TRUE:
-        error = gl.glGetProgramInfoLog(program).decode()
+    if not gl.glGetProgramiv(program, gl.GL_LINK_STATUS):
+        error = gl.glGetProgramInfoLog(program)
+        if isinstance(error, bytes):
+            error = error.decode(errors="replace")
         gl.glDeleteProgram(program)
         raise RuntimeError(f"Program linking failed:\n{error}")
 
@@ -530,9 +421,6 @@ def _render_shader_batch(
     ctx = GLContext()
     ctx.make_current()
 
-    # Convert from GLSL ES to desktop GLSL 330
-    fragment_source = _convert_es_to_desktop(fragment_code)
-
     # Detect how many outputs the shader actually uses
     num_outputs = _detect_output_count(fragment_code)
 
@@ -558,9 +446,9 @@ def _render_shader_batch(
     try:
         # Compile shaders (once for all batches)
         try:
-            program = _create_program(VERTEX_SHADER, fragment_source)
+            program = _create_program(VERTEX_SHADER, fragment_code)
         except RuntimeError:
-            logger.error(f"Fragment shader:\n{fragment_source}")
+            logger.error(f"Fragment shader:\n{fragment_code}")
             raise
 
         gl.glUseProgram(program)
@@ -723,13 +611,13 @@ def _render_shader_batch(
                     gl.glDrawArrays(gl.GL_TRIANGLES, 0, 3)
 
             # Read back outputs for this batch
-            # (glGetTexImage is synchronous, implicitly waits for rendering)
+            gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, fbo)
             batch_outputs = []
-            for tex in output_textures:
-                gl.glBindTexture(gl.GL_TEXTURE_2D, tex)
-                data = gl.glGetTexImage(gl.GL_TEXTURE_2D, 0, gl.GL_RGBA, gl.GL_FLOAT)
-                img = np.frombuffer(data, dtype=np.float32).reshape(height, width, 4)
-                batch_outputs.append(img[::-1, :, :].copy())
+            for i in range(num_outputs):
+                gl.glReadBuffer(gl.GL_COLOR_ATTACHMENT0 + i)
+                buf = np.empty((height, width, 4), dtype=np.float32)
+                gl.glReadPixels(0, 0, width, height, gl.GL_RGBA, gl.GL_FLOAT, buf)
+                batch_outputs.append(buf[::-1, :, :].copy())
 
             # Pad with black images for unused outputs
             black_img = np.zeros((height, width, 4), dtype=np.float32)
@@ -750,18 +638,18 @@ def _render_shader_batch(
         gl.glBindFramebuffer(gl.GL_FRAMEBUFFER, 0)
         gl.glUseProgram(0)
 
-        for tex in input_textures:
-            gl.glDeleteTextures(int(tex))
-        for tex in curve_textures:
-            gl.glDeleteTextures(int(tex))
-        for tex in output_textures:
-            gl.glDeleteTextures(int(tex))
-        for tex in ping_pong_textures:
-            gl.glDeleteTextures(int(tex))
+        if input_textures:
+            gl.glDeleteTextures(len(input_textures), input_textures)
+        if curve_textures:
+            gl.glDeleteTextures(len(curve_textures), curve_textures)
+        if output_textures:
+            gl.glDeleteTextures(len(output_textures), output_textures)
+        if ping_pong_textures:
+            gl.glDeleteTextures(len(ping_pong_textures), ping_pong_textures)
         if fbo is not None:
             gl.glDeleteFramebuffers(1, [fbo])
-        for pp_fbo in ping_pong_fbos:
-            gl.glDeleteFramebuffers(1, [pp_fbo])
+        if ping_pong_fbos:
+            gl.glDeleteFramebuffers(len(ping_pong_fbos), ping_pong_fbos)
         if program is not None:
             gl.glDeleteProgram(program)
 

