124 lines
3.5 KiB
Python
124 lines
3.5 KiB
Python
import os
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import time
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import json
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import torch
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import random
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import requests
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import numpy as np
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from PIL import Image
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from copy import deepcopy
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from .utils import clean_url, get_client_id
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def clear_remote_queue(remote_url):
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r = requests.get(f"{remote_url}/queue", timeout=4)
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r.raise_for_status()
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queue = r.json()
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to_cancel = []
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client_id = get_client_id()
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for k in queue.get("queue_pending", []):
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if k[3].get("client_id") == client_id:
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to_cancel.append(k[1]) # job UUID
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r = requests.post(
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f"{remote_url}/queue",
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json = {"delete" : to_cancel},
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timeout = 4,
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)
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r.raise_for_status()
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for k in queue.get("queue_running", []):
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if k[3].get("client_id") == client_id:
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r = requests.post(
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f"{remote_url}/interrupt",
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json = {},
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timeout = 4,
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)
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r.raise_for_status()
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break
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def get_remote_os(remote_url):
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url = f"{remote_url}/system_stats"
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r = requests.get(url)
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r.raise_for_status()
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data = r.json()
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return data["system"]["os"]
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def dispatch_to_remote(remote_url, prompt, job_id=f"{get_client_id()}-unknown"):
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### PROMPT LOGIC ###
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prompt = deepcopy(prompt)
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to_del = []
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def recursive_node_deletion(start_node):
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target_nodes = [start_node]
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if start_node not in to_del:
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to_del.append(start_node)
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while len(target_nodes) > 0:
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new_targets = []
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for target in target_nodes:
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for node in prompt.keys():
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inputs = prompt[node].get("inputs")
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if not inputs:
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continue
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for i in inputs.values():
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if type(i) == list:
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if len(i) > 0 and i[0] in to_del:
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if node not in to_del:
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to_del.append(node)
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new_targets.append(node)
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target_nodes += new_targets
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target_nodes.remove(target)
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# find current node and disable all others
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output_src = None
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for i in prompt.keys():
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if prompt[i]["class_type"].startswith("RemoteQueue"):
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if clean_url(prompt[i]["inputs"]["remote_url"]) == remote_url:
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prompt[i]["inputs"]["enabled"] = "remote"
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output_src = i
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else:
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prompt[i]["inputs"]["enabled"] = "false"
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output = None
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for i in prompt.keys():
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# only leave current fetch but replace with PreviewImage
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if prompt[i]["class_type"] == "FetchRemote":
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if prompt[i]["inputs"]["remote_info"][0] == output_src:
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output = {
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"inputs": {"images": prompt[i]["inputs"]["final_image"]},
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"class_type": 'PreviewImage',
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}
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recursive_node_deletion(i)
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# do not save output on remote
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# todo: other output types
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if prompt[i]["class_type"] in ["SaveImage", "PreviewImage"]:
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recursive_node_deletion(i)
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prompt[str(max([int(x) for x in prompt.keys()])+1)] = output
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for i in to_del: del prompt[i]
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### OS LOGIC ###
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sep_remote = "\\" if get_remote_os(remote_url) == "nt" else "/"
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sep_local = "\\" if os.name == "nt" else "/"
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sem_input_map = { # class type : input to replace
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"CheckpointLoaderSimple" : "ckpt_name",
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"CheckpointLoader" : "ckpt_name",
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"LoraLoader" : "lora_name",
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"VAELoader" : "vae_name",
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}
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if sep_remote != sep_local:
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for i in prompt.keys():
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if prompt[i]["class_type"] in sem_input_map.keys():
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key = sem_input_map[prompt[i]["class_type"]]
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prompt[i]["inputs"][key] = prompt[i]["inputs"][key].replace(sep_local, sep_remote)
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### SEND REQUEST ###
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data = {
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"prompt": prompt,
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"client_id": get_client_id(),
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"extra_data": {
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"job_id": job_id,
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}
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}
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ar = requests.post(f"{remote_url}/prompt", json=data, timeout=4)
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ar.raise_for_status()
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return
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