Merge branch 'master' of github.com:mrhblfx/chatgpt_academic
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mrhblfx
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20bec70160
@ -68,11 +68,13 @@ huggingface免科学上网[在线体验](https://huggingface.co/spaces/qingxu98/
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<img src="https://user-images.githubusercontent.com/96192199/226935232-6b6a73ce-8900-4aee-93f9-733c7e6fef53.png" width="700" >
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</div>
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- 多种大语言模型混合调用（[v3.1分支](https://github.com/binary-husky/chatgpt_academic/tree/v3.1)测试中）
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- 多种大语言模型混合调用（ChatGLM + OpenAI-GPT3.5 + [API2D](https://api2d.com/)-GPT4， [v3.1分支](https://github.com/binary-husky/chatgpt_academic/tree/v3.1)测试中）
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<div align="center">
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<img src="https://user-images.githubusercontent.com/96192199/231222778-34776885-a7f0-4f2c-b5f4-7cc2ef3ecb58.png" width="700" >
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<img src="https://user-images.githubusercontent.com/96192199/232537274-deca0563-7aa6-4b5d-94a2-b7c453c47794.png" width="700" >
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</div>
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v3.1的[huggingface测试版](https://huggingface.co/spaces/qingxu98/academic-chatgpt-beta)（huggingface版不支持chatglm）
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## 直接运行 (Windows, Linux or MacOS)
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@ -444,6 +444,7 @@ def read_and_clean_pdf_text(fp):
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pf = 998
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for l in t['lines']:
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txt_line = "".join([wtf['text'] for wtf in l['spans']])
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if len(txt_line) == 0: continue
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pf = primary_ffsize(l)
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meta_line.append([txt_line, pf, l['bbox'], l])
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for wtf in l['spans']: # for l in t['lines']:
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@ -554,8 +555,8 @@ def read_and_clean_pdf_text(fp):
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meta_txt = meta_txt.replace('\n', '\n\n')
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############################## <第 5 步，展示分割效果> ##################################
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for f in finals:
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print亮黄(f)
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print亮绿('***************************')
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# for f in finals:
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# print亮黄(f)
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# print亮绿('***************************')
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return meta_txt, page_one_meta
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@ -13,7 +13,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_
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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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"批量总结PDF文档。函数插件贡献者: Binary-Husky"])
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"批量翻译PDF文档。函数插件贡献者: Binary-Husky"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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# 尝试导入依赖，如果缺少依赖，则给出安装建议
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@ -59,7 +59,7 @@ 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 = 1600
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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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@ -91,13 +91,13 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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# 多线，翻译
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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=[
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f"以下是你需要翻译的论文片段：\n{frag}" for frag in paper_fragments],
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f"你需要翻译以下内容：\n{frag}" for frag in paper_fragments],
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inputs_show_user_array=[f"\n---\n 原文： \n\n {frag.replace('#', '')} \n---\n 翻译：\n " for frag in paper_fragments],
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llm_kwargs=llm_kwargs,
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chatbot=chatbot,
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history_array=[[paper_meta] for _ in paper_fragments],
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sys_prompt_array=[
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"请你作为一个学术翻译，负责把学术论文的片段准确翻译成中文。" for _ in paper_fragments],
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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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@ -456,7 +456,7 @@ def on_file_uploaded(files, chatbot, txt):
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chatbot.append(['我上传了文件，请查收',
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f'[Local Message] 收到以下文件: \n\n{moved_files_str}' +
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f'\n\n调用路径参数已自动修正到: \n\n{txt}' +
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f'\n\n现在您点击任意实验功能时，以上文件将被作为输入参数'+err_msg])
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f'\n\n现在您点击任意“红颜色”标识的函数插件时，以上文件将被作为输入参数'+err_msg])
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return chatbot, txt
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