add context clip policy

Co-authored-by: 柯仕锋 <12029064@zju.edu.cn>

README.md

@@ -1,5 +1,5 @@
 > [!IMPORTANT]
-> `master主分支`最新动态(2025.2.4): 增加deepseek-r1支持  
+> `master主分支`最新动态(2025.3.2): 修复大量代码typo / 联网组件支持Jina的api / 增加deepseek-r1支持  
 > `frontier开发分支`最新动态(2024.12.9): 更新对话时间线功能，优化xelatex论文翻译  
 > `wiki文档`最新动态(2024.12.5): 更新ollama接入指南  
 >
@@ -8,7 +8,7 @@
 > 2024.10.10: 突发停电，紧急恢复了提供[whl包](https://drive.google.com/drive/folders/14kR-3V-lIbvGxri4AHc8TpiA1fqsw7SK?usp=sharing)的文件服务器  
 > 2024.5.1: 加入Doc2x翻译PDF论文的功能，[查看详情](https://github.com/binary-husky/gpt_academic/wiki/Doc2x)  
 > 2024.3.11: 全力支持Qwen、GLM、DeepseekCoder等中文大语言模型！ SoVits语音克隆模块，[查看详情](https://www.bilibili.com/video/BV1Rp421S7tF/) 
-> 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。本项目完全开源免费，您可通过订阅[在线服务](https://github.com/binary-husky/gpt_academic/wiki/online)的方式鼓励本项目的发展。
+> 2024.1.17: 安装依赖时，请选择`requirements.txt`中**指定的版本**。 安装命令：`pip install -r requirements.txt`。
 
 <br>
 
@@ -428,7 +428,6 @@ timeline LR
 1. `master` 分支: 主分支，稳定版
 2. `frontier` 分支: 开发分支，测试版
 3. 如何[接入其他大模型](request_llms/README.md)
-4. 访问GPT-Academic的[在线服务并支持我们](https://github.com/binary-husky/gpt_academic/wiki/online)
 
 ### V：参考与学习
 

config.py

@@ -7,11 +7,11 @@
     Configuration reading priority: environment variable > config_private.py > config.py
 """
 
-# [step 1-1]>> ( 接入GPT等模型 ) API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"。极少数情况下，还需要填写组织（格式如org-123456789abcdefghijklmno的），请向下翻，找 API_ORG 设置项
+# [step 1-1]>> ( 接入OpenAI模型家族 ) API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789"。极少数情况下，还需要填写组织（格式如org-123456789abcdefghijklmno的），请向下翻，找 API_ORG 设置项
 API_KEY = "在此处填写APIKEY"    # 可同时填写多个API-KEY，用英文逗号分割，例如API_KEY = "sk-openaikey1,sk-openaikey2,fkxxxx-api2dkey3,azure-apikey4"
 
-# [step 1-2]>> ( 接入通义 qwen-max ) 接入通义千问在线大模型，api-key获取地址 https://dashscope.console.aliyun.com/
-DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY
+# [step 1-2]>> ( 强烈推荐！接入通义家族 & 大模型服务平台百炼 ) 接入通义千问在线大模型，api-key获取地址 https://dashscope.console.aliyun.com/
+DASHSCOPE_API_KEY = "" # 阿里灵积云API_KEY（用于接入qwen-max，dashscope-qwen3-14b，dashscope-deepseek-r1等）
 
 # [step 1-3]>> ( 接入 deepseek-reasoner, 即 deepseek-r1 ) 深度求索(DeepSeek) API KEY，默认请求地址为"https://api.deepseek.com/v1/chat/completions"
 DEEPSEEK_API_KEY = ""
@@ -43,7 +43,10 @@ AVAIL_LLM_MODELS = ["qwen-max", "o1-mini", "o1-mini-2024-09-12", "o1", "o1-2024-
                     "gpt-3.5-turbo-1106", "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
                     "gpt-4", "gpt-4-32k", "azure-gpt-4", "glm-4", "glm-4v", "glm-3-turbo",
                     "gemini-1.5-pro", "chatglm3", "chatglm4",
-                    "deepseek-chat", "deepseek-coder", "deepseek-reasoner"
+                    "deepseek-chat", "deepseek-coder", "deepseek-reasoner", 
+                    "volcengine-deepseek-r1-250120", "volcengine-deepseek-v3-241226",
+                    "dashscope-deepseek-r1", "dashscope-deepseek-v3",
+                    "dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-32b",
                     ]
 
 EMBEDDING_MODEL = "text-embedding-3-small"
@@ -81,7 +84,7 @@ API_URL_REDIRECT = {}
 
 # 多线程函数插件中，默认允许多少路线程同时访问OpenAI。Free trial users的限制是每分钟3次，Pay-as-you-go users的限制是每分钟3500次
 # 一言以蔽之：免费（5刀）用户填3，OpenAI绑了信用卡的用户可以填 16 或者更高。提高限制请查询：https://platform.openai.com/docs/guides/rate-limits/overview
-DEFAULT_WORKER_NUM = 3
+DEFAULT_WORKER_NUM = 8
 
 
 # 色彩主题, 可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
@@ -103,6 +106,7 @@ AVAIL_FONTS = [
     "华文中宋(STZhongsong)",  
     "华文新魏(STXinwei)",  
     "华文隶书(STLiti)", 
+    # 备注：以下字体需要网络支持，您可以自定义任意您喜欢的字体，如下所示，需要满足的格式为 "字体昵称(字体英文真名@字体css下载链接)" 
     "思源宋体(Source Han Serif CN VF@https://chinese-fonts-cdn.deno.dev/packages/syst/dist/SourceHanSerifCN/result.css)",
     "月星楷(Moon Stars Kai HW@https://chinese-fonts-cdn.deno.dev/packages/moon-stars-kai/dist/MoonStarsKaiHW-Regular/result.css)",
     "珠圆体(MaokenZhuyuanTi@https://chinese-fonts-cdn.deno.dev/packages/mkzyt/dist/猫啃珠圆体/result.css)",
@@ -266,6 +270,10 @@ MOONSHOT_API_KEY = ""
 YIMODEL_API_KEY = ""
 
 
+# 接入火山引擎的在线大模型)，api-key获取地址 https://console.volcengine.com/ark/region:ark+cn-beijing/endpoint
+ARK_API_KEY = "00000000-0000-0000-0000-000000000000" # 火山引擎 API KEY
+
+
 # 紫东太初大模型 https://ai-maas.wair.ac.cn
 TAICHU_API_KEY = ""
 
@@ -343,6 +351,19 @@ NUM_CUSTOM_BASIC_BTN = 4
 DAAS_SERVER_URLS = [ f"https://niuziniu-biligpt{i}.hf.space/stream" for i in range(1,5) ]
 
 
+# 在互联网搜索组件中，负责将搜索结果整理成干净的Markdown
+JINA_API_KEY = ""
+
+
+# 是否自动裁剪上下文长度（是否启动，默认不启动）
+AUTO_CONTEXT_CLIP_ENABLE = False
+# 目标裁剪上下文的token长度（如果超过这个长度，则会自动裁剪）
+AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN = 30*1000
+# 无条件丢弃x以上的轮数
+AUTO_CONTEXT_MAX_ROUND = 64
+# 在裁剪上下文时，倒数第x次对话能“最多”保留的上下文token的比例占 AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN 的多少
+AUTO_CONTEXT_MAX_CLIP_RATIO = [0.80, 0.60, 0.45, 0.25, 0.20, 0.18, 0.16, 0.14, 0.12, 0.10, 0.08, 0.07, 0.06, 0.05, 0.04, 0.03, 0.02, 0.01]
+
 
 """
 --------------- 配置关联关系说明 ---------------

crazy_functional.py

@@ -113,7 +113,7 @@ def get_crazy_functions():
             "Group": "学术",
             "Color": "stop",
             "AsButton": True,
-            "Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
+            "Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
             "Function": HotReload(Latex翻译中文并重新编译PDF),  # 当注册Class后，Function旧接口仅会在“虚空终端”中起作用
             "Class": Arxiv_Localize,    # 新一代插件需要注册Class
         },
@@ -352,7 +352,7 @@ def get_crazy_functions():
             "ArgsReminder": r"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。 "
                             r"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: "
                             r'If the term "agent" is used in this section, it should be translated to "智能体". ',
-            "Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
+            "Info": "ArXiv论文精细翻译 | 输入参数arxiv论文的ID，比如1812.10695",
             "Function": HotReload(Latex翻译中文并重新编译PDF),  # 当注册Class后，Function旧接口仅会在“虚空终端”中起作用
             "Class": Arxiv_Localize,    # 新一代插件需要注册Class
         },
@@ -434,36 +434,6 @@ def get_crazy_functions():
         logger.error(trimmed_format_exc())
         logger.error("Load function plugin failed")
 
-    # 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（输入问题后点击该插件，需要访问谷歌）": {
-    #                 "Group": "对话",
-    #                 "Color": "stop",
-    #                 "AsButton": False,  # 加入下拉菜单中
-    #                 # "Info": "连接网络回答问题（需要访问谷歌）| 输入参数是一个问题",
-    #                 "Function": HotReload(连接网络回答问题),
-    #             }
-    #         }
-    #     )
-    #     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）": {
-    #                 "Group": "对话",
-    #                 "Color": "stop",
-    #                 "AsButton": False,  # 加入下拉菜单中
-    #                 "Info": "连接网络回答问题（需要访问中文Bing）| 输入参数是一个问题",
-    #                 "Function": HotReload(连接bing搜索回答问题),
-    #             }
-    #         }
-    #     )
-    # except:
-    #     logger.error(trimmed_format_exc())
-    #     logger.error("Load function plugin failed")
 
     try:
         from crazy_functions.SourceCode_Analyse import 解析任意code项目
@@ -771,6 +741,9 @@ def get_multiplex_button_functions():
         "常规对话":
             "",
 
