add

app2.py

@@ -1,56 +0,0 @@
-import torch
-from transformers import pipeline
-import gradio as gr
-
-# 모델 로드
-def load_model(model_name="deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"):
-    pipe = pipeline(
-        "text-generation",
-        model=model_name,
-        device_map="auto",
-        torch_dtype=torch.float16,
-        trust_remote_code=True,
-        truncation=True,
-        max_new_tokens=2048
-    )
-    return pipe
-
-# 챗봇 응답 생성 함수
-def chat(message, history):
-    pipe = load_model()
-    prompt = f"Human: {message}\n\nAssistant:"
-    
-    response = pipe(
-        prompt,
-        max_new_tokens=2048,
-        temperature=0.7,
-        do_sample=True,
-        truncation=True,
-        pad_token_id=50256
-    )
-    
-    # 응답 추출 및 처리
-    try:
-        bot_text = response[0]["generated_text"]
-        bot_text = bot_text.split("Assistant:")[-1].strip()
-        if "</think>" in bot_text:
-            bot_text = bot_text.split("</think>")[-1].strip()
-    except:
-        bot_text = "Sorry, there was a problem generating the response."
-    
-    return bot_text
-
-# Gradio 인터페이스 설정
-demo = gr.ChatInterface(
-    chat,
-    chatbot=gr.Chatbot(height=600),
-    textbox=gr.Textbox(placeholder="Enter your message...", container=False, scale=7),
-    title="DeepSeek-R1 Chatbot",
-    description="DeepSeek-R1-Distill-Qwen-1.5B 모델을 사용한 대화 테스트용 데모입니다.",
-    examples=["Hello", "Who are you?", "What can you do?"],
-    theme=gr.themes.Soft()
-)
-
-# 서버 실행
-if __name__ == "__main__":
-    demo.launch(share=True, server_name="0.0.0.0") 

requirements.txt

@@ -1,5 +1,5 @@
 streamlit
 torch
 transformers>=4.35.0
-accelerate
-gradio>=4.0.0
+accelerate>=0.20.0
+