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# This is an example that uses the websockets api to know when a prompt execution is done
# Once the prompt execution is done it downloads the images using the /history endpoint
import websocket # NOTE: websocket-client (https://github.com/websocket-client/websocket-client)
import uuid
import json
import urllib.request
import urllib.parse
import requests
from typing import Union
from fastapi import FastAPI
app = FastAPI()
server_address = "http://127.0.0.1:8188"
client_id = str(uuid.uuid4())
session = requests.Session()
def queue_prompt(prompt):
data = {"prompt": prompt, "client_id": client_id}
# data = json.dumps(p).encode('utf-8')
response = session.post("http://{}/prompt".format(server_address), json=data, headers={'User-Agent': 'Mozilla/5.0'})
return json.loads(response.content)
def get_image(filename, subfolder, folder_type):
data = {"filename": filename, "subfolder": subfolder, "type": folder_type}
url_values = urllib.parse.urlencode(data)
response = session.get("http://{}/view?{}".format(server_address, url_values),
headers={'User-Agent': 'Mozilla/5.0'})
return response.content
def get_history(prompt_id):
response = session.get("http://{}/history/{}".format(server_address, prompt_id),
headers={'User-Agent': 'Mozilla/5.0'})
return json.loads(response.content)
def get_images(ws, prompt):
global images_output
prompt_id = queue_prompt(prompt)['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)[prompt_id]
for o in history['outputs']:
for node_id in history['outputs']:
node_output = history['outputs'][node_id]
if 'images' in node_output:
images_output = []
for image in node_output['images']:
image_data = get_image(image['filename'], image['subfolder'], image['type'])
images_output.append(image_data)
output_images[node_id] = images_output
return output_images
# load workflow from file
with open("ChangeBackground_v1_Compact_api (1).json", "r", encoding="utf-8") as f:
prompt_texts = f.read()
prompt = json.loads(prompt_texts)
# set the text prompt for our positive CLIPTextEncode
# prompt["6"]["inputs"]["text"] = "masterpiece best quality man"
# set the seed for our KSampler node
# prompt["3"]["inputs"]["seed"] = 5
ws = websocket.WebSocket()
ws.connect("ws://{}/ws?clientId={}".format(server_address, client_id))
@app.get("/items")
def read_item(params: Union[str, None] = None):
params = json.loads(params)
for key in params:
value = params[key]
if key in prompt:
if "prompt" in prompt[key]["inputs"]:
prompt[key]["inputs"]["prompt"] = value
elif "text" in prompt[key]["inputs"]:
prompt[key]["inputs"]["text"] = value
elif "image" in prompt[key]["inputs"]:
prompt[key]["inputs"]["image"] = value
images = get_images(ws, prompt)
for node_id in images:
for image_data in images[node_id]:
from PIL import Image
import io
image = Image.open(io.BytesIO(image_data))
image.show()
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