镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 14:36:48 +00:00
Merge branch 'master' into huggingface
这个提交包含在：
binary-husky
@@ -108,6 +108,13 @@ def test_联网回答问题():
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print("当前问答：", cb[-1][-1].replace("\n"," "))
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for i, it in enumerate(cb): print亮蓝(it[0]); print亮黄(it[1])
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def test_解析ipynb文件():
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from crazy_functions.解析JupyterNotebook import 解析ipynb文件
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txt = "crazy_functions/test_samples"
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for cookies, cb, hist, msg in 解析ipynb文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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print(cb)
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# test_解析一个Python项目()
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# test_Latex英文润色()
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# test_Markdown中译英()
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@@ -116,9 +123,8 @@ def test_联网回答问题():
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# test_总结word文档()
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# test_下载arxiv论文并翻译摘要()
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# test_解析一个Cpp项目()
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test_联网回答问题()
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# test_联网回答问题()
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test_解析ipynb文件()
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input("程序完成，回车退出。")
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print("退出。")
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42
crazy_functions/对话历史存档.py
普通文件
42
crazy_functions/对话历史存档.py
普通文件
@@ -0,0 +1,42 @@
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from toolbox import CatchException, update_ui
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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def write_chat_to_file(chatbot, file_name=None):
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"""
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将对话记录history以Markdown格式写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
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"""
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import os
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import time
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if file_name is None:
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file_name = 'chatGPT对话历史' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.html'
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os.makedirs('./gpt_log/', exist_ok=True)
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with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
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for i, contents in enumerate(chatbot):
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for content in contents:
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try: # 这个bug没找到触发条件，暂时先这样顶一下
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if type(content) != str: content = str(content)
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except:
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continue
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f.write(content)
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f.write('\n\n')
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f.write('<hr color="red"> \n\n')
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res = '对话历史写入：' + os.path.abspath(f'./gpt_log/{file_name}')
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print(res)
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return res
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@CatchException
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def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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"""
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txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
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llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行
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plugin_kwargs 插件模型的参数，暂时没有用武之地
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chatbot 聊天显示框的句柄，用于显示给用户
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history 聊天历史，前情提要
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system_prompt 给gpt的静默提醒
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web_port 当前软件运行的端口号
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"""
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chatbot.append(("保存当前对话", f"[Local Message] {write_chat_to_file(chatbot)}"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
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145
crazy_functions/解析JupyterNotebook.py
普通文件
145
crazy_functions/解析JupyterNotebook.py
普通文件
@@ -0,0 +1,145 @@
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from toolbox import update_ui
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from toolbox import CatchException, report_execption, write_results_to_file
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fast_debug = True
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class PaperFileGroup():
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def __init__(self):
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self.file_paths = []
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self.file_contents = []
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self.sp_file_contents = []
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self.sp_file_index = []
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self.sp_file_tag = []
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# count_token
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from request_llm.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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def get_token_num(txt): return len(
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enc.encode(txt, disallowed_special=()))
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self.get_token_num = get_token_num
