Websocket API stopt working after installing a Custom Node

Hello I Like the Programm and Thanks for your work.

I am trying to use your [ComfyUI]/[script_examples]/websockets_api_example.py
just with my changes to use it as an img2img upscaler with a florence2 model later.

But after installing the [ComfyUI-Florence2](https://github.com/kijai/ComfyUI-Florence2) node the skript stopt working an I dont know why.
In the manager I geht this masage after reinstalling the ComfyUI Destop.

Maybe this has samthing to do with this.

with the [rgthree-comfy](https://github.com/rgthree/rgthree-comfy) nodes I have no problems.

With is my skript.
```
import requests
import websocket
import uuid
import json
import io
from PIL import Image
import os

load_image_node = "10"
eingabe_ordner = "temp"
ausgabe_ordner = "temp_output"

server_address = "127.0.0.1:8000"
client_id = str(uuid.uuid4())
debug_level = 1 # 0=aus, 1=Infos, 2=Debug

# Workflow laden
with open("workflow.json", "r", encoding="utf-8") as f:
workflow_template = json.load(f)

def log(msg, level=1):
"""Hilfsfunktion für Debug-Ausgaben"""
if debug_level >= level:
print(msg)

def upscale_image(image_path, output_path):
log(f"🚀 Starte Upscale für {image_path}", 1)

# 1. Bild hochladen
with open(image_path, "rb") as f:
resp = requests.post(f"http://{server_address}/upload/image", files={"image": f})
if resp.status_code != 200:
log(f"❌ Upload fehlgeschlagen: {resp.text}", 1)
return
upload_info = resp.json()
filename = upload_info["name"]
log(f"✅ Upload erfolgreich: {filename}", 2)

# 2. Workflow anpassen
workflow = workflow_template.copy()
if load_image_node not in workflow or "inputs" not in workflow[load_image_node]:
log(f"❌ Workflow hat keinen Node {load_image_node} mit 'inputs'", 1)
return
workflow[load_image_node]["inputs"]["image"] = filename

# 3. Prompt an Server schicken
p = {"prompt": workflow, "client_id": client_id}
r = requests.post(f"http://{server_address}/prompt", json=p)
if r.status_code != 200:
log(f"❌ Prompt senden fehlgeschlagen: {r.text}", 1)
return
prompt_id = r.json()["prompt_id"]
log(f"📨 Prompt gesendet. Prompt-ID: {prompt_id}", 1)

# 4. Auf Fertigmeldung warten
ws = websocket.WebSocket()
ws.connect(f"ws://{server_address}/ws?clientId={client_id}")
log("🔌 WebSocket verbunden – warte auf Fertigmeldung...", 2)
while True:
msg = json.loads(ws.recv())
log(f"📥 WS: {msg}", 2)
if msg["type"] == "executing" and msg["data"]["node"] is None:
if msg["data"]["prompt_id"] == prompt_id:
log("✅ Workflow fertig ausgeführt", 1)
break
ws.close()

# 5. Output-Dateien aus history lesen
history_resp = requests.get(f"http://{server_address}/history/{prompt_id}")
if history_resp .status_code != 200:
log(f"❌ History konnte nicht geladen werden: {history.text}", 1)
return
history = history_resp.json()
outputs = history[prompt_id]["outputs"]
log(f"📂 Outputs im History: {list(outputs.keys())}", 2)

found = False
for node_id, node_output in outputs.items():
if "images" in node_output:
for img in node_output["images"]:
url = f"http://{server_address}/view?filename={img['filename']}&subfolder={img['subfolder']}&type={img['type']}"
log(f"⬇️ Lade Bild von {url}", 2)
img_bytes = requests.get(url).content
image = Image.open(io.BytesIO(img_bytes))
image.save(output_path)
log(f"✅ Gespeichert: {output_path}", 1)
found = True
if not found:
log("❌ Keine Bilder im Output gefunden!", 1)

# for node_id, node_output in outputs.items():
# if "images" in node_output:
# for img in node_output["images"]:
# img_bytes = requests.get(
# f"http://{server_address}/view?filename={img['filename']}&subfolder={img['subfolder']}&type={img['type']}"
# ).content
# image = Image.open(io.BytesIO(img_bytes))
# image.save(output_path)
# print(f"✅ {image_path} → {output_path}")
# return

# -------------------
# Mehrere Bilder abarbeiten
# -------------------

# sicherstellen, dass der Ausgabeordner existiert
os.makedirs(ausgabe_ordner, exist_ok=True)

for datei in os.listdir(eingabe_ordner):
if datei.lower().endswith((".jpg", ".png", ".jpeg", ".bmp", ".webp")):
input_path = os.path.join(eingabe_ordner, datei)
output_path = os.path.join(ausgabe_ordner, f"{datei}")

upscale_image(input_path, output_path)

#bilder = ["temp/frame_00001.jpg", "temp/frame_00002.jpg", "temp/frame_00003.jpg"]

#for i, pfad in enumerate(bilder, start=1):
# upscale_image(pfad, f"temp_output/frame_{i}.png")

```
and my simpel workflow that i use to test

[workflow.json](https://github.com/user-attachments/files/22046434/workflow.json)

Maybe one of you have a tip how I can uploade und get the imeages In an other way
thanks for your help.