CSPON-TSC/aiAgent_gd/qwen_server/app.py

import datetime
import importlib
import json
import os
import random
import shutil
import sys
from pathlib import Path

import gradio as gr
import jsonlines

import config_browserqwen

sys.path.insert(
    0,
    str(Path(__file__).absolute().parent.parent))  # NOQA

from qwen_agent.tools.tools import tools_list, call_plugin  # NOQA
from qwen_agent.utils.util import get_last_one_line_context, save_text_to_file, count_tokens, get_html_content, format_answer  # NOQA
from qwen_agent.actions import ContinueWriting, Simple, WriteFromZero, ReAct  # NOQA
from qwen_agent.memory import Memory  # NOQA
from qwen_agent.actions.func_call import func_call  # NOQA

prompt_lan = sys.argv[1]
llm_name = sys.argv[2]
max_ref_token = int(sys.argv[3])
workstation_port = int(sys.argv[4])
model_server = sys.argv[5]
api_key = sys.argv[6]
server_host = sys.argv[7]

print(sys.argv)

if model_server.startswith('http'):
    source = 'local'
elif model_server.startswith('dashscope'):
    source = 'dashscope'

if llm_name.startswith('gpt'):
    module = 'qwen_agent.llm.gpt'
    llm = importlib.import_module(module).GPT(llm_name)
elif llm_name.startswith('Qwen') or llm_name.startswith('qwen'):
    module = 'qwen_agent.llm.qwen'
    llm = importlib.import_module(module).Qwen(llm_name, model_server=model_server, api_key=api_key)
else:
    raise NotImplementedError

mem = Memory(config_browserqwen.similarity_search, config_browserqwen.similarity_search_type)

app_global_para = {
    'time': [str(datetime.date.today()), str(datetime.date.today())],
    'cache_file': os.path.join(config_browserqwen.cache_root, config_browserqwen.browser_cache_file),
    'use_ci_flag': False,
    'use_bidding_flag': True,
    'messages': [],
    'last_turn_msg_id': [],
    'is_first_upload': True
}

with open(Path(__file__).resolve().parent / 'css/main.css', 'r') as f:
    css = f.read()
with open(Path(__file__).resolve().parent / 'js/main.js', 'r') as f:
    js = f.read()


def add_text(history, text):
    history = history + [(text, None)]
    app_global_para['last_turn_msg_id'] = []
    return history, gr.update(value='', interactive=False)


def rm_text(history):
    if not history:
        gr.Warning('No input content!')
    elif not history[-1][1]:
        return history, gr.update(value='', interactive=False)
    else:
        history = history[:-1] + [(history[-1][0], None)]
        return history, gr.update(value='', interactive=False)


def chat_clear():
    app_global_para['messages'] = []
    return None, None, None


def chat_clear_last():
    # print(app_global_para['last_turn_msg_id'][::-1])
    # print(app_global_para['messages'])
    for index in app_global_para['last_turn_msg_id'][::-1]:
        del app_global_para['messages'][index]
    app_global_para['last_turn_msg_id'] = []


def add_file(file):
    output_filepath = config_browserqwen.code_interpreter_ws
    fn = os.path.basename(file.name)
    new_path = os.path.join(output_filepath, fn)
    if os.path.exists(new_path):
        os.remove(new_path)
    shutil.move(file.name, output_filepath)
    path_show = '<p></p><p>File</p>'  # NOQA
    app_global_para['is_first_upload'] = True
    return path_show, new_path


def check_file():
    if not app_global_para['use_ci_flag']:
        gr.Warning('Select the Code Interpreter to analyze the file!')


