Generik

app.py

@@ -5,7 +5,6 @@ import logging
 import os
 from pathlib import Path
 from datetime import datetime
-import re
 
 import torch
 import numpy as np
@@ -16,42 +15,19 @@ from diffusers import AutoModel
 import gradio as gr
 import tempfile
 from huggingface_hub import hf_hub_download
-import traceback
-
-# Patch for scaled_dot_product_attention to fix enable_gqa issue
-import torch.nn.functional as F
-
-original_sdpa = F.scaled_dot_product_attention
-
-def patched_scaled_dot_product_attention(query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False, scale=None, enable_gqa=None):
-   # enable_gqa 파라미터를 무시하고 나머지 파라미터만 전달
-   kwargs = {}
-   if attn_mask is not None:
-       kwargs['attn_mask'] = attn_mask
-   if dropout_p != 0.0:
-       kwargs['dropout_p'] = dropout_p
-   if is_causal:
-       kwargs['is_causal'] = is_causal
-   if scale is not None:
-       kwargs['scale'] = scale
-   
-   return original_sdpa(query, key, value, **kwargs)
-
-# 패치 적용
-F.scaled_dot_product_attention = patched_scaled_dot_product_attention
 
 from src.pipeline_wan_nag import NAGWanPipeline
 from src.transformer_wan_nag import NagWanTransformer3DModel
 
 # MMAudio imports
 try:
-   import mmaudio
+    import mmaudio
 except ImportError:
-   os.system("pip install -e .")
-   import mmaudio
+    os.system("pip install -e .")
+    import mmaudio
 
 from mmaudio.eval_utils import (ModelConfig, all_model_cfg, generate as mmaudio_generate, 
-                               load_video, make_video, setup_eval_logging)
+                                load_video, make_video, setup_eval_logging)
 from mmaudio.model.flow_matching import FlowMatching
 from mmaudio.model.networks import MMAudio, get_my_mmaudio
 from mmaudio.model.sequence_config import SequenceConfig
@@ -75,7 +51,7 @@ MIN_FRAMES_MODEL = 8
 MAX_FRAMES_MODEL = 129
 
 DEFAULT_NAG_NEGATIVE_PROMPT = "Static, motionless, still, ugly, bad quality, worst quality, poorly drawn, low resolution, blurry, lack of details"
-DEFAULT_AUDIO_NEGATIVE_PROMPT = "music, speech, voice, singing, narration"
+DEFAULT_AUDIO_NEGATIVE_PROMPT = "music"
 
 # NAG Model Settings
 MODEL_ID = "Wan-AI/Wan2.1-T2V-14B-Diffusers"
@@ -96,500 +72,421 @@ setup_eval_logging()
 
 # Initialize NAG Video Model
 try:
-   vae = AutoencoderKLWan.from_pretrained(MODEL_ID, subfolder="vae", torch_dtype=torch.float32)
-   wan_path = hf_hub_download(repo_id=SUB_MODEL_ID, filename=SUB_MODEL_FILENAME)
-   transformer = NagWanTransformer3DModel.from_single_file(wan_path, torch_dtype=torch.bfloat16)
-   pipe = NAGWanPipeline.from_pretrained(
-       MODEL_ID, vae=vae, transformer=transformer, torch_dtype=torch.bfloat16
-   )
-   pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=5.0)
-   pipe.to("cuda")
-
-   pipe.transformer.__class__.attn_processors = NagWanTransformer3DModel.attn_processors
-   pipe.transformer.__class__.set_attn_processor = NagWanTransformer3DModel.set_attn_processor
-   pipe.transformer.__class__.forward = NagWanTransformer3DModel.forward
-   print("NAG Video Model loaded successfully!")
+    vae = AutoencoderKLWan.from_pretrained(MODEL_ID, subfolder="vae", torch_dtype=torch.float32)
+    wan_path = hf_hub_download(repo_id=SUB_MODEL_ID, filename=SUB_MODEL_FILENAME)
+    transformer = NagWanTransformer3DModel.from_single_file(wan_path, torch_dtype=torch.bfloat16)
+    pipe = NAGWanPipeline.from_pretrained(
+        MODEL_ID, vae=vae, transformer=transformer, torch_dtype=torch.bfloat16
+    )
+    pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=5.0)
+    pipe.to("cuda")
+
+    pipe.transformer.__class__.attn_processors = NagWanTransformer3DModel.attn_processors
+    pipe.transformer.__class__.set_attn_processor = NagWanTransformer3DModel.set_attn_processor
+    pipe.transformer.__class__.forward = NagWanTransformer3DModel.forward
+    print("NAG Video Model loaded successfully!")
 except Exception as e:
-   print(f"Error loading NAG Video Model: {e}")
-   pipe = None
+    print(f"Error loading NAG Video Model: {e}")
+    pipe = None
 
