app.py

import gradio as gr
import os
from lumaai import AsyncLumaAI
import asyncio
import aiohttp

# 전역 변수로 카메라 모션 목록을 저장합니다.
camera_motions = []

async def get_camera_motions():
    global camera_motions
    api_key = os.getenv("LMGEN_KEY")
    if not api_key:
        raise gr.Error("LMGEN_KEY environment variable is not set.")
    
    client = AsyncLumaAI(auth_token=api_key)
    motions = await client.generations.camera_motion.list()
    camera_motions = [motion.name for motion in motions]

# 앱 시작 시 카메라 모션 목록을 가져옵니다.
asyncio.run(get_camera_motions())

async def generate_video(client, prompt, loop=False, aspect_ratio="16:9", camera_motion=None, extend_id=None, reverse_extend_id=None, interpolate_ids=None, progress=gr.Progress()):
    generation_params = {
        "prompt": prompt,
        "loop": loop,
        "aspect_ratio": aspect_ratio
    }

    if camera_motion:
        generation_params["prompt"] += f" {camera_motion}"

    if extend_id:
        generation_params["keyframes"] = {
            "frame0": {
                "type": "generation",
                "id": extend_id
            }
        }
    elif reverse_extend_id:
        generation_params["keyframes"] = {
            "frame1": {
                "type": "generation",
                "id": reverse_extend_id
            }
        }
    elif interpolate_ids:
        generation_params["keyframes"] = {
            "frame0": {
                "type": "generation",
                "id": interpolate_ids[0]
            },
            "frame1": {
                "type": "generation",
                "id": interpolate_ids[1]
            }
        }

    progress(0, desc="Initiating video generation...")
    generation = await client.generations.create(**generation_params)
    
    progress(0.1, desc="Video generation started. Waiting for completion...")
    
    # Poll for completion
    start_time = asyncio.get_event_loop().time()
    while True:
        status = await client.generations.get(id=generation.id)
        if status.state == "completed":
            break
        elif status.state == "failed":
            raise Exception("Video generation failed")
        
        # Update progress based on time elapsed (assuming 60 seconds total)
        elapsed_time = asyncio.get_event_loop().time() - start_time
        progress_value = min(0.1 + (elapsed_time / 60) * 0.8, 0.9)
        progress(progress_value, desc="Generating video...")
        
        await asyncio.sleep(5)

    progress(0.9, desc="Downloading generated video...")
    
    # Download the video
    video_url = status.assets.video
    async with aiohttp.ClientSession() as session:
        async with session.get(video_url) as resp:
            if resp.status == 200:
                file_name = f"luma_ai_generated_{generation.id}.mp4"
                with open(file_name, 'wb') as fd:
                    while True:
                        chunk = await resp.content.read(1024)
                        if not chunk:
                            break
                        fd.write(chunk)
    
    progress(1.0, desc="Video generation complete!")
    return file_name

async def text_to_video(prompt, loop, aspect_ratio, camera_motion, extend_id, reverse_extend_id, interpolate_id1, interpolate_id2, progress=gr.Progress()):
    api_key = os.getenv("LMGEN_KEY")
    if not api_key:
        raise gr.Error("LMGEN_KEY environment variable is not set.")
    
    client = AsyncLumaAI(auth_token=api_key)
    
    try:
        interpolate_ids = None
        if interpolate_id1 and interpolate_id2:
            interpolate_ids = [interpolate_id1, interpolate_id2]

        video_path = await generate_video(
            client, prompt, loop, aspect_ratio, camera_motion, 
            extend_id, reverse_extend_id, interpolate_ids, progress
        )
        return video_path, ""
    except Exception as e:
        return None, f"An error occurred: {str(e)}"

async def image_to_video(prompt, image_url, loop, aspect_ratio, camera_motion, progress=gr.Progress()):
    api_key = os.getenv("LMGEN_KEY")
    if not api_key:
        raise gr.Error("LMGEN_KEY environment variable is not set.")
    
    client = AsyncLumaAI(auth_token=api_key)
    
    try:
        generation_params = {
            "prompt": prompt + (f" {camera_motion}" if camera_motion else ""),
            "loop": loop,
            "aspect_ratio": aspect_ratio,
            "keyframes": {
                "frame0": {
                    "type": "image",
                    "url": image_url
                }
            }
        }
        
        progress(0, desc="Initiating video generation from image...")
        generation = await client.generations.create(**generation_params)
        
        progress(0.1, desc="Video generation started. Waiting for completion...")
        
