Update app.py

app.py

@@ -8,16 +8,12 @@ import scipy.io.wavfile
 import numpy as np
 from transformers import pipeline
 
-# 1. API 키 설정
 GENAI_KEY = os.getenv("GEMINI_KEY")
 
-# 2. [작곡가] MusicGen 로드
-print("⏳ 작곡가 소집 중...")
 try:
+    # 음질 보정 모델 로드
     music_synthesiser = pipeline("text-to-audio", "facebook/musicgen-small")
-    print("✅ 작곡가 준비 완료!")
 except Exception as e:
-    print(f"⚠️ 모델 로드 실패: {e}")
     music_synthesiser = None
 
 def find_working_model():
@@ -34,9 +30,8 @@ def find_working_model():
 
 ACTIVE_MODEL = find_working_model()
 
-# 8인 멤버 데이터
 MEMBERS = {
-    "서윤 (Korea)": { "voice": "ko-KR-SunHiNeural", "prompt": "당신은 보컬 '서윤'입니다. 시니컬하고 음악에 진심입니다." },
+    "서윤 (Korea)": { "voice": "ko-KR-SunHiNeural", "prompt": "당신은 보컬 '서윤'입니다. 시니컬하지만 음악에 진심입니다." },
     "Chloe (USA)": { "voice": "en-US-AriaNeural", "prompt": "You are 'Chloe', the lead guitarist. Cool rockstar vibe." },
     "Beatrice (Brazil)": { "voice": "pt-BR-FranciscaNeural", "prompt": "You are 'Beatrice', the drummer. Focus on rhythm." },
     "Naomi (Japan)": { "voice": "ja-JP-NanamiNeural", "prompt": "You are 'Naomi'. Focus on harmony." },
@@ -49,24 +44,22 @@ MEMBERS = {
 async def band_consulting(user_input, member_name, consult_category):
     try:
         member = MEMBERS.get(member_name, MEMBERS["서윤 (Korea)"])
+        # 리더님 요청: 영어 상담 시 무조건 영어만 사용
         requested_lang = "English" if "English" in consult_category else "Korean"
 
-        # 답변 5줄 요약 및 상세 설명 악보 이동 지시
         system_instruction = f"""
         {member['prompt']}
-        [CRITICAL: LANGUAGE] You MUST speak 100% in {requested_lang}. NEVER use other languages.
-        [CRITICAL: STYLE] 
-        1. Your verbal advice (main text) must be VERY CONCISE (under 5 lines).
-        2. Put ALL detailed musical explanations, scales, and tips inside the [TAB] section.
-        3. Start with a cool rockstar greeting.
+        [LANGUAGE RULE] Respond 100% in {requested_lang}. NEVER use other languages.
+        [RESPONSE STYLE] 
+        1. Keep your verbal response (main text) VERY CONCISE, under 5 short lines. 
+        2. Put ALL technical details, scales, and long musical advice inside the [TAB] section.
+        3. Start with a charismatic rockstar greeting.
 
-        조언 후 반드시 포함:
-        1. [TAB]: 상세 설명 + 코드 진행/텍스트 악보.
-        2. [MUSIC]: 영어 음악 프롬프트.
+        After advice, you MUST include:
+        1. [TAB]: Detailed musical explanation + Chord/Tab progression.
+        2. [MUSIC]: English music prompt (high quality, studio recording).
         """
         
-        # ... (Gemini 호출 및 데이터 추출 로직 동일)
-        
         url = f"https://generativelanguage.googleapis.com/v1beta/models/{ACTIVE_MODEL}:generateContent?key={GENAI_KEY}"
         payload = {"contents": [{"parts": [{"text": f"{system_instruction}\n질문: {user_input}"}]}]}
         res = requests.post(url, json=payload, headers={'Content-Type': 'application/json'})
@@ -78,15 +71,16 @@ async def band_consulting(user_input, member_name, consult_category):
         
         clean_text = re.sub(r'\[TAB\].*?(\[|$)', '', ai_text_raw, flags=re.DOTALL)
         clean_text = re.sub(r'\[MUSIC:.*?\]', '', clean_text).strip()
-        tts_text = re.sub(r'[\*\#\-\_\~]', '', clean_text) # 특수문자 제거
+        tts_text = re.sub(r'[\*\#\-\_\~]', '', clean_text) 
 
         voice_path = f"/tmp/v_{member_name.replace(' ', '_')}.mp3"
         await edge_tts.Communicate(tts_text, member['voice']).save(voice_path)
         
         music_path = None
         if music_match and music_synthesiser:
-            music_p = music_match.group(1).strip() + ", high quality, studio recording, master sound"
-            music_output = music_synthesiser(music_p, forward_params={"max_new_tokens": 512, "guidance_scale": 4.5, "do_sample": True})
+            p = music_match.group(1).strip() + ", high quality, studio recording"
+            # 리더님 요청: 길이 약 10~12초(512 tokens)
+            music_output = music_synthesiser(p, forward_params={"max_new_tokens": 512, "guidance_scale": 4.5, "do_sample": True})
             music_path = f"/tmp/m_{member_name.replace(' ', '_')}.wav"
             scipy.io.wavfile.write(music_path, music_output["sampling_rate"], music_output["audio"][0].T)