app.py

import json
import gradio as gr
# import openai
import os
import sys
import traceback
import requests
# import markdown
import csv

my_api_key = ""    # 在这里输入你的 API 密钥
HIDE_MY_KEY = False # 如果你想在UI中隐藏你的 API 密钥，将此值设置为 True

initial_prompt = "You are a helpful assistant."
API_URL = "https://api.openai.com/v1/chat/completions"
HISTORY_DIR = "history"
TEMPLATES_DIR = "templates"



#if we are running in Docker
if os.environ.get('dockerrun') == 'yes':
    dockerflag = True
else:
    dockerflag = False

if dockerflag:
    my_api_key = os.environ.get('my_api_key')
    if my_api_key == "empty":
        print("Please give a api key!")
        sys.exit(1)
    #auth
    username = os.environ.get('USERNAME')
    password = os.environ.get('PASSWORD')
    if isinstance(username, type(None)) or isinstance(password, type(None)):
        authflag = False
    else:
        authflag = True


def parse_text(text):
    lines = text.split("\n")
    lines = [line for line in lines if line != ""]
    count = 0
    firstline = False
    for i, line in enumerate(lines):
        if "```" in line:
            count += 1
            items = line.split('`')
            if count % 2 == 1:
                lines[i] = f'<pre><code class="{items[-1]}">'
                firstline = True
            else:
                lines[i] = f'</code></pre>'
        else:
            if i > 0:
                if count % 2 == 1:
                    line = line.replace("`", "\`")
                    line = line.replace("\"", "`\"`")
                    line = line.replace("\'", "`\'`")
                    # line = line.replace("&", "&amp;")
                    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(inputs, top_p, temperature, openai_api_key, chatbot=[], history=[], system_prompt=initial_prompt, retry=False, summary=False, summary_on_crash = False, stream = True):  # repetition_penalty, top_k

    if summary:
        stream = False

    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {openai_api_key}"
    }

    chat_counter = len(history) // 2

    print(f"chat_counter - {chat_counter}")

    messages = [compose_system(system_prompt)]
    if chat_counter:
        for index in range(0, 2*chat_counter, 2):
            temp1 = {}
            temp1["role"] = "user"
            temp1["content"] = history[index]
            temp2 = {}
            temp2["role"] = "assistant"
            temp2["content"] = history[index+1]
            if temp1["content"] != "":
                if temp2["content"] != "" or retry:
                    messages.append(temp1)
                    messages.append(temp2)
            else:
                messages[-1]['content'] = temp2['content']
    if retry and chat_counter:
        messages.pop()
    elif summary:
        history = [*[i["content"] for i in messages[-2:]], "我们刚刚聊了什么？"]
        messages.append(compose_user(
            "请帮我总结一下上述对话的内容，实现减少字数的同时，保证对话的质量。在总结中不要加入这一句话。"))
    else:
        temp3 = {}
        temp3["role"] = "user"
        temp3["content"] = inputs
        messages.append(temp3)
        chat_counter += 1
    # messages
    payload = {
        "model": "gpt-3.5-turbo",
        "messages": messages,  # [{"role": "user", "content": f"{inputs}"}],
        "temperature": temperature,  # 1.0,
        "top_p": top_p,  # 1.0,
        "n": 1,
        "stream": stream,
        "presence_penalty": 0,
        "frequency_penalty": 0,
    }

    if not summary:
        history.append(inputs)
    else:
        print("精简中...")
    # make a POST request to the API endpoint using the requests.post method, passing in stream=True
    response = requests.post(API_URL, headers=headers,
                             json=payload, stream=True)

    token_counter = 0
    partial_words = ""

    counter = 0
    if stream:
        chatbot.append((parse_text(history[-1]), ""))
        for chunk in response.iter_lines():
            if counter == 0:
                counter += 1
                continue
            counter += 1
            # check whether each line is non-empty
            if chunk:
                # decode each line as response data is in bytes
                try:
                    if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
                        break
                except Exception as e:
                    traceback.print_exc()
                    print("Context 过长，正在尝试精简……")
                    chatbot.pop()
                    chatbot, history, status_text = next(predict(inputs, top_p, temperature, openai_api_key, chatbot, history, system_prompt, retry, summary=True, summary_on_crash=True, stream=False))
                    yield chatbot, history, status_text
                    if not "ERROR" in status_text:
                        print("精简完成，正在尝试重新生成……")
                        yield next(predict(inputs, top_p, temperature, openai_api_key, chatbot, history, system_prompt, retry, summary=False, summary_on_crash=True, stream=False))
                    else:
                        print("精简出错了，可能是网络原因。")
                    break
                chunkjson = json.loads(chunk.decode()[6:])
                status_text = f"id: {chunkjson['id']}, finish_reason: {chunkjson['choices'][0]['finish_reason']}"
                partial_words = partial_words + \
                    json.loads(chunk.decode()[6:])[
                        'choices'][0]["delta"]["content"]
                if token_counter == 0:
                    history.append(" " + partial_words)
                else:
                    history[-1] = partial_words
                chatbot[-1] = (parse_text(history[-2]), parse_text(history[-1]))
                token_counter += 1
                yield chatbot, history, status_text
    else:
        try:
            responsejson = json.loads(response.text)
            content = responsejson["choices"][0]["message"]["content"]
            history.append(content)
            chatbot.append((parse_text(history[-2]), parse_text(content)))
            status_text = "精简完成"
        except:
            chatbot.append((parse_text(history[-1]), "☹️发生了错误，请检查网络连接或者稍后再试。"))
            status_text = "status: ERROR"
        yield chatbot, history, status_text



