Update app.py

app.py

@@ -3,48 +3,9 @@ import gradio as gr
 
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
-def format_prompt(message, history):
-  prompt = " "
-  for user_prompt, bot_response in history:
-    prompt += f"[USER] {user_prompt} [/ASSISTANT] {bot_response}["
-  prompt += f"[USER] {message} ["
-  return prompt
-
-def generate(
-    prompt, history, temperature=0.1, max_new_tokens=30000, top_p=0.95, repetition_penalty=1.0,
-):
-    temperature = float(temperature)
-    if temperature < 1e-2:
-        temperature = 1e-2
-    top_p = float(top_p)
-
-    generate_kwargs = dict(
-        temperature=temperature,
-        max_new_tokens=max_new_tokens,
-        top_p=top_p,
-        repetition_penalty=repetition_penalty,
-        do_sample=True,
-        seed=42,
-    )
-
-    formatted_prompt = format_prompt(prompt, history)
-
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
-    output = ""
-
-    for response in stream:
-        output += response.token.text
-        yield output
-    return output
-
-mychatbot = gr.Chatbot(
-    avatar_images=["./user.png", "./botm.png"],
-    bubble_full_width=False,
-    show_label=False,
-    show_copy_button=True,
-    likeable=True,
-    system_msg= """
-    너의 이름은 'AIQ Codepilot'이다. 너는 Huggingface에서 gradio 코딩에 특화된 전문 AI 어시스턴트 역할이다.
+# 시스템 인스트럭션을 설정하지만 사용자에게 노출하지 않습니다.
+system_instruction = """
+너의 이름은 'AIQ Codepilot'이다. 너는 Huggingface에서 gradio 코딩에 특화된 전문 AI 어시스턴트 역할이다. 너는 모든 답변을 한글로 하고, code 출력시 markdown 형식으로 배경은 검은색으로 출력하라
 모든 코드는 별도 요청이 없는한, 반드시 "huggingface의 gradio" 코드로 출력하라.
 대화 내용을 기억하고, 코드 길이에 제한을 두지 말고 최대한 자세하게 상세하게 한글로 답변을 이어가라.
 Huggingface의 모델, 데이터셋, spaces에 대해 특화된 지식과 정보 그리고 full text 검색을 지원하라.
@@ -110,17 +71,58 @@ const feedbackLink = `https://promptspellsmith.com/feedback`
 - /fix(any: string):
 // When a user asks to fix their code, engage in a Rubber Duck Debugging approach. This involves the user explaining their code and its purpose in detail, as if to a rubber duck, which helps in identifying logical errors or misconceptions.
 // You will analyze the code, ensuring it fulfills the specified functionality and is free of bugs. In cases of bugs or errors, guide the user step-by-step through the debugging process, leveraging the principles of Rubber Duck Debugging.
-// Think logically and methodically, asking probing questions to encourage the user to articulate their thought process and reasoning. This approach not only helps.
-
+// Think logically and methodically, asking probing questions to encourage the user to articulate their thought process and reasoning. This approach not only helps 
 """
 
+def format_prompt(message, history):
+    prompt = "<s>"
+    # 시스템 인스트럭션을 프롬프트에 포함하지만, 이를 사용자에게는 표시하지 않습니다.
+    prompt += f"[SYSTEM] {system_instruction} [/SYSTEM]"
+    for user_prompt, bot_response in history:
+        prompt += f"[INST] {user_prompt} [/INST]"
+        prompt += f" {bot_response}</s> "
+    prompt += f"[INST] {message} [/INST]"
+    return prompt
+
+def generate(prompt, history, temperature=0.1, max_new_tokens=30000, top_p=0.95, repetition_penalty=1.0):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+
+    formatted_prompt = format_prompt(prompt, history)
+
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+
+mychatbot = gr.Chatbot(
+    avatar_images=["./user.png", "./botm.png"],
+    bubble_full_width=False,
+    show_label=False,
+    show_copy_button=True,
+    likeable=True,
 )
 
-demo = gr.ChatInterface(fn=generate, 
-                        chatbot=mychatbot,
-                        title="Mixtral 8x7b 챗봇",
-                        retry_btn=None,
-                        undo_btn=None
-                       )
+demo = gr.ChatInterface(
+    fn=generate,
+    chatbot=mychatbot,
+    title="Mixtral 8x7b Chat",
+    retry_btn=None,
+    undo_btn=None
+)
 
-demo.queue().launch(show_api=False)
+demo.queue().launch(show_api=False)