FramePack-Studio / modules /video_queue.py
rahul7star's picture
Upload 24 files
88f15c0 verified
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