 # Initialize MMAudio Model
 def get_mmaudio_model() -> tuple[MMAudio, FeaturesUtils, SequenceConfig]:
-   seq_cfg = audio_model_config.seq_cfg
-   
-   net: MMAudio = get_my_mmaudio(audio_model_config.model_name).to(device, dtype).eval()
-   net.load_weights(torch.load(audio_model_config.model_path, map_location=device, weights_only=True))
-   log.info(f'Loaded MMAudio weights from {audio_model_config.model_path}')
-   
-   feature_utils = FeaturesUtils(tod_vae_ckpt=audio_model_config.vae_path,
-                                 synchformer_ckpt=audio_model_config.synchformer_ckpt,
-                                 enable_conditions=True,
-                                 mode=audio_model_config.mode,
-                                 bigvgan_vocoder_ckpt=audio_model_config.bigvgan_16k_path,
-                                 need_vae_encoder=False)
-   feature_utils = feature_utils.to(device, dtype).eval()
-   
-   return net, feature_utils, seq_cfg
+    seq_cfg = audio_model_config.seq_cfg
+    
+    net: MMAudio = get_my_mmaudio(audio_model_config.model_name).to(device, dtype).eval()
+    net.load_weights(torch.load(audio_model_config.model_path, map_location=device, weights_only=True))
+    log.info(f'Loaded MMAudio weights from {audio_model_config.model_path}')
+    
+    feature_utils = FeaturesUtils(tod_vae_ckpt=audio_model_config.vae_path,
+                                  synchformer_ckpt=audio_model_config.synchformer_ckpt,
+                                  enable_conditions=True,
+                                  mode=audio_model_config.mode,
+                                  bigvgan_vocoder_ckpt=audio_model_config.bigvgan_16k_path,
+                                  need_vae_encoder=False)
+    feature_utils = feature_utils.to(device, dtype).eval()
+    
+    return net, feature_utils, seq_cfg
 
 try:
-   audio_net, audio_feature_utils, audio_seq_cfg = get_mmaudio_model()
-   print("MMAudio Model loaded successfully!")
+    audio_net, audio_feature_utils, audio_seq_cfg = get_mmaudio_model()
+    print("MMAudio Model loaded successfully!")
 except Exception as e:
-   print(f"Error loading MMAudio Model: {e}")
-   audio_net = None
-
-# 비디오 프롬프트를 오디오 프롬프트로 변환하는 함수
-def extract_audio_description(video_prompt):
-   """비디오 프롬프트에서 오디오 관련 설명 추출/변환"""
-   
-   # 키워드 매핑
-   audio_keywords = {
-       'car': 'car engine sound, vehicle noise',
-       'porsche': 'sports car engine roar, exhaust sound',
-       'guitar': 'electric guitar playing, guitar music',
-       'concert': 'crowd cheering, live music, applause',
-       'motorcycle': 'motorcycle engine sound, motor rumble',
-       'highway': 'traffic noise, road ambience',
-       'rain': 'rain sounds, water drops',
-       'wind': 'wind blowing sound',
-       'ocean': 'ocean waves, water sounds',
-       'city': 'urban ambience, city traffic sounds',
-       'singer': 'singing voice, vocals',
-       'crowd': 'crowd noise, people talking',
-       'flames': 'fire crackling sound',
-       'pyro': 'fire whoosh, flame burst sound',
-       'explosion': 'explosion sound, blast',
-       'countryside': 'nature ambience, birds chirping',
-       'wheat fields': 'wind through grass, rural ambience',
-       'engine': 'motor sound, mechanical noise',
-       'flat-six engine': 'sports car engine sound',
-       'roaring': 'loud engine roar',
-       'thunderous': 'loud booming sound',
-       'child': 'children playing sounds',
-       'running': 'footsteps sound',
-       'woman': 'ambient sounds',
-       'phone': 'subtle electronic ambience',
-       'advertisement': 'modern ambient sounds'
-   }
-   
-   # 간단한 키워드 기반 변환
-   audio_descriptions = []
-   lower_prompt = video_prompt.lower()
-   
-   for key, value in audio_keywords.items():
-       if key in lower_prompt:
-           audio_descriptions.append(value)
-   
-   # 기본값 설정
-   if not audio_descriptions:
-       # 프롬프트에 명시적인 오디오 설명이 있는지 확인
-       if 'sound' in lower_prompt or 'audio' in lower_prompt or 'noise' in lower_prompt:
-           # 프롬프트에서 오디오 관련 부분만 추출
-           audio_pattern = r'([^.]*(?:sound|audio|noise|music|voice|roar|rumble)[^.]*)'
-           matches = re.findall(audio_pattern, lower_prompt, re.IGNORECASE)
-           if matches:
-               return ', '.join(matches)
-       
-       # 기본 ambient sound
-       return "ambient environmental sounds matching the scene"
-   
-   return ', '.join(audio_descriptions)
+    print(f"Error loading MMAudio Model: {e}")
+    audio_net = None
 