comfy_extras/nodes_photomaker.py

@@ -123,7 +123,8 @@ class PhotoMakerLoader(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="PhotoMakerLoader",
-            category="experimental/photomaker",
+            display_name="Load PhotoMaker Model",
+            category="model/loaders",
             inputs=[
                 io.Combo.Input("photomaker_model_name", options=folder_paths.get_filename_list("photomaker")),
             ],
@@ -149,7 +150,8 @@ class PhotoMakerEncode(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="PhotoMakerEncode",
-            category="experimental/photomaker",
+            display_name="PhotoMaker Encode",
+            category="model/conditioning/photomaker",
             inputs=[
                 io.Photomaker.Input("photomaker"),
                 io.Image.Input("image"),

comfy_extras/nodes_stable_cascade.py

@@ -119,7 +119,7 @@ class StableCascade_SuperResolutionControlnet(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="StableCascade_SuperResolutionControlnet",
-            category="experimental/stable_cascade",
+            category="experimental/stable cascade",
             is_experimental=True,
             inputs=[
                 io.Image.Input("image"),

comfy_extras/nodes_triposplat.py

@@ -143,7 +143,7 @@ class VAEDecodeTripoSplat(IO.ComfyNode):
         return IO.Schema(
             node_id="VAEDecodeTripoSplat",
             display_name="TripoSplat Decode",
-            category="3d/latent",
+            category="model/latent/triposplat",
             description="Decode the sampled TripoSplat latent into a 3D gaussian splat. "
                         "Modify the number of gaussians to vary the density.",
             inputs=[
@@ -188,7 +188,7 @@ class TripoSplatSamplingPreview(IO.ComfyNode):
         return IO.Schema(
             node_id="TripoSplatSamplingPreview",
             display_name="TripoSplat Sampling Preview",
-            category="3d/latent",
+            category="model/latent/triposplat",
             description="Patch the TripoSplat model for the standard Ksampler node to show a live decoded "
                         "gaussian splat preview at each step.",
             inputs=[

comfyui_version.py

@@ -1,3 +1,3 @@
 # This file is automatically generated by the build process when version is
 # updated in pyproject.toml.
-__version__ = "0.26.0"
+__version__ = "0.27.0"

execution.py

@@ -1113,32 +1113,6 @@ def full_type_name(klass):
         return klass.__qualname__
     return module + '.' + klass.__qualname__
 
-def node_not_executable_reason(class_def, class_type):
-    """Return a human-readable reason the node cannot be executed, or None if it's fine.
-
-    Catches a node whose declared entry point doesn't resolve to a real method
-    (e.g. a V1 ``FUNCTION = "invert"`` where the method is misspelled, or a V3 node
-    missing its ``execute`` override). Running this during validation surfaces the
-    problem before execution starts, instead of after upstream nodes have run.
-
-    Only the class is inspected; the node is never instantiated here, so a node's
-    ``__init__`` side effects cannot run (or fail) during validation.
-    """
-    try:
-        if issubclass(class_def, _ComfyNodeInternal):
-            # V3: validates that execute()/define_schema() overrides exist.
-            class_def.VALIDATE_CLASS()
-            return None
-        # V1: FUNCTION names the method to call; it must exist on the class.
-        function_name = getattr(class_def, "FUNCTION", None)
-        if function_name is None:
-            return f"'{class_type}' does not define FUNCTION"
-        if not callable(getattr(class_def, function_name, None)):
-            return f"'{class_type}' has no method '{function_name}' (declared in FUNCTION)"
-        return None
-    except Exception as ex:
-        return str(ex)
-
 async def validate_prompt(prompt_id, prompt, partial_execution_list: Union[list[str], None]):
     outputs = set()
     for x in prompt:
@@ -1174,35 +1148,6 @@ async def validate_prompt(prompt_id, prompt, partial_execution_list: Union[list[
             }
             return (False, error, [], {})
 
