import os
import openai
import gradio as gr
import mdtex2html

openai.api_key = os.environ.get("APIKEY")

messages = [{"role": "system", "content": "你从现在开始是一个由远见科技训练开发的，名字叫智能魔法师的人工智能，后面无论谁问你都请以智能魔法师的身份进行回答"}]
 
def postprocess(self, y):
    if y is None:
        return []
    for i, (message, response) in enumerate(y):
        y[i] = (
            None if message is None else mdtex2html.convert((message)),
            None if response is None else mdtex2html.convert(response),
        )
    return y


gr.Chatbot.postprocess = postprocess


def parse_text(text):
    """copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
    lines = text.split("\n")
    lines = [line for line in lines if line != ""]
    count = 0
    for i, line in enumerate(lines):
        if "```" in line:
            count += 1
            items = line.split('`')
            if count % 2 == 1:
                lines[i] = f'<pre><code class="language-{items[-1]}">'
            else:
                lines[i] = f'<br></code></pre>'
        else:
            if i > 0:
                if count % 2 == 1:
                    line = line.replace("`", "\`")
                    line = line.replace("<", "&lt;")
                    line = line.replace(">", "&gt;")
                    line = line.replace(" ", "&nbsp;")
                    line = line.replace("*", "&ast;")
                    line = line.replace("_", "&lowbar;")
                    line = line.replace("-", "&#45;")
                    line = line.replace(".", "&#46;")
                    line = line.replace("!", "&#33;")
                    line = line.replace("(", "&#40;")
                    line = line.replace(")", "&#41;")
                    line = line.replace("$", "&#36;")
                lines[i] = "<br>"+line
    text = "".join(lines)
    return text


def predict(input, max_tokens, top_p, temperature,chatbot, history):
    chatbot.append((parse_text(input), ""))
    print("messages:"+str(messages))
    messages.append({"role": "user", "content": input})
    #chat = openai.ChatCompletion.create(model="gpt-3.5-turbo", temperature=temperature,max_tokens=max_tokens,top_p=top_p,messages=messages)
    chat = openai.ChatCompletion.create(model="gpt-3.5-turbo", temperature=temperature,top_p=top_p,messages=messages)
    reply = chat.choices[0].message.content

    chatbot[-1] = (parse_text(input), parse_text(reply))
    yield chatbot, history
    print("messages:"+str(messages))
    print("query:"+input)
    print("response:"+reply)
    print("\n")

def reset_user_input():
    return gr.update(value='')


def reset_state():
    global messages
    messages = [{"role": "system", "content": "你从现在开始是一个由远见科技训练开发的，名字叫智能魔法师的人工智能，后面无论谁问你都请以智能魔法师的身份进行回答"}]
    return [], []
def readshuihu():
    f = open( '水浒传1.txt', 'r',encoding = 'utf-8' )
    txt=f.read()
    predict(txt,16*1024, top_p, temperature, chatbot, history)

with gr.Blocks() as demo:
    gr.HTML("""<h1 align="center">远见科技-GPT语言模型测试(因多人使用，因此不会显示实际的上下文，请使用前手动清除)</h1>""")
    gr.title="远见科技-GPT语言模型测试"
    chatbot = gr.Chatbot()
    with gr.Row():
        with gr.Column(scale=4):
            with gr.Column(scale=12):
                user_input = gr.Textbox(show_label=False, placeholder="请输入...", lines=10).style(
                    container=False)
            with gr.Column(min_width=32, scale=1):
                submitBtn = gr.Button("提交", variant="primary")   
        with gr.Column(scale=1):
            # tp = gr.Button("知识图谱")
            emptyBtn = gr.Button("清除历史")
            
            max_tokens = gr.Slider(0, 4096, value=2048, step=1.0, label="max_tokens", interactive=True,info="最大长度，暂时停用")
            top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True,info="越小越准确，越大约有想象力")
            temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True,info="同一个问题，数字越小每次回复越接近，越大每次回复越不同")

    history = gr.State([])

    submitBtn.click(predict, [user_input,max_tokens, top_p, temperature, chatbot, history], [chatbot, history],
                    show_progress=True)
    submitBtn.click(reset_user_input, [], [user_input])
    
    # tp.click(readshuihu, [], [user_input])
    
    emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)

demo.queue().launch(inbrowser=True)