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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

# [MODIFIED] OpenAI 라이브러리 μ‚¬μš© 방식 μˆ˜μ •
try:
    import openai
    api_key = os.getenv("LLM_API") or os.getenv("OPENAI_API_KEY")
    if api_key:
        openai.api_key = api_key
        client_available = True
        print("βœ… OpenAI API client initialized successfully")
    else:
        client_available = False
        print("⚠️ Warning: No OpenAI API key found. AI lyrics generation will be disabled.")
except Exception as e:
    client_available = False
    print(f"❌ Warning: Failed to initialize OpenAI client: {e}")

# ─── openai μ΄ˆκΈ°ν™” λΆ€λΆ„ λ°”λ‘œ μ•„λž˜μ— μΆ”κ°€ ───
from packaging import version
def _chat_completion(**kwargs):
    """SDK 버전에 맞좰 ChatCompletion ν˜ΈμΆœμ„ 좔상화"""
    if version.parse(openai.__version__) >= version.parse("1.0.0"):
        # v1 μŠ€νƒ€μΌ
        return openai.chat.completions.create(**kwargs)
    else:
        # ꡬ버전 μŠ€νƒ€μΌ
        return openai.ChatCompletion.create(**kwargs)



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

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

[chorus - duet]
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 - male]
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 - female]
Voices blend in harmony
Lost in pure cacophony
Timeless echoes timeless cries
Soulful shouts beneath the skies

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

# ν™•μž₯된 μž₯λ₯΄ 프리셋 (κΈ°μ‘΄ + κ°œμ„ λœ νƒœκ·Έ)
GENRE_PRESETS = {
    "Modern Pop": "pop, synth, drums, guitar, 120 bpm, upbeat, catchy, vibrant, polished vocals, radio-ready, commercial, layered vocals",
    "Rock": "rock, electric guitar, drums, bass, 130 bpm, energetic, rebellious, gritty, powerful vocals, raw vocals, power chords, driving rhythm",
    "Hip Hop": "hip hop, 808 bass, hi-hats, synth, 90 bpm, bold, urban, intense, rhythmic vocals, trap beats, punchy drums",
    "Country": "country, acoustic guitar, steel guitar, fiddle, 100 bpm, heartfelt, rustic, warm, 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, 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, crooning vocals, swing feel, sophisticated",
    "Metal": "metal, electric guitar, double kick drum, bass, 160 bpm, aggressive, intense, heavy, powerful vocals, distorted, powerful",
    "R&B": "r&b, synth, bass, drums, 85 bpm, sultry, groovy, romantic, silky vocals, smooth production, neo-soul",
    "K-Pop": "k-pop, synth, bass, drums, 128 bpm, catchy, energetic, polished, mixed vocals, electronic elements, danceable",
    "Ballad": "ballad, piano, strings, acoustic guitar, 70 bpm, emotional, heartfelt, romantic, expressive vocals, orchestral arrangement"
}

# 곑 μŠ€νƒ€μΌ μ˜΅μ…˜
SONG_STYLES = {
    "λ“€μ—£ (남녀 ν˜Όμ„±)": "duet, male and female vocals, harmonious, call and response",
    "μ†”λ‘œ (남성)": "solo, male vocals, powerful voice",
    "μ†”λ‘œ (μ—¬μ„±)": "solo, female vocals, emotional voice",
    "κ·Έλ£Ή (ν˜Όμ„±)": "group vocals, mixed gender, layered harmonies",
    "ν•©μ°½": "choir, multiple voices, choral arrangement",
    "랩/νž™ν•©": "rap vocals, rhythmic flow, urban style",
    "μΈμŠ€νŠΈλ£¨λ©˜νƒˆ": "instrumental, no vocals"
}

# AI μž‘μ‚¬ μ‹œμŠ€ν…œ ν”„λ‘¬ν”„νŠΈ
LYRIC_SYSTEM_PROMPT = """λ„ˆλŠ” λ…Έλž˜ 가사λ₯Ό μž‘μ‚¬ν•˜λŠ” μ „λ¬Έκ°€ 역할이닀. μ΄μš©μžκ°€ μž…λ ₯ν•˜λŠ” μ£Όμ œμ™€ μŠ€νƒ€μΌμ— 따라 κ΄€λ ¨λœ λ…Έλž˜ 가사λ₯Ό μž‘μ„±ν•˜λΌ. 

