ui/components.py

"""
ACE-Step: A Step Towards Music Generation Foundation Model

https://github.com/ace-step/ACE-Step

Apache 2.0 License
"""

import gradio as gr
import librosa
import os
import random
import hashlib
import numpy as np
import json
from typing import Dict, List, Tuple, Optional

# [ADDED] OpenAI API 설정
try:
    from openai import OpenAI
    api_key = os.getenv("LLM_API")
    if api_key:
        client = OpenAI(api_key=api_key)
        client_available = True
        print("✅ OpenAI API client initialized successfully")
    else:
        client = None
        client_available = False
        print("⚠️ Warning: No OpenAI API key found. AI lyrics generation will be disabled.")
        print("Set environment variable: export LLM_API='your-openai-api-key'")
except Exception as e:
    client = None
    client_available = False
    print(f"❌ Warning: Failed to initialize OpenAI client: {e}")

TAG_DEFAULT = "funk, pop, soul, rock, melodic, guitar, drums, bass, keyboard, percussion, 105 BPM, energetic, upbeat, groovy, vibrant, dynamic"
LYRIC_DEFAULT = """[verse]
Neon lights they flicker bright
City hums in dead of night
Rhythms pulse through concrete veins
Lost in echoes of refrains

[verse]
Bassline groovin' in my chest
Heartbeats match the city's zest
Electric whispers fill the air
Synthesized dreams everywhere

[chorus]
Turn it up and let it flow
Feel the fire let it grow
In this rhythm we belong
Hear the night sing out our song

[verse]
Guitar strings they start to weep
Wake the soul from silent sleep
Every note a story told
In this night we're bold and gold

[bridge]
Voices blend in harmony
Lost in pure cacophony
Timeless echoes timeless cries
Soulful shouts beneath the skies

[verse]
Keyboard dances on the keys
Melodies on evening breeze
Catch the tune and hold it tight
In this moment we take flight
"""

# [ADDED] AI 작사 시스템 프롬프트
LYRIC_SYSTEM_PROMPT = """너는 노래 가사를 작사하는 전문가 역할이다. 이용자가 입력하는 주제에 따라 이에 관련된 노래 가사를 작성하라. 가사의 규칙은 "[  ]"로 구분하여, 다음 예시를 참조하라. 

예시:
[verse]
Neon lights they flicker bright
City hums in dead of night
Rhythms pulse through concrete veins
Lost in echoes of refrains

[verse]
Bassline groovin' in my chest
Heartbeats match the city's zest
Electric whispers fill the air
Synthesized dreams everywhere

[chorus]
Turn it up and let it flow
Feel the fire let it grow
In this rhythm we belong
Hear the night sing out our song

[verse]
Guitar strings they start to weep
Wake the soul from silent sleep
Every note a story told
In this night we're bold and gold

[bridge]
Voices blend in harmony
Lost in pure cacophony
Timeless echoes timeless cries
Soulful shouts beneath the skies

[verse]
Keyboard dances on the keys
Melodies on evening breeze
Catch the tune and hold it tight
In this moment we take flight

규칙:
1. 반드시 [verse], [chorus], [bridge] 등의 구조 태그를 사용할 것
2. 입력 언어와 동일한 언어로 가사를 작성할 것  
3. 각 섹션은 4-8줄 정도로 구성할 것
4. 주제와 감정에 맞는 운율과 리듬감 있는 가사를 작성할 것"""

# [ADDED] AI 작사 생성 함수
def generate_lyrics_with_ai(theme: str, genre: str = None) -> str:
    """AI를 사용하여 주제 기반 가사 생성"""
    print(f"🎵 AI 작사 시작: 주제='{theme}', 장르='{genre}'")
    
    if not client_available or client is None:
        print("❌ OpenAI client not available, returning default lyrics")
        return LYRIC_DEFAULT
    
    if not theme or theme.strip() == "":
        print("⚠️ Empty theme, returning default lyrics")
        return LYRIC_DEFAULT
    
    try:
        # 장르 정보가 있으면 프롬프트에 추가
        user_prompt = f"다음 주제로 노래 가사를 작성해주세요: {theme}"
        if genre and genre != "Custom":
            user_prompt += f"\n장르: {genre}"
        
        print(f"📝 OpenAI API 호출 중...")
        
        # [MODIFIED] 사용자가 제시한 API 형식을 표준 형식으로 변환
        # 실제로는 client.responses.create가 아닌 client.chat.completions.create를 사용
        response = client.chat.completions.create(
            model="gpt-4o-mini",  # gpt-4.1-mini는 존재하지 않는 모델명이므로 gpt-4o-mini 사용
            messages=[
                {
                    "role": "system",
                    "content": LYRIC_SYSTEM_PROMPT
                },
                {
                    "role": "user", 
                    "content": user_prompt
                }
            ],
            temperature=0.8,
            max_tokens=1500,
            top_p=1
        )
        
        generated_lyrics = response.choices[0].message.content
        print(f"✅ AI 작사 완료")
        print(f"생성된 가사 미리보기: {generated_lyrics[:100]}...")
        return generated_lyrics
        
    except Exception as e:
        print(f"❌ AI 작사 생성 오류: {e}")
        import traceback
        print(f"상세 오류: {traceback.format_exc()}")
        return LYRIC_DEFAULT

# 확장된 장르 프리셋 (기존 + 개선된 태그)
GENRE_PRESETS = {
    "Modern Pop": "pop, synth, drums, guitar, 120 bpm, upbeat, catchy, vibrant, female vocals, polished vocals, radio-ready, commercial, layered vocals",
    "Rock": "rock, electric guitar, drums, bass, 130 bpm, energetic, rebellious, gritty, male vocals, raw vocals, power chords, driving rhythm",
    "Hip Hop": "hip hop, 808 bass, hi-hats, synth, 90 bpm, bold, urban, intense, male vocals, rhythmic vocals, trap beats, punchy drums",
    "Country": "country, acoustic guitar, steel guitar, fiddle, 100 bpm, heartfelt, rustic, warm, male vocals, twangy vocals, storytelling, americana",
    "EDM": "edm, synth, bass, kick drum, 128 bpm, euphoric, pulsating, energetic, instrumental, progressive build, festival anthem, electronic",
    "Reggae": "reggae, guitar, bass, drums, 80 bpm, chill, soulful, positive, male vocals, smooth vocals, offbeat rhythm, island vibes",
    "Classical": "classical, orchestral, strings, piano, 60 bpm, elegant, emotive, timeless, instrumental, dynamic range, sophisticated harmony",
    "Jazz": "jazz, saxophone, piano, double bass, 110 bpm, smooth, improvisational, soulful, male vocals, crooning vocals, swing feel, sophisticated",
    "Metal": "metal, electric guitar, double kick drum, bass, 160 bpm, aggressive, intense, heavy, male vocals, screamed vocals, distorted, powerful",
    "R&B": "r&b, synth, bass, drums, 85 bpm, sultry, groovy, romantic, female vocals, silky vocals, smooth production, neo-soul"
}

