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# app.py - Ultra-Safe Debugging Version

import os
import sys
import traceback
import tempfile
import warnings
warnings.filterwarnings('ignore')

print("🚀 Starting ULTRA-SAFE mode...")
print(f"Python: {sys.version}")

# Safe imports with individual error handling
IMPORTS = {
    'torch': False,
    'numpy': False,
    'PIL': False,
    'gradio': False,
    'soundfile': False,
    'transformers': False
}

try:
    import torch
    IMPORTS['torch'] = True
    print("✅ PyTorch imported")
except Exception as e:
    print(f"❌ PyTorch failed: {e}")

try:
    import numpy as np
    IMPORTS['numpy'] = True
    print("✅ NumPy imported")
except Exception as e:
    print(f"❌ NumPy failed: {e}")

try:
    from PIL import Image
    IMPORTS['PIL'] = True
    print("✅ PIL imported")
except Exception as e:
    print(f"❌ PIL failed: {e}")

try:
    import gradio as gr
    IMPORTS['gradio'] = True
    print("✅ Gradio imported")
except Exception as e:
    print(f"❌ Gradio failed: {e}")

try:
    import soundfile as sf
    IMPORTS['soundfile'] = True
    print("✅ SoundFile imported")
except Exception as e:
    print(f"❌ SoundFile failed: {e}")

# Only try transformers if basic imports work
if IMPORTS['torch']:
    try:
        from transformers import BlipProcessor, BlipForConditionalGeneration
        from transformers import MusicgenForConditionalGeneration, AutoProcessor
        IMPORTS['transformers'] = True
        print("✅ Transformers imported")
    except Exception as e:
        print(f"❌ Transformers failed: {e}")

class SafeGenerator:
    def __init__(self):
        print("🔧 Initializing Safe Generator...")
        self.working = True
        
    def safe_string_test(self, input_val):
        """Test string operations safely"""
        print(f"🧪 Testing string operations with: {input_val} (type: {type(input_val)})")
        
        try:
            # Convert to string safely
            if input_val is None:
                str_val = "none"
            elif isinstance(input_val, str):
                str_val = input_val
            elif isinstance(input_val, (int, float, bool)):
                str_val = str(input_val)
            else:
                str_val = repr(input_val)
            
            print(f"✅ String conversion: '{str_val}'")
            
            # Test lower operation
            lower_val = str_val.lower()
            print(f"✅ Lower operation: '{lower_val}'")
            
            # Test 'in' operation with known string
            test_keywords = ['test', 'image', 'bright']
            results = []
            
            for keyword in test_keywords:
                try:
                    result = keyword in lower_val
                    results.append(f"{keyword}: {result}")
                    print(f"✅ '{keyword}' in '{lower_val}': {result}")
                except Exception as e:
                    error_msg = f"❌ Error with '{keyword}': {e}"
                    results.append(error_msg)
                    print(error_msg)
            
            return f"String test passed. Results: {', '.join(results)}"
            
        except Exception as e:
            error_msg = f"❌ String test failed: {e}\n{traceback.format_exc()}"
            print(error_msg)
            return error_msg
    
    def create_simple_description(self, image):
        """Create description without any AI models"""
        try:
            if not IMPORTS['numpy'] or not IMPORTS['PIL']:
                return "simple image", "simple image, ambient music"
            
            print("🔍 Creating simple description...")
            
            # Basic image analysis
            img_array = np.array(image)
            h, w, c = img_array.shape
            print(f"📏 Image dimensions: {w}x{h}x{c}")
            
            # Safe color analysis
            try:
                mean_color = np.mean(img_array, axis=(0, 1))
                brightness = float(np.mean(mean_color))
                print(f"💡 Brightness: {brightness}")
                
                # Safe brightness categorization
                if brightness > 200:
                    brightness_desc = "bright"
                elif brightness < 100:
                    brightness_desc = "dark"
                else:
                    brightness_desc = "medium"
                
                print(f"🏷️ Brightness category: {brightness_desc}")
                
            except Exception as e:
                print(f"⚠️ Color analysis failed: {e}")
                brightness_desc = "colorful"
            
            # Build description safely
            base_desc = f"{brightness_desc} image"
            enhanced_desc = f"{base_desc}, peaceful music"
            
            print(f"📝 Description: '{base_desc}' -> '{enhanced_desc}'")
            
            # Test the strings before returning
            test_result = self.safe_string_test(base_desc)
            print(f"🧪 String test result: {test_result}")
            
            return base_desc, enhanced_desc
            
        except Exception as e:
            error_msg = f"❌ Description creation failed: {e}\n{traceback.format_exc()}"
            print(error_msg)
            return "error image", "error image, quiet music"
    
    def create_simple_audio(self, duration=10):
        """Create simple audio without AI"""
        try:
            if not IMPORTS['numpy']:
                print("❌ NumPy not available for audio")
                return None, None
            
            print(f"🎵 Creating {duration}s simple audio...")
            