가사 μž‘μ„± κ·œμΉ™:
1. ꡬ쑰 νƒœκ·ΈλŠ” λ°˜λ“œμ‹œ "[  ]"둜 κ΅¬λΆ„ν•œλ‹€
2. μ‚¬μš© κ°€λŠ₯ν•œ ꡬ쑰 νƒœκ·Έ: [verse], [chorus], [bridge], [intro], [outro], [pre-chorus]
3. 듀엣인 경우 [verse - male], [verse - female], [chorus - duet] ν˜•μ‹μœΌλ‘œ 파트λ₯Ό λͺ…μ‹œν•œλ‹€
4. μž…λ ₯ 언어와 λ™μΌν•œ μ–Έμ–΄λ‘œ 가사λ₯Ό μž‘μ„±ν•œλ‹€
5. 각 κ΅¬μ‘°λŠ” 4-8쀄 μ •λ„λ‘œ μž‘μ„±ν•œλ‹€
6. μŒμ•… μž₯λ₯΄μ™€ λΆ„μœ„κΈ°μ— λ§žλŠ” 가사λ₯Ό μž‘μ„±ν•œλ‹€

μ˜ˆμ‹œ ν˜•μ‹:
[verse - male]
첫 번째 ꡬ절 가사
두 번째 ꡬ절 가사
...

[chorus - duet]
후렴ꡬ 가사
...
"""

def generate_lyrics_with_ai(prompt: str, genre: str, song_style: str) -> str:
    """AIλ₯Ό μ‚¬μš©ν•˜μ—¬ 가사 생성"""
    print(f"🎡 generate_lyrics_with_ai called with: prompt='{prompt}', genre='{genre}', style='{song_style}'")
    
    # [MODIFIED] client_available 체크 + openai API 호좜둜 λ³€κ²½
    if not client_available:
        print("❌ OpenAI client not available, returning default lyrics")
        return LYRIC_DEFAULT
    
    if not prompt or prompt.strip() == "":
        print("⚠️ Empty prompt, returning default lyrics")
        return LYRIC_DEFAULT
    
    try:
        # μ–Έμ–΄ 감지 및 μŠ€νƒ€μΌ 정보 μΆ”κ°€
        style_info = ""
        if "λ“€μ—£" in song_style:
            style_info = "남녀 λ“€μ—£ ν˜•μ‹μœΌλ‘œ 파트λ₯Ό λ‚˜λˆ„μ–΄ μž‘μ„±ν•΄μ£Όμ„Έμš”. [verse - male], [verse - female], [chorus - duet] ν˜•μ‹μ„ μ‚¬μš©ν•˜μ„Έμš”."
        elif "μ†”λ‘œ (남성)" in song_style:
            style_info = "남성 μ†”λ‘œ κ°€μˆ˜λ₯Ό μœ„ν•œ 가사λ₯Ό μž‘μ„±ν•΄μ£Όμ„Έμš”."
        elif "μ†”λ‘œ (μ—¬μ„±)" in song_style:
            style_info = "μ—¬μ„± μ†”λ‘œ κ°€μˆ˜λ₯Ό μœ„ν•œ 가사λ₯Ό μž‘μ„±ν•΄μ£Όμ„Έμš”."
        elif "κ·Έλ£Ή" in song_style:
            style_info = "그룹이 λΆ€λ₯΄λŠ” ν˜•μ‹μœΌλ‘œ 파트λ₯Ό λ‚˜λˆ„μ–΄ μž‘μ„±ν•΄μ£Όμ„Έμš”."
        elif "μΈμŠ€νŠΈλ£¨λ©˜νƒˆ" in song_style:
            return "[instrumental]\n\n[inst]\n\n[instrumental break]\n\n[inst]"
        
        user_prompt = f"""
주제: {prompt}
μž₯λ₯΄: {genre}
μŠ€νƒ€μΌ: {style_info}

μœ„ 정보λ₯Ό λ°”νƒ•μœΌλ‘œ λ…Έλž˜ 가사λ₯Ό μž‘μ„±ν•΄μ£Όμ„Έμš”. μž…λ ₯된 언어와 λ™μΌν•œ μ–Έμ–΄λ‘œ μž‘μ„±ν•˜κ³ , ꡬ쑰 νƒœκ·Έλ₯Ό λ°˜λ“œμ‹œ ν¬ν•¨ν•΄μ£Όμ„Έμš”.
"""
        
        print(f"πŸ“ Sending request to OpenAI...")
        
        # [MODIFIED] openai.ChatCompletion μ‚¬μš©


        response = _chat_completion(
            model="gpt-4.1-mini",
            messages=[
                {"role": "system", "content": LYRIC_SYSTEM_PROMPT},
                {"role": "user", "content": user_prompt}
            ],
            temperature=0.8,
            max_tokens=1000,
        )

        
        generated_lyrics = response.choices[0].message.content
        print(f"βœ… Generated lyrics successfully")
        return generated_lyrics
        
    except Exception as e:
        print(f"❌ AI 가사 생성 였λ₯˜: {e}")
        return LYRIC_DEFAULT