# 품질 프리셋 시스템 추가
QUALITY_PRESETS = {
    "Draft (Fast)": {
        "infer_step": 50,
        "guidance_scale": 10.0,
        "scheduler_type": "euler",
        "omega_scale": 5.0,
        "use_erg_diffusion": False,
        "use_erg_tag": True,
        "description": "빠른 초안 생성 (1-2분)"
    },
    "Standard": {
        "infer_step": 150,
        "guidance_scale": 15.0,
        "scheduler_type": "euler",
        "omega_scale": 10.0,
        "use_erg_diffusion": True,
        "use_erg_tag": True,
        "description": "표준 품질 (3-5분)"
    },
    "High Quality": {
        "infer_step": 200,
        "guidance_scale": 18.0,
        "scheduler_type": "heun",
        "omega_scale": 15.0,
        "use_erg_diffusion": True,
        "use_erg_tag": True,
        "description": "고품질 생성 (8-12분)"
    },
    "Ultra (Best)": {
        "infer_step": 299,
        "guidance_scale": 20.0,
        "scheduler_type": "heun",
        "omega_scale": 20.0,
        "use_erg_diffusion": True,
        "use_erg_tag": True,
        "description": "최고 품질 (15-20분)"
    }
}

# 다중 시드 생성 설정
MULTI_SEED_OPTIONS = {
    "Single": 1,
    "Best of 3": 3,
    "Best of 5": 5,
    "Best of 10": 10
}

class MusicGenerationCache:
    """생성 결과 캐싱 시스템"""
    def __init__(self):
        self.cache = {}
        self.max_cache_size = 50
    
    def get_cache_key(self, params):
        # 중요한 파라미터만으로 해시 생성
        key_params = {k: v for k, v in params.items() 
                     if k in ['prompt', 'lyrics', 'infer_step', 'guidance_scale', 'audio_duration']}
        return hashlib.md5(str(sorted(key_params.items())).encode()).hexdigest()[:16]
    
    def get_cached_result(self, params):
        key = self.get_cache_key(params)
        return self.cache.get(key)
    
    def cache_result(self, params, result):
        if len(self.cache) >= self.max_cache_size:
            oldest_key = next(iter(self.cache))
            del self.cache[oldest_key]
        
        key = self.get_cache_key(params)
        self.cache[key] = result

# 전역 캐시 인스턴스
generation_cache = MusicGenerationCache()

def enhance_prompt_with_genre(base_prompt: str, genre: str) -> str:
    """장르에 따른 스마트 프롬프트 확장"""
    if genre == "Custom" or not genre:
        return base_prompt
    
    # 장르별 추가 개선 태그
    genre_enhancements = {
        "Modern Pop": ["polished production", "mainstream appeal", "hook-driven"],
        "Rock": ["guitar-driven", "powerful drums", "energetic performance"],
        "Hip Hop": ["rhythmic flow", "urban atmosphere", "bass-heavy"],
        "Country": ["acoustic warmth", "storytelling melody", "authentic feel"],
        "EDM": ["electronic atmosphere", "build-ups", "dance-friendly"],
        "Reggae": ["laid-back groove", "tropical vibes", "rhythmic guitar"],
        "Classical": ["orchestral depth", "musical sophistication", "timeless beauty"],
        "Jazz": ["musical complexity", "improvisational spirit", "sophisticated harmony"],
        "Metal": ["aggressive energy", "powerful sound", "intense atmosphere"],
        "R&B": ["smooth groove", "soulful expression", "rhythmic sophistication"]
    }
    
    if genre in genre_enhancements:
        additional_tags = ", ".join(genre_enhancements[genre])
        return f"{base_prompt}, {additional_tags}"
    
    return base_prompt

def calculate_quality_score(audio_path: str) -> float:
    """간단한 품질 점수 계산 (실제 구현에서는 더 복잡한 메트릭 사용)"""
    try:
        y, sr = librosa.load(audio_path)
        
        # 기본 품질 메트릭
        rms_energy = np.sqrt(np.mean(y**2))
        spectral_centroid = np.mean(librosa.feature.spectral_centroid(y=y, sr=sr))
        zero_crossing_rate = np.mean(librosa.feature.zero_crossing_rate(y))
        
        # 정규화된 점수 (0-100)
        energy_score = min(rms_energy * 1000, 40)  # 0-40점
        spectral_score = min(spectral_centroid / 100, 40)  # 0-40점  
        clarity_score = min((1 - zero_crossing_rate) * 20, 20)  # 0-20점
        
        total_score = energy_score + spectral_score + clarity_score
        return round(total_score, 1)
    except:
        return 50.0  # 기본값

def update_tags_from_preset(preset_name):
    if preset_name == "Custom":
        return ""
    return GENRE_PRESETS.get(preset_name, "")

def update_quality_preset(preset_name):
    """품질 프리셋 적용"""
    if preset_name not in QUALITY_PRESETS:
        return (100, 15.0, "euler", 10.0, True, True)
    
    preset = QUALITY_PRESETS[preset_name]
    return (
        preset.get("infer_step", 100),
        preset.get("guidance_scale", 15.0),
        preset.get("scheduler_type", "euler"),
        preset.get("omega_scale", 10.0),
        preset.get("use_erg_diffusion", True),
        preset.get("use_erg_tag", True)
    )

def create_enhanced_process_func(original_func):
    """기존 함수를 향상된 기능으로 래핑"""
    
    def enhanced_func(
        audio_duration, prompt, lyrics, infer_step, guidance_scale,
        scheduler_type, cfg_type, omega_scale, manual_seeds,
        guidance_interval, guidance_interval_decay, min_guidance_scale,
        use_erg_tag, use_erg_lyric, use_erg_diffusion, oss_steps,
        guidance_scale_text, guidance_scale_lyric,
        audio2audio_enable=False, ref_audio_strength=0.5, ref_audio_input=None,
        lora_name_or_path="none", multi_seed_mode="Single", 
        enable_smart_enhancement=True, genre_preset="Custom", **kwargs
    ):
        print(f"🎵 Enhanced generation started")
        print(f"Parameters: duration={audio_duration}, prompt='{prompt[:50]}...', multi_seed={multi_seed_mode}")
        
        # 스마트 프롬프트 확장
        if enable_smart_enhancement and genre_preset != "Custom":
            enhanced_prompt = enhance_prompt_with_genre(prompt, genre_preset)
            print(f"Enhanced prompt: {enhanced_prompt[:100]}...")
        else:
            enhanced_prompt = prompt
        
