|
|
|
|
@ -3,8 +3,10 @@
|
|
|
|
|
DaSiWa I2V/FLF2V API Server для ComfyUI.
|
|
|
|
|
Работает рядом с ComfyUI на той же машине.
|
|
|
|
|
|
|
|
|
|
Принимает HTTP запросы с HMAC авторизацией,
|
|
|
|
|
отправляет workflow в ComfyUI, возвращает видео.
|
|
|
|
|
Асинхронный API (как RunPod):
|
|
|
|
|
POST /run → {"id": "job_id", "status": "IN_QUEUE"}
|
|
|
|
|
GET /status/ID → {"id": ..., "status": "IN_QUEUE|IN_PROGRESS|COMPLETED|FAILED", "output": ...}
|
|
|
|
|
GET /health → {"status": "ok", "comfyui": "ok", "queue": 0}
|
|
|
|
|
"""
|
|
|
|
|
|
|
|
|
|
import os
|
|
|
|
|
@ -18,6 +20,8 @@ import random
|
|
|
|
|
import logging
|
|
|
|
|
import binascii
|
|
|
|
|
import subprocess
|
|
|
|
|
import threading
|
|
|
|
|
import queue
|
|
|
|
|
import urllib.request
|
|
|
|
|
import urllib.parse
|
|
|
|
|
import websocket as ws_client
|
|
|
|
|
@ -69,6 +73,14 @@ used_nonces = set()
|
|
|
|
|
# WebSocket client ID
|
|
|
|
|
ws_client_id = str(uuid.uuid4())
|
|
|
|
|
|
|
|
|
|
# ============================================================================
|
|
|
|
|
# Job Queue (асинхронная очередь как в RunPod)
|
|
|
|
|
# ============================================================================
|
|
|
|
|
|
|
|
|
|
job_queue = queue.Queue()
|
|
|
|
|
jobs = {} # job_id -> {status, input, output, error, created_at, started_at, completed_at}
|
|
|
|
|
jobs_lock = threading.Lock()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# ============================================================================
|
|
|
|
|
# Утилиты
|
|
|
|
|
@ -185,6 +197,162 @@ def generate_video(prompt):
|
|
|
|
|
return None
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# ============================================================================
|
|
|
|
|
# Background Worker (обработка задач из очереди)
|
|
|
|
|
# ============================================================================
|
|
|
|
|
|
|
|
|
|
def build_prompt(job_input, image_path, last_image_path, use_flf2v):
|
|
|
|
|
"""Загружает workflow и патчит параметрами задачи."""
|
|
|
|
|
with open(WORKFLOW_FILE, "r") as f:
|
|
|
|
|
prompt = json.load(f)
|
|
|
|
|
|
|
|
|
|
width = to_nearest_multiple_of_16(job_input.get("width", 528))
|
|
|
|
|
height = to_nearest_multiple_of_16(job_input.get("height", 768))
|
|
|
|
|
length = job_input.get("length", 81)
|
|
|
|
|
steps = job_input.get("steps", 4)
|
|
|
|
|
cfg = job_input.get("cfg", 1.0)
|
|
|
|
|
seed = job_input.get("seed", -1)
|
|
|
|
|
fps = job_input.get("fps", 16)
|
|
|
|
|
sampler_name = job_input.get("sampler_name", "euler")
|
|
|
|
|
scheduler = job_input.get("scheduler", "linear_quadratic")
|
|
|
|
|
|
|
|
|
|
if seed == -1:
|
|
|
|
|
seed = random.randint(0, 2**63 - 1)
|
|
|
|
|
|
|
|
|
|