-        # Make sure the node is actually executable (its FUNCTION/execute entry
-        # point resolves to a real method) before we touch any schema-derived
-        # attributes below or start execution. Catches code typos up front and
-        # attributes the error to the offending node.
-        not_executable = node_not_executable_reason(class_, class_type)
-        if not_executable is not None:
-            node_title = prompt[x].get('_meta', {}).get('title', class_type)
-            error = {
-                "type": "invalid_node_definition",
-                "message": "Node is not executable",
-                "details": f"{not_executable} (Node ID '#{x}')",
-                "extra_info": {
-                    "node_id": x,
-                    "class_type": class_type,
-                    "node_title": node_title,
-                }
-            }
-            node_errors = {x: {
-                "errors": [{
-                    "type": "invalid_node_definition",
-                    "message": "Node is not executable",
-                    "details": not_executable,
-                    "extra_info": {},
-                }],
-                "dependent_outputs": [],
-                "class_type": class_type,
-            }}
-            return (False, error, [], node_errors)
-
         if hasattr(class_, 'OUTPUT_NODE') and class_.OUTPUT_NODE is True:
             if partial_execution_list is None or x in partial_execution_list:
                 outputs.add(x)

main.py

@@ -403,7 +403,7 @@ def prompt_worker(q, server_instance):
                 hook_breaker_ac10a0.restore_functions()
 
                 if not asset_seeder.is_disabled():
-                    asset_seeder.enqueue_enrich(roots=("output",), compute_hashes=True)
+                    asset_seeder.enqueue_enrich(roots=("output",), compute_hashes=args.enable_asset_hashing)
                 asset_seeder.resume()
 
 
@@ -458,7 +458,7 @@ def setup_database():
         if dependencies_available():
             init_db()
             if args.enable_assets:
-                if asset_seeder.start(roots=("models", "input", "output"), prune_first=True, compute_hashes=True):
+                if asset_seeder.start(roots=("models", "input", "output"), prune_first=True, compute_hashes=args.enable_asset_hashing):
                     logging.info("Background asset scan initiated for models, input, output")
     except Exception as e:
         if "database is locked" in str(e):

nodes.py

@@ -159,6 +159,29 @@ class ConditioningConcat:
 
         return (out, )
 
+class ConditioningMultiply:
+    SEARCH_ALIASES = ["scale conditioning", "scale prompt", "multiply conditioning", "multiply prompt"]
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {"required": {"conditioning": ("CONDITIONING", ),
+                            "multiplier": ("FLOAT", {"default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01})
+                            }}
+    RETURN_TYPES = ("CONDITIONING",)
+    FUNCTION     = "multiply"
+    CATEGORY     = "model/conditioning/transform"
+
+    def multiply(self, conditioning, multiplier):
+        c = []
+        for t in conditioning:
+            values = {}
+            pooled_output = t[1].get("pooled_output", None)
+            if pooled_output is not None:
+                values["pooled_output"] = pooled_output * multiplier
+            scaled = node_helpers.conditioning_set_values([[t[0] * multiplier, t[1]]], values)[0]
+            c.append(scaled)
+        return (c,)
+
 class ConditioningSetArea:
     SEARCH_ALIASES = ["regional prompt", "area prompt", "spatial conditioning", "localized prompt"]
 
@@ -326,7 +349,7 @@ class VAEDecodeTiled:
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "decode"
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     def decode(self, vae, samples, tile_size, overlap=64, temporal_size=64, temporal_overlap=8):
         if tile_size < overlap * 4:
@@ -373,7 +396,7 @@ class VAEEncodeTiled:
     RETURN_TYPES = ("LATENT",)
     FUNCTION = "encode"
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     def encode(self, vae, pixels, tile_size, overlap, temporal_size=64, temporal_overlap=8):
         t = vae.encode_tiled(pixels, tile_x=tile_size, tile_y=tile_size, overlap=overlap, tile_t=temporal_size, overlap_t=temporal_overlap)
@@ -491,7 +514,7 @@ class SaveLatent:
 
     OUTPUT_NODE = True
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     def save(self, samples, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None):
         full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(filename_prefix, self.output_dir)
@@ -536,7 +559,7 @@ class LoadLatent:
         files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f)) and f.endswith(".latent")]
         return {"required": {"latent": [sorted(files), ]}, }
 
-    CATEGORY = "experimental"
+    CATEGORY = "model/latent"
 