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def run_file_split(self, max_token_limit=1900):
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"""
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将长文本分离开来
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"""
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for index, file_content in enumerate(self.file_contents):
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if self.get_token_num(file_content) < max_token_limit:
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self.sp_file_contents.append(file_content)
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self.sp_file_index.append(index)
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self.sp_file_tag.append(self.file_paths[index])
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else:
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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segments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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file_content, self.get_token_num, max_token_limit)
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for j, segment in enumerate(segments):
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self.sp_file_contents.append(segment)
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self.sp_file_index.append(index)
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self.sp_file_tag.append(
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self.file_paths[index] + f".part-{j}.txt")
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def parseNotebook(filename, enable_markdown=1):
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import json
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CodeBlocks = []
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with open(filename, 'r', encoding='utf-8', errors='replace') as f:
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notebook = json.load(f)
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for cell in notebook['cells']:
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if cell['cell_type'] == 'code' and cell['source']:
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# remove blank lines
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cell['source'] = [line for line in cell['source'] if line.strip()
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!= '']
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CodeBlocks.append("".join(cell['source']))
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elif enable_markdown and cell['cell_type'] == 'markdown' and cell['source']:
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cell['source'] = [line for line in cell['source'] if line.strip()
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!= '']
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CodeBlocks.append("Markdown:"+"".join(cell['source']))
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Code = ""
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for idx, code in enumerate(CodeBlocks):
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Code += f"This is {idx+1}th code block: \n"
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Code += code+"\n"
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return Code
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def ipynb解释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
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from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
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enable_markdown = plugin_kwargs.get("advanced_arg", "1")
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try:
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enable_markdown = int(enable_markdown)
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except ValueError:
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enable_markdown = 1
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pfg = PaperFileGroup()
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for fp in file_manifest:
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file_content = parseNotebook(fp, enable_markdown=enable_markdown)
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pfg.file_paths.append(fp)
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pfg.file_contents.append(file_content)
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# <-------- 拆分过长的IPynb文件 ---------->
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pfg.run_file_split(max_token_limit=1024)
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n_split = len(pfg.sp_file_contents)
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inputs_array = [r"This is a Jupyter Notebook file, tell me about Each Block in Chinese. Focus Just On Code." +
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r"If a block starts with `Markdown` which means it's a markdown block in ipynbipynb. " +
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r"Start a new line for a block and block num use Chinese." +
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f"\n\n{frag}" for frag in pfg.sp_file_contents]
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inputs_show_user_array = [f"{f}的分析如下" for f in pfg.sp_file_tag]
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sys_prompt_array = ["You are a professional programmer."] * n_split
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gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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inputs_array=inputs_array,
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inputs_show_user_array=inputs_show_user_array,
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llm_kwargs=llm_kwargs,
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chatbot=chatbot,
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history_array=[[""] for _ in range(n_split)],
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sys_prompt_array=sys_prompt_array,
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# max_workers=5, # OpenAI所允许的最大并行过载
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scroller_max_len=80
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)
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# <-------- 整理结果，退出 ---------->
