#安装一下 Python 的 Gradio 的包：conda install -c conda-forge gradio
#依赖tiktoken：pip install tiktoken，使用不同的 GPT 模型，对应着不同的 Tiktoken 的编码器模型：https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb。
import gradio as gr
import openai
import os
#import tiktoken

openai.api_key = os.environ.get("OPENAI_API_KEY")
#encoding = tiktoken.get_encoding("p50k_base")

class Conversation:
    def __init__(self, prompt, num_of_round):
        self.prompt = prompt
        self.num_of_round = num_of_round
        self.messages = []
        self.messages.append(self.prompt)

    def ask(self, question):
        #if len(encoding.encode(question)) > 512:
        if len(question) > 512:
            return "输入的文字过长，请精简后再提问"
            
        try:
            self.messages.append(question)
            response = openai.Completion.create(
                engine="text-davinci-003",
                prompt=question,
                max_tokens=3580,
                n=1,
                stop=None,
                temperature=0.5,
            )
        except Exception as e:
            print(e)
            return e

        message = response.choices[0].text.strip()
        
        if len(self.messages) > self.num_of_round*2 + 1:
            del self.messages[1:3] #Remove the first round conversation left.
            
        return message
        
prompt = """你是一个聊天机器人，请尽可能回答用户的所有问题"""

conv = Conversation(prompt, 10)

def answer(question, history=[]):
    history.append(question)
    response = conv.ask(question)
    history.append(response)
    responses = [(u,b) for u,b in zip(history[::2], history[1::2])]
    return responses, history

with gr.Blocks(css="#chatbot{height:300px} .overflow-y-auto{height:500px}") as demo:
    chatbot = gr.Chatbot(elem_id="chatbot")
    state = gr.State([])

    with gr.Row():
        txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter").style(container=False)

    txt.submit(answer, [txt, state], [chatbot, state])

demo.launch()