# ν’ˆμ§ˆ 프리셋 μ‹œμŠ€ν…œ μΆ”κ°€
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": "λΉ λ₯Έ μ΄ˆμ•ˆ 생성 (1-2λΆ„)"
    },
    "Standard": {
        "infer_step": 150,
        "guidance_scale": 15.0,
        "scheduler_type": "euler",
        "omega_scale": 10.0,
        "use_erg_diffusion": True,
        "use_erg_tag": True,
        "description": "ν‘œμ€€ ν’ˆμ§ˆ (3-5λΆ„)"
    },
    "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": "κ³ ν’ˆμ§ˆ 생성 (8-12λΆ„)"
    },
    "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": "졜고 ν’ˆμ§ˆ (15-20λΆ„)"
    }
}

# 닀쀑 μ‹œλ“œ 생성 μ„€μ •
MULTI_SEED_OPTIONS = {
    "Single": 1,
    "Best of 3": 3,
    "Best of 5": 5,
    "Best of 10": 10
}

class MusicGenerationCache:
    """생성 κ²°κ³Ό 캐싱 μ‹œμŠ€ν…œ"""
    def __init__(self):
        self.cache = {}
        self.max_cache_size = 50
    
    def get_cache_key(self, params):
        # μ€‘μš”ν•œ νŒŒλΌλ―Έν„°λ§ŒμœΌλ‘œ ν•΄μ‹œ 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

# μ „μ—­ μΊμ‹œ μΈμŠ€ν„΄μŠ€
generation_cache = MusicGenerationCache()

def enhance_prompt_with_genre(base_prompt: str, genre: str, song_style: str) -> str:
    """μž₯λ₯΄μ™€ μŠ€νƒ€μΌμ— λ”°λ₯Έ 슀마트 ν”„λ‘¬ν”„νŠΈ ν™•μž₯"""
    enhanced_prompt = base_prompt
    
    if genre != "Custom" and genre:
        # μž₯λ₯΄λ³„ μΆ”κ°€ κ°œμ„  νƒœκ·Έ
        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"],
            "K-Pop": ["catchy hooks", "dynamic arrangement", "polished production"],
            "Ballad": ["emotional depth", "slow tempo", "heartfelt delivery"]
        }
        
        if genre in genre_enhancements:
            additional_tags = ", ".join(genre_enhancements[genre])
            enhanced_prompt = f"{base_prompt}, {additional_tags}"
    
    # μŠ€νƒ€μΌ νƒœκ·Έ μΆ”κ°€
    if song_style in SONG_STYLES:
        style_tags = SONG_STYLES[song_style]
        enhanced_prompt = f"{enhanced_prompt}, {style_tags}"
    
    return enhanced_prompt

def calculate_quality_score(audio_path: str) -> float:
    """κ°„λ‹¨ν•œ ν’ˆμ§ˆ 점수 계산 (μ‹€μ œ κ΅¬ν˜„μ—μ„œλŠ” 더 λ³΅μž‘ν•œ λ©”νŠΈλ¦­ μ‚¬μš©)"""
    try:
        y, sr = librosa.load(audio_path)
        
        # κΈ°λ³Έ ν’ˆμ§ˆ λ©”νŠΈλ¦­
        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))
        
        # μ •κ·œν™”λœ 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  # κΈ°λ³Έκ°’

def update_quality_preset(preset_name):
    """ν’ˆμ§ˆ 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):
    """κΈ°μ‘΄ ν•¨μˆ˜λ₯Ό ν–₯μƒλœ κΈ°λŠ₯으둜 λž˜ν•‘"""
    
    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", song_style="λ“€μ—£ (남녀 ν˜Όμ„±)", **kwargs
    ):
        # 슀마트 ν”„λ‘¬ν”„νŠΈ ν™•μž₯
        if enable_smart_enhancement:
            prompt = enhance_prompt_with_genre(prompt, genre_preset, song_style)
        
        # μΊμ‹œ 확인
        cache_params = {
            'prompt': 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:
            return cached_result
        
        # 닀쀑 μ‹œλ“œ 생성
        num_candidates = MULTI_SEED_OPTIONS.get(multi_seed_mode, 1)
        
        if num_candidates == 1:
            # κΈ°μ‘΄ ν•¨μˆ˜ 호좜
            result = original_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,
                ref_audio_strength, ref_audio_input, lora_name_or_path, **kwargs
            )
        else:
            # 닀쀑 μ‹œλ“œ 생성 및 졜적 선택
            candidates = []
            
            for i in range(num_candidates):
                seed = random.randint(1, 10000)
                
                try:
                    result = original_func(
                        audio_duration, prompt, lyrics, infer_step, guidance_scale,
                        scheduler_type, cfg_type, omega_scale, str(seed),
                        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
                    )
                    
                    if result and len(result) > 0:
                        audio_path = result[0]  # 첫 번째 κ²°κ³Όκ°€ μ˜€λ””μ˜€ 파일 경둜
                        if audio_path and os.path.exists(audio_path):
                            quality_score = calculate_quality_score(audio_path)
                            candidates.append({
                                "result": result,
                                "quality_score": quality_score,
                                "seed": seed
                            })
                except Exception as e:
                    print(f"Generation {i+1} failed: {e}")
                    continue
            
            if candidates:
                # 졜고 ν’ˆμ§ˆ 선택
                best_candidate = max(candidates, key=lambda x: x["quality_score"])
                result = best_candidate["result"]
                