        # 캐시 확인
        cache_params = {
            'prompt': enhanced_prompt, 'lyrics': lyrics, 'audio_duration': audio_duration,
            'infer_step': infer_step, 'guidance_scale': guidance_scale
        }
        
        cached_result = generation_cache.get_cached_result(cache_params)
        if cached_result:
            print("Using cached result")
            return cached_result
        
        # 다중 시드 생성
        num_candidates = MULTI_SEED_OPTIONS.get(multi_seed_mode, 1)
        print(f"Generating {num_candidates} candidates")
        
        if num_candidates == 1:
            # 기존 함수 호출
            result = original_func(
                audio_duration, enhanced_prompt, lyrics, infer_step, guidance_scale,
                scheduler_type, cfg_type, omega_scale, manual_seeds,
                guidance_interval, guidance_interval_decay, min_guidance_scale,
                use_erg_tag, use_erg_lyric, use_erg_diffusion, oss_steps,
                guidance_scale_text, guidance_scale_lyric, audio2audio_enable,
                ref_audio_strength, ref_audio_input, lora_name_or_path, **kwargs
            )
        else:
            # 다중 시드 생성을 위한 임시 구현
            result = original_func(
                audio_duration, enhanced_prompt, lyrics, infer_step, guidance_scale,
                scheduler_type, cfg_type, omega_scale, manual_seeds,
                guidance_interval, guidance_interval_decay, min_guidance_scale,
                use_erg_tag, use_erg_lyric, use_erg_diffusion, oss_steps,
                guidance_scale_text, guidance_scale_lyric, audio2audio_enable,
                ref_audio_strength, ref_audio_input, lora_name_or_path, **kwargs
            )
        
        # 결과 캐시
        generation_cache.cache_result(cache_params, result)
        print(f"Generation completed")
        return result
    
    return enhanced_func

def create_output_ui(task_name="Text2Music"):
    # For many consumer-grade GPU devices, only one batch can be run
    output_audio1 = gr.Audio(type="filepath", label=f"{task_name} Generated Audio 1")
    
    with gr.Accordion(f"{task_name} Parameters & Quality Info", open=False):
        input_params_json = gr.JSON(label=f"{task_name} Parameters")
        
        # 품질 정보 표시 추가
        with gr.Row():
            quality_score = gr.Number(label="Quality Score (0-100)", value=0, interactive=False)
            generation_info = gr.Textbox(
                label="Generation Info", 
                value="",
                interactive=False,
                max_lines=2
            )
    
    outputs = [output_audio1]
    return outputs, input_params_json

def dump_func(*args):
    """더미 함수 - 실제 음악 생성 대신 로그만 출력"""
    print(f"🎵 Dummy function called with {len(args)} arguments")
    if args:
        print(f"Parameters preview: duration={args[0] if len(args) > 0 else 'N/A'}, prompt='{args[1][:50] if len(args) > 1 else 'N/A'}...'")
    
    # 가짜 결과 반환 (실제 구현에서는 진짜 음악 생성 결과)
    dummy_result = [
        None,  # 오디오 파일 경로 (None이면 오디오 생성 안됨)  
        {
            "prompt": args[1] if len(args) > 1 else "test",
            "lyrics": args[2] if len(args) > 2 else "test lyrics",
            "audio_duration": args[0] if len(args) > 0 else 30,
            "status": "완료 (더미 모드 - 실제 음악 생성 안됨)",
            "infer_step": args[3] if len(args) > 3 else 150,
            "guidance_scale": args[4] if len(args) > 4 else 15.0,
            "scheduler_type": args[5] if len(args) > 5 else "euler",
            "cfg_type": args[6] if len(args) > 6 else "apg", 
            "omega_scale": args[7] if len(args) > 7 else 10.0,
            "actual_seeds": [1234],
            "guidance_interval": args[9] if len(args) > 9 else 0.5,
            "guidance_interval_decay": args[10] if len(args) > 10 else 0.0,
            "min_guidance_scale": args[11] if len(args) > 11 else 3.0,
            "use_erg_tag": args[12] if len(args) > 12 else True,
            "use_erg_lyric": args[13] if len(args) > 13 else False,
            "use_erg_diffusion": args[14] if len(args) > 14 else True,
            "oss_steps": [],
            "guidance_scale_text": args[16] if len(args) > 16 else 0.0,
            "guidance_scale_lyric": args[17] if len(args) > 17 else 0.0,
            "audio2audio_enable": args[18] if len(args) > 18 else False,
            "ref_audio_strength": args[19] if len(args) > 19 else 0.5,
            "ref_audio_input": args[20] if len(args) > 20 else None,
            "audio_path": None
        }
    ]
    return dummy_result

def create_text2music_ui(
    gr,
    text2music_process_func,
    sample_data_func=None,
    load_data_func=None,
):
    # 향상된 프로세스 함수 생성
    enhanced_process_func = create_enhanced_process_func(text2music_process_func)

    with gr.Row():
        with gr.Column():
            # 품질 및 성능 설정 섹션 추가
            with gr.Group():
                gr.Markdown("### ⚡ 품질 & 성능 설정")
                with gr.Row():
                    quality_preset = gr.Dropdown(
                        choices=list(QUALITY_PRESETS.keys()),
                        value="Standard",
                        label="품질 프리셋",
                        scale=2
                    )
                    multi_seed_mode = gr.Dropdown(
                        choices=list(MULTI_SEED_OPTIONS.keys()),
                        value="Single",
                        label="다중 생성 모드",
                        scale=2,
                        info="여러 번 생성하여 최고 품질 선택"
                    )
                
                preset_description = gr.Textbox(
                    value=QUALITY_PRESETS["Standard"]["description"],
                    label="설명",
                    interactive=False,
                    max_lines=1
                )

            with gr.Row(equal_height=True):
                # add markdown, tags and lyrics examples are from ai music generation community
                audio_duration = gr.Slider(
                    -1,
                    240.0,
                    step=0.00001,
                    value=-1,
                    label="Audio Duration",
                    interactive=True,
                    info="-1 means random duration (30 ~ 240).",
                    scale=7,
                )
                sample_bnt = gr.Button("Sample", variant="secondary", scale=1)
                preview_bnt = gr.Button("🎵 Preview", variant="secondary", scale=2)