def read_records(file, times=None):
    lines = []
    if times:
        for line in jsonlines.open(file):
            if times[0] <= line['time'] <= times[1]:
                lines.append(line)
    return lines


def update_rec_list(flag):
    rec_list = []
    if not os.path.exists(app_global_para['cache_file']):
        return 'No browsing records'
    lines = []
    for line in jsonlines.open(app_global_para['cache_file']):
        if (app_global_para['time'][0] <= line['time'] <= app_global_para['time'][1]) and line['checked']:
            if flag == 'load' and line['topic']:
                rec_list.append(line['topic'])
            else:
                agent = Simple(llm=llm, stream=False)
                page_number = len(line['raw'])
                index = random.randint(0, page_number-1)
                if prompt_lan == 'CN':
                    topicprompt = '请提出一个有新意的吸引人的话题'
                elif prompt_lan == 'EN':
                    topicprompt = 'Please propose a new and attractive topic'
                rec = agent.run(line['raw'][index]['page_content'], topicprompt, prompt_lan=prompt_lan)
                assert isinstance(rec, str)
                rec_list.append(rec)
                line['topic'] = rec

        lines.append(line)
    if lines:
        # update cache file
        with jsonlines.open(app_global_para['cache_file'], mode='w') as writer:
            for new_line in lines:
                writer.write(new_line)

    res = '<ol>{rec}</ol>'
    rec = ''
    for x in rec_list:
        rec += '<li>{rec_topic}</li>'.format(rec_topic=x)
    res = res.format(rec=rec)
    return res


def update_app_global_para(date1, date2):
    app_global_para['time'][0] = date1
    app_global_para['time'][1] = date2
    app_global_para['use_ci_flag'] = False
    app_global_para['use_bidding_flag'] = True


def update_browser_list():
    if not os.path.exists(app_global_para['cache_file']):
        return 'No browsing records'
    lines = read_records(app_global_para['cache_file'], times=app_global_para['time'])

    br_list = [[line['url'], line['extract'], line['checked']] for line in lines]
    print('browser_list: ', len(br_list))
    res = '<ol>{bl}</ol>'
    bl = ''
    for i, x in enumerate(br_list):
        ck = '<input type="checkbox" class="custom-checkbox" id="ck-'+x[0]+'" '
        if x[2]:
            ck += 'checked>'
        else:
            ck += '>'
        bl += '<li>{checkbox}{title}<a href="{url}"> [url]</a></li>'.format(checkbox=ck, url=x[0], title=x[1])
    res = res.format(bl=bl)
    return res


def update_all(date1, date2):
    update_app_global_para(date1, date2)
    return update_browser_list(), update_rec_list('update')


def layout_to_right(text):
    return text, text


def download_text(text):
    now = datetime.datetime.now()
    current_time = now.strftime('%Y-%m-%d_%H-%M-%S')
    filename = f'file_{current_time}.md'
    rsp = save_text_to_file(os.path.join(config_browserqwen.download_root, filename), text)
    if rsp == 'SUCCESS':
        raise gr.Info('Saved')
    else:
        raise gr.Error("Can't Save: ", rsp)


def count_token(text):
    return count_tokens(text)


def change_use_ci_flag():
    if app_global_para['use_ci_flag']:
        app_global_para['use_ci_flag'] = False
    else:
        app_global_para['use_ci_flag'] = True


def change_use_bidding_flag():
    if app_global_para['use_bidding_flag']:
        app_global_para['use_bidding_flag'] = False
    else:
        app_global_para['use_bidding_flag'] = True


def add_url_manu(url, date):
    text = get_html_content(url)
    msg = {'content': text, 'query': '', 'url': url, 'task': 'cache', 'type': 'html'}

    from main import cache_data  # NOQA
    cache_data(msg, app_global_para['cache_file'])


