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import threading
import time
import uuid
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, Any, Optional, List
import queue as queue_module # Renamed to avoid conflicts
import io
import base64
from PIL import Image
import numpy as np
from diffusers_helper.thread_utils import AsyncStream
# Simple LIFO queue implementation to avoid dependency on queue.LifoQueue
class SimpleLifoQueue:
def __init__(self):
self._queue = []
self._mutex = threading.Lock()
self._not_empty = threading.Condition(self._mutex)
def put(self, item):
with self._mutex:
self._queue.append(item)
self._not_empty.notify()
def get(self):
with self._not_empty:
while not self._queue:
self._not_empty.wait()
return self._queue.pop()
def task_done(self):
pass # For compatibility with queue.Queue
class JobStatus(Enum):
PENDING = "pending"
RUNNING = "running"
COMPLETED = "completed"
FAILED = "failed"
CANCELLED = "cancelled"
@dataclass
class Job:
id: str
params: Dict[str, Any]
status: JobStatus = JobStatus.PENDING
created_at: float = field(default_factory=time.time)
started_at: Optional[float] = None
completed_at: Optional[float] = None
error: Optional[str] = None
result: Optional[str] = None
progress_data: Optional[Dict] = None
queue_position: Optional[int] = None
stream: Optional[Any] = None
input_image: Optional[np.ndarray] = None
latent_type: Optional[str] = None
thumbnail: Optional[str] = None
generation_type: Optional[str] = None # Added generation_type
def __post_init__(self):
# Store generation type
self.generation_type = self.params.get('model_type', 'Original') # Initialize generation_type
# Store input image or latent type
if 'input_image' in self.params and self.params['input_image'] is not None:
self.input_image = self.params['input_image']
# Create thumbnail
img = Image.fromarray(self.input_image)
img.thumbnail((100, 100))
buffered = io.BytesIO()
img.save(buffered, format="PNG")
self.thumbnail = f"data:image/png;base64,{base64.b64encode(buffered.getvalue()).decode()}"
elif 'latent_type' in self.params:
self.latent_type = self.params['latent_type']
# Create a colored square based on latent type
color_map = {
"Black": (0, 0, 0),
"White": (255, 255, 255),
"Noise": (128, 128, 128),
"Green Screen": (0, 177, 64)
}
color = color_map.get(self.latent_type, (0, 0, 0))
img = Image.new('RGB', (100, 100), color)
buffered = io.BytesIO()
img.save(buffered, format="PNG")
self.thumbnail = f"data:image/png;base64,{base64.b64encode(buffered.getvalue()).decode()}"
class VideoJobQueue:
def __init__(self):
self.queue = queue_module.Queue() # Using standard Queue instead of LifoQueue
self.jobs = {}
self.current_job = None
self.lock = threading.Lock()
self.worker_thread = threading.Thread(target=self._worker_loop, daemon=True)
self.worker_thread.start()
self.worker_function = None # Will be set from outside
self.is_processing = False # Flag to track if we're currently processing a job
def set_worker_function(self, worker_function):
"""Set the worker function to use for processing jobs"""
self.worker_function = worker_function
def add_job(self, params):
"""Add a job to the queue and return its ID"""
job_id = str(uuid.uuid4())
job = Job(
id=job_id,
params=params,
status=JobStatus.PENDING,
created_at=time.time(),
progress_data={},
stream=AsyncStream()
)
with self.lock:
print(f"Adding job {job_id} to queue, current job is {self.current_job.id if self.current_job else 'None'}")
self.jobs[job_id] = job
self.queue.put(job_id)
return job_id
def get_job(self, job_id):
"""Get job by ID"""
with self.lock:
return self.jobs.get(job_id)
def get_all_jobs(self):
"""Get all jobs"""
with self.lock:
return list(self.jobs.values())
def cancel_job(self, job_id):
"""Cancel a pending job"""
with self.lock:
job = self.jobs.get(job_id)
if job and job.status == JobStatus.PENDING:
job.status = JobStatus.CANCELLED
job.completed_at = time.time() # Mark completion time
return True
elif job and job.status == JobStatus.RUNNING:
# Send cancel signal to the job's stream
job.stream.input_queue.push('end')
# Mark job as cancelled (this will be confirmed when the worker processes the end signal)
job.status = JobStatus.CANCELLED
job.completed_at = time.time() # Mark completion time
return True
return False
def get_queue_position(self, job_id):
"""Get position in queue (0 = currently running)"""
with self.lock:
job = self.jobs.get(job_id)
if not job:
return None
if job.status == JobStatus.RUNNING:
return 0
if job.status != JobStatus.PENDING:
return None
