Added Ideogram and Minimax back in.

.github/workflows/update-api-stubs.yml

@@ -22,10 +22,19 @@ jobs:
         run: |
           python -m pip install --upgrade pip
           pip install 'datamodel-code-generator[http]'
+          npm install @redocly/cli
+      
+      - name: Download OpenAPI spec
+        run: |
+          curl -o openapi.yaml https://api.comfy.org/openapi
+      
+      - name: Filter OpenAPI spec with Redocly
+        run: |
+          npx @redocly/cli bundle openapi.yaml --output filtered-openapi.yaml --config comfy_api_nodes/redocly.yaml --remove-unused-components
       
       - name: Generate API models
         run: |
-          datamodel-codegen  --use-subclass-enum --url https://api.comfy.org/openapi --output comfy_api_nodes/apis --output-model-type pydantic_v2.BaseModel
+          datamodel-codegen --use-subclass-enum --input filtered-openapi.yaml --output comfy_api_nodes/apis --output-model-type pydantic_v2.BaseModel
       
       - name: Check for changes
         id: git-check

.gitignore

@@ -21,3 +21,6 @@ venv/
 *.log
 web_custom_versions/
 .DS_Store
+openapi.yaml
+filtered-openapi.yaml
+uv.lock

comfy_api_nodes/README.md

@@ -0,0 +1,30 @@
+# ComfyUI API Nodes
+
+## Introduction 
+
+Below are a collection of nodes that work by calling external APIs. More information available in our [docs](https://docs.comfy.org/tutorials/api-nodes/overview#api-nodes).
+
+## Development
+
+API stubs are generated through automatic codegen tools from OpenAPI definitions. Since the Comfy Org OpenAPI definition contains many things from the Comfy Registry as well, we use redocly/cli to filter out only the paths relevant for API nodes.
+
+### Redocly Instructions 
+
+**Tip**
+When developing locally, use the `redocly-dev.yaml` file to generate pydantic models. This lets you use stubs for APIs that are not marked `Released` yet.
+
+Before your API node PR merges, make sure to add the `Released` tag to the `openapi.yaml` file and test in staging.
+
+```bash
+# Download the OpenAPI file from prod server.
+curl -o openapi.yaml https://api.comfy.org/openapi
+
+# Filter out unneeded API definitions.
+npm install -g @redocly/cli
+redocly bundle openapi.yaml --output filtered-openapi.yaml --config comfy_api_nodes/redocly-dev.yaml --remove-unused-components
+
+# Generate the pydantic datamodels for validation.
+datamodel-codegen --use-subclass-enum --input filtered-openapi.yaml --output comfy_api_nodes/apis/__init__.py --output-model-type pydantic_v2.BaseModel
+
+```
+

comfy_api_nodes/apis/PixverseController.py

@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
-#   filename:  https://api.comfy.org/openapi
+#   filename:  filtered-openapi.yaml
-#   timestamp: 2025-04-23T15:56:33+00:00
+#   timestamp: 2025-04-24T22:16:48+00:00
 
 from __future__ import annotations
 

comfy_api_nodes/apis/PixverseDto.py

@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
-#   filename:  https://api.comfy.org/openapi
+#   filename:  filtered-openapi.yaml
-#   timestamp: 2025-04-23T15:56:33+00:00
+#   timestamp: 2025-04-24T22:16:48+00:00
 
 from __future__ import annotations
 

comfy_api_nodes/apis/__init__.py

@@ -1,6 +1,6 @@
 # generated by datamodel-codegen:
-#   filename:  https://api.comfy.org/openapi
+#   filename:  filtered-openapi.yaml
-#   timestamp: 2025-04-23T15:56:33+00:00
+#   timestamp: 2025-04-24T22:29:35+00:00
 
 from __future__ import annotations
 
@@ -8,34 +8,14 @@ from datetime import datetime
 from enum import Enum
 from typing import Any, Dict, List, Optional
 
