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Parse and generate ipynb (Issue #501)
Browse filesImplemented code to parse and generate the ipynb files. The solution addresses Issue #501.
- crazy_functional.py +6 -0
- crazy_functions/解析JupyterNotebook.py +135 -0
crazy_functional.py
CHANGED
@@ -19,12 +19,18 @@ def get_crazy_functions():
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from crazy_functions.解析项目源代码 import 解析一个Lua项目
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from crazy_functions.解析项目源代码 import 解析一个CSharp项目
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from crazy_functions.总结word文档 import 总结word文档
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function_plugins = {
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"解析整个Python项目": {
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"Color": "stop", # 按钮颜色
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"Function": HotReload(解析一个Python项目)
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},
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"批量总结Word文档": {
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"Color": "stop",
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"Function": HotReload(总结word文档)
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from crazy_functions.解析项目源代码 import 解析一个Lua项目
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from crazy_functions.解析项目源代码 import 解析一个CSharp项目
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from crazy_functions.总结word文档 import 总结word文档
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from crazy_functions.解析JupyterNotebook import 解析ipynb文件
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function_plugins = {
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"解析整个Python项目": {
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"Color": "stop", # 按钮颜色
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"Function": HotReload(解析一个Python项目)
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},
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"解析Jupyter Notebook文件": {
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"Color": "stop",
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"AsButton":False,
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"Function": HotReload(解析ipynb文件),
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},
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"批量总结Word文档": {
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"Color": "stop",
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"Function": HotReload(总结word文档)
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crazy_functions/解析JupyterNotebook.py
ADDED
@@ -0,0 +1,135 @@
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from toolbox import update_ui
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from toolbox import CatchException, report_execption
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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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pfg = PaperFileGroup()
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print(file_manifest)
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for fp in file_manifest:
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file_content = parseNotebook(fp, enable_markdown=1)
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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 = [f"This is a Jupyter Notebook file, tell me about Each Block in Chinese. Focus Just On Code." +
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f"If a block starts with `Markdown` which means it's a markdown block in ipynbipynb. " +
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f"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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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"])
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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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