mirror of
https://github.com/open-webui/open-webui
synced 2024-11-30 07:47:34 +00:00
235 lines
5.6 KiB
Python
235 lines
5.6 KiB
Python
import websocket # NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
|
|
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 # Execution is done
|
|
else:
|
|
continue # previews are binary data
|
|
|
|
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
|
|
|
|
# set the text prompt for our positive CLIPTextEncode
|
|
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
|