Automating Scalable Video Generation and FFmpeg Rendering Pipelines with Generative AI Models

import subprocess
import os

def render_final_video(
    video_clips: list[str],
    audio_track: str,
    output_path: str
) -> str:
    """Stitches video segments, attaches audio, and burns subtitled overlays using FFmpeg."""
    
    # 1. Create temporary file list for FFmpeg concatenation
    concat_file = "temp_clips.txt"
    with open(concat_file, "w") as f:
        for clip in video_clips:
            f.write(f"file '{clip}'\n")
            
    # 2. Build high-performance GPU-accelerated FFmpeg command
    cmd = [
        "ffmpeg", "-y",
        "-f", "concat", "-safe", "0", "-i", concat_file,
        "-i", audio_track,
        "-c:v", "h264_nvenc",  # NVIDIA GPU Acceleration
        "-preset", "p4",
        "-b:v", "8M",
        "-c:a", "aac", "-b:a", "192k",
        "-shortest",
        output_path
    ]
    
    result = subprocess.run(cmd, capture_output=True, text=True)
    if result.returncode != 0:
        raise RuntimeError(f"FFmpeg rendering failed: {result.stderr}")
        
    os.remove(concat_file)
    return output_path