            # Create simple tone
            sample_rate = 22050
            t = np.linspace(0, duration, int(duration * sample_rate))
            
            # Simple pleasant tone (C major chord)
            freq1, freq2, freq3 = 261.63, 329.63, 392.00  # C, E, G
            audio = (np.sin(2 * np.pi * freq1 * t) * 0.3 + 
                    np.sin(2 * np.pi * freq2 * t) * 0.2 + 
                    np.sin(2 * np.pi * freq3 * t) * 0.2)
            
            # Add fade in/out
            fade_samples = int(0.5 * sample_rate)  # 0.5 second fade
            audio[:fade_samples] *= np.linspace(0, 1, fade_samples)
            audio[-fade_samples:] *= np.linspace(1, 0, fade_samples)
            
            print(f"✅ Audio created: {len(audio)} samples at {sample_rate}Hz")
            return audio.astype(np.float32), sample_rate
            
        except Exception as e:
            print(f"❌ Audio creation failed: {e}")
            return None, None
    
    def process_image_safe(self, image):
        """Ultra-safe image processing"""
        print("🔄 Starting SAFE image processing...")
        
        if image is None:
            return None, "❌ No image provided", None, None
        
        try:
            # Step 1: Test the image
            print("📸 Step 1: Testing image...")
            img_info = f"Image type: {type(image)}"
            if hasattr(image, 'size'):
                img_info += f", Size: {image.size}"
            print(img_info)
            
            # Step 2: Create description
            print("📝 Step 2: Creating description...")
            description, music_prompt = self.create_simple_description(image)
            
            # Step 3: Test strings
            print("🧪 Step 3: Testing strings...")
            desc_test = self.safe_string_test(description)
            prompt_test = self.safe_string_test(music_prompt)
            
            # Step 4: Create audio
            print("🎵 Step 4: Creating audio...")
            audio_data, sample_rate = self.create_simple_audio(10)
            
            # Step 5: Save audio if successful
            audio_file = None
            if audio_data is not None and IMPORTS['soundfile']:
                try:
                    print("💾 Step 5: Saving audio...")
                    with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as f:
                        sf.write(f.name, audio_data, sample_rate)
                        audio_file = f.name
                        print(f"✅ Audio saved: {audio_file}")
                except Exception as e:
                    print(f"⚠️ Audio save failed: {e}")
            
            # Prepare results
            status_msg = f"""
**✅ SAFE MODE PROCESSING COMPLETE**
**Image Analysis:**
- {img_info}
**Generated Text:**
- Description: "{description}"
- Music Prompt: "{music_prompt}"
**String Tests:**
- Description test: {desc_test[:100]}...
- Prompt test: {prompt_test[:100]}...
**Audio:**
- Status: {'✅ Created' if audio_data is not None else '❌ Failed'}
- Duration: {len(audio_data)/sample_rate:.1f}s if audio_data else 'N/A'
**System Status:**
- PyTorch: {'✅' if IMPORTS['torch'] else '❌'}
- NumPy: {'✅' if IMPORTS['numpy'] else '❌'}
- PIL: {'✅' if IMPORTS['PIL'] else '❌'}
- SoundFile: {'✅' if IMPORTS['soundfile'] else '❌'}
- Transformers: {'✅' if IMPORTS['transformers'] else '❌'}
"""
            
            audio_output = (sample_rate, audio_data) if audio_data is not None else None
            
            print("✅ Safe processing completed successfully!")
            return None, status_msg, audio_output, audio_file
            
        except Exception as e:
            error_msg = f"""
❌ **SAFE MODE ERROR**
**Error:** {str(e)}
**Location:** {traceback.format_exc()}
**System Info:**
- Python: {sys.version}
- Working directory: {os.getcwd()}
- Environment: {dict(os.environ).get('SPACE_ID', 'Local')}
**Import Status:**
{chr(10).join([f"- {k}: {'✅' if v else '❌'}" for k, v in IMPORTS.items()])}
"""
            print(error_msg)
            return None, error_msg, None, None

