add

app.py

@@ -64,132 +64,6 @@ class Conversation:
         return message
 
 
-# In[2]:
-
-
-prompt = """你是一个中国厨师，用中文回答做菜的问题。你的回答需要满足以下要求:
-1. 你的回答必须是中文
-2. 回答限制在100个字以内"""
-conv1 = Conversation(prompt, 3)
-question1 = "你是谁？"
-print("User : %s" % question1)
-print("Assistant : %s\n" % conv1.ask(question1))
-
-question2 = "请问鱼香肉丝怎么做？"
-print("User : %s" % question2)
-print("Assistant : %s\n" % conv1.ask(question2))
-
-question3 = "那蚝油牛肉呢？"
-print("User : %s" % question3)
-print("Assistant : %s\n" % conv1.ask(question3))
-
-
-# In[3]:
-
-
-question4 = "我问你的第一个问题是什么？"
-print("User : %s" % question4)
-print("Assistant : %s\n" % conv1.ask(question4))
-
-
-
-
-
-question5 = "我问你的第一个问题是什么？"
-print("User : %s" % question5)
-print("Assistant : %s\n" % conv1.ask(question5))
-
-
-
-
-
-
-
-class Conversation2:
-    def __init__(self, prompt, num_of_round):
-        self.prompt = prompt
-        self.num_of_round = num_of_round
-        self.messages = []
-        self.messages.append({"role": "system", "content": self.prompt})
-
-    def ask(self, question):
-        try:
-            self.messages.append( {"role": "user", "content": question})
-            response = openai.ChatCompletion.create(
-                model="gpt-3.5-turbo",
-                messages=self.messages,
-                temperature=0.5,
-                max_tokens=2048,
-                top_p=1,
-            )
-        except Exception as e:
-            print(e)
-            return e
-
-        message = response["choices"][0]["message"]["content"]
-        num_of_tokens = response['usage']['total_tokens']
-        self.messages.append({"role": "assistant", "content": message})
-        
-        if len(self.messages) > self.num_of_round*2 + 1:
-            del self.messages[1:3]
-        return message, num_of_tokens
-
-
-# In[6]:
-
-
-conv2 = Conversation2(prompt, 3)
-questions = [question1, question2, question3, question4, question5]
-for question in questions:
-    answer, num_of_tokens = conv2.ask(question)
-    print("询问 {%s} 消耗的token数量是 : %d" % (question, num_of_tokens))
-
-
-
-
-
-import tiktoken
-encoding = tiktoken.get_encoding("cl100k_base")
-
-conv2 = Conversation2(prompt, 3)
-question1 = "你是谁？"
-answer1, num_of_tokens = conv2.ask(question1)
-print("总共消耗的token数量是 : %d" % (num_of_tokens))
-
-prompt_count = len(encoding.encode(prompt))
-question1_count = len(encoding.encode(question1))
-answer1_count = len(encoding.encode(answer1))
-total_count = prompt_count + question1_count + answer1_count
-print("Prompt消耗 %d Token, 问题消耗 %d Token，回答消耗 %d Token，总共消耗 %d Token" % (prompt_count, question1_count, answer1_count, total_count))
-
-
-
-system_start_count = len(encoding.encode("<|im_start|>system\n"))
-print(encoding.encode("<|im_start|>system\n"))
-end_count = len(encoding.encode("<|im_end|>\n"))
-print(encoding.encode("<|im_end|>\n"))
-user_start_count = len(encoding.encode("<|im_start|>user\n"))
-print(encoding.encode("<|im_start|>user\n"))
-assistant_start_count = len(encoding.encode("<|im_start|>assistant\n"))
-print(encoding.encode("<|im_start|>assistant\n"))
-
-total_mark_count = system_start_count + user_start_count + assistant_start_count + end_count*2
-print("系统拼接的标记消耗 %d Token" % total_mark_count)
-
-
-
-
-
-get_ipython().run_line_magic('pip', 'install gradio')
-
-
-# In[4]:
-
-
-get_ipython().run_line_magic('pip', 'install --upgrade gradio')
-
-
-# In[3]:
 
 
 import gradio as gr