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block_result = " \n".join(gpt_response_collection)
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chatbot.append(("解析的结果如下", block_result))
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history.extend(["解析的结果如下", block_result])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# <-------- 写入文件，退出 ---------->
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res = write_results_to_file(history)
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chatbot.append(("完成了吗？", res))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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@CatchException
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def 解析ipynb文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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chatbot.append([
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"函数插件功能？",
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"对IPynb文件进行解析。Contributor: codycjy."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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history = [] # 清空历史
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import glob
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import os
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if os.path.exists(txt):
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project_folder = txt
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else:
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if txt == "":
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txt = '空空如也的输入栏'
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report_execption(chatbot, history,
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a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
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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 txt.endswith('.ipynb'):
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file_manifest = [txt]
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else:
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file_manifest = [f for f in glob.glob(
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f'{project_folder}/**/*.ipynb', recursive=True)]
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if len(file_manifest) == 0:
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report_execption(chatbot, history,
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a=f"解析项目: {txt}", b=f"找不到任何.ipynb文件: {txt}")
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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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yield from ipynb解释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, )
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@@ -11,7 +11,7 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
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history_array = []
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sys_prompt_array = []
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report_part_1 = []
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assert len(file_manifest) <= 512, "源文件太多（超过512个）, 请缩减输入文件的数量。或者，您也可以选择删除此行警告，并修改代码拆分file_manifest列表，从而实现分批次处理。"
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############################## <第一步，逐个文件分析，多线程> ##################################
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for index, fp in enumerate(file_manifest):
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@@ -63,10 +63,10 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
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current_iteration_focus = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(this_iteration_file_manifest)])
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i_say = f'根据以上分析，对程序的整体功能和构架重新做出概括。然后用一张markdown表格整理每个文件的功能（包括{previous_iteration_files_string}）。'
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inputs_show_user = f'根据以上分析，对程序的整体功能和构架重新做出概括，由于输入长度限制，可能需要分组处理，本组文件为 {current_iteration_focus} + 已经汇总的文件组。'
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this_iteration_history = copy.deepcopy(this_iteration_gpt_response_collection)
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this_iteration_history = copy.deepcopy(this_iteration_gpt_response_collection)
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this_iteration_history.append(last_iteration_result)
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result = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=i_say, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot,
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inputs=i_say, inputs_show_user=inputs_show_user, llm_kwargs=llm_kwargs, chatbot=chatbot,
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history=this_iteration_history, # 迭代之前的分析
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sys_prompt="你是一个程序架构分析师，正在分析一个项目的源代码。")
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report_part_2.extend([i_say, result])
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@@ -222,8 +222,8 @@ def 解析一个Golang项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
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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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yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
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|
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|
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|
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@CatchException
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def 解析一个Lua项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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history = [] # 清空历史，以免输入溢出
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@@ -243,9 +243,9 @@ def 解析一个Lua项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
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report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何lua文件: {txt}")
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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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yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
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|
