From b44a6156253857c62447580c4c502f0adbdee5bc Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Zeyu=20Huang=20=7C=20=E9=BB=83=E6=BE=A4=E5=AE=87?=
<11222265+fhfuih@users.noreply.github.com>
Date: Thu, 26 Feb 2026 21:03:54 +0800
Subject: [PATCH] [Doc][Test][Misc] ComfyUI test, more screenshot, and code
cleaning (#1435)
Signed-off-by: Huang, Zeyu <11222265+fhfuih@users.noreply.github.com>
Signed-off-by: Samit <285365963@qq.com>
Co-authored-by: Samit <285365963@qq.com>
---
.github/workflows/comfyui-publish.yml | 27 -
.github/workflows/comfyui-validate.yml | 40 -
apps/ComfyUI-vLLM-Omni/README.md | 41 +-
apps/ComfyUI-vLLM-Omni/__init__.py | 10 +-
.../comfyui_vllm_omni/nodes.py | 47 +-
.../comfyui_vllm_omni/utils/api_client.py | 46 +-
.../comfyui_vllm_omni/utils/models.py | 9 +-
.../comfyui_vllm_omni/utils/types.py | 14 +-
.../comfyui_vllm_omni/utils/validators.py | 31 +-
.../docs/images/comfyui-chaining-services.jpg | Bin 0 -> 265984 bytes
...ehension.jpg => comfyui-understanding.jpg} | Bin
.../vLLM-Omni Annotated Example.json | 1 -
.../vLLM-Omni Chaining Services.json | 552 +++++++++++++
.../vLLM-Omni Image Generation.json | 2 +-
.../vLLM-Omni Multimodal Understanding.json | 761 ++++++++++++++++++
pyproject.toml | 3 +-
tests/comfyui/conftest.py | 82 ++
tests/comfyui/test_comfyui_integration.py | 567 +++++++++++++
18 files changed, 2067 insertions(+), 166 deletions(-)
delete mode 100644 .github/workflows/comfyui-publish.yml
delete mode 100644 .github/workflows/comfyui-validate.yml
create mode 100644 apps/ComfyUI-vLLM-Omni/docs/images/comfyui-chaining-services.jpg
rename apps/ComfyUI-vLLM-Omni/docs/images/{comfyui-comprehension.jpg => comfyui-understanding.jpg} (100%)
delete mode 100644 apps/ComfyUI-vLLM-Omni/example_workflows/vLLM-Omni Annotated Example.json
create mode 100644 apps/ComfyUI-vLLM-Omni/example_workflows/vLLM-Omni Chaining Services.json
create mode 100644 apps/ComfyUI-vLLM-Omni/example_workflows/vLLM-Omni Multimodal Understanding.json
create mode 100644 tests/comfyui/conftest.py
create mode 100644 tests/comfyui/test_comfyui_integration.py
diff --git a/.github/workflows/comfyui-publish.yml b/.github/workflows/comfyui-publish.yml
deleted file mode 100644
index c282bcada..000000000
--- a/.github/workflows/comfyui-publish.yml
+++ /dev/null
@@ -1,27 +0,0 @@
-name: ComfyUI Integration -- Publish to Comfy registry
-on:
- workflow_dispatch:
- push:
- tags:
- - "*"
- paths:
- - "apps/ComfyUI-vLLM-Omni/**"
-
-permissions:
- issues: write
-
-defaults:
- run:
- working-directory: apps/ComfyUI-vLLM-Omni
-
-jobs:
- publish-node:
- name: Publish Custom Node to registry
- runs-on: ubuntu-latest
- steps:
- - name: ♻️ Check out code
- uses: actions/checkout@v4
- - name: 📦 Publish Custom Node
- uses: Comfy-Org/publish-node-action@main
- with:
- personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
diff --git a/.github/workflows/comfyui-validate.yml b/.github/workflows/comfyui-validate.yml
deleted file mode 100644
index 06b9b1f91..000000000
--- a/.github/workflows/comfyui-validate.yml
+++ /dev/null
@@ -1,40 +0,0 @@
-name: ComfyUI Integration -- Validate backwards compatibility
-
-on:
- pull_request:
- branches:
- - master
- - main
- paths:
- - "apps/ComfyUI-vLLM-Omni/**"
-
-defaults:
- run:
- working-directory: apps/ComfyUI-vLLM-Omni
-
-jobs:
- check-base-path:
- runs-on: ubuntu-latest
- outputs:
- exists: ${{ steps.check.outputs.exists }}
- defaults:
- run:
- working-directory: .