                # ν’ˆμ§ˆ 정보 μΆ”κ°€
                if len(result) > 1 and isinstance(result[1], dict):
                    result[1]["quality_score"] = best_candidate["quality_score"]
                    result[1]["selected_seed"] = best_candidate["seed"]
                    result[1]["candidates_count"] = len(candidates)
            else:
                # λͺ¨λ“  생성 μ‹€νŒ¨μ‹œ κΈ°λ³Έ 생성
                result = original_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,
                    ref_audio_strength, ref_audio_input, lora_name_or_path, **kwargs
                )
        
        # κ²°κ³Ό μΊμ‹œ
        generation_cache.cache_result(cache_params, result)
        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")
        
        # ν’ˆμ§ˆ 정보 ν‘œμ‹œ μΆ”κ°€
        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):
    print(args)
    return []

def create_text2music_ui(
    gr,
    text2music_process_func,
    sample_data_func=None,
    load_data_func=None,
):
    # ν–₯μƒλœ ν”„λ‘œμ„ΈμŠ€ ν•¨μˆ˜ 생성
    enhanced_process_func = create_enhanced_process_func(text2music_process_func)
    
    # UI μš”μ†Œλ₯Ό μ €μž₯ν•  λ”•μ…”λ„ˆλ¦¬
    ui = {}

    with gr.Row():
        with gr.Column():
            # ν’ˆμ§ˆ 및 μ„±λŠ₯ μ„€μ • μ„Ήμ…˜ μΆ”κ°€
            with gr.Group():
                gr.Markdown("### ⚑ ν’ˆμ§ˆ & μ„±λŠ₯ μ„€μ •")
                with gr.Row():
                    ui['quality_preset'] = gr.Dropdown(
                        choices=list(QUALITY_PRESETS.keys()),
                        value="Standard",
                        label="ν’ˆμ§ˆ 프리셋",
                        scale=2,
                        interactive=True
                    )
                    ui['multi_seed_mode'] = gr.Dropdown(
                        choices=list(MULTI_SEED_OPTIONS.keys()),
                        value="Single",
                        label="닀쀑 생성 λͺ¨λ“œ",
                        scale=2,
                        info="μ—¬λŸ¬ 번 μƒμ„±ν•˜μ—¬ 졜고 ν’ˆμ§ˆ 선택",
                        interactive=True
                    )
                
                ui['preset_description'] = gr.Textbox(
                    value=QUALITY_PRESETS["Standard"]["description"],
                    label="μ„€λͺ…",
                    interactive=False,
                    max_lines=1
                )

            with gr.Row(equal_height=True):
                ui['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,
                )
                ui['random_bnt'] = gr.Button("🎲 Random", variant="secondary", scale=1)
                ui['preview_bnt'] = gr.Button("🎡 Preview", variant="secondary", scale=2)

            # audio2audio
            with gr.Row(equal_height=True):
                ui['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"
                )
                ui['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,
                )

            ui['ref_audio_input'] = gr.Audio(
                type="filepath", 
                label="Reference Audio (for Audio2Audio)", 
                visible=False, 
                elem_id="ref_audio_input", 
                show_download_button=True
            )
            ui['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,
            )

            with gr.Column(scale=2):
                with gr.Group():
                    gr.Markdown("""### 🎼 슀마트 ν”„λ‘¬ν”„νŠΈ μ‹œμŠ€ν…œ
                    <center>μž₯λ₯΄μ™€ μŠ€νƒ€μΌμ„ μ„ νƒν•˜λ©΄ μžλ™μœΌλ‘œ μ΅œμ ν™”λœ νƒœκ·Έκ°€ μΆ”κ°€λ©λ‹ˆλ‹€.</center>""")
                    
                    with gr.Row():
                        ui['genre_preset'] = gr.Dropdown(
                            choices=["Custom"] + list(GENRE_PRESETS.keys()),
                            value="Custom",
                            label="μž₯λ₯΄ 프리셋",
                            scale=1,
                            interactive=True
                        )
                        ui['song_style'] = gr.Dropdown(
                            choices=list(SONG_STYLES.keys()),
                            value="λ“€μ—£ (남녀 ν˜Όμ„±)",
                            label="곑 μŠ€νƒ€μΌ",
                            scale=1,
                            interactive=True
                        )
                        ui['enable_smart_enhancement'] = gr.Checkbox(
                            label="슀마트 ν–₯상",
                            value=True,
                            info="μžλ™ νƒœκ·Έ μ΅œμ ν™”",
                            scale=1
                        )
                    