# Node 5: Positive prompt
|
|
|
|
|
prompt["5"]["inputs"]["text"] = job_input.get("prompt", "")
|
|
|
|
|
|
|
|
|
|
# Node 6: Negative prompt (use default or custom)
|
|
|
|
|
negative_prompt = job_input.get("negative_prompt", prompt["6"]["inputs"]["text"])
|
|
|
|
|
prompt["6"]["inputs"]["text"] = negative_prompt
|
|
|
|
|
|
|
|
|
|
# Node 7: Load first frame image
|
|
|
|
|
prompt["7"]["inputs"]["image"] = image_path
|
|
|
|
|
|
|
|
|
|
# Node 15: Load last frame image (for FLF2V mode)
|
|
|
|
|
if use_flf2v and last_image_path:
|
|
|
|
|
prompt["15"]["inputs"]["image"] = last_image_path
|
|
|
|
|
logger.info(f"🎬 FLF2V: last frame = {last_image_path}")
|
|
|
|
|
else:
|
|
|
|
|
# I2V mode: switch to WanImageToVideo, remove end_image
|
|
|
|
|
prompt["8"]["class_type"] = "WanImageToVideo"
|
|
|
|
|
if "end_image" in prompt["8"]["inputs"]:
|
|
|
|
|
del prompt["8"]["inputs"]["end_image"]
|
|
|
|
|
if "15" in prompt:
|
|
|
|
|
del prompt["15"]
|
|
|
|
|
logger.info("🎬 I2V: single image mode")
|
|
|
|
|
|
|
|
|
|
# Node 8: WanFirstLastFrameToVideo / WanImageToVideo
|
|
|
|
|
prompt["8"]["inputs"]["width"] = width
|
|
|
|
|
prompt["8"]["inputs"]["height"] = height
|
|
|
|
|
prompt["8"]["inputs"]["length"] = length
|
|
|
|
|
|
|
|
|
|
# Node 11: KSampler High
|
|
|
|
|
prompt["11"]["inputs"]["noise_seed"] = seed
|
|
|
|
|
prompt["11"]["inputs"]["steps"] = steps
|
|
|
|
|
prompt["11"]["inputs"]["cfg"] = cfg
|
|
|
|
|
prompt["11"]["inputs"]["sampler_name"] = sampler_name
|
|
|
|
|
prompt["11"]["inputs"]["scheduler"] = scheduler
|
|
|
|
|
prompt["11"]["inputs"]["end_at_step"] = steps // 2
|
|
|
|
|
|
|
|
|
|
# Node 12: KSampler Low
|
|
|
|
|
prompt["12"]["inputs"]["noise_seed"] = seed
|
|
|
|
|
prompt["12"]["inputs"]["steps"] = steps
|
|
|
|
|
prompt["12"]["inputs"]["cfg"] = cfg
|
|
|
|
|
prompt["12"]["inputs"]["sampler_name"] = sampler_name
|
|
|
|
|
prompt["12"]["inputs"]["scheduler"] = scheduler
|
|
|
|
|
prompt["12"]["inputs"]["start_at_step"] = steps // 2
|
|
|
|
|
|
|
|
|
|
# Node 14: Video output
|
|
|
|
|
prompt["14"]["inputs"]["frame_rate"] = fps
|
|
|
|
|
|
|
|
|
|
return prompt, seed, width, height
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def cleanup_comfy_output():
|
|
|
|
|
"""Очистка output директории ComfyUI."""
|
|
|
|
|
try:
|
|
|
|
|
if os.path.exists(COMFY_OUTPUT_DIR):
|
|
|
|
|
for fname in os.listdir(COMFY_OUTPUT_DIR):
|
|
|
|
|
fpath = os.path.join(COMFY_OUTPUT_DIR, fname)
|
|
|
|
|
if os.path.isfile(fpath):
|
|
|
|
|
os.unlink(fpath)
|
|
|
|
|
elif os.path.isdir(fpath):
|
|
|
|
|
shutil.rmtree(fpath)
|
|
|
|
|
except Exception:
|
|
|
|
|
pass
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def worker_loop():
|
|
|
|
|
"""Фоновый воркер — берёт задачи из очереди и выполняет по одной."""