def bot(history, upload_file):
    if not history:
        yield history
    else:
        history[-1][1] = ''
        if app_global_para['use_ci_flag']:  # use code interpreter
            prompt_upload_file = ''
            if upload_file and app_global_para['is_first_upload']:
                workspace_dir = config_browserqwen.code_interpreter_ws
                file_relpath = os.path.relpath(path=upload_file, start=workspace_dir)
                if prompt_lan == 'EN':
                    prompt_upload_file = f'[Upload file {file_relpath}]'
                elif prompt_lan == 'CN':
                    prompt_upload_file = f'上传了[文件]({file_relpath})到当前目录，'
                app_global_para['is_first_upload'] = False
            history[-1][0] = prompt_upload_file+history[-1][0]
            if source == 'local':  # using func call interface
                message = {
                    'role': 'user', 'content': history[-1][0]
                }
                app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
                app_global_para['messages'].append(message)
                while True:
                    print(app_global_para['messages'])
                    functions = [x for x in tools_list if x['name_for_model'] == 'code_interpreter']
                    rsp = llm.qwen_chat_func(app_global_para['messages'], functions)
                    if rsp['function_call']:
                        history[-1][1] += rsp['content'].strip() + '\n'
                        yield history
                        history[-1][1] += 'Action: '+rsp['function_call']['name'].strip() + '\n'
                        yield history
                        history[-1][1] += 'Action Input:\n'+rsp['function_call']['arguments'] + '\n'
                        yield history
                        bot_msg = {
                            'role': 'assistant',
                            'content': rsp['content'],
                            'function_call': {
                                'name': rsp['function_call']['name'],
                                'arguments': rsp['function_call']['arguments'],
                            }
                        }
                        app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
                        app_global_para['messages'].append(bot_msg)

                        obs = call_plugin(rsp['function_call']['name'], rsp['function_call']['arguments'])
                        func_msg = {
                            'role': 'function',
                            'name': rsp['function_call']['name'],
                            'content': obs,
                        }
                        history[-1][1] += ('Observation: ' + obs + '\n')
                        yield history
                        app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
                        app_global_para['messages'].append(func_msg)
                    else:
                        bot_msg = {
                            'role': 'assistant',
                            'content': rsp['content'],
                        }
                        history[-1][1] += rsp['content']
                        yield history
                        app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
                        app_global_para['messages'].append(bot_msg)
                        break
            elif source == 'dashscope':  # using dashscope interface:
                print(app_global_para['messages'])
                functions = [x for x in tools_list if x['name_for_model'] == 'code_interpreter']
                agent = ReAct(llm=llm, list_of_plugin_info=functions)
                response = agent.run(history[-1][0], messages=app_global_para['messages'])
                if 'Action' not in response:
                    response = response.split('Final Answer:')[-1]
                history[-1][1] = response
                yield history

                message = {
                    'role': 'user', 'content': history[-1][0]
                }
                app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
                app_global_para['messages'].append(message)
                rsp_message = {
                    'role': 'assistant', 'content': history[-1][1]
                }
                app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
                app_global_para['messages'].append(rsp_message)

        elif app_global_para['use_bidding_flag']:
            sp_query = history[-1][0]
            print('history_message:', app_global_para['messages'])
            # if config_browserqwen.ifbunit_flag in sp_query:  # router to code interpreter
            # if True:
            from qwen_agent.planning.plan_dispatcher import PlanDispatcher
            import copy
            # from qwen_agent.messages.base import UserResponseStream
            # sp_query = sp_query.split(config_browserqwen.ifbunit_flag)[-1]
            agent = PlanDispatcher(llm=llm, stream=False, enable_critic=True)
            response = agent.run(sp_query, messages=app_global_para['messages'])
            details_info = copy.deepcopy(history)
            thought = ''
            summary = ''
            for res in response:
                # yield f'######## {res.type}: {res.content}\n'
                if res.type == 'thought':
                    thought += res.content
                elif res.type == 'summary':
                    summary += res.content
                details_info[-1][1] += f"{res.type.upper()}: {res.content}\n"
                yield details_info
            if thought:
                history[-1][1] += f'Final Thought: {thought}\n'
            if summary:
                history[-1][1] += f'Final Summary: {summary}\n'
                # yield history
            print(f'Fineshed Query:{sp_query}')
            message = {
                'role': 'user', 'content': history[-1][0]
            }
            app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
            app_global_para['messages'].append(message)

            message = {
                'role': 'assistant', 'content': history[-1][1]
            }
            app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
            app_global_para['messages'].append(message)
        else:
            lines = []
            if not os.path.exists(app_global_para['cache_file']):
                _ref = ''
            else:
                for line in jsonlines.open(app_global_para['cache_file']):
                    if (app_global_para['time'][0] <= line['time'] <= app_global_para['time'][1]) and line['checked']:
                        lines.append(line)
                if lines:
                    _ref_list = mem.get(history[-1][0], lines, llm=llm, stream=True, max_token=max_ref_token)
                    _ref = '\n'.join(json.dumps(x, ensure_ascii=False) for x in _ref_list)
                else:
                    _ref = ''
                    gr.Warning('No reference materials selected, Qwen will answer directly')

            agent = Simple(llm=llm, stream=True)
            response = agent.run(_ref, history)

            for chunk in response:
                history[-1][1] += chunk
                yield history

