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Runtime error
Runtime error
修复pdf翻译的问题
Browse files- crazy_functions/批量翻译PDF文档_多线程.py +94 -9
- toolbox.py +7 -4
crazy_functions/批量翻译PDF文档_多线程.py
CHANGED
@@ -58,14 +58,17 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_
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def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, sys_prompt):
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import os
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import tiktoken
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TOKEN_LIMIT_PER_FRAGMENT = 1280
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generated_conclusion_files = []
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for index, fp in enumerate(file_manifest):
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# 读取PDF文件
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file_content, page_one = read_and_clean_pdf_text(fp)
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-
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# 递归地切割PDF文件
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from request_llm.bridge_all import model_info
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@@ -74,7 +77,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=file_content, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
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page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=
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# 为了更好的效果,我们剥离Introduction之后的部分(如果有)
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paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
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@@ -100,15 +103,15 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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"请你作为一个学术翻译,负责把学术论文准确翻译成中文。注意文章中的每一句话都要翻译。" for _ in paper_fragments],
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# max_workers=5 # OpenAI所允许的最大并行过载
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)
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-
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# 整理报告的格式
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for i,k in enumerate(
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if i%2==0:
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-
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else:
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-
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final = ["一、论文概况\n\n---\n\n", paper_meta_info.replace('# ', '### ') + '\n\n---\n\n', "二、论文翻译", ""]
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-
final.extend(
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create_report_file_name = f"{os.path.basename(fp)}.trans.md"
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res = write_results_to_file(final, file_name=create_report_file_name)
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@@ -117,15 +120,97 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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chatbot.append((f"{fp}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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# 准备文件的下载
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import shutil
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for pdf_path in generated_conclusion_files:
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# 重命名文件
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-
rename_file = f'./gpt_log
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if os.path.exists(rename_file):
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os.remove(rename_file)
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shutil.copyfile(pdf_path, rename_file)
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if os.path.exists(pdf_path):
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os.remove(pdf_path)
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-
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, sys_prompt):
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import os
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import copy
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import tiktoken
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TOKEN_LIMIT_PER_FRAGMENT = 1280
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generated_conclusion_files = []
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generated_html_files = []
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for index, fp in enumerate(file_manifest):
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# 读取PDF文件
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file_content, page_one = read_and_clean_pdf_text(fp)
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file_content = file_content.encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
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page_one = str(page_one).encode('utf-8', 'ignore').decode() # avoid reading non-utf8 chars
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# 递归地切割PDF文件
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from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
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from request_llm.bridge_all import model_info
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paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=file_content, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT)
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page_one_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
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txt=page_one, get_token_fn=get_token_num, limit=TOKEN_LIMIT_PER_FRAGMENT//4)
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# 为了更好的效果,我们剥离Introduction之后的部分(如果有)
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paper_meta = page_one_fragments[0].split('introduction')[0].split('Introduction')[0].split('INTRODUCTION')[0]
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"请你作为一个学术翻译,负责把学术论文准确翻译成中文。注意文章中的每一句话都要翻译。" for _ in paper_fragments],
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# max_workers=5 # OpenAI所允许的最大并行过载
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)
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gpt_response_collection_md = copy.deepcopy(gpt_response_collection)
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# 整理报告的格式
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for i,k in enumerate(gpt_response_collection_md):
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if i%2==0:
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gpt_response_collection_md[i] = f"\n\n---\n\n ## 原文[{i//2}/{len(gpt_response_collection_md)//2}]: \n\n {paper_fragments[i//2].replace('#', '')} \n\n---\n\n ## 翻译[{i//2}/{len(gpt_response_collection_md)//2}]:\n "
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else:
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gpt_response_collection_md[i] = gpt_response_collection_md[i]
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final = ["一、论文概况\n\n---\n\n", paper_meta_info.replace('# ', '### ') + '\n\n---\n\n', "二、论文翻译", ""]
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final.extend(gpt_response_collection_md)
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create_report_file_name = f"{os.path.basename(fp)}.trans.md"
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res = write_results_to_file(final, file_name=create_report_file_name)
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chatbot.append((f"{fp}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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# write html
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try:
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ch = construct_html()
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orig = ""
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trans = ""
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gpt_response_collection_html = copy.deepcopy(gpt_response_collection)
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for i,k in enumerate(gpt_response_collection_html):
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if i%2==0:
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gpt_response_collection_html[i] = paper_fragments[i//2].replace('#', '')
