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import json
import gradio as gr
import pandas as pd
from llm import OpenAI3, OpenAI4
from mock_data import *
block_css = """
.importantButton {
background: linear-gradient(45deg, #7e0570,#5d1c99, #6e00ff) !important;
border: none !important;
}
.importantButton:hover {
background: linear-gradient(45deg, #ff00e0,#8500ff, #6e00ff) !important;
border: none !important;
}"""
webui_title = "📚📚📚📚📚📚📚📚📚📚📚📚* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * ☘️ * * *学思案* * * ☘️ * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *📚📚📚📚📚📚📚📚📚📚📚📚"
llm_name_dict = {'chatgpt-3.5': 'OpenAI3', 'chatgpt-4': 'OpenAI4', 'chatglm—6b': 'ChatGLM'}
def llm_change(name):
llm = eval(eval('llm_name_dict[name]'))()
return llm
def generate_comment_post_process(_summary):
_summary = _summary.split('如下:')[-1]
while _summary[0] == '\n':
_summary = _summary[1:]
return _summary
def show_config():
return gr.update(visible=True)
def show_stand_file(stand_file_path, stand_file):
df = pd.read_excel(stand_file_path)
return gr.update(visible=True, value=df)
def hide_config():
return gr.update(visible=False), gr.update(visible=False)
def clear_screen(chatbot):
chatbot = [[None, None]]
return chatbot
def generate_mock_data(_topic, _stand_file_path, _rewrite_prompt, _generate_num, _chatbot):
try:
scores_and_comments, stand_file = \
generate_scores_and_comments(_stand_file_path, _rewrite_prompt, _topic, _generate_num)
chat = ''
for i in range(len(scores_and_comments)):
chat = chat + 'Teacher' + str(i+1) + ':\n\n'
for key, value in scores_and_comments[i]['scores'].items():
chat = chat + key + ': ' + str(value) + ' - - '
chat = chat[:-5] + '\n\n'
chat = chat + scores_and_comments[i]['comment'] + '\n\n'
_chatbot = _chatbot + [[None, chat]]
return _chatbot, scores_and_comments, stand_file, gr.update(visible=True), gr.update(visible=True)
except Exception as e:
_chatbot = _chatbot + [[None, e]]
return _chatbot, gr.Json(visible=False), gr.DataFrame(visible=False), gr.update(visible=False), \
gr.update(visible=False)
def rewrite(standard_file, rewrite_prompt, topic, assessments, chatbot):
try:
rewrite_comment = medium_score_rewrite(standard_file, rewrite_prompt, topic, assessments)
rewrite_comment = generate_comment_post_process(rewrite_comment)
message = '上述评价按照中位法则改写结果如下:\n\n' + rewrite_comment
except Exception as e:
message = e
chatbot = chatbot + [[None, message]]
return chatbot
def summary(summary_prompt, assessments, chatbot):
try:
summary_comment = quantile_summary(summary_prompt, assessments)
summary_comment = generate_comment_post_process(summary_comment)
message = '上述评价按照四分位法则改写结果如下:\n\n' + summary_comment
except Exception as e:
message = e
chatbot = chatbot + [[None, message]]
return chatbot
with gr.Blocks(css=block_css) as demo:
gr.Markdown('\n\n\n\n')
gr.Markdown(webui_title)
gr.Markdown('\n\n\n\n')
show_config_button = gr.Button('标准评价和prompt配置', visible=True)
config = gr.Column(visible=False)
show_config_button.click(show_config, outputs=[config])
mock = gr.Column(visible=True)
with config:
# llm = gr.State('')
# model_mode = gr.Radio(['chatgpt-3.5', "chatgpt-4", 'chatglm—6b'], label="请选择驱动模型")
# model_name = gr.Radio(['chatgpt-3.5'], label="请选择驱动模型")
# model_name.change(fn=llm_change, inputs=[model_name], outputs=[llm])
stand_file_path = gr.Textbox('指标评价标准.xlsx', label='请输入评价标准文件路径')
stand_comment = gr.DataFrame(visible=False)
r_prompt = """尖括号里面的内容是对关于{topic}知识点教学设计的评价,但是该评价语言没有结合{topic}这个主题,请结合{topic}这个主题对该评价进行修改,修改后每句话都要体现{topic}这个主题且保持评价角度及正负性不变,但是从文字上看更像是专门针对{topic}这个主题做的评价。
<{stand_comment}>
"""
r_prompt = gr.Text(value=r_prompt, label='请配置改写prompt', lines=3)
s_prompt = """尖括号里面的内容是多位老师对某堂课的教学评价,每位老师的评价用换行符进行了分隔,请对各位老师的评价进行摘要总结
'<{comment}>'
"""
s_prompt = gr.Text(value=s_prompt, label='请配置摘要prompt', lines=3)
with gr.Row():
with gr.Column(scale=2):
set_config_button = gr.Button('确定', visible=True)
with gr.Column(scale=2):
show_stand_button = gr.Button('加载/更新标准评价', visible=True)
set_config_button.click(hide_config, outputs=[stand_comment, config])
show_stand_button.click(show_stand_file, inputs=[stand_file_path, stand_comment], outputs=stand_comment)
with mock:
with gr.Row():
with gr.Column(scale=10):
topic = gr.Textbox('升华和凝华', label='请输入讲课主题')
# data_out_path = gr.Textbox('', label='请输入模拟数据导出路径')
generate_num = gr.Slider(1, 10, value=2, step=1, label="评课人数量", interactive=True)
mock_data = gr.Json(visible=False)
with gr.Row():
with gr.Column(scale=2):
generate_button = gr.Button('生成模拟测评')
with gr.Column(scale=2):
clear_screen_button = gr.Button('清屏', visible=True)
with gr.Column(scale=2):
rewrite_button = gr.Button('中位值改写', visible=False)
with gr.Column(scale=2):
summary_button = gr.Button('四分位摘要', visible=False)
with gr.Column(scale=10):
chatbot = gr.Chatbot([[None, None]],
elem_id="chat-box",
show_label=False).style(height=1000)
generate_button.click(generate_mock_data, inputs=[topic, stand_file_path, r_prompt, generate_num,
chatbot], outputs=[chatbot, mock_data, stand_comment, rewrite_button, summary_button])
rewrite_button.click(rewrite, inputs=[stand_comment, r_prompt, topic, mock_data, chatbot],
outputs=chatbot)
summary_button.click(summary, inputs=[s_prompt, mock_data, chatbot],
outputs=chatbot)
clear_screen_button.click(clear_screen, inputs=[chatbot], outputs=chatbot)
# demo.queue(concurrency_count=5).launch(server_name='0.0.0.0', server_port=7858, share=True)
demo.queue(concurrency_count=5).launch()
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