def delete_last_conversation(chatbot, history):
    if "☹️发生了错误" in chatbot[-1][1]:
        chatbot.pop()
        print(history)
        return chatbot, history
    history.pop()
    history.pop()
    print(history)
    return chatbot, history

def save_chat_history(filename, system, history, chatbot):
    if filename == "":
        return
    if not filename.endswith(".json"):
        filename += ".json"
    os.makedirs(HISTORY_DIR, exist_ok=True)
    json_s = {"system": system, "history": history, "chatbot": chatbot}
    print(json_s)
    with open(os.path.join(HISTORY_DIR, filename), "w") as f:
        json.dump(json_s, f)


def load_chat_history(filename):
    with open(os.path.join(HISTORY_DIR, filename), "r") as f:
        json_s = json.load(f)
    print(json_s)
    return filename, json_s["system"], json_s["history"], json_s["chatbot"]


def get_file_names(dir, plain=False, filetype=".json"):
    # find all json files in the current directory and return their names
    try:
        files = sorted([f for f in os.listdir(dir) if f.endswith(filetype)])
    except FileNotFoundError:
        files = []
    if plain:
        return files
    else:
        return gr.Dropdown.update(choices=files)

def get_history_names(plain=False):
    return get_file_names(HISTORY_DIR, plain)

def load_template(filename, plain=False):
    lines = []
    with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as csvfile:
        reader = csv.reader(csvfile)
        lines = list(reader)
    lines = lines[1:]
    if plain:
        return sorted([row[0] for row in lines])
    else:
        return {row[0]:row[1] for row in lines}, gr.Dropdown.update(choices=sorted([row[0] for row in lines]))

def get_template_names(plain=False):
    return get_file_names(TEMPLATES_DIR, plain, filetype=".csv")

def reset_state():
    return [], []


def compose_system(system_prompt):
    return {"role": "system", "content": system_prompt}


def compose_user(user_input):
    return {"role": "user", "content": user_input}


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

title = """<h1 align="center">川虎ChatGPT 🚀</h1>"""
description = """<div align=center>

由Bilibili [土川虎虎虎](https://space.bilibili.com/29125536) 和 [明昭MZhao](https://space.bilibili.com/24807452)开发

访问川虎ChatGPT的 [GitHub项目](https://github.com/GaiZhenbiao/ChuanhuChatGPT) 下载最新版脚本

此App使用 `gpt-3.5-turbo` 大语言模型
</div>
"""
customCSS = """
code {
    display: inline;
    white-space: break-spaces;
    border-radius: 6px;
    margin: 0 2px 0 2px;
    padding: .2em .4em .1em .4em;
    background-color: rgba(175,184,193,0.2);
}
pre {
    display: block;
    white-space: pre;
    background-color: hsla(0, 0%, 0%, 72%);
    border: solid 5px var(--color-border-primary) !important;
    border-radius: 8px;
    padding: 0 1.2rem 1.2rem;
    margin-top: 1em !important;
    color: #FFF;
    box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2)
}
pre code, pre code code {
    background-color: transparent !important;
    margin: 0;
    padding: 0;
}
"""

with gr.Blocks(css=customCSS) as demo:
    gr.HTML(title)
    gr.HTML('''<center><a href="https://huggingface.co/spaces/JohnSmith9982/ChuanhuChatGPT?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="复制 Space"></a>强烈建议点击上面的按钮复制一份这个Space，在你自己的Space里运行，响应更迅速、也更安全👆</center>''')
    keyTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入你的OpenAI API-key...",
                        value=my_api_key, label="API Key", type="password", visible=not HIDE_MY_KEY).style(container=True)
    chatbot = gr.Chatbot()  # .style(color_map=("#1D51EE", "#585A5B"))
    history = gr.State([])
    promptTemplates = gr.State({})
    TRUECOMSTANT = gr.State(True)
    FALSECONSTANT = gr.State(False)
    topic = gr.State("未命名对话历史记录")

