‘增加模拟测评加载功能’

app.py

@@ -20,6 +20,15 @@ webui_title = "📚📚📚📚📚📚📚📚📚📚📚📚* * * * * * * * *
 llm_name_dict = {'chatgpt-3.5': 'OpenAI3', 'chatgpt-4': 'OpenAI4', 'chatglm—6b': 'ChatGLM'}
 
 
+def function_select(mode):
+    if mode == "测评智能摘要":
+        return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+    elif mode == "生成模拟测评":
+        return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
+    else:
+        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
+
+
 def llm_change(name):
     llm = eval(eval('llm_name_dict[name]'))()
     return llm
@@ -27,8 +36,10 @@ def llm_change(name):
 
 def generate_comment_post_process(_summary):
     _summary = _summary.split('如下：')[-1]
+    _summary = _summary.split('follows:')[-1]
     while _summary[0] == '\n':
         _summary = _summary[1:]
+    _summary = _summary.split('\n\n')[0]
     return _summary
 
 
@@ -36,18 +47,25 @@ def show_config():
     return gr.update(visible=True)
 
 
+def load_comments(comments_file_path):
+    file_path = comments_file_path.name
+    _comments = load_scores_and_comments(file_path)
+
+    return _comments, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True), 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 hide_stand_file():
+    return gr.update(visible=False)
 
 
-def clear_screen(chatbot):
-    chatbot = [[None, None]]
-    return chatbot
+def clear_screen(_chatbot):
+    _chatbot = [[None, None]]
+    return _chatbot
 
 
 def generate_mock_data(_topic, _stand_file_path, _rewrite_prompt, _generate_num, _chatbot):
@@ -103,11 +121,14 @@ 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)
+    fun_mode = gr.Radio(["测评智能摘要", "生成模拟测评", "系统配置"], value="系统配置",
+                        label="请先选择功能模式")
+    # show_config_button = gr.Button('标准评价和prompt配置', visible=True)
+    do_summary = gr.Row(visible=False)
+    config = gr.Column(visible=True)
+    mock = gr.Row(visible=False)
+    # show_config_button.click(show_config, outputs=[config])
+    fun_mode.change(fn=function_select, inputs=[fun_mode], outputs=[do_summary, mock, config])
 
     with config:
         # llm = gr.State('')
@@ -116,6 +137,7 @@ with gr.Blocks(css=block_css) as demo:
         # 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)
+        show_stand_button = gr.Button('使用模拟测评/中位值改写功能,务必先加载标准评价', visible=True)
         r_prompt = """The content within the angle brackets is an evaluation of the instructional design regarding the {topic} knowledge point. However, the evaluation does not incorporate the {topic} theme. Please modify the evaluation by incorporating the {topic} theme in each sentence while maintaining the same evaluative perspective and positive/negative nature. The modified evaluation should appear to be specifically targeted towards the {topic} theme.
         <{stand_comment}>
         """
@@ -125,18 +147,19 @@ with gr.Blocks(css=block_css) as demo:
         '<{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])
+        set_config_button = gr.Button('确定', visible=True)
+        # 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/查看标准评价', visible=True)
+        set_config_button.click(hide_stand_file, outputs=[stand_comment])
         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')
+                mock_topic = gr.Textbox('升华和凝华', label='请输入讲课主题')
 
                 # data_out_path = gr.Textbox('', label='请��入模拟数据导出路径')
                 generate_num = gr.Slider(1, 20, value=3, step=1, label="评课人数量", interactive=True)
@@ -144,7 +167,7 @@ with gr.Blocks(css=block_css) as demo:
 
                 with gr.Row():
                     with gr.Column(scale=2):
-                        generate_button = gr.Button('生成模拟测评')
+                        generate_button = gr.Button('生成模拟测评(需先加载系统配置文件)')
                     with gr.Column(scale=2):
                         clear_screen_button = gr.Button('清屏', visible=True)
                     with gr.Column(scale=2):
@@ -157,14 +180,45 @@ with gr.Blocks(css=block_css) as demo:
                 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,
+                generate_button.click(generate_mock_data, inputs=[mock_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],
+                rewrite_button.click(rewrite, inputs=[stand_comment, r_prompt, mock_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)
 
+    with do_summary:
+        with gr.Column(scale=10):
+            file = gr.File(label='请先上传待摘要文件')
+            rewrite_topic = gr.Textbox('升华和凝华', label='如采用中位值改写的方法，请输先入讲课主题', visible=False)
+
+            comments = gr.Json(visible=False)
+
+            with gr.Row():
+                with gr.Column(scale=2):
+                    summary_button = gr.Button('四分位摘要', visible=False)
+                with gr.Column(scale=2):
+                    rewrite_button = gr.Button('中位值改写(需先加载系统配置文件)', visible=False)
+
+                with gr.Column(scale=2):
+                    clear_screen_button = gr.Button('清屏', visible=False)
+
+                file.upload(load_comments, inputs=[file],
+                            outputs=[comments, summary_button, rewrite_button, clear_screen_button, rewrite_topic])
+
+        with gr.Column(scale=10):
+
+            chatbot = gr.Chatbot([[None, None]],
+                                 elem_id="chat-box",
+                                 show_label=False).style(height=1000)
+
+            rewrite_button.click(rewrite, inputs=[stand_comment, r_prompt, rewrite_topic, comments, chatbot],
+                                 outputs=chatbot)
+            summary_button.click(summary, inputs=[s_prompt, comments, 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)
 