            # append message
            message = {
                'role': 'user', 'content': history[-1][0]
            }
            app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
            app_global_para['messages'].append(message)

            message = {
                'role': 'assistant', 'content': history[-1][1]
            }
            app_global_para['last_turn_msg_id'].append(len(app_global_para['messages']))
            app_global_para['messages'].append(message)


def generate(context):
    print("context", context)
    sp_query = get_last_one_line_context(context)
    res = ''
    # if config_browserqwen.ifbunit_flag in sp_query:  # router to code interpreter
    from qwen_agent.planning.plan_dispatcher import PlanDispatcher
    sp_query = sp_query.split(config_browserqwen.ifbunit_flag)[-1]
    agent = PlanDispatcher(llm=llm, stream=False)
    response = agent.run(sp_query, messages=[])

    for chunk in response:
        res += chunk.content
        yield res
    # if config_browserqwen.code_flag in sp_query:  # router to code interpreter
    #     sp_query = sp_query.split(config_browserqwen.code_flag)[-1]
    #     sp_query += ', 必须使用code_interpreter工具'
    #     functions = [x for x in tools_list if x['name_for_model'] == 'code_interpreter']
    #     if source == 'local':  # using func call interface
    #         response = func_call(sp_query, functions, llm)
    #         for chunk in response:
    #             res += chunk
    #             yield res
    #     elif source == 'dashscope':  # using dashscope interface
    #         agent = ReAct(llm=llm, list_of_plugin_info=functions)
    #         response = agent.run(sp_query, messages=[])
    #         yield response
    # elif config_browserqwen.plugin_flag in sp_query:  # router to plugin
    #     sp_query = sp_query.split(config_browserqwen.plugin_flag)[-1]
    #     functions = tools_list
    #     if source == 'local':  # using func call interface
    #         response = func_call(sp_query, functions, llm)
    #         for chunk in response:
    #             res += chunk
    #             yield res
    #     elif source == 'dashscope':  # using dashscope interface
    #         agent = ReAct(llm=llm, list_of_plugin_info=functions)
    #         response = agent.run(sp_query, messages=[])
    #         yield response
    # else:  # router to continue writing
    #     lines = []
    #     for line in jsonlines.open(app_global_para['cache_file']):
    #         if (app_global_para['time'][0] <= line['time'] <= app_global_para['time'][1]) and line['checked']:
    #             lines.append(line)
    #     if lines:
    #         if config_browserqwen.similarity_search:
    #             res += '\n========================= \n'
    #             yield res
    #             res += '> Search for relevant information: \n'
    #             yield res
    #         sp_query_no_title = sp_query
    #         if config_browserqwen.title_flag in sp_query:  # /title
    #             sp_query_no_title = sp_query.split(config_browserqwen.title_flag)[-1]

    #         _ref_list = mem.get(sp_query_no_title, lines, llm=llm, stream=True, max_token=max_ref_token)
    #         _ref = '\n'.join(json.dumps(x, ensure_ascii=False) for x in _ref_list)
    #         res += _ref
    #         yield res
    #         res += '\n'
    #     else:
    #         _ref = ''
    #         gr.Warning('No reference materials selected, Qwen will answer directly')

    #     if config_browserqwen.title_flag in sp_query:  # /title
    #         sp_query = sp_query.split(config_browserqwen.title_flag)[-1]
    #         agent = WriteFromZero(llm=llm, stream=True, auto_agent=config_browserqwen.auto_agent)
    #     else:
    #         res += '\n========================= \n'
    #         res += '> Writing Text: \n'
    #         yield res
    #         agent = ContinueWriting(llm=llm, stream=True)

