Reigh-Worker

GPU worker for Reigh — processes video generation tasks using Wan2GP.

Quick Start

# 1. Create venv
python3 -m venv venv && source venv/bin/activate

# 2. Install dependencies
pip install -r Wan2GP/requirements.txt
pip install -r requirements.txt

# 3. Run worker
SUPABASE_SERVICE_ROLE_KEY="your-key" python worker.py \
    --supabase-url "https://your-project.supabase.co" \
    --worker "my-worker-001"

Get credentials from reigh.art.

Standalone Usage

Use the generation engine without Reigh for local testing or custom pipelines:

# Join two video clips with AI-generated transition
python examples/join_clips_example.py \
    --clip1 scene1.mp4 --clip2 scene2.mp4 \
    --output transition.mp4 --prompt "smooth camera glide"

# Regenerate corrupted frames
python examples/inpaint_frames_example.py \
    --video my_video.mp4 --start-frame 45 --end-frame 61 \
    --output fixed.mp4 --prompt "smooth motion"

Using HeadlessTaskQueue Directly

from headless_model_management import HeadlessTaskQueue, GenerationTask
from pathlib import Path

queue = HeadlessTaskQueue(wan_dir=str(Path(__file__).parent / "Wan2GP"), max_workers=1)
queue.start()

task = GenerationTask(
    id="my_task",
    model="wan_2_2_vace_lightning_baseline_2_2_2",
    prompt="a cat walking through a garden",
    parameters={"video_length": 81, "resolution": "896x512", "seed": 42}
)

queue.submit_task(task)
result = queue.wait_for_completion(task.id, timeout=600)
print(f"Output: {result.get('output_path')}" if result.get("success") else f"Error: {result.get('error')}")

queue.stop()

Debugging

python debug.py task <task_id>          # Investigate a task
python debug.py tasks --status Failed   # List recent failures

Project Structure

See STRUCTURE.md for detailed project layout.

Powered By

Wan2GP by deepbeepmeep — the Wan2GP/ directory contains the upstream engine.