import gradio as gr
import torch
import numpy as np
import os
# from diffusers import MotionCtrlPipeline # Placeholder for actual diffusers/custom pipeline

# --- Configuration & Model Loading ---
DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
# Model initialization would go here. 
# Example: 
# pipe = MotionCtrlPipeline.from_pretrained("TencentARC/MotionCtrl").to(DEVICE)

def generate_motion_video(
    prompt, 
    camera_pan, 
    camera_tilt, 
    camera_zoom, 
    camera_roll,
    num_frames,
    guidance_scale,
    num_inference_steps,
    seed,
    progress=gr.Progress()
):
    """
    Core generation function. 
    Connect your specific Diffusers or PyTorch motion control pipeline here.
    """
    progress(0, desc="Initializing...")
    
    # Set seed for reproducibility
    if seed == -1:
        seed = np.random.randint(0, 2**32 - 1)
    generator = torch.Generator(device=DEVICE).manual_seed(seed)
    
    progress(0.2, desc="Encoding prompts and trajectories...")
    
    # ---------------------------------------------------------
    # INSERT INFERENCE CODE HERE
    # Example for a generic MotionCtrl-style pipeline:
    # 
    # camera_poses = calculate_poses(camera_pan, camera_tilt, camera_zoom, camera_roll)
    # video = pipe(
    #     prompt=prompt,
    #     camera_poses=camera_poses,
    #     num_frames=num_frames,
    #     guidance_scale=guidance_scale,
    #     num_inference_steps=num_inference_steps,
    #     generator=generator
    # ).frames[0]
    # 
    # video_path = export_to_video(video)
    # ---------------------------------------------------------
    
    # Simulated delay/output for UI demonstration purposes
    import time
    for i in range(1, 11):
        time.sleep(0.5) # Simulating generation time
        progress(i / 10, desc=f"Generating frame {i*(num_frames//10)}/{num_frames}...")
        
    placeholder_output = "output_placeholder.mp4"
    # open(placeholder_output, 'w').close() # creates a dummy file
    
    return placeholder_output, seed

# --- UI Layout ---
# Using a clean, modern theme
theme = gr.themes.Soft(
    primary_hue="indigo",
    secondary_hue="blue",
    neutral_hue="slate",
    font=[gr.themes.GoogleFont("Inter"), "sans-serif"]
)

with gr.Blocks(theme=theme, title="Advanced Motion Control Generation") as app:
    gr.Markdown(
        """
        # 🎬 Advanced Motion Control Video Generation
        Control camera trajectories and object movement seamlessly. Enter your prompt, dial in your camera movements, and generate.
        """
    )
    
    with gr.Row():
        with gr.Column(scale=4):
            # Prompt Area
            prompt = gr.Textbox(
                label="Prompt", 
                placeholder="A cinematic drone shot of a futuristic city at sunset, neon lights...", 
                lines=3
            )
            
            # Motion Controls
            with gr.Group():
                gr.Markdown("### 🎥 Camera Controls")
                with gr.Row():
                    camera_pan = gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Pan (Left/Right)")
                    camera_tilt = gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Tilt (Up/Down)")
                with gr.Row():
                    camera_zoom = gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Zoom (In/Out)")
                    camera_roll = gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Roll (Rotation)")
            
            # Advanced Settings
            with gr.Accordion("⚙️ Advanced Settings", open=False):
                with gr.Row():
                    num_frames = gr.Slider(minimum=8, maximum=32, step=8, value=16, label="Number of Frames")
                    num_inference_steps = gr.Slider(minimum=10, maximum=100, step=1, value=25, label="Inference Steps")
                with gr.Row():
                    guidance_scale = gr.Slider(minimum=1.0, maximum=20.0, step=0.5, value=7.5, label="CFG Scale")
                    seed = gr.Number(value=-1, label="Seed (-1 for random)", precision=0)
            
            generate_btn = gr.Button("Generate Video 🚀", variant="primary", size="lg")
            
        with gr.Column(scale=3):
            # Output Area
            output_video = gr.Video(label="Generated Video", interactive=False)
            output_seed = gr.Number(label="Used Seed", interactive=False)
            
            gr.Markdown(
                """
                ### 💡 Tips for Better Results
                * **Pan/Tilt:** Negative values go Left/Up, positive values go Right/Down.
                * **Zoom:** Positive values zoom in, negative values zoom out.
                * High CFG scales (>10) might cause visual artifacts depending on the prompt.
                """
            )

    # Event Wiring
    generate_btn.click(
        fn=generate_motion_video,
        inputs=[
            prompt, 
            camera_pan, 
            camera_tilt, 
            camera_zoom, 
            camera_roll,
            num_frames,
            guidance_scale,
            num_inference_steps,
            seed
        ],
        outputs=[output_video, output_seed]
    )

if __name__ == "__main__":
    # Launching with debug mode enabled and queue for handling multiple users smoothly
    app.queue(max_size=10).launch(debug=True, show_api=False)