| |
| |
| |
| import importlib |
| from toolbox import clear_line_break |
|
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|
|
| def get_core_functions(): |
| return { |
| "英语学术润色": { |
| |
| "Prefix": r"Below is a paragraph from an academic paper. Polish the writing to meet the academic style, " + |
| r"improve the spelling, grammar, clarity, concision and overall readability. When necessary, rewrite the whole sentence. " + |
| r"Firstly, you should provide the polished paragraph. " |
| r"Secondly, you should list all your modification and explain the reasons to do so in markdown table." + "\n\n", |
| |
| "Suffix": r"", |
| |
| "Color": r"secondary", |
| |
| "Visible": True, |
| |
| "AutoClearHistory": False |
| }, |
| "中文学术润色": { |
| "Prefix": r"作为一名中文学术论文写作改进助理,你的任务是改进所提供文本的拼写、语法、清晰、简洁和整体可读性," + |
| r"同时分解长句,减少重复,并提供改进建议。请只提供文本的更正版本,避免包括解释。请编辑以下文本" + "\n\n", |
| "Suffix": r"", |
| }, |
| "查找语法错误": { |
| "Prefix": r"Help me ensure that the grammar and the spelling is correct. " |
| r"Do not try to polish the text, if no mistake is found, tell me that this paragraph is good. " |
| r"If you find grammar or spelling mistakes, please list mistakes you find in a two-column markdown table, " |
| r"put the original text the first column, " |
| r"put the corrected text in the second column and highlight the key words you fixed. " |
| r"Finally, please provide the proofreaded text.""\n\n" |
| r"Example:""\n" |
| r"Paragraph: How is you? Do you knows what is it?""\n" |
| r"| Original sentence | Corrected sentence |""\n" |
| r"| :--- | :--- |""\n" |
| r"| How **is** you? | How **are** you? |""\n" |
| r"| Do you **knows** what **is** **it**? | Do you **know** what **it** **is** ? |""\n\n" |
| r"Below is a paragraph from an academic paper. " |
| r"You need to report all grammar and spelling mistakes as the example before." |
| + "\n\n", |
| "Suffix": r"", |
| "PreProcess": clear_line_break, |
| }, |
| "中译英": { |
| "Prefix": r"Please translate following sentence to English:" + "\n\n", |
| "Suffix": r"", |
| }, |
| "学术中英互译": { |
| "Prefix": r"I want you to act as a scientific English-Chinese translator, " + |
| r"I will provide you with some paragraphs in one language " + |
| r"and your task is to accurately and academically translate the paragraphs only into the other language. " + |
| r"Do not repeat the original provided paragraphs after translation. " + |
| r"You should use artificial intelligence tools, " + |
| r"such as natural language processing, and rhetorical knowledge " + |
| r"and experience about effective writing techniques to reply. " + |
| r"I'll give you my paragraphs as follows, tell me what language it is written in, and then translate:" + "\n\n", |
| "Suffix": "", |
| "Color": "secondary", |
| }, |
| "英译中": { |
| "Prefix": r"翻译成地道的中文:" + "\n\n", |
| "Suffix": r"", |
| "Visible": False, |
| }, |
| "找图片": { |
| "Prefix": r"我需要你找一张网络图片。使用Unsplash API(https://source.unsplash.com/960x640/?<英语关键词>)获取图片URL," + |
| r"然后请使用Markdown格式封装,并且不要有反斜线,不要用代码块。现在,请按以下描述给我发送图片:" + "\n\n", |
| "Suffix": r"", |
| "Visible": False, |
| }, |
| "解释代码": { |
| "Prefix": r"请解释以下代码:" + "\n```\n", |
| "Suffix": "\n```\n", |
| }, |
| "参考文献转Bib": { |
| "Prefix": r"Here are some bibliography items, please transform them into bibtex style." + |
| r"Note that, reference styles maybe more than one kind, you should transform each item correctly." + |
| r"Items need to be transformed:", |
| "Visible": False, |
| "Suffix": r"", |
| } |
| } |
|
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|
|
| def handle_core_functionality(additional_fn, inputs, history, chatbot): |
| import core_functional |
| importlib.reload(core_functional) |
| core_functional = core_functional.get_core_functions() |
| addition = chatbot._cookies['customize_fn_overwrite'] |
| if additional_fn in addition: |
| |
| inputs = addition[additional_fn]["Prefix"] + inputs + addition[additional_fn]["Suffix"] |
| return inputs, history |
| else: |
| |
| if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) |
| inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"] |
| if core_functional[additional_fn].get("AutoClearHistory", False): |
| history = [] |
| return inputs, history |
|
|