 # Audio generation function
 @torch.inference_mode()
-def add_audio_to_video(video_path, prompt, audio_custom_prompt, audio_negative_prompt, audio_steps, audio_cfg_strength, duration):
-   """Generate and add audio to video using MMAudio"""
-   if audio_net is None:
-       print("MMAudio model not loaded, returning video without audio")
-       return video_path
-       
-   try:
-       # 커스텀 오디오 프롬프트가 있으면 사용, 없으면 비디오 프롬프트에서 추출
-       if audio_custom_prompt and audio_custom_prompt.strip():
-           audio_prompt = audio_custom_prompt.strip()
-       else:
-           audio_prompt = extract_audio_description(prompt)
-       
-       print(f"Original prompt: {prompt}")
-       print(f"Audio prompt: {audio_prompt}")
-       
-       rng = torch.Generator(device=device)
-       rng.manual_seed(random.randint(0, 2**32 - 1))  # 더 명확한 랜덤 시드
-       fm = FlowMatching(min_sigma=0, inference_mode='euler', num_steps=audio_steps)
-       
-       video_info = load_video(video_path, duration)
-       clip_frames = video_info.clip_frames
-       sync_frames = video_info.sync_frames
-       duration = video_info.duration_sec
-       clip_frames = clip_frames.unsqueeze(0)
-       sync_frames = sync_frames.unsqueeze(0)
-       audio_seq_cfg.duration = duration
-       audio_net.update_seq_lengths(audio_seq_cfg.latent_seq_len, audio_seq_cfg.clip_seq_len, audio_seq_cfg.sync_seq_len)
-       
-       # 향상된 네거티브 프롬프트
-       enhanced_negative = f"{audio_negative_prompt}, distortion, static noise, silence, random beeps"
-       
-       audios = mmaudio_generate(clip_frames,
-                                 sync_frames, [audio_prompt],  # 변환된 오디오 프롬프트 사용
-                                 negative_text=[enhanced_negative],
-                                 feature_utils=audio_feature_utils,
-                                 net=audio_net,
-                                 fm=fm,
-                                 rng=rng,
-                                 cfg_strength=audio_cfg_strength)
-       audio = audios.float().cpu()[0]
-       
-       # Create video with audio
-       video_with_audio_path = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4').name
-       make_video(video_info, video_with_audio_path, audio, sampling_rate=audio_seq_cfg.sampling_rate)
-       
-       return video_with_audio_path
-   except Exception as e:
-       print(f"Error in audio generation: {e}")
-       traceback.print_exc()
-       return video_path
+def add_audio_to_video(video_path, prompt, audio_negative_prompt, audio_steps, audio_cfg_strength, duration):
+    """Generate and add audio to video using MMAudio"""
+    if audio_net is None:
+        print("MMAudio model not loaded, returning video without audio")
+        return video_path
+        
+    try:
+        rng = torch.Generator(device=device)
+        rng.seed()  # Random seed for audio
+        fm = FlowMatching(min_sigma=0, inference_mode='euler', num_steps=audio_steps)
+        
+        video_info = load_video(video_path, duration)
+        clip_frames = video_info.clip_frames
+        sync_frames = video_info.sync_frames
+        duration = video_info.duration_sec
+        clip_frames = clip_frames.unsqueeze(0)
+        sync_frames = sync_frames.unsqueeze(0)
+        audio_seq_cfg.duration = duration
+        audio_net.update_seq_lengths(audio_seq_cfg.latent_seq_len, audio_seq_cfg.clip_seq_len, audio_seq_cfg.sync_seq_len)
+        
+        audios = mmaudio_generate(clip_frames,
+                                  sync_frames, [prompt],
+                                  negative_text=[audio_negative_prompt],
+                                  feature_utils=audio_feature_utils,
+                                  net=audio_net,
+                                  fm=fm,
+                                  rng=rng,
+                                  cfg_strength=audio_cfg_strength)
+        audio = audios.float().cpu()[0]
+        
+        # Create video with audio
+        video_with_audio_path = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4').name
+        make_video(video_info, video_with_audio_path, audio, sampling_rate=audio_seq_cfg.sampling_rate)
+        
+        return video_with_audio_path
+    except Exception as e:
+        print(f"Error in audio generation: {e}")
+        return video_path
 
 # Combined generation function
 def get_duration(prompt, nag_negative_prompt, nag_scale, height, width, duration_seconds, 
-                steps, seed, randomize_seed, enable_audio, audio_custom_prompt,
-                audio_negative_prompt, audio_steps, audio_cfg_strength):
-   # Calculate total duration including audio processing if enabled
-   video_duration = int(duration_seconds) * int(steps) * 2.25 + 5
-   audio_duration = 30 if enable_audio else 0  # Additional time for audio processing
-   return video_duration + audio_duration
+                 steps, seed, randomize_seed, enable_audio, audio_negative_prompt, 
+                 audio_steps, audio_cfg_strength):
+    # Calculate total duration including audio processing if enabled
+    video_duration = int(duration_seconds) * int(steps) * 2.25 + 5
+    audio_duration = 30 if enable_audio else 0  # Additional time for audio processing
+    return video_duration + audio_duration
 