# Initialize generator
print("🎬 Initializing generator...")
try:
    generator = SafeGenerator()
    print("✅ Generator ready!")
except Exception as e:
    print(f"❌ Generator failed: {e}")
    generator = None

def create_minimal_interface():
    """Create minimal interface for debugging"""
    
    if not IMPORTS['gradio']:
        print("❌ Cannot create interface - Gradio not available")
        return None
    
    print("🖥️ Creating minimal interface...")
    
    with gr.Blocks(title="🧪 Ultra-Safe Debug Mode") as demo:
        
        gr.HTML("""
        <div style="text-align: center; background: #fff3cd; padding: 20px; border-radius: 10px; margin: 20px 0;">
            <h1>🧪 ULTRA-SAFE DEBUG MODE</h1>
            <p><strong>This version isolates and tests each component individually</strong></p>
        </div>
        """)
        
        # System status
        status_html = f"""
        <div style="background: #f8f9fa; padding: 15px; border-radius: 8px; margin: 10px 0;">
            <h3>🔧 Import Status</h3>
            <ul>
                {"".join([f"<li><strong>{k}:</strong> {'🟢 OK' if v else '🔴 Failed'}</li>" for k, v in IMPORTS.items()])}
            </ul>
        </div>
        """
        gr.HTML(status_html)
        
        with gr.Tabs():
            # Tab 1: Basic String Test
            with gr.TabItem("🧪 String Test"):
                with gr.Row():
                    test_input = gr.Textbox(
                        value="bright colorful sunset image",
                        label="Test String Input"
                    )
                    test_btn = gr.Button("Test String Operations")
                
                test_output = gr.Textbox(
                    label="Test Results",
                    lines=10
                )
                
                if generator:
                    test_btn.click(
                        fn=generator.safe_string_test,
                        inputs=[test_input],
                        outputs=[test_output]
                    )
            
            # Tab 2: Image Processing Test
            with gr.TabItem("📸 Image Test"):
                with gr.Row():
                    with gr.Column():
                        image_input = gr.Image(
                            type="pil",
                            label="Upload Test Image"
                        )
                        process_btn = gr.Button(
                            "🔄 Process Image (Safe Mode)",
                            variant="primary"
                        )
                    
                    with gr.Column():
                        status_output = gr.Markdown(
                            value="Upload an image and click process",
                            label="Processing Results"
                        )
                
                with gr.Row():
                    audio_output = gr.Audio(label="Generated Audio")
                    file_output = gr.File(label="Audio File")
                
                if generator:
                    process_btn.click(
                        fn=generator.process_image_safe,
                        inputs=[image_input],
                        outputs=[gr.Video(visible=False), status_output, audio_output, file_output]
                    )
        
        gr.HTML("""
        <div style="background: #e3f2fd; padding: 15px; border-radius: 8px; margin: 20px 0;">
            <h3>🎯 Debug Instructions</h3>
            <ol>
                <li><strong>String Test:</strong> Test if string operations work correctly</li>
                <li><strong>Image Test:</strong> Upload an image to see where the error occurs</li>
                <li><strong>Check Results:</strong> Look for the exact error location in the output</li>
            </ol>
        </div>
        """)
    
    return demo

# Launch
if __name__ == "__main__":
    print("🚀 Launching debug interface...")
    
    try:
        demo = create_minimal_interface()
        if demo is not None:
            demo.launch(
                server_name="0.0.0.0",
                server_port=7860,
                share=True
            )
        else:
            print("❌ Could not create interface")
    except Exception as e:
        print(f"❌ Launch failed: {e}")
        print(traceback.format_exc())

# Minimal requirements.txt
"""
gradio==4.44.0
Pillow>=9.5.0
numpy>=1.24.0
soundfile>=0.12.0
torch>=2.0.0
transformers>=4.30.0
"""

# Updated README.md
"""
---
title: Ultra-Safe Photo Soundtrack Debug
emoji: 🧪
colorFrom: red
colorTo: orange
sdk: gradio
sdk_version: "4.44.0"
app_file: app.py
pinned: false
license: apache-2.0
---
# 🧪 Ultra-Safe Debug Mode
This is a debugging version to isolate the "bool is not iterable" error.
## Features
- ✅ Safe imports with individual error handling
- ✅ Step-by-step processing with detailed logs
- ✅ String operation testing
- ✅ Fallbacks for every component
- ✅ Detailed error reporting
## Debug Process
1. Upload to see import status
2. Test string operations
3. Process an image to find exact error location
4. Check detailed logs for the root cause
This version will work even with missing dependencies and show exactly where errors occur.
"""

