Update "Generate multiple Mermaid charts" plugin (#1503)
* Update crazy_functional.py with new functionality deal with PDF * Update crazy_functional.py and Mermaid.py for plugin_kwargs
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@ -70,12 +70,14 @@ def get_crazy_functions():
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"Info": "清除所有缓存文件,谨慎操作 | 不需要输入参数",
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"Function": HotReload(清除缓存),
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},
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"生成多种Mermaid图表(从当前对话内容中生产多种图表)": {
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"生成多种Mermaid图表(从当前对话或文件(.pdf)中生产图表)": {
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"Group": "对话",
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"Color": "stop",
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"AsButton": False,
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"Info" : "基于当前对话或PDF生成多种Mermaid图表,图表类型由模型判断",
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"Function": HotReload(生成多种Mermaid图表),
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"AdvancedArgs": True,
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"ArgsReminder": "请输入图类型对应的数字:1-流程图,2-序列图,3-类图,4-饼图,5-甘特图,6-状态图,7-实体关系图,8-象限提示图",
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},
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"批量总结Word文档": {
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"Group": "学术",
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@ -1,4 +1,4 @@
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from toolbox import CatchException, update_ui
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from toolbox import CatchException, update_ui, report_exception
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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from .crazy_utils import read_and_clean_pdf_text
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import datetime
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@ -136,7 +136,7 @@ graph LR
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```
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"""
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def 解析历史输入(history,llm_kwargs,chatbot):
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def 解析历史输入(history,llm_kwargs,chatbot,plugin_kwargs):
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############################## <第 0 步,切割输入> ##################################
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# 借用PDF切割中的函数对文本进行切割
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TOKEN_LIMIT_PER_FRAGMENT = 2500
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@ -163,22 +163,25 @@ def 解析历史输入(history,llm_kwargs,chatbot):
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results.append(gpt_say)
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last_iteration_result = gpt_say
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############################## <第 2 步,根据整理的摘要选择图表类型> ##################################
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i_say_show_user = f'接下来将判断适合的图表类型,如连续3次判断失败将会使用流程图进行绘制'; gpt_say = "[Local Message] 收到。" # 用户提示
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chatbot.append([i_say_show_user, gpt_say]); yield from update_ui(chatbot=chatbot, history=[]) # 更新UI
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results_txt = '\n'.join(results)
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i_say = SELECT_PROMPT.format(subject=results_txt)
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i_say_show_user = f'请判断适合使用的流程图类型,其中数字对应关系为:1-流程图,2-序列图,3-类图,4-饼图,5-甘特图,6-状态图,7-实体关系图,8-象限提示图'
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for i in range(3):
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say,
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inputs_show_user=i_say_show_user,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt=""
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)
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if gpt_say in ['1','2','3','4','5','6','7','8']: #判断返回是否正确
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break
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if gpt_say not in ['1','2','3','4','5','6','7','8']:
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gpt_say = '1'
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if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
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gpt_say = plugin_kwargs.get("advanced_arg", "") #将图表类型参数赋值为插件参数
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results_txt = '\n'.join(results) #合并摘要
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if gpt_say not in ['1','2','3','4','5','6','7','8']: #如插件参数不正确则使用对话模型判断
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i_say_show_user = f'接下来将判断适合的图表类型,如连续3次判断失败将会使用流程图进行绘制'; gpt_say = "[Local Message] 收到。" # 用户提示
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chatbot.append([i_say_show_user, gpt_say]); yield from update_ui(chatbot=chatbot, history=[]) # 更新UI
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i_say = SELECT_PROMPT.format(subject=results_txt)
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i_say_show_user = f'请判断适合使用的流程图类型,其中数字对应关系为:1-流程图,2-序列图,3-类图,4-饼图,5-甘特图,6-状态图,7-实体关系图,8-象限提示图'
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for i in range(3):
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say,
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inputs_show_user=i_say_show_user,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt=""
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)
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if gpt_say in ['1','2','3','4','5','6','7','8']: #判断返回是否正确
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break
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if gpt_say not in ['1','2','3','4','5','6','7','8']:
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gpt_say = '1'
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############################## <第 3 步,根据选择的图表类型绘制图表> ##################################
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if gpt_say == '1':
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i_say = PROMPT_1.format(subject=results_txt)
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@ -193,7 +196,7 @@ def 解析历史输入(history,llm_kwargs,chatbot):
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elif gpt_say == '6':
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i_say = PROMPT_6.format(subject=results_txt)
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elif gpt_say == '7':
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i_say = PROMPT_7.format(subject=results_txt)
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i_say = PROMPT_7.replace("{subject}", results_txt) #由于实体关系图用到了{}符号
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elif gpt_say == '8':
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i_say = PROMPT_8.format(subject=results_txt)
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i_say_show_user = f'请根据判断结果绘制相应的图表。'
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@ -233,11 +236,28 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,
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web_port 当前软件运行的端口号
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"""
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import os
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# 基本信息:功能、贡献者
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chatbot.append([
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"函数插件功能?",
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"根据当前聊天历史或PDF中绘制多种mermaid图表的功能,将会首先判断适合的图表类型,随后绘制图表。函数插件贡献者: Menghuan1918"])
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"根据当前聊天历史或PDF中(文件内容优先)绘制多种mermaid图表,将会由对话模型首先判断适合的图表类型,随后绘制图表。\
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\n您也可以使用插件参数指定绘制的图表类型,函数插件贡献者: Menghuan1918"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# 尝试导入依赖,如果缺少依赖,则给出安装建议
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try:
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import fitz
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except:
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report_exception(chatbot, history,
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a = f"解析项目: {txt}",
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b = f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade pymupdf```。")
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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if os.path.exists(txt): #如输入区无内容则直接解析历史记录
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file_exist, txt = 输入区文件处理(txt)
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if file_exist : history = [] #如输入区内容为文件则清空历史记录
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history.append(txt) #将解析后的txt传递加入到历史中
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yield from 解析历史输入(history,llm_kwargs,chatbot)
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yield from 解析历史输入(history,llm_kwargs,chatbot,plugin_kwargs)
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