- steps:
- - uses: actions/checkout@v4
- with:
- ref: ${{ github.event.pull_request.base.sha }}
- fetch-depth: 1
- - id: check
- run: |
- if [ -d "apps/ComfyUI-vLLM-Omni" ]; then
- echo "exists=true" >> "$GITHUB_OUTPUT"
- else
- echo "exists=false" >> "$GITHUB_OUTPUT"
- fi
- validate:
- needs: check-base-path
- if: needs.check-base-path.outputs.exists == 'true'
- runs-on: ubuntu-latest
- steps:
- - uses: comfy-org/node-diff@main
diff --git a/apps/ComfyUI-vLLM-Omni/README.md b/apps/ComfyUI-vLLM-Omni/README.md
index dd530174f..23bbe5b72 100644
--- a/apps/ComfyUI-vLLM-Omni/README.md
+++ b/apps/ComfyUI-vLLM-Omni/README.md
@@ -47,12 +47,12 @@ If no, check your shell running the ComfyUI process. There may be some error mes
This extension offers the following nodes based on the output modalities (at **ComfyUI sidebar -> Node Library**):
- **Generate Image** for text-to-image and image-to-image tasks
-- **Multimodality Comprehension** for multimodality-to-text and multimodality-to-audio tasks
+- **Multimodality Understanding** for multimodality-to-text and multimodality-to-audio tasks
- **TTS** and **TTS Voice Clone** for TTS tasks
This extension also offers example workflows (at **ComfyUI sidebar -> Templates -> vLLM-Omni**)
-> [!INFO]
+> [!NOTE]
> The node UI and feature designs are intended to match vLLM-Omni online serving interfaces. It cannot offer more than what the interfaces support.
To build a simple workflow yourself,
@@ -65,28 +65,16 @@ To build a simple workflow yourself,
- For some multi-stage models like BAGEL, [only one stage's sampling parameters are exposed and tunable via vLLM-Omni's online serving API](https://docs.vllm.ai/projects/vllm-omni/en/latest/user_guide/examples/online_serving/bagel/). Thus, these models are treated as single-stage ones. Please check the vLLM-Omni documentation on how to correctly set each model's sampling parameters.
- For multi-stage models where all stages are either autoregression or diffusion, you can also connect only a single Sampling Params node, indicating that this set of sampling parameters will be used for all stages.
-**The following features are tested**:
-
-- Single-node workflows for
- - Multimodal Comprehension (e.g., Qwen Omni, BAGEL)
- - Text-to-Image Generation (e.g., Qwen-Image)
- - Image-to-Image Generation (e.g., Qwen-Image-Edit)
- - TTS (e.g., Qwen TTS, including VoiceDesign, VoiceClone, CustomVoice)
-
-**The following features are not currently tested**. They may work or break. You are welcomed to test it out and offer comments.
-
-- Multi-node workflow that connects multiple model services together.
-
## Screenshots and Examples
-### Multimodal comprehension (e.g., Qwen Omni series, BAGEL)
+### Multimodal understanding (e.g., Qwen Omni series, BAGEL)
-(Also available at **ComfyUI sidebar->Template->vLLM-Omni->vLLM-Omni Annotated Example**)
+(Also available at **ComfyUI sidebar->Template->vLLM-Omni->vLLM-Omni Multimodal Understanding**)
-
-
+
+
@@ -98,7 +86,7 @@ You can configure per-stage sampling parameters for multi-stage models.
-
+
@@ -109,7 +97,7 @@ You can configure per-stage sampling parameters for multi-stage models.
-
+
@@ -123,13 +111,24 @@ You can configure per-stage sampling parameters for multi-stage models.
-
+
> [!TIP]
> There is a dedicated node for VoiceClone tasks with reference audio input. Other simple text-to-speech tasks should use the regular TTS node.
