Spaces:
Running
Running
prgarg007
commited on
Commit
·
7c676e8
1
Parent(s):
aaf9cdd
fix3
Browse files
app.py
CHANGED
@@ -1,178 +1,253 @@
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import os
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import gradio as gr
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from dotenv import load_dotenv
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def
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"""
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Call the private space as a function and return the results
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"""
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if style_transfer_function is None:
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return None, None, "Error: Could not connect to the AI processing service. Please try again later."
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if not swatch_image or not product_image or not room_image:
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return None, None, "Please upload all three images (swatch, product, and room)."
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try:
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except Exception as e:
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def create_public_interface():
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"""Create
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) as app:
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gr.Markdown("""
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# 🚀 AI Powered Style Transfer & Room Integration
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## Public Access Portal
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Transform your furniture with AI-powered style transfer and room integration!
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**How it works:**
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1. Upload a **swatch image** (fabric/pattern you want to apply)
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2. Upload a **product image** (furniture piece to style)
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3. Upload a **room image** (where you want to place the furniture)
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4. Select your preferred **room style**
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5. Let AI work its magic! ✨
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""")
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# Check if the private space is loaded
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if style_transfer_function is None:
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gr.Markdown("""
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⚠️
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- Authentication problems
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- Service maintenance
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""")
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)
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product_input = gr.Image(
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label="📦 Furniture/Product Image",
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type="pil",
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height=200
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)
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label="🏠 Room/Background Image",
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type="pil",
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height=200,
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)
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"🤖 Transform with AI",
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variant="primary",
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size="lg",
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scale=1
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)
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gr.Markdown("""
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### 💡 Tips for Best Results:
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- Use high-quality, clear images
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- Ensure good lighting in your photos
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- Choose images with similar perspectives
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- Swatch images work best when the pattern/texture is clearly visible
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""")
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with gr.Column(scale=1):
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gr.Markdown("### 🎯 AI Generated Results")
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styled_product_output = gr.Image(
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label="🎨 Step 1: Styled Product",
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height=300
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)
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gr.Markdown("""
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###
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""")
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show_progress=True
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)
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#
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gr.
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import os
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import sys
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import importlib.util
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from pathlib import Path
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from huggingface_hub import hf_hub_download, snapshot_download, HfFileSystem
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import gradio as gr
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# Your private space details
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PRIVATE_SPACE_REPO = "prgarg007/ai-style-transfer-dreamsofa" # Replace with your actual private space name
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HF_TOKEN = os.getenv("HF_TOKEN")
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def setup_cache_directory():
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"""Setup and return cache directory for private space files"""
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cache_dir = Path("private_space_cache")
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cache_dir.mkdir(exist_ok=True)
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return cache_dir
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def download_private_assets(cache_dir):
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"""Download necessary files from private space"""
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try:
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print("Downloading private space assets...")
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# Download entire repository snapshot for directory structure
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snapshot_download(
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repo_id=PRIVATE_SPACE_REPO,
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repo_type="space",
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local_dir=cache_dir,
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token=HF_TOKEN
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)
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print("Successfully downloaded private space assets!")
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return True
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except Exception as e:
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print(f"Error downloading private assets: {str(e)}")
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return False
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def load_private_app():
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"""Download and import the private space app"""
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try:
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print("Setting up cache directory...")
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cache_dir = setup_cache_directory()
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print("Downloading private space files...")
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if not download_private_assets(cache_dir):
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return None
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print("Loading private app code...")
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# Download the main app.py file from private space
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app_path = hf_hub_download(
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repo_id=PRIVATE_SPACE_REPO,
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filename="app.py",
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repo_type="space",
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token=HF_TOKEN
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)
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print(f"App file downloaded to: {app_path}")
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# Add the cache directory to Python path so imports work
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sys.path.insert(0, str(cache_dir))
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# Import and execute the private app
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spec_app = importlib.util.spec_from_file_location("private_app", app_path)
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private_app_module = importlib.util.module_from_spec(spec_app)
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# Set environment variables that might be needed
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# Copy any environment variables from current space to the imported module
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env_vars_to_copy = ["OPENAI_API_KEY", "HF_TOKEN"]
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for var in env_vars_to_copy:
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if os.getenv(var):
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os.environ[var] = os.getenv(var)
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# Execute the module
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spec_app.loader.exec_module(private_app_module)
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print("Successfully loaded private app module!")