     RETURN_TYPES = ("LATENT", )
     FUNCTION = "load"
@@ -2050,6 +2073,7 @@ NODE_CLASS_MAPPINGS = {
     "ConditioningAverage": ConditioningAverage,
     "ConditioningCombine": ConditioningCombine,
     "ConditioningConcat": ConditioningConcat,
+    "ConditioningMultiply": ConditioningMultiply,
     "ConditioningSetArea": ConditioningSetArea,
     "ConditioningSetAreaPercentage": ConditioningSetAreaPercentage,
     "ConditioningSetAreaStrength": ConditioningSetAreaStrength,
@@ -2121,6 +2145,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ConditioningAverage ": "Conditioning (Average)",
     "ConditioningAverage": "Conditioning (Average)",
     "ConditioningConcat": "Conditioning (Concat)",
+    "ConditioningMultiply": "Conditioning (Multiply)",
     "ConditioningSetArea": "Conditioning (Set Area)",
     "ConditioningSetAreaPercentage": "Conditioning (Set Area with Percentage)",
     "ConditioningSetAreaStrength": "Conditioning (Set Area Strength)",
@@ -2130,6 +2155,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "GLIGENTextBoxApply": "Apply GLIGEN Text Box",
     "ConditioningZeroOut": "Conditioning Zero Out",
     # Latent
+    "LoadLatent": "Load Latent",
+    "SaveLatent": "Save Latent",
     "VAEEncodeForInpaint": "VAE Encode (for Inpainting)",
     "SetLatentNoiseMask": "Set Latent Noise Mask",
     "VAEDecode": "VAE Decode",
@@ -2164,7 +2191,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ImageSharpen": "Sharpen Image",
     "ImageScaleToTotalPixels": "Scale Image to Total Pixels",
     "GetImageSize": "Get Image Size",
-    # experimental
     "VAEDecodeTiled": "VAE Decode (Tiled)",
     "VAEEncodeTiled": "VAE Encode (Tiled)",
 }

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ComfyUI"
-version = "0.26.0"
+version = "0.27.0"
 readme = "README.md"
 license = { file = "LICENSE" }
 requires-python = ">=3.10"

requirements.txt

@@ -1,6 +1,6 @@
-comfyui-frontend-package==1.45.19
-comfyui-workflow-templates==0.10.7
-comfyui-embedded-docs==0.5.5
+comfyui-frontend-package==1.45.20
+comfyui-workflow-templates==0.11.1
+comfyui-embedded-docs==0.5.6
 torch
 torchsde
 torchvision
@@ -22,7 +22,7 @@ alembic
 SQLAlchemy>=2.0.0
 filelock
 av>=16.0.0
-comfy-kitchen==0.2.12
+comfy-kitchen==0.2.16
 comfy-aimdo==0.4.10
 requests
 simpleeval>=1.0.0
@@ -33,5 +33,5 @@ kornia>=0.7.1
 spandrel
 pydantic~=2.0
 pydantic-settings~=2.0
-PyOpenGL
-glfw
+PyOpenGL>=3.1.8
+comfy-angle

server.py

@@ -16,6 +16,8 @@ from comfy_execution.jobs import (
     cancel_job,
     CANCEL_PENDING,
     CANCEL_RUNNING,
+    parse_ids_filter,
+    JobIdsFilterError,
 )
 import uuid
 import urllib
@@ -791,6 +793,7 @@ class PromptServer():
             Query parameters:
                 status: Filter by status (comma-separated): pending, in_progress, completed, failed
                 workflow_id: Filter by workflow ID
+                ids: Filter by job id (comma-separated UUIDs, max 100)
                 sort_by: Sort field: created_at (default), execution_duration
                 sort_order: Sort direction: asc, desc (default)
                 limit: Max items to return (positive integer)
@@ -800,6 +803,7 @@ class PromptServer():
 
             status_param = query.get('status')
             workflow_id = query.get('workflow_id')
+            ids_param = query.get('ids')
             sort_by = query.get('sort_by', 'created_at').lower()
             sort_order = query.get('sort_order', 'desc').lower()
 
