Merge pull request #841 from KelvinF97/master

Optimize some code and fix some bugs

.github/workflows/build-image.yaml

@@ -1,38 +0,0 @@
-name: Build Image
-
-
-on:
-  workflow_dispatch:
-    inputs:
-      release_tag:
-        description: 'Tag for the images'
-        required: true
-
-env:
-  REGISTRY: registry.cn-hongkong.aliyuncs.com
-  NAMESPACE: chatwithpaper
-  IMAGE: academic
-  TAG: ${{ github.event.inputs.release_tag || github.event.client_payload.release_tag }}
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    environment: production
-    steps:
-    - name: Checkout
-      uses: actions/checkout@v3
-
-    - name: Login to Registry
-      uses: docker/login-action@v2.1.0
-      with:
-        registry: "${{ env.REGISTRY }}"
-        username: "${{ secrets.ACR_USER }}"
-        password: "${{ secrets.ACR_PASSWORD }}"
-
-    - name: Build and push image
-      uses: docker/build-push-action@v4
-      with:
-        context: .
-        file: docs/Dockerfile+NoLocal+Latex
-        tags: ${{ env.REGISTRY }}/${{ env.NAMESPACE }}/${{ env.IMAGE }}:${{ env.TAG }}
-        push: true

.github/workflows/build-with-chatglm.yml

@@ -0,0 +1,44 @@
+# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
+name: Create and publish a Docker image for ChatGLM support
+
+on:
+  push:
+    branches:
+      - 'master'
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}_chatglm_moss
+
+jobs:
+  build-and-push-image:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Log in to the Container registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          push: true
+          file: docs/GithubAction+ChatGLM+Moss
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}

.github/workflows/build-with-jittorllms.yml

@@ -0,0 +1,44 @@
+# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
+name: Create and publish a Docker image for ChatGLM support
+
+on:
+  push:
+    branches:
+      - 'master'
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}_jittorllms
+
+jobs:
+  build-and-push-image:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Log in to the Container registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          push: true
+          file: docs/GithubAction+JittorLLMs
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}

.github/workflows/build-without-local-llms.yml

@@ -0,0 +1,44 @@
+# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
+name: Create and publish a Docker image
+
+on:
+  push:
+    branches:
+      - 'master'
+
+env:
+  REGISTRY: ghcr.io
+  IMAGE_NAME: ${{ github.repository }}_nolocal
+
+jobs:
+  build-and-push-image:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Log in to the Container registry
+        uses: docker/login-action@v2
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Extract metadata (tags, labels) for Docker
+        id: meta
+        uses: docker/metadata-action@v4
+        with:
+          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v4
+        with:
+          context: .
+          push: true
+          file: docs/GithubAction+NoLocal
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}

check_proxy.py

@@ -1,10 +1,10 @@
 
-def check_proxy(proxies):
+def check_proxy(proxies: dict):
     import requests
-    proxies_https = proxies['https'] if proxies is not None else '无'
+    proxies_https = proxies.get('https') if proxies is not None else '无'
     try:
         response = requests.get("https://ipapi.co/json/",
-                                proxies=proxies, timeout=4)
+                                proxies=proxies, timeout=30)
         data = response.json()
         print(f'查询代理的地理位置，返回的结果是{data}')
         if 'country_name' in data:
@@ -12,10 +12,12 @@ def check_proxy(proxies):
             result = f"代理配置 {proxies_https}, 代理所在地：{country}"
         elif 'error' in data:
             result = f"代理配置 {proxies_https}, 代理所在地：未知，IP查询频率受限"
+        else:
+            result = f"代理配置 {proxies_https}, 代理数据解析失败：{data}"
         print(result)
         return result
-    except:
-        result = f"代理配置 {proxies_https}, 代理所在地查询超时，代理可能无效"
+    except Exception as e:
+        result = f"代理 {proxies_https} 查询出现异常: {e}，代理可能无效"
         print(result)
         return result
 

config.py

@@ -47,7 +47,7 @@ MAX_RETRY = 2
 
 # 模型选择是 (注意: LLM_MODEL是默认选中的模型, 同时它必须被包含在AVAIL_LLM_MODELS切换列表中 )
 LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
-AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo"]
+AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt35", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "newbing-free", "stack-claude"]
 # P.S. 其他可用的模型还包括 ["gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "newbing-free", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
 
 # 本地LLM模型如ChatGLM的执行方式 CPU/GPU
@@ -56,6 +56,9 @@ LOCAL_MODEL_DEVICE = "cpu" # 可选 "cuda"
 # 设置gradio的并行线程数（不需要修改）
 CONCURRENT_COUNT = 100
 
+# 是否在提交时自动清空输入框
+AUTO_CLEAR_TXT = False
+
 # 加一个live2d装饰
 ADD_WAIFU = False
 

core_functional.py

@@ -42,7 +42,6 @@ def get_core_functions():
         "中译英": {
             "Prefix":   r"Please translate following sentence to English:" + "\n\n",
             "Suffix":   r"",
-            "Visible": False,
         },
         "学术中英互译": {
             "Prefix":   r"I want you to act as a scientific English-Chinese translator, " +
@@ -75,6 +74,5 @@ def get_core_functions():
                         r"Note that, reference styles maybe more than one kind, you should transform each item correctly." +
                         r"Items need to be transformed:",
             "Suffix":   r"",
-            "Visible": False,
         }
     }

crazy_functional.py

@@ -26,7 +26,6 @@ def get_crazy_functions():
     from crazy_functions.对话历史存档 import 删除所有本地对话历史记录
     
     from crazy_functions.批量Markdown翻译 import Markdown英译中
-        
     function_plugins = {
         "解析整个Python项目": {
             "Color": "stop",    # 按钮颜色
@@ -48,10 +47,10 @@ def get_crazy_functions():
             "AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
             "ArgsReminder": "若输入0，则不解析notebook中的Markdown块", # 高级参数输入区的显示提示
         },
-        # "批量总结Word文档": {
-        #     "Color": "stop",
-        #     "Function": HotReload(总结word文档)
-        # },
+        "批量总结Word文档": {
+            "Color": "stop",
+            "Function": HotReload(总结word文档)
+        },
         "解析整个C++项目头文件": {
             "Color": "stop",    # 按钮颜色
             "AsButton": False,  # 加入下拉菜单中
@@ -109,10 +108,10 @@ def get_crazy_functions():
         "保存当前的对话": {
             "Function": HotReload(对话历史存档)
         },
-        # "[多线程Demo] 解析此项目本身（源码自译解）": {
-        #     "AsButton": False,  # 加入下拉菜单中
-        #     "Function": HotReload(解析项目本身)
-        # },
+        "[多线程Demo] 解析此项目本身（源码自译解）": {
+            "AsButton": False,  # 加入下拉菜单中
+            "Function": HotReload(解析项目本身)
+        },
         # "[老旧的Demo] 把本项目源代码切换成全英文": {
         #     # HotReload 的意思是热更新，修改函数插件代码后，不需要重启程序，代码直接生效
         #     "AsButton": False,  # 加入下拉菜单中
@@ -138,15 +137,15 @@ def get_crazy_functions():
     from crazy_functions.批量Markdown翻译 import Markdown中译英
 