+        "查互联网后回答":
+            "查互联网后回答",
+
         "多模型对话": 
             "询问多个GPT模型", # 映射到上面的 `询问多个GPT模型` 插件
 

crazy_functions/Conversation_To_File.py

@@ -172,7 +172,7 @@ def 载入对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
     user_request    当前用户的请求信息（IP地址等）
     """
     from crazy_functions.crazy_utils import get_files_from_everything
-    success, file_manifest, _ = get_files_from_everything(txt, type='.html')
+    success, file_manifest, _ = get_files_from_everything(txt, type='.html',chatbot=chatbot)
 
     if not success:
         if txt == "": txt = '空空如也的输入栏'

crazy_functions/Internet_GPT.py

@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
 from functools import lru_cache
 from itertools import zip_longest
 from check_proxy import check_proxy
-from toolbox import CatchException, update_ui, get_conf, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, get_conf, update_ui_latest_msg
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
 from request_llms.bridge_all import model_info
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -49,7 +49,7 @@ def search_optimizer(
     mutable = ["", time.time(), ""]
     llm_kwargs["temperature"] = 0.8
     try:
-        querys_json = predict_no_ui_long_connection(
+        query_json = predict_no_ui_long_connection(
             inputs=query,
             llm_kwargs=llm_kwargs,
             history=[],
@@ -57,31 +57,31 @@ def search_optimizer(
             observe_window=mutable,
         )
     except Exception:
-        querys_json = "1234"
+        query_json = "null"
     #* 尝试解码优化后的搜索结果
-    querys_json = re.sub(r"```json|```", "", querys_json)
+    query_json = re.sub(r"```json|```", "", query_json)
     try:
-        querys = json.loads(querys_json)
+        queries = json.loads(query_json)
     except Exception:
         #* 如果解码失败,降低温度再试一次
         try:
             llm_kwargs["temperature"] = 0.4
-            querys_json = predict_no_ui_long_connection(
+            query_json = predict_no_ui_long_connection(
                 inputs=query,
                 llm_kwargs=llm_kwargs,
                 history=[],
                 sys_prompt=sys_prompt,
                 observe_window=mutable,
             )
-            querys_json = re.sub(r"```json|```", "", querys_json)
-            querys = json.loads(querys_json)
+            query_json = re.sub(r"```json|```", "", query_json)
+            queries = json.loads(query_json)
         except Exception:
             #* 如果再次失败，直接返回原始问题
-            querys = [query]
+            queries = [query]
     links = []
     success = 0
     Exceptions = ""
-    for q in querys:
+    for q in queries:
         try:
             link = searxng_request(q, proxies, categories, searxng_url, engines=engines)
             if len(link) > 0:
@@ -175,10 +175,17 @@ def scrape_text(url, proxies) -> str:
     Returns:
         str: The scraped text
     """
+    from loguru import logger
     headers = {
         'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
         'Content-Type': 'text/plain',
     }
+
+    # 首先采用Jina进行文本提取
+    if get_conf("JINA_API_KEY"):
+        try: return jina_scrape_text(url)
+        except: logger.debug("Jina API 请求失败，回到旧方法")
+
     try:
         response = requests.get(url, headers=headers, proxies=proxies, timeout=8)
         if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
@@ -193,21 +200,39 @@ def scrape_text(url, proxies) -> str:
     text = "\n".join(chunk for chunk in chunks if chunk)
     return text
 
+
+def jina_scrape_text(url) -> str:
+    "jina_39727421c8fa4e4fa9bd698e5211feaaDyGeVFESNrRaepWiLT0wmHYJSh-d"
+    headers = {
+        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36',
+        'Content-Type': 'text/plain',
+        "X-Retain-Images": "none",
+        "Authorization": f'Bearer {get_conf("JINA_API_KEY")}'
+    }
+    response = requests.get("https://r.jina.ai/" + url, headers=headers, proxies=None, timeout=8)
+    if response.status_code != 200:
+        raise ValueError("Jina API 请求失败，开始尝试旧方法！" + response.text)
+    if response.encoding == "ISO-8859-1": response.encoding = response.apparent_encoding
+    result = response.text
+    result = result.replace("\\[", "[").replace("\\]", "]").replace("\\(", "(").replace("\\)", ")")
+    return response.text
+
+
 def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, chatbot):
     from toolbox import get_conf
     proxies = get_conf('proxies')
     categories = 'general'
     searxng_url = None  # 使用默认的searxng_url
     engines = None  # 使用默认的搜索引擎
-    yield from update_ui_lastest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
+    yield from update_ui_latest_msg(lastmsg=f"检索中: {prompt} ...", chatbot=chatbot, history=[], delay=1)
     urls = searxng_request(prompt, proxies, categories, searxng_url, engines=engines)
-    yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
+    yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站 ...", chatbot=chatbot, history=[], delay=1)
     if len(urls) == 0:
         return None
     max_search_result = 5   # 最多收纳多少个网页的结果
     history = []
     for index, url in enumerate(urls[:max_search_result]):
-        yield from update_ui_lastest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
+        yield from update_ui_latest_msg(lastmsg=f"依次访问搜索到的网站: {url['link']} ...", chatbot=chatbot, history=[], delay=1)
         res = scrape_text(url['link'], proxies)
         prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
         history.extend([prefix, res])
@@ -222,7 +247,7 @@ def internet_search_with_analysis_prompt(prompt, analysis_prompt, llm_kwargs, ch
         llm_kwargs=llm_kwargs,
         history=history,
         sys_prompt="请从搜索结果中抽取信息，对最相关的两个搜索结果进行总结，然后回答问题。",
-        console_slience=False,
+        console_silence=False,
     )
     return gpt_say
 
@@ -246,23 +271,52 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         urls = search_optimizer(txt, proxies, optimizer_history, llm_kwargs, optimizer, categories, searxng_url, engines)
     history = []
     if len(urls) == 0:
-        chatbot.append((f"结论：{txt}",
-                        "[Local Message] 受到限制，无法从searxng获取信息！请尝试更换搜索引擎。"))
+        chatbot.append((f"结论：{txt}", "[Local Message] 受到限制，无法从searxng获取信息！请尝试更换搜索引擎。"))
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         return
 
     # ------------- < 第2步：依次访问网页 > -------------
+    from concurrent.futures import ThreadPoolExecutor
+    from textwrap import dedent
     max_search_result = 5   # 最多收纳多少个网页的结果
     if optimizer == "开启(增强)":
         max_search_result = 8
-    chatbot.append(["联网检索中 ...", None])
-    for index, url in enumerate(urls[:max_search_result]):
-        res = scrape_text(url['link'], proxies)
-        prefix = f"第{index}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
-        history.extend([prefix, res])
-        res_squeeze = res.replace('\n', '...')
-        chatbot[-1] = [prefix + "\n\n" + res_squeeze[:500] + "......", None]
-        yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+    template = dedent("""
+        <details>
+        <summary>{TITLE}</summary>
+        <div class="search_result">{URL}</div>
+        <div class="search_result">{CONTENT}</div>
+        </details>
+    """)
+
+    buffer = ""
+
+    # 创建线程池
+    with ThreadPoolExecutor(max_workers=5) as executor:
+        # 提交任务到线程池
+        futures = []
+        for index, url in enumerate(urls[:max_search_result]):
+            future = executor.submit(scrape_text, url['link'], proxies)
+            futures.append((index, future, url))
+
+        # 处理完成的任务
+        for index, future, url in futures:
+            # 开始
+            prefix = f"正在加载 第{index+1}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
+            string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT="正在加载，请稍后 ......")
+            yield from update_ui_latest_msg(lastmsg=(buffer + string_structure), chatbot=chatbot, history=history, delay=0.1)  # 刷新界面
+
+            # 获取结果
+            res = future.result()
+
+            # 显示结果
+            prefix = f"第{index+1}份搜索结果 [源自{url['source'][0]}搜索] （{url['title'][:25]}）："
+            string_structure = template.format(TITLE=prefix, URL=url['link'], CONTENT=res[:1000] + "......")
+            buffer += string_structure
+
+            # 更新历史
+            history.extend([prefix, res])
+            yield from update_ui_latest_msg(lastmsg=buffer, chatbot=chatbot, history=history, delay=0.1)  # 刷新界面
 
     # ------------- < 第3步：ChatGPT综合 > -------------
     if (optimizer != "开启(增强)"):

crazy_functions/Internet_GPT_Wrap.py

@@ -38,11 +38,12 @@ class NetworkGPT_Wrap(GptAcademicPluginTemplate):
         }
         return gui_definition
 
-    def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
+    def execute(txt, llm_kwargs, plugin_kwargs:dict, chatbot, history, system_prompt, user_request):
         """
         执行插件
         """
-        if plugin_kwargs["categories"] == "网页": plugin_kwargs["categories"] = "general"
-        if plugin_kwargs["categories"] == "学术论文": plugin_kwargs["categories"] = "science"
+        if plugin_kwargs.get("categories", None) == "网页": plugin_kwargs["categories"] = "general"
+        elif plugin_kwargs.get("categories", None) == "学术论文": plugin_kwargs["categories"] = "science"
+        else: plugin_kwargs["categories"] = "general"
         yield from 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
 

crazy_functions/Latex_Function.py

@@ -1,5 +1,5 @@
 from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone, check_repeat_upload, map_file_to_sha256
-from toolbox import CatchException, report_exception, update_ui_lastest_msg, zip_result, gen_time_str
+from toolbox import CatchException, report_exception, update_ui_latest_msg, zip_result, gen_time_str
 from functools import partial
 from loguru import logger
 
@@ -41,7 +41,7 @@ def switch_prompt(pfg, mode, more_requirement):
     return inputs_array, sys_prompt_array
 
 
-def desend_to_extracted_folder_if_exist(project_folder):
+def descend_to_extracted_folder_if_exist(project_folder):
     """
     Descend into the extracted folder if it exists, otherwise return the original folder.
 