@@ -813,6 +817,16 @@ class PromptServer():
                         status=400
                     )
 
+            # Optional batch filter: narrow the result to a known set of job ids
+            # (e.g. polling a submitted batch in one request). Parsing/validation
+            # lives in parse_ids_filter so this handler and its tests share one
+            # implementation. Absent => no filter; present-but-empty (`?ids=`,
+            # `?ids=,,`) => zero matches, not "everything".
+            try:
+                ids_filter = parse_ids_filter(ids_param)
+            except JobIdsFilterError as e:
+                return web.json_response(e.payload, status=400)
+
             if sort_by not in {'created_at', 'execution_duration'}:
                 return web.json_response(
                     {"error": "sort_by must be 'created_at' or 'execution_duration'"},
@@ -864,6 +878,7 @@ class PromptServer():
                 running, queued, history,
                 status_filter=status_filter,
                 workflow_id=workflow_id,
+                ids=ids_filter,
                 sort_by=sort_by,
                 sort_order=sort_order,
                 limit=limit,

tests-unit/execution_test/validate_node_executable_test.py

@@ -1,137 +0,0 @@
-"""Tests for pre-execution validation that a node is actually executable.
-
-validate_prompt rejects a node whose declared entry point does not resolve to a
-real method (a V1 FUNCTION typo, or a V3 node missing its execute override) before
-any node runs, attributing the error to the offending node.
-"""
-import asyncio
-
-import nodes
-from comfy_api.latest import io
-from execution import node_not_executable_reason, validate_prompt
-
-
-class _GoodV1Node:
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {"required": {}}
-
-    RETURN_TYPES = ("IMAGE",)
-    FUNCTION = "run"
-    OUTPUT_NODE = True
-    CATEGORY = "Test"
-
-    def run(self):
-        return (None,)
-
-
-class _TypoV1Node:
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {"required": {}}
-
-    RETURN_TYPES = ("IMAGE",)
-    FUNCTION = "invert"  # method below is misspelled
-    OUTPUT_NODE = True
-    CATEGORY = "Test"
-
-    def invvert(self):
-        return (None,)
-
-
-class _SideEffectInitV1Node:
-    """Valid class-level method, but a constructor that must never run in validation."""
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {"required": {}}
-
-    RETURN_TYPES = ("IMAGE",)
-    FUNCTION = "run"
-    OUTPUT_NODE = True
-    CATEGORY = "Test"
-
-    def __init__(self):
-        raise RuntimeError("__init__ must not run during validation")
-
-    def run(self):
-        return (None,)
-
-
-def _v3_schema(node_id):
-    return io.Schema(
-        node_id=node_id,
-        display_name=node_id,
-        category="Test",
-        inputs=[],
-        outputs=[io.Image.Output()],
-        is_output_node=True,
-    )
-
-
-class _GoodV3Node(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return _v3_schema("GoodV3Node")
-
-    @classmethod
-    def execute(cls):
-        return io.NodeOutput(None)
-
-
-class _TypoV3Node(io.ComfyNode):
-    @classmethod
-    def define_schema(cls):
-        return _v3_schema("TypoV3Node")
-
-    @classmethod
-    def exicute(cls):  # typo: should be "execute"
-        return io.NodeOutput(None)
-
-
-def _register(class_type, class_def):
-    nodes.NODE_CLASS_MAPPINGS[class_type] = class_def
-
-
-def _validate(class_type):
-    prompt = {"1": {"class_type": class_type, "inputs": {}}}
-    return asyncio.run(validate_prompt("pid", prompt, None))
-
-
-def test_good_node_passes():
-    _register("GoodV1Node", _GoodV1Node)
-    assert node_not_executable_reason(_GoodV1Node, "GoodV1Node") is None
-    valid, _, _, _ = _validate("GoodV1Node")
-    assert valid is True
-
-
-def test_typo_node_rejected_with_node_error():
-    _register("TypoV1Node", _TypoV1Node)
-    valid, error, _, node_errors = _validate("TypoV1Node")
-    assert valid is False
-    assert error["type"] == "invalid_node_definition"
-    assert node_errors["1"]["class_type"] == "TypoV1Node"
-    assert node_errors["1"]["errors"][0]["type"] == "invalid_node_definition"
-    assert "invert" in node_errors["1"]["errors"][0]["details"]
-
-
-def test_validation_does_not_instantiate_node():
-    """A valid node is not constructed during validation, so __init__ never runs."""
-    _register("SideEffectInitV1Node", _SideEffectInitV1Node)
-    assert node_not_executable_reason(_SideEffectInitV1Node, "SideEffectInitV1Node") is None
-    valid, _, _, _ = _validate("SideEffectInitV1Node")
-    assert valid is True
-
-
-def test_good_v3_node_passes():
-    _register("GoodV3Node", _GoodV3Node)
-    assert node_not_executable_reason(_GoodV3Node, "GoodV3Node") is None
-    valid, _, _, _ = _validate("GoodV3Node")
-    assert valid is True
-
-
-def test_typo_v3_node_rejected_with_node_error():
-    _register("TypoV3Node", _TypoV3Node)
-    valid, error, _, node_errors = _validate("TypoV3Node")
-    assert valid is False
-    assert error["type"] == "invalid_node_definition"
-    assert node_errors["1"]["errors"][0]["type"] == "invalid_node_definition"