     function_plugins.update({
-        "本地PDF全文翻译": {
+        "批量翻译PDF文档（多线程）": {
             "Color": "stop",
             "AsButton": True,  # 加入下拉菜单中
             "Function": HotReload(批量翻译PDF文档)
         },
-        # "询问多个GPT模型": {
-        #     "Color": "stop",    # 按钮颜色
-        #     "Function": HotReload(同时问询)
-        # },
+        "询问多个GPT模型": {
+            "Color": "stop",    # 按钮颜色
+            "Function": HotReload(同时问询)
+        },
         "[测试功能] 批量总结PDF文档": {
             "Color": "stop",
             "AsButton": False,  # 加入下拉菜单中
@@ -223,57 +222,54 @@ def get_crazy_functions():
         })
     except:
         print('Load function plugin failed')
-    from crazy_functions.Latex输出PDF结果 import Latex翻译中文并重新编译PDF
+
+    try:
+        from crazy_functions.联网的ChatGPT import 连接网络回答问题
         function_plugins.update({
-        "ArXiv Latex一键翻译（输入区给定arXiv ID）": {
+            "连接网络回答问题（输入问题后点击该插件，需要访问谷歌）": {
                 "Color": "stop",
-            "AsButton": True,
-            "AdvancedArgs": True,
-            "ArgsReminder": 
-                "如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "+ 
-                "例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " + 'If the term "agent" is used in this section, it should be translated to "智能体". ',
-            "Function": HotReload(Latex翻译中文并重新编译PDF)
+                "AsButton": False,  # 加入下拉菜单中
+                "Function": HotReload(连接网络回答问题)
             }
         })
-    # try:
-    #     from crazy_functions.联网的ChatGPT import 连接网络回答问题
-    #     function_plugins.update({
-    #         "连接网络回答问题（先输入问题，再点击按钮，需要访问谷歌）": {
-    #             "Color": "stop",
-    #             "AsButton": False,  # 加入下拉菜单中
-    #             "Function": HotReload(连接网络回答问题)
-    #         }
-    #     })
-    # except:
-    #     print('Load function plugin failed')
+        from crazy_functions.联网的ChatGPT_bing版 import 连接bing搜索回答问题
+        function_plugins.update({
+            "连接网络回答问题（中文Bing版，输入问题后点击该插件）": {
+                "Color": "stop",
+                "AsButton": False,  # 加入下拉菜单中
+                "Function": HotReload(连接bing搜索回答问题)
+            }
+        })
+    except:
+        print('Load function plugin failed')
 
-    # try:
-    #     from crazy_functions.解析项目源代码 import 解析任意code项目
-    #     function_plugins.update({
-    #         "解析项目源代码（手动指定和筛选源代码文件类型）": {
-    #             "Color": "stop",
-    #             "AsButton": False,
-    #             "AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
-    #             "ArgsReminder": "输入时用逗号隔开, *代表通配符, 加了^代表不匹配; 不输入代表全部匹配。例如: \"*.c, ^*.cpp, config.toml, ^*.toml\"", # 高级参数输入区的显示提示
-    #             "Function": HotReload(解析任意code项目)
-    #         },
-    #     })
-    # except:
-    #     print('Load function plugin failed')
+    try:
+        from crazy_functions.解析项目源代码 import 解析任意code项目
+        function_plugins.update({
+            "解析项目源代码（手动指定和筛选源代码文件类型）": {
+                "Color": "stop",
+                "AsButton": False,
+                "AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
+                "ArgsReminder": "输入时用逗号隔开, *代表通配符, 加了^代表不匹配; 不输入代表全部匹配。例如: \"*.c, ^*.cpp, config.toml, ^*.toml\"", # 高级参数输入区的显示提示
+                "Function": HotReload(解析任意code项目)
+            },
+        })
+    except:
+        print('Load function plugin failed')
 
-    # try:
-    #     from crazy_functions.询问多个大语言模型 import 同时问询_指定模型
-    #     function_plugins.update({
-    #         "询问多个GPT模型（手动指定询问哪些模型）": {
-    #             "Color": "stop",
-    #             "AsButton": False,
-    #             "AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
-    #             "ArgsReminder": "支持任意数量的llm接口，用&符号分隔。例如chatglm&gpt-3.5-turbo&api2d-gpt-4", # 高级参数输入区的显示提示
-    #             "Function": HotReload(同时问询_指定模型)
-    #         },
-    #     })
-    # except:
-    #     print('Load function plugin failed')
+    try:
+        from crazy_functions.询问多个大语言模型 import 同时问询_指定模型
+        function_plugins.update({
+            "询问多个GPT模型（手动指定询问哪些模型）": {
+                "Color": "stop",
+                "AsButton": False,
+                "AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
+                "ArgsReminder": "支持任意数量的llm接口，用&符号分隔。例如chatglm&gpt-3.5-turbo&api2d-gpt-4", # 高级参数输入区的显示提示
+                "Function": HotReload(同时问询_指定模型)
+            },
+        })
+    except:
+        print('Load function plugin failed')
 
     try:
         from crazy_functions.图片生成 import 图片生成
@@ -368,18 +364,29 @@ def get_crazy_functions():
                 "Function": HotReload(Latex英文纠错加PDF对比)
             }
         })
-        
-        # function_plugins.update({
-        #     "本地论文翻译（上传Latex压缩包） [需Latex]": {
-        #         "Color": "stop",
-        #         "AsButton": False,
-        #         "AdvancedArgs": True,
-        #         "ArgsReminder": 
-        #             "如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "+ 
-        #             "例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " + 'If the term "agent" is used in this section, it should be translated to "智能体". ',
-        #         "Function": HotReload(Latex翻译中文并重新编译PDF)
-        #     }
-        # })
+        from crazy_functions.Latex输出PDF结果 import Latex翻译中文并重新编译PDF
+        function_plugins.update({
+            "Arixv翻译（输入arxivID）[需Latex]": {
+                "Color": "stop",
+                "AsButton": False,
+                "AdvancedArgs": True,
+                "ArgsReminder": 
+                    "如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "+ 
+                    "例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " + 'If the term "agent" is used in this section, it should be translated to "智能体". ',
+                "Function": HotReload(Latex翻译中文并重新编译PDF)
+            }
+        })
+        function_plugins.update({
+            "本地论文翻译（上传Latex压缩包）[需Latex]": {
+                "Color": "stop",
+                "AsButton": False,
+                "AdvancedArgs": True,
+                "ArgsReminder": 
+                    "如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 "+ 
+                    "例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " + 'If the term "agent" is used in this section, it should be translated to "智能体". ',
+                "Function": HotReload(Latex翻译中文并重新编译PDF)
+            }
+        })
     except:
         print('Load function plugin failed')
 
@@ -397,18 +404,4 @@ def get_crazy_functions():
     # except:
     #     print('Load function plugin failed')
 
-    # try:
-    #     from crazy_functions.虚空终端 import 终端
-    #     function_plugins.update({
-    #         "超级终端": {
-    #             "Color": "stop",
-    #             "AsButton": False,
-    #             # "AdvancedArgs": True,
-    #             # "ArgsReminder": "",
-    #             "Function": HotReload(终端)
-    #         }
-    #     })
-    # except:
-    #     print('Load function plugin failed')
-
     return function_plugins

crazy_functions/Latex输出PDF结果.py

@@ -3,9 +3,7 @@ from toolbox import CatchException, report_execption, update_ui_lastest_msg, zip
 from functools import partial
 import glob, os, requests, time
 pj = os.path.join
-# ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")
-# ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")
-ARXIV_CACHE_DIR = os.getenv("Arxiv_Cache")
+ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")
 
 # =================================== 工具函数 ===============================================
 专业词汇声明  = 'If the term "agent" is used in this section, it should be translated to "智能体". '
@@ -192,9 +190,9 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
 
 
     # <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
-    if not os.path.exists(project_folder + '/merge_proofread.tex'):
+    if not os.path.exists(project_folder + '/merge_proofread_en.tex'):
         yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, 
-                                chatbot, history, system_prompt, mode='proofread_latex', switch_prompt=switch_prompt)
+                                chatbot, history, system_prompt, mode='proofread_en', switch_prompt=_switch_prompt_)
 