-from pydantic import AnyUrl, BaseModel, Field, confloat, conint
+from pydantic import BaseModel, Field, conint, constr
-
-class Customer(BaseModel):
-    createdAt: Optional[datetime] = Field(
-        None, description='The date and time the user was created'
-    )
-    email: Optional[str] = Field(None, description='The email address for this user')
-    id: str = Field(..., description='The firebase UID of the user')
-    name: Optional[str] = Field(None, description='The name for this user')
-    updatedAt: Optional[datetime] = Field(
-        None, description='The date and time the user was last updated'
-    )
-
-
-class Error(BaseModel):
-    details: Optional[List[str]] = Field(
-        None,
-        description='Optional detailed information about the error or hints for resolving it.',
-    )
-    message: Optional[str] = Field(
-        None, description='A clear and concise description of the error.'
-    )
 
 
 class ErrorResponse(BaseModel):
     error: str
     message: str
 
+
 class ImageRequest(BaseModel):
     aspect_ratio: Optional[str] = Field(
         None,
@@ -71,6 +51,12 @@ class ImageRequest(BaseModel):
     )
 
 
+class IdeogramGenerateRequest(BaseModel):
+    image_request: ImageRequest = Field(
+        ..., description='The image generation request parameters.'
+    )
+
+
 class Datum(BaseModel):
     is_image_safe: Optional[bool] = Field(
         None, description='Indicates whether the image is considered safe.'
@@ -91,6 +77,15 @@ class Datum(BaseModel):
     url: Optional[str] = Field(None, description='URL to the generated image.')
 
 
+class IdeogramGenerateResponse(BaseModel):
+    created: Optional[datetime] = Field(
+        None, description='Timestamp when the generation was created.'
+    )
+    data: Optional[List[Datum]] = Field(
+        None, description='Array of generated image information.'
+    )
+
+
 class Code(Enum):
     int_1100 = 1100
     int_1101 = 1101
@@ -106,135 +101,14 @@ class Code1(Enum):
     int_1004 = 1004
 
 
-class AspectRatio(str, Enum):
+class KlingErrorResponse(BaseModel):
-    field_16_9 = '16:9'
+    code: int = Field(
-    field_9_16 = '9:16'
+        ..., description='Error code value as defined in the API documentation'
-    field_1_1 = '1:1'
+    )
-
+    message: str = Field(..., description='Human-readable error message')
-
+    request_id: str = Field(
-class Config(BaseModel):
+        ..., description='Request ID for tracking and troubleshooting'
-    horizontal: Optional[confloat(ge=-10.0, le=10.0)] = None
+    )
-    pan: Optional[confloat(ge=-10.0, le=10.0)] = None
-    roll: Optional[confloat(ge=-10.0, le=10.0)] = None
-    tilt: Optional[confloat(ge=-10.0, le=10.0)] = None
-    vertical: Optional[confloat(ge=-10.0, le=10.0)] = None
-    zoom: Optional[confloat(ge=-10.0, le=10.0)] = None
-
-
-class Type(str, Enum):
-    simple = 'simple'
-    down_back = 'down_back'
-    forward_up = 'forward_up'
-    right_turn_forward = 'right_turn_forward'
-    left_turn_forward = 'left_turn_forward'
-
-
-class CameraControl(BaseModel):
-    config: Optional[Config] = None
-    type: Optional[Type] = Field(None, description='Predefined camera movements type')
-
-
-class Duration(str, Enum):
-    field_5 = 5
-    field_10 = 10
-
-
-class Mode(str, Enum):
-    std = 'std'
-    pro = 'pro'
-
-
-class TaskInfo(BaseModel):
-    external_task_id: Optional[str] = None
-
-
-class Video(BaseModel):
-    duration: Optional[str] = Field(None, description='Total video duration')
-    id: Optional[str] = Field(None, description='Generated video ID')
-    url: Optional[AnyUrl] = Field(None, description='URL for generated video')
-
-
-class TaskResult(BaseModel):
-    videos: Optional[List[Video]] = None
-
-
-class TaskStatus(str, Enum):
-    submitted = 'submitted'
-    processing = 'processing'
-    succeed = 'succeed'
-    failed = 'failed'
-
-
-class Data(BaseModel):
-    created_at: Optional[int] = Field(None, description='Task creation time')
-    task_id: Optional[str] = Field(None, description='Task ID')
-    task_info: Optional[TaskInfo] = None
-    task_result: Optional[TaskResult] = None
-    task_status: Optional[TaskStatus] = None
-    updated_at: Optional[int] = Field(None, description='Task update time')
-
-
-class AspectRatio1(str, Enum):
-    field_16_9 = '16:9'
-    field_9_16 = '9:16'
-    field_1_1 = '1:1'
-    field_4_3 = '4:3'
-    field_3_4 = '3:4'
-    field_3_2 = '3:2'
-    field_2_3 = '2:3'
-    field_21_9 = '21:9'
-
-
-class ImageReference(str, Enum):
-    subject = 'subject'
-    face = 'face'
-
-
-class Image(BaseModel):
-    index: Optional[int] = Field(None, description='Image Number (0-9)')
-    url: Optional[AnyUrl] = Field(None, description='URL for generated image')
-
-
-class TaskResult1(BaseModel):
-    images: Optional[List[Image]] = None
-
-
-class Data1(BaseModel):
-    created_at: Optional[int] = Field(None, description='Task creation time')
-    task_id: Optional[str] = Field(None, description='Task ID')
-    task_result: Optional[TaskResult1] = None
-    task_status: Optional[TaskStatus] = None
-    task_status_msg: Optional[str] = Field(None, description='Task status information')
-    updated_at: Optional[int] = Field(None, description='Task update time')
-
-
-class AspectRatio2(str, Enum):
-    field_16_9 = '16:9'
-    field_9_16 = '9:16'
-    field_1_1 = '1:1'
-
-
-class CameraControl1(BaseModel):
-    config: Optional[Config] = None
-    type: Optional[Type] = Field(None, description='Predefined camera movements type')
-
-
-class ModelName2(str, Enum):
-    kling_v1 = 'kling-v1'
-    kling_v1_6 = 'kling-v1-6'
-
-
-class TaskResult2(BaseModel):
-    videos: Optional[List[Video]] = None
-
-
-class Data2(BaseModel):
-    created_at: Optional[int] = Field(None, description='Task creation time')
-    task_id: Optional[str] = Field(None, description='Task ID')
-    task_info: Optional[TaskInfo] = None
-    task_result: Optional[TaskResult2] = None
-    task_status: Optional[TaskStatus] = None
-    updated_at: Optional[int] = Field(None, description='Task update time')
 