|
|
|
|
|
logger.info("⚙️ Worker thread started")
|
|
|
|
|
while True:
|
|
|
|
|
job_id = job_queue.get() # блокируется пока нет задач
|
|
|
|
|
with jobs_lock:
|
|
|
|
|
job = jobs.get(job_id)
|
|
|
|
|
if not job:
|
|
|
|
|
continue
|
|
|
|
|
|
|
|
|
|
logger.info("=" * 60)
|
|
|
|
|
logger.info(f"🎬 Job {job_id}: Начинаем генерацию")
|
|
|
|
|
logger.info("=" * 60)
|
|
|
|
|
|
|
|
|
|
with jobs_lock:
|
|
|
|
|
job["status"] = "IN_PROGRESS"
|
|
|
|
|
job["started_at"] = time.time()
|
|
|
|
|
|
|
|
|
|
job_input = job["input"]
|
|
|
|
|
temp_dir = job["temp_dir"]
|
|
|
|
|
|
|
|
|
|
try:
|
|
|
|
|
# Обработка изображений
|
|
|
|
|
image_path, has_image = process_image_input(job_input, "image", temp_dir)
|
|
|
|
|
if not has_image:
|
|
|
|
|
raise ValueError("No input image provided")
|
|
|
|
|
|
|
|
|
|
last_image_path, use_flf2v = process_image_input(job_input, "last_image", temp_dir)
|
|
|
|
|
mode = "FLF2V" if use_flf2v else "I2V"
|
|
|
|
|
logger.info(f"🎬 Job {job_id}: Режим {mode}")
|
|
|
|
|
|
|
|
|
|
# Сборка промпта
|
|
|
|
|
prompt, seed, width, height = build_prompt(job_input, image_path, last_image_path, use_flf2v)
|
|
|
|
|
logger.info(f"📐 Job {job_id}: {width}x{height}, seed {seed}")
|
|
|
|
|
|
|
|
|
|
# Генерация
|
|
|
|
|
video_b64 = generate_video(prompt)
|
|
|
|
|
|
|
|
|
|
if not video_b64:
|
|
|
|
|
raise RuntimeError("Video generation failed — no output from ComfyUI")
|
|
|
|
|
|
|
|
|
|
elapsed = time.time() - job["started_at"]
|
|
|
|
|
logger.info(f"✅ Job {job_id}: Видео готово за {elapsed:.1f}s")
|
|
|
|
|
|
|
|
|
|
with jobs_lock:
|
|
|
|
|
job["status"] = "COMPLETED"
|
|
|
|
|
job["completed_at"] = time.time()
|
|
|
|
|
job["output"] = {
|
|
|
|
|
"video": video_b64,
|
|
|
|
|
"seed": seed,
|
|
|
|
|
"mode": mode,
|
|
|
|
|
"elapsed": round(elapsed, 1)
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(f"❌ Job {job_id}: {e}", exc_info=True)
|
|
|
|
|
with jobs_lock:
|
|
|
|
|
job["status"] = "FAILED"
|
|
|
|
|
job["completed_at"] = time.time()
|
|
|
|
|
job["error"] = str(e)
|
|
|
|
|
|
|
|
|
|
finally:
|
|
|
|
|
# Очистка
|
|
|
|
|
if os.path.exists(temp_dir):
|
|
|
|
|
shutil.rmtree(temp_dir, ignore_errors=True)
|
|
|
|
|
cleanup_comfy_output()
|
|
|
|
|
|
|
|
|
|
job_queue.task_done()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# ============================================================================
|
|
|
|
|
# API Endpoints
|
|
|
|
|
# ============================================================================
|
|
|
|
|
@ -222,146 +390,85 @@ def health():
|
|
|
|
|
return jsonify({
|
|
|
|
|
"status": "ok",
|
|
|
|
|
"comfyui": comfy_status,
|
|
|
|
|
"queue": job_queue.qsize(),
|
|
|
|
|
"timestamp": int(time.time())
|
|
|
|
|
})
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
@app.route("/generate", methods=["POST"])
|
|
|
|
|
def generate():
|
|
|
|
|
"""Основной endpoint для генерации видео."""
|
|
|
|
|
start_time = time.time()
|
|
|
|
|
|
|
|
|
|
@app.route("/run", methods=["POST"])
|
|
|
|
|
def run_job():
|
|
|
|
|
"""Отправляет задачу в очередь. Возвращает job_id сразу."""