 
     # <-------------- compile PDF ------------->

crazy_functions/crazy_functions_test.py

@@ -195,7 +195,7 @@ def test_Latex():
     # txt = r"https://arxiv.org/abs/2303.08774"
     # txt = r"https://arxiv.org/abs/2303.12712"
     # txt = r"C:\Users\fuqingxu\arxiv_cache\2303.12712\workfolder"
-    txt = r"C:\Users\fuqingxu\Desktop\9"
+    txt = r"2306.17157" # 这个paper有个input命令文件名大小写错误！
     
 
     for cookies, cb, hist, msg in (Latex翻译中文并重新编译PDF)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):

crazy_functions/crazy_utils.py

@@ -1,16 +1,19 @@
 from toolbox import update_ui, get_conf, trimmed_format_exc
 import threading
 
+
 def input_clipping(inputs, history, max_token_limit):
     import numpy as np
     from request_llm.bridge_all import model_info
     enc = model_info["gpt-3.5-turbo"]['tokenizer']
-    def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
+
+    def get_token_num(txt):
+        return len(enc.encode(txt, disallowed_special=()))
 
     mode = 'input-and-history'
     # 当 输入部分的token占比 小于 全文的一半时，只裁剪历史
     input_token_num = get_token_num(inputs)
-    if input_token_num < max_token_limit//2: 
+    if input_token_num < max_token_limit // 2:
         mode = 'only-history'
         max_token_limit = max_token_limit - input_token_num
 
@@ -23,7 +26,7 @@ def input_clipping(inputs, history, max_token_limit):
     while n_token > max_token_limit:
         where = np.argmax(everything_token)
         encoded = enc.encode(everything[where], disallowed_special=())
-        clipped_encoded = encoded[:len(encoded)-delta]
+        clipped_encoded = encoded[:len(encoded) - delta]
         everything[where] = enc.decode(clipped_encoded)[:-1]  # -1 to remove the may-be illegal char
         everything_token[where] = get_token_num(everything[where])
         n_token = get_token_num('\n'.join(everything))
@@ -35,12 +38,13 @@ def input_clipping(inputs, history, max_token_limit):
     history = everything[1:]
     return inputs, history
 
+
 def request_gpt_model_in_new_thread_with_ui_alive(
         inputs, inputs_show_user, llm_kwargs,
         chatbot, history, sys_prompt, refresh_interval=0.2,
         handle_token_exceed=True,
         retry_times_at_unknown_error=2,
-        ):
+):
     """
     Request GPT model，请求GPT模型同时维持用户界面活跃。
 
@@ -67,12 +71,13 @@ def request_gpt_model_in_new_thread_with_ui_alive(
     yield from update_ui(chatbot=chatbot, history=[])  # 刷新界面
     executor = ThreadPoolExecutor(max_workers=16)
     mutable = ["", time.time(), ""]
+
     def _req_gpt(inputs, history, sys_prompt):
         retry_op = retry_times_at_unknown_error
         exceeded_cnt = 0
         while True:
             # watchdog error
-            if len(mutable) >= 2 and (time.time()-mutable[1]) > 5: 
+            if len(mutable) >= 2 and (time.time() - mutable[1]) > 5:
                 raise RuntimeError("检测到程序终止。")
             try:
                 # 【第一种情况】：顺利完成
@@ -89,7 +94,7 @@ def request_gpt_model_in_new_thread_with_ui_alive(
                     p_ratio, n_exceed = get_reduce_token_percent(str(token_exceeded_error))
                     MAX_TOKEN = 4096
                     EXCEED_ALLO = 512 + 512 * exceeded_cnt
-                    inputs, history = input_clipping(inputs, history, max_token_limit=MAX_TOKEN-EXCEED_ALLO)
+                    inputs, history = input_clipping(inputs, history, max_token_limit=MAX_TOKEN - EXCEED_ALLO)
                     mutable[0] += f'[Local Message] 警告，文本过长将进行截断，Token溢出数：{n_exceed}。\n\n'
                     continue  # 返回重试
                 else:
@@ -104,7 +109,8 @@ def request_gpt_model_in_new_thread_with_ui_alive(
                 mutable[0] += f"[Local Message] 警告，在执行过程中遭遇问题, Traceback：\n\n{tb_str}\n\n"
                 if retry_op > 0:
                     retry_op -= 1
-                    mutable[0] += f"[Local Message] 重试中，请稍等 {retry_times_at_unknown_error-retry_op}/{retry_times_at_unknown_error}：\n\n"
+                    mutable[
+                        0] += f"[Local Message] 重试中，请稍等 {retry_times_at_unknown_error - retry_op}/{retry_times_at_unknown_error}：\n\n"
                     if ("Rate limit reached" in tb_str) or ("Too Many Requests" in tb_str):
                         time.sleep(30)
                     time.sleep(5)
@@ -137,7 +143,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
         refresh_interval=0.2, max_workers=-1, scroller_max_len=30,
         handle_token_exceed=True, show_user_at_complete=False,
         retry_times_at_unknown_error=2,
-        ):
+):
     """
     Request GPT model using multiple threads with UI and high efficiency
     请求GPT模型的[多线程]版。
@@ -171,8 +177,10 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
     assert len(inputs_array) == len(history_array)
     assert len(inputs_array) == len(sys_prompt_array)
     if max_workers == -1:  # 读取配置文件
-        try: max_workers, = get_conf('DEFAULT_WORKER_NUM')
-        except: max_workers = 8
+        try:
+            max_workers, = get_conf('DEFAULT_WORKER_NUM')
+        except:
+            max_workers = 8
         if max_workers <= 0: max_workers = 3
     # 屏蔽掉 chatglm的多线程，可能会导致严重卡顿
     if not (llm_kwargs['llm_model'].startswith('gpt-') or llm_kwargs['llm_model'].startswith('api2d-')):
@@ -194,7 +202,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
         mutable[index][2] = "执行中"
         while True:
             # watchdog error
-            if len(mutable[index]) >= 2 and (time.time()-mutable[index][1]) > 5: 
+            if len(mutable[index]) >= 2 and (time.time() - mutable[index][1]) > 5:
                 raise RuntimeError("检测到程序终止。")
             try:
                 # 【第一种情况】：顺利完成
@@ -214,7 +222,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
                     p_ratio, n_exceed = get_reduce_token_percent(str(token_exceeded_error))
                     MAX_TOKEN = 4096
                     EXCEED_ALLO = 512 + 512 * exceeded_cnt
-                    inputs, history = input_clipping(inputs, history, max_token_limit=MAX_TOKEN-EXCEED_ALLO)
+                    inputs, history = input_clipping(inputs, history, max_token_limit=MAX_TOKEN - EXCEED_ALLO)
                     gpt_say += f'[Local Message] 警告，文本过长将进行截断，Token溢出数：{n_exceed}。\n\n'
                     mutable[index][2] = f"截断重试"
                     continue  # 返回重试
@@ -222,15 +230,17 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
                     # 【选择放弃】
                     tb_str = '```\n' + trimmed_format_exc() + '```'
                     gpt_say += f"[Local Message] 警告，线程{index}在执行过程中遭遇问题, Traceback：\n\n{tb_str}\n\n"
-                    if len(mutable[index][0]) > 0: gpt_say += "此线程失败前收到的回答：\n\n" + mutable[index][0]
+                    if len(mutable[index][0]) > 0:
+                        gpt_say += "此线程失败前收到的回答：\n\n" + mutable[index][0]
                     mutable[index][2] = "输入过长已放弃"
                     return gpt_say  # 放弃
-            except:
+            except Exception as e:
                 # 【第三种情况】：其他错误
                 tb_str = '```\n' + trimmed_format_exc() + '```'
-                print(tb_str)
+                print(f"发生异常：{e}, 调用栈信息：{tb_str}")
                 gpt_say += f"[Local Message] 警告，线程{index}在执行过程中遭遇问题, Traceback：\n\n{tb_str}\n\n"
-                if len(mutable[index][0]) > 0: gpt_say += "此线程失败前收到的回答：\n\n" + mutable[index][0]
+                if len(mutable[index][0]) > 0:
+                    gpt_say += "此线程失败前收到的回答：\n\n" + mutable[index][0]
                 if retry_op > 0:
                     retry_op -= 1
                     wait = random.randint(5, 20)
@@ -241,9 +251,11 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
                         fail_info = ""
                     # 也许等待十几秒后，情况会好转
                     for i in range(wait):
-                        mutable[index][2] = f"{fail_info}等待重试 {wait-i}"; time.sleep(1)
+                        mutable[index][2] = f"{fail_info}等待重试 {wait - i}";
+                        time.sleep(1)
                     # 开始重试
-                    mutable[index][2] = f"重试中 {retry_times_at_unknown_error-retry_op}/{retry_times_at_unknown_error}"
+                    mutable[index][
+                        2] = f"重试中 {retry_times_at_unknown_error - retry_op}/{retry_times_at_unknown_error}"
                     continue  # 返回重试
                 else:
                     mutable[index][2] = "已失败"
@@ -252,7 +264,8 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
                     return gpt_say  # 放弃
 