tests-unit/jobs_list_test/jobs_list_test.py

@@ -0,0 +1,277 @@
+"""Tests for the ``ids`` batch filter on the jobs listing endpoint.
+
+Covers both layers:
+
+* the pure ``comfy_execution.jobs.get_all_jobs`` filtering logic (the ``ids``
+  argument narrows the result, composes with ``status_filter``, and silently
+  ignores ids that match nothing), and
+
+* the HTTP contract of ``GET /api/jobs`` for the ``ids`` query parameter
+  (a valid set narrows the response, an oversized set or a malformed id is
+  rejected with 400).
+
+The HTTP layer is exercised against a small aiohttp app whose handler calls the
+SAME ``parse_ids_filter`` that ``server.py`` uses (no hand-copied wiring, so it
+cannot drift), driven by a fake queue. This keeps the test free of the heavy
+ComfyUI runtime (torch, nodes, ...) while still testing the real parsing
+contract.
+"""
+
+import pytest
+from aiohttp import web
+
+from comfy_execution.jobs import (
+    JobStatus,
+    JobIdsFilterError,
+    MAX_JOB_IDS_FILTER,
+    get_all_jobs,
+    parse_ids_filter,
+)
+
+# Canonical UUID ids (the endpoint validates UUID format).
+_UUID_A = "aaaaaaaa-aaaa-4aaa-aaaa-aaaaaaaaaaaa"
+_UUID_B = "bbbbbbbb-bbbb-4bbb-bbbb-bbbbbbbbbbbb"
+_UUID_C = "cccccccc-cccc-4ccc-cccc-cccccccccccc"
+_UUID_MISSING = "ffffffff-ffff-4fff-ffff-ffffffffffff"
+
+
+def make_queue_item(prompt_id, priority=0):
+    """Build a queue tuple shaped like the real ones (5 elements, id at index 1)."""
+    return (priority, prompt_id, {}, {}, [])
+
+
+def make_history_item(status_str="success"):
+    """Build a history item dict shaped like the real ones."""
+    return {
+        "prompt": (0, "", {}, {}, []),
+        "status": {"status_str": status_str, "messages": []},
+        "outputs": {},
+    }
+
+
+# ---------------------------------------------------------------------------
+# Pure get_all_jobs filtering logic
+# ---------------------------------------------------------------------------
+
+
+def test_ids_filter_returns_only_requested():
+    running = [make_queue_item(_UUID_A)]
+    queued = [make_queue_item(_UUID_B)]
+    history = {_UUID_C: make_history_item()}
+
+    jobs, total = get_all_jobs(running, queued, history, ids=[_UUID_A, _UUID_C])
+
+    returned = {j["id"] for j in jobs}
+    assert returned == {_UUID_A, _UUID_C}
+    assert total == 2
+    assert _UUID_B not in returned
+
+
+def test_ids_filter_absent_returns_all():
+    running = [make_queue_item(_UUID_A)]
+    queued = [make_queue_item(_UUID_B)]
+    history = {_UUID_C: make_history_item()}
+
+    jobs, total = get_all_jobs(running, queued, history)
+
+    assert {j["id"] for j in jobs} == {_UUID_A, _UUID_B, _UUID_C}
+    assert total == 3
+
+
+def test_ids_filter_empty_list_returns_none():
+    """A present-but-empty ids list is a zero-match filter, not "no filter".
+
+    ``None`` means "no id filter"; ``[]`` means "restrict to nothing".
+    """
+    running = [make_queue_item(_UUID_A)]
+    queued = [make_queue_item(_UUID_B)]
+
+    jobs, total = get_all_jobs(running, queued, {}, ids=[])
+
+    assert jobs == []
+    assert total == 0
+
+
+def test_ids_filter_unknown_id_silently_absent():