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|
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yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
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|
||||
|
||||
@CatchException
|
||||
def 解析一个CSharp项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
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history = [] # 清空历史，以免输入溢出
|
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@@ -263,4 +263,45 @@ def 解析一个CSharp项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
|
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report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何CSharp文件: {txt}")
|
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
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yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
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yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析任意code项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
txt_pattern = plugin_kwargs.get("advanced_arg")
|
||||
txt_pattern = txt_pattern.replace("，", ",")
|
||||
# 将要匹配的模式(例如: *.c, *.cpp, *.py, config.toml)
|
||||
pattern_include = [_.lstrip(" ,").rstrip(" ,") for _ in txt_pattern.split(",") if _ != "" and not _.strip().startswith("^")]
|
||||
if not pattern_include: pattern_include = ["*"] # 不输入即全部匹配
|
||||
# 将要忽略匹配的文件后缀(例如: ^*.c, ^*.cpp, ^*.py)
|
||||
pattern_except_suffix = [_.lstrip(" ^*.,").rstrip(" ,") for _ in txt_pattern.split(" ") if _ != "" and _.strip().startswith("^*.")]
|
||||
pattern_except_suffix += ['zip', 'rar', '7z', 'tar', 'gz'] # 避免解析压缩文件
|
||||
# 将要忽略匹配的文件名(例如: ^README.md)
|
||||
pattern_except_name = [_.lstrip(" ^*,").rstrip(" ,").replace(".", "\.") for _ in txt_pattern.split(" ") if _ != "" and _.strip().startswith("^") and not _.strip().startswith("^*.")]
|
||||
# 生成正则表达式
|
||||
pattern_except = '/[^/]+\.(' + "|".join(pattern_except_suffix) + ')$'
|
||||
pattern_except += '|/(' + "|".join(pattern_except_name) + ')$' if pattern_except_name != [] else ''
|
||||
|
||||
history.clear()
|
||||
import glob, os, re
|
||||
if os.path.exists(txt):
|
||||
project_folder = txt
|
||||
else:
|
||||
if txt == "": txt = '空空如也的输入栏'
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
# 若上传压缩文件, 先寻找到解压的文件夹路径, 从而避免解析压缩文件
|
||||
maybe_dir = [f for f in glob.glob(f'{project_folder}/*') if os.path.isdir(f)]
|
||||
if len(maybe_dir)>0 and maybe_dir[0].endswith('.extract'):
|
||||
extract_folder_path = maybe_dir[0]
|
||||
else:
|
||||
extract_folder_path = project_folder
|
||||
# 按输入的匹配模式寻找上传的非压缩文件和已解压的文件
|
||||
file_manifest = [f for pattern in pattern_include for f in glob.glob(f'{extract_folder_path}/**/{pattern}', recursive=True) if "" != extract_folder_path and \
|
||||
os.path.isfile(f) and (not re.search(pattern_except, f) or pattern.endswith('.' + re.search(pattern_except, f).group().split('.')[-1]))]
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何文件: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
||||
@@ -25,6 +25,35 @@ def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
|
||||
retry_times_at_unknown_error=0
|
||||
)
|
||||
|
||||
history.append(txt)
|
||||
history.append(gpt_say)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
|
||||
|
||||
@CatchException
|
||||
def 同时问询_指定模型(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
"""
|
||||
txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
|
||||
llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行
|
||||
plugin_kwargs 插件模型的参数，如温度和top_p等，一般原样传递下去就行
|
||||
chatbot 聊天显示框的句柄，用于显示给用户
|
||||
history 聊天历史，前情提要
|
||||
system_prompt 给gpt的静默提醒
|
||||
web_port 当前软件运行的端口号
|
||||
"""
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
chatbot.append((txt, "正在同时咨询ChatGPT和ChatGLM……"))
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新
|
||||
|
||||
# llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
|
||||
llm_kwargs['llm_model'] = plugin_kwargs.get("advanced_arg", 'chatglm&gpt-3.5-turbo') # 'chatglm&gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=txt, inputs_show_user=txt,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
||||
sys_prompt=system_prompt,
|
||||
retry_times_at_unknown_error=0
|
||||
)
|
||||
|
||||
history.append(txt)
|
||||
history.append(gpt_say)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
@@ -70,6 +70,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
||||
# 尝试导入依赖，如果缺少依赖，则给出安装建议
|
||||
try:
|
||||
import arxiv
|
||||
import math
|
||||
from bs4 import BeautifulSoup
|
||||
except:
|
||||
report_execption(chatbot, history,
|
||||
@@ -80,25 +81,26 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
||||
|
||||
# 清空历史，以免输入溢出
|
||||
history = []
|
||||
|
||||
meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
|
||||
batchsize = 5
|
||||
for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):
|
||||
if len(meta_paper_info_list[:batchsize]) > 0:
|
||||
i_say = "下面是一些学术文献的数据，提取出以下内容：" + \
|
||||
"1、英文题目；2、中文题目翻译；3、作者；4、arxiv公开（is_paper_in_arxiv）；4、引用数量（cite）；5、中文摘要翻译。" + \
|
||||
f"以下是信息源：{str(meta_paper_info_list[:batchsize])}"
|
||||
|
||||
if len(meta_paper_info_list[:10]) > 0:
|
||||
i_say = "下面是一些学术文献的数据，请从中提取出以下内容。" + \
|
||||
"1、英文题目；2、中文题目翻译；3、作者；4、arxiv公开（is_paper_in_arxiv）；4、引用数量（cite）；5、中文摘要翻译。" + \
|
||||
f"以下是信息源：{str(meta_paper_info_list[:10])}"
|
||||
inputs_show_user = f"请分析此页面中出现的所有文章：{txt}，这是第{batch+1}批"
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=inputs_show_user,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||
sys_prompt="你是一个学术翻译，请从数据中提取信息。你必须使用Markdown表格。你必须逐个文献进行处理。"
|
||||
)
|
||||
|
||||
inputs_show_user = f"请分析此页面中出现的所有文章：{txt}"
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=inputs_show_user,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||
sys_prompt="你是一个学术翻译，请从数据中提取信息。你必须使用Markdown格式。你必须逐个文献进行处理。"
|
||||
)
|
||||
history.extend([ f"第{batch+1}批", gpt_say ])
|
||||
meta_paper_info_list = meta_paper_info_list[batchsize:]
|
||||
|
||||
history.extend([ "第一批", gpt_say ])
|
||||
meta_paper_info_list = meta_paper_info_list[10:]
|
||||
|
||||
chatbot.append(["状态？", "已经全部完成"])
|
||||
chatbot.append(["状态？",
|
||||
"已经全部完成，您可以试试让AI写一个Related Works，例如您可以继续输入Write a \"Related Works\" section about \"你搜索的研究领域\" for me."])
|
||||
msg = '正常'
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
|
||||
res = write_results_to_file(history)
|
||||
|
||||
在新工单中引用
屏蔽一个用户