Enhance project structure with new app entry point, updated README, and improved UI components; refine .gitignore and loading messages

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -1,2 +1,4 @@
-*.env
-*.pyc
+__pycache__/
+*.pyc
+.env
+.DS_Store

README.md

@@ -1,14 +1,40 @@
----
-title: Luma Api Dreammachine Gui
-emoji: 🚀
-colorFrom: red
-colorTo: green
-sdk: gradio
-sdk_version: 5.4.0
-app_file: app.py
-pinned: false
-license: mit
-short_description: BYOK LumaAI DreamMachine Interface
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# LumaAI Video Generator
+
+A Gradio web interface for generating videos using LumaAI's API. Transform your prompts into mesmerizing videos with optional image input and camera motion controls.
+
+## Features
+
+- Text-to-video generation
+- Image-to-video generation
+- Camera motion controls
+- Real-time status updates with fun messages
+- Modern, user-friendly interface
+
+## Usage
+
+1. Enter your LumaAI API key
+2. Type your creative prompt
+3. (Optional) Select a camera motion
+4. (Optional) Upload an image
+5. Click Generate and watch the magic happen!
+
+## Development
+
+To run locally:
+
+```bash
+pip install -r requirements.txt
+python gradio_app.py
+```
+
+## Deployment
+
+This app is ready for Hugging Face Spaces deployment. Simply push to your Spaces repository and it will automatically deploy.
+
+## Environment Variables
+
+- No environment variables required - API key is input through the UI
+
+## License
+
+MIT

TestVideo.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fa8d3ee0ed2c9f6f9de381a4d6ef8a5cee442d65ef5138fcc4a6396e2add1ada
+size 8015996

app.py

@@ -0,0 +1,5 @@
+# Hugging Face Spaces entry point
+from gradio_app import app
+
+if __name__ == "__main__":
+    app.launch()

gradio_app.py

@@ -5,31 +5,36 @@ import requests
 from lumaai import LumaAI
 import traceback
 
-from lib.status_utils import StatusTracker, load_messages
+from lib.status_utils import load_messages, StatusTracker
 from lib.image_utils import prepare_image
 from lib.api_utils import get_camera_motions
-from lib.ui_components import create_input_column, create_output_column
+from lib.ui_components import create_interface
 
-def generate_video(api_key, prompt, camera_motion, image=None, progress=gr.Progress()):
-    status_box = gr.Markdown()  # Create status box
+def generate_video(api_key, prompt, camera_motion, loop_video, image=None, progress=gr.Progress()):
     if not api_key or not prompt:
-        return None, "Please provide both API key and prompt (I'm not a mind reader... yet)"
+        raise gr.Error("Please enter your LumaAI API key and prompt")
     
     try:
-        status_tracker = StatusTracker(progress, status_box)
-        status_tracker.add_step("LumaAI initialized", 0.01)
+        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": True,
+            "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": {
@@ -37,23 +42,23 @@ def generate_video(api_key, prompt, camera_motion, image=None, progress=gr.Progr
                         "url": cdn_url
                     }
                 }
-                status_tracker.add_step("Image ready for its starring role", 0.1)
             except Exception as e:
-                return None, f"🎭 Drama in the image department: {str(e)}"
+                raise gr.Error("Failed to process the input image")
 
-        status_tracker.add_step("Sending your creative masterpiece to LumaAI", 0.15)
+        progress(0.2, desc="Starting generation...")
         try:
             generation = client.generations.create(**generation_params)
         except Exception as e:
-            return None, f"🎬 LumaAI didn't like that: {str(e)}"
+            raise gr.Error("Failed to start video generation. Please check your API key.")
         
-        # Load and shuffle status messages
+        # 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()
-        message_index = 0
         last_status = None
         
         while True:
@@ -61,36 +66,35 @@ def generate_video(api_key, prompt, camera_motion, image=None, progress=gr.Progr
                 generation_status = client.generations.get(generation.id)
                 status = generation_status.state
                 elapsed_time = time.time() - start_time
+                current_time = time.time()
                 
-                if status != last_status:
-                    status_tracker.add_step(f"Status: {status}", min(0.2 + (elapsed_time/300), 0.8))
-                    last_status = status
-                
-                current_message = status_messages[message_index % len(status_messages)]
-                status_tracker.update_message(current_message, min(0.2 + (elapsed_time/300), 0.8))
-                message_index += 1
+                # 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':
-                    status_tracker.add_step("Generation completed!", 0.9)
+                    progress(0.9, desc="Generation completed!")
                     download_url = generation_status.assets.video
                     break
                 elif status == 'failed':
-                    failure_reason = generation_status.failure_reason or "It's not you, it's me"
-                    return None, f"🎭 Generation failed: {failure_reason}"
+                    raise gr.Error("Video generation failed")
                 
                 if elapsed_time > 300:
-                    return None, "⏰ Generation timeout (5 minutes of awkward silence)"
+                    raise gr.Error("Generation timed out after 5 minutes")
                 