	# app.py - Ultra-Safe Debugging Version

	import os
	import sys
	import traceback
	import tempfile
	import warnings
	warnings.filterwarnings('ignore')

	print("🚀 Starting ULTRA-SAFE mode...")
	print(f"Python: {sys.version}")

	# Safe imports with individual error handling
	IMPORTS = {
	'torch': False,
	'numpy': False,
	'PIL': False,
	'gradio': False,
	'soundfile': False,
	'transformers': False
	}

	try:
	import torch
	IMPORTS['torch'] = True
	print("✅ PyTorch imported")
	except Exception as e:
	print(f"❌ PyTorch failed: {e}")

	try:
	import numpy as np
	IMPORTS['numpy'] = True
	print("✅ NumPy imported")
	except Exception as e:
	print(f"❌ NumPy failed: {e}")

	try:
	from PIL import Image
	IMPORTS['PIL'] = True
	print("✅ PIL imported")
	except Exception as e:
	print(f"❌ PIL failed: {e}")

	try:
	import gradio as gr
	IMPORTS['gradio'] = True
	print("✅ Gradio imported")
	except Exception as e:
	print(f"❌ Gradio failed: {e}")

	try:
	import soundfile as sf
	IMPORTS['soundfile'] = True
	print("✅ SoundFile imported")
	except Exception as e:
	print(f"❌ SoundFile failed: {e}")

	# Only try transformers if basic imports work
	if IMPORTS['torch']:
	try:
	from transformers import BlipProcessor, BlipForConditionalGeneration
	from transformers import MusicgenForConditionalGeneration, AutoProcessor
	IMPORTS['transformers'] = True
	print("✅ Transformers imported")
	except Exception as e:
	print(f"❌ Transformers failed: {e}")

	class SafeGenerator:
	def __init__(self):
	print("🔧 Initializing Safe Generator...")
	self.working = True

	def safe_string_test(self, input_val):
	"""Test string operations safely"""
	print(f"🧪 Testing string operations with: {input_val} (type: {type(input_val)})")

	try:
	# Convert to string safely
	if input_val is None:
	str_val = "none"
	elif isinstance(input_val, str):
	str_val = input_val
	elif isinstance(input_val, (int, float, bool)):
	str_val = str(input_val)
	else:
	str_val = repr(input_val)

	print(f"✅ String conversion: '{str_val}'")

	# Test lower operation
	lower_val = str_val.lower()
	print(f"✅ Lower operation: '{lower_val}'")

	# Test 'in' operation with known string
	test_keywords = ['test', 'image', 'bright']
	results = []

	for keyword in test_keywords:
	try:
	result = keyword in lower_val
	results.append(f"{keyword}: {result}")
	print(f"✅ '{keyword}' in '{lower_val}': {result}")
	except Exception as e:
	error_msg = f"❌ Error with '{keyword}': {e}"
	results.append(error_msg)
	print(error_msg)

	return f"String test passed. Results: {', '.join(results)}"

	except Exception as e:
	error_msg = f"❌ String test failed: {e}\n{traceback.format_exc()}"
	print(error_msg)
	return error_msg

	def create_simple_description(self, image):
	"""Create description without any AI models"""
	try:
	if not IMPORTS['numpy'] or not IMPORTS['PIL']:
	return "simple image", "simple image, ambient music"

	print("🔍 Creating simple description...")

	# Basic image analysis
	img_array = np.array(image)
	h, w, c = img_array.shape
	print(f"📏 Image dimensions: {w}x{h}x{c}")

	# Safe color analysis
	try:
	mean_color = np.mean(img_array, axis=(0, 1))
	brightness = float(np.mean(mean_color))
	print(f"💡 Brightness: {brightness}")

	# Safe brightness categorization
	if brightness > 200:
	brightness_desc = "bright"
	elif brightness < 100:
	brightness_desc = "dark"
	else:
	brightness_desc = "medium"

	print(f"🏷️ Brightness category: {brightness_desc}")

	except Exception as e:
	print(f"⚠️ Color analysis failed: {e}")
	brightness_desc = "colorful"

	# Build description safely
	base_desc = f"{brightness_desc} image"
	enhanced_desc = f"{base_desc}, peaceful music"

	print(f"📝 Description: '{base_desc}' -> '{enhanced_desc}'")

	# Test the strings before returning
	test_result = self.safe_string_test(base_desc)
	print(f"🧪 String test result: {test_result}")

	return base_desc, enhanced_desc

	except Exception as e:
	error_msg = f"❌ Description creation failed: {e}\n{traceback.format_exc()}"
	print(error_msg)
	return "error image", "error image, quiet music"

	def create_simple_audio(self, duration=10):
	"""Create simple audio without AI"""
	try:
	if not IMPORTS['numpy']:
	print("❌ NumPy not available for audio")
	return None, None

	print(f"🎵 Creating {duration}s simple audio...")