|
|
|
|
|
job_input = request.json or {}
|
|
|
|
|
|
|
|
|
|
logger.info("=" * 60)
|
|
|
|
|
logger.info("🎬 Новый запрос на генерацию")
|
|
|
|
|
logger.info("=" * 60)
|
|
|
|
|
# Валидация: должно быть хотя бы одно изображение
|
|
|
|
|
has_image = any(k in job_input and job_input[k]
|
|
|
|
|
for k in ("image_base64", "image_url", "image_path"))
|
|
|
|
|
if not has_image:
|
|
|
|
|
return jsonify({"error": "No input image. Use image_base64, image_url, or image_path"}), 400
|
|
|
|
|
|
|
|
|
|
job_id = str(uuid.uuid4())
|
|
|
|
|
temp_dir = os.path.join("/tmp", f"job_{job_id[:8]}")
|
|
|
|
|
|
|
|
|
|
# Логирование (без base64)
|
|
|
|
|
log_input = {k: (f"[{len(v)}chars]" if k.endswith("_base64") else v)
|
|
|
|
|
for k, v in job_input.items()}
|
|
|
|
|
logger.info(f"📥 Job {job_id}: поставлен в очередь")
|
|
|
|
|
logger.info(f" Параметры: {json.dumps(log_input, ensure_ascii=False)}")
|
|
|
|
|
|
|
|
|
|
with jobs_lock:
|
|
|
|
|
jobs[job_id] = {
|
|
|
|
|
"status": "IN_QUEUE",
|
|
|
|
|
"input": job_input,
|
|
|
|
|
"temp_dir": temp_dir,
|
|
|
|
|
"output": None,
|
|
|
|
|
"error": None,
|
|
|
|
|
"created_at": time.time(),
|
|
|
|
|
"started_at": None,
|
|
|
|
|
"completed_at": None,
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
job_queue.put(job_id)
|
|
|
|
|
|
|
|
|
|
# Логирование (без base64 данных)
|
|
|
|
|
log_input = {k: v for k, v in job_input.items()
|
|
|
|
|
if not k.endswith("_base64")}
|
|
|
|
|
logger.info(f"Параметры: {json.dumps(log_input, ensure_ascii=False)}")
|
|
|
|
|
return jsonify({
|
|
|
|
|
"id": job_id,
|
|
|
|
|
"status": "IN_QUEUE"
|
|
|
|
|
})
|
|
|
|
|
|
|
|
|
|
task_id = f"task_{uuid.uuid4().hex[:8]}"
|
|
|
|
|
temp_dir = os.path.join("/tmp", task_id)
|
|
|
|
|
|
|
|
|
|
try:
|
|
|
|
|
# === Обработка изображений ===
|
|
|
|
|
image_path, has_image = process_image_input(job_input, "image", temp_dir)
|
|
|
|
|
if not has_image:
|
|
|
|
|
return jsonify({"error": "No input image provided. Use image_base64, image_url, or image_path"}), 400
|
|
|
|
|
|
|
|
|
|
last_image_path, use_flf2v = process_image_input(job_input, "last_image", temp_dir)
|
|
|
|
|
|
|
|
|
|
mode = "FLF2V" if use_flf2v else "I2V"
|
|
|
|
|
logger.info(f"🎬 Режим: {mode}")
|
|
|
|
|
|
|
|
|
|
# === Загрузка workflow ===
|
|
|
|
|
if not os.path.exists(WORKFLOW_FILE):
|
|
|
|
|
return jsonify({"error": f"Workflow file not found: {WORKFLOW_FILE}"}), 500
|
|
|
|
|
|
|
|
|
|
with open(WORKFLOW_FILE, "r") as f:
|
|
|
|
|
prompt = json.load(f)
|
|
|
|
|
|
|
|
|
|
# === Параметры генерации ===
|
|
|
|
|
width = to_nearest_multiple_of_16(job_input.get("width", 528))
|
|
|
|
|
height = to_nearest_multiple_of_16(job_input.get("height", 768))
|
|
|
|
|
length = job_input.get("length", 81)
|
|
|
|
|
steps = job_input.get("steps", 4)
|
|
|
|
|
cfg = job_input.get("cfg", 1.0)
|
|
|
|
|
seed = job_input.get("seed", -1)
|
|
|
|
|
fps = job_input.get("fps", 16)
|
|
|
|
|
sampler_name = job_input.get("sampler_name", "euler")
|
|
|
|
|
scheduler = job_input.get("scheduler", "linear_quadratic")
|
|
|
|
|
|
|
|
|
|
if seed == -1:
|
|
|
|
|
seed = random.randint(0, 2**63 - 1)
|
|
|
|
|
|
|
|
|
|
logger.info(f"📐 {width}x{height}, {length} frames, {steps} steps, CFG {cfg}, seed {seed}")
|
|
|
|
|
|
|
|
|
|