     # 异步任务开始
-    futures = [executor.submit(_req_gpt, index, inputs, history, sys_prompt) for index, inputs, history, sys_prompt in zip(
+    futures = [executor.submit(_req_gpt, index, inputs, history, sys_prompt) for index, inputs, history, sys_prompt in
+               zip(
                    range(len(inputs_array)), inputs_array, history_array, sys_prompt_array)]
     cnt = 0
     while True:
@@ -267,16 +280,16 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
             mutable[thread_index][1] = time.time()
         # 在前端打印些好玩的东西
         for thread_index, _ in enumerate(worker_done):
-            print_something_really_funny = "[ ...`"+mutable[thread_index][0][-scroller_max_len:].\
+            print_something_really_funny = "[ ...`" + mutable[thread_index][0][-scroller_max_len:]. \
                 replace('\n', '').replace('```', '...').replace(
-                    ' ', '.').replace('<br/>', '.....').replace('$', '.')+"`... ]"
+                ' ', '.').replace('<br/>', '.....').replace('$', '.') + "`... ]"
             observe_win.append(print_something_really_funny)
         # 在前端打印些好玩的东西
         stat_str = ''.join([f'`{mutable[thread_index][2]}`: {obs}\n\n'
                             if not done else f'`{mutable[thread_index][2]}`\n\n'
                             for thread_index, done, obs in zip(range(len(worker_done)), worker_done, observe_win)])
         # 在前端打印些好玩的东西
-        chatbot[-1] = [chatbot[-1][0], f'多线程操作已经开始，完成情况: \n\n{stat_str}' + ''.join(['.']*(cnt % 10+1))]
+        chatbot[-1] = [chatbot[-1][0], f'多线程操作已经开始，完成情况: \n\n{stat_str}' + ''.join(['.'] * (cnt % 10 + 1))]
         yield from update_ui(chatbot=chatbot, history=[])  # 刷新界面
         if all(worker_done):
             executor.shutdown()
@@ -306,6 +319,7 @@ def breakdown_txt_to_satisfy_token_limit(txt, get_token_fn, limit):
             lines = txt_tocut.split('\n')
             estimated_line_cut = limit / get_token_fn(txt_tocut) * len(lines)
             estimated_line_cut = int(estimated_line_cut)
+            cnt = 0
             for cnt in reversed(range(estimated_line_cut)):
                 if must_break_at_empty_line:
                     if lines[cnt] != "":
@@ -322,6 +336,7 @@ def breakdown_txt_to_satisfy_token_limit(txt, get_token_fn, limit):
             result = [prev]
             result.extend(cut(post, must_break_at_empty_line))
             return result
+
     try:
         return cut(txt, must_break_at_empty_line=True)
     except RuntimeError:
@@ -337,6 +352,7 @@ def force_breakdown(txt, limit, get_token_fn):
             return txt[:i], txt[i:]
     return "Tiktoken未知错误", "Tiktoken未知错误"
 
+
 def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit):
     # 递归
     def cut(txt_tocut, must_break_at_empty_line, break_anyway=False):
@@ -365,6 +381,7 @@ def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit):
             result = [prev]
             result.extend(cut(post, must_break_at_empty_line, break_anyway=break_anyway))
             return result
+
     try:
         # 第1次尝试，将双空行（\n\n）作为切分点
         return cut(txt, must_break_at_empty_line=True)
@@ -387,7 +404,6 @@ def breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn, limit):
                     return cut(txt, must_break_at_empty_line=False, break_anyway=True)
 
 
-
 def read_and_clean_pdf_text(fp):
     """
     这个函数用于分割pdf，用了很多trick，逻辑较乱，效果奇好
@@ -417,6 +433,7 @@ def read_and_clean_pdf_text(fp):
     fb = 2  # Index 2 框框
     REMOVE_FOOT_NOTE = True  # 是否丢弃掉 不是正文的内容 （比正文字体小，如参考文献、脚注、图注等）
     REMOVE_FOOT_FFSIZE_PERCENT = 0.95  # 小于正文的？时，判定为不是正文（有些文章的正文部分字体大小不是100%统一的，有肉眼不可见的小变化）
+
     def primary_ffsize(l):
         """
         提取文本块主字体
@@ -427,11 +444,11 @@ def read_and_clean_pdf_text(fp):
             fsize_statiscs[wtf['size']] += len(wtf['text'])
         return max(fsize_statiscs, key=fsize_statiscs.get)
 
-    def ffsize_same(a,b):
+    def ffsize_same(a, b):
         """
         提取字体大小是否近似相等
         """
-        return abs((a-b)/max(a,b)) < 0.02
+        return abs((a - b) / max(a, b)) < 0.02
 
     with fitz.open(fp) as doc:
         meta_txt = []
@@ -454,7 +471,8 @@ def read_and_clean_pdf_text(fp):
                         for wtf in l['spans']:  # for l in t['lines']:
                             meta_span.append([wtf['text'], wtf['size'], len(wtf['text'])])
                     # meta_line.append(["NEW_BLOCK", pf])
-            # 块元提取                           for each word segment with in line                       for each line         cross-line words                          for each block
+            # 块元提取                           for each word segment with in line                       for each line
+            # cross-line words                          for each block
             meta_txt.extend([" ".join(["".join([wtf['text'] for wtf in l['spans']]) for l in t['lines']]).replace(
                 '- ', '') for t in text_areas['blocks'] if 'lines' in t])
             meta_font.extend([np.mean([np.mean([wtf['size'] for wtf in l['spans']])
@@ -482,18 +500,19 @@ def read_and_clean_pdf_text(fp):
             if REMOVE_FOOT_NOTE:
                 if meta_line[index][fs] <= give_up_fize_threshold:
                     continue
-            if ffsize_same(meta_line[index][fs], meta_line[index-1][fs]):
+            if ffsize_same(meta_line[index][fs], meta_line[index - 1][fs]):
                 # 尝试识别段落
-                if meta_line[index][fc].endswith('.') and\
-                    (meta_line[index-1][fc] != 'NEW_BLOCK') and \
-                    (meta_line[index][fb][2] - meta_line[index][fb][0]) < (meta_line[index-1][fb][2] - meta_line[index-1][fb][0]) * 0.7:
+                if meta_line[index][fc].endswith('.') and \
+                        (meta_line[index - 1][fc] != 'NEW_BLOCK') and \
+                        (meta_line[index][fb][2] - meta_line[index][fb][0]) < (
+                        meta_line[index - 1][fb][2] - meta_line[index - 1][fb][0]) * 0.7:
                     sec[-1] += line[fc]
                     sec[-1] += "\n\n"
                 else:
                     sec[-1] += " "
                     sec[-1] += line[fc]
             else:
-                if (index+1 < len(meta_line)) and \
+                if (index + 1 < len(meta_line)) and \
                         meta_line[index][fs] > main_fsize:
                     # 单行 + 字体大
                     mega_sec.append(copy.deepcopy(sec))
@@ -501,7 +520,7 @@ def read_and_clean_pdf_text(fp):
                     sec.append("# " + line[fc])
                 else:
                     # 尝试识别section
-                    if meta_line[index-1][fs] > meta_line[index][fs]:
+                    if meta_line[index - 1][fs] > meta_line[index][fs]:
                         sec.append("\n" + line[fc])
                     else:
                         sec.append(line[fc])
@@ -520,13 +539,15 @@ def read_and_clean_pdf_text(fp):
                 if len(block_txt) < 100:
                     meta_txt[index] = '\n'
             return meta_txt
+
         meta_txt = 把字符太少的块清除为回车(meta_txt)
 