@@ -130,7 +130,7 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
 
     if not txt.startswith('https://arxiv.org/abs/'):
         msg = f"解析arxiv网址失败, 期望格式例如: https://arxiv.org/abs/1707.06690。实际得到格式: {url_}。"
-        yield from update_ui_lastest_msg(msg, chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(msg, chatbot=chatbot, history=history)  # 刷新界面
         return msg, None
     # <-------------- set format ------------->
     arxiv_id = url_.split('/abs/')[-1]
@@ -156,16 +156,16 @@ def arxiv_download(chatbot, history, txt, allow_cache=True):
         return False
 
     if os.path.exists(dst) and allow_cache:
-        yield from update_ui_lastest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(f"调用缓存 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
         success = True
     else:
-        yield from update_ui_lastest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(f"开始下载 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
         success = fix_url_and_download()
-        yield from update_ui_lastest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
+        yield from update_ui_latest_msg(f"下载完成 {arxiv_id}", chatbot=chatbot, history=history)  # 刷新界面
 
 
     if not success:
-        yield from update_ui_lastest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
+        yield from update_ui_latest_msg(f"下载失败 {arxiv_id}", chatbot=chatbot, history=history)
         raise tarfile.ReadError(f"论文下载失败 {arxiv_id}")
 
     # <-------------- extract file ------------->
@@ -288,7 +288,7 @@ def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, histo
         return
 
     # <-------------- if is a zip/tar file ------------->
-    project_folder = desend_to_extracted_folder_if_exist(project_folder)
+    project_folder = descend_to_extracted_folder_if_exist(project_folder)
 
     # <-------------- move latex project away from temp folder ------------->
     from shared_utils.fastapi_server import validate_path_safety
@@ -365,7 +365,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
     try:
         txt, arxiv_id = yield from arxiv_download(chatbot, history, txt, allow_cache)
     except tarfile.ReadError as e:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             "无法自动下载该论文的Latex源码，请前往arxiv打开此论文下载页面，点other Formats，然后download source手动下载latex源码包。接下来调用本地Latex翻译插件即可。",
             chatbot=chatbot, history=history)
         return
@@ -404,7 +404,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
         return
 
     # <-------------- if is a zip/tar file ------------->
-    project_folder = desend_to_extracted_folder_if_exist(project_folder)
+    project_folder = descend_to_extracted_folder_if_exist(project_folder)
 
     # <-------------- move latex project away from temp folder ------------->
     from shared_utils.fastapi_server import validate_path_safety
@@ -518,7 +518,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
     # repeat, project_folder = check_repeat_upload(file_manifest[0], hash_tag)
 
     # if repeat:
-    #     yield from update_ui_lastest_msg(f"发现重复上传，请查收结果（压缩包）...", chatbot=chatbot, history=history)
+    #     yield from update_ui_latest_msg(f"发现重复上传，请查收结果（压缩包）...", chatbot=chatbot, history=history)
     #     try:
     #         translate_pdf = [f for f in glob.glob(f'{project_folder}/**/merge_translate_zh.pdf', recursive=True)][0]
     #         promote_file_to_downloadzone(translate_pdf, rename_file=None, chatbot=chatbot)
@@ -531,7 +531,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
     #         report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"发现重复上传，但是无法找到相关文件")
     #         yield from update_ui(chatbot=chatbot, history=history)
     # else:
-    #     yield from update_ui_lastest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
+    #     yield from update_ui_latest_msg(f"未发现重复上传", chatbot=chatbot, history=history)
 
     # <-------------- convert pdf into tex ------------->
     chatbot.append([f"解析项目: {txt}", "正在将PDF转换为tex项目，请耐心等待..."])
@@ -543,7 +543,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
         return False
 
     # <-------------- translate latex file into Chinese ------------->
-    yield from update_ui_lastest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
+    yield from update_ui_latest_msg("正在tex项目将翻译为中文...", chatbot=chatbot, history=history)
     file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)]
     if len(file_manifest) == 0:
         report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.tex文件: {txt}")
@@ -551,7 +551,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
         return
 
     # <-------------- if is a zip/tar file ------------->
-    project_folder = desend_to_extracted_folder_if_exist(project_folder)
+    project_folder = descend_to_extracted_folder_if_exist(project_folder)
 
     # <-------------- move latex project away from temp folder ------------->
     from shared_utils.fastapi_server import validate_path_safety
@@ -571,7 +571,7 @@ def PDF翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, h
                                     switch_prompt=_switch_prompt_)
 
     # <-------------- compile PDF ------------->
-    yield from update_ui_lastest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
+    yield from update_ui_latest_msg("正在将翻译好的项目tex项目编译为PDF...", chatbot=chatbot, history=history)
     success = yield from 编译Latex(chatbot, history, main_file_original='merge',
                                 main_file_modified='merge_translate_zh', mode='translate_zh',
                                 work_folder_original=project_folder, work_folder_modified=project_folder,

crazy_functions/Latex_Project_Polish.py

@@ -1,3 +1,4 @@
+from shared_utils.fastapi_server import validate_path_safety
 from toolbox import update_ui, trimmed_format_exc, promote_file_to_downloadzone, get_log_folder
 from toolbox import CatchException, report_exception, write_history_to_file, zip_folder
 from loguru import logger
@@ -155,6 +156,7 @@ def Latex英文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
     import glob, os
     if os.path.exists(txt):
         project_folder = txt
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "": txt = '空空如也的输入栏'
         report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
@@ -193,6 +195,7 @@ def Latex中文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
     import glob, os
     if os.path.exists(txt):
         project_folder = txt
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "": txt = '空空如也的输入栏'
         report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
@@ -229,6 +232,7 @@ def Latex英文纠错(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
     import glob, os
     if os.path.exists(txt):
         project_folder = txt
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "": txt = '空空如也的输入栏'
         report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")

crazy_functions/Markdown_Translate.py

@@ -1,5 +1,6 @@
 import glob, shutil, os, re
 from loguru import logger
+from shared_utils.fastapi_server import validate_path_safety
 from toolbox import update_ui, trimmed_format_exc, gen_time_str
 from toolbox import CatchException, report_exception, get_log_folder
 from toolbox import write_history_to_file, promote_file_to_downloadzone
@@ -118,7 +119,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
     yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
 
-def get_files_from_everything(txt, preference=''):
+def get_files_from_everything(txt, preference='', chatbox=None):
     if txt == "": return False, None, None
     success = True
     if txt.startswith('http'):
@@ -146,9 +147,11 @@ def get_files_from_everything(txt, preference=''):
         # 直接给定文件
         file_manifest = [txt]
         project_folder = os.path.dirname(txt)
+        validate_path_safety(project_folder, chatbot.get_user())
     elif os.path.exists(txt):
         # 本地路径，递归搜索
         project_folder = txt
+        validate_path_safety(project_folder, chatbot.get_user())
         file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.md', recursive=True)]
     else:
         project_folder = None
@@ -177,7 +180,7 @@ def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
         return
     history = []    # 清空历史，以免输入溢出
 
-    success, file_manifest, project_folder = get_files_from_everything(txt, preference="Github")
+    success, file_manifest, project_folder = get_files_from_everything(txt, preference="Github", chatbox=chatbot)
 
     if not success:
         # 什么都没有

crazy_functions/PDF_Translate.py

@@ -1,5 +1,5 @@
 from toolbox import CatchException, check_packages, get_conf
-from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion
 from toolbox import trimmed_format_exc_markdown
 from crazy_functions.crazy_utils import get_files_from_everything
 from crazy_functions.pdf_fns.parse_pdf import get_avail_grobid_url
@@ -26,7 +26,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
 
     # 清空历史，以免输入溢出
     history = []
-    success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf')
+    success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf', chatbot=chatbot)
 
     # 检测输入参数，如没有给定输入参数，直接退出
     if (not success) and txt == "": txt = '空空如也的输入栏。提示：请先上传文件（把PDF文件拖入对话）。'
@@ -57,9 +57,9 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
             yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
             return
 
-    if method == "ClASSIC":
+    if method == "Classic":
         # ------- 第三种方法，早期代码，效果不理想 -------
-        yield from update_ui_lastest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
+        yield from update_ui_latest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
         yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
         return
 
@@ -77,7 +77,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         if grobid_url is not None:
             yield from 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url)
             return
-        yield from update_ui_lastest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
+        yield from update_ui_latest_msg("GROBID服务不可用，请检查config中的GROBID_URL。作为替代，现在将执行效果稍差的旧版代码。", chatbot, history, delay=3)
         yield from 解析PDF_简单拆解(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
         return
 

crazy_functions/PDF_Translate_Wrap.py

@@ -19,7 +19,7 @@ class PDF_Tran(GptAcademicPluginTemplate):
             "additional_prompt":
                 ArgProperty(title="额外提示词", description="例如：对专有名词、翻译语气等方面的要求", default_value="", type="string").model_dump_json(), # 高级参数输入区，自动同步
             "pdf_parse_method":
-                ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "ClASSIC"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
+                ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "Classic"], description="无", default_value="GROBID", type="dropdown").model_dump_json(),
         }
         return gui_definition
 

crazy_functions/Rag_Interface.py

@@ -4,7 +4,7 @@ from typing import List
 from shared_utils.fastapi_server import validate_path_safety
 
 from toolbox import report_exception
-from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
 from shared_utils.fastapi_server import validate_path_safety
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
@@ -92,7 +92,7 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
         chatbot.append([txt, f'正在清空 ({current_context}) ...'])
         yield from update_ui(chatbot=chatbot, history=history)  # 刷新界面
         rag_worker.purge_vector_store()
-        yield from update_ui_lastest_msg('已清空', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_latest_msg('已清空', chatbot, history, delay=0)  # 刷新界面
         return
 
     # 3. Normal Q&A processing
@@ -109,10 +109,10 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
 
     # 5. If input is clipped, add input to vector store before retrieve
     if input_is_clipped_flag:
-        yield from update_ui_lastest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_latest_msg('检测到长输入, 正在向量化 ...', chatbot, history, delay=0)  # 刷新界面
         # Save input to vector store
         rag_worker.add_text_to_vector_store(txt_origin)
-        yield from update_ui_lastest_msg('向量化完成 ...', chatbot, history, delay=0)  # 刷新界面
+        yield from update_ui_latest_msg('向量化完成 ...', chatbot, history, delay=0)  # 刷新界面
 
         if len(txt_origin) > REMEMBER_PREVIEW:
             HALF = REMEMBER_PREVIEW // 2
@@ -142,7 +142,7 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
     )
 
     # 8. Remember Q&A
-    yield from update_ui_lastest_msg(
+    yield from update_ui_latest_msg(
         model_say + '</br></br>' + f'对话记忆中, 请稍等 ({current_context}) ...',
         chatbot, history, delay=0.5
     )
@@ -150,4 +150,4 @@ def Rag问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, u
     history.extend([i_say, model_say])
 