+    """An id that matches nothing is simply not present (no error)."""
+    running = [make_queue_item(_UUID_A)]
+
+    jobs, total = get_all_jobs(running, [], {}, ids=[_UUID_A, _UUID_MISSING])
+
+    assert {j["id"] for j in jobs} == {_UUID_A}
+    assert total == 1
+
+
+def test_ids_filter_composes_with_status():
+    """ids only narrows; it composes with the status filter."""
+    running = [make_queue_item(_UUID_A)]
+    queued = [make_queue_item(_UUID_B)]
+    history = {_UUID_C: make_history_item()}
+
+    # Request A and C by id, but restrict to in_progress only -> just A.
+    jobs, total = get_all_jobs(
+        running, queued, history,
+        status_filter=[JobStatus.IN_PROGRESS],
+        ids=[_UUID_A, _UUID_C],
+    )
+
+    assert {j["id"] for j in jobs} == {_UUID_A}
+    assert total == 1
+
+
+# ---------------------------------------------------------------------------
+# parse_ids_filter -- the shared parsing/validation (server.py + these tests)
+# ---------------------------------------------------------------------------
+
+
+def test_parse_ids_absent_is_none():
+    assert parse_ids_filter(None) is None
+
+
+def test_parse_ids_present_but_empty_is_empty_list():
+    # `?ids=` and `?ids=,,` parse to [] -> zero-match filter, not None.
+    assert parse_ids_filter("") == []
+    assert parse_ids_filter(",,") == []
+
+
+def test_parse_ids_dedupes_preserving_order():
+    assert parse_ids_filter(f"{_UUID_A},{_UUID_B},{_UUID_A}") == [_UUID_A, _UUID_B]
+
+
+def test_parse_ids_cap_counts_distinct_not_duplicates():
+    # A small distinct set repeated far past the cap is still under it.
+    repeated = ",".join([_UUID_A, _UUID_B] * MAX_JOB_IDS_FILTER)
+    assert parse_ids_filter(repeated) == [_UUID_A, _UUID_B]
+    # But more than MAX distinct ids is rejected.
+    distinct = ",".join(
+        f"{i:08d}-0000-4000-8000-000000000000" for i in range(MAX_JOB_IDS_FILTER + 1)
+    )
+    with pytest.raises(JobIdsFilterError):
+        parse_ids_filter(distinct)
+
+
+def test_parse_ids_invalid_raises_with_payload():
+    with pytest.raises(JobIdsFilterError) as exc:
+        parse_ids_filter(f"{_UUID_A},not-a-uuid")
+    assert "not-a-uuid" in exc.value.payload["invalid_ids"]
+
+
+# ---------------------------------------------------------------------------
+# HTTP contract for the ids query parameter
+# ---------------------------------------------------------------------------
+
+
+class FakePromptQueue:
+    """Minimal stand-in exposing the accessors get_jobs uses."""
+
+    def __init__(self, running=None, queued=None, history=None):
+        self._running = list(running or [])
+        self._queued = list(queued or [])
+        self._history = dict(history or {})
+
+    def get_current_queue_volatile(self):
+        return (list(self._running), list(self._queued))
+
+    def get_history(self):
+        return dict(self._history)
+
+
+def make_app(prompt_queue):
+    """Build an aiohttp app whose handler calls the REAL parse_ids_filter.
+
+    No hand-copied parsing wiring, so this test cannot stay green while the