+### Chaining multiple model services
+
+(Also available at **ComfyUI sidebar->Template->vLLM-Omni->vLLM-Omni Chaining Services**)
+
+
+
+
+
+
+
+
## Develop
Follow the [development convention and rules of vLLM-Omni](https://docs.vllm.ai/projects/vllm-omni/en/latest/contributing/).
diff --git a/apps/ComfyUI-vLLM-Omni/__init__.py b/apps/ComfyUI-vLLM-Omni/__init__.py
index ffb86ddb3..641824add 100644
--- a/apps/ComfyUI-vLLM-Omni/__init__.py
+++ b/apps/ComfyUI-vLLM-Omni/__init__.py
@@ -6,18 +6,18 @@ __all__ = [
"WEB_DIRECTORY",
]
-__author__ = """Zeyu Huang"""
-__email__ = "11222265+fhfuih@users.noreply.github.com"
+__author__ = """vLLM-Omni Team"""
+__email__ = "vllm-omni@vllm.ai"
__version__ = "0.0.1"
from .comfyui_vllm_omni.nodes import (
VLLMOmniARSampling,
- VLLMOmniComprehension,
VLLMOmniDiffusionSampling,
VLLMOmniGenerateImage,
VLLMOmniQwenTTSParams,
VLLMOmniSamplingParamsList,
VLLMOmniTTS,
+ VLLMOmniUnderstanding,
VLLMOmniVoiceClone,
)
@@ -25,7 +25,7 @@ from .comfyui_vllm_omni.nodes import (
NODE_CLASS_MAPPINGS = {
# === Generation ===
"VLLMOmniGenerateImage": VLLMOmniGenerateImage,
- "VLLMOmniComprehension": VLLMOmniComprehension,
+ "VLLMOmniUnderstanding": VLLMOmniUnderstanding,
"VLLMOmniTTS": VLLMOmniTTS,
"VLLMOmniVoiceClone": VLLMOmniVoiceClone,
# === Params ===
@@ -39,7 +39,7 @@ NODE_CLASS_MAPPINGS = {
NODE_DISPLAY_NAME_MAPPINGS = {
# === Generation ===
"VLLMOmniGenerateImage": "Generate Image",
- "VLLMOmniComprehension": "Multimodality Comprehension",
+ "VLLMOmniUnderstanding": "Multimodality Understanding",
"VLLMOmniTTS": "TTS (Text to Speech)",
"VLLMOmniVoiceClone": "TTS Voice Cloning",
# === Params ===
diff --git a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/nodes.py b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/nodes.py
index ebc2822df..5caa3869e 100644
--- a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/nodes.py
+++ b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/nodes.py
@@ -1,4 +1,4 @@
-from typing import Literal, cast
+from typing import Literal
import torch
from comfy_api.input import AudioInput, VideoInput
@@ -6,7 +6,12 @@ from comfy_api.input import AudioInput, VideoInput
from .utils.api_client import VLLMOmniClient
from .utils.logger import get_logger
from .utils.models import lookup_model_spec
-from .utils.types import AudioFormat
+from .utils.types import (
+ AudioFormat,
+ AutoregressionSamplingParams,
+ DiffusionSamplingParams,
+ QwenTTSModelSpecificParams,
+)
from .utils.validators import (
add_sampling_parameters_to_stage,
validate_model_and_sampling_params_types,
@@ -86,7 +91,10 @@ class VLLMOmniGenerateImage(_VLLMOmniGenerateBase):
# Prefer DALL-E compatible API for simple (one-stage) diffusion models
if (spec is None or spec["stages"] == ["diffusion"]) and not is_bagel:
- sampling_params = cast(dict | None, sampling_params)
+ # The number of sampling parameter groups should have been validated.
+ # Now, simply convert single-item list to dict.
+ if isinstance(sampling_params, list):
+ sampling_params = sampling_params[0]
if audio is None and image is None and video is None:
# No multimodal input --- use DALL-E image generation
logger.info("Using DALL-E image generation endpoint")
@@ -133,7 +141,7 @@ class VLLMOmniGenerateImage(_VLLMOmniGenerateBase):
return (output,)
-class VLLMOmniComprehension(_VLLMOmniGenerateBase):
+class VLLMOmniUnderstanding(_VLLMOmniGenerateBase):
@classmethod
def INPUT_TYPES(cls):
return {
@@ -197,7 +205,7 @@ class VLLMOmniComprehension(_VLLMOmniGenerateBase):
(
text_response,
_,
- ) = await client.generate_comprehension_chat_completion(
+ ) = await client.generate_understanding_chat_completion(
model=model,
prompt=prompt,
image=image,
@@ -221,7 +229,7 @@ class VLLMOmniComprehension(_VLLMOmniGenerateBase):
(
text_response,
audio,
- ) = await client.generate_comprehension_chat_completion(
+ ) = await client.generate_understanding_chat_completion(
model=model,
prompt=prompt,
image=image,
@@ -287,15 +295,13 @@ class VLLMOmniTTS(_VLLMOmniGenerateBase):
logger.info("Got extra kwargs in TTS: %s", kwargs)
is_qwen_tts = "qwen3-tts" in model.lower()
- extra_params_type = None if model_specific_params is None else model_specific_params["type"]
- if not is_qwen_tts and extra_params_type == "qwen-tts":
+ if not is_qwen_tts and isinstance(model_specific_params, QwenTTSModelSpecificParams):
raise ValueError(
"You have provided Qwen-specific TTS params."
