Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -2,43 +2,120 @@ import os
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import sys
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import subprocess
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#
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print("
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print(f"
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if os.getcwd() not in sys.path:
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sys.path.insert(0, os.getcwd())
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try:
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import gradio as gr
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import torch
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from diffusers import CosmosTextToImagePipeline
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import random
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print("
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except ImportError as e:
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print(f"Import
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print("
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sys.exit(1)
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# Available checkpoints: nvidia/Cosmos-Predict2-2B-Text2Image, nvidia/Cosmos-Predict2-14B-Text2Image
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model_id = "diffusers-internal-dev/ct2i-14B"
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# Load the pipeline once to avoid repeated loading
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pipe.to("cuda")
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print("Pipeline loaded successfully")
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except Exception as e:
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print(f"Error loading pipeline: {e}")
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sys.exit(1)
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@spaces.GPU
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def generate_image(prompt, negative_prompt, seed, randomize_seed):
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import sys
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import subprocess
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# Debug: Print environment information
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def print_env_info():
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print("=== ENVIRONMENT DEBUG INFO ===")
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print(f"Python executable: {sys.executable}")
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print(f"Python version: {sys.version}")
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print(f"Current working directory: {os.getcwd()}")
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print(f"Python path: {sys.path[:3]}...") # First 3 entries
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# Check if we can find pip
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try:
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pip_result = subprocess.run([sys.executable, '-m', 'pip', '--version'],
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capture_output=True, text=True)
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print(f"Pip version: {pip_result.stdout.strip()}")
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except Exception as e:
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print(f"Pip check failed: {e}")
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# List contents of current directory
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print(f"Directory contents: {os.listdir('.')}")
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if os.path.exists('diffusers_repo'):
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print("β diffusers_repo found")
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else:
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print("β diffusers_repo NOT found")
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print("===============================")
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print_env_info()
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# Install diffusers from local repository
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def install_diffusers():
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try:
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# Change to diffusers repo directory
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original_dir = os.getcwd()
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if not os.path.exists('diffusers_repo'):
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print("ERROR: diffusers_repo directory not found!")
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return False
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os.chdir('diffusers_repo')
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print(f"Changed to directory: {os.getcwd()}")
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# Use the exact same Python executable for pip
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python_exe = sys.executable
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print(f"Using Python executable: {python_exe}")
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# Install in editable mode with verbose output
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cmd = [python_exe, '-m', 'pip', 'install', '-e', '.', '--verbose']
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print(f"Running command: {' '.join(cmd)}")
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result = subprocess.run(cmd, capture_output=True, text=True)
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print("Installation stdout:", result.stdout[-1000:]) # Last 1000 chars
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if result.stderr:
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print("Installation stderr:", result.stderr[-1000:]) # Last 1000 chars
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# Change back to original directory
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os.chdir(original_dir)
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# Add diffusers_repo to Python path
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diffusers_path = os.path.join(original_dir, 'diffusers_repo')
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if diffusers_path not in sys.path:
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sys.path.insert(0, diffusers_path)
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print(f"Added to Python path: {diffusers_path}")
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# Test if we can import after installation
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try:
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import diffusers
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print(f"β Successfully imported diffusers from: {diffusers.__file__}")
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return True
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except ImportError as e:
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print(f"β Failed to import diffusers after installation: {e}")
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return False
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except Exception as e:
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print(f"Installation failed with exception: {e}")
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return False
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# Attempt installation
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print("Starting diffusers installation...")
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if not install_diffusers():
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print("Failed to install local diffusers, exiting...")
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sys.exit(1)
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else:
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print("β Local diffusers installation successful!")
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# Now import required modules
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print("Importing required modules...")
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try:
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import gradio as gr
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print("β Gradio imported")
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import spaces
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print("β Spaces imported")
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import torch
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print("β Torch imported")
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from diffusers import CosmosTextToImagePipeline
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print("β CosmosTextToImagePipeline imported")
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import random
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print("β Random imported")
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print("All imports successful!")
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except ImportError as e:
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print(f"β Import failed: {e}")
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print("Checking installed packages...")
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try:
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result = subprocess.run([sys.executable, '-m', 'pip', 'list'],
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capture_output=True, text=True)
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print("Installed packages:")
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print(result.stdout)
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except:
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pass
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sys.exit(1)
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# Available checkpoints: nvidia/Cosmos-Predict2-2B-Text2Image, nvidia/Cosmos-Predict2-14B-Text2Image
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model_id = "diffusers-internal-dev/ct2i-14B"
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# Load the pipeline once to avoid repeated loading
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pipe = CosmosTextToImagePipeline.from_pretrained(model_id, torch_dtype=torch.bfloat16)
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pipe.to("cuda")
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@spaces.GPU
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def generate_image(prompt, negative_prompt, seed, randomize_seed):
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