app.py

import gradio as gr
from llm_inference_video import VideoLLMInferenceNode
import random

title = """<h1 align="center">CineGen: AI Video Prompt Architect</h1>
<p align="center">Generate cinematic video prompts with technical specifications</p>"""

def create_video_interface():
    llm_node = VideoLLMInferenceNode()

    with gr.Blocks(theme='bethecloud/storj_theme') as demo:
        gr.HTML(title)
        
        with gr.Row():
            with gr.Column(scale=2):
                input_concept = gr.Textbox(label="Core Concept/Thematic Input", lines=3)
                duration = gr.Slider(15, 600, value=60, label="Duration (seconds)")
                style = gr.Dropdown(
                    choices=["Cinematic", "Documentary", "Animation", "Action", "Experimental"],
                    value="Cinematic",
                    label="Video Style"
                )
                camera_style = gr.Dropdown(
                    choices=["Steadicam flow", "Drone aerials", "Handheld urgency", "Crane elegance", 
                           "Dolly precision", "VR 360", "Multi-angle rig"],
                    value="Steadicam flow",
                    label="Camera Movement Style"
                )
                
            with gr.Column(scale=2):
                pacing = gr.Dropdown(
                    choices=["Slow burn", "Rhythmic pulse", "Frantic energy", "Ebb and flow", "Hypnotic drift"],
                    value="Rhythmic pulse",
                    label="Pacing Rhythm"
                )
                special_effects = gr.Dropdown(
                    choices=["Practical effects", "CGI enhancement", "Analog glitches", 
                           "Light painting", "Projection mapping", "Nanosecond exposures"],
                    value="Practical effects",
                    label="SFX Approach"
                )
                custom_elements = gr.Textbox(label="Custom Technical Elements", 
                                           placeholder="e.g., Infrared hybrid, Datamosh transitions")
                
                provider = gr.Dropdown(
                    choices=["Hugging Face", "Groq", "SambaNova"],
                    value="Hugging Face",
                    label="LLM Provider"
                )
                model = gr.Dropdown(label="Model", value="meta-llama/Meta-Llama-3.1-70B-Instruct")

        generate_btn = gr.Button("Generate Video Blueprint", variant="primary")
        output = gr.Textbox(label="Video Production Prompt", lines=12, interactive=False)

        generate_btn.click(
            llm_node.generate_video_prompt,
            inputs=[input_concept, duration, style, camera_style, pacing, special_effects, 
                   custom_elements, provider, model],
            outputs=output
        )

    return demo

if __name__ == "__main__":
    demo = create_video_interface()
    demo.launch(share=True)