Add AK's files

app.py

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+import gradio as gr
+import os
+from lumaai import AsyncLumaAI
+import asyncio
+import aiohttp
+
+async def generate_video(api_key, prompt, loop=False, aspect_ratio="16:9", progress=gr.Progress()):
+    client = AsyncLumaAI(auth_token=api_key)
+    
+    progress(0, desc="Initiating video generation...")
+    generation = await client.generations.create(
+        prompt=prompt,
+        loop=loop,
+        aspect_ratio=aspect_ratio
+    )
+    
+    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(api_key, prompt, loop, aspect_ratio, progress=gr.Progress()):
+    if not api_key:
+        raise gr.Error("Please enter your Luma AI API key.")
+    
+    try:
+        video_path = await generate_video(api_key, prompt, loop, aspect_ratio, progress)
+        return video_path, ""
+    except Exception as e:
+        return None, f"An error occurred: {str(e)}"
+
+async def image_to_video(api_key, prompt, image_url, loop, aspect_ratio, progress=gr.Progress()):
+    if not api_key:
+        raise gr.Error("Please enter your Luma AI API key.")
+    
+    try:
+        client = AsyncLumaAI(auth_token=api_key)
+        
+        progress(0, desc="Initiating video generation from image...")
+        generation = await client.generations.create(
+            prompt=prompt,
+            loop=loop,
+            aspect_ratio=aspect_ratio,
+            keyframes={
+                "frame0": {
+                    "type": "image",
+                    "url": image_url
+                }
+            }
+        )
+        
+        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")
+    
+    api_key = gr.Textbox(label="Luma AI API Key", type="password")
+    
+    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")
+        
+        generate_btn.click(
+            text_to_video,
+            inputs=[api_key, prompt, loop, aspect_ratio],
+            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_generate_btn.click(
+            image_to_video,
+            inputs=[api_key, img_prompt, img_url, img_loop, img_aspect_ratio],
+            outputs=[img_video_output, img_error_output]
+        )
+
+demo.queue().launch(share=True)

requirements.txt

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+lumaai