Add application file

app.py

@@ -0,0 +1,99 @@
+import os
+import openai
+import tiktoken
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+
+class Conversation:
+    def __init__(self, prompt, model="gpt-3.5-turbo", temperature=0.8, max_tokens=250):
+        self.prompt = prompt
+        self.model = model
+        self.temperature = temperature
+        self.max_tokens = max_tokens
+
+        self._init_messages()
+
+    def _init_messages(self):
+        self.messages = [{"role": "system", "content": self.prompt}]
+
+    def reset(self):
+        self._init_messages()
+
+    def ask(self, question, pprint=False):
+        self.messages.append({"role": "user", "content": question})
+
+        if self.num_tokens(self.messages, self.model) >= self.max_tokens:
+            if len(self.messages) > 3:
+                self.messages = self.messages[:1] + self.messages[3:] # remove the first user message
+            else:
+                return "Error: max tokens exceeded."
+        
+        try:
+            response = openai.ChatCompletion.create(
+                model=self.model,
+                messages=self.messages
+            )
+        except Exception as e:
+            return e
+
+        if pprint:
+            print(f"tiktoken: {self.num_tokens(self.messages, self.model)}\ntokens: {response['usage']}")
+        
+        assistant_message = response["choices"][0]["message"]["content"]
+        self.messages.append({"role": "assistant", "content": assistant_message})
+
+        return assistant_message
+    
+    def num_tokens(self, messages, model):
+        """Returns the number of tokens used by a list of messages."""
+        try:
+            encoding = tiktoken.encoding_for_model(model)
+        except KeyError:
+            print("Warning: model not found. Using cl100k_base encoding.")
+            encoding = tiktoken.get_encoding("cl100k_base")
+        if model == "gpt-3.5-turbo":
+            print("Warning: gpt-3.5-turbo may change over time. Returning num tokens assuming gpt-3.5-turbo-0301.")
+            return self.num_tokens(messages, model="gpt-3.5-turbo-0301")
+        elif model == "gpt-4":
+            print("Warning: gpt-4 may change over time. Returning num tokens assuming gpt-4-0314.")
+            return self.num_tokens(messages, model="gpt-4-0314")
+        elif model == "gpt-3.5-turbo-0301":
+            tokens_per_message = 4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
+            tokens_per_name = -1  # if there's a name, the role is omitted
+        elif model == "gpt-4-0314":
+            tokens_per_message = 3
+            tokens_per_name = 1
+        else:
+            raise NotImplementedError(f"""num_tokens_from_messages() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens.""")
+        num_tokens = 0
+        for message in messages:
+            num_tokens += tokens_per_message
+            for key, value in message.items():
+                num_tokens += len(encoding.encode(value))
+                if key == "name":
+                    num_tokens += tokens_per_name
+        num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
+        return num_tokens
+
+
+import gradio as gr
+
+system_prompt_foodie = "您是一名美食家，帮助别人了解美食的信息，回答要简洁有效并控制在100字左右。"
+
+conv = Conversation(system_prompt_foodie, max_tokens=1024)
+
+with gr.Blocks(title="ChatGPT 助手") as demo:
+    chatbot = gr.Chatbot(elem_id="chatbot")#.style(height=700)
+    msg = gr.Textbox(show_label=False).style(container=False)
+    clear = gr.Button("Clear")
+
+    def ask(message, chat_history):
+        bot_message = conv.ask(message)
+        chat_history.append((message, bot_message))
+        return "", chat_history
+
+    msg.submit(ask, [msg, chatbot], [msg, chatbot])
+    clear.click(lambda: conv.reset(), None, chatbot, queue=False)
+
+demo.launch()

requirements.txt

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+openai
+tiktoken
+