	# Create simple tone
	sample_rate = 22050
	t = np.linspace(0, duration, int(duration * sample_rate))

	# Simple pleasant tone (C major chord)
	freq1, freq2, freq3 = 261.63, 329.63, 392.00 # C, E, G
	audio = (np.sin(2 * np.pi * freq1 * t) * 0.3 +
	np.sin(2 * np.pi * freq2 * t) * 0.2 +
	np.sin(2 * np.pi * freq3 * t) * 0.2)

	# Add fade in/out
	fade_samples = int(0.5 * sample_rate) # 0.5 second fade
	audio[:fade_samples] *= np.linspace(0, 1, fade_samples)
	audio[-fade_samples:] *= np.linspace(1, 0, fade_samples)

	print(f"✅ Audio created: {len(audio)} samples at {sample_rate}Hz")
	return audio.astype(np.float32), sample_rate

	except Exception as e:
	print(f"❌ Audio creation failed: {e}")
	return None, None

	def process_image_safe(self, image):
	"""Ultra-safe image processing"""
	print("🔄 Starting SAFE image processing...")

	if image is None:
	return None, "❌ No image provided", None, None

	try:
	# Step 1: Test the image
	print("📸 Step 1: Testing image...")
	img_info = f"Image type: {type(image)}"
	if hasattr(image, 'size'):
	img_info += f", Size: {image.size}"
	print(img_info)

	# Step 2: Create description
	print("📝 Step 2: Creating description...")
	description, music_prompt = self.create_simple_description(image)

	# Step 3: Test strings
	print("🧪 Step 3: Testing strings...")
	desc_test = self.safe_string_test(description)
	prompt_test = self.safe_string_test(music_prompt)

	# Step 4: Create audio
	print("🎵 Step 4: Creating audio...")
	audio_data, sample_rate = self.create_simple_audio(10)

	# Step 5: Save audio if successful
	audio_file = None
	if audio_data is not None and IMPORTS['soundfile']:
	try:
	print("💾 Step 5: Saving audio...")
	with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as f:
	sf.write(f.name, audio_data, sample_rate)
	audio_file = f.name
	print(f"✅ Audio saved: {audio_file}")
	except Exception as e:
	print(f"⚠️ Audio save failed: {e}")

	# Prepare results
	status_msg = f"""
	✅ SAFE MODE PROCESSING COMPLETE

	Image Analysis:
	- {img_info}

	Generated Text:
	- Description: "{description}"
	- Music Prompt: "{music_prompt}"

	String Tests:
	- Description test: {desc_test[:100]}...
	- Prompt test: {prompt_test[:100]}...

	Audio:
	- Status: {'✅ Created' if audio_data is not None else '❌ Failed'}
	- Duration: {len(audio_data)/sample_rate:.1f}s if audio_data else 'N/A'

	System Status:
	- PyTorch: {'✅' if IMPORTS['torch'] else '❌'}
	- NumPy: {'✅' if IMPORTS['numpy'] else '❌'}
	- PIL: {'✅' if IMPORTS['PIL'] else '❌'}
	- SoundFile: {'✅' if IMPORTS['soundfile'] else '❌'}
	- Transformers: {'✅' if IMPORTS['transformers'] else '❌'}
	"""

	audio_output = (sample_rate, audio_data) if audio_data is not None else None

	print("✅ Safe processing completed successfully!")
	return None, status_msg, audio_output, audio_file

	except Exception as e:
	error_msg = f"""
	❌ SAFE MODE ERROR

	Error: {str(e)}

	Location: {traceback.format_exc()}

	System Info:
	- Python: {sys.version}
	- Working directory: {os.getcwd()}
	- Environment: {dict(os.environ).get('SPACE_ID', 'Local')}

	Import Status:
	{chr(10).join([f"- {k}: {'✅' if v else '❌'}" for k, v in IMPORTS.items()])}
	"""
	print(error_msg)
	return None, error_msg, None, None