        # response = agent.run(_ref, context, prompt_lan=prompt_lan)

    # if config_browserqwen.code_flag in sp_query:  # router to code interpreter
    #     sp_query = sp_query.split(config_browserqwen.code_flag)[-1]
    #     sp_query += ', 必须使用code_interpreter工具'
    #     functions = [x for x in tools_list if x['name_for_model'] == 'code_interpreter']
    #     if source == 'local':  # using func call interface
    #         response = func_call(sp_query, functions, llm)
    #         for chunk in response:
    #             res += chunk
    #             yield res
    #     elif source == 'dashscope':  # using dashscope interface
    #         agent = ReAct(llm=llm, list_of_plugin_info=functions, source=source)
    #         response = agent.run(sp_query, messages=[])
    #         yield response
    # elif config_browserqwen.plugin_flag in sp_query:  # router to plugin
    #     sp_query = sp_query.split(config_browserqwen.plugin_flag)[-1]
    #     functions = tools_list
    #     if source == 'local':  # using func call interface
    #         response = func_call(sp_query, functions, llm)
    #         for chunk in response:
    #             res += chunk
    #             yield res
    #     elif source == 'dashscope':  # using dashscope interface
    #         agent = ReAct(llm=llm, list_of_plugin_info=functions, source=source)
    #         response = agent.run(sp_query, messages=[])
    #         yield response
    # else:  # router to continue writing
    #     lines = []
    #     for line in jsonlines.open(app_global_para['cache_file']):
    #         if (app_global_para['time'][0] <= line['time'] <= app_global_para['time'][1]) and line['checked']:
    #             lines.append(line)
    #     if lines:
    #         if config_browserqwen.similarity_search:
    #             res += '\n========================= \n'
    #             yield res
    #             res += '> Search for relevant information: \n'
    #             yield res
    #         sp_query_no_title = sp_query
    #         if config_browserqwen.title_flag in sp_query:  # /title
    #             sp_query_no_title = sp_query.split(config_browserqwen.title_flag)[-1]

    #         _ref_list = mem.get(sp_query_no_title, lines, llm=llm, stream=True, max_token=max_ref_token)
    #         _ref = '\n'.join(json.dumps(x, ensure_ascii=False) for x in _ref_list)
    #         res += _ref
    #         yield res
    #         res += '\n'
    #     else:
    #         _ref = ''
    #         gr.Warning('No reference materials selected, Qwen will answer directly')


def format_generate(edit, context):
    res = edit
    yield res
    if '> Writing Text: ' in context:
        text = context.split('> Writing Text: ')[-1].strip()
        res += '\n'
        res += text
        yield res
    elif 'Final Answer' in context:
        response = format_answer(context)
        res += '\n'
        res += response
        yield res
    else:
        res += context
        yield res

# generate('/ifbunit 浙江万维今年的中标情况')

with gr.Blocks(css=css, theme='soft') as demo:
    title = gr.Markdown('Qwen Agent: BrowserQwen', elem_classes='title')
    desc = gr.Markdown(
        'This is the editing workstation of BrowserQwen, where Qwen has collected the browsing history. Qwen can assist you in completing your creative work!',
        elem_classes='desc')

    with gr.Row():
        with gr.Column():
            rec = gr.Markdown('Browsing History', elem_classes='rec')
            with gr.Row():
                with gr.Column(scale=0.3, min_width=0):
                    date1 = gr.Dropdown([str(datetime.date.today()-datetime.timedelta(days=i)) for i in range(
                        config_browserqwen.max_days)], value=str(datetime.date.today()), label='Start Date')  # NOQA
                    date2 = gr.Dropdown([str(datetime.date.today()-datetime.timedelta(days=i)) for i in range(
                        config_browserqwen.max_days)], value=str(datetime.date.today()), label='End Date')  # NOQA
                with gr.Column(scale=0.7, min_width=0):
                    browser_list = gr.HTML(value='', label='browser_list', elem_classes=['div_tmp', 'add_scrollbar'])