 @spaces.GPU(duration=get_duration)
 def generate_video_with_audio(
-       prompt,
-       nag_negative_prompt, nag_scale,
-       height=DEFAULT_H_SLIDER_VALUE, width=DEFAULT_W_SLIDER_VALUE, duration_seconds=DEFAULT_DURATION_SECONDS,
-       steps=DEFAULT_STEPS,
-       seed=DEFAULT_SEED, randomize_seed=False,
-       enable_audio=True, audio_custom_prompt="",
-       audio_negative_prompt=DEFAULT_AUDIO_NEGATIVE_PROMPT,
-       audio_steps=30, audio_cfg_strength=4.5,
+        prompt,
+        nag_negative_prompt, nag_scale,
+        height=DEFAULT_H_SLIDER_VALUE, width=DEFAULT_W_SLIDER_VALUE, duration_seconds=DEFAULT_DURATION_SECONDS,
+        steps=DEFAULT_STEPS,
+        seed=DEFAULT_SEED, randomize_seed=False,
+        enable_audio=True, audio_negative_prompt=DEFAULT_AUDIO_NEGATIVE_PROMPT,
+        audio_steps=25, audio_cfg_strength=4.5,
 ):
-   if pipe is None:
-       return None, DEFAULT_SEED
-       
-   try:
-       # Generate video first
-       target_h = max(MOD_VALUE, (int(height) // MOD_VALUE) * MOD_VALUE)
-       target_w = max(MOD_VALUE, (int(width) // MOD_VALUE) * MOD_VALUE)
-       
-       num_frames = np.clip(int(round(int(duration_seconds) * FIXED_FPS) + 1), MIN_FRAMES_MODEL, MAX_FRAMES_MODEL)
-       
-       current_seed = random.randint(0, MAX_SEED) if randomize_seed else int(seed)
-       
-       print(f"Generating video with: prompt='{prompt}', resolution={target_w}x{target_h}, frames={num_frames}")
-       
-       with torch.inference_mode():
-           nag_output_frames_list = pipe(
-               prompt=prompt,
-               nag_negative_prompt=nag_negative_prompt,
-               nag_scale=nag_scale,
-               nag_tau=3.5,
-               nag_alpha=0.5,
-               height=target_h, width=target_w, num_frames=num_frames,
-               guidance_scale=0.,
-               num_inference_steps=int(steps),
-               generator=torch.Generator(device="cuda").manual_seed(current_seed)
-           ).frames[0]
-       
-       # Save initial video without audio
-       with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
-           temp_video_path = tmpfile.name
-       export_to_video(nag_output_frames_list, temp_video_path, fps=FIXED_FPS)
-       print(f"Video saved to: {temp_video_path}")
-       
-       # Add audio if enabled
-       if enable_audio:
-           try:
-               print("Adding audio to video...")
-               final_video_path = add_audio_to_video(
-                   temp_video_path, 
-                   prompt,
-                   audio_custom_prompt,
-                   audio_negative_prompt,
-                   audio_steps,
-                   audio_cfg_strength,
-                   duration_seconds
-               )
-               # Clean up temp video
-               if os.path.exists(temp_video_path) and final_video_path != temp_video_path:
-                   os.remove(temp_video_path)
-               print(f"Final video with audio: {final_video_path}")
-           except Exception as e:
-               log.error(f"Audio generation failed: {e}")
-               final_video_path = temp_video_path
-       else:
-           final_video_path = temp_video_path
-       
-       return final_video_path, current_seed
-   except Exception as e:
-       print(f"Error in video generation: {e}")
-       return None, current_seed
+    if pipe is None:
+        return None, DEFAULT_SEED
+        
+    try:
+        # Generate video first
+        target_h = max(MOD_VALUE, (int(height) // MOD_VALUE) * MOD_VALUE)
+        target_w = max(MOD_VALUE, (int(width) // MOD_VALUE) * MOD_VALUE)
+        
+        num_frames = np.clip(int(round(int(duration_seconds) * FIXED_FPS) + 1), MIN_FRAMES_MODEL, MAX_FRAMES_MODEL)
+        
+        current_seed = random.randint(0, MAX_SEED) if randomize_seed else int(seed)
+        
+        print(f"Generating video with: prompt='{prompt}', resolution={target_w}x{target_h}, frames={num_frames}")
+        
+        with torch.inference_mode():
+            nag_output_frames_list = pipe(
+                prompt=prompt,
+                nag_negative_prompt=nag_negative_prompt,
+                nag_scale=nag_scale,
+                nag_tau=3.5,
+                nag_alpha=0.5,
+                height=target_h, width=target_w, num_frames=num_frames,
+                guidance_scale=0.,
+                num_inference_steps=int(steps),
+                generator=torch.Generator(device="cuda").manual_seed(current_seed)
+            ).frames[0]
+        
+        # Save initial video without audio
+        with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmpfile:
+            temp_video_path = tmpfile.name
+        export_to_video(nag_output_frames_list, temp_video_path, fps=FIXED_FPS)
+        print(f"Video saved to: {temp_video_path}")
+        
+        # Add audio if enabled
+        if enable_audio:
+            try:
+                print("Adding audio to video...")
+                final_video_path = add_audio_to_video(
+                    temp_video_path, 
+                    prompt,  # Use the same prompt for audio generation
+                    audio_negative_prompt,
+                    audio_steps,
+                    audio_cfg_strength,
+                    duration_seconds
+                )
+                # Clean up temp video
+                if os.path.exists(temp_video_path) and final_video_path != temp_video_path:
+                    os.remove(temp_video_path)
+                print(f"Final video with audio: {final_video_path}")
+            except Exception as e:
+                log.error(f"Audio generation failed: {e}")
+                final_video_path = temp_video_path
+        else:
+            final_video_path = temp_video_path
+        
+        return final_video_path, current_seed
+    except Exception as e:
+        print(f"Error in video generation: {e}")
+        return None, current_seed
 