                    ui['prompt'] = gr.Textbox(
                        lines=2,
                        label="Tags",
                        max_lines=4,
                        value=TAG_DEFAULT,
                        placeholder="콀마둜 κ΅¬λΆ„λœ νƒœκ·Έλ“€...",
                        interactive=True
                    )

            with gr.Group():
                gr.Markdown("""### πŸ“ AI μž‘μ‚¬ μ‹œμŠ€ν…œ
                <center>주제λ₯Ό μž…λ ₯ν•˜κ³  'AI μž‘μ‚¬' λ²„νŠΌμ„ ν΄λ¦­ν•˜λ©΄ μžλ™μœΌλ‘œ 가사가 μƒμ„±λ©λ‹ˆλ‹€.</center>""")
                
                with gr.Row():
                    ui['lyric_prompt'] = gr.Textbox(
                        label="μž‘μ‚¬ 주제",
                        placeholder="예: μ²«μ‚¬λž‘μ˜ μ„€λ ˜, μ΄λ³„μ˜ μ•„ν””, 희망찬 내일...",
                        scale=3,
                        interactive=True
                    )
                    ui['generate_lyrics_btn'] = gr.Button("πŸ€– AI μž‘μ‚¬", variant="secondary", scale=1)
                
                ui['lyrics'] = gr.Textbox(
                    lines=9,
                    label="Lyrics",
                    max_lines=13,
                    value=LYRIC_DEFAULT,
                    placeholder="가사λ₯Ό μž…λ ₯ν•˜μ„Έμš”. [verse], [chorus] λ“±μ˜ ꡬ쑰 νƒœκ·Έ μ‚¬μš©μ„ ꢌμž₯ν•©λ‹ˆλ‹€.",
                    interactive=True
                )

            with gr.Accordion("Basic Settings", open=False):
                ui['infer_step'] = gr.Slider(
                    minimum=1,
                    maximum=300,
                    step=1,
                    value=150,
                    label="Infer Steps",
                    interactive=True,
                )
                ui['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.",
                )
                ui['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",
                )
                ui['guidance_scale_lyric'] = gr.Slider(
                    minimum=0.0,
                    maximum=10.0,
                    step=0.1,
                    value=0.0,
                    label="Guidance Scale Lyric",
                    interactive=True,
                )

                ui['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):
                ui['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.",
                )
                ui['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.",
                )
                ui['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.",
                )
                ui['use_erg_lyric'] = gr.Checkbox(
                    label="use ERG for lyric",
                    value=False,
                    info="The same but apply to lyric encoder's attention.",
                )
                ui['use_erg_diffusion'] = gr.Checkbox(
                    label="use ERG for diffusion",
                    value=True,
                    info="The same but apply to diffusion model's attention.",
                )

                ui['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",
                )

                ui['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)",
                )
                ui['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.",
                )
                ui['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",
                )
                ui['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",
                )

            ui['text2music_bnt'] = gr.Button("🎡 Generate Music", variant="primary", size="lg")

        with gr.Column():
            outputs, input_params_json = create_output_ui()
            # (retake, repainting, edit, extend λ“± 탭듀은 μƒλž΅)

    # [MODIFIED] μ•„λž˜λΆ€ν„°λŠ” @gr.on(...) λŒ€μ‹  μ΅œμ‹  이벀트 바인딩 λ°©μ‹μœΌλ‘œ μ—°κ²°

    # 1) Audio2Audio ν† κΈ€
    def _toggle_audio2audio(x):
        return (gr.update(visible=x), gr.update(visible=x))

    ui['audio2audio_enable'].change(
        fn=_toggle_audio2audio,
        inputs=[ui['audio2audio_enable']],
        outputs=[ui['ref_audio_input'], ui['ref_audio_strength']]
    )
    
    # 2) μž₯λ₯΄ λ³€κ²½ ν•Έλ“€λŸ¬
    def update_tags_for_genre(genre, style):
        print(f"🎡 Genre changed: {genre}, Style: {style}")
        if genre == "Custom":
            return TAG_DEFAULT
        tags = GENRE_PRESETS.get(genre, TAG_DEFAULT)
        if style in SONG_STYLES:
            tags = f"{tags}, {SONG_STYLES[style]}"
        return tags
    
    ui['genre_preset'].change(
        fn=update_tags_for_genre,
        inputs=[ui['genre_preset'], ui['song_style']],
        outputs=[ui['prompt']]
    )
    