 
 class Code2(Enum):
@@ -244,43 +118,141 @@ class Code2(Enum):
     int_1203 = 1203
 
 
-class ResourcePackType(str, Enum):
+class KlingRequestError(KlingErrorResponse):
-    decreasing_total = 'decreasing_total'
+    code: Optional[Code2] = Field(
-    constant_period = 'constant_period'
+        None,
+        description='- 1200: Invalid request parameters\n- 1201: Invalid parameters\n- 1202: Invalid request method\n- 1203: Requested resource does not exist\n',
+    )
+
+
+class Code3(Enum):
+    int_5000 = 5000
+    int_5001 = 5001
+    int_5002 = 5002
+
+
+class KlingServerError(KlingErrorResponse):
+    code: Optional[Code3] = Field(
+        None,
+        description='- 5000: Internal server error\n- 5001: Service temporarily unavailable\n- 5002: Server internal timeout\n',
+    )
+
+
+class Code4(Enum):
+    int_1300 = 1300
+    int_1301 = 1301
+    int_1302 = 1302
+    int_1303 = 1303
+    int_1304 = 1304
+
+
+class KlingStrategyError(KlingErrorResponse):
+    code: Optional[Code4] = Field(
+        None,
+        description='- 1300: Trigger platform strategy\n- 1301: Trigger content security policy\n- 1302: API request too frequent\n- 1303: Concurrency/QPS exceeds limit\n- 1304: Trigger IP whitelist policy\n',
+    )
+
+
+class MinimaxBaseResponse(BaseModel):
+    status_code: int = Field(
+        ...,
+        description='Status code. 0 indicates success, other values indicate errors.',
+    )
+    status_msg: str = Field(
+        ..., description='Specific error details or success message.'
+    )
+
+
+class File(BaseModel):
+    bytes: Optional[int] = Field(None, description='File size in bytes')
+    created_at: Optional[int] = Field(
+        None, description='Unix timestamp when the file was created, in seconds'
+    )
+    download_url: Optional[str] = Field(
+        None, description='The URL to download the video'
+    )
+    file_id: Optional[int] = Field(None, description='Unique identifier for the file')
+    filename: Optional[str] = Field(None, description='The name of the file')
+    purpose: Optional[str] = Field(None, description='The purpose of using the file')
+
+
+class MinimaxFileRetrieveResponse(BaseModel):
+    base_resp: MinimaxBaseResponse
+    file: File
 
 
 class Status(str, Enum):
-    toBeOnline = 'toBeOnline'
+    Queueing = 'Queueing'
-    online = 'online'
+    Preparing = 'Preparing'
-    expired = 'expired'
+    Processing = 'Processing'
-    runOut = 'runOut'
+    Success = 'Success'
+    Fail = 'Fail'
 