    with gr.Tab('Editor', elem_id='default-tab'):
        with gr.Row():
            with gr.Column():
                with gr.Row():
                    edit_area = gr.Textbox(
                        value='',
                        elem_classes=['textbox_default', 'add_scrollbar'],
                        lines=30,
                        label='Input',
                        show_copy_button=True)
                    # token_count = gr.HTML(value='<span>0</span>',
                    #                       elem_classes=[
                    #                           'token-counter',
                    #                           'default-token-counter'
                    #                       ])

                with gr.Row():
                    ctn_bt = gr.Button('Continue', variant='primary')
                    stop_bt = gr.Button('Stop')
                    clr_bt = gr.Button('Clear')
                    dld_bt = gr.Button('Download')

                # with gr.Row():
                #     layout_bt = gr.Button('👉', variant='primary')

            with gr.Column():
                cmd_area = gr.Textbox(lines=10, max_lines=10, label="Qwen's Inner Thought", elem_id='cmd')
                with gr.Tab('Markdown'):
                    # md_out_bt = gr.Button('Render')
                    md_out_area = gr.Markdown(elem_classes=[
                                                   'md_tmp',
                                                   'add_scrollbar'
                                               ])

                with gr.Tab('HTML'):
                    html_out_area = gr.HTML()

                with gr.Tab('Raw'):
                    text_out_area = gr.Textbox(lines=20,
                                               label='',
                                               elem_classes=[
                                                   'textbox_default_output',
                                                   'add_scrollbar'
                                               ],
                                               show_copy_button=True)
        # br_input_bt.click(add_url_manu, br_input, None).then(update_browser_list, None, browser_list).then(lambda: None, None, None, _js=f'() => {{{js}}}')
        # .then(update_rec_list, gr.Textbox('update', visible=False), rec_list)
        # clk_ctn_bt = ctn_bt.click(qwen_ctn, edit_area, edit_area)
        clk_ctn_bt = ctn_bt.click(generate, edit_area, cmd_area)
        clk_ctn_bt.then(format_generate, [edit_area, cmd_area], edit_area)

        edit_area_change = edit_area.change(layout_to_right, edit_area, [text_out_area, md_out_area])
        # edit_area_change.then(count_token, edit_area, token_count)

        stop_bt.click(lambda: None, cancels=[clk_ctn_bt], queue=False)
        clr_bt.click(lambda: [None, None, None], None, [edit_area, cmd_area, md_out_area], queue=False)
        dld_bt.click(download_text, edit_area, None)

        # layout_bt.click(layout_to_right,
        #                 edit_area, [text_out_area, md_out_area],
        #                 queue=False)
        gr.Markdown('''
    ### Usage Tips:
    - Browsing History:
        - Start Date/End Date: Selecting the browsed materials for the desired time period, including the start and end dates
        - The browsed materials list: supporting the selection or removal of specific browsing content
    - Editor: In the editing area, you can directly input content or special instructions, and then click the ```Continue``` button to have Qwen assist in completing the editing work:
        - After inputting the content, directly click the ```Continue``` button: Qwen will begin to continue writing based on the browsing information
        - Using special instructions:
            - /title + content: Qwen enables the built-in planning process and writes a complete manuscript
            - /code + content: Qwen enables the code interpreter plugin, writes and runs Python code, and generates replies
            - /plug + content: Qwen enables plugin and select appropriate plugin to generate reply
    - Chat: Interactive area. Qwen generates replies based on given reference materials. Selecting Code Interpreter will enable the code interpreter plugin