     # 9. Final UI Update
-    yield from update_ui_lastest_msg(model_say, chatbot, history, delay=0, msg=tip)
+    yield from update_ui_latest_msg(model_say, chatbot, history, delay=0, msg=tip)

crazy_functions/Social_Helper.py

@@ -1,5 +1,5 @@
 import pickle, os, random
-from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, get_conf, get_log_folder, update_ui_latest_msg
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -9,7 +9,7 @@ from loguru import logger
 from typing import List
 
 
-SOCIAL_NETWOK_WORKER_REGISTER = {}
+SOCIAL_NETWORK_WORKER_REGISTER = {}
 
 class SocialNetwork():
     def __init__(self):
@@ -78,7 +78,7 @@ class SocialNetworkWorker(SaveAndLoad):
             for f in friend.friends_list: 
                 self.add_friend(f)
             msg = f"成功添加{len(friend.friends_list)}个联系人: {str(friend.friends_list)}"
-            yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
+            yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=0)
 
 
     def run(self, txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
@@ -104,12 +104,12 @@ class SocialNetworkWorker(SaveAndLoad):
         }
 
         try:
-            Explaination = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
+            Explanation = '\n'.join([f'{k}: {v["explain_to_llm"]}' for k, v in self.tools_to_select.items()])
             class UserSociaIntention(BaseModel):
                 intention_type: str = Field(
                     description=
                         f"The type of user intention. You must choose from {self.tools_to_select.keys()}.\n\n" 
-                        f"Explaination:\n{Explaination}", 
+                        f"Explanation:\n{Explanation}", 
                     default="SocialAdvice"
                 )
             pydantic_cls_instance, err_msg = select_tool(
@@ -118,7 +118,7 @@ class SocialNetworkWorker(SaveAndLoad):
                 pydantic_cls=UserSociaIntention
             )
         except Exception as e:
-            yield from update_ui_lastest_msg(
+            yield from update_ui_latest_msg(
                 lastmsg=f"无法理解用户意图 {err_msg}", 
                 chatbot=chatbot, 
                 history=history, 
@@ -150,10 +150,10 @@ def I人助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt,
     # 1. we retrieve worker from global context
     user_name = chatbot.get_user()
     checkpoint_dir=get_log_folder(user_name, plugin_name='experimental_rag')
-    if user_name in SOCIAL_NETWOK_WORKER_REGISTER:
-        social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name]
+    if user_name in SOCIAL_NETWORK_WORKER_REGISTER:
+        social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name]
     else:
-        social_network_worker = SOCIAL_NETWOK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
+        social_network_worker = SOCIAL_NETWORK_WORKER_REGISTER[user_name] = SocialNetworkWorker(
             user_name, 
             llm_kwargs, 
             checkpoint_dir=checkpoint_dir, 

crazy_functions/SourceCode_Comment.py

@@ -1,5 +1,5 @@
 import os, copy, time
-from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_lastest_msg, get_conf, generate_file_link
+from toolbox import CatchException, report_exception, update_ui, zip_result, promote_file_to_downloadzone, update_ui_latest_msg, get_conf, generate_file_link
 from shared_utils.fastapi_server import validate_path_safety
 from crazy_functions.crazy_utils import input_clipping
 from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
@@ -117,7 +117,7 @@ def 注释源代码(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
                 logger.error(f"文件: {fp} 的注释结果未能成功")
         file_links = generate_file_link(preview_html_list)
 
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             f"当前任务: <br/>{'<br/>'.join(tasks)}.<br/>" + 
             f"剩余源文件数量: {remain}.<br/>" + 
             f"已完成的文件: {sum(worker_done)}.<br/>" + 

crazy_functions/VideoResource_GPT.py

@@ -7,7 +7,7 @@ from bs4 import BeautifulSoup
 from functools import lru_cache
 from itertools import zip_longest
 from check_proxy import check_proxy
-from toolbox import CatchException, update_ui, get_conf, promote_file_to_downloadzone, update_ui_lastest_msg, generate_file_link
+from toolbox import CatchException, update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
 from request_llms.bridge_all import model_info
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -46,7 +46,7 @@ def download_video(bvid, user_name, chatbot, history):
     # pause a while
     tic_time = 8
     for i in range(tic_time):
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"即将下载音频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。", 
             chatbot=chatbot, history=[], delay=1)
 
@@ -61,13 +61,13 @@ def download_video(bvid, user_name, chatbot, history):
     # preview
     preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files]
     file_links = generate_file_link(preview_list)
-    yield from update_ui_lastest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
     chatbot.append((None, f"即将下载视频。"))
 
     # pause a while
     tic_time = 16
     for i in range(tic_time):
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"即将下载视频。等待{tic_time-i}秒后自动继续, 点击“停止”键取消此操作。", 
             chatbot=chatbot, history=[], delay=1)
 
@@ -78,7 +78,7 @@ def download_video(bvid, user_name, chatbot, history):
     # preview
     preview_list = [promote_file_to_downloadzone(fp) for fp in downloaded_files_part2]
     file_links = generate_file_link(preview_list)
-    yield from update_ui_lastest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(f"已完成的文件: <br/>" + file_links, chatbot=chatbot, history=history, delay=0)
 
     # return
     return downloaded_files + downloaded_files_part2
@@ -110,7 +110,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
         # 结构化生成
         internet_search_keyword = user_wish
 
-        yield from update_ui_lastest_msg(lastmsg=f"发起互联网检索: {internet_search_keyword} ...", chatbot=chatbot, history=[], delay=1)
+        yield from update_ui_latest_msg(lastmsg=f"发起互联网检索: {internet_search_keyword} ...", chatbot=chatbot, history=[], delay=1)
         from crazy_functions.Internet_GPT import internet_search_with_analysis_prompt
         result = yield from internet_search_with_analysis_prompt(
             prompt=internet_search_keyword,
@@ -119,7 +119,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
             chatbot=chatbot
         )
 
-        yield from update_ui_lastest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
+        yield from update_ui_latest_msg(lastmsg=f"互联网检索结论: {result} \n\n 正在生成进一步检索方案 ...", chatbot=chatbot, history=[], delay=1)
         rf_req = dedent(f"""
         The user wish to get the following resource:
             {user_wish}
@@ -132,7 +132,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
         rf_req = dedent(f"""
         The user wish to get the following resource:
             {user_wish}
-        Generate reseach keywords (less than 5 keywords) accordingly.
+        Generate research keywords (less than 5 keywords) accordingly.
         """)
     gpt_json_io = GptJsonIO(Query)
     inputs = rf_req + gpt_json_io.format_instructions
@@ -146,12 +146,12 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
     yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
     # 获取候选资源
-    candadate_dictionary: dict =  get_video_resource(video_engine_keywords)
-    candadate_dictionary_as_str = json.dumps(candadate_dictionary, ensure_ascii=False, indent=4)
+    candidate_dictionary: dict =  get_video_resource(video_engine_keywords)
+    candidate_dictionary_as_str = json.dumps(candidate_dictionary, ensure_ascii=False, indent=4)
 
     # 展示候选资源
-    candadate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candadate_dictionary)])
-    chatbot.append((None, f"候选:\n\n{candadate_display}"))
+    candidate_display = "\n".join([f"{i+1}. {it['title']}" for i, it in enumerate(candidate_dictionary)])
+    chatbot.append((None, f"候选:\n\n{candidate_display}"))
     yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
 
     # 结构化生成
@@ -160,7 +160,7 @@ def 多媒体任务(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
         {user_wish}
 
     Select the most relevant and suitable video resource from the following search results:
-        {candadate_dictionary_as_str}
+        {candidate_dictionary_as_str}
 
     Note:
         1. The first several search video results are more likely to satisfy the user's wish.

crazy_functions/agent_fns/auto_agent.py

@@ -1,5 +1,5 @@
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
-from toolbox import report_exception, get_log_folder, update_ui_lastest_msg, Singleton
+from toolbox import report_exception, get_log_folder, update_ui_latest_msg, Singleton
 from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
 from crazy_functions.agent_fns.general import AutoGenGeneral
 

crazy_functions/agent_fns/echo_agent.py

@@ -8,7 +8,7 @@ class EchoDemo(PluginMultiprocessManager):
         while True:
             msg = self.child_conn.recv() # PipeCom
             if msg.cmd == "user_input":
-                # wait futher user input
+                # wait father user input
                 self.child_conn.send(PipeCom("show", msg.content))
                 wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.")
                 if not wait_success:

crazy_functions/agent_fns/general.py

@@ -27,7 +27,7 @@ def gpt_academic_generate_oai_reply(
         llm_kwargs=llm_config,
         history=history,
         sys_prompt=self._oai_system_message[0]['content'],
-        console_slience=True
+        console_silence=True
     )
     assumed_done = reply.endswith('\nTERMINATE')
     return True, reply

crazy_functions/agent_fns/python_comment_agent.py

@@ -10,7 +10,7 @@ from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_
 # TODO: 解决缩进问题
 
 find_function_end_prompt = '''
-Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to sperate functions, class functions etc.
+Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to separate functions, class functions etc.
 - Provide the line number where the first visible function ends.
 - Provide the line number where the next visible function begins.
 - If there are no other functions in this page, you should simply return the line number of the last line.
@@ -59,7 +59,7 @@ OUTPUT:
 
 
 
-revise_funtion_prompt = '''
+revise_function_prompt = '''
 You need to read the following code, and revise the source code ({FILE_BASENAME}) according to following instructions:
 1. You should analyze the purpose of the functions (if there are any).
 2. You need to add docstring for the provided functions (if there are any).
@@ -117,7 +117,7 @@ def zip_result(folder):
 '''
 