"However, the model appears to not be a Qwen TTS model (no 'Qwen3-TTS' in model name)."
)
combined_params = {**kwargs, **(model_specific_params or {})}
- combined_params.pop("type", None) # Internal fields in model_specific_params
client = VLLMOmniClient(url)
@@ -352,8 +358,7 @@ class VLLMOmniVoiceClone(_VLLMOmniGenerateBase):
**kwargs,
):
is_qwen_tts = "qwen3-tts" in model.lower()
- extra_params_type = None if model_specific_params is None else model_specific_params["type"]
- if not is_qwen_tts and extra_params_type == "qwen-tts":
+ if not is_qwen_tts and isinstance(model_specific_params, QwenTTSModelSpecificParams):
raise ValueError(
"You have provided Qwen-specific TTS params."
"However, the model appears to not be a Qwen TTS model (no 'Qwen3-TTS' in model name)."
@@ -366,7 +371,6 @@ class VLLMOmniVoiceClone(_VLLMOmniGenerateBase):
**kwargs,
**(model_specific_params or {}),
}
- combined_params.pop("type", None) # Internal fields in model_specific_params
client = VLLMOmniClient(url)
@@ -419,10 +423,7 @@ class VLLMOmniARSampling:
CATEGORY = "vLLM-Omni/Sampling Params"
def get_params(self, seed, **kwargs):
- params = {
- "type": "autoregression", # for internal use, removed before sending the request
- **kwargs,
- }
+ params = AutoregressionSamplingParams(kwargs)
if seed >= 0:
params["seed"] = seed
return (params,)
@@ -479,6 +480,13 @@ class VLLMOmniDiffusionSampling:
"tooltip": "Enable VAE slicing for reduced memory usage (slight quality trade-off)",
},
),
+ "vae_use_tiling": (
+ "BOOLEAN",
+ {
+ "default": False,
+ "tooltip": "Enable VAE tiling for reduced memory usage (slight quality trade-off)",
+ },
+ ),
# === Put seed at last. ===
# Whenever a field named "seed" is present, ComfyUI adds another field called "control after generate"
"seed": (
@@ -499,10 +507,7 @@ class VLLMOmniDiffusionSampling:
CATEGORY = "vLLM-Omni/Sampling Params"
def get_params(self, seed, **kwargs):
- params = {
- "type": "diffusion", # for internal use, removed before sending the request
- **kwargs,
- }
+ params = DiffusionSamplingParams(kwargs)
if seed >= 0:
params["seed"] = seed
return (params,)
@@ -566,4 +571,4 @@ class VLLMOmniQwenTTSParams:
CATEGORY = "vLLM-Omni/TTS Params"
def get_params(self, **kwargs):
- return ({"type": "qwen-tts", **kwargs},)
+ return (QwenTTSModelSpecificParams(kwargs),)
diff --git a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/api_client.py b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/api_client.py
index c5372641f..d340073bc 100644
--- a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/api_client.py
+++ b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/api_client.py
@@ -57,16 +57,7 @@ class VLLMOmniClient:
if negative_prompt:
payload["negative_prompt"] = negative_prompt
if sampling_params is not None:
- # Only select specific sampling params
- for k in (
- "n",
- "num_inference_steps",
- "guidance_scale",
- "true_cfg_scale",
- "vae_use_slicing",
- ):
- if k in sampling_params and sampling_params[k] is not None:
- payload[k] = sampling_params[k]
+ payload.update(sampling_params)
logger.debug("img gen payload: %s", payload)