 
-class ResourcePackSubscribeInfo(BaseModel):
+class MinimaxTaskResultResponse(BaseModel):
-    effective_time: Optional[int] = Field(
+    base_resp: MinimaxBaseResponse
-        None, description='Effective time, Unix timestamp in ms'
+    file_id: Optional[str] = Field(
-    )
-    invalid_time: Optional[int] = Field(
-        None, description='Expiration time, Unix timestamp in ms'
-    )
-    purchase_time: Optional[int] = Field(
-        None, description='Purchase time, Unix timestamp in ms'
-    )
-    remaining_quantity: Optional[float] = Field(
-        None, description='Remaining quantity (updated with a 12-hour delay)'
-    )
-    resource_pack_id: Optional[str] = Field(None, description='Resource package ID')
-    resource_pack_name: Optional[str] = Field(None, description='Resource package name')
-    resource_pack_type: Optional[ResourcePackType] = Field(
         None,
-        description='Resource package type (decreasing_total=decreasing total, constant_period=constant periodicity)',
+        description='After the task status changes to Success, this field returns the file ID corresponding to the generated video.',
     )
-    status: Optional[Status] = Field(None, description='Resource Package Status')
+    status: Status = Field(
-    total_quantity: Optional[float] = Field(None, description='Total quantity')
+        ...,
+        description="Task status: 'Queueing' (in queue), 'Preparing' (task is preparing), 'Processing' (generating), 'Success' (task completed successfully), or 'Fail' (task failed).",
+    )
+    task_id: str = Field(..., description='The task ID being queried.')
 
-class Background(str, Enum):
+
-    transparent = 'transparent'
+class Model(str, Enum):
-    opaque = 'opaque'
+    T2V_01_Director = 'T2V-01-Director'
+    I2V_01_Director = 'I2V-01-Director'
+    S2V_01 = 'S2V-01'
+    I2V_01 = 'I2V-01'
+    I2V_01_live = 'I2V-01-live'
+    T2V_01 = 'T2V-01'
+
+
+class SubjectReferenceItem(BaseModel):
+    image: Optional[str] = Field(
+        None, description='URL or base64 encoding of the subject reference image.'
+    )
+    mask: Optional[str] = Field(
+        None,
+        description='URL or base64 encoding of the mask for the subject reference image.',
+    )
+
+
+class MinimaxVideoGenerationRequest(BaseModel):
+    callback_url: Optional[str] = Field(
+        None,
+        description='Optional. URL to receive real-time status updates about the video generation task.',
+    )
+    first_frame_image: Optional[str] = Field(
+        None,
+        description='URL or base64 encoding of the first frame image. Required when model is I2V-01, I2V-01-Director, or I2V-01-live.',
+    )
+    model: Model = Field(
+        ...,
+        description='Required. ID of model. Options: T2V-01-Director, I2V-01-Director, S2V-01, I2V-01, I2V-01-live, T2V-01',
+    )
+    prompt: Optional[constr(max_length=2000)] = Field(
+        None,
+        description='Description of the video. Should be less than 2000 characters. Supports camera movement instructions in [brackets].',
+    )
+    prompt_optimizer: Optional[bool] = Field(
+        True,
+        description='If true (default), the model will automatically optimize the prompt. Set to false for more precise control.',
+    )
+    subject_reference: Optional[List[SubjectReferenceItem]] = Field(
+        None,
+        description='Only available when model is S2V-01. The model will generate a video based on the subject uploaded through this parameter.',
+    )
+
+
+class MinimaxVideoGenerationResponse(BaseModel):
+    base_resp: MinimaxBaseResponse
+    task_id: str = Field(
+        ..., description='The task ID for the asynchronous video generation task.'
+    )
 
 
 class Moderation(str, Enum):
@@ -294,12 +266,6 @@ class OutputFormat(str, Enum):
     jpeg = 'jpeg'
 