         def 清理多余的空行(meta_txt):
             for index in reversed(range(1, len(meta_txt))):
-                if meta_txt[index] == '\n' and meta_txt[index-1] == '\n':
+                if meta_txt[index] == '\n' and meta_txt[index - 1] == '\n':
                     meta_txt.pop(index)
             return meta_txt
+
         meta_txt = 清理多余的空行(meta_txt)
 
         def 合并小写开头的段落块(meta_txt):
@@ -537,16 +558,18 @@ def read_and_clean_pdf_text(fp):
                     return True
                 else:
                     return False
+
             for _ in range(100):
                 for index, block_txt in enumerate(meta_txt):
                     if starts_with_lowercase_word(block_txt):
-                        if meta_txt[index-1] != '\n':
-                            meta_txt[index-1] += ' '
+                        if meta_txt[index - 1] != '\n':
+                            meta_txt[index - 1] += ' '
                         else:
-                            meta_txt[index-1] = ''
-                        meta_txt[index-1] += meta_txt[index]
+                            meta_txt[index - 1] = ''
+                        meta_txt[index - 1] += meta_txt[index]
                         meta_txt[index] = '\n'
             return meta_txt
+
         meta_txt = 合并小写开头的段落块(meta_txt)
         meta_txt = 清理多余的空行(meta_txt)
 
@@ -588,9 +611,10 @@ def get_files_from_everything(txt, type): # type='.md'
         from toolbox import get_conf
         proxies, = get_conf('proxies')
         r = requests.get(txt, proxies=proxies)
-        with open('./gpt_log/temp'+type, 'wb+') as f: f.write(r.content)
+        with open('./gpt_log/temp' + type, 'wb+') as f:
+            f.write(r.content)
         project_folder = './gpt_log/'
-        file_manifest = ['./gpt_log/temp'+type]
+        file_manifest = ['./gpt_log/temp' + type]
     elif txt.endswith(type):
         # 直接给定文件
         file_manifest = [txt]
@@ -598,7 +622,7 @@ def get_files_from_everything(txt, type): # type='.md'
     elif os.path.exists(txt):
         # 本地路径，递归搜索
         project_folder = txt
-        file_manifest = [f for f in glob.glob(f'{project_folder}/**/*'+type, recursive=True)]
+        file_manifest = [f for f in glob.glob(f'{project_folder}/**/*' + type, recursive=True)]
         if len(file_manifest) == 0:
             success = False
     else:
@@ -609,8 +633,6 @@ def get_files_from_everything(txt, type): # type='.md'
     return success, file_manifest, project_folder
 
 
-
-
 def Singleton(cls):
     _instance = {}
 
@@ -642,7 +664,6 @@ class knowledge_archive_interface():
 
         return self.text2vec_large_chinese
 
-
     def feed_archive(self, file_manifest, id="default"):
         self.threadLock.acquire()
         # import uuid
@@ -655,7 +676,7 @@ class knowledge_archive_interface():
             history=[],
             one_conent="",
             one_content_segmentation="",
-            text2vec = self.get_chinese_text2vec(),
+            text2vec=self.get_chinese_text2vec(),
         )
         self.threadLock.release()
 
@@ -677,23 +698,24 @@ class knowledge_archive_interface():
                 history=[],
                 one_conent="",
                 one_content_segmentation="",
-                text2vec = self.get_chinese_text2vec(),
+                text2vec=self.get_chinese_text2vec(),
             )
         VECTOR_SEARCH_SCORE_THRESHOLD = 0
         VECTOR_SEARCH_TOP_K = 4
         CHUNK_SIZE = 512
         resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
-            query = txt,
-            vs_path = self.kai_path,
+            query=txt,
+            vs_path=self.kai_path,
             score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
             vector_search_top_k=VECTOR_SEARCH_TOP_K,
             chunk_conent=True,
             chunk_size=CHUNK_SIZE,
-            text2vec = self.get_chinese_text2vec(),
+            text2vec=self.get_chinese_text2vec(),
         )
         self.threadLock.release()
         return resp, prompt
 
+
 def try_install_deps(deps):
     for dep in deps:
         import subprocess, sys

crazy_functions/latex_utils.py

@@ -203,6 +203,7 @@ def merge_tex_files_(project_foler, main_file, mode):
                 c = fx.read()
         else:  
             # e.g., \input{srcs/07_appendix}
+            assert os.path.exists(fp+'.tex'), f'即找不到{fp}，也找不到{fp}.tex，Tex源文件缺失！'
             with open(fp+'.tex', 'r', encoding='utf-8', errors='replace') as fx:
                 c = fx.read()
         c = merge_tex_files_(project_foler, c, mode)
@@ -449,10 +450,9 @@ class LatexPaperSplit():
     """
     def __init__(self) -> None:
         self.nodes = None
-        self.msg = "{\\scriptsize\\textbf{警告：该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成，" + \
+        self.msg = "*{\\scriptsize\\textbf{警告：该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成，" + \
             "版权归原文作者所有。翻译内容可靠性无保障，请仔细鉴别并以原文为准。" + \
-            "项目Github地址: \\url{https://github.com/binary-husky/gpt_academic/}。" + \
-            "项目在线体验地址: \\url{https://chatpaper.org}。"
+            "项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
         # 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加REAME中的QQ联系开发者）
         self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响，禁止移除或修改此警告。}}\\\\" 
 

crazy_functions/图片生成.py

@@ -27,8 +27,10 @@ def gen_image(llm_kwargs, prompt, resolution="256x256"):
     }
     response = requests.post(url, headers=headers, json=data, proxies=proxies)
     print(response.content)
+    try:
         image_url = json.loads(response.content.decode('utf8'))['data'][0]['url']
-
+    except:
+        raise RuntimeError(response.content.decode())
     # 文件保存到本地
     r = requests.get(image_url, proxies=proxies)
     file_path = 'gpt_log/image_gen/'

crazy_functions/读文章写摘要.py

@@ -1,17 +1,19 @@
-from toolbox import update_ui
 from toolbox import CatchException, report_execption, write_results_to_file
+from toolbox import update_ui
 from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+
 fast_debug = False
 
 
 def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
-    import time, glob, os
+    import time
+    import os
     print('begin analysis on:', file_manifest)
     for index, fp in enumerate(file_manifest):
         with open(fp, 'r', encoding='utf-8', errors='replace') as f:
             file_content = f.read()
 
