diff --git a/comfy_api_nodes/apis/BFLPolling.py b/comfy_api_nodes/apis/BFLPolling.py deleted file mode 100644 index e40bf3344..000000000 --- a/comfy_api_nodes/apis/BFLPolling.py +++ /dev/null @@ -1,29 +0,0 @@ -from __future__ import annotations - -from enum import Enum -from typing import Any, Dict, Optional - -from pydantic import BaseModel, Field, confloat - - -class BFLStatus(str, Enum): - task_not_found = "Task not found" - pending = "Pending" - request_moderated = "Request Moderated" - content_moderated = "Content Moderated" - ready = "Ready" - error = "Error" - - -class BFLFluxProStatusResponse(BaseModel): - id: str = Field(..., description="The unique identifier for the generation task.") - status: BFLStatus = Field(..., description="The status of the task.") - result: Optional[Dict[str, Any]] = Field( - None, description="The result of the task (null if not completed)." - ) - progress: confloat(ge=0.0, le=1.0) = Field( - ..., description="The progress of the task (0.0 to 1.0)." - ) - details: Optional[Dict[str, Any]] = Field( - None, description="Additional details about the task (null if not available)." - ) diff --git a/comfy_api_nodes/nodes_api.py b/comfy_api_nodes/nodes_api.py index f47de0bfb..d1055059e 100644 --- a/comfy_api_nodes/nodes_api.py +++ b/comfy_api_nodes/nodes_api.py @@ -14,12 +14,9 @@ from comfy_api_nodes.apis import ( MinimaxTaskResultResponse, IdeogramGenerateRequest, IdeogramGenerateResponse, - BFLFluxProGenerateRequest, - BFLFluxProGenerateResponse, ImageRequest, Model ) -from comfy_api_nodes.apis.BFLPolling import BFLStatus from comfy_api_nodes.apis.client import ( ApiClient, ApiEndpoint, @@ -38,7 +35,6 @@ import torch import math import base64 import logging -import time import uuid import folder_paths from io import BytesIO @@ -996,212 +992,6 @@ class IdeogramTextToImage(ComfyNodeABC): # def IS_CHANGED(s, image, string_field, int_field, float_field, print_to_screen): # return "" - -class FluxProUltraImageNode(ComfyNodeABC): - """ - Generates images synchronously based on prompt and resolution. - """ - - MINIMUM_RATIO = 1 / 4 - MAXIMUM_RATIO = 4 / 1 - MINIMUM_RATIO_STR = "1:4" - MAXIMUM_RATIO_STR = "4:1" - - @classmethod - def INPUT_TYPES(s): - return { - "required": { - "prompt": ( - IO.STRING, - { - "multiline": True, - "default": "", - "tooltip": "Prompt for the image generation", - }, - ), - "prompt_upsampling": ( - IO.BOOLEAN, - { - "default": False, - "tooltip": "Whether to perform upsampling on the prompt. If active, automatically modifies the prompt for more creative generation, but results are nondeterministic (same seed will not produce exactly the same result).", - }, - ), - "seed": ( - IO.INT, - { - "default": 0, - "min": 0, - "max": 0xFFFFFFFFFFFFFFFF, - "control_after_generate": True, - "tooltip": "The random seed used for creating the noise.", - }, - ), - "aspect_ratio": ( - IO.STRING, - { - "default": "16:9", - "tooltip": "Aspect ratio of image; must be between 1:4 and 4:1.", - }, - ), - "raw": ( - IO.BOOLEAN, - { - "default": False, - "tooltip": "When True, generate less processed, more natural-looking images.", - }, - ), - }, - "optional": { - "image_prompt": (IO.IMAGE,), - "image_prompt_strength": ( - IO.FLOAT, - { - "default": 0.1, - "min": 0.0, - "max": 1.0, - "step": 0.01, - "tooltip": "Blend between the prompt and the image prompt.", - }, - ), - }, - "hidden": { - "auth_token": "AUTH_TOKEN_COMFY_ORG", - }, - } - - @classmethod - def VALIDATE_INPUTS(cls, aspect_ratio: str): - try: - validate_aspect_ratio( - aspect_ratio, - minimum_ratio=cls.MINIMUM_RATIO, - maximum_ratio=cls.MAXIMUM_RATIO, - minimum_ratio_str=cls.MINIMUM_RATIO_STR, - maximum_ratio_str=cls.MAXIMUM_RATIO_STR, - ) - except Exception as e: - return str(e) - return True - - RETURN_TYPES = (IO.IMAGE,) - DESCRIPTION = cleandoc(__doc__ or "") # Handle potential None value - FUNCTION = "api_call" - API_NODE = True - CATEGORY = "api node/image/bfl" - - def api_call( - self, - prompt: str, - aspect_ratio: str, - prompt_upsampling=False, - raw=False, - seed=0, - image_prompt=None, - image_prompt_strength=0.1, - auth_token=None, - **kwargs, - ): - operation = SynchronousOperation( - endpoint=ApiEndpoint( - path="/proxy/bfl/flux-pro-1.1-ultra/generate", - method=HttpMethod.POST, - request_model=BFLFluxProGenerateRequest, - response_model=BFLFluxProGenerateResponse, - ), - request=BFLFluxProGenerateRequest( - prompt=prompt, - prompt_upsampling=prompt_upsampling, - seed=seed, - aspect_ratio=validate_aspect_ratio( - aspect_ratio, - minimum_ratio=self.MINIMUM_RATIO, - maximum_ratio=self.MAXIMUM_RATIO, - minimum_ratio_str=self.MINIMUM_RATIO_STR, - maximum_ratio_str=self.MAXIMUM_RATIO_STR, - ), - raw=raw, - image_prompt=( - image_prompt - if image_prompt is None - else self._convert_image_to_base64(image_prompt) - ), - image_prompt_strength=( - None if image_prompt is None else round(image_prompt_strength, 2) - ), - ), - auth_token=auth_token, - ) - output_image = self._handle_bfl_synchronous_operation(operation) - return (output_image,) - - def _handle_bfl_synchronous_operation( - self, operation: SynchronousOperation, timeout_bfl_calls=360 - ): - response_api: BFLFluxProGenerateResponse = operation.execute() - return self._poll_until_generated( - response_api.polling_url, timeout=timeout_bfl_calls - ) - - def _poll_until_generated(self, polling_url: str, timeout=360): - # used bfl-comfy-nodes to verify code implementation: - # https://github.com/black-forest-labs/bfl-comfy-nodes/tree/main - start_time = time.time() - retries_404 = 0 - max_retries_404 = 5 - retry_404_seconds = 2 - retry_202_seconds = 2 - retry_pending_seconds = 1 - request = requests.Request(method=HttpMethod.GET, url=polling_url) - # NOTE: should True loop be replaced with checking if workflow has been interrupted? - while True: - response = requests.Session().send(request.prepare()) - if response.status_code == 200: - result = response.json() - if result["status"] == BFLStatus.ready: - img_url = result["result"]["sample"] - img_response = requests.get(img_url) - return process_image_response(img_response) - elif result["status"] in [ - BFLStatus.request_moderated, - BFLStatus.content_moderated, - ]: - status = result["status"] - raise Exception( - f"BFL API did not return an image due to: {status}." - ) - elif result["status"] == BFLStatus.error: - raise Exception(f"BFL API encountered an error: {result}.") - elif result["status"] == BFLStatus.pending: - time.sleep(retry_pending_seconds) - continue - elif response.status_code == 404: - if retries_404 < max_retries_404: - retries_404 += 1 - time.sleep(retry_404_seconds) - continue - raise Exception( - f"BFL API could not find task after {max_retries_404} tries." - ) - elif response.status_code == 202: - time.sleep(retry_202_seconds) - elif time.time() - start_time > timeout: - raise Exception( - f"BFL API experienced a timeout; could not return request under {timeout} seconds." - ) - else: - raise Exception(f"BFL API encountered an error: {response.json()}") - - def _convert_image_to_base64(self, image: torch.Tensor): - scaled_image = downscale_input(image, total_pixels=2048 * 2048) - # remove batch dimension if present - if len(scaled_image.shape) > 3: - scaled_image = scaled_image[0] - image_np = (scaled_image.numpy() * 255).astype(np.uint8) - img = Image.fromarray(image_np) - img_byte_arr = io.BytesIO() - img.save(img_byte_arr, format="PNG") - return base64.b64encode(img_byte_arr.getvalue()).decode() - class MinimaxTextToVideoNode: """ Generates videos synchronously based on a prompt, and optional parameters using Minimax's API. @@ -1348,7 +1138,6 @@ NODE_CLASS_MAPPINGS = { "OpenAIDalle3": OpenAIDalle3, "OpenAIGPTImage1": OpenAIGPTImage1, "IdeogramTextToImage": IdeogramTextToImage, - "FluxProUltraImageNode": FluxProUltraImageNode, "MinimaxTextToVideoNode": MinimaxTextToVideoNode, } @@ -1358,6 +1147,5 @@ NODE_DISPLAY_NAME_MAPPINGS = { "OpenAIDalle3": "OpenAI DALL·E 3", "OpenAIGPTImage1": "OpenAI GPT Image 1", "IdeogramTextToImage": "Ideogram Text to Image", - "FluxProUltraImageNode": "Flux 1.1 [pro] Ultra Image", "MinimaxTextToVideoNode": "Minimax Text to Video", }