 
-revise_funtion_prompt_chinese = '''
+revise_function_prompt_chinese = '''
 您需要阅读以下代码，并根据以下说明修订源代码({FILE_BASENAME}):
 1. 如果源代码中包含函数的话, 你应该分析给定函数实现了什么功能
 2. 如果源代码中包含函数的话, 你需要为函数添加docstring, docstring必须使用中文
@@ -188,9 +188,9 @@ class PythonCodeComment():
         self.language = language
         self.observe_window_update = observe_window_update
         if self.language == "chinese":
-            self.core_prompt = revise_funtion_prompt_chinese
+            self.core_prompt = revise_function_prompt_chinese
         else:
-            self.core_prompt = revise_funtion_prompt
+            self.core_prompt = revise_function_prompt
         self.path = None
         self.file_basename = None
         self.file_brief = ""
@@ -222,7 +222,7 @@ class PythonCodeComment():
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_slience=True
+            console_silence=True
         )
 
         def extract_number(text):
@@ -316,7 +316,7 @@ class PythonCodeComment():
     def tag_code(self, fn, hint):
         code = fn
         _, n_indent = self.dedent(code)
-        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preseve them in the OUTPUT.)"
+        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preserve them in the OUTPUT.)"
         brief_reminder = "" if self.file_brief == "" else f"({self.file_basename} abstract: {self.file_brief})"
         hint_reminder = "" if hint is None else f"(Reminder: do not ignore or modify code such as `{hint}`, provide complete code in the OUTPUT.)"
         self.llm_kwargs['temperature'] = 0
@@ -333,7 +333,7 @@ class PythonCodeComment():
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_slience=True
+            console_silence=True
         )
 
         def get_code_block(reply):
@@ -400,7 +400,7 @@ class PythonCodeComment():
         return revised
 
     def begin_comment_source_code(self, chatbot=None, history=None):
-        # from toolbox import update_ui_lastest_msg
+        # from toolbox import update_ui_latest_msg
         assert self.path is not None
         assert '.py' in self.path   # must be python source code
         # write_target = self.path + '.revised.py'
@@ -409,10 +409,10 @@ class PythonCodeComment():
         # with open(self.path + '.revised.py', 'w+', encoding='utf8') as f:
         while True:
             try:
-                # yield from update_ui_lastest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
+                # yield from update_ui_latest_msg(f"({self.file_basename}) 正在读取下一段代码片段:\n", chatbot=chatbot, history=history, delay=0)
                 next_batch, line_no_start, line_no_end = self.get_next_batch()
                 self.observe_window_update(f"正在处理{self.file_basename} - {line_no_start}/{len(self.full_context)}\n")
-                # yield from update_ui_lastest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
+                # yield from update_ui_latest_msg(f"({self.file_basename}) 处理代码片段:\n\n{next_batch}", chatbot=chatbot, history=history, delay=0)
                 
                 hint = None
                 MAX_ATTEMPT = 2

crazy_functions/crazy_utils.py

@@ -1,7 +1,8 @@
 import os
 import threading
 from loguru import logger
-from shared_utils.char_visual_effect import scolling_visual_effect
+from shared_utils.fastapi_server import validate_path_safety
+from shared_utils.char_visual_effect import scrolling_visual_effect
 from toolbox import update_ui, get_conf, trimmed_format_exc, get_max_token, Singleton
 
 def input_clipping(inputs, history, max_token_limit, return_clip_flags=False):
@@ -256,7 +257,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
                 # 【第一种情况】：顺利完成
                 gpt_say = predict_no_ui_long_connection(
                     inputs=inputs, llm_kwargs=llm_kwargs, history=history,
-                    sys_prompt=sys_prompt, observe_window=mutable[index], console_slience=True
+                    sys_prompt=sys_prompt, observe_window=mutable[index], console_silence=True
                 )
                 mutable[index][2] = "已成功"
                 return gpt_say
@@ -326,7 +327,7 @@ 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 = f"[ ...`{scolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
+            print_something_really_funny = f"[ ...`{scrolling_visual_effect(mutable[thread_index][0], scroller_max_len)}`... ]"
             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'
@@ -389,11 +390,11 @@ def read_and_clean_pdf_text(fp):
         """
         提取文本块主字体
         """
-        fsize_statiscs = {}
+        fsize_statistics = {}
         for wtf in l['spans']:
-            if wtf['size'] not in fsize_statiscs: fsize_statiscs[wtf['size']] = 0
-            fsize_statiscs[wtf['size']] += len(wtf['text'])
-        return max(fsize_statiscs, key=fsize_statiscs.get)
+            if wtf['size'] not in fsize_statistics: fsize_statistics[wtf['size']] = 0
+            fsize_statistics[wtf['size']] += len(wtf['text'])
+        return max(fsize_statistics, key=fsize_statistics.get)
 
     def ffsize_same(a,b):
         """
@@ -433,11 +434,11 @@ def read_and_clean_pdf_text(fp):
 
         ############################## <第 2 步，获取正文主字体> ##################################
         try:
-            fsize_statiscs = {}
+            fsize_statistics = {}
             for span in meta_span:
-                if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
-                fsize_statiscs[span[1]] += span[2]
-            main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
+                if span[1] not in fsize_statistics: fsize_statistics[span[1]] = 0
+                fsize_statistics[span[1]] += span[2]
+            main_fsize = max(fsize_statistics, key=fsize_statistics.get)
             if REMOVE_FOOT_NOTE:
                 give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
         except:
@@ -539,7 +540,7 @@ def read_and_clean_pdf_text(fp):
     return meta_txt, page_one_meta
 
 
-def get_files_from_everything(txt, type): # type='.md'
+def get_files_from_everything(txt, type, chatbot=None): # type='.md'
     """
     这个函数是用来获取指定目录下所有指定类型（如.md）的文件，并且对于网络上的文件，也可以获取它。
     下面是对每个参数和返回值的说明：
@@ -551,6 +552,7 @@ def get_files_from_everything(txt, type): # type='.md'
     - file_manifest: 文件路径列表，里面包含以指定类型为后缀名的所有文件的绝对路径。
     - project_folder: 字符串，表示文件所在的文件夹路径。如果是网络上的文件，就是临时文件夹的路径。
     该函数详细注释已添加，请确认是否满足您的需要。
+    - chatbot 带Cookies的Chatbot类，为实现更多强大的功能做基础
     """
     import glob, os
 
@@ -573,9 +575,13 @@ def get_files_from_everything(txt, type): # type='.md'
         # 直接给定文件
         file_manifest = [txt]
         project_folder = os.path.dirname(txt)
+        if chatbot is not None:
+            validate_path_safety(project_folder, chatbot.get_user())
     elif os.path.exists(txt):
         # 本地路径，递归搜索
         project_folder = txt
+        if chatbot is not None:
+            validate_path_safety(project_folder, chatbot.get_user())
         file_manifest = [f for f in glob.glob(f'{project_folder}/**/*'+type, recursive=True)]
         if len(file_manifest) == 0:
             success = False
@@ -610,9 +616,9 @@ class nougat_interface():
 
 
     def NOUGAT_parse_pdf(self, fp, chatbot, history):
-        from toolbox import update_ui_lastest_msg
+        from toolbox import update_ui_latest_msg
 
-        yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度：正在排队, 等待线程锁...",
+        yield from update_ui_latest_msg("正在解析论文, 请稍候。进度：正在排队, 等待线程锁...",
                                          chatbot=chatbot, history=history, delay=0)
         self.threadLock.acquire()
         import glob, threading, os
@@ -620,7 +626,7 @@ class nougat_interface():
         dst = os.path.join(get_log_folder(plugin_name='nougat'), gen_time_str())
         os.makedirs(dst)
 
-        yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度：正在加载NOUGAT... （提示：首次运行需要花费较长时间下载NOUGAT参数）",
+        yield from update_ui_latest_msg("正在解析论文, 请稍候。进度：正在加载NOUGAT... （提示：首次运行需要花费较长时间下载NOUGAT参数）",
                                          chatbot=chatbot, history=history, delay=0)
         command = ['nougat', '--out', os.path.abspath(dst), os.path.abspath(fp)]
         self.nougat_with_timeout(command, cwd=os.getcwd(), timeout=3600)

crazy_functions/game_fns/game_ascii_art.py

@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, update_ui_latest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -13,7 +13,7 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
         else:
             if prompt.strip() == 'exit':
                 self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.)
                 return
             chatbot.append([prompt, ""])
         yield from update_ui(chatbot=chatbot, history=history)
@@ -31,12 +31,12 @@ class MiniGame_ASCII_Art(GptAcademicGameBaseState):
             self.cur_task = 'identify user guess'
             res = get_code_block(raw_res)
             history += ['', f'the answer is {self.obj}', inputs, res]
-            yield from update_ui_lastest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.)
 
         elif self.cur_task == 'identify user guess':
             if is_same_thing(self.obj, prompt, self.llm_kwargs):
                 self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.)
             else:
                 self.cur_task = 'identify user guess'
-                yield from update_ui_lastest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.)

crazy_functions/game_fns/game_interactive_story.py

@@ -63,7 +63,7 @@ prompts_terminate = """小说的前文回顾：
 """
 
 
-from toolbox import CatchException, update_ui, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, update_ui_latest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection
@@ -112,7 +112,7 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
             if prompt.strip() == 'exit' or prompt.strip() == '结束剧情':
                 # should we terminate game here?
                 self.delete_game = True
-                yield from update_ui_lastest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
+                yield from update_ui_latest_msg(lastmsg=f"游戏结束。", chatbot=chatbot, history=history, delay=0.)
                 return
             if '剧情收尾' in prompt:
                 self.cur_task = 'story_terminate'
@@ -137,8 +137,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
             )
             self.story.append(story_paragraph)
             # # 配图
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
 
             # # 构建后续剧情引导
             previously_on_story = ""
@@ -171,8 +171,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
             )
             self.story.append(story_paragraph)
             # # 配图
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
 
             # # 构建后续剧情引导
             previously_on_story = ""
@@ -204,8 +204,8 @@ class MiniGame_ResumeStory(GptAcademicGameBaseState):
                 chatbot, history_, self.sys_prompt_
             )
             # # 配图
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
-            yield from update_ui_lastest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>正在生成插图中 ...', chatbot=chatbot, history=history, delay=0.)
+            yield from update_ui_latest_msg(lastmsg=story_paragraph + '<br/>'+ self.generate_story_image(story_paragraph), chatbot=chatbot, history=history, delay=0.)
 