-        prefix = "接下来请你逐文件分析下面的论文文件，概括其内容" if index==0 else ""
+        prefix = "接下来请你逐文件分析下面的论文文件，概括其内容" if index == 0 else ""
         i_say = prefix + f'请对下面的文章片段用中文做一个概述，文件名是{os.path.relpath(fp, project_folder)}，文章内容是 ```{file_content}```'
         i_say_show_user = prefix + f'[{index}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}'
         chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
@@ -20,10 +22,13 @@ def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
         if not fast_debug:
             msg = '正常'
             # ** gpt request **
-            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, llm_kwargs, chatbot, history=[], sys_prompt=system_prompt)   # 带超时倒计时
+            gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, llm_kwargs,
+                                                                               chatbot, history=[],
+                                                                               sys_prompt=system_prompt)  # 带超时倒计时
 
             chatbot[-1] = (i_say_show_user, gpt_say)
-            history.append(i_say_show_user); history.append(gpt_say)
+            history.append(i_say_show_user);
+            history.append(gpt_say)
             yield from update_ui(chatbot=chatbot, history=history, msg=msg)  # 刷新界面
             if not fast_debug: time.sleep(2)
 
@@ -35,33 +40,39 @@ def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
     if not fast_debug:
         msg = '正常'
         # ** gpt request **
-        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say, llm_kwargs, chatbot, history=history, sys_prompt=system_prompt)   # 带超时倒计时
+        gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say, llm_kwargs, chatbot,
+                                                                           history=history,
+                                                                           sys_prompt=system_prompt)  # 带超时倒计时
 
         chatbot[-1] = (i_say, gpt_say)
-        history.append(i_say); history.append(gpt_say)
+        history.append(i_say)
+        history.append(gpt_say)
         yield from update_ui(chatbot=chatbot, history=history, msg=msg)  # 刷新界面
         res = write_results_to_file(history)
         chatbot.append(("完成了吗？", res))
         yield from update_ui(chatbot=chatbot, history=history, msg=msg)  # 刷新界面
 
 
-
 @CatchException
-def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
+def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, system_prompt, web_port, history=None):
+    # history = []    # 清空历史，以免输入溢出
+    if history is None:
         history = []  # 清空历史，以免输入溢出
-    import glob, os
+    import glob
+    import os
     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}")
+        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
     file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]  # + \
     # [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
     # [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
     if len(file_manifest) == 0:
-        report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
+        report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
         yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
         return
     yield from 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)

crazy_functions/辅助回答.py

@@ -0,0 +1,28 @@
+# encoding: utf-8
+# @Time   : 2023/4/19
+# @Author : Spike
+# @Descr   :
+from toolbox import update_ui
+from toolbox import CatchException, report_execption, write_results_to_file
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+
+
+@CatchException
+def 猜你想问(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
+    if txt:
+        show_say = txt
+        prompt = txt+'\n回答完问题后，再列出用户可能提出的三个问题。'
+    else:
+        prompt = history[-1]+"\n分析上述回答，再列出用户可能提出的三个问题。"
+        show_say = '分析上述回答，再列出用户可能提出的三个问题。'
+    gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
+        inputs=prompt,
+        inputs_show_user=show_say,
+        llm_kwargs=llm_kwargs,
+        chatbot=chatbot,
+        history=history,
+        sys_prompt=system_prompt
+    )
+    chatbot[-1] = (show_say, gpt_say)
+    history.extend([show_say, gpt_say])
+    yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面

docs/use_azure.md

@@ -96,6 +96,15 @@
 
 ● 部署名（不是模型名）
 
+# 修改 config.py
+
+```
+AZURE_ENDPOINT = "填入终结点"
+AZURE_API_KEY = "填入azure openai api的密钥"
+AZURE_API_VERSION = "2023-05-15"  # 默认使用 2023-05-15 版本，无需修改
+AZURE_ENGINE = "填入部署名"
+
+```
 # API的使用
 
 接下来就是具体怎么使用API了，还是可以参考官方文档：[快速入门 - 开始通过 Azure OpenAI 服务使用 ChatGPT 和 GPT-4 - Azure OpenAI Service | Microsoft Learn](https://learn.microsoft.com/zh-cn/azure/cognitive-services/openai/chatgpt-quickstart?pivots=programming-language-python)

main.py

@@ -1,5 +1,4 @@
 import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
-from pathlib import Path
 
 def main():
     import gradio as gr
@@ -7,8 +6,8 @@ def main():
     from request_llm.bridge_all import predict
     from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
     # 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
-    proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY, AVAIL_LLM_MODELS = \
-        get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY', 'AVAIL_LLM_MODELS')
+    proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = \
+        get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
 
     # 如果WEB_PORT是-1, 则随机选取WEB端口
     PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
@@ -16,7 +15,7 @@ def main():
 
     from check_proxy import get_current_version
     initial_prompt = "Serve me as a writing and programming assistant."
-    title_html = f"<h1 align=\"center\">ChatGPT 学术优化 网页测试版 {get_current_version()}</h1>"
+    title_html = f"<h1 align=\"center\">ChatGPT 学术优化 {get_current_version()}</h1>"
     description =  """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic)，感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
 
     # 问询记录, python 版本建议3.9+（越新越好）
@@ -53,21 +52,7 @@ def main():
         CHATBOT_HEIGHT /= 2
 
     cancel_handles = []
-    # Read your Baidu statistics code from the file
-    baidu_stats_code = Path('./sites/baidu_stats.html').read_text()
     with gr.Blocks(title="ChatGPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
-        # Insert your Baidu statistics code here
-        gradio_original_template_fn = gr.routes.templates.TemplateResponse
-
-        def gradio_new_template_fn(*args, **kwargs):
-            res = gradio_original_template_fn(*args, **kwargs)
-            res.body = res.body.replace(b'</html>', f'{baidu_stats_code}</html>'.encode("utf8"))
-            res.init_headers()
-            return res
-
-        gr.routes.templates.TemplateResponse = gradio_new_template_fn  # override gradio template
-
-        # Insert Title
         gr.HTML(title_html)
         cookies = gr.State({'api_key': API_KEY, 'llm_model': LLM_MODEL})
         with gr_L1():
@@ -86,13 +71,7 @@ def main():
                         stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
                         clearBtn = gr.Button("清除", variant="secondary", visible=False); clearBtn.style(size="sm")
                     with gr.Row():
-                        status = gr.Markdown(f"""Tips: 1. 按Enter提交, 按Shift+Enter换行；2. 当前模型: {LLM_MODEL} \n {proxy_info}.
-                                             3. 请注意隐私保护和遵守法律法规；
-                                             4. 请勿使用本服务进行违法犯罪活动；
-                                             5. 我和qingxu都希望能够为大家提供一个好的**学术工具**，希望大家不要攻击和滥用本服务；
-                                             6. 本服务还存在各种bug，如果发现bug，欢迎加群反馈或者发issue告诉我们；
-                                             7. 希望大家能结合ChatPaper的速读，找到需要精读的，再用本工具的全文翻译，实现快速知识摄取。
-                                             """)
+                        status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}")
                 with gr.Accordion("基础功能区", open=True) as area_basic_fn:
                     with gr.Row():
                         for k in functional:
@@ -125,7 +104,7 @@ def main():
                     system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
                     top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
                     temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
-                    max_length_sl = gr.Slider(minimum=256, maximum=4096, value=512, step=1, interactive=True, label="Local LLM MaxLength",)
+                    max_length_sl = gr.Slider(minimum=256, maximum=8192, value=4096, step=1, interactive=True, label="Local LLM MaxLength",)
                     checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "底部输入区", "输入清除键", "插件参数区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
                     md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
 
