Merge branch 'frontier' of github.com:binary-husky/chatgpt_academic into frontier
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binary-husky
commit
1c0764753a
@ -70,14 +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(从当前对话或文件(.pdf)中生产图表）": {
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"生成多种Mermaid图表(从当前对话或文件(.pdf/.md)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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"ArgsReminder": "请输入图类型对应的数字,不输入则为模型自行判断: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,9-思维导图",
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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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@ -3,7 +3,7 @@ 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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#暂时只写了这几种的PROMPT
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#以下是每类图表的PROMPT
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SELECT_PROMPT = """
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“{subject}”
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=============
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@ -18,6 +18,7 @@ SELECT_PROMPT = """
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8 象限提示图
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不需要解释原因，仅需要输出单个不带任何标点符号的数字。
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"""
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#没有思维导图!!!测试发现模型始终会优先选择思维导图
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#流程图
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PROMPT_1 = """
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请你给出围绕“{subject}”的逻辑关系图，使用mermaid语法，mermaid语法举例：
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@ -135,6 +136,31 @@ graph LR
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D[Soft skill] --> F(Communication)
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```
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"""
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#思维导图
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PROMPT_9 = """
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{subject}
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==========
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请给出上方内容的思维导图，充分考虑其之间的逻辑，使用mermaid语法，mermaid语法举例：
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```mermaid
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mindmap
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root((mindmap))
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Origins
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Long history
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::icon(fa fa-book)
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Popularisation
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British popular psychology author Tony Buzan
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Research
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On effectiveness<br/>and features
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On Automatic creation
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Uses
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Creative techniques
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Strategic planning
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Argument mapping
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Tools
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Pen and paper
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Mermaid
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```
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"""
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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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@ -166,11 +192,11 @@ def 解析历史输入(history,llm_kwargs,chatbot,plugin_kwargs):
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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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if gpt_say not in ['1','2','3','4','5','6','7','8','9']: #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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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。由于不管提供文本是什么,模型大概率认为"思维导图"最合适,因此思维导图仅能通过参数调用。'
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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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@ -178,9 +204,9 @@ def 解析历史输入(history,llm_kwargs,chatbot,plugin_kwargs):
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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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if gpt_say in ['1','2','3','4','5','6','7','8','9']: #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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if gpt_say not in ['1','2','3','4','5','6','7','8','9']:
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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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@ -199,12 +225,14 @@ def 解析历史输入(history,llm_kwargs,chatbot,plugin_kwargs):
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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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elif gpt_say == '9':
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i_say = PROMPT_9.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。如需绘制思维导图请使用参数调用,同时过大的图表可能需要复制到在线编辑器中进行渲染。'
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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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sys_prompt="你精通使用mermaid语法来绘制图表,首先确保语法正确,其次避免在mermaid语法中使用不允许的字符,此外也应当分考虑图表的可读性。"
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)
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history.append(gpt_say)
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
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@ -215,13 +243,22 @@ def 输入区文件处理(txt):
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import glob
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from .crazy_utils import get_files_from_everything
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file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
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if not file_pdf or len(pdf_manifest) == 0:
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return False, txt #如不是pdf文件则返回输入区内容
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file_md,md_manifest,folder_md = get_files_from_everything(txt, '.md')
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if len(pdf_manifest) == 0 and len(md_manifest) == 0:
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return False, txt #如输入区内容不是文件则直接返回输入区内容
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final_result = ""
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for index, fp in enumerate(pdf_manifest):
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file_content, page_one = read_and_clean_pdf_text(fp) # （尝试）按照章节切割PDF
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file_content = file_content.encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
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final_result += file_content
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if file_pdf:
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for index, fp in enumerate(pdf_manifest):
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file_content, page_one = read_and_clean_pdf_text(fp) # （尝试）按照章节切割PDF
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file_content = file_content.encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
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final_result += "\n" + file_content
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if file_md:
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for index, fp in enumerate(md_manifest):
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with open(fp, 'r', encoding='utf-8', errors='replace') as f:
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file_content = f.read()
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file_content = file_content.encode('utf-8', 'ignore').decode()
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final_result += "\n" + file_content
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return True, final_result
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@CatchException
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@ -240,7 +277,7 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,
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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(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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"根据当前聊天历史或文件中(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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@ -256,6 +293,8 @@ def 生成多种Mermaid图表(txt, llm_kwargs, plugin_kwargs, chatbot, history,
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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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else:
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file_exist = False
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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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