        # Poll for completion
        start_time = asyncio.get_event_loop().time()
        while True:
            status = await client.generations.get(id=generation.id)
            if status.state == "completed":
                break
            elif status.state == "failed":
                raise Exception("Video generation failed")
            
            # Update progress based on time elapsed (assuming 60 seconds total)
            elapsed_time = asyncio.get_event_loop().time() - start_time
            progress_value = min(0.1 + (elapsed_time / 60) * 0.8, 0.9)
            progress(progress_value, desc="Generating video...")
            
            await asyncio.sleep(5)

        progress(0.9, desc="Downloading generated video...")
        
        # Download the video
        video_url = status.assets.video
        async with aiohttp.ClientSession() as session:
            async with session.get(video_url) as resp:
                if resp.status == 200:
                    file_name = f"luma_ai_generated_{generation.id}.mp4"
                    with open(file_name, 'wb') as fd:
                        while True:
                            chunk = await resp.content.read(1024)
                            if not chunk:
                                break
                            fd.write(chunk)
        
        progress(1.0, desc="Video generation complete!")
        return file_name, ""
    except Exception as e:
        return None, f"An error occurred: {str(e)}"

with gr.Blocks() as demo:
    gr.Markdown("# Luma AI Text-to-Video Demo")
    
    with gr.Tab("Text to Video"):
        prompt = gr.Textbox(label="Prompt")
        generate_btn = gr.Button("Generate Video")
        video_output = gr.Video(label="Generated Video")
        error_output = gr.Textbox(label="Error Messages", visible=True)
        
        with gr.Accordion("Advanced Options", open=False):
            loop = gr.Checkbox(label="Loop", value=False)
            aspect_ratio = gr.Dropdown(label="Aspect Ratio", choices=["16:9", "1:1", "9:16", "4:3", "3:4"], value="16:9")
            camera_motion = gr.Dropdown(label="Camera Motion", choices=camera_motions)
            extend_id = gr.Textbox(label="Extend Video ID (optional)")
            reverse_extend_id = gr.Textbox(label="Reverse Extend Video ID (optional)")
            with gr.Row():
                interpolate_id1 = gr.Textbox(label="Interpolate Video ID 1 (optional)")
                interpolate_id2 = gr.Textbox(label="Interpolate Video ID 2 (optional)")
        
        generate_btn.click(
            text_to_video,
            inputs=[prompt, loop, aspect_ratio, camera_motion, extend_id, reverse_extend_id, interpolate_id1, interpolate_id2],
            outputs=[video_output, error_output]
        )
    
    with gr.Tab("Image to Video"):
        img_prompt = gr.Textbox(label="Prompt")
        img_url = gr.Textbox(label="Image URL")
        img_generate_btn = gr.Button("Generate Video from Image")
        img_video_output = gr.Video(label="Generated Video")
        img_error_output = gr.Textbox(label="Error Messages", visible=True)
        
        with gr.Accordion("Advanced Options", open=False):
            img_loop = gr.Checkbox(label="Loop", value=False)
            img_aspect_ratio = gr.Dropdown(label="Aspect Ratio", choices=["16:9", "1:1", "9:16", "4:3", "3:4"], value="16:9")
            img_camera_motion = gr.Dropdown(label="Camera Motion", choices=camera_motions)
        
        img_generate_btn.click(
            image_to_video,
            inputs=[img_prompt, img_url, img_loop, img_aspect_ratio, img_camera_motion],
            outputs=[img_video_output, img_error_output]
        )

demo.queue().launch(share=True)