    # 3) 곑 μŠ€νƒ€μΌ λ³€κ²½ ν•Έλ“€λŸ¬
    def update_tags_for_style(genre, style):
        print(f"🎀 Style changed: {style}, Genre: {genre}")
        if genre == "Custom":
            base_tags = TAG_DEFAULT
        else:
            base_tags = GENRE_PRESETS.get(genre, TAG_DEFAULT)
        
        if style in SONG_STYLES:
            return f"{base_tags}, {SONG_STYLES[style]}"
        return base_tags
    
    ui['song_style'].change(
        fn=update_tags_for_style,
        inputs=[ui['genre_preset'], ui['song_style']],
        outputs=[ui['prompt']]
    )
    
    # 4) ν’ˆμ§ˆ 프리셋 λ³€κ²½
    def update_quality_settings(preset):
        print(f"⚑ Quality preset: {preset}")
        if preset not in QUALITY_PRESETS:
            return ("", 150, 15.0, "euler", 10.0, True, True)
        
        p = QUALITY_PRESETS[preset]
        return (
            p["description"], 
            p["infer_step"], 
            p["guidance_scale"], 
            p["scheduler_type"], 
            p["omega_scale"], 
            p["use_erg_diffusion"], 
            p["use_erg_tag"]
        )
    
    ui['quality_preset'].change(
        fn=update_quality_settings,
        inputs=[ui['quality_preset']],
        outputs=[
            ui['preset_description'], 
            ui['infer_step'], 
            ui['guidance_scale'], 
            ui['scheduler_type'], 
            ui['omega_scale'], 
            ui['use_erg_diffusion'], 
            ui['use_erg_tag']
        ]
    )

    # 5) AI μž‘μ‚¬
    def generate_lyrics_handler(prompt, genre, style):
        print(f"πŸ€– Generate lyrics: {prompt}")
        if not prompt or prompt.strip() == "":
            # Gradio μ΅œμ‹  λ²„μ „μ—μ„œλŠ” gr.Warning λŒ€μ‹  이벀트 바인딩 ν›„ return이 κΈ°λ³Έ
            return "⚠️ μž‘μ‚¬ 주제λ₯Ό μž…λ ₯ν•΄μ£Όμ„Έμš”!"
        return generate_lyrics_with_ai(prompt, genre, style)
    
    ui['generate_lyrics_btn'].click(
        fn=generate_lyrics_handler,
        inputs=[ui['lyric_prompt'], ui['genre_preset'], ui['song_style']],
        outputs=[ui['lyrics']]
    )

    # 6) Random λ²„νŠΌ
    def random_generation(genre, style):
        print("🎲 Random generation")
        if genre == "Custom":
            genre = random.choice(list(GENRE_PRESETS.keys()))
        
        themes = ["λ„μ‹œμ˜ λ°€", "μ²«μ‚¬λž‘", "여름 ν•΄λ³€", "가을 μ •μ·¨"]
        theme = random.choice(themes)
        duration = random.choice([30, 60, 90, 120])
        
        tags = GENRE_PRESETS.get(genre, TAG_DEFAULT)
        if style in SONG_STYLES:
            tags = f"{tags}, {SONG_STYLES[style]}"
        
        new_lyrics = generate_lyrics_with_ai(theme, genre, style)
        
        return [
            duration, 
            tags, 
            new_lyrics, 
            150, 15.0, 
            "euler", 
            "apg", 
            10.0,
            str(random.randint(1, 10000)), 
            0.5, 
            0.0, 
            3.0, 
            True, 
            False, 
            True,
            None, 
            0.0, 
            0.0, 
            False, 
            0.5, 
            None
        ]
    
    ui['random_bnt'].click(
        fn=random_generation,
        inputs=[ui['genre_preset'], ui['song_style']],
        outputs=[
            ui['audio_duration'], 
            ui['prompt'], 
            ui['lyrics'], 
            ui['infer_step'], 
            ui['guidance_scale'], 
            ui['scheduler_type'], 
            ui['cfg_type'], 
            ui['omega_scale'],
            ui['manual_seeds'], 
            ui['guidance_interval'], 
            ui['guidance_interval_decay'],
            ui['min_guidance_scale'], 
            ui['use_erg_tag'], 
            ui['use_erg_lyric'], 
            ui['use_erg_diffusion'],
            ui['oss_steps'], 
            ui['guidance_scale_text'],
            ui['guidance_scale_lyric'], 
            ui['audio2audio_enable'], 
            ui['ref_audio_strength'],
            ui['ref_audio_input']
        ]
    )

    # 7) 메인 생성 λ²„νŠΌ
    ui['text2music_bnt'].click(
        fn=enhanced_process_func,
        inputs=[
            ui['audio_duration'], ui['prompt'], ui['lyrics'], ui['infer_step'], 
            ui['guidance_scale'], ui['scheduler_type'], ui['cfg_type'], ui['omega_scale'],
            ui['manual_seeds'], ui['guidance_interval'], ui['guidance_interval_decay'],
            ui['min_guidance_scale'], ui['use_erg_tag'], ui['use_erg_lyric'], 
            ui['use_erg_diffusion'], ui['oss_steps'], ui['guidance_scale_text'],
            ui['guidance_scale_lyric'], ui['audio2audio_enable'], ui['ref_audio_strength'],
            ui['ref_audio_input'], ui['lora_name_or_path'], ui['multi_seed_mode'],
            ui['enable_smart_enhancement'], ui['genre_preset'], ui['song_style']
        ],
        outputs=outputs + [input_params_json]
    )
    
    print("βœ… 이벀트 ν•Έλ“€λŸ¬ μ—°κ²° μ™„λ£Œ!")