             # terminate game
             self.delete_game = True

crazy_functions/gen_fns/gen_fns_shared.py

@@ -2,7 +2,7 @@ import time
 import importlib
 from toolbox import trimmed_format_exc, gen_time_str, get_log_folder
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
-from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
+from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
 import multiprocessing
 
 def get_class_name(class_string):

crazy_functions/json_fns/pydantic_io.py

@@ -102,10 +102,10 @@ class GptJsonIO():
                 logging.info(f'Repairing json：{response}')
                 repair_prompt = self.generate_repair_prompt(broken_json = response, error=repr(e))
                 result = self.generate_output(gpt_gen_fn(repair_prompt, self.format_instructions))
-                logging.info('Repaire json success.')
+                logging.info('Repair json success.')
             except Exception as e:
                 # 没辙了，放弃治疗
-                logging.info('Repaire json fail.')
+                logging.info('Repair json fail.')
                 raise JsonStringError('Cannot repair json.', str(e))
         return result
 

crazy_functions/latex_fns/latex_actions.py

@@ -3,7 +3,7 @@ import re
 import shutil
 import numpy as np
 from loguru import logger
-from toolbox import update_ui, update_ui_lastest_msg, get_log_folder, gen_time_str
+from toolbox import update_ui, update_ui_latest_msg, get_log_folder, gen_time_str
 from toolbox import get_conf, promote_file_to_downloadzone
 from crazy_functions.latex_fns.latex_toolbox import PRESERVE, TRANSFORM
 from crazy_functions.latex_fns.latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
@@ -20,7 +20,7 @@ def split_subprocess(txt, project_folder, return_dict, opts):
     """
     break down latex file to a linked list,
     each node use a preserve flag to indicate whether it should
-    be proccessed by GPT.
+    be processed by GPT.
     """
     text = txt
     mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM
@@ -85,14 +85,14 @@ class LatexPaperSplit():
     """
     break down latex file to a linked list,
     each node use a preserve flag to indicate whether it should
-    be proccessed by GPT.
+    be processed by GPT.
     """
     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，" + \
             "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/}。"
-        # 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）
+        # 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README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。}}\\\\"
         self.title = "unknown"
         self.abstract = "unknown"
@@ -151,7 +151,7 @@ class LatexPaperSplit():
         """
         break down latex file to a linked list,
         each node use a preserve flag to indicate whether it should
-        be proccessed by GPT.
+        be processed by GPT.
         P.S. use multiprocessing to avoid timeout error
         """
         import multiprocessing
@@ -351,7 +351,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
     max_try = 32
     chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder}，如果程序停顿5分钟以上，请直接去该路径下取回翻译结果，或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
     chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
-    yield from update_ui_lastest_msg('编译已经开始...', chatbot, history)   # 刷新Gradio前端界面
+    yield from update_ui_latest_msg('编译已经开始...', chatbot, history)   # 刷新Gradio前端界面
     # 检查是否需要使用xelatex
     def check_if_need_xelatex(tex_path):
         try:
@@ -396,32 +396,32 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
             shutil.copyfile(may_exist_bbl, target_bbl)
 
         # https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
-        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
+        yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history)   # 刷新Gradio前端界面
         ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
 
-        yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
+        yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history)   # 刷新Gradio前端界面
         ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
 
         if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
             # 只有第二步成功，才能继续下面的步骤
-            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history)    # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history)    # 刷新Gradio前端界面
             if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
                 ok = compile_latex_with_timeout(f'bibtex  {main_file_original}.aux', work_folder_original)
             if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
                 ok = compile_latex_with_timeout(f'bibtex  {main_file_modified}.aux', work_folder_modified)
 
-            yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history)  # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history)  # 刷新Gradio前端界面
             ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
             ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
             ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_original), work_folder_original)
             ok = compile_latex_with_timeout(get_compile_command(compiler, main_file_modified), work_folder_modified)
 
             if mode!='translate_zh':
-                yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
+                yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
                 logger.info(    f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex  {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
                 ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex  {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex', os.getcwd())
 
-                yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
+                yield from update_ui_latest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history)   # 刷新Gradio前端界面
                 ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
                 ok = compile_latex_with_timeout(f'bibtex    merge_diff.aux', work_folder)
                 ok = compile_latex_with_timeout(get_compile_command(compiler, 'merge_diff'), work_folder)
@@ -435,13 +435,13 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
         results_ += f"原始PDF编译是否成功: {original_pdf_success};"
         results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
         results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
-        yield from update_ui_lastest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
+        yield from update_ui_latest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
 
         if diff_pdf_success:
             result_pdf = pj(work_folder_modified, f'merge_diff.pdf')    # get pdf path
             promote_file_to_downloadzone(result_pdf, rename_file=None, chatbot=chatbot)  # promote file to web UI
         if modified_pdf_success:
-            yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history)    # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'转化PDF编译已经成功, 正在尝试生成对比PDF, 请稍候 ...', chatbot, history)    # 刷新Gradio前端界面
             result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf') # get pdf path
             origin_pdf = pj(work_folder_original, f'{main_file_original}.pdf') # get pdf path
             if os.path.exists(pj(work_folder, '..', 'translation')):
@@ -472,7 +472,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
                 work_folder_modified=work_folder_modified,
                 fixed_line=fixed_line
             )
-            yield from update_ui_lastest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history)   # 刷新Gradio前端界面
+            yield from update_ui_latest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history)   # 刷新Gradio前端界面
             if not can_retry: break
 
     return False # 失败啦

crazy_functions/latex_fns/latex_toolbox.py

@@ -168,7 +168,7 @@ def set_forbidden_text(text, mask, pattern, flags=0):
 def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
     """
     Move area out of preserve area (make text editable for GPT)
-    count the number of the braces so as to catch compelete text area.
+    count the number of the braces so as to catch complete text area.
     e.g.
     \begin{abstract} blablablablablabla. \end{abstract}
     """
@@ -188,7 +188,7 @@ def reverse_forbidden_text(text, mask, pattern, flags=0, forbid_wrapper=True):
 def set_forbidden_text_careful_brace(text, mask, pattern, flags=0):
     """
     Add a preserve text area in this paper (text become untouchable for GPT).
-    count the number of the braces so as to catch compelete text area.
+    count the number of the braces so as to catch complete text area.
     e.g.
     \caption{blablablablabla\texbf{blablabla}blablabla.}
     """
@@ -214,7 +214,7 @@ def reverse_forbidden_text_careful_brace(
 ):
     """
     Move area out of preserve area (make text editable for GPT)
-    count the number of the braces so as to catch compelete text area.
+    count the number of the braces so as to catch complete text area.
     e.g.
     \caption{blablablablabla\texbf{blablabla}blablabla.}
     """
@@ -287,23 +287,23 @@ def find_main_tex_file(file_manifest, mode):
     在多Tex文档中，寻找主文件，必须包含documentclass，返回找到的第一个。
     P.S. 但愿没人把latex模板放在里面传进来 (6.25 加入判定latex模板的代码)
     """
-    canidates = []
+    candidates = []
     for texf in file_manifest:
         if os.path.basename(texf).startswith("merge"):
             continue
         with open(texf, "r", encoding="utf8", errors="ignore") as f:
             file_content = f.read()
         if r"\documentclass" in file_content:
-            canidates.append(texf)
+            candidates.append(texf)
         else:
             continue
 
-    if len(canidates) == 0:
+    if len(candidates) == 0:
         raise RuntimeError("无法找到一个主Tex文件（包含documentclass关键字）")
-    elif len(canidates) == 1:
-        return canidates[0]
-    else:  # if len(canidates) >= 2 通过一些Latex模板中常见（但通常不会出现在正文）的单词，对不同latex源文件扣分，取评分最高者返回
-        canidates_score = []
+    elif len(candidates) == 1:
+        return candidates[0]
+    else:  # if len(candidates) >= 2 通过一些Latex模板中常见（但通常不会出现在正文）的单词，对不同latex源文件扣分，取评分最高者返回
+        candidates_score = []
         # 给出一些判定模板文档的词作为扣分项
         unexpected_words = [
             "\\LaTeX",
@@ -316,19 +316,19 @@ def find_main_tex_file(file_manifest, mode):
             "reviewers",
         ]
         expected_words = ["\\input", "\\ref", "\\cite"]
-        for texf in canidates:
-            canidates_score.append(0)
+        for texf in candidates:
+            candidates_score.append(0)
             with open(texf, "r", encoding="utf8", errors="ignore") as f:
                 file_content = f.read()
                 file_content = rm_comments(file_content)
             for uw in unexpected_words:
                 if uw in file_content:
-                    canidates_score[-1] -= 1
+                    candidates_score[-1] -= 1
             for uw in expected_words:
                 if uw in file_content:
-                    canidates_score[-1] += 1
-        select = np.argmax(canidates_score)  # 取评分最高者返回
-        return canidates[select]
+                    candidates_score[-1] += 1
+        select = np.argmax(candidates_score)  # 取评分最高者返回
+        return candidates[select]
 
 
 def rm_comments(main_file):
@@ -374,7 +374,7 @@ def find_tex_file_ignore_case(fp):
 
 def merge_tex_files_(project_foler, main_file, mode):
     """
-    Merge Tex project recrusively
+    Merge Tex project recursively
     """
     main_file = rm_comments(main_file)
     for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
@@ -429,7 +429,7 @@ def find_title_and_abs(main_file):
 
 def merge_tex_files(project_foler, main_file, mode):
     """
-    Merge Tex project recrusively
+    Merge Tex project recursively
     P.S. 顺便把CTEX塞进去以支持中文
     P.S. 顺便把Latex的注释去除
     """

crazy_functions/media_fns/get_media.py

@@ -1,4 +1,4 @@
-from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_lastest_msg, generate_file_link
+from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link
 from shared_utils.docker_as_service_api import stream_daas
 from shared_utils.docker_as_service_api import DockerServiceApiComModel
 import random
@@ -25,7 +25,7 @@ def download_video(video_id, only_audio, user_name, chatbot, history):
         status_buf += "\n\n"
         status_buf += "DaaS file attach: \n\n"
         status_buf += str(output_manifest['server_file_attach'])
-        yield from update_ui_lastest_msg(status_buf, chatbot, history)
+        yield from update_ui_latest_msg(status_buf, chatbot, history)
 
     return output_manifest['server_file_attach']
 

crazy_functions/multi_stage/multi_stage_utils.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui_latest_msg, disable_auto_promotion
 from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError

crazy_functions/pdf_fns/parse_pdf.py

@@ -113,7 +113,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
             return [txt]
         else:
             # raw_token_num > TOKEN_LIMIT_PER_FRAGMENT
-            # find a smooth token limit to achieve even seperation
+            # find a smooth token limit to achieve even separation
             count = int(math.ceil(raw_token_num / TOKEN_LIMIT_PER_FRAGMENT))
             token_limit_smooth = raw_token_num // count + count
             return breakdown_text_to_satisfy_token_limit(txt, limit=token_limit_smooth, llm_model=llm_kwargs['llm_model'])

crazy_functions/pdf_fns/parse_pdf_grobid.py

@@ -1,6 +1,6 @@
 import os
 from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages
-from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
 from toolbox import write_history_to_file, promote_file_to_downloadzone, get_conf, extract_archive
 from crazy_functions.pdf_fns.parse_pdf import parse_pdf, translate_pdf
 

crazy_functions/pdf_fns/parse_pdf_via_doc2x.py

@@ -242,9 +242,7 @@ def 解析PDF_DOC2X_单文件(
         extract_archive(file_path=this_file_path, dest_dir=ex_folder)
 