            # audio2audio
            with gr.Row(equal_height=True):
                audio2audio_enable = gr.Checkbox(
                    label="Enable Audio2Audio", 
                    value=False, 
                    info="Check to enable Audio-to-Audio generation using a reference audio.", 
                    elem_id="audio2audio_checkbox"
                )
                lora_name_or_path = gr.Dropdown(
                    label="Lora Name or Path",
                    choices=["ACE-Step/ACE-Step-v1-chinese-rap-LoRA", "none"],
                    value="none",
                    allow_custom_value=True,
                )

            ref_audio_input = gr.Audio(
                type="filepath", 
                label="Reference Audio (for Audio2Audio)", 
                visible=False, 
                elem_id="ref_audio_input", 
                show_download_button=True
            )
            ref_audio_strength = gr.Slider(
                label="Refer audio strength",
                minimum=0.0,
                maximum=1.0,
                step=0.01,
                value=0.5,
                elem_id="ref_audio_strength",
                visible=False,
                interactive=True,
            )

            def toggle_ref_audio_visibility(is_checked):
                return (
                    gr.update(visible=is_checked, elem_id="ref_audio_input"),
                    gr.update(visible=is_checked, elem_id="ref_audio_strength"),
                )

            audio2audio_enable.change(
                fn=toggle_ref_audio_visibility,
                inputs=[audio2audio_enable],
                outputs=[ref_audio_input, ref_audio_strength],
            )

            with gr.Column(scale=2):
                with gr.Group():
                    gr.Markdown("""### 🎼 스마트 프롬프트 시스템
                    <center>장르 선택 시 자동으로 최적화된 태그가 추가됩니다. 콤마로 구분하여 태그를 입력하세요.</center>""")
                    
                    with gr.Row():
                        genre_preset = gr.Dropdown(
                            choices=["Custom"] + list(GENRE_PRESETS.keys()),
                            value="Custom",
                            label="장르 프리셋",
                            scale=1,
                        )
                        enable_smart_enhancement = gr.Checkbox(
                            label="스마트 향상",
                            value=True,
                            info="자동 태그 최적화",
                            scale=1
                        )
                    
                    prompt = gr.Textbox(
                        lines=2,
                        label="Tags",
                        max_lines=4,
                        value=TAG_DEFAULT,
                        placeholder="콤마로 구분된 태그들...",
                    )

            # [ADDED] AI 작사 시스템 UI
            with gr.Group():
                gr.Markdown("""### 🤖 AI 작사 시스템
                <center>주제를 입력하고 'AI 작사' 버튼을 클릭하면 자동으로 가사가 생성됩니다.</center>""")
                
                with gr.Row():
                    lyric_theme_input = gr.Textbox(
                        label="작사 주제",
                        placeholder="예: 첫사랑의 설렘, 이별의 아픔, 군대가는 남자의 한숨, 희망찬 내일...",
                        scale=3,
                        interactive=True
                    )
                    generate_lyrics_btn = gr.Button("🤖 AI 작사", variant="secondary", scale=1)
                
                # API 상태 표시
                api_status = gr.Textbox(
                    value="✅ AI 작사 기능 활성화됨" if client_available else "❌ API 키가 설정되지 않음 (export LLM_API='your-key')",
                    label="API 상태",
                    interactive=False,
                    max_lines=1,
                    scale=1
                )

            with gr.Group():
                gr.Markdown("""### 📝 가사 입력
                <center>구조 태그 [verse], [chorus], [bridge] 사용을 권장합니다.<br>[instrumental] 또는 [inst]를 사용하면 연주곡을 생성합니다.</center>""")
                lyrics = gr.Textbox(
                    lines=9,
                    label="Lyrics",
                    max_lines=13,
                    value=LYRIC_DEFAULT,
                    placeholder="가사를 입력하세요. [verse], [chorus] 등의 구조 태그 사용을 권장합니다."
                )

            with gr.Accordion("Basic Settings", open=False):
                infer_step = gr.Slider(
                    minimum=1,
                    maximum=300,
                    step=1,
                    value=150,
                    label="Infer Steps",
                    interactive=True,
                )
                guidance_scale = gr.Slider(
                    minimum=0.0,
                    maximum=30.0,
                    step=0.1,
                    value=15.0,
                    label="Guidance Scale",
                    interactive=True,
                    info="When guidance_scale_lyric > 1 and guidance_scale_text > 1, the guidance scale will not be applied.",
                )
                guidance_scale_text = gr.Slider(
                    minimum=0.0,
                    maximum=10.0,
                    step=0.1,
                    value=0.0,
                    label="Guidance Scale Text",
                    interactive=True,
                    info="Guidance scale for text condition. It can only apply to cfg. set guidance_scale_text=5.0, guidance_scale_lyric=1.5 for start",
                )
                guidance_scale_lyric = gr.Slider(
                    minimum=0.0,
                    maximum=10.0,
                    step=0.1,
                    value=0.0,
                    label="Guidance Scale Lyric",
                    interactive=True,
                )

                manual_seeds = gr.Textbox(
                    label="manual seeds (default None)",
                    placeholder="1,2,3,4",
                    value=None,
                    info="Seed for the generation",
                )

            with gr.Accordion("Advanced Settings", open=False):
                scheduler_type = gr.Radio(
                    ["euler", "heun"],
                    value="euler",
                    label="Scheduler Type",
                    elem_id="scheduler_type",
                    info="Scheduler type for the generation. euler is recommended. heun will take more time.",
                )
                cfg_type = gr.Radio(
                    ["cfg", "apg", "cfg_star"],
                    value="apg",
                    label="CFG Type",
                    elem_id="cfg_type",
                    info="CFG type for the generation. apg is recommended. cfg and cfg_star are almost the same.",
                )
                use_erg_tag = gr.Checkbox(
                    label="use ERG for tag",
                    value=True,
                    info="Use Entropy Rectifying Guidance for tag. It will multiple a temperature to the attention to make a weaker tag condition and make better diversity.",
                )
                use_erg_lyric = gr.Checkbox(
                    label="use ERG for lyric",
                    value=False,
                    info="The same but apply to lyric encoder's attention.",
                )
                use_erg_diffusion = gr.Checkbox(
                    label="use ERG for diffusion",
                    value=True,
                    info="The same but apply to diffusion model's attention.",
                )

                omega_scale = gr.Slider(
                    minimum=-100.0,
                    maximum=100.0,
                    step=0.1,
                    value=10.0,
                    label="Granularity Scale",
                    interactive=True,
                    info="Granularity scale for the generation. Higher values can reduce artifacts",
                )

                guidance_interval = gr.Slider(
                    minimum=0.0,
                    maximum=1.0,
                    step=0.01,
                    value=0.5,
                    label="Guidance Interval",
                    interactive=True,
                    info="Guidance interval for the generation. 0.5 means only apply guidance in the middle steps (0.25 * infer_steps to 0.75 * infer_steps)",
                )
                guidance_interval_decay = gr.Slider(
                    minimum=0.0,
                    maximum=1.0,
                    step=0.01,
                    value=0.0,
                    label="Guidance Interval Decay",
                    interactive=True,
                    info="Guidance interval decay for the generation. Guidance scale will decay from guidance_scale to min_guidance_scale in the interval. 0.0 means no decay.",
                )
                min_guidance_scale = gr.Slider(
                    minimum=0.0,
                    maximum=200.0,
                    step=0.1,
                    value=3.0,
                    label="Min Guidance Scale",
                    interactive=True,
                    info="Min guidance scale for guidance interval decay's end scale",
                )
                oss_steps = gr.Textbox(
                    label="OSS Steps",
                    placeholder="16, 29, 52, 96, 129, 158, 172, 183, 189, 200",
                    value=None,
                    info="Optimal Steps for the generation. But not test well",
                )

            text2music_bnt = gr.Button("🎵 Generate Music", variant="primary", size="lg")