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",
        theme=gr.themes.Soft(),
        css="""
        /* κ·ΈλΌλ””μ–ΈνŠΈ λ°°κ²½ */
        .gradio-container {
            max-width: 1200px !important;
            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
            min-height: 100vh;
        }
        
        /* 메인 μ»¨ν…Œμ΄λ„ˆ μŠ€νƒ€μΌ */
        .main-container {
            background: rgba(255, 255, 255, 0.95);
            border-radius: 20px;
            padding: 30px;
            margin: 20px auto;
            box-shadow: 0 20px 40px rgba(0, 0, 0, 0.1);
        }
        
        /* 헀더 μŠ€νƒ€μΌ */
        .header-title {
            background: linear-gradient(45deg, #667eea, #764ba2);
            -webkit-background-clip: text;
            -webkit-text-fill-color: transparent;
            font-size: 3em;
            font-weight: bold;
            text-align: center;
            margin-bottom: 10px;
        }
        
        /* λ²„νŠΌ μŠ€νƒ€μΌ */
        .gr-button-primary {
            background: linear-gradient(45deg, #667eea, #764ba2) !important;
            border: none !important;
            color: white !important;
            font-weight: bold !important;
            transition: all 0.3s ease !important;
        }
        
        .gr-button-primary:hover {
            transform: translateY(-2px);
            box-shadow: 0 10px 20px rgba(102, 126, 234, 0.3);
        }
        
        .gr-button-secondary {
            background: linear-gradient(45deg, #f093fb, #f5576c) !important;
            border: none !important;
            color: white !important;
            transition: all 0.3s ease !important;
        }
        
        /* κ·Έλ£Ή μŠ€νƒ€μΌ */
        .gr-group {
            background: rgba(255, 255, 255, 0.8) !important;
            border: 1px solid rgba(102, 126, 234, 0.2) !important;
            border-radius: 15px !important;
            padding: 20px !important;
            margin: 10px 0 !important;
            backdrop-filter: blur(10px) !important;
        }
        
        /* νƒ­ μŠ€νƒ€μΌ */
        .gr-tab {
            background: rgba(255, 255, 255, 0.9) !important;
            border-radius: 10px !important;
            padding: 15px !important;
        }
        
        /* μž…λ ₯ ν•„λ“œ μŠ€νƒ€μΌ */
        .gr-textbox, .gr-dropdown, .gr-slider {
            border: 2px solid rgba(102, 126, 234, 0.3) !important;
            border-radius: 10px !important;
            transition: all 0.3s ease !important;
        }
        
        .gr-textbox:focus, .gr-dropdown:focus {
            border-color: #667eea !important;
            box-shadow: 0 0 10px rgba(102, 126, 234, 0.2) !important;
        }
        
        /* ν’ˆμ§ˆ 정보 μŠ€νƒ€μΌ */
        .quality-info {
            background: linear-gradient(135deg, #f093fb20, #f5576c20);
            padding: 15px;
            border-radius: 10px;
            margin: 10px 0;
            border: 1px solid rgba(240, 147, 251, 0.3);
        }
        
        /* μ• λ‹ˆλ©”μ΄μ…˜ */
        @keyframes fadeIn {
            from {
                opacity: 0;
                transform: translateY(20px);
            }
            to {
                opacity: 1;
                transform: translateY(0);
            }
        }
        
        .gr-row, .gr-column {
            animation: fadeIn 0.5s ease-out;
        }
        
        /* μŠ€ν¬λ‘€λ°” μŠ€νƒ€μΌ */
        ::-webkit-scrollbar {
            width: 10px;
        }
        
        ::-webkit-scrollbar-track {
            background: rgba(255, 255, 255, 0.1);
            border-radius: 10px;
        }
        
        ::-webkit-scrollbar-thumb {
            background: linear-gradient(45deg, #667eea, #764ba2);
            border-radius: 10px;
        }
        
        /* λ§ˆν¬λ‹€μš΄ μŠ€νƒ€μΌ */
        .gr-markdown {
            color: #4a5568 !important;
        }
        
