Update app.py

app.py

@@ -31,24 +31,29 @@ class ModelManager:
             cls._music_pipeline = pipeline("text-to-audio", "facebook/musicgen-small", device="cpu")
         return cls._music_pipeline
 
-# 8인 멤버 보이스 (상담 언어와 관계없이 멤버 고유 보이스 유지)
-MEMBERS_VOICE = {
-    "서윤 (Korea)": "ko-KR-SunHiNeural", "Chloe (USA)": "en-US-AriaNeural", 
-    "Naomi (Japan)": "ja-JP-NanamiNeural", "Beatrice (Brazil)": "pt-BR-FranciscaNeural",
-    "Elena (Spain)": "es-ES-ElviraNeural", "Amira (Egypt)": "ar-EG-SalmaNeural",
-    "Liwei (China)": "zh-CN-XiaoxiaoNeural", "Sophie (France)": "fr-FR-DeniseNeural"
+# 8개 언어별 전담 멤버 및 보이스 설정
+LANG_MEMBER_MAP = {
+    "Korean": {"name": "서윤 (Korea)", "voice": "ko-KR-SunHiNeural"},
+    "English": {"name": "Chloe (USA)", "voice": "en-US-AriaNeural"},
+    "Japanese": {"name": "Naomi (Japan)", "voice": "ja-JP-NanamiNeural"},
+    "Portuguese": {"name": "Beatrice (Brazil)", "voice": "pt-BR-FranciscaNeural"},
+    "Spanish": {"name": "Elena (Spain)", "voice": "es-ES-ElviraNeural"},
+    "Arabic": {"name": "Amira (Egypt)", "voice": "ar-EG-SalmaNeural"},
+    "Chinese": {"name": "Liwei (China)", "voice": "zh-CN-XiaoxiaoNeural"},
+    "French": {"name": "Sophie (France)", "voice": "fr-FR-DeniseNeural"}
 }
 
-async def band_consulting(user_input, member_name, consult_lang, g_inst, b_inst, d_inst, chords):
+async def band_consulting(user_input, selected_lang, g_inst, b_inst, d_inst, chords):
     req_id = str(uuid.uuid4())[:8]
     voice_path = f"/tmp/v_{req_id}.mp3"
     music_path = f"/tmp/m_{req_id}.wav"
     
-    jam_context = f"Guitar: {g_inst}, Bass: {b_inst}, Drums: {d_inst}, Chords: {chords}"
+    # 선택된 언어에 따른 멤버 자동 매칭
+    member_info = LANG_MEMBER_MAP.get(selected_lang, LANG_MEMBER_MAP["Korean"])
+    member_name = member_info["name"]
     
-    # 리더님 지시: 선택된 consult_lang으로 답변 강제
-    system_prompt = f"""You are {member_name}, a global rock star. 
-    You MUST respond ONLY in the language: {consult_lang}.
+    jam_context = f"Guitar: {g_inst}, Bass: {b_inst}, Drums: {d_inst}, Chords: {chords}"
+    system_prompt = f"""You are {member_name}. You MUST respond ONLY in {selected_lang}.
     Provide 5-7 lines of professional music advice. 
     [TAB] Section: Detailed chords/tabs.
     [MUSIC] Section: English prompt reflecting: {jam_context}"""
@@ -71,17 +76,17 @@ async def band_consulting(user_input, member_name, consult_lang, g_inst, b_inst,
 
     tab_match = re.search(r'\[TAB\](.*?)(\[|$)', ai_text_raw, re.DOTALL | re.IGNORECASE)
     music_match = re.search(r'\[MUSIC:(.*?)\]', ai_text_raw, re.IGNORECASE)
-    tab_display = tab_match.group(1).strip() if tab_match else "No Score Data"
+    tab_display = tab_match.group(1).strip() if tab_match else "No Data"
     clean_text = re.sub(r'\[TAB\].*?(\[|$)', '', ai_text_raw, flags=re.DOTALL | re.IGNORECASE)
     clean_text = re.sub(r'\[MUSIC:.*?\]', '', clean_text, flags=re.IGNORECASE).strip()
     
-    # TTS 보이스 (멤버 이름에 맞는 보이스 선택)
-    voice_name = MEMBERS_VOICE.get(member_name, "en-US-AriaNeural")
-    communicate = edge_tts.Communicate(re.sub(r'[\*\#\-\_\~\|]', '', clean_text), voice_name)
+    # TTS 생성
+    communicate = edge_tts.Communicate(re.sub(r'[\*\#\-\_\~\|]', '', clean_text), member_info["voice"])
     await communicate.save(voice_path)
 
+    # MusicGen 생성 (12초)
     music_gen = ModelManager.get_music()
-    music_p = music_match.group(1).strip() if music_match else "rock guitar riff"
+    music_p = music_match.group(1).strip() if music_match else "rock guitar"
     music_output = music_gen(music_p, forward_params={"max_new_tokens": 512})
     audio_data = np.squeeze(music_output["audio"])
     audio_int16 = (audio_data * 32767).astype(np.int16)
@@ -90,7 +95,8 @@ async def band_consulting(user_input, member_name, consult_lang, g_inst, b_inst,
     return clean_text, voice_path, music_path, tab_display
 
 with gr.Blocks() as demo:
-    inputs = [gr.Textbox(visible=False) for _ in range(7)]
+    # 파라미터 6개 (상담내용, 상담언어, 기타, 베이스, 드럼, 코드)
+    inputs = [gr.Textbox(visible=False) for _ in range(6)]
     outputs = [gr.Textbox(visible=False), gr.Audio(visible=False), gr.Audio(visible=False), gr.Textbox(visible=False)]
     btn = gr.Button("API", visible=False)
     btn.click(band_consulting, inputs, outputs, api_name="predict")