| import websocket |
| import uuid |
| import json |
| import urllib.request |
| import urllib.parse |
| import random |
| import logging |
|
|
| from config import SRC_LOG_LEVELS |
|
|
| log = logging.getLogger(__name__) |
| log.setLevel(SRC_LOG_LEVELS["COMFYUI"]) |
|
|
| from pydantic import BaseModel |
|
|
| from typing import Optional |
|
|
| COMFYUI_DEFAULT_PROMPT = """ |
| { |
| "3": { |
| "inputs": { |
| "seed": 0, |
| "steps": 20, |
| "cfg": 8, |
| "sampler_name": "euler", |
| "scheduler": "normal", |
| "denoise": 1, |
| "model": [ |
| "4", |
| 0 |
| ], |
| "positive": [ |
| "6", |
| 0 |
| ], |
| "negative": [ |
| "7", |
| 0 |
| ], |
| "latent_image": [ |
| "5", |
| 0 |
| ] |
| }, |
| "class_type": "KSampler", |
| "_meta": { |
| "title": "KSampler" |
| } |
| }, |
| "4": { |
| "inputs": { |
| "ckpt_name": "model.safetensors" |
| }, |
| "class_type": "CheckpointLoaderSimple", |
| "_meta": { |
| "title": "Load Checkpoint" |
| } |
| }, |
| "5": { |
| "inputs": { |
| "width": 512, |
| "height": 512, |
| "batch_size": 1 |
| }, |
| "class_type": "EmptyLatentImage", |
| "_meta": { |
| "title": "Empty Latent Image" |
| } |
| }, |
| "6": { |
| "inputs": { |
| "text": "Prompt", |
| "clip": [ |
| "4", |
| 1 |
| ] |
| }, |
| "class_type": "CLIPTextEncode", |
| "_meta": { |
| "title": "CLIP Text Encode (Prompt)" |
| } |
| }, |
| "7": { |
| "inputs": { |
| "text": "Negative Prompt", |
| "clip": [ |
| "4", |
| 1 |
| ] |
| }, |
| "class_type": "CLIPTextEncode", |
| "_meta": { |
| "title": "CLIP Text Encode (Prompt)" |
| } |
| }, |
| "8": { |
| "inputs": { |
| "samples": [ |
| "3", |
| 0 |
| ], |
| "vae": [ |
| "4", |
| 2 |
| ] |
| }, |
| "class_type": "VAEDecode", |
| "_meta": { |
| "title": "VAE Decode" |
| } |
| }, |
| "9": { |
| "inputs": { |
| "filename_prefix": "ComfyUI", |
| "images": [ |
| "8", |
| 0 |
| ] |
| }, |
| "class_type": "SaveImage", |
| "_meta": { |
| "title": "Save Image" |
| } |
| } |
| } |
| """ |
|
|
|
|
| def queue_prompt(prompt, client_id, base_url): |
| log.info("queue_prompt") |
| p = {"prompt": prompt, "client_id": client_id} |
| data = json.dumps(p).encode("utf-8") |
| req = urllib.request.Request(f"{base_url}/prompt", data=data) |
| return json.loads(urllib.request.urlopen(req).read()) |
|
|
|
|
| def get_image(filename, subfolder, folder_type, base_url): |
| log.info("get_image") |
| data = {"filename": filename, "subfolder": subfolder, "type": folder_type} |
| url_values = urllib.parse.urlencode(data) |
| with urllib.request.urlopen(f"{base_url}/view?{url_values}") as response: |
| return response.read() |
|
|
|
|
| def get_image_url(filename, subfolder, folder_type, base_url): |
| log.info("get_image") |
| data = {"filename": filename, "subfolder": subfolder, "type": folder_type} |
| url_values = urllib.parse.urlencode(data) |
| return f"{base_url}/view?{url_values}" |
|
|
|
|
| def get_history(prompt_id, base_url): |
| log.info("get_history") |
| with urllib.request.urlopen(f"{base_url}/history/{prompt_id}") as response: |
| return json.loads(response.read()) |
|
|
|
|
| def get_images(ws, prompt, client_id, base_url): |
| prompt_id = queue_prompt(prompt, client_id, base_url)["prompt_id"] |
| output_images = [] |
| while True: |
| out = ws.recv() |
| if isinstance(out, str): |
| message = json.loads(out) |
| if message["type"] == "executing": |
| data = message["data"] |
| if data["node"] is None and data["prompt_id"] == prompt_id: |
| break |
| else: |
| continue |
|
|
| history = get_history(prompt_id, base_url)[prompt_id] |
| for o in history["outputs"]: |
| for node_id in history["outputs"]: |
| node_output = history["outputs"][node_id] |
| if "images" in node_output: |
| for image in node_output["images"]: |
| url = get_image_url( |
| image["filename"], image["subfolder"], image["type"], base_url |
| ) |
| output_images.append({"url": url}) |
| return {"data": output_images} |
|
|
|
|
| class ImageGenerationPayload(BaseModel): |
| prompt: str |
| negative_prompt: Optional[str] = "" |
| steps: Optional[int] = None |
| seed: Optional[int] = None |
| width: int |
| height: int |
| n: int = 1 |
|
|
|
|
| def comfyui_generate_image( |
| model: str, payload: ImageGenerationPayload, client_id, base_url |
| ): |
| ws_url = base_url.replace("http://", "ws://").replace("https://", "wss://") |
|
|
| comfyui_prompt = json.loads(COMFYUI_DEFAULT_PROMPT) |
|
|
| comfyui_prompt["4"]["inputs"]["ckpt_name"] = model |
| comfyui_prompt["5"]["inputs"]["batch_size"] = payload.n |
| comfyui_prompt["5"]["inputs"]["width"] = payload.width |
| comfyui_prompt["5"]["inputs"]["height"] = payload.height |
|
|
| |
| comfyui_prompt["6"]["inputs"]["text"] = payload.prompt |
| comfyui_prompt["7"]["inputs"]["text"] = payload.negative_prompt |
|
|
| if payload.steps: |
| comfyui_prompt["3"]["inputs"]["steps"] = payload.steps |
|
|
| comfyui_prompt["3"]["inputs"]["seed"] = ( |
| payload.seed if payload.seed else random.randint(0, 18446744073709551614) |
| ) |
|
|
| try: |
| ws = websocket.WebSocket() |
| ws.connect(f"{ws_url}/ws?clientId={client_id}") |
| log.info("WebSocket connection established.") |
| except Exception as e: |
| log.exception(f"Failed to connect to WebSocket server: {e}") |
| return None |
|
|
| try: |
| images = get_images(ws, comfyui_prompt, client_id, base_url) |
| except Exception as e: |
| log.exception(f"Error while receiving images: {e}") |
| images = None |
|
|
| ws.close() |
|
|
| return images |
|
|