# === Заполнение workflow ===
|
|
|
|
|
|
|
|
|
|
# Positive prompt
|
|
|
|
|
prompt["5"]["inputs"]["text"] = job_input.get("prompt", "")
|
|
|
|
|
|
|
|
|
|
# Negative prompt
|
|
|
|
|
negative_prompt = job_input.get("negative_prompt", prompt["6"]["inputs"]["text"])
|
|
|
|
|
prompt["6"]["inputs"]["text"] = negative_prompt
|
|
|
|
|
|
|
|
|
|
# First frame image
|
|
|
|
|
prompt["7"]["inputs"]["image"] = image_path
|
|
|
|
|
|
|
|
|
|
# FLF2V / I2V mode
|
|
|
|
|
if use_flf2v and last_image_path:
|
|
|
|
|
prompt["15"]["inputs"]["image"] = last_image_path
|
|
|
|
|
logger.info(f"🎬 FLF2V: last frame = {last_image_path}")
|
|
|
|
|
else:
|
|
|
|
|
prompt["8"]["class_type"] = "WanImageToVideo"
|
|
|
|
|
if "end_image" in prompt["8"]["inputs"]:
|
|
|
|
|
del prompt["8"]["inputs"]["end_image"]
|
|
|
|
|
if "15" in prompt:
|
|
|
|
|
del prompt["15"]
|
|
|
|
|
logger.info("🎬 I2V: single image mode")
|
|
|
|
|
|
|
|
|
|
# Video dimensions
|
|
|
|
|
prompt["8"]["inputs"]["width"] = width
|
|
|
|
|
prompt["8"]["inputs"]["height"] = height
|
|
|
|
|
prompt["8"]["inputs"]["length"] = length
|
|
|
|
|
|
|
|
|
|
# KSampler High
|
|
|
|
|
prompt["11"]["inputs"]["noise_seed"] = seed
|
|
|
|
|
prompt["11"]["inputs"]["steps"] = steps
|
|
|
|
|
prompt["11"]["inputs"]["cfg"] = cfg
|
|
|
|
|
prompt["11"]["inputs"]["sampler_name"] = sampler_name
|
|
|
|
|
prompt["11"]["inputs"]["scheduler"] = scheduler
|
|
|
|
|
prompt["11"]["inputs"]["end_at_step"] = steps // 2
|
|
|
|
|
|
|
|
|
|
# KSampler Low
|
|
|
|
|
prompt["12"]["inputs"]["noise_seed"] = seed
|
|
|
|
|
prompt["12"]["inputs"]["steps"] = steps
|
|
|
|
|
prompt["12"]["inputs"]["cfg"] = cfg
|
|
|
|
|
prompt["12"]["inputs"]["sampler_name"] = sampler_name
|
|
|
|
|
prompt["12"]["inputs"]["scheduler"] = scheduler
|
|
|
|
|
prompt["12"]["inputs"]["start_at_step"] = steps // 2
|
|
|
|
|
|
|
|
|
|
# Video output
|
|
|
|
|
prompt["14"]["inputs"]["frame_rate"] = fps
|
|
|
|
|
|
|
|
|
|
# === Генерация ===
|
|
|
|
|
video_b64 = generate_video(prompt)
|
|
|
|
|
|
|
|
|
|
if not video_b64:
|
|
|
|
|
return jsonify({"error": "Video generation failed — no output"}), 500
|
|
|
|
|
|
|
|
|
|
elapsed = time.time() - start_time
|
|
|
|
|
logger.info(f"✅ Видео сгенерировано за {elapsed:.1f}s")
|
|
|
|
|
|
|
|
|
|
return jsonify({
|
|
|
|
|
"video": video_b64,
|
|
|
|
|
"seed": seed,
|
|
|
|
|
"mode": mode,
|
|
|
|
|
"elapsed": round(elapsed, 1)
|
|
|
|
|
})
|
|
|
|
|
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(f"❌ Ошибка: {e}", exc_info=True)
|
|
|
|
|
return jsonify({"error": str(e)}), 500
|
|
|
|
|
|
|
|
|
|
finally:
|
|
|
|
|
# Очистка temp файлов
|
|
|
|
|
if os.path.exists(temp_dir):
|
|
|
|
|
shutil.rmtree(temp_dir, ignore_errors=True)
|
|
|
|
|
# Очистка output ComfyUI
|
|
|
|
|
try:
|
|
|
|
|
if os.path.exists(COMFY_OUTPUT_DIR):
|
|
|
|
|
for fname in os.listdir(COMFY_OUTPUT_DIR):
|
|
|
|
|
fpath = os.path.join(COMFY_OUTPUT_DIR, fname)
|
|
|
|
|
if os.path.isfile(fpath):
|
|
|
|
|
os.unlink(fpath)
|
|
|
|
|
elif os.path.isdir(fpath):
|
|
|
|
|
shutil.rmtree(fpath)
|
|
|
|
|
except Exception:
|
|
|
|
|
pass
|
|
|
|
|
@app.route("/status/<job_id>", methods=["GET"])
|
|
|
|
|
def job_status(job_id):
|
|
|
|
|
"""Получить статус задачи. Когда COMPLETED — возвращает результат."""