-                time.sleep(10)
+                time.sleep(1)
                 
             except Exception as e:
                 print(f"Error during generation polling: {str(e)}")
                 print(traceback.format_exc())
-                time.sleep(10)
+                time.sleep(1)
                 continue
         
         # Download the video
-        status_tracker.update_message("Downloading your masterpiece...", 0.95)
+        progress(0.95, desc="Downloading video...")
         try:
             response = requests.get(download_url, stream=True, timeout=30)
             response.raise_for_status()
@@ -98,38 +102,23 @@ def generate_video(api_key, prompt, camera_motion, image=None, progress=gr.Progr
             with open(file_path, 'wb') as file:
                 file.write(response.content)
             
-            status_tracker.add_step("🎉 Video ready!", 1.0)
-            return file_path, status_box
+            progress(1.0, desc="Video ready!")
+            return file_path
         except Exception as e:
-            return None, f"📺 Video download failed: {str(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())
-        return None, f"🎪 The show must go on, but: {str(e)}"
+        raise gr.Error("An unexpected error occurred")
 
-# Create Gradio interface with a modern theme
-with gr.Blocks(theme=gr.themes.Soft(
-    primary_hue="indigo",
-    secondary_hue="purple",
-)) as app:
-    gr.Markdown(
-        """
-        # 🎬 LumaAI Video Generator
-        ### Transform your prompts into mesmerizing videos
-        """
-    )
-    
-    with gr.Row():
-        # Create input and output columns
-        prompt, camera_motion, api_key, image_input, generate_btn, status_display = create_input_column()
-        video_output = create_output_column()
-    
-    generate_btn.click(
-        fn=generate_video,
-        inputs=[api_key, prompt, camera_motion, image_input],
-        outputs=[video_output, status_display]
-    )
+# 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()

lib/status_utils.py

@@ -16,7 +16,7 @@ class StatusTracker:
         self.status_box = status_box
         self.steps = []
         self.current_message = ""
-        self._status_markdown = "### 🎬 Ready to Generate"
+        self._status_markdown = ""
         
     def add_step(self, message: str, progress_value: float):
         """
@@ -26,9 +26,8 @@ class StatusTracker:
             message: Step description
             progress_value: Progress value between 0 and 1
         """
-        self.steps.append(f"✓ {message}")
+        self.steps.append(message)
         self._update_display(progress_value)
-        time.sleep(0.5)  # Brief pause for visibility
         
     def update_message(self, message: str, progress_value: float):
         """
@@ -38,7 +37,7 @@ class StatusTracker:
             message: Current status message
             progress_value: Progress value between 0 and 1
         """
-        self.current_message = f"➤ {message}"
+        self.current_message = message
         self._update_display(progress_value)
         
     def _update_display(self, progress_value: float):
@@ -48,17 +47,23 @@ class StatusTracker:
         Args:
             progress_value: Progress value between 0 and 1
         """
-        # Create markdown-formatted status display
-        status_md = "### 🎬 Generation Progress:\n"
-        for step in self.steps:
-            status_md += f"- {step}\n"
+        # Create status display
+        status_md = "### 🎬 Generation Progress\n\n"
+        
+        # Show completed steps
+        if self.steps:
+            for step in self.steps:
+                status_md += f"✓ {step}\n"
+            status_md += "\n"
+        
+        # Show current message prominently
         if self.current_message:
-            status_md += f"\n**Current Step:**\n{self.current_message}"
+            status_md += f"### 🔄 {self.current_message}\n"
             
         self._status_markdown = status_md
         self.progress(progress_value)
         
-        # Only try to update status_box if it exists
+        # Update status box if it exists
         if self.status_box is not None:
             try:
                 self.status_box.update(value=self._status_markdown)

lib/ui_components.py

@@ -1,57 +1,103 @@
 import gradio as gr
 from .api_utils import get_camera_motions
+from pathlib import Path
 