url = self.base_url + "/images/generations"
@@ -138,10 +129,8 @@ class VLLMOmniClient:
if negative_prompt:
form.add_field("negative_prompt", negative_prompt)
if sampling_params is not None:
- # Only select specific sampling params
- for k in ("n", "num_inference_steps", "guidance_scale", "true_cfg_scale"):
- if k in sampling_params and sampling_params[k] is not None:
- form.add_field(k, str(sampling_params[k]))
+ for k, v in sampling_params.items():
+ form.add_field(k, str(v))
if mask is not None:
mask_filename = "mask.png"
form.add_field(
@@ -217,7 +206,7 @@ class VLLMOmniClient:
return torch.stack(image_tensors, dim=0)
- async def generate_comprehension_chat_completion(
+ async def generate_understanding_chat_completion(
self,
*,
model: str,
@@ -427,30 +416,28 @@ class VLLMOmniClient:
message_content.append({"type": "video_url", "video_url": {"url": video_to_base64(video)}})
messages = [{"role": "user", "content": message_content}]
+ payload: dict[str, Any] = {"messages": messages, "model": model}
+ if modalities:
+ payload["modalities"] = modalities
+
combined_extra_body: dict[str, Any] = {}
if sampling_params is not None:
spec, _ = lookup_model_spec(model)
is_single_sampling_param = isinstance(sampling_params, dict) or len(sampling_params) == 1
- # Exclude internal key
- if isinstance(sampling_params, dict):
- sampling_params = {k: v for k, v in sampling_params.items() if k != "type"}
- else:
- sampling_params = [{k: v for k, v in sp.items() if k != "type"} for sp in sampling_params]
-
if (spec is None and is_single_sampling_param) or (spec is not None and spec["stages"] == ["diffusion"]):
# Diffusion format: extra_body directly contains sampling params.
- # Validation should have taken care of matching sampling params' types.
+ # Validation has already taken care of matching sampling params' types and length. Safe to take [0].
# * Use this mode if the model is a simple one-stage diffusion model.
# * Fallback to this mode if model is not registered and a single sampling param is provided.
sampling_params = sampling_params if isinstance(sampling_params, dict) else sampling_params[0]
- combined_extra_body: dict[str, Any] = {**sampling_params}
+ combined_extra_body: dict[str, Any] = sampling_params.copy()
if "n" in combined_extra_body:
- combined_extra_body["num_outputs_per_prompt"] = combined_extra_body["n"]
- del combined_extra_body["n"]
+ combined_extra_body["num_outputs_per_prompt"] = combined_extra_body.pop("n")
else:
- # Use AR style payload, extra_body has a sampling_params_list field
- combined_extra_body: dict[str, Any] = {"sampling_params_list": sampling_params}
+ # AR format: the payload has a sampling_params_list field, containing a list.
+ sampling_params_list = sampling_params if isinstance(sampling_params, list) else [sampling_params]
+ payload["sampling_params_list"] = sampling_params_list
if negative_prompt:
combined_extra_body["negative_prompt"] = negative_prompt
@@ -458,12 +445,11 @@ class VLLMOmniClient:
if extra_body:
combined_extra_body.update(extra_body)
- payload: dict[str, Any] = {"messages": messages, "model": model}
+ # Add extra_body only if it has any content.
