gradio_app.py

import gradio as gr
import time
import random
import requests
from lumaai import LumaAI
import traceback

from lib.status_utils import load_messages, StatusTracker
from lib.image_utils import prepare_image
from lib.ui_components import create_interface

def generate_video(api_key, prompt, camera_motion, loop_video, image=None, progress=gr.Progress()):
    if not api_key or not prompt:
        raise gr.Error("Please enter your LumaAI API key and prompt")
    
    try:
        progress(0, desc="Initializing LumaAI...")
        client = LumaAI(auth_token=api_key)
        
        # Create status tracker with progress object
        status_tracker = StatusTracker(
            progress=lambda x: progress(x),
            status_box=None
        )
        
        # Prepare generation parameters
        generation_params = {
            "prompt": f"{prompt} {camera_motion if camera_motion != 'None' else ''}",
            "loop": loop_video,
            "aspect_ratio": "1:1"  # Force square aspect ratio
        }

        # Handle image if provided
        if image is not None:
            try:
                progress(0.1, desc="Preparing image...")
                cdn_url = prepare_image(image, status_tracker)
                generation_params["keyframes"] = {
                    "frame0": {
                        "type": "image",
                        "url": cdn_url
                    }
                }
            except Exception as e:
                raise gr.Error("Failed to process the input image")

        progress(0.2, desc="Starting generation...")
        try:
            generation = client.generations.create(**generation_params)
        except Exception as e:
            raise gr.Error("Failed to start video generation. Please check your API key.")
        
        # Load and shuffle status messages for variety
        status_messages = load_messages()
        random.shuffle(status_messages)
        message_index = 0
        last_message_time = time.time()
        
        # Poll for completion
        start_time = time.time()
        last_status = None
        
        while True:
            try:
                generation_status = client.generations.get(generation.id)
                status = generation_status.state
                elapsed_time = time.time() - start_time
                current_time = time.time()
                
                # Update status message at random intervals between 2-8 seconds
                if current_time - last_message_time >= random.uniform(2, 8):
                    progress_val = min(0.2 + (elapsed_time/60), 0.8)  # Adjusted for 1-minute expectation
                    progress(progress_val, desc=status_messages[message_index % len(status_messages)])
                    message_index += 1
                    last_message_time = current_time
                
                if status == 'completed':
                    progress(0.9, desc="Generation completed!")
                    download_url = generation_status.assets.video
                    break
                elif status == 'failed':
                    raise gr.Error("Video generation failed")
                
                if elapsed_time > 300:
                    raise gr.Error("Generation timed out after 5 minutes")
                
                time.sleep(1)
                
            except Exception as e:
                print(f"Error during generation polling: {str(e)}")
                print(traceback.format_exc())
                time.sleep(1)
                continue
        
        # Download the video
        progress(0.95, desc="Downloading video...")
        try:
            response = requests.get(download_url, stream=True, timeout=30)
            response.raise_for_status()
            file_path = "output_video.mp4"
            with open(file_path, 'wb') as file:
                file.write(response.content)
            
            progress(1.0, desc="Video ready!")
            return file_path
        except Exception as e:
            raise gr.Error("Failed to download the generated video")
    
    except gr.Error as e:
        raise e
    except Exception as e:
        print(f"Error during generation: {str(e)}")
        print(traceback.format_exc())
        raise gr.Error("An unexpected error occurred")

# Create Gradio interface
app = create_interface(generate_video)

# For Hugging Face Spaces, we want to specify a smaller queue size
app.queue(max_size=5)

if __name__ == "__main__":
    app.launch()