 
-class Quality(str, Enum):
-    low = 'low'
-    medium = 'medium'
-    high = 'high'
-
-
 class OpenAIImageEditRequest(BaseModel):
     background: Optional[str] = Field(
         None, description='Background transparency', examples=['opaque']
@@ -337,7 +303,12 @@ class OpenAIImageEditRequest(BaseModel):
     )
 
 
-class Quality1(str, Enum):
+class Background(str, Enum):
+    transparent = 'transparent'
+    opaque = 'opaque'
+
+
+class Quality(str, Enum):
     low = 'low'
     medium = 'medium'
     high = 'high'
@@ -381,7 +352,7 @@ class OpenAIImageGenerationRequest(BaseModel):
         description='A text description of the desired image',
         examples=['Draw a rocket in front of a blackhole in deep space'],
     )
-    quality: Optional[Quality1] = Field(
+    quality: Optional[Quality] = Field(
         None, description='The quality of the generated image', examples=['high']
     )
     response_format: Optional[ResponseFormat] = Field(
@@ -410,13 +381,17 @@ class Datum1(BaseModel):
 
 class OpenAIImageGenerationResponse(BaseModel):
     data: Optional[List[Datum1]] = None
-class User(BaseModel):
+
-    email: Optional[str] = Field(None, description='The email address for this user.')
+
-    id: Optional[str] = Field(None, description='The unique id for this user.')
+class KlingAccountError(KlingErrorResponse):
-    isAdmin: Optional[bool] = Field(
+    code: Optional[Code] = Field(
-        None, description='Indicates if the user has admin privileges.'
+        None,
+        description='- 1100: Account exception\n- 1101: Account in arrears (postpaid scenario)\n- 1102: Resource pack depleted or expired (prepaid scenario)\n- 1103: Unauthorized access to requested resource\n',
     )
-    isApproved: Optional[bool] = Field(
+
-        None, description='Indicates if the user is approved.'
+
+class KlingAuthenticationError(KlingErrorResponse):
+    code: Optional[Code1] = Field(
+        None,
+        description='- 1000: Authentication failed\n- 1001: Authorization is empty\n- 1002: Authorization is invalid\n- 1003: Authorization is not yet valid\n- 1004: Authorization has expired\n',
     )
-    name: Optional[str] = Field(None, description='The name for this user.')

comfy_api_nodes/apis/client.py

@@ -99,11 +99,10 @@ from typing import (
     Any,
     TypeVar,
     Generic,
-    Callable,
+
 )
 from pydantic import BaseModel
 from enum import Enum
-import time
 import json
 import requests
 from urllib.parse import urljoin

comfy_api_nodes/nodes_api.py

@@ -2,21 +2,38 @@ import base64
 import io
 import math
 from inspect import cleandoc
-
+from comfy.comfy_types.node_typing import FileLocator
-import numpy as np
+from typing import Literal
-import requests
+from comfy.utils import common_upscale
-import torch
-from PIL import Image
-
 from comfy.comfy_types.node_typing import IO, ComfyNodeABC, InputTypeDict
 from comfy.utils import common_upscale
 from comfy_api_nodes.apis import (
     OpenAIImageEditRequest,
     OpenAIImageGenerationRequest,
+    OpenAIImageEditRequest,
     OpenAIImageGenerationResponse,
+    MinimaxVideoGenerationRequest,
+    MinimaxVideoGenerationResponse,
+    MinimaxFileRetrieveResponse,
+    MinimaxTaskResultResponse,
+    IdeogramGenerateRequest,
+    IdeogramGenerateResponse,
+    ImageRequest,
+    Model
 )
-from comfy_api_nodes.apis.client import ApiEndpoint, HttpMethod, SynchronousOperation
+from comfy_api_nodes.apis.client import ApiEndpoint, HttpMethod, SynchronousOperation, PollingOperation, EmptyRequest
 
+import numpy as np
+from PIL import Image
+import requests
+import torch
+import math
+import base64
+import logging
+import json
+import av
+import os
+import folder_paths
 
 def downscale_input(image):
     samples = image.movedim(-1,1)
@@ -435,14 +452,168 @@ class OpenAIGPTImage1(ComfyNodeABC):
         return (img_tensor,)
 