        ''')

    with gr.Tab('Chat', elem_id='chat-tab'):
        with gr.Column():

            chatbot = gr.Chatbot([],
                                 elem_id='chatbot',
                                 height=680,
                                 show_copy_button=True,
                                 avatar_images=(None, (os.path.join(
                                     Path(__file__).resolve().parent, 'img/logo.png'))))
            with gr.Row():
                with gr.Column(scale=1, min_width=0):
                    file_btn = gr.UploadButton('Upload', file_types=['file'])  # NOQA
                with gr.Column(scale=3, min_width=0):
                    plug_bt = gr.Checkbox(label='Code Interpreter')
                with gr.Column(scale=3, min_width=0):
                    bidding_bt = gr.Checkbox(label='Bidding Analysis', value=True)
                with gr.Column(scale=1, min_width=0):
                    show_path_md = gr.HTML('')
                # with gr.Column(scale=0.03, min_width=0):
                #     show_path_bt = gr.Button('✖️', visible=False)  # NOQA
                with gr.Column(scale=13):
                    chat_txt = gr.Textbox(show_label=False, placeholder='Chat with Qwen...', container=False)  # NOQA
                # with gr.Column(scale=0.05, min_width=0):
                #     chat_smt_bt = gr.Button('⏎')  # NOQA
                with gr.Column(scale=1, min_width=0):
                    chat_clr_bt = gr.Button('Clear')  # NOQA

                with gr.Column(scale=1, min_width=0):
                    chat_stop_bt = gr.Button('Stop')  # NOQA
                with gr.Column(scale=1, min_width=0):
                    chat_re_bt = gr.Button('Again')  # NOQA

            hidden_file_path = gr.Textbox(visible=False)

            txt_msg = chat_txt.submit(add_text, [chatbot, chat_txt], [chatbot, chat_txt], queue=False).then(bot, [chatbot, hidden_file_path], chatbot)
            txt_msg.then(lambda: gr.update(interactive=True), None, [chat_txt], queue=False)

            # txt_msg_bt = chat_smt_bt.click(add_text, [chatbot, chat_txt], [chatbot, chat_txt], queue=False).then(bot, chatbot, chatbot)
            # txt_msg_bt.then(lambda: gr.update(interactive=True), None, [chat_txt], queue=False)
            # (None, None, None, cancels=[txt_msg], queue=False).then
            re_txt_msg = chat_re_bt.click(rm_text, [chatbot], [chatbot, chat_txt], queue=False).then(chat_clear_last, None, None).then(bot, [chatbot, hidden_file_path], chatbot)
            re_txt_msg.then(lambda: gr.update(interactive=True), None, [chat_txt], queue=False)

            file_msg = file_btn.upload(add_file, [file_btn], [show_path_md, hidden_file_path], queue=False).then(check_file, None, None)

            chat_clr_bt.click(chat_clear, None, [chatbot, hidden_file_path, show_path_md], queue=False)
            # re_bt.click(re_bot, chatbot, chatbot)
            chat_stop_bt.click(chat_clear_last, None, None, cancels=[txt_msg, re_txt_msg], queue=False)

            # show_path_bt.click(lambda x:[None, gr.update(visible=False)], hidden_file_path, [show_path_md,show_path_bt])

            plug_bt.change(change_use_ci_flag)

            bidding_bt.change(change_use_bidding_flag)

    # img_cloud = gr.Image(height='50px')
    # update_bt.click(update_rec_list, gr.Textbox('update', visible=False), rec_list, queue=False)

    # date.change(update_all, date,  [img_cloud, browser_list, rec_list], queue=False)
    date1.change(update_app_global_para, [date1, date2], None).then(update_browser_list, None, browser_list).then(lambda: None, None, None, _js=f'() => {{{js}}}').then(chat_clear, None, [chatbot, hidden_file_path, show_path_md])
    date2.change(update_app_global_para, [date1, date2], None).then(update_browser_list, None, browser_list).then(lambda: None, None, None, _js=f'() => {{{js}}}').then(chat_clear, None, [chatbot, hidden_file_path, show_path_md])

    # demo.load(update_all, date,  [img_cloud, browser_list, rec_list])
    demo.load(update_app_global_para, [date1, date2], None).then(update_browser_list, None, browser_list).then(lambda: None, None, None, _js=f'() => {{{js}}}').then(chat_clear, None, [chatbot, hidden_file_path, show_path_md])
    # .then(update_rec_list, gr.Textbox('load', visible=False), rec_list, queue=False)

demo.queue().launch(server_name=server_host, server_port=workstation_port)