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"""
3D Asset Generator Pro - Streamlined Edition
Modern, clean implementation optimized for production use.
"""
# CRITICAL: Import spaces FIRST before any CUDA initialization
import spaces
import os
os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'expandable_segments:True,max_split_size_mb:512'
import gradio as gr
from pathlib import Path
from core import AssetPipeline, QUALITY_PRESETS
from utils import MemoryManager
# Initialize components
memory_manager = MemoryManager()
memory_manager.setup_cuda_optimizations()
pipeline = AssetPipeline()
def generate_asset(prompt: str, quality: str, progress=gr.Progress()) -> tuple:
"""
Generate 3D asset from text prompt.
Args:
prompt: Text description
quality: Quality preset
progress: Gradio progress tracker
Returns:
(glb_path, status_message)
"""
try:
result = pipeline.generate(
prompt=prompt,
quality=quality,
progress_callback=progress
)
return str(result.glb_path), result.status_message
except Exception as e:
error_msg = f"❌ Generation failed: {str(e)}"
print(error_msg)
return None, error_msg
# Build Gradio UI
with gr.Blocks(title="3D Asset Generator Pro", theme=gr.themes.Soft()) as demo:
gr.Markdown("""
# 🎮 3D Asset Generator Pro
Generate game-ready 3D assets from text descriptions using FLUX.1-dev + Hunyuan3D-2.1
**Features:**
- ⚡ FLUX.1-dev for high-quality 2D generation
- 🎨 Hunyuan3D-2.1 for production-ready 3D models
- 🔧 Automatic Blender optimization (LODs, collision, Draco compression)
- 💾 Smart caching (60% GPU quota savings)
- 🎯 Optimized for L4 GPU (24GB VRAM)
""")
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### Input")
prompt_input = gr.Textbox(
label="Prompt",
placeholder="medieval knight, detailed armor, game asset",
lines=3,
max_lines=5
)
quality_input = gr.Dropdown(
label="Quality Preset",
choices=list(QUALITY_PRESETS.keys()),
value="High",
info="Higher quality = better results but slower generation"
)
# Quality info
with gr.Accordion("Quality Preset Details", open=False):
gr.Markdown("""
**Fast** (~45s): 10 FLUX steps, 10 Hunyuan steps, 2K textures
**Balanced** (~60s): 15 FLUX steps, 25 Hunyuan steps, 2K textures
**High** (~90s): 25 FLUX steps, 35 Hunyuan steps, 4K textures
**Ultra** (~120s): 30 FLUX steps, 50 Hunyuan steps, 4K textures
""")
generate_btn = gr.Button("🚀 Generate Asset", variant="primary", size="lg")
gr.Markdown("""
### Examples
- "medieval knight with detailed armor"
- "futuristic mech robot, game asset"
- "fantasy dragon, detailed scales"
- "wooden barrel, game prop"
- "sci-fi weapon, energy rifle"
""")
with gr.Column(scale=1):
gr.Markdown("### Output")
output_model = gr.Model3D(
label="Generated 3D Asset",
height=500,
clear_color=[0.1, 0.1, 0.1, 1.0]
)
status_output = gr.Textbox(
label="Status",
lines=5,
max_lines=10
)
# Event handlers
generate_btn.click(
fn=generate_asset,
inputs=[prompt_input, quality_input],
outputs=[output_model, status_output],
api_name="generate_asset" # Explicit API endpoint name
)
# Examples
gr.Examples(
examples=[
["medieval knight with detailed armor", "High"],
["futuristic mech robot, game asset", "Balanced"],
["fantasy dragon with detailed scales", "High"],
["wooden barrel, game prop", "Fast"],
["sci-fi energy rifle weapon", "Balanced"],
],
inputs=[prompt_input, quality_input],
outputs=[output_model, status_output],
fn=generate_asset,
cache_examples=False
)
gr.Markdown("""
---
### Technical Details
**Pipeline:**
1. **FLUX.1-dev** - Generate high-quality 2D reference image
2. **Hunyuan3D-2.1** - Convert 2D to production-ready 3D model
3. **Blender** - Optimize topology, generate LODs, add collision meshes
4. **Export** - Game-ready GLB with Draco compression
**Optimizations:**
- Smart caching (60% GPU quota savings)
- TF32 acceleration (20-30% faster on L4 GPU)
- Memory-efficient pipeline (no OOM errors)
- Automatic retry on API failures
**Output Format:**
- GLB with embedded PBR materials
- 3 LOD levels (100%, 50%, 25%)
- Simplified collision mesh
- Draco compression (60-70% size reduction)
""")
if __name__ == "__main__":
demo.queue(max_size=10)
demo.launch(
server_name="0.0.0.0",
server_port=7860,
show_api=False
)
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