+    shipped parsing in server.py regresses -- both go through parse_ids_filter.
+    """
+
+    async def get_jobs(request):
+        try:
+            ids_filter = parse_ids_filter(request.rel_url.query.get('ids'))
+        except JobIdsFilterError as e:
+            return web.json_response(e.payload, status=400)
+
+        running, queued = prompt_queue.get_current_queue_volatile()
+        history = prompt_queue.get_history()
+
+        jobs, total = get_all_jobs(running, queued, history, ids=ids_filter)
+
+        return web.json_response({
+            'jobs': jobs,
+            'pagination': {'total': total},
+        })
+
+    app = web.Application()
+    app.router.add_get('/api/jobs', get_jobs)
+    return app
+
+
+@pytest.fixture
+def queue():
+    return FakePromptQueue(
+        running=[make_queue_item(_UUID_A)],
+        queued=[make_queue_item(_UUID_B)],
+        history={_UUID_C: make_history_item()},
+    )
+
+
+@pytest.mark.asyncio
+async def test_http_ids_filter_narrows(aiohttp_client, queue):
+    client = await aiohttp_client(make_app(queue))
+
+    resp = await client.get(f"/api/jobs?ids={_UUID_A},{_UUID_C}")
+    assert resp.status == 200
+    body = await resp.json()
+    assert {j["id"] for j in body["jobs"]} == {_UUID_A, _UUID_C}
+
+
+@pytest.mark.asyncio
+async def test_http_ids_unknown_id_is_not_an_error(aiohttp_client, queue):
+    client = await aiohttp_client(make_app(queue))
+
+    resp = await client.get(f"/api/jobs?ids={_UUID_A},{_UUID_MISSING}")
+    assert resp.status == 200
+    body = await resp.json()
+    assert {j["id"] for j in body["jobs"]} == {_UUID_A}
+
+
+@pytest.mark.asyncio
+async def test_http_ids_over_limit_returns_400(aiohttp_client, queue):
+    client = await aiohttp_client(make_app(queue))
+
+    # Distinct ids past the cap. (Repeats of one id are de-duped and would NOT
+    # trip the cap -- see test_parse_ids_cap_counts_distinct_not_duplicates.)
+    too_many = ",".join(
+        f"{i:08d}-0000-4000-8000-000000000000" for i in range(MAX_JOB_IDS_FILTER + 1)
+    )
+    resp = await client.get(f"/api/jobs?ids={too_many}")
+    assert resp.status == 400
+
+
+@pytest.mark.asyncio
+async def test_http_ids_invalid_id_returns_400(aiohttp_client, queue):
+    client = await aiohttp_client(make_app(queue))
+
+    resp = await client.get(f"/api/jobs?ids={_UUID_A},not-a-uuid")
+    assert resp.status == 400
+    body = await resp.json()
+    assert "not-a-uuid" in body["invalid_ids"]
+
+
+@pytest.mark.asyncio
+async def test_http_ids_absent_returns_all(aiohttp_client, queue):
+    client = await aiohttp_client(make_app(queue))
+
+    resp = await client.get("/api/jobs")
+    assert resp.status == 200
+    body = await resp.json()
+    assert {j["id"] for j in body["jobs"]} == {_UUID_A, _UUID_B, _UUID_C}
+
+
+@pytest.mark.asyncio
+async def test_http_ids_present_but_empty_returns_none(aiohttp_client, queue):
+    """`?ids=` (present but empty) is a zero-match filter, not "return all"."""
+    client = await aiohttp_client(make_app(queue))
+
+    resp = await client.get("/api/jobs?ids=")
+    assert resp.status == 200
+    body = await resp.json()
+    assert body["jobs"] == []