# Count pending jobs ahead in queue
position = 1 # Start at 1 because 0 means running
for j in self.jobs.values():
if (j.status == JobStatus.PENDING and
j.created_at < job.created_at):
position += 1
return position
def update_job_progress(self, job_id, progress_data):
"""Update job progress data"""
with self.lock:
job = self.jobs.get(job_id)
if job:
job.progress_data = progress_data
def _worker_loop(self):
"""Worker thread that processes jobs from the queue"""
while True:
try:
# Get the next job ID from the queue
try:
job_id = self.queue.get(block=True, timeout=1.0) # Use timeout to allow periodic checks
except queue_module.Empty:
# No jobs in queue, just continue the loop
continue
with self.lock:
job = self.jobs.get(job_id)
if not job:
self.queue.task_done()
continue
# Skip cancelled jobs
if job.status == JobStatus.CANCELLED:
self.queue.task_done()
continue
# If we're already processing a job, wait for it to complete
if self.is_processing:
# Put the job back in the queue
self.queue.put(job_id)
self.queue.task_done()
time.sleep(0.1) # Small delay to prevent busy waiting
continue
print(f"Starting job {job_id}, current job was {self.current_job.id if self.current_job else 'None'}")
job.status = JobStatus.RUNNING
job.started_at = time.time()
self.current_job = job
self.is_processing = True
job_completed = False
try:
if self.worker_function is None:
raise ValueError("Worker function not set. Call set_worker_function() first.")
# Start the worker function with the job parameters
from diffusers_helper.thread_utils import async_run
async_run(
self.worker_function,
**job.params,
job_stream=job.stream
)
# Process the results from the stream
output_filename = None
# Set a maximum time to wait for the job to complete
max_wait_time = 3600 # 1 hour in seconds
start_time = time.time()
last_activity_time = time.time()
while True:
# Check if job has been cancelled before processing next output
with self.lock:
if job.status == JobStatus.CANCELLED:
print(f"Job {job_id} was cancelled, breaking out of processing loop")
job_completed = True
break
# Check if we've been waiting too long without any activity
current_time = time.time()
if current_time - start_time > max_wait_time:
print(f"Job {job_id} timed out after {max_wait_time} seconds")
with self.lock:
job.status = JobStatus.FAILED
job.error = "Job timed out"
job.completed_at = time.time()
job_completed = True
break
# Check for inactivity (no output for a while)
if current_time - last_activity_time > 60: # 1 minute of inactivity
print(f"Checking if job {job_id} is still active...")
# Just a periodic check, don't break yet
try:
# Try to get data from the queue with a non-blocking approach
flag, data = job.stream.output_queue.next()
# Update activity time since we got some data
last_activity_time = time.time()
if flag == 'file':
output_filename = data
with self.lock:
job.result = output_filename
elif flag == 'progress':
preview, desc, html = data
with self.lock:
job.progress_data = {
'preview': preview,
'desc': desc,
'html': html
}
elif flag == 'end':
print(f"Received end signal for job {job_id}")
job_completed = True
break
except IndexError:
# Queue is empty, wait a bit and try again
time.sleep(0.1)
continue
except Exception as e:
print(f"Error processing job output: {e}")
# Wait a bit before trying again
time.sleep(0.1)
continue
except Exception as e:
import traceback
traceback.print_exc()
print(f"Error processing job {job_id}: {e}")
with self.lock:
job.status = JobStatus.FAILED
job.error = str(e)
job.completed_at = time.time()
job_completed = True
finally:
with self.lock:
# Make sure we properly clean up the job state
if job.status == JobStatus.RUNNING:
if job_completed:
job.status = JobStatus.COMPLETED
else:
# Something went wrong but we didn't mark it as completed
job.status = JobStatus.FAILED
job.error = "Job processing was interrupted"
job.completed_at = time.time()
print(f"Finishing job {job_id} with status {job.status}")
self.is_processing = False
self.current_job = None
self.queue.task_done()
except Exception as e:
import traceback
traceback.print_exc()
print(f"Error in worker loop: {e}")
# Make sure we reset processing state if there was an error
with self.lock:
self.is_processing = False
if self.current_job:
self.current_job.status = JobStatus.FAILED
self.current_job.error = f"Worker loop error: {str(e)}"
self.current_job.completed_at = time.time()
self.current_job = None
time.sleep(0.5) # Prevent tight loop on error
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