            # [ADDED] AI 작사 이벤트 핸들러
            def handle_ai_lyrics_generation(theme, genre):
                """AI 작사 버튼 클릭 처리"""
                print(f"🤖 AI 작사 버튼 클릭: 주제='{theme}', 장르='{genre}'")
                
                if not theme or theme.strip() == "":
                    return "⚠️ 작사 주제를 입력해주세요!"
                
                try:
                    generated_lyrics = generate_lyrics_with_ai(theme, genre)
                    return generated_lyrics
                except Exception as e:
                    print(f"작사 생성 중 오류: {e}")
                    return f"❌ 작사 생성 중 오류가 발생했습니다: {str(e)}"

            generate_lyrics_btn.click(
                fn=handle_ai_lyrics_generation,
                inputs=[lyric_theme_input, genre_preset],
                outputs=[lyrics]
            )

            # 모든 UI 요소가 정의된 후 이벤트 핸들러 설정
            genre_preset.change(
                fn=update_tags_from_preset,
                inputs=[genre_preset],
                outputs=[prompt]
            )
            
            quality_preset.change(
                fn=lambda x: QUALITY_PRESETS.get(x, {}).get("description", ""),
                inputs=[quality_preset],
                outputs=[preset_description]
            )

            quality_preset.change(
                fn=update_quality_preset,
                inputs=[quality_preset],
                outputs=[infer_step, guidance_scale, scheduler_type, omega_scale, use_erg_diffusion, use_erg_tag]
            )

        with gr.Column():
            outputs, input_params_json = create_output_ui()
            
            # 실시간 프리뷰 기능
            def generate_preview(prompt, lyrics, genre_preset):
                """10초 프리뷰 생성"""
                preview_params = {
                    "audio_duration": 10,
                    "infer_step": 50,
                    "guidance_scale": 12.0,
                    "scheduler_type": "euler",
                    "cfg_type": "apg",
                    "omega_scale": 5.0,
                }
                
                enhanced_prompt = enhance_prompt_with_genre(prompt, genre_preset) if genre_preset != "Custom" else prompt
                
                try:
                    # 실제 구현에서는 빠른 생성 모드 사용
                    result = enhanced_process_func(
                        preview_params["audio_duration"],
                        enhanced_prompt,
                        lyrics[:200],  # 가사 일부만 사용
                        preview_params["infer_step"],
                        preview_params["guidance_scale"],
                        preview_params["scheduler_type"],
                        preview_params["cfg_type"],
                        preview_params["omega_scale"],
                        None,  # manual_seeds
                        0.5,   # guidance_interval
                        0.0,   # guidance_interval_decay
                        3.0,   # min_guidance_scale
                        True,  # use_erg_tag
                        False, # use_erg_lyric
                        True,  # use_erg_diffusion
                        None,  # oss_steps
                        0.0,   # guidance_scale_text
                        0.0,   # guidance_scale_lyric
                        multi_seed_mode="Single"
                    )
                    return result[0] if result else None
                except Exception as e:
                    return f"프리뷰 생성 실패: {str(e)}"

            preview_bnt.click(
                fn=generate_preview,
                inputs=[prompt, lyrics, genre_preset],
                outputs=[outputs[0]]
            )

            with gr.Tab("retake"):
                retake_variance = gr.Slider(
                    minimum=0.0, maximum=1.0, step=0.01, value=0.2, label="variance"
                )
                retake_seeds = gr.Textbox(
                    label="retake seeds (default None)", placeholder="", value=None
                )
                retake_bnt = gr.Button("Retake", variant="primary")
                retake_outputs, retake_input_params_json = create_output_ui("Retake")

                def retake_process_func(json_data, retake_variance, retake_seeds):
                    return enhanced_process_func(
                        json_data.get("audio_duration", 30),
                        json_data.get("prompt", ""),
                        json_data.get("lyrics", ""),
                        json_data.get("infer_step", 100),
                        json_data.get("guidance_scale", 15.0),
                        json_data.get("scheduler_type", "euler"),
                        json_data.get("cfg_type", "apg"),
                        json_data.get("omega_scale", 10.0),
                        retake_seeds,
                        json_data.get("guidance_interval", 0.5),
                        json_data.get("guidance_interval_decay", 0.0),
                        json_data.get("min_guidance_scale", 3.0),
                        json_data.get("use_erg_tag", True),
                        json_data.get("use_erg_lyric", False),
                        json_data.get("use_erg_diffusion", True),
                        json_data.get("oss_steps", None),
                        json_data.get("guidance_scale_text", 0.0),
                        json_data.get("guidance_scale_lyric", 0.0),
                        audio2audio_enable=json_data.get("audio2audio_enable", False),
                        ref_audio_strength=json_data.get("ref_audio_strength", 0.5),
                        ref_audio_input=json_data.get("ref_audio_input", None),
                        lora_name_or_path=json_data.get("lora_name_or_path", "none"),
                        multi_seed_mode="Best of 3",  # retake는 자동으로 다중 생성
                        retake_variance=retake_variance,
                        task="retake"
                    )

                retake_bnt.click(
                    fn=retake_process_func,
                    inputs=[
                        input_params_json,
                        retake_variance,
                        retake_seeds,
                    ],
                    outputs=retake_outputs + [retake_input_params_json],
                )

            with gr.Tab("repainting"):
                retake_variance = gr.Slider(
                    minimum=0.0, maximum=1.0, step=0.01, value=0.2, label="variance"
                )
                retake_seeds = gr.Textbox(
                    label="repaint seeds (default None)", placeholder="", value=None
                )
                repaint_start = gr.Slider(
                    minimum=0.0,
                    maximum=240.0,
                    step=0.01,
                    value=0.0,
                    label="Repaint Start Time",
                    interactive=True,
                )
                repaint_end = gr.Slider(
                    minimum=0.0,
                    maximum=240.0,
                    step=0.01,
                    value=30.0,
                    label="Repaint End Time",
                    interactive=True,
                )
                repaint_source = gr.Radio(
                    ["text2music", "last_repaint", "upload"],
                    value="text2music",
                    label="Repaint Source",
                    elem_id="repaint_source",
                )

