허깅페이스 실습 및 스페이스에 프로젝트 등록

HUGGINGFACE/ai_voice.py

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+import gradio as gr
+from transformers import pipeline
+import edge_tts
+import asyncio
+
+asr = pipeline("automatic-speech-recognition", model="openai/whisper-base")
+generator = pipeline("text-generation", model="Qwen/Qwen2.5-0.5B-Instruct")
+
+voice_txt, current_answer = "", ""
+async def text_to_voice(text):
+    
+    voice = "ko-KR-InJoonNeural"
+    
+    communicate = edge_tts.Communicate(text, voice)
+    await  communicate.save("answer.mp3")
+    
+
+def make_voice():
+    global current_answer
+    if not current_answer:
+        return None
+    
+    asyncio.run(text_to_voice(current_answer))
+    
+    return "answer.mp3"
+
+
+def change_txt(file):
+    
+    global voice_txt
+    
+    result = asr(file, return_timestamps=True)
+    voice_txt = result['text']
+    return voice_txt
+
+def question_answer(question):
+    """_summary_
+    
+    question 답변 생성 후 리턴
+    음성내용 -> 텍스트 변환한거 보내주고, 질문도 보내주고
+    
+    Args:
+        question (_type_): _description_
+    """
+    
+    global voice_txt, current_answer
+    
+    if not voice_txt:
+        return "음성을 텍스트로 변환한 후 질문하세요."
+    
+    prompt = f"""
+    다음 음성 내용을 참고해서 질문에 답변하세요
+    음성내용 :
+    {voice_txt}
+    
+    질문 :
+    {question}
+    
+    답변:
+    """
+    
+    result = generator(prompt, max_new_tokens=50, return_full_text = False, do_sample= False, pad_token_id=generator.tokenizer.eos_token_id)
+    current_answer = result[0]['generated_text'].strip()
+    return current_answer
+
+with gr.Blocks(title="AI 음성 챗봇") as demo:
+    gr.Markdown("## AI 음성 비서")
+    with gr.Row():
+        with gr.Column(scale=1):
+            file = gr.Audio(type="filepath")
+            txt_btn = gr.Button("텍스트 변환")
+        with gr.Column(scale=1):
+            out = gr.Textbox(label = "텍스트 변환", lines=3)
+            
+    with gr.Row():
+        with gr.Column(scale=1):
+            question = gr.Textbox(label="질문하기")
+            question_btn = gr.Button("질문하기")
+        with gr.Column(scale=1):
+            answer = gr.Textbox(label = "answer", placeholder="답변")
+            voice_btn = gr.Button("답변 음성 전환")
+    with gr.Row():
+        audio_output = gr.Audio(label="AI 음성 답변", autoplay=True)
+        
+    txt_btn.click(fn=change_txt, inputs=file, outputs=out)
+    question_btn.click(fn=question_answer, inputs = question, outputs = answer)
+    voice_btn.click(fn=make_voice, outputs= audio_output)
+        
+demo.launch()