 # Example generation function - simplified
 def set_example(prompt, nag_negative_prompt, nag_scale):
-   """Set example values in the UI without triggering generation"""
-   return (
-       prompt,
-       nag_negative_prompt,
-       nag_scale,
-       DEFAULT_H_SLIDER_VALUE,
-       DEFAULT_W_SLIDER_VALUE,
-       DEFAULT_DURATION_SECONDS,
-       DEFAULT_STEPS,
-       DEFAULT_SEED,
-       True,  # randomize_seed
-       True,  # enable_audio
-       "",    # audio_custom_prompt
-       DEFAULT_AUDIO_NEGATIVE_PROMPT,
-       30,    # audio_steps
-       4.5    # audio_cfg_strength
-   )
+    """Set example values in the UI without triggering generation"""
+    return (
+        prompt,
+        nag_negative_prompt,
+        nag_scale,
+        DEFAULT_H_SLIDER_VALUE,
+        DEFAULT_W_SLIDER_VALUE,
+        DEFAULT_DURATION_SECONDS,
+        DEFAULT_STEPS,
+        DEFAULT_SEED,
+        True,  # randomize_seed
+        True,  # enable_audio
+        DEFAULT_AUDIO_NEGATIVE_PROMPT,
+        25,    # audio_steps
+        4.5    # audio_cfg_strength
+    )
 
 # Examples with audio descriptions
 examples = [
-   ["Midnight highway outside a neon-lit city. A black 1973 Porsche 911 Carrera RS speeds at 120 km/h. Inside, a stylish singer-guitarist sings while driving, vintage sunburst guitar on the passenger seat. Sodium streetlights streak over the hood; RGB panels shift magenta to blue on the driver. Camera: drone dive, Russian-arm low wheel shot, interior gimbal, FPV barrel roll, overhead spiral. Neo-noir palette, rain-slick asphalt reflections, roaring flat-six engine blended with live guitar.", DEFAULT_NAG_NEGATIVE_PROMPT, 11],
-   ["Arena rock concert packed with 20 000 fans. A flamboyant lead guitarist in leather jacket and mirrored aviators shreds a cherry-red Flying V on a thrust stage. Pyro flames shoot up on every downbeat, CO₂ jets burst behind. Moving-head spotlights swirl teal and amber, follow-spots rim-light the guitarist's hair. Steadicam 360-orbit, crane shot rising over crowd, ultra-slow-motion pick attack at 1 000 fps. Film-grain teal-orange grade, thunderous crowd roar mixes with screaming guitar solo.", DEFAULT_NAG_NEGATIVE_PROMPT, 11],
-   ["Golden-hour countryside road winding through rolling wheat fields. A man and woman ride a vintage café-racer motorcycle, hair and scarf fluttering in the warm breeze. Drone chase shot reveals endless patchwork farmland; low slider along rear wheel captures dust trail. Sun-flare back-lights the riders, lens blooms on highlights. Soft acoustic rock underscore; engine rumble mixed at –8 dB. Warm pastel color grade, gentle film-grain for nostalgic vibe.", DEFAULT_NAG_NEGATIVE_PROMPT, 11],
+    ["Midnight highway outside a neon-lit city. A black 1973 Porsche 911 Carrera RS speeds at 120 km/h. Inside, a stylish singer-guitarist sings while driving, vintage sunburst guitar on the passenger seat. Sodium streetlights streak over the hood; RGB panels shift magenta to blue on the driver. Camera: drone dive, Russian-arm low wheel shot, interior gimbal, FPV barrel roll, overhead spiral. Neo-noir palette, rain-slick asphalt reflections, roaring flat-six engine blended with live guitar.", DEFAULT_NAG_NEGATIVE_PROMPT, 11],
+    ["Arena rock concert packed with 20 000 fans. A flamboyant lead guitarist in leather jacket and mirrored aviators shreds a cherry-red Flying V on a thrust stage. Pyro flames shoot up on every downbeat, CO₂ jets burst behind. Moving-head spotlights swirl teal and amber, follow-spots rim-light the guitarist's hair. Steadicam 360-orbit, crane shot rising over crowd, ultra-slow-motion pick attack at 1 000 fps. Film-grain teal-orange grade, thunderous crowd roar mixes with screaming guitar solo.", DEFAULT_NAG_NEGATIVE_PROMPT, 11],
+    ["Golden-hour countryside road winding through rolling wheat fields. A man and woman ride a vintage café-racer motorcycle, hair and scarf fluttering in the warm breeze. Drone chase shot reveals endless patchwork farmland; low slider along rear wheel captures dust trail. Sun-flare back-lights the riders, lens blooms on highlights. Soft acoustic rock underscore; engine rumble mixed at –8 dB. Warm pastel color grade, gentle film-grain for nostalgic vibe.", DEFAULT_NAG_NEGATIVE_PROMPT, 11],
 ]
 