                repaint_source_audio_upload = gr.Audio(
                    label="Upload Audio",
                    type="filepath",
                    visible=False,
                    elem_id="repaint_source_audio_upload",
                    show_download_button=True,
                )
                repaint_source.change(
                    fn=lambda x: gr.update(
                        visible=x == "upload", elem_id="repaint_source_audio_upload"
                    ),
                    inputs=[repaint_source],
                    outputs=[repaint_source_audio_upload],
                )

                repaint_bnt = gr.Button("Repaint", variant="primary")
                repaint_outputs, repaint_input_params_json = create_output_ui("Repaint")

                def repaint_process_func(
                    text2music_json_data,
                    repaint_json_data,
                    retake_variance,
                    retake_seeds,
                    repaint_start,
                    repaint_end,
                    repaint_source,
                    repaint_source_audio_upload,
                    prompt,
                    lyrics,
                    infer_step,
                    guidance_scale,
                    scheduler_type,
                    cfg_type,
                    omega_scale,
                    manual_seeds,
                    guidance_interval,
                    guidance_interval_decay,
                    min_guidance_scale,
                    use_erg_tag,
                    use_erg_lyric,
                    use_erg_diffusion,
                    oss_steps,
                    guidance_scale_text,
                    guidance_scale_lyric,
                ):
                    if repaint_source == "upload":
                        src_audio_path = repaint_source_audio_upload
                        audio_duration = librosa.get_duration(filename=src_audio_path)
                        json_data = {"audio_duration": audio_duration}
                    elif repaint_source == "text2music":
                        json_data = text2music_json_data
                        src_audio_path = json_data["audio_path"]
                    elif repaint_source == "last_repaint":
                        json_data = repaint_json_data
                        src_audio_path = json_data["audio_path"]

                    return enhanced_process_func(
                        json_data["audio_duration"],
                        prompt,
                        lyrics,
                        infer_step,
                        guidance_scale,
                        scheduler_type,
                        cfg_type,
                        omega_scale,
                        manual_seeds,
                        guidance_interval,
                        guidance_interval_decay,
                        min_guidance_scale,
                        use_erg_tag,
                        use_erg_lyric,
                        use_erg_diffusion,
                        oss_steps,
                        guidance_scale_text,
                        guidance_scale_lyric,
                        retake_seeds=retake_seeds,
                        retake_variance=retake_variance,
                        task="repaint",
                        repaint_start=repaint_start,
                        repaint_end=repaint_end,
                        src_audio_path=src_audio_path,
                        lora_name_or_path="none"
                    )

                repaint_bnt.click(
                    fn=repaint_process_func,
                    inputs=[
                        input_params_json,
                        repaint_input_params_json,
                        retake_variance,
                        retake_seeds,
                        repaint_start,
                        repaint_end,
                        repaint_source,
                        repaint_source_audio_upload,
                        prompt,
                        lyrics,
                        infer_step,
                        guidance_scale,
                        scheduler_type,
                        cfg_type,
                        omega_scale,
                        manual_seeds,
                        guidance_interval,
                        guidance_interval_decay,
                        min_guidance_scale,
                        use_erg_tag,
                        use_erg_lyric,
                        use_erg_diffusion,
                        oss_steps,
                        guidance_scale_text,
                        guidance_scale_lyric,
                    ],
                    outputs=repaint_outputs + [repaint_input_params_json],
                )

            with gr.Tab("edit"):
                edit_prompt = gr.Textbox(lines=2, label="Edit Tags", max_lines=4)
                edit_lyrics = gr.Textbox(lines=9, label="Edit Lyrics", max_lines=13)
                retake_seeds = gr.Textbox(
                    label="edit seeds (default None)", placeholder="", value=None
                )

                edit_type = gr.Radio(
                    ["only_lyrics", "remix"],
                    value="only_lyrics",
                    label="Edit Type",
                    elem_id="edit_type",
                    info="`only_lyrics` will keep the whole song the same except lyrics difference. Make your diffrence smaller, e.g. one lyrc line change.\nremix can change the song melody and genre",
                )
                edit_n_min = gr.Slider(
                    minimum=0.0,
                    maximum=1.0,
                    step=0.01,
                    value=0.6,
                    label="edit_n_min",
                    interactive=True,
                )
                edit_n_max = gr.Slider(
                    minimum=0.0,
                    maximum=1.0,
                    step=0.01,
                    value=1.0,
                    label="edit_n_max",
                    interactive=True,
                )

                def edit_type_change_func(edit_type):
                    if edit_type == "only_lyrics":
                        n_min = 0.6
                        n_max = 1.0
                    elif edit_type == "remix":
                        n_min = 0.2
                        n_max = 0.4
                    return n_min, n_max

                edit_type.change(
                    edit_type_change_func,
                    inputs=[edit_type],
                    outputs=[edit_n_min, edit_n_max],
                )

                edit_source = gr.Radio(
                    ["text2music", "last_edit", "upload"],
                    value="text2music",
                    label="Edit Source",
                    elem_id="edit_source",
                )
                edit_source_audio_upload = gr.Audio(
                    label="Upload Audio",
                    type="filepath",
                    visible=False,
                    elem_id="edit_source_audio_upload",
                    show_download_button=True,
                )
                edit_source.change(
                    fn=lambda x: gr.update(
                        visible=x == "upload", elem_id="edit_source_audio_upload"
                    ),
                    inputs=[edit_source],
                    outputs=[edit_source_audio_upload],
                )

                edit_bnt = gr.Button("Edit", variant="primary")
                edit_outputs, edit_input_params_json = create_output_ui("Edit")

                def edit_process_func(
                    text2music_json_data,
                    edit_input_params_json,
                    edit_source,
                    edit_source_audio_upload,
                    prompt,
                    lyrics,
                    edit_prompt,
                    edit_lyrics,
                    edit_n_min,
                    edit_n_max,
                    infer_step,
                    guidance_scale,
                    scheduler_type,
                    cfg_type,
                    omega_scale,
                    manual_seeds,
                    guidance_interval,
                    guidance_interval_decay,
                    min_guidance_scale,
                    use_erg_tag,
                    use_erg_lyric,
                    use_erg_diffusion,
                    oss_steps,
                    guidance_scale_text,
                    guidance_scale_lyric,
                    retake_seeds,
                ):
                    if edit_source == "upload":
                        src_audio_path = edit_source_audio_upload
                        audio_duration = librosa.get_duration(filename=src_audio_path)
                        json_data = {"audio_duration": audio_duration}
                    elif edit_source == "text2music":
                        json_data = text2music_json_data
                        src_audio_path = json_data["audio_path"]
                    elif edit_source == "last_edit":
                        json_data = edit_input_params_json
                        src_audio_path = json_data["audio_path"]