 
-class MinimaxVideoNode:
+class IdeogramTextToImage(ComfyNodeABC):
+    """
+    Generates images synchronously based on a given prompt and optional parameters.
+
+    Images links are available for a limited period of time; if you would like to keep the image, you must download it.
+    """
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(cls) -> InputTypeDict:
+        """
+            Return a dictionary which contains config for all input fields.
+            Some types (string): "MODEL", "VAE", "CLIP", "CONDITIONING", "LATENT", "IMAGE", "INT", "STRING", "FLOAT".
+            Input types "INT", "STRING" or "FLOAT" are special values for fields on the node.
+            The type can be a list for selection.
+
+            Returns: `dict`:
+                - Key input_fields_group (`string`): Can be either required, hidden or optional. A node class must have property `required`
+                - Value input_fields (`dict`): Contains input fields config:
+                    * Key field_name (`string`): Name of a entry-point method's argument
+                    * Value field_config (`tuple`):
+                        + First value is a string indicate the type of field or a list for selection.
+                        + Secound value is a config for type "INT", "STRING" or "FLOAT".
+        """
+        return {
+            "required": {
+                "prompt": (IO.STRING, {
+                    "multiline": True,
+                    "default": "",
+                    "tooltip": "Prompt for the image generation",
+                }),
+                "model": (IO.COMBO, { "options": ["V_2", "V_2_TURBO", "V_1", "V_1_TURBO"], "default": "V_2", "tooltip": "Model to use for image generation"}),
+            },
+            "optional": {
+                "aspect_ratio": (IO.COMBO, { "options": ["ASPECT_1_1", "ASPECT_4_3", "ASPECT_3_4", "ASPECT_16_9", "ASPECT_9_16", "ASPECT_2_1", "ASPECT_1_2", "ASPECT_3_2", "ASPECT_2_3", "ASPECT_4_5", "ASPECT_5_4"], "default": "ASPECT_1_1", "tooltip": "The aspect ratio for image generation. Cannot be used with resolution"
+                }),
+                "resolution": (IO.COMBO, { "options": ["1024x1024", "1024x1792", "1792x1024"],
+                    "default": "1024x1024",
+                    "tooltip": "The resolution for image generation (V2 only). Cannot be used with aspect_ratio"
+                }),
+                "magic_prompt_option": (IO.COMBO, { "options": ["AUTO", "ON", "OFF"],
+                    "default": "AUTO",
+                    "tooltip": "Determine if MagicPrompt should be used in generation"
+                }),
+                "seed": (IO.INT, {
+                    "default": 0,
+                    "min": 0,
+                    "max": 2147483647,
+                    "step": 1,
+                    "display": "number"
+                }),
+                "style_type": (IO.COMBO, { "options": ["NONE", "ANIME", "CINEMATIC", "CREATIVE", "DIGITAL_ART", "PHOTOGRAPHIC"],
+                    "default": "NONE",
+                    "tooltip": "Style type for generation (V2+ only)"
+                }),
+                "negative_prompt": (IO.STRING, {
+                    "multiline": True,
+                    "default": "",
+                    "tooltip": "Description of what to exclude from the image (V1/V2 only)"
+                }),
+                "num_images": (IO.INT, {
+                    "default": 1,
+                    "min": 1,
+                    "max": 8,
+                    "step": 1,
+                    "display": "number"
+                }),
+                "color_palette": (IO.STRING, {
+                    "multiline": False,
+                    "default": "",
+                    "tooltip": "Color palette preset name or hex colors with weights (V2/V2_TURBO only)"
+                }),
+            },
+            "hidden": {
+                "auth_token": "AUTH_TOKEN_COMFY_ORG"
+            }
+        }
+
+    RETURN_TYPES = (IO.IMAGE,)
+    DESCRIPTION = cleandoc(__doc__ or "")  # Handle potential None value
+    FUNCTION = "api_call"
+    API_NODE = True
+    CATEGORY = "Example"
+
+    def api_call(self, prompt, model, aspect_ratio=None, resolution=None,
+                 magic_prompt_option="AUTO", seed=0, style_type="NONE",
+                 negative_prompt="", num_images=1, color_palette="", auth_token=None):
+        import torch
+        from PIL import Image
+        import io
+        import numpy as np
+        import requests
+
+        operation = SynchronousOperation(
+            endpoint=ApiEndpoint(
+                path="/proxy/ideogram/generate",
+                method=HttpMethod.POST,
+                request_model=IdeogramGenerateRequest,
+                response_model=IdeogramGenerateResponse
+            ),
+            request=IdeogramGenerateRequest(
+                image_request=ImageRequest(
+                  prompt=prompt,
+                  model=model,
+                  num_images=num_images,
+                  seed=seed,
+                  aspect_ratio=aspect_ratio if aspect_ratio != "ASPECT_1_1" else None,
+                  resolution=resolution if resolution != "1024x1024" else None,
+                  magic_prompt_option=magic_prompt_option if magic_prompt_option != "AUTO" else None,
+                  style_type=style_type if style_type != "NONE" else None,
+                  negative_prompt=negative_prompt if negative_prompt else None,
+                  color_palette=None
+                )
+            ),
+            auth_token=auth_token
+        )
+
+        response = operation.execute()
+
+        if not response.data or len(response.data) == 0:
+            raise Exception("No images were generated in the response")
+        image_url = response.data[0].url
+
+        if not image_url:
+            raise Exception("No image URL was generated in the response")
+        img_response = requests.get(image_url)
+        if img_response.status_code != 200:
+            raise Exception("Failed to download the image")
+
+        img = Image.open(io.BytesIO(img_response.content))
+        img = img.convert("RGB")  # Ensure RGB format
+
+        # Convert to numpy array, normalize to float32 between 0 and 1
+        img_array = np.array(img).astype(np.float32) / 255.0
+
+        # Convert to torch tensor and add batch dimension
+        img_tensor = torch.from_numpy(img_array)[None,]
+
+        return (img_tensor,)
+
+    """
+        The node will always be re executed if any of the inputs change but
+        this method can be used to force the node to execute again even when the inputs don't change.
+        You can make this node return a number or a string. This value will be compared to the one returned the last time the node was
+        executed, if it is different the node will be executed again.
+        This method is used in the core repo for the LoadImage node where they return the image hash as a string, if the image hash
+        changes between executions the LoadImage node is executed again.
+    """
+    #@classmethod
+    #def IS_CHANGED(s, image, string_field, int_field, float_field, print_to_screen):
+    #    return ""
+
+
+class MinimaxTextToVideoNode:
     """
     Generates videos synchronously based on a prompt, and optional parameters using Minimax's API.
     """
 