 # CSS styling - Fixed for better layout
 css = """
 /* Right column - video output */
 .video-output {
-   border-radius: 15px;
-   overflow: hidden;
-   box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2);
-   width: 100% !important;
-   height: auto !important;
-   min-height: 400px;
+    border-radius: 15px;
+    overflow: hidden;
+    box-shadow: 0 10px 30px rgba(0, 0, 0, 0.2);
+    width: 100% !important;
+    height: auto !important;
+    min-height: 400px;
 }
 
 /* Ensure video container is responsive */
 .video-output video {
-   width: 100% !important;
-   height: auto !important;
-   max-height: 600px;
-   object-fit: contain;
-   display: block;
+    width: 100% !important;
+    height: auto !important;
+    max-height: 600px;
+    object-fit: contain;
+    display: block;
 }
 
 /* Remove any overlay or background from video container */
 .video-output > div {
-   background: transparent !important;
-   padding: 0 !important;
+    background: transparent !important;
+    padding: 0 !important;
 }
 
 /* Remove gradio's default video player overlay */
 .video-output .wrap {
-   background: transparent !important;
+    background: transparent !important;
 }
 
 /* Ensure no gray overlay on video controls */
 .video-output video::-webkit-media-controls-enclosure {
-   background: transparent;
+    background: transparent;
 }
 """
 