        .gr-markdown h3 {
            color: #667eea !important;
            font-weight: 600 !important;
            margin: 15px 0 !important;
        }
        """
    ) as demo:
        with gr.Column(elem_classes="main-container"):
            gr.HTML(
                """
                <h1 class="header-title">🎡 ACE-Step PRO</h1>
                <div style="text-align: center; margin: 20px;">
                    <p style="font-size: 1.2em; color: #4a5568;"><strong>πŸš€ μƒˆλ‘œμš΄ κΈ°λŠ₯:</strong> AI μž‘μ‚¬ | ν’ˆμ§ˆ 프리셋 | 닀쀑 생성 | 슀마트 ν”„λ‘¬ν”„νŠΈ | μ‹€μ‹œκ°„ 프리뷰</p>
                    <p style="margin-top: 10px;">
                        <a href="https://ace-step.github.io/" target='_blank' style="color: #667eea; text-decoration: none; margin: 0 10px;">πŸ“„ Project</a> |
                        <a href="https://huggingface.co/ACE-Step/ACE-Step-v1-3.5B" style="color: #667eea; text-decoration: none; margin: 0 10px;">πŸ€— Checkpoints</a> |
                        <a href="https://discord.gg/rjAZz2xBdG" target='_blank' style="color: #667eea; text-decoration: none; margin: 0 10px;">πŸ’¬ Discord</a> 
                    </p>
                </div>
                """
            )
            
            # μ‚¬μš©λ²• κ°€μ΄λ“œ μΆ”κ°€
            with gr.Accordion("πŸ“– μ‚¬μš©λ²• κ°€μ΄λ“œ", open=False):
                gr.Markdown("""
                ### 🎯 λΉ λ₯Έ μ‹œμž‘
                1. **μž₯λ₯΄ & μŠ€νƒ€μΌ 선택**: μ›ν•˜λŠ” μŒμ•… μž₯λ₯΄μ™€ 곑 μŠ€νƒ€μΌ(λ“€μ—£, μ†”λ‘œ λ“±)을 μ„ νƒν•©λ‹ˆλ‹€
                2. **AI μž‘μ‚¬**: 주제λ₯Ό μž…λ ₯ν•˜κ³  'AI μž‘μ‚¬' λ²„νŠΌμœΌλ‘œ μžλ™ 가사λ₯Ό μƒμ„±ν•©λ‹ˆλ‹€
                3. **ν’ˆμ§ˆ μ„€μ •**: Draft(빠름) β†’ Standard(ꢌμž₯) β†’ High Quality β†’ Ultra 쀑 선택
                4. **닀쀑 생성**: "Best of 3/5/10" μ„ νƒν•˜λ©΄ μ—¬λŸ¬ 번 μƒμ„±ν•˜μ—¬ 졜고 ν’ˆμ§ˆμ„ μžλ™ μ„ νƒν•©λ‹ˆλ‹€
                5. **프리뷰**: 전체 생성 μ „ 10초 ν”„λ¦¬λ·°λ‘œ λΉ λ₯΄κ²Œ 확인할 수 μžˆμŠ΅λ‹ˆλ‹€
                
                ### πŸ’‘ ν’ˆμ§ˆ ν–₯상 팁
                - **κ³ ν’ˆμ§ˆ 생성**: "High Quality" + "Best of 5" μ‘°ν•© μΆ”μ²œ
                - **λΉ λ₯Έ ν…ŒμŠ€νŠΈ**: "Draft" + "프리뷰" κΈ°λŠ₯ ν™œμš©
                - **μž₯λ₯΄ νŠΉν™”**: μž₯λ₯΄ 프리셋 선택 ν›„ "슀마트 ν–₯상" 체크
                - **가사 ꡬ쑰**: [verse], [chorus], [bridge] νƒœκ·Έ 적극 ν™œμš©
                - **λ‹€κ΅­μ–΄ 지원**: ν•œκ΅­μ–΄λ‘œ 주제λ₯Ό μž…λ ₯ν•˜λ©΄ ν•œκ΅­μ–΄ 가사가 μƒμ„±λ©λ‹ˆλ‹€
                
                ### ⚠️ OpenAI API μ„€μ •
                AI μž‘μ‚¬ κΈ°λŠ₯을 μ‚¬μš©ν•˜λ €λ©΄ ν™˜κ²½λ³€μˆ˜μ— OpenAI API ν‚€λ₯Ό μ„€μ •ν•΄μ•Ό ν•©λ‹ˆλ‹€:
                ```bash
                export LLM_API="your-openai-api-key"
                # λ˜λŠ”
                export OPENAI_API_KEY="your-openai-api-key"
                ```
                """)
            
            with gr.Tab("🎡 Enhanced Text2Music", elem_classes="gr-tab"):
                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("πŸš€ ACE-Step PRO μ‹œμž‘ 쀑...")
    demo = create_main_demo_ui()

    demo.launch(
        server_name="0.0.0.0",
        server_port=7860,
        share=True,          # 곡유 링크
        ssr_mode=False       # ← SSR λΉ„ν™œμ„±ν™”
    )