fix launch for hf

README.md

@@ -5,10 +5,59 @@ colorFrom: pink
 colorTo: red
 sdk: gradio
 sdk_version: 5.22.0
-app_file: app.py
+app_file: main.py
 pinned: false
-license: other
-short_description: Generate and edit images
+license: mit
+short_description: Generate and edit images with diffusion models and ControlNet
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Diffusion Models App
+
+A unified interface for text-to-image and image-to-image generation using Hugging Face models.
+
+## Features
+
+- 🖼️ **Text to Image**: Generate images from text prompts
+- 🔄 **Image to Image**: Transform images using text prompts
+- 🧠 **ControlNet Support**: Built-in ControlNet depth model for enhanced image transformations
+- 🌐 **Flexible Models**: Use inference endpoints or on-device models
+- 🚀 **Dual Interface**: Web UI and API endpoints
+
+## Deployment Notes
+
+### IMPORTANT: Using ControlNet on Hugging Face Spaces
+
+For ControlNet to work correctly:
+
+1. Import `spaces` before any `torch` or CUDA-related imports
+2. Select GPU hardware in Space settings
+3. Add your HF_TOKEN as a Repository Secret (Settings → Repository Secrets)
+4. Do NOT commit any sensitive tokens to the repository
+
+If you encounter CUDA initialization errors, ensure spaces package is imported first.
+
+## Usage
+
+### Text to Image
+1. Enter your text prompt
+2. Optionally provide a negative prompt to exclude unwanted elements
+3. Choose a model or use the default
+4. Click "Generate Image"
+
+### Image to Image
+1. Upload an image
+2. Enter a prompt to guide the transformation
+3. Choose between HF inference API or ControlNet on-device model
+4. Click "Transform Image"
+
+---
+
+tags:
+- diffusers
+- stable-diffusion
+- text-to-image
+- image-to-image
+- depth-estimation
+- controlnet
+- spaces
+- huggingface-hub

controlnet_pipeline.py

@@ -1,3 +1,7 @@
+# Import spaces before any CUDA/torch imports
+import spaces
+
+# Other imports below
 import torch
 import numpy as np
 from PIL import Image
@@ -6,7 +10,6 @@ from diffusers import StableDiffusionControlNetPipeline, ControlNetModel, UniPCM
 from diffusers.utils import load_image
 import os
 import huggingface_hub
-import spaces
 import config
 
 class ControlNetPipeline:

main.py

@@ -36,13 +36,8 @@ def main():
     
     # Check if HF_TOKEN is set
     if not config.HF_TOKEN:
-        print("\n")
-        print("*" * 80)
-        print("WARNING: HF_TOKEN environment variable is not set!")
-        print("* For local development: Create a .env file with HF_TOKEN=your_token")
-        print("* For Hugging Face Spaces: Add HF_TOKEN as a secret in your Space settings")
-        print("*" * 80)
-        print("\n")
+        print("Warning: HF_TOKEN environment variable is not set. Please set it for API access.")
+        print("You can create a .env file with HF_TOKEN=your_token or set it in your environment.")
     
     if args.mode == "all":
         # Run both API and UI in separate threads

requirements.txt

@@ -7,6 +7,6 @@ python-dotenv
 torch
 transformers
 diffusers
-spaces
+spaces>=0.14.0
 xformers
 numpy