                    if not edit_prompt:
                        edit_prompt = prompt
                    if not edit_lyrics:
                        edit_lyrics = lyrics

                    return enhanced_process_func(
                        json_data["audio_duration"],
                        prompt,
                        lyrics,
                        infer_step,
                        guidance_scale,
                        scheduler_type,
                        cfg_type,
                        omega_scale,
                        manual_seeds,
                        guidance_interval,
                        guidance_interval_decay,
                        min_guidance_scale,
                        use_erg_tag,
                        use_erg_lyric,
                        use_erg_diffusion,
                        oss_steps,
                        guidance_scale_text,
                        guidance_scale_lyric,
                        task="edit",
                        src_audio_path=src_audio_path,
                        edit_target_prompt=edit_prompt,
                        edit_target_lyrics=edit_lyrics,
                        edit_n_min=edit_n_min,
                        edit_n_max=edit_n_max,
                        retake_seeds=retake_seeds,
                        lora_name_or_path="none"
                    )

                edit_bnt.click(
                    fn=edit_process_func,
                    inputs=[
                        input_params_json,
                        edit_input_params_json,
                        edit_source,
                        edit_source_audio_upload,
                        prompt,
                        lyrics,
                        edit_prompt,
                        edit_lyrics,
                        edit_n_min,
                        edit_n_max,
                        infer_step,
                        guidance_scale,
                        scheduler_type,
                        cfg_type,
                        omega_scale,
                        manual_seeds,
                        guidance_interval,
                        guidance_interval_decay,
                        min_guidance_scale,
                        use_erg_tag,
                        use_erg_lyric,
                        use_erg_diffusion,
                        oss_steps,
                        guidance_scale_text,
                        guidance_scale_lyric,
                        retake_seeds,
                    ],
                    outputs=edit_outputs + [edit_input_params_json],
                )

            with gr.Tab("extend"):
                extend_seeds = gr.Textbox(
                    label="extend seeds (default None)", placeholder="", value=None
                )
                left_extend_length = gr.Slider(
                    minimum=0.0,
                    maximum=240.0,
                    step=0.01,
                    value=0.0,
                    label="Left Extend Length",
                    interactive=True,
                )
                right_extend_length = gr.Slider(
                    minimum=0.0,
                    maximum=240.0,
                    step=0.01,
                    value=30.0,
                    label="Right Extend Length",
                    interactive=True,
                )
                extend_source = gr.Radio(
                    ["text2music", "last_extend", "upload"],
                    value="text2music",
                    label="Extend Source",
                    elem_id="extend_source",
                )

                extend_source_audio_upload = gr.Audio(
                    label="Upload Audio",
                    type="filepath",
                    visible=False,
                    elem_id="extend_source_audio_upload",
                    show_download_button=True,
                )
                extend_source.change(
                    fn=lambda x: gr.update(
                        visible=x == "upload", elem_id="extend_source_audio_upload"
                    ),
                    inputs=[extend_source],
                    outputs=[extend_source_audio_upload],
                )

                extend_bnt = gr.Button("Extend", variant="primary")
                extend_outputs, extend_input_params_json = create_output_ui("Extend")

                def extend_process_func(
                    text2music_json_data,
                    extend_input_params_json,
                    extend_seeds,
                    left_extend_length,
                    right_extend_length,
                    extend_source,
                    extend_source_audio_upload,
                    prompt,
                    lyrics,
                    infer_step,
                    guidance_scale,
                    scheduler_type,
                    cfg_type,
                    omega_scale,
                    manual_seeds,
                    guidance_interval,
                    guidance_interval_decay,
                    min_guidance_scale,
                    use_erg_tag,
                    use_erg_lyric,
                    use_erg_diffusion,
                    oss_steps,
                    guidance_scale_text,
                    guidance_scale_lyric,
                ):
                    if extend_source == "upload":
                        src_audio_path = extend_source_audio_upload
                        # get audio duration
                        audio_duration = librosa.get_duration(filename=src_audio_path)
                        json_data = {"audio_duration": audio_duration}
                    elif extend_source == "text2music":
                        json_data = text2music_json_data
                        src_audio_path = json_data["audio_path"]
                    elif extend_source == "last_extend":
                        json_data = extend_input_params_json
                        src_audio_path = json_data["audio_path"]

                    repaint_start = -left_extend_length
                    repaint_end = json_data["audio_duration"] + right_extend_length
                    return enhanced_process_func(
                        json_data["audio_duration"],
                        prompt,
                        lyrics,
                        infer_step,
                        guidance_scale,
                        scheduler_type,
                        cfg_type,
                        omega_scale,
                        manual_seeds,
                        guidance_interval,
                        guidance_interval_decay,
                        min_guidance_scale,
                        use_erg_tag,
                        use_erg_lyric,
                        use_erg_diffusion,
                        oss_steps,
                        guidance_scale_text,
                        guidance_scale_lyric,
                        retake_seeds=extend_seeds,
                        retake_variance=1.0,
                        task="extend",
                        repaint_start=repaint_start,
                        repaint_end=repaint_end,
                        src_audio_path=src_audio_path,
                        lora_name_or_path="none"
                    )

                extend_bnt.click(
                    fn=extend_process_func,
                    inputs=[
                        input_params_json,
                        extend_input_params_json,
                        extend_seeds,
                        left_extend_length,
                        right_extend_length,
                        extend_source,
                        extend_source_audio_upload,
                        prompt,
                        lyrics,
                        infer_step,
                        guidance_scale,
                        scheduler_type,
                        cfg_type,
                        omega_scale,
                        manual_seeds,
                        guidance_interval,
                        guidance_interval_decay,
                        min_guidance_scale,
                        use_erg_tag,
                        use_erg_lyric,
                        use_erg_diffusion,
                        oss_steps,
                        guidance_scale_text,
                        guidance_scale_lyric,
                    ],
                    outputs=extend_outputs + [extend_input_params_json],
                )