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else:
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gpt_response_collection_html[i] = gpt_response_collection_html[i]
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final = ["论文概况", paper_meta_info.replace('# ', '### '), "二、论文翻译", ""]
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final.extend(gpt_response_collection_html)
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for i, k in enumerate(final):
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if i%2==0:
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orig = k
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if i%2==1:
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trans = k
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ch.add_row(a=orig, b=trans)
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create_report_file_name = f"{os.path.basename(fp)}.trans.html"
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ch.save_file(create_report_file_name)
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generated_html_files.append(f'./gpt_log/{create_report_file_name}')
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except:
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from toolbox import trimmed_format_exc
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print('writing html result failed:', trimmed_format_exc())
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# 准备文件的下载
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import shutil
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for pdf_path in generated_conclusion_files:
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# 重命名文件
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rename_file = f'./gpt_log/翻译-{os.path.basename(pdf_path)}'
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if os.path.exists(rename_file):
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os.remove(rename_file)
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shutil.copyfile(pdf_path, rename_file)
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if os.path.exists(pdf_path):
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os.remove(pdf_path)
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for html_path in generated_html_files:
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# 重命名文件
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rename_file = f'./gpt_log/翻译-{os.path.basename(html_path)}'
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if os.path.exists(rename_file):
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os.remove(rename_file)
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shutil.copyfile(html_path, rename_file)
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if os.path.exists(html_path):
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os.remove(html_path)
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chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files)))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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class construct_html():
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def __init__(self) -> None:
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self.css = """
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.row {
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display: flex;
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flex-wrap: wrap;
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}
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.column {
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flex: 1;
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padding: 10px;
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}
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.table-header {
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font-weight: bold;
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border-bottom: 1px solid black;
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}
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.table-row {
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border-bottom: 1px solid lightgray;
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}
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.table-cell {
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padding: 5px;
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}
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"""
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self.html_string = f'<!DOCTYPE html><head><meta charset="utf-8"><title>翻译结果</title><style>{self.css}</style></head>'
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def add_row(self, a, b):
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tmp = """
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<div class="row table-row">
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<div class="column table-cell">REPLACE_A</div>
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<div class="column table-cell">REPLACE_B</div>
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</div>
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"""
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from toolbox import markdown_convertion
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tmp = tmp.replace('REPLACE_A', markdown_convertion(a))
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tmp = tmp.replace('REPLACE_B', markdown_convertion(b))
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self.html_string += tmp
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def save_file(self, file_name):
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with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
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f.write(self.html_string.encode('utf-8', 'ignore').decode())
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toolbox.py
CHANGED
@@ -168,14 +168,17 @@ def write_results_to_file(history, file_name=None):
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with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
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f.write('# chatGPT 分析报告\n')
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for i, content in enumerate(history):
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try:
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if type(content) != str:
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content = str(content)
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except:
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continue
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if i % 2 == 0:
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f.write('## ')
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-
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f.write('\n\n')
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res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}')
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print(res)
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with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
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f.write('# chatGPT 分析报告\n')
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for i, content in enumerate(history):
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try:
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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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if i % 2 == 0:
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f.write('## ')
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try:
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f.write(content)
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except:
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# remove everything that cannot be handled by utf8
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f.write(content.encode('utf-8', 'ignore').decode())
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f.write('\n\n')
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res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}')
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print(res)
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