 # Gradio interface - Fixed structure
 with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
-   gr.HTML("""
-       <div class="container">
-           <h1 class="main-title">🎬 VEO3 Free</h1>
-           <p class="subtitle">Wan2.1-T2V-14B + Fast 4-step with NAG + Automatic Audio Generation</p>
-       </div>
-   """)
-   
-   gr.HTML("""
-       <div class='container' style='display:flex; justify-content:center; gap:12px; margin-bottom: 20px;'>
-           <a href="https://huggingface.co/spaces/openfree/Best-AI" target="_blank">
-               <img src="https://img.shields.io/static/v1?label=OpenFree&message=BEST%20AI%20Services&color=%230000ff&labelColor=%23000080&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="OpenFree badge">
-           </a>
-
-           <a href="https://discord.gg/openfreeai" target="_blank">
-               <img src="https://img.shields.io/static/v1?label=Discord&message=Openfree%20AI&color=%230000ff&labelColor=%23800080&logo=discord&logoColor=white&style=for-the-badge" alt="Discord badge">
-           </a>
-       </div>
-   """)
-   
-   with gr.Row(equal_height=True):
-       with gr.Column(scale=5):
-           with gr.Group(elem_classes="prompt-container"):
-               prompt = gr.Textbox(
-                   label="✨ Video Prompt (also used for audio generation)",
-                   placeholder="Describe your video scene in detail...",
-                   lines=3,
-                   elem_classes="prompt-input"
-               )
-               
-               with gr.Accordion("🎨 Advanced Video Settings", open=False):
-                   nag_negative_prompt = gr.Textbox(
-                       label="Video Negative Prompt",
-                       value=DEFAULT_NAG_NEGATIVE_PROMPT,
-                       lines=2,
-                   )
-                   nag_scale = gr.Slider(
-                       label="NAG Scale",
-                       minimum=1.0,
-                       maximum=20.0,
-                       step=0.25,
-                       value=11.0,
-                       info="Higher values = stronger guidance"
-                   )
-           
-           with gr.Group(elem_classes="settings-panel"):
-               gr.Markdown("### ⚙️ Video Settings")
-               
-               with gr.Row():
-                   duration_seconds_input = gr.Slider(
-                       minimum=1,
-                       maximum=8,
-                       step=1,
-                       value=DEFAULT_DURATION_SECONDS,
-                       label="📱 Duration (seconds)",
-                       elem_classes="slider-container"
-                   )
-                   steps_slider = gr.Slider(
-                       minimum=1,
-                       maximum=8,
-                       step=1,
-                       value=DEFAULT_STEPS,
-                       label="🔄 Inference Steps",
-                       elem_classes="slider-container"
-                   )
-               
-               with gr.Row():
-                   height_input = gr.Slider(
-                       minimum=SLIDER_MIN_H,
-                       maximum=SLIDER_MAX_H,
-                       step=MOD_VALUE,
-                       value=DEFAULT_H_SLIDER_VALUE,
-                       label=f"📐 Height (×{MOD_VALUE})",
-                       elem_classes="slider-container"
-                   )
-                   width_input = gr.Slider(
-                       minimum=SLIDER_MIN_W,
-                       maximum=SLIDER_MAX_W,
-                       step=MOD_VALUE,
-                       value=DEFAULT_W_SLIDER_VALUE,
-                       label=f"📐 Width (×{MOD_VALUE})",
-                       elem_classes="slider-container"
-                   )
-               
-               with gr.Row():
-                   seed_input = gr.Slider(
-                       label="🌱 Seed",
-                       minimum=0,
-                       maximum=MAX_SEED,
-                       step=1,
-                       value=DEFAULT_SEED,
-                       interactive=True
-                   )
-                   randomize_seed_checkbox = gr.Checkbox(
-                       label="🎲 Random Seed",
-                       value=True,
-                       interactive=True
-                   )
-           
-           with gr.Group(elem_classes="audio-settings"):
-               gr.Markdown("### 🎵 Audio Generation Settings")
-               
-               enable_audio = gr.Checkbox(
-                   label="🔊 Enable Automatic Audio Generation",
-                   value=True,
-                   interactive=True
-               )
-               
-               with gr.Column(visible=True) as audio_settings_group:
-                   audio_custom_prompt = gr.Textbox(
-                       label="Custom Audio Prompt (Optional)",
-                       placeholder="Leave empty to auto-generate from video prompt, or specify custom audio description (e.g., 'car engine sound, traffic noise')",
-                       value="",
-                   )
-                   audio_negative_prompt = gr.Textbox(
-                       label="Audio Negative Prompt",
-                       value=DEFAULT_AUDIO_NEGATIVE_PROMPT,
-                       placeholder="Elements to avoid in audio",
-                   )
-                   
-                   with gr.Row():
-                       audio_steps = gr.Slider(
-                           minimum=10,
-                           maximum=50,
-                           step=5,
-                           value=30,
-                           label="🎚️ Audio Steps",
-                           info="More steps = better quality"
-                       )
-                       audio_cfg_strength = gr.Slider(
-                           minimum=1.0,
-                           maximum=10.0,
-                           step=0.5,
-                           value=4.5,
-                           label="🎛️ Audio Guidance",
-                           info="Strength of prompt guidance"
-                       )
-               
-               # Toggle audio settings visibility
-               enable_audio.change(
-                   fn=lambda x: gr.update(visible=x),
-                   inputs=[enable_audio],
-                   outputs=[audio_settings_group]
-               )
-           
-           generate_button = gr.Button(
-               "🎬 Generate Video with Audio",
-               variant="primary",
-               elem_classes="generate-btn"
-           )
-       
-       with gr.Column(scale=5):
-           video_output = gr.Video(
-               label="Generated Video with Audio",
-               autoplay=True,
-               interactive=False,
-               elem_classes="video-output",
-               height=600
-           )
-           
-           gr.HTML("""
-               <div style="text-align: center; margin-top: 20px; color: #6b7280;">
-                   <p>💡 Tip: For better audio, use Custom Audio Prompt with sound descriptions!</p>
-                   <p>🎧 Examples: "car engine sound", "crowd cheering", "nature ambience"</p>
-               </div>
-           """)
-   
-   # Examples section moved outside of columns
-   with gr.Row():
-       gr.Markdown("### 🎯 Example Prompts")
-   
-   gr.Examples(
-       examples=examples,
-       inputs=[prompt, nag_negative_prompt, nag_scale],
-       outputs=None,  # Don't connect outputs to avoid index issues
-       cache_examples=False
-   )
-   
-   # Connect UI elements
-   ui_inputs = [
-       prompt,
-       nag_negative_prompt, nag_scale,
-       height_input, width_input, duration_seconds_input,
-       steps_slider,
-       seed_input, randomize_seed_checkbox,
-       enable_audio, audio_custom_prompt, audio_negative_prompt, 
-       audio_steps, audio_cfg_strength,
-   ]
-   
-   generate_button.click(