main.py

@@ -1,16 +0,0 @@
-# This is a sample Python script.
-
-# Press Shift+F10 to execute it or replace it with your code.
-# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
-
-
-def print_hi(name):
-    # Use a breakpoint in the code line below to debug your script.
-    print(f'Hi, {name}')  # Press Ctrl+F8 to toggle the breakpoint.
-
-
-# Press the green button in the gutter to run the script.
-if __name__ == '__main__':
-    print_hi('PyCharm')
-
-# See PyCharm help at https://www.jetbrains.com/help/pycharm/

mock_data.py

@@ -0,0 +1,118 @@
+import random
+import math
+import pandas as pd
+import gradio as gr
+import numpy as np
+from typing import List
+from llm import OpenAI3
+
+
+llm = OpenAI3()
+
+
+def _scores_recalculate(scores: List):
+    scores_array = np.array(scores)
+    scores_dis = abs(scores_array - scores_array.mean())
+    scores_count = np.ceil(1 / (scores_dis + scores_dis.mean()) * len(scores)).astype(int)
+    new_scores = []
+    for i in range(len(scores)):
+        new_scores.extend([scores[i]] * scores_count[i])
+    return new_scores
+
+
+def generate_scores_and_comments(standard_file_path, rewrite_prompt, topic, num=10):
+    df = pd.read_excel(standard_file_path)
+    pd.set_option('display.max_colwidth', None)
+    standard_index = df.columns.to_list()
+    standard_index.pop(standard_index.index('得分'))
+    standard_scores = list(tuple(df['得分'].to_list()))
+    scores_choice = _scores_recalculate(standard_scores)
+    assessments = []
+    for i in range(num):
+        assessment = dict()
+        scores = dict()
+        stand_comment = []
+        for index in standard_index:
+            score = random.choice(scores_choice)
+            scores[index] = score
+            content = df[df['得分'] == score][index].to_string(index=False)
+            stand_comment.append(content)
+        mean_score = np.array(list(scores.values()))
+        # scores['mean_score'] = mean_score
+
+        assessment['scores'] = scores
+        stand_comment = '；'.join(stand_comment)
+        prompt = 'f"""' + rewrite_prompt + '"""'
+        r_comment = llm(eval(prompt))
+        r_comment = r_comment.split('\n')[-1]
+        assessment['comment'] = r_comment
+        assessments.append(assessment)
+    return assessments, df
+
+
+def load_scores_and_comments(comments_file_path):
+    df = pd.read_excel(comments_file_path)
+    pd.set_option('display.max_colwidth', None)
+    comments = df['comments'].to_list()
+    df.pop('comments')
+    scores = df.to_dict(orient='records')
+    assessments = [{'scores': scores[i], 'comment': comments[i]} for i in range(len(comments))]
+    return assessments
+
+
+def medium_score_rewrite(standard_file, rewrite_prompt, topic, assessments):
+    scores = [i['scores'] for i in assessments]
+    scores = pd.DataFrame(scores)
+    try:
+        medium = scores.quantile(0.5)
+    except Exception as e:  # incase that the values in one column are all None
+        scores = scores.fillna(0)
+        medium = scores.quantile(0.5)
+    medium = medium.astype(int)
+
+    stand_comment = []
+    df = standard_file
+    for index in medium.index:
+        score = math.ceil(medium[index])
+        content = df[df['得分'] == score][index].to_string(index=False)
+        stand_comment.append(content)
+
+    s_comment = ';'.join(stand_comment)
+    prompt = 'f"""' + rewrite_prompt + '"""'
+    r_comment = llm(eval(prompt))
+    return r_comment
+
+
+def quantile_summary(summary_prompt, assessments):
+    if not isinstance(assessments[0], dict):
+        comment = '\n'.join(assessments)
+    else:
+        comments = [i['comment'] for i in assessments]
+        comments = pd.Series(comments)
+        scores = [i['scores'] for i in assessments]
+        scores = pd.DataFrame(scores)
+
+        try:
+            quartiles = scores.quantile([0.25, 0.75])
+        except Exception as e:  # incase that the values in one column are all None
+            scores = scores.fillna(0)
+            quartiles = scores.quantile([0.25, 0.75])
+        quartiles = quartiles.astype(int)
+        up = (scores - quartiles.loc[0.75]) < 0
+        down = (scores - quartiles.loc[0.25]) > 0
+        select_index = (up & down).all(axis=1)
+        if not select_index.any():
+            select_index = (up & down).any(axis=1)
+
+        if select_index.any():
+            select_comments = comments[select_index].to_list()
+        else:
+            select_comments = comments.to_list()
+
+        comment = '\n'.join(select_comments)
+
+    prompt = 'f"""' + summary_prompt + '"""'
+    s_comment = llm(eval(prompt))
+    return s_comment
+
+