@@ -165,6 +144,11 @@ def main():
         resetBtn2.click(lambda: ([], [], "已重置"), None, [chatbot, history, status])
         clearBtn.click(lambda: ("",""), None, [txt, txt2])
         clearBtn2.click(lambda: ("",""), None, [txt, txt2])
+        if AUTO_CLEAR_TXT:
+            submitBtn.click(lambda: ("",""), None, [txt, txt2])
+            submitBtn2.click(lambda: ("",""), None, [txt, txt2])
+            txt.submit(lambda: ("",""), None, [txt, txt2])
+            txt2.submit(lambda: ("",""), None, [txt, txt2])
         # 基础功能区的回调函数注册
         for k in functional:
             if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
@@ -188,7 +172,6 @@ def main():
                 ret.update({plugin_advanced_arg: gr.update(visible=False, label=f"插件[{k}]不需要高级参数。")})
             return ret
         dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt, plugin_advanced_arg] )
-        
         def on_md_dropdown_changed(k):
             return {chatbot: gr.update(label="当前模型："+k)}
         md_dropdown.select(on_md_dropdown_changed, [md_dropdown], [chatbot] )
@@ -202,7 +185,6 @@ def main():
         # 终止按钮的回调函数注册
         stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
         stopBtn2.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
-        demo.load(on_dropdown_changed, inputs=gr.State("ArXiv Latex一键翻译（输入区给定arXiv ID）"), outputs=[switchy_bt, plugin_advanced_arg])
 
     # gradio的inbrowser触发不太稳定，回滚代码到原始的浏览器打开函数
     def auto_opentab_delay():

request_llm/bridge_all.py

@@ -152,7 +152,7 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
     },
 
-    # chatglm
+    # 将 chatglm 直接对齐到 chatglm2
     "chatglm": {
         "fn_with_ui": chatglm_ui,
         "fn_without_ui": chatglm_noui,
@@ -161,6 +161,15 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "chatglm2": {
+        "fn_with_ui": chatglm_ui,
+        "fn_without_ui": chatglm_noui,
+        "endpoint": None,
+        "max_token": 1024,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
+    
     # newbing
     "newbing": {
         "fn_with_ui": newbing_ui,

request_llm/bridge_chatglm.py

@@ -40,12 +40,12 @@ class GetGLMHandle(Process):
         while True:
             try:
                 if self.chatglm_model is None:
-                    self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
+                    self.chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
                     device, = get_conf('LOCAL_MODEL_DEVICE')
                     if device=='cpu':
-                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float()
+                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).float()
                     else:
-                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
+                        self.chatglm_model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).half().cuda()
                     self.chatglm_model = self.chatglm_model.eval()
                     break
                 else:

request_llm/bridge_chatgpt.py

@@ -28,6 +28,7 @@ proxies, API_KEY, TIMEOUT_SECONDS, MAX_RETRY = \
 timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
                   '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
 
+
 def get_full_error(chunk, stream_response):
     """
         获取完整的从Openai返回的报错
@@ -40,7 +41,9 @@ def get_full_error(chunk, stream_response):
     return chunk
 
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+def predict_no_ui_long_connection(
+        inputs, llm_kwargs, history=None, sys_prompt="", observe_window=None, console_slience=False
+):
     """
     发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免中途网线被掐。
     inputs：
@@ -54,45 +57,59 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
     observe_window = None：
         用于负责跨越线程传递已经输出的部分，大部分时候仅仅为了fancy的视觉效果，留空即可。observe_window[0]：观测窗。observe_window[1]：看门狗
     """
+    if history is None:
+        history = []
     watch_dog_patience = 5  # 看门狗的耐心, 设置5秒即可
     headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True)
     retry = 0
+    from bridge_all import model_info
     while True:
         try:
             # make a POST request to the API endpoint, stream=False
-            from .bridge_all import model_info
             endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
             response = requests.post(endpoint, headers=headers, proxies=proxies,
-                                    json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
-        except requests.exceptions.ReadTimeout as e:
+                                     json=payload, stream=True, timeout=TIMEOUT_SECONDS)
+            stream_response = response.iter_lines()
+            break
+        except (requests.exceptions.ReadTimeout, requests.exceptions.ConnectionError):
             retry += 1
             traceback.print_exc()
-            if retry > MAX_RETRY: raise TimeoutError
-            if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
+            if retry > MAX_RETRY:
+                raise TimeoutError
+            if MAX_RETRY != 0:
+                print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
+        except Exception as e:
+            print(f"出现异常：{e}")
+            raise e
 
-    stream_response =  response.iter_lines()
     result = ''
     while True:
-        try: chunk = next(stream_response).decode()
+        try:
+            chunk = next(stream_response).decode()
         except StopIteration: 
             break
-        except requests.exceptions.ConnectionError:
-            chunk = next(stream_response).decode() # 失败了，重试一次？再失败就没办法了。
-        if len(chunk)==0: continue
+        # except requests.exceptions.ConnectionError:
+        #     chunk = next(stream_response).decode()  # 失败了，重试一次？再失败就没办法了。
+        if len(chunk) == 0:
+            continue
         if not chunk.startswith('data:'): 
             error_msg = get_full_error(chunk.encode('utf8'), stream_response).decode()
             if "reduce the length" in error_msg:
                 raise ConnectionAbortedError("OpenAI拒绝了请求:" + error_msg)
             else:
                 raise RuntimeError("OpenAI拒绝了请求：" + error_msg)
-        if ('data: [DONE]' in chunk): break # api2d 正常完成
+        if 'data: [DONE]' in chunk:
+            break  # api2d 正常完成
         json_data = json.loads(chunk.lstrip('data:'))['choices'][0]
         delta = json_data["delta"]
-        if len(delta) == 0: break
-        if "role" in delta: continue
+        if len(delta) == 0:
+            break
+        if "role" in delta:
+            continue
         if "content" in delta: 
             result += delta["content"]
-            if not console_slience: print(delta["content"], end='')
+            if not console_slience:
+                print(delta["content"], end='')
             if observe_window is not None: 
                 # 观测窗，把已经获取的数据显示出去
                 if len(observe_window) >= 1: observe_window[0] += delta["content"]
@@ -100,7 +117,8 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
                 if len(observe_window) >= 2:  
                     if (time.time()-observe_window[1]) > watch_dog_patience:
                         raise RuntimeError("用户取消了程序。")
-        else: raise RuntimeError("意外Json结构："+delta)
+        else:
+            raise RuntimeError("意外Json结构："+delta)
     if json_data['finish_reason'] == 'length':
         raise ConnectionAbortedError("正常结束，但显示Token不足，导致输出不完整，请削减单次输入的文本量。")
     return result
@@ -228,6 +246,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                     yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
                     return
 
+
 def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     """
     整合所有信息，选择LLM模型，生成http请求，为发送请求做准备
@@ -247,23 +266,19 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     messages = [{"role": "system", "content": system_prompt}]
     if conversation_cnt:
         for index in range(0, 2*conversation_cnt, 2):
-            what_i_have_asked = {}
-            what_i_have_asked["role"] = "user"
-            what_i_have_asked["content"] = history[index]
-            what_gpt_answer = {}
-            what_gpt_answer["role"] = "assistant"
-            what_gpt_answer["content"] = history[index+1]
+            what_i_have_asked = {"role": "user", "content": history[index]}
+            what_gpt_answer = {"role": "assistant", "content": history[index + 1]}
             if what_i_have_asked["content"] != "":
-                if what_gpt_answer["content"] == "": continue
-                if what_gpt_answer["content"] == timeout_bot_msg: continue
+                if what_gpt_answer["content"] == "":
+                    continue
+                if what_gpt_answer["content"] == timeout_bot_msg:
+                    continue
                 messages.append(what_i_have_asked)
                 messages.append(what_gpt_answer)
             else:
                 messages[-1]['content'] = what_gpt_answer['content']
 