if combined_extra_body:
payload["extra_body"] = combined_extra_body
- if modalities:
- payload["modalities"] = modalities
+ # Place to inject any model-specific payload adjustment
spec, _ = lookup_model_spec(model)
if spec:
preprocessor = spec.get("payload_preprocessor", None)
diff --git a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/models.py b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/models.py
index 83bf64fe7..bfeddd82b 100644
--- a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/models.py
+++ b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/models.py
@@ -11,8 +11,7 @@ def _bagel_payload_preprocessor(payload: dict) -> dict:
content["text"] = "<|im_start|>" + content["text"] + "<|im_end|>"
except (KeyError, TypeError):
raise RuntimeError("Internal Error: malformatted BAGEL payload")
- extra_body = payload.pop("extra_body", {})
- return {**payload, **extra_body}
+ return payload
def _qwen25_payload_preprocessor(payload: dict) -> dict:
@@ -37,7 +36,7 @@ _MODEL_PIPELINE_SPECS: dict[str, Spec] = {
],
"modes": [
{
- "mode": ModelMode.COMPREHENSION,
+ "mode": ModelMode.UNDERSTANDING,
"input_modalities": [Modality.TEXT, Modality.IMAGE],
}
],
@@ -48,7 +47,7 @@ _MODEL_PIPELINE_SPECS: dict[str, Spec] = {
"payload_preprocessor": _qwen25_payload_preprocessor,
"modes": [
{
- "mode": ModelMode.COMPREHENSION,
+ "mode": ModelMode.UNDERSTANDING,
"input_modalities": [
Modality.TEXT,
Modality.IMAGE,
@@ -62,7 +61,7 @@ _MODEL_PIPELINE_SPECS: dict[str, Spec] = {
"stages": ["autoregression", "autoregression", "autoregression"],
"modes": [
{
- "mode": ModelMode.COMPREHENSION,
+ "mode": ModelMode.UNDERSTANDING,
"input_modalities": [
Modality.TEXT,
Modality.IMAGE,
diff --git a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/types.py b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/types.py
index 29be9648c..6cc79f3ed 100644
--- a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/types.py
+++ b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/types.py
@@ -11,11 +11,23 @@ from typing import (
AudioFormat: TypeAlias = Literal["mp3", "opus", "aac", "flac", "wav", "pcm"]
+class AutoregressionSamplingParams(dict):
+ pass
+
+
+class DiffusionSamplingParams(dict):
+ pass
+
+
+class QwenTTSModelSpecificParams(dict):
+ pass
+
+
class ModelMode(Enum):
IMAGE_GENERATION = auto()
VIDEO_GENERATION = auto()
AUDIO_GENERATION = auto()
- COMPREHENSION = auto()
+ UNDERSTANDING = auto()
class Modality(Enum):
diff --git a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/validators.py b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/validators.py
index f1af7b2e9..2abdd2100 100644
--- a/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/validators.py
+++ b/apps/ComfyUI-vLLM-Omni/comfyui_vllm_omni/utils/validators.py
@@ -1,5 +1,6 @@
from .logger import get_logger
from .models import lookup_model_spec
+from .types import AutoregressionSamplingParams, DiffusionSamplingParams
logger = get_logger(__name__)
@@ -31,24 +32,20 @@ def validate_model_and_sampling_params_types(
)
# Check that each stage's type match
for i, sp in enumerate(sampling_param_list):
- if "type" not in sp:
- raise RuntimeError("Internal error: unknown sampling parameter type")
- if sp["type"] != stages[i]:
+ if not _check_sampling_param_matches_stage(sp, stages[i]):
raise ValueError(
- f"Sampling parameter type ({sp['type']}) does not match "
+ f"Sampling parameter type ({sp.__class__.__name__}) does not match "
f"stage type ({stages[i]}) at index {i} for model {model_name}."
)
elif isinstance(sampling_param_list, dict):
- if "type" not in sampling_param_list:
- raise RuntimeError("Internal error: unknown sampling parameter type")
# Check that the provided single sampling param matches all stages
- elif any(stage != sampling_param_list["type"] for stage in stages):
- raise ValueError(
- f"When passing a single sampling parameter node, all stages of the model must match "
- f"the provided sampling parameter's type. "
- f"However, the stages of model {model_name} are: {stages}. "
- f"The provided sampling parameter is {sampling_param_list['type']}"
- )
+ for i, stage in enumerate(stages):
+ if not _check_sampling_param_matches_stage(sampling_param_list, stage):
+ raise ValueError(
+ f"Provided single sampling parameter type ({sampling_param_list.__class__.__name__}) must match "
+ f"the types of all stages of the model. "
+ f"However, stage {i} of model {model_name} is of type {stage}."
+ )
def add_sampling_parameters_to_stage(
@@ -82,3 +79,11 @@ def add_sampling_parameters_to_stage(
sampling_param_list[i].update(params_to_add)
return sampling_param_list
+
+
+def _check_sampling_param_matches_stage(sampling_param: dict, stage_type: str) -> bool:
+ if stage_type == "autoregression":
+ return isinstance(sampling_param, AutoregressionSamplingParams)
+ if stage_type == "diffusion":
+ return isinstance(sampling_param, DiffusionSamplingParams)
+ raise RuntimeError(f"Internal error: unknown stage type {stage_type}.")
diff --git a/apps/ComfyUI-vLLM-Omni/docs/images/comfyui-chaining-services.jpg b/apps/ComfyUI-vLLM-Omni/docs/images/comfyui-chaining-services.jpg
new file mode 100644
index 0000000000000000000000000000000000000000..20d9d077938df094011562435b194a415e837d23
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