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return private_app_module
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except Exception as e:
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print(f"Error loading private app: {str(e)}")
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return None
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def create_public_interface():
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"""Create public interface that uses private app functionality"""
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# Load the private app
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private_app = load_private_app()
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if private_app is None:
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# Fallback interface if loading fails
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with gr.Blocks(title="AI Style Transfer - Loading Error") as error_app:
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gr.Markdown("""
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# ⚠️ Service Temporarily Unavailable
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We're experiencing technical difficulties loading the AI processing service.
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**Possible causes:**
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- Network connectivity issues
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- Authentication problems
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- Service maintenance
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**Solutions:**
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1. Check that HF_TOKEN environment variable is set correctly
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2. Verify the private space name is correct
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3. Ensure you have access to the private space
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4. Try refreshing the page in a few minutes
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If the problem persists, please contact support.
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""")
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return error_app
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# If we successfully loaded the private app, create the interface using its functions
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try:
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# The private app should have a create_interface function
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if hasattr(private_app, 'create_interface'):
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print("Using create_interface from private app...")
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return private_app.create_interface()
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# Alternative: if it has the main components, build interface manually
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elif hasattr(private_app, 'process_images'):
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print("Building interface using private app functions...")
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with gr.Blocks(title="AI Style Transfer & Room Integration", theme=gr.themes.Soft()) as app:
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gr.Markdown("""
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# 🚀 AI Powered Style Transfer & Room Integration
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## Secure Processing Portal
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Transform your furniture with AI-powered style transfer and room integration!
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**How it works:**
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1. Upload a **swatch image** (fabric/pattern you want to apply)
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2. Upload a **product image** (furniture piece to style)
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3. Upload a **room image** (where you want to place the furniture)
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4. Select your preferred **room style**
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5. Let AI work its magic! ✨
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*Your code and processing logic are securely protected*
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""")
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with gr.Row():
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with gr.Column():
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gr.Markdown("### 📤 Upload Your Images")
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swatch_input = gr.Image(
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label="🎨 Swatch/Pattern Image",
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type="pil",
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height=200
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)
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product_input = gr.Image(
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label="📦 Furniture/Product Image",
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type="pil",
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height=200
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)
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room_input = gr.Image(
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label="🏠 Room/Background Image",
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type="pil",
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height=200
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)
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room_style = gr.Dropdown(
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choices=["modern", "vintage", "industrial", "scandinavian", "bohemian", "rustic"],
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value="modern",
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label="🎭 Room Style Theme"
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)
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process_btn = gr.Button("🤖 Transform with AI", variant="primary", size="lg")
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with gr.Column():
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gr.Markdown("### 🎯 AI Generated Results")
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styled_product_output = gr.Image(
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label="🎨 Step 1: Styled Product",
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height=300
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)
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final_output = gr.Image(
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label="🏆 Step 2: Room Integration",
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height=300
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)
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status_output = gr.Textbox(
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label="🔄 Processing Status",
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value="Ready to transform your furniture with AI...",
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interactive=False
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)
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# Connect to the private app's processing function
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process_btn.click(
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fn=private_app.process_images, # Use the function from private space
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inputs=[swatch_input, product_input, room_input, room_style],
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outputs=[styled_product_output, final_output, status_output],
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show_progress=True
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)
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gr.Markdown("""
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### 🎨 Example Use Cases:
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- **Interior Design**: Preview how different fabrics look on your furniture
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- **E-commerce**: Show products in various styles and room settings
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- **Home Renovation**: Experiment with different design aesthetics
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- **Furniture Customization**: Visualize custom upholstery options
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### ⚡ Powered by:
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- OpenAI DALL-E for image generation
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- Advanced AI for style analysis and transfer
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- Secure code execution from private repository
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### 🔒 Privacy & Security:
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- Your processing code is kept private and secure
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- Images are processed securely without permanent storage
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- Code execution happens in isolated environment
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""")
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return app
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else:
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raise Exception("Private app doesn't have expected functions")
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except Exception as e:
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print(f"Error creating interface with private app: {str(e)}")
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# Final fallback
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with gr.Blocks(title="AI Style Transfer - Configuration Error") as fallback_app:
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gr.Markdown(f"""
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# ⚠️ Configuration Error
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Successfully connected to private space but encountered a configuration error:
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`{str(e)}`
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Please check:
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1. Private space code structure
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2. Required functions are properly defined
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3. Environment variables are set correctly
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Contact support if this issue persists.
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""")
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return fallback_app
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"""Main function to create and launch the public interface"""
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print("Starting public interface...")
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print(f"Private space: {PRIVATE_SPACE_REPO}")
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print(f"HF Token available: {'Yes' if HF_TOKEN else 'No'}")
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# Create the public interface
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app = create_public_interface()
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# Launch the app
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print("Launching public interface...")
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app.launch()
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