-    what_i_ask_now = {}
-    what_i_ask_now["role"] = "user"
-    what_i_ask_now["content"] = inputs
+    what_i_ask_now = {"role": "user", "content": inputs}
     messages.append(what_i_ask_now)
 
     payload = {
@@ -278,8 +293,8 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     }
     try:
         print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........")
-    except:
-        print('输入中可能存在乱码。')
-    return headers,payload
+    except Exception as e:
+        print(f'输入中可能存在乱码。抛出异常: {e}')
+    return headers, payload
 
 

requirements.txt

@@ -1,4 +1,4 @@
-./docs/gradio-3.32.2-py3-none-any.whl
+gradio>=3.33.1
 tiktoken>=0.3.3
 requests[socks]
 transformers
@@ -16,3 +16,5 @@ openai
 numpy
 arxiv
 rich
+langchain
+zh_langchain

sites/baidu_stats.html

@@ -1,10 +0,0 @@
-<!-- baidu_stats.html -->
-<script>
-var _hmt = _hmt || [];
-(function() {
-  var hm = document.createElement("script");
-  hm.src = "https://hm.baidu.com/hm.js?208673d55832a94b9bbe10b1f4e70c09";
-  var s = document.getElementsByTagName("script")[0];
-  s.parentNode.insertBefore(hm, s);
-})();
-</script>

toolbox.py

@@ -21,6 +21,7 @@ pj = os.path.join
 ========================================================================
 """
 
+
 class ChatBotWithCookies(list):
     def __init__(self, cookie):
         self._cookies = cookie
@@ -71,11 +72,13 @@ def update_ui(chatbot, history, msg='正常', **kwargs):  # 刷新界面
     assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时，可用clear将其清空，然后用for+append循环重新赋值。"
     yield chatbot.get_cookies(), chatbot, history, msg
 
+
 def update_ui_lastest_msg(lastmsg, chatbot, history, delay=1):  # 刷新界面
     """
     刷新用户界面
     """
-    if len(chatbot) == 0: chatbot.append(["update_ui_last_msg", lastmsg])
+    if len(chatbot) == 0:
+        chatbot.append(["update_ui_last_msg", lastmsg])
     chatbot[-1] = list(chatbot[-1])
     chatbot[-1][-1] = lastmsg
     yield from update_ui(chatbot=chatbot, history=history)
@@ -83,24 +86,25 @@ def update_ui_lastest_msg(lastmsg, chatbot, history, delay=1):  # 刷新界面
 
 
 def trimmed_format_exc():
-    import os, traceback
-    str = traceback.format_exc()
+    import os
+    import traceback
+    _str = traceback.format_exc()
     current_path = os.getcwd()
     replace_path = "."
-    return str.replace(current_path, replace_path)
+    return _str.replace(current_path, replace_path)
+
 
 def CatchException(f):
     """
     装饰器函数，捕捉函数f中的异常并封装到一个生成器中返回，并显示到聊天当中。
     """
-
     @wraps(f)
     def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT=-1):
         try:
             yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
         except Exception as e:
             from check_proxy import check_proxy
-            from toolbox import get_conf
+            # from toolbox import get_conf  # 不需要导入本文件内容
             proxies, = get_conf('proxies')
             tb_str = '```\n' + trimmed_format_exc() + '```'
             if len(chatbot) == 0:
@@ -148,6 +152,7 @@ def HotReload(f):
 ========================================================================
 """
 
+
 def get_reduce_token_percent(text):
     """
         * 此函数未来将被弃用
@@ -207,8 +212,6 @@ def regular_txt_to_markdown(text):
     return text
 
 
-
-
 def report_execption(chatbot, history, a, b):
     """
     向chatbot中添加错误信息
@@ -238,6 +241,7 @@ def text_divide_paragraph(text):
         text = "</br>".join(lines)
         return pre + text + suf
 
+
 @lru_cache(maxsize=128) # 使用 lru缓存 加快转换速度
 def markdown_convertion(txt):
     """
@@ -440,6 +444,7 @@ def find_recent_files(directory):
 
     return recent_files
 
+
 def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
     # 将文件复制一份到下载区
     import shutil
@@ -452,6 +457,7 @@ def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
         else: current = []
         chatbot._cookies.update({'file_to_promote': [new_path] + current})
 
+
 def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
     """
     当文件被上传时的回调函数
@@ -505,17 +511,20 @@ def on_report_generated(cookies, files, chatbot):
     chatbot.append(['报告如何远程获取？', f'报告已经添加到右侧“文件上传区”（可能处于折叠状态），请查收。{file_links}'])
     return cookies, report_files, chatbot
 
+
 def is_openai_api_key(key):
     API_MATCH_ORIGINAL = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
     API_MATCH_AZURE = re.match(r"[a-zA-Z0-9]{32}$", key)
     return bool(API_MATCH_ORIGINAL) or bool(API_MATCH_AZURE)
 
+
 def is_api2d_key(key):
     if key.startswith('fk') and len(key) == 41:
         return True
     else:
         return False
 
+
 def is_any_api_key(key):
     if ',' in key:
         keys = key.split(',')
@@ -525,6 +534,7 @@ def is_any_api_key(key):
     else:
         return is_openai_api_key(key) or is_api2d_key(key)
 
+
 def what_keys(keys):
     avail_key_list = {'OpenAI Key':0, "API2D Key":0}
     key_list = keys.split(',')
@@ -539,6 +549,7 @@ def what_keys(keys):
 
     return f"检测到： OpenAI Key {avail_key_list['OpenAI Key']} 个，API2D Key {avail_key_list['API2D Key']} 个"
 
+
 def select_api_key(keys, llm_model):
     import random
     avail_key_list = []
@@ -558,6 +569,7 @@ def select_api_key(keys, llm_model):
     api_key = random.choice(avail_key_list) # 随机负载均衡
     return api_key
 
+
 def read_env_variable(arg, default_value):
     """
     环境变量可以是 `GPT_ACADEMIC_CONFIG`(优先)，也可以直接是`CONFIG`
@@ -612,6 +624,7 @@ def read_env_variable(arg, default_value):
     print亮绿(f"[ENV_VAR] 成功读取环境变量{arg}")
     return r
 
+
 @lru_cache(maxsize=128)
 def read_single_conf_with_lru_cache(arg):
     from colorful import print亮红, print亮绿, print亮蓝
@@ -676,6 +689,7 @@ class DummyWith():
     def __exit__(self, exc_type, exc_value, traceback):
         return
 
+
 def run_gradio_in_subpath(demo, auth, port, custom_path):
     """
     把gradio的运行地址更改到指定的二次路径上
@@ -770,6 +784,7 @@ def clip_history(inputs, history, tokenizer, max_token_limit):
 ========================================================================
 """
 
+
 def zip_folder(source_folder, dest_folder, zip_name):
     import zipfile
     import os
@@ -801,6 +816,7 @@ def zip_folder(source_folder, dest_folder, zip_name):
 
     print(f"Zip file created at {zip_file}")
 
+
 def zip_result(folder):
     import time
     t = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
@@ -811,6 +827,7 @@ def gen_time_str():
     import time
     return time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
 
+
 class ProxyNetworkActivate():
     """
     这段代码定义了一个名为TempProxy的空上下文管理器, 用于给一小段代码上代理
@@ -830,12 +847,14 @@ class ProxyNetworkActivate():
         if 'HTTPS_PROXY' in os.environ: os.environ.pop('HTTPS_PROXY')
         return
 
+
 def objdump(obj, file='objdump.tmp'):
     import pickle
     with open(file, 'wb+') as f:
         pickle.dump(obj, f)
     return
 
+
 def objload(file='objdump.tmp'):
     import pickle, os
     if not os.path.exists(file):