	# Initialize generator
	print("🎬 Initializing generator...")
	try:
	generator = SafeGenerator()
	print("✅ Generator ready!")
	except Exception as e:
	print(f"❌ Generator failed: {e}")
	generator = None

	def create_minimal_interface():
	"""Create minimal interface for debugging"""

	if not IMPORTS['gradio']:
	print("❌ Cannot create interface - Gradio not available")
	return None

	print("🖥️ Creating minimal interface...")

	with gr.Blocks(title="🧪 Ultra-Safe Debug Mode") as demo:

	gr.HTML("""
	<div style="text-align: center; background: #fff3cd; padding: 20px; border-radius: 10px; margin: 20px 0;">
	<h1>🧪 ULTRA-SAFE DEBUG MODE</h1>
	<p><strong>This version isolates and tests each component individually</strong></p>
	</div>
	""")

	# System status
	status_html = f"""
	<div style="background: #f8f9fa; padding: 15px; border-radius: 8px; margin: 10px 0;">
	<h3>🔧 Import Status</h3>
	<ul>
	{"".join([f"<li><strong>{k}:</strong> {'🟢 OK' if v else '🔴 Failed'}</li>" for k, v in IMPORTS.items()])}
	</ul>
	</div>
	"""
	gr.HTML(status_html)

	with gr.Tabs():
	# Tab 1: Basic String Test
	with gr.TabItem("🧪 String Test"):
	with gr.Row():
	test_input = gr.Textbox(
	value="bright colorful sunset image",
	label="Test String Input"
	)
	test_btn = gr.Button("Test String Operations")

	test_output = gr.Textbox(
	label="Test Results",
	lines=10
	)

	if generator:
	test_btn.click(
	fn=generator.safe_string_test,
	inputs=[test_input],
	outputs=[test_output]
	)

	# Tab 2: Image Processing Test
	with gr.TabItem("📸 Image Test"):
	with gr.Row():
	with gr.Column():
	image_input = gr.Image(
	type="pil",
	label="Upload Test Image"
	)
	process_btn = gr.Button(
	"🔄 Process Image (Safe Mode)",
	variant="primary"
	)

	with gr.Column():
	status_output = gr.Markdown(
	value="Upload an image and click process",
	label="Processing Results"
	)

	with gr.Row():
	audio_output = gr.Audio(label="Generated Audio")
	file_output = gr.File(label="Audio File")

	if generator:
	process_btn.click(
	fn=generator.process_image_safe,
	inputs=[image_input],
	outputs=[gr.Video(visible=False), status_output, audio_output, file_output]
	)

	gr.HTML("""
	<div style="background: #e3f2fd; padding: 15px; border-radius: 8px; margin: 20px 0;">
	<h3>🎯 Debug Instructions</h3>
	<ol>
	<li><strong>String Test:</strong> Test if string operations work correctly</li>
	<li><strong>Image Test:</strong> Upload an image to see where the error occurs</li>
	<li><strong>Check Results:</strong> Look for the exact error location in the output</li>
	</ol>
	</div>
	""")

	return demo

	# Launch
	if __name__ == "__main__":
	print("🚀 Launching debug interface...")

	try:
	demo = create_minimal_interface()
	if demo is not None:
	demo.launch(
	server_name="0.0.0.0",
	server_port=7860,
	share=True
	)
	else:
	print("❌ Could not create interface")
	except Exception as e:
	print(f"❌ Launch failed: {e}")
	print(traceback.format_exc())

	# Minimal requirements.txt
	"""
	gradio==4.44.0
	Pillow>=9.5.0
	numpy>=1.24.0
	soundfile>=0.12.0
	torch>=2.0.0
	transformers>=4.30.0
	"""

	# Updated README.md
	"""
	---
	title: Ultra-Safe Photo Soundtrack Debug
	emoji: 🧪
	colorFrom: red
	colorTo: orange
	sdk: gradio
	sdk_version: "4.44.0"
	app_file: app.py
	pinned: false
	license: apache-2.0
	---

	# 🧪 Ultra-Safe Debug Mode

	This is a debugging version to isolate the "bool is not iterable" error.

	## Features
	- ✅ Safe imports with individual error handling
	- ✅ Step-by-step processing with detailed logs
	- ✅ String operation testing
	- ✅ Fallbacks for every component
	- ✅ Detailed error reporting

	## Debug Process
	1. Upload to see import status
	2. Test string operations
	3. Process an image to find exact error location
	4. Check detailed logs for the root cause

	This version will work even with missing dependencies and show exactly where errors occur.
	"""