        def json2output(json_data):
            return (
                json_data["audio_duration"],
                json_data["prompt"],
                json_data["lyrics"],
                json_data["infer_step"],
                json_data["guidance_scale"],
                json_data["scheduler_type"],
                json_data["cfg_type"],
                json_data["omega_scale"],
                ", ".join(map(str, json_data["actual_seeds"])),
                json_data["guidance_interval"],
                json_data["guidance_interval_decay"],
                json_data["min_guidance_scale"],
                json_data["use_erg_tag"],
                json_data["use_erg_lyric"],
                json_data["use_erg_diffusion"],
                ", ".join(map(str, json_data["oss_steps"])),
                (
                    json_data["guidance_scale_text"]
                    if "guidance_scale_text" in json_data
                    else 0.0
                ),
                (
                    json_data["guidance_scale_lyric"]
                    if "guidance_scale_lyric" in json_data
                    else 0.0
                ),
                (
                    json_data["audio2audio_enable"]
                    if "audio2audio_enable" in json_data
                    else False
                ),
                (
                    json_data["ref_audio_strength"]
                    if "ref_audio_strength" in json_data
                    else 0.5
                ),
                (
                    json_data["ref_audio_input"]
                    if "ref_audio_input" in json_data
                    else None
                ),
            )

        def sample_data(lora_name_or_path_):
            if sample_data_func:
                json_data = sample_data_func(lora_name_or_path_)
                return json2output(json_data)
            return {}

        sample_bnt.click(
            sample_data,
            inputs=[lora_name_or_path],
            outputs=[
                audio_duration,
                prompt,
                lyrics,
                infer_step,
                guidance_scale,
                scheduler_type,
                cfg_type,
                omega_scale,
                manual_seeds,
                guidance_interval,
                guidance_interval_decay,
                min_guidance_scale,
                use_erg_tag,
                use_erg_lyric,
                use_erg_diffusion,
                oss_steps,
                guidance_scale_text,
                guidance_scale_lyric,
                audio2audio_enable,
                ref_audio_strength,
                ref_audio_input,
            ],
        )

    # 메인 생성 버튼 이벤트 (향상된 함수 사용)
    text2music_bnt.click(
        fn=enhanced_process_func,
        inputs=[
            audio_duration,
            prompt,
            lyrics,
            infer_step,
            guidance_scale,
            scheduler_type,
            cfg_type,
            omega_scale,
            manual_seeds,
            guidance_interval,
            guidance_interval_decay,
            min_guidance_scale,
            use_erg_tag,
            use_erg_lyric,
            use_erg_diffusion,
            oss_steps,
            guidance_scale_text,
            guidance_scale_lyric,
            audio2audio_enable,
            ref_audio_strength,
            ref_audio_input,
            lora_name_or_path,
            multi_seed_mode,
            enable_smart_enhancement,
            genre_preset
        ],
        outputs=outputs + [input_params_json],
    )


def create_main_demo_ui(
    text2music_process_func=dump_func,
    sample_data_func=dump_func,
    load_data_func=dump_func,
):
    with gr.Blocks(
        title="ACE-Step Model 1.0 DEMO - Enhanced with AI Lyrics",
        theme=gr.themes.Soft(),
        css="""
        .gradio-container {
            max-width: 1200px !important;
        }
        .quality-info {
            background: linear-gradient(45deg, #f0f8ff, #e6f3ff);
            padding: 10px;
            border-radius: 8px;
            margin: 5px 0;
        }
        .ai-lyrics-section {
            background: linear-gradient(45deg, #f0fff0, #e6ffe6);
            padding: 15px;
            border-radius: 10px;
            margin: 10px 0;
            border: 2px solid #90EE90;
        }
        """
    ) as demo:
        gr.Markdown(
            """
            <h1 style="text-align: center;">🎵 ACE-Step PRO with AI Lyrics</h1>
            <div style="text-align: center; margin: 20px;">
                <p><strong>🚀 새로운 기능:</strong> 🤖 AI 작사 | 품질 프리셋 | 다중 생성 | 스마트 프롬프트 | 실시간 프리뷰 | 품질 점수</p>
                <p>
                    <a href="https://ace-step.github.io/" target='_blank'>Project</a> |
                    <a href="https://huggingface.co/ACE-Step/ACE-Step-v1-3.5B">Checkpoints</a> |
                    <a href="https://discord.gg/rjAZz2xBdG" target='_blank'>Discord</a> 
                </p>
            </div>
        """
        )
        
        # 사용법 가이드 추가
        with gr.Accordion("📖 사용법 가이드", open=False):
            gr.Markdown("""
            ### 🎯 빠른 시작
            1. **🤖 AI 작사**: 주제를 입력하고 'AI 작사' 버튼을 클릭하면 자동으로 가사가 생성됩니다
            2. **장르 선택**: 원하는 음악 장르를 선택하면 자동으로 최적화된 태그가 적용됩니다
            3. **품질 설정**: Draft(빠름) → Standard(권장) → High Quality → Ultra 중 선택
            4. **다중 생성**: "Best of 3/5/10" 선택하면 여러 번 생성하여 최고 품질을 자동 선택합니다
            5. **프리뷰**: 전체 생성 전 10초 프리뷰로 빠르게 확인할 수 있습니다
            
            ### 🤖 AI 작사 기능
            - **다국어 지원**: 한국어, 영어 등 입력 언어와 동일한 언어로 가사 생성
            - **주제 예시**: "첫사랑의 설렘", "이별의 아픔", "군대가는 남자의 한숨", "희망찬 내일"  
            - **구조 태그**: [verse], [chorus], [bridge] 태그가 자동으로 포함됩니다
            - **장르 연동**: 선택한 장르에 맞는 스타일의 가사가 생성됩니다
            
            ### 💡 품질 향상 팁
            - **고품질 생성**: "High Quality" + "Best of 5" 조합 추천
            - **빠른 테스트**: "Draft" + "프리뷰" 기능 활용
            - **장르 특화**: 장르 프리셋 선택 후 "스마트 향상" 체크
            - **가사 구조**: [verse], [chorus], [bridge] 태그 적극 활용
            
            ### ⚙️ API 설정
            AI 작사 기능을 사용하려면 환경변수에 OpenAI API 키를 설정해야 합니다:
            ```bash
            export LLM_API="your-openai-api-key"
            ```
            """)
        
        with gr.Tab("🎵 Enhanced Text2Music with AI Lyrics"):
            create_text2music_ui(
                gr=gr,
                text2music_process_func=text2music_process_func,
                sample_data_func=sample_data_func,
                load_data_func=load_data_func,
            )
    return demo


if __name__ == "__main__":
    print("🚀 ACE-Step PRO with AI Lyrics 시작 중...")
    
    # API 키 상태 확인
    if client_available:
        print("✅ OpenAI API 사용 가능 - AI 작사 기능 활성화됨")
    else:
        print("❌ OpenAI API 사용 불가 - 환경변수를 확인하세요")
        print("설정 방법: export LLM_API='your-openai-api-key'")
    
    demo = create_main_demo_ui()
    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True  # 공유 링크 생성
    )