     def __init__(self):
         self.output_dir = folder_paths.get_output_directory()
-        self.type = "output"
+        self.type: Literal["output"] = "output"
 
     @classmethod
     def INPUT_TYPES(s):
@@ -604,13 +775,14 @@ class MinimaxVideoNode:
 
         return {"ui": {"images": results, "animated": (True,)}}
 
-
 # A dictionary that contains all nodes you want to export with their names
 # NOTE: names should be globally unique
 NODE_CLASS_MAPPINGS = {
     "OpenAIDalle2": OpenAIDalle2,
     "OpenAIDalle3": OpenAIDalle3,
     "OpenAIGPTImage1": OpenAIGPTImage1,
+    "IdeogramTextToImage": IdeogramTextToImage,
+    "MinimaxTextToVideoNode": MinimaxTextToVideoNode,
 }
 
 # A dictionary that contains the friendly/humanly readable titles for the nodes
@@ -618,4 +790,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "OpenAIDalle2": "OpenAI DALL·E 2",
     "OpenAIDalle3": "OpenAI DALL·E 3",
     "OpenAIGPTImage1": "OpenAI GPT Image 1",
+    "IdeogramTextToImage": "Ideogram Text to Image",
+    "MinimaxTextToVideoNode": "Minimax Text to Video",
 }

comfy_api_nodes/redocly-dev.yaml

@@ -0,0 +1,10 @@
+# This file is used to filter the Comfy Org OpenAPI spec for schemas related to API Nodes.
+# This is used for development purposes to generate stubs for unreleased API endpoints.
+apis:
+  filter:
+    root: openapi.yaml
+    decorators:
+      filter-in:
+        property: tags
+        value: ['API Nodes']
+        matchStrategy: all

comfy_api_nodes/redocly.yaml

@@ -0,0 +1,10 @@
+# This file is used to filter the Comfy Org OpenAPI spec for schemas related to API Nodes.
+
+apis:
+  filter:
+    root: openapi.yaml
+    decorators:
+      filter-in:
+        property: tags
+        value: ['API Nodes', 'Released']
+        matchStrategy: all