-def create_input_column():
-    """Create the input column of the UI."""
-    with gr.Column(scale=1, min_width=400) as column:
-        # Main inputs
-        prompt = gr.Textbox(
-            label="Prompt",
-            placeholder="Describe your video scene here...",
-            lines=3
-        )
-        camera_motion = gr.Dropdown(
-            choices=get_camera_motions(),
-            label="Camera Motion",
-            value="None"
-        )
-        
-        # Collapsible sections
-        with gr.Accordion("🔑 API Settings", open=False):
+def create_header():
+    """Create the header with title and API settings in 3 columns."""
+    with gr.Row():
+        # Title column
+        with gr.Column(scale=1):
+            gr.Markdown(
+                """
+                # 🎬 LumaAI Video Generator
+                ### Transform your prompts into mesmerizing videos
+                """
+            )
+            
+        # API info column
+        with gr.Column(scale=1):
+            gr.Markdown("Get an API key from [LumaAI Dream Machine](https://lumalabs.ai/dream-machine/api)")
+            gr.Markdown("*$0.0032 USD/megapixel: 720p, 5 sec video is around $0.4 USD*")
+    
+        # Empty column for symmetry
+        with gr.Column(scale=1):
+            pass
+
+def create_main_interface(generate_fn):
+    """Create the main interface with input and output columns."""
+    with gr.Row():
+        # Input column
+        with gr.Column(scale=1):
             api_key = gr.Textbox(
                 label="LumaAI API Key", 
-                placeholder="Enter your API key here",
-                type="password"
+                placeholder="Enter a LumaAI API key",
+                type="password",
+                autofocus=True,
+                show_label=False,
+                container=False,
+                scale=1
             )
-        
-        with gr.Accordion("🖼️ Advanced Options", open=False):
-            image_input = gr.Image(
-                label="Starting Image (will be resized to 512x512)",
-                type="pil"
+            
+            with gr.Row():
+                prompt = gr.Textbox(
+                    label="Prompt",
+                    placeholder="Describe your video scene here...",
+                    lines=3,
+                    value="Dreamlike scene transforms into circuitry"
+                )
+            
+            camera_motion = gr.Dropdown(
+                choices=get_camera_motions(),
+                label="Camera Motion",
+                value="None"
             )
+            
+            loop_video = gr.Checkbox(
+                label="Loop Video",
+                value=False,
+                info="Enable video looping"
+            )
+            
+            generate_btn = gr.Button("🚀 Generate Video", variant="primary", size="lg")
+            clear_btn = gr.Button("🗑️ Clear Placeholders", size="sm", variant="huggingface")
         
-        generate_btn = gr.Button("🚀 Generate Video", variant="primary", size="lg")
-        
-        # Status display
-        status_display = gr.Markdown()
-        
-        gr.Markdown(
-            """
-            ### 🎯 Pro Tips:
-            - Be specific and descriptive in your prompts
-            - Try different camera motions for dynamic effects
-            - Generation usually takes 1-3 minutes ☕
-            """
+        # Output column
+        with gr.Column(scale=1):
+            video_output = gr.Video(
+                label="Generated Video",
+                show_label=True,
+                width="100%",
+                height="400px",
+                value="TestVideo.mp4"
+            )
+            
+            with gr.Accordion("🖼️ Starting Image [Optional]", open=True):
+                image_input = gr.Image(
+                    label="Starting Image (will be resized to 512x512)",
+                    type="pil",
+                    value="TestImage.png"
+                )
+
+        # Set up event handlers
+        def clear_all():
+            return ["", None, None]  # Clear prompt, image, and video
+            
+        clear_btn.click(
+            fn=clear_all,
+            inputs=[],
+            outputs=[prompt, image_input, video_output]
         )
         
-        return prompt, camera_motion, api_key, image_input, generate_btn, status_display
-
-def create_output_column():
-    """Create the output column of the UI."""
-    with gr.Column(scale=1, min_width=600) as column:
-        video_output = gr.Video(
-            label="Generated Video",
-            width="100%",
-            height="400px"
+        generate_btn.click(
+            fn=generate_fn,
+            inputs=[api_key, prompt, camera_motion, loop_video, image_input],
+            outputs=video_output,
+            api_name=False
         )
-        return video_output
+
+def create_interface(generate_fn):
+    """Create the complete interface."""
+    with gr.Blocks(theme=gr.themes.Monochrome()) as interface:
+        create_header()
+        create_main_interface(generate_fn)
+        return interface

loading_messages.json

@@ -29,6 +29,26 @@
         "Performing ritual sacrifices to the GPU gods...",
         "Translating prompt into binary and back again...",
         "Asking AI to think outside the box (it's stuck)...",
-        "Generating random excuses for slow processing..."
+        "Generating random excuses for slow processing...",
+        "Convincing the AI this isn't just another cat video...",
+        "Teaching neural networks about personal space...",
+        "Negotiating with the cloud for better weather...",
+        "Explaining to AI why it can't have a coffee break...",
+        "Converting prompt into interpretive dance moves...",
+        "Asking the GPU if it needs a hug...",
+        "Teaching AI about fashion (still wearing pixels)...",
+        "Consulting the magic 8-ball for rendering advice...",
+        "Trying to explain memes to the neural network...",
+        "Asking AI to stop playing Minecraft with the pixels...",
+        "Converting your ideas into digital daydreams...",
+        "Teaching AI about personal boundaries (again)...",
+        "Explaining to GPU why overtime is mandatory...",
+        "Convincing AI that lens flares aren't always necessary...",
+        "Debugging the space-time continuum...",
+        "Asking AI to stop making everything cyberpunk...",
+        "Teaching neural networks about work-life balance...",
+        "Explaining to AI why it can't have a TikTok account...",
+        "Negotiating with pixels for better composition...",
+        "Convincing the render farm to work weekends..."
     ]
 }