|
|
|
|
|
with jobs_lock:
|
|
|
|
|
job = jobs.get(job_id)
|
|
|
|
|
|
|
|
|
|
if not job:
|
|
|
|
|
return jsonify({"error": "Job not found"}), 404
|
|
|
|
|
|
|
|
|
|
response = {
|
|
|
|
|
"id": job_id,
|
|
|
|
|
"status": job["status"],
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
if job["status"] == "COMPLETED":
|
|
|
|
|
response["output"] = job["output"]
|
|
|
|
|
elif job["status"] == "FAILED":
|
|
|
|
|
response["error"] = job["error"]
|
|
|
|
|
|
|
|
|
|
return jsonify(response)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
@app.route("/purge/<job_id>", methods=["POST"])
|
|
|
|
|
def purge_job(job_id):
|
|
|
|
|
"""Удалить завершённую задачу из памяти (освободить RAM от base64 видео)."""
|
|
|
|
|
with jobs_lock:
|
|
|
|
|
job = jobs.get(job_id)
|
|
|
|
|
if not job:
|
|
|
|
|
return jsonify({"error": "Job not found"}), 404
|
|
|
|
|
if job["status"] in ("IN_QUEUE", "IN_PROGRESS"):
|
|
|
|
|
return jsonify({"error": "Cannot purge active job"}), 400
|
|
|
|
|
del jobs[job_id]
|
|
|
|
|
|
|
|
|
|
return jsonify({"id": job_id, "purged": True})
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
# ============================================================================
|
|
|
|
|
@ -370,10 +477,15 @@ def generate():
|
|
|
|
|
|
|
|
|
|
if __name__ == "__main__":
|
|
|
|
|
logger.info("=" * 60)
|
|
|
|
|
logger.info("🚀 DaSiWa API Server")
|
|
|
|
|
logger.info("🚀 DaSiWa API Server (async worker mode)")
|
|
|
|
|
logger.info(f" ComfyUI: http://{COMFY_HOST}:{COMFY_PORT}")
|
|
|
|
|
logger.info(f" API Port: {API_PORT}")
|
|
|
|
|
logger.info(f" Workflow: {WORKFLOW_FILE}")
|
|
|
|
|
logger.info(" Endpoints:")
|
|
|
|
|
logger.info(" POST /run → поставить задачу")
|
|
|
|
|
logger.info(" GET /status/<id> → статус / результат")
|
|
|
|
|
logger.info(" POST /purge/<id> → удалить задачу из памяти")
|
|
|
|
|
logger.info(" GET /health → здоровье")
|
|
|
|
|
logger.info("=" * 60)
|
|
|
|
|
|
|
|
|
|
# Проверяем подключение к ComfyUI
|
|
|
|
|
@ -381,6 +493,11 @@ if __name__ == "__main__":
|
|
|
|
|
urllib.request.urlopen(f"http://{COMFY_HOST}:{COMFY_PORT}/", timeout=5)
|
|
|
|
|
logger.info("✅ ComfyUI доступен")
|
|
|
|
|
except Exception:
|
|
|
|
|
logger.warning("⚠️ ComfyUI недоступен — запросы будут ждать")
|
|
|
|
|
logger.warning("⚠️ ComfyUI недоступен — запросы будут ждать"
|
|
|
|
|
" пока ComfyUI запустится")
|
|
|
|
|
|
|
|
|
|
# Запуск фонового воркера
|
|
|
|
|
worker_thread = threading.Thread(target=worker_loop, daemon=True)
|
|
|
|
|
worker_thread.start()
|
|
|
|
|
|
|
|
|
|
app.run(host="0.0.0.0", port=API_PORT, debug=False)
|
|
|
|
|
|