-       fn=generate_video_with_audio,
-       inputs=ui_inputs,
-       outputs=[video_output, seed_input],
-   )
+    gr.HTML("""
+        <div class="container">
+            <h1 class="main-title">🎬 VEO3 Free</h1>
+            <p class="subtitle">Wan2.1-T2V-14B + Fast 4-step with NAG + Automatic Audio Generation</p>
+        </div>
+    """)
+    
+    gr.HTML("""
+        <div class='container' style='display:flex; justify-content:center; gap:12px; margin-bottom: 20px;'>
+            <a href="https://huggingface.co/spaces/openfree/Best-AI" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=OpenFree&message=BEST%20AI%20Services&color=%230000ff&labelColor=%23000080&logo=huggingface&logoColor=%23ffa500&style=for-the-badge" alt="OpenFree badge">
+            </a>
+
+            <a href="https://discord.gg/openfreeai" target="_blank">
+                <img src="https://img.shields.io/static/v1?label=Discord&message=Openfree%20AI&color=%230000ff&labelColor=%23800080&logo=discord&logoColor=white&style=for-the-badge" alt="Discord badge">
+            </a>
+        </div>
+    """)
+    
+    with gr.Row(equal_height=True):
+        with gr.Column(scale=5):
+            with gr.Group(elem_classes="prompt-container"):
+                prompt = gr.Textbox(
+                    label="✨ Video Prompt (also used for audio generation)",
+                    placeholder="Describe your video scene in detail...",
+                    lines=3,
+                    elem_classes="prompt-input"
+                )
+                
+                with gr.Accordion("🎨 Advanced Video Settings", open=False):
+                    nag_negative_prompt = gr.Textbox(
+                        label="Video Negative Prompt",
+                        value=DEFAULT_NAG_NEGATIVE_PROMPT,
+                        lines=2,
+                    )
+                    nag_scale = gr.Slider(
+                        label="NAG Scale",
+                        minimum=1.0,
+                        maximum=20.0,
+                        step=0.25,
+                        value=11.0,
+                        info="Higher values = stronger guidance"
+                    )
+            
+            with gr.Group(elem_classes="settings-panel"):
+                gr.Markdown("### ⚙️ Video Settings")
+                
+                with gr.Row():
+                    duration_seconds_input = gr.Slider(
+                        minimum=1,
+                        maximum=8,
+                        step=1,
+                        value=DEFAULT_DURATION_SECONDS,
+                        label="📱 Duration (seconds)",
+                        elem_classes="slider-container"
+                    )
+                    steps_slider = gr.Slider(
+                        minimum=1,
+                        maximum=8,
+                        step=1,
+                        value=DEFAULT_STEPS,
+                        label="🔄 Inference Steps",
+                        elem_classes="slider-container"
+                    )
+                
+                with gr.Row():
+                    height_input = gr.Slider(
+                        minimum=SLIDER_MIN_H,
+                        maximum=SLIDER_MAX_H,
+                        step=MOD_VALUE,
+                        value=DEFAULT_H_SLIDER_VALUE,
+                        label=f"📐 Height (×{MOD_VALUE})",
+                        elem_classes="slider-container"
+                    )
+                    width_input = gr.Slider(
+                        minimum=SLIDER_MIN_W,
+                        maximum=SLIDER_MAX_W,
+                        step=MOD_VALUE,
+                        value=DEFAULT_W_SLIDER_VALUE,
+                        label=f"📐 Width (×{MOD_VALUE})",
+                        elem_classes="slider-container"
+                    )
+                
+                with gr.Row():
+                    seed_input = gr.Slider(
+                        label="🌱 Seed",
+                        minimum=0,
+                        maximum=MAX_SEED,
+                        step=1,
+                        value=DEFAULT_SEED,
+                        interactive=True
+                    )
+                    randomize_seed_checkbox = gr.Checkbox(
+                        label="🎲 Random Seed",
+                        value=True,
+                        interactive=True
+                    )
+            
+            with gr.Group(elem_classes="audio-settings"):
+                gr.Markdown("### 🎵 Audio Generation Settings")
+                
+                enable_audio = gr.Checkbox(
+                    label="🔊 Enable Automatic Audio Generation",
+                    value=True,
+                    interactive=True
+                )
+                
+                with gr.Column(visible=True) as audio_settings_group:
+                    audio_negative_prompt = gr.Textbox(
+                        label="Audio Negative Prompt",
+                        value=DEFAULT_AUDIO_NEGATIVE_PROMPT,
+                        placeholder="Elements to avoid in audio (e.g., music, speech)",
+                    )
+                    
+                    with gr.Row():
+                        audio_steps = gr.Slider(
+                            minimum=10,
+                            maximum=50,
+                            step=5,
+                            value=25,
+                            label="🎚️ Audio Steps",
+                            info="More steps = better quality"
+                        )
+                        audio_cfg_strength = gr.Slider(
+                            minimum=1.0,
+                            maximum=10.0,
+                            step=0.5,
+                            value=4.5,
+                            label="🎛️ Audio Guidance",
+                            info="Strength of prompt guidance"
+                        )
+                
+                # Toggle audio settings visibility
+                enable_audio.change(
+                    fn=lambda x: gr.update(visible=x),
+                    inputs=[enable_audio],
+                    outputs=[audio_settings_group]
+                )
+            
+            generate_button = gr.Button(
+                "🎬 Generate Video with Audio",
+                variant="primary",
+                elem_classes="generate-btn"
+            )
+        
+        with gr.Column(scale=5):
+            video_output = gr.Video(
+                label="Generated Video with Audio",
+                autoplay=True,
+                interactive=False,
+                elem_classes="video-output",
+                height=600
+            )
+            
+            gr.HTML("""
+                <div style="text-align: center; margin-top: 20px; color: #6b7280;">
+                    <p>💡 Tip: The same prompt is used for both video and audio generation!</p>
+                    <p>🎧 Audio is automatically matched to the visual content</p>
+                </div>
+            """)
+    
+    # Examples section moved outside of columns
+    with gr.Row():
+        gr.Markdown("### 🎯 Example Prompts")
+    
+    gr.Examples(
+        examples=examples,
+        inputs=[prompt, nag_negative_prompt, nag_scale],
+        outputs=None,  # Don't connect outputs to avoid index issues
+        cache_examples=False
+    )
+    
+    # Connect UI elements
+    ui_inputs = [
+        prompt,
+        nag_negative_prompt, nag_scale,
+        height_input, width_input, duration_seconds_input,
+        steps_slider,
+        seed_input, randomize_seed_checkbox,
+        enable_audio, audio_negative_prompt, audio_steps, audio_cfg_strength,
+    ]
+    
+    generate_button.click(
+        fn=generate_video_with_audio,
+        inputs=ui_inputs,
+        outputs=[video_output, seed_input],
+    )
 
 if __name__ == "__main__":
-   demo.queue().launch()
+    demo.queue().launch()