    with gr.Row():
        with gr.Column(scale=12):
            txt = gr.Textbox(show_label=False, placeholder="在这里输入").style(
                container=False)
        with gr.Column(min_width=50, scale=1):
            submitBtn = gr.Button("🚀", variant="primary")
    with gr.Row():
        emptyBtn = gr.Button("🧹 新的对话")
        retryBtn = gr.Button("🔄 重新生成")
        delLastBtn = gr.Button("🗑️ 删除上条对话")
        reduceTokenBtn = gr.Button("♻️ 总结对话")
    statusDisplay = gr.Markdown("status: ready")
    systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...",
                                 label="System prompt", value=initial_prompt).style(container=True)
    with gr.Accordion(label="加载Prompt模板", open=False):
        with gr.Column():
            with gr.Row():
                with gr.Column(scale=6):
                    templateFileSelectDropdown = gr.Dropdown(label="选择Prompt模板集合文件（.csv）", choices=get_template_names(plain=True), multiselect=False)
                with gr.Column(scale=1):
                    templateRefreshBtn = gr.Button("🔄 刷新")
                    templaeFileReadBtn = gr.Button("📂 读入模板")
            with gr.Row():
                with gr.Column(scale=6):
                    templateSelectDropdown = gr.Dropdown(label="从Prompt模板中加载", choices=load_template(get_template_names(plain=True)[0], plain=True), multiselect=False)
                with gr.Column(scale=1):
                    templateApplyBtn = gr.Button("⬇️ 应用")
    with gr.Accordion(label="保存/加载对话历史记录(在文本框中输入文件名，点击“保存对话”按钮，历史记录文件会被存储到Python文件旁边)", open=False):
        with gr.Column():
            with gr.Row():
                with gr.Column(scale=6):
                    saveFileName = gr.Textbox(
                        show_label=True, placeholder=f"在这里输入保存的文件名...", label="设置保存文件名", value="对话历史记录").style(container=True)
                with gr.Column(scale=1):
                    saveBtn = gr.Button("💾 保存对话")
            with gr.Row():
                with gr.Column(scale=6):
                    historyFileSelectDropdown = gr.Dropdown(label="从列表中加载对话", choices=get_history_names(plain=True), multiselect=False)
                with gr.Column(scale=1):
                    historyRefreshBtn = gr.Button("🔄 刷新")
                    historyReadBtn = gr.Button("📂 读入对话")
    #inputs, top_p, temperature, top_k, repetition_penalty
    with gr.Accordion("参数", open=False):
        top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.05,
                          interactive=True, label="Top-p (nucleus sampling)",)
        temperature = gr.Slider(minimum=-0, maximum=5.0, value=1.0,
                                step=0.1, interactive=True, label="Temperature",)
        #top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",)
        #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
    gr.Markdown(description)


    txt.submit(predict, [txt, top_p, temperature, keyTxt,
               chatbot, history, systemPromptTxt], [chatbot, history, statusDisplay])
    txt.submit(reset_textbox, [], [txt])
    submitBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot,
                    history, systemPromptTxt], [chatbot, history, statusDisplay], show_progress=True)
    submitBtn.click(reset_textbox, [], [txt])
    emptyBtn.click(reset_state, outputs=[chatbot, history])
    retryBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot, history,
                   systemPromptTxt, TRUECOMSTANT], [chatbot, history, statusDisplay], show_progress=True)
    delLastBtn.click(delete_last_conversation, [chatbot, history], [
                     chatbot, history], show_progress=True)
    reduceTokenBtn.click(predict, [txt, top_p, temperature, keyTxt, chatbot, history,
                         systemPromptTxt, FALSECONSTANT, TRUECOMSTANT], [chatbot, history, statusDisplay], show_progress=True)
    saveBtn.click(save_chat_history, [
                  saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
    saveBtn.click(get_history_names, None, [historyFileSelectDropdown])
    historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
    historyReadBtn.click(load_chat_history, [historyFileSelectDropdown],  [saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
    templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown])
    templaeFileReadBtn.click(load_template, [templateFileSelectDropdown],  [promptTemplates, templateSelectDropdown], show_progress=True)
    templateApplyBtn.click(lambda x, y: x[y], [promptTemplates, templateSelectDropdown],  [systemPromptTxt], show_progress=True)

print("川虎的温馨提示：访问 http://localhost:7860 查看界面")
# 默认开启本地服务器，默认可以直接从IP访问，默认不创建公开分享链接
demo.title = "川虎ChatGPT 🚀"

#if running in Docker
if dockerflag:
    if authflag:
        demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=(username, password))
    else:
        demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False)
#if not running in Docker
else:
    demo.queue().launch(share=False) # 改为 share=True 可以创建公开分享链接
    #demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False) # 可自定义端口
    #demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=("在这里填写用户名", "在这里填写密码")) # 可设置用户名与密码
    #demo.queue().launch(auth=("在这里填写用户名", "在这里填写密码")) # 适合Nginx反向代理