         # edit markdown files
-        success, file_manifest, project_folder = get_files_from_everything(
-            ex_folder, type=".md"
-        )
+        success, file_manifest, project_folder = get_files_from_everything(ex_folder, type='.md', chatbot=chatbot)
         for generated_fp in file_manifest:
             # 修正一些公式问题
             with open(generated_fp, "r", encoding="utf8") as f:

crazy_functions/pdf_fns/parse_word.py

@@ -14,39 +14,39 @@ def extract_text_from_files(txt, chatbot, history):
         final_result(list):文本内容
         page_one(list):第一页内容/摘要
         file_manifest(list):文件路径
-        excption(string):需要用户手动处理的信息,如没出错则保持为空
+        exception(string):需要用户手动处理的信息,如没出错则保持为空
     """
 
     final_result = []
     page_one = []
     file_manifest = []
-    excption = ""
+    exception = ""
 
     if txt == "":
         final_result.append(txt)
-        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
+        return False, final_result, page_one, file_manifest, exception   #如输入区内容不是文件则直接返回输入区内容
 
     #查找输入区内容中的文件
-    file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf')
-    file_md,md_manifest,folder_md = get_files_from_everything(txt, '.md')
-    file_word,word_manifest,folder_word = get_files_from_everything(txt, '.docx')
-    file_doc,doc_manifest,folder_doc = get_files_from_everything(txt, '.doc')
+    file_pdf,pdf_manifest,folder_pdf = get_files_from_everything(txt, '.pdf', chatbot=chatbot)
+    file_md,md_manifest,folder_md = get_files_from_everything(txt, '.md', chatbot=chatbot)
+    file_word,word_manifest,folder_word = get_files_from_everything(txt, '.docx', chatbot=chatbot)
+    file_doc,doc_manifest,folder_doc = get_files_from_everything(txt, '.doc', chatbot=chatbot)
 
     if file_doc:
-        excption = "word"
-        return False, final_result, page_one, file_manifest, excption
+        exception = "word"
+        return False, final_result, page_one, file_manifest, exception
 
     file_num = len(pdf_manifest) + len(md_manifest) + len(word_manifest)
     if file_num == 0:
         final_result.append(txt)
-        return False, final_result, page_one, file_manifest, excption   #如输入区内容不是文件则直接返回输入区内容
+        return False, final_result, page_one, file_manifest, exception   #如输入区内容不是文件则直接返回输入区内容
 
     if file_pdf:
         try:    # 尝试导入依赖，如果缺少依赖，则给出安装建议
             import fitz
         except:
-            excption = "pdf"
-            return False, final_result, page_one, file_manifest, excption
+            exception = "pdf"
+            return False, final_result, page_one, file_manifest, exception
         for index, fp in enumerate(pdf_manifest):
             file_content, pdf_one = read_and_clean_pdf_text(fp) # （尝试）按照章节切割PDF
             file_content = file_content.encode('utf-8', 'ignore').decode()   # avoid reading non-utf8 chars
@@ -72,8 +72,8 @@ def extract_text_from_files(txt, chatbot, history):
         try:    # 尝试导入依赖，如果缺少依赖，则给出安装建议
             from docx import Document
         except:
-            excption = "word_pip"
-            return False, final_result, page_one, file_manifest, excption
+            exception = "word_pip"
+            return False, final_result, page_one, file_manifest, exception
         for index, fp in enumerate(word_manifest):
             doc = Document(fp)
             file_content = '\n'.join([p.text for p in doc.paragraphs])
@@ -82,4 +82,4 @@ def extract_text_from_files(txt, chatbot, history):
             final_result.append(file_content)
             file_manifest.append(os.path.relpath(fp, folder_word))
 
-    return True, final_result, page_one, file_manifest, excption
+    return True, final_result, page_one, file_manifest, exception

crazy_functions/vector_fns/vector_database.py

@@ -60,7 +60,7 @@ def similarity_search_with_score_by_vector(
         self, embedding: List[float], k: int = 4
 ) -> List[Tuple[Document, float]]:
 
-    def seperate_list(ls: List[int]) -> List[List[int]]:
+    def separate_list(ls: List[int]) -> List[List[int]]:
         lists = []
         ls1 = [ls[0]]
         for i in range(1, len(ls)):
@@ -82,7 +82,7 @@ def similarity_search_with_score_by_vector(
             continue
         _id = self.index_to_docstore_id[i]
         doc = self.docstore.search(_id)
-        if not self.chunk_conent:
+        if not self.chunk_content:
             if not isinstance(doc, Document):
                 raise ValueError(f"Could not find document for id {_id}, got {doc}")
             doc.metadata["score"] = int(scores[0][j])
@@ -104,12 +104,12 @@ def similarity_search_with_score_by_vector(
                         id_set.add(l)
             if break_flag:
                 break
-    if not self.chunk_conent:
+    if not self.chunk_content:
         return docs
     if len(id_set) == 0 and self.score_threshold > 0:
         return []
     id_list = sorted(list(id_set))
-    id_lists = seperate_list(id_list)
+    id_lists = separate_list(id_list)
     for id_seq in id_lists:
         for id in id_seq:
             if id == id_seq[0]:
@@ -132,7 +132,7 @@ class LocalDocQA:
     embeddings: object = None
     top_k: int = VECTOR_SEARCH_TOP_K
     chunk_size: int = CHUNK_SIZE
-    chunk_conent: bool = True
+    chunk_content: bool = True
     score_threshold: int = VECTOR_SEARCH_SCORE_THRESHOLD
 
     def init_cfg(self,
@@ -209,16 +209,16 @@ class LocalDocQA:
 
     # query      查询内容
     # vs_path    知识库路径
-    # chunk_conent   是否启用上下文关联
+    # chunk_content   是否启用上下文关联
     # score_threshold    搜索匹配score阈值
     # vector_search_top_k   搜索知识库内容条数，默认搜索5条结果
     # chunk_sizes    匹配单段内容的连接上下文长度
-    def get_knowledge_based_conent_test(self, query, vs_path, chunk_conent,
+    def get_knowledge_based_content_test(self, query, vs_path, chunk_content,
                                         score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
                                         vector_search_top_k=VECTOR_SEARCH_TOP_K, chunk_size=CHUNK_SIZE,
                                         text2vec=None):
         self.vector_store = FAISS.load_local(vs_path, text2vec)
-        self.vector_store.chunk_conent = chunk_conent
+        self.vector_store.chunk_content = chunk_content
         self.vector_store.score_threshold = score_threshold
         self.vector_store.chunk_size = chunk_size
 
@@ -241,7 +241,7 @@ class LocalDocQA:
 
 
 
-def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_conent, one_content_segmentation, text2vec):
+def construct_vector_store(vs_id, vs_path, files, sentence_size, history, one_content, one_content_segmentation, text2vec):
     for file in files:
         assert os.path.exists(file), "输入文件不存在：" + file
     import nltk
@@ -297,7 +297,7 @@ class knowledge_archive_interface():
             files=file_manifest,
             sentence_size=100,
             history=[],
-            one_conent="",
+            one_content="",
             one_content_segmentation="",
             text2vec = self.get_chinese_text2vec(),
         )
@@ -319,19 +319,19 @@ class knowledge_archive_interface():
                 files=[],
                 sentence_size=100,
                 history=[],
-                one_conent="",
+                one_content="",
                 one_content_segmentation="",
                 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(
+        resp, prompt = self.qa_handle.get_knowledge_based_content_test(
             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_content=True,
             chunk_size=CHUNK_SIZE,
             text2vec = self.get_chinese_text2vec(),
         )

crazy_functions/vt_fns/vt_call_plugin.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui_latest_msg, disable_auto_promotion
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
 import copy, json, pickle, os, sys, time
@@ -9,14 +9,14 @@ import copy, json, pickle, os, sys, time
 def read_avail_plugin_enum():
     from crazy_functional import get_crazy_functions
     plugin_arr = get_crazy_functions()
-    # remove plugins with out explaination
+    # remove plugins with out explanation
     plugin_arr = {k:v for k, v in plugin_arr.items() if ('Info' in v) and ('Function' in v)}
     plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)})
     prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2)
-    prompt = "\n\nThe defination of PluginEnum:\nPluginEnum=" + prompt
+    prompt = "\n\nThe definition of PluginEnum:\nPluginEnum=" + prompt
     return prompt, plugin_arr_dict, plugin_arr_dict_parse
 
 def wrap_code(txt):
@@ -55,7 +55,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000")
         reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most")
     # ⭐ ⭐ ⭐ 选择插件
-    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
     gpt_json_io = GptJsonIO(Plugin)
     gpt_json_io.format_instructions = "The format of your output should be a json that can be parsed by json.loads.\n"
     gpt_json_io.format_instructions += """Output example: {"plugin_selection":"F_1234", "reason_of_selection":"F_1234 plugin satisfy user requirement most"}\n"""
@@ -74,13 +74,13 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         msg += "请求的Prompt为：\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
         msg += "语言模型回复为：\n" + wrap_code(gpt_reply)
         msg += "\n但您可以尝试再试一次\n"
-        yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+        yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
     if plugin_sel.plugin_selection not in plugin_arr_dict_parse:
         msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。"
         msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件：\n" + wrap_code(gpt_reply)
         msg += "\n但您可以尝试再试一次\n"
-        yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+        yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
 
     # ⭐ ⭐ ⭐ 确认插件参数
@@ -90,7 +90,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         appendix_info = get_recent_file_prompt_support(chatbot)
 
     plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection]
-    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
     class PluginExplicit(BaseModel):
         plugin_selection: str = plugin_sel.plugin_selection
         plugin_arg: str = Field(description="The argument of the plugin.", default="")
@@ -109,6 +109,6 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
     fn = plugin['Function']
     fn_name = fn.__name__
     msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明：{plugin["Info"]}\n\n插件参数：{plugin_sel.plugin_arg}\n\n假如偏离了您的要求，按停止键终止。'
-    yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
+    yield from update_ui_latest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
     yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1)
     return

crazy_functions/vt_fns/vt_modify_config.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_lastest_msg, get_conf
+from toolbox import update_ui_latest_msg, get_conf
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO
 import copy, json, pickle, os, sys
@@ -9,7 +9,7 @@ import copy, json, pickle, os, sys
 def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
     ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
     if not ALLOW_RESET_CONFIG:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
             chatbot=chatbot, history=history, delay=2
         )
@@ -30,7 +30,7 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         new_option_value: str = Field(description="the new value of the option", default=None)
 
     # ⭐ ⭐ ⭐ 分析用户意图
-    yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
+    yield from update_ui_latest_msg(lastmsg=f"正在执行任务: {txt}\n\n读取新配置中", chatbot=chatbot, history=history, delay=0)
     gpt_json_io = GptJsonIO(ModifyConfigurationIntention)
     inputs = "Analyze how to change configuration according to following user input, answer me with json: \n\n" + \
              ">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
@@ -44,11 +44,11 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
 
     ok = (explicit_conf in txt)
     if ok:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}",
             chatbot=chatbot, history=history, delay=1
         )
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n新配置{explicit_conf}={user_intention.new_option_value}\n\n正在修改配置中",
             chatbot=chatbot, history=history, delay=2
         )
@@ -57,25 +57,25 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
         from toolbox import set_conf
         set_conf(explicit_conf, user_intention.new_option_value)
 
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n配置修改完成，重新页面即可生效。", chatbot=chatbot, history=history, delay=1
         )
     else:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"失败，如果需要配置{explicit_conf}，您需要明确说明并在指令中提到它。", chatbot=chatbot, history=history, delay=5
         )
 
 def modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
     ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
     if not ALLOW_RESET_CONFIG:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
             chatbot=chatbot, history=history, delay=2
         )
         return
 
     yield from modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
-    yield from update_ui_lastest_msg(
+    yield from update_ui_latest_msg(
         lastmsg=f"正在执行任务: {txt}\n\n配置修改完成，五秒后即将重启！若出现报错请无视即可。", chatbot=chatbot, history=history, delay=5
     )
     os.execl(sys.executable, sys.executable, *sys.argv)

crazy_functions/vt_fns/vt_state.py

@@ -5,7 +5,7 @@ class VoidTerminalState():
         self.reset_state()
 
     def reset_state(self):
-        self.has_provided_explaination = False
+        self.has_provided_explanation = False
 
     def lock_plugin(self, chatbot):
         chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'

crazy_functions/互动小游戏.py

@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, update_ui_lastest_msg
+from toolbox import CatchException, update_ui, update_ui_latest_msg
 from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from request_llms.bridge_all import predict_no_ui_long_connection

crazy_functions/函数动态生成.py

@@ -15,7 +15,7 @@ Testing:
 
 
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
-from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
+from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
 from crazy_functions.crazy_utils import input_clipping, try_install_deps
 from crazy_functions.gen_fns.gen_fns_shared import is_function_successfully_generated
@@ -27,7 +27,7 @@ import time
 import glob
 import multiprocessing
 
-templete = """
+template = """
 ```python
 import ...  # Put dependencies here, e.g. import numpy as np.
 
@@ -77,10 +77,10 @@ def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
 
     # 第二步
     prompt_compose = [
-        "If previous stage is successful, rewrite the function you have just written to satisfy following templete: \n",
-        templete
+        "If previous stage is successful, rewrite the function you have just written to satisfy following template: \n",
+        template
     ]
-    i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable templete. "
+    i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable template. "
     gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
         inputs=i_say, inputs_show_user=inputs_show_user,
         llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
@@ -164,18 +164,18 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
     if get_plugin_arg(plugin_kwargs, key="file_path_arg", default=False):
         file_path = get_plugin_arg(plugin_kwargs, key="file_path_arg", default=None)
         file_list.append(file_path)
-        yield from update_ui_lastest_msg(f"当前文件: {file_path}", chatbot, history, 1)
+        yield from update_ui_latest_msg(f"当前文件: {file_path}", chatbot, history, 1)
     elif have_any_recent_upload_files(chatbot):
         file_dir = get_recent_file_prompt_support(chatbot)
         file_list = glob.glob(os.path.join(file_dir, '**/*'), recursive=True)
-        yield from update_ui_lastest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
+        yield from update_ui_latest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
     else:
         chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
-        yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
+        yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
         return  # 2. 如果没有文件
     if len(file_list) == 0:
         chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
-        yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
+        yield from update_ui_latest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
         return  # 2. 如果没有文件
 
     # 读取文件
@@ -183,7 +183,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
 
     # 粗心检查
     if is_the_upload_folder(txt):
-        yield from update_ui_lastest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件，不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
+        yield from update_ui_latest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件，不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
         return
 
     # 开始干正事
@@ -195,7 +195,7 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
             code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
                 yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
             chatbot.append(["代码生成阶段结束", ""])
-            yield from update_ui_lastest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
+            yield from update_ui_latest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
             # ⭐ 分离代码块
             code = get_code_block(code)
             # ⭐ 检查模块
@@ -206,11 +206,11 @@ def 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
             if not traceback: traceback = trimmed_format_exc()
         # 处理异常
         if not traceback: traceback = trimmed_format_exc()
-        yield from update_ui_lastest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
+        yield from update_ui_latest_msg(f"第 {j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
 
     # 代码生成结束, 开始执行
     TIME_LIMIT = 15
-    yield from update_ui_lastest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
+    yield from update_ui_latest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
     manager = multiprocessing.Manager()
     return_dict = manager.dict()
 

crazy_functions/多智能体.py

@@ -8,7 +8,7 @@
 
 import time
 from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
-from toolbox import get_conf, select_api_key, update_ui_lastest_msg, Singleton
+from toolbox import get_conf, select_api_key, update_ui_latest_msg, Singleton
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
 from crazy_functions.crazy_utils import input_clipping, try_install_deps
 from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersistentClasses

crazy_functions/总结word文档.py

@@ -104,6 +104,8 @@ def 总结word文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr
     # 检测输入参数，如没有给定输入参数，直接退出
     if os.path.exists(txt):
         project_folder = txt
+        from shared_utils.fastapi_server import validate_path_safety
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "": txt = '空空如也的输入栏'
         report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")

crazy_functions/批量翻译PDF文档_NOUGAT.py

@@ -1,5 +1,5 @@
 from toolbox import CatchException, report_exception, get_log_folder, gen_time_str
-from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion
 from toolbox import write_history_to_file, promote_file_to_downloadzone
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
@@ -61,7 +61,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
     history = []
 
     from crazy_functions.crazy_utils import get_files_from_everything
-    success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf')
+    success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf', chatbot=chatbot)
     if len(file_manifest) > 0:
         # 尝试导入依赖，如果缺少依赖，则给出安装建议
         try:
@@ -73,7 +73,7 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
                              b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade nougat-ocr tiktoken```。")
             yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
             return
-    success_mmd, file_manifest_mmd, _ = get_files_from_everything(txt, type='.mmd')
+    success_mmd, file_manifest_mmd, _ = get_files_from_everything(txt, type='.mmd', chatbot=chatbot)
     success = success or success_mmd
     file_manifest += file_manifest_mmd
     chatbot.append(["文件列表：", ", ".join([e.split('/')[-1] for e in file_manifest])]);

crazy_functions/数学动画生成manim.py

@@ -166,7 +166,7 @@ class PointWithTrace(Scene):
 
 ```
 
-# do not use get_graph, this funciton is deprecated
+# do not use get_graph, this function is deprecated
 
 class ExampleFunctionGraph(Scene):
     def construct(self):

crazy_functions/理解PDF文档内容.py

@@ -87,6 +87,8 @@ def 理解PDF文档内容标准文件输入(txt, llm_kwargs, plugin_kwargs, chat
     # 检测输入参数，如没有给定输入参数，直接退出
     if os.path.exists(txt):
         project_folder = txt
+        from shared_utils.fastapi_server import validate_path_safety
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "":
             txt = '空空如也的输入栏'

crazy_functions/生成函数注释.py

@@ -39,6 +39,8 @@ def 批量生成函数注释(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
     import glob, os
     if os.path.exists(txt):
         project_folder = txt
+        from shared_utils.fastapi_server import validate_path_safety
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "": txt = '空空如也的输入栏'
         report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")

crazy_functions/生成多种Mermaid图表.py

@@ -324,16 +324,16 @@ def 生成多种Mermaid图表(
     if os.path.exists(txt):  # 如输入区无内容则直接解析历史记录
         from crazy_functions.pdf_fns.parse_word import extract_text_from_files
 
-        file_exist, final_result, page_one, file_manifest, excption = (
+        file_exist, final_result, page_one, file_manifest, exception = (
             extract_text_from_files(txt, chatbot, history)
         )
     else:
         file_exist = False
-        excption = ""
+        exception = ""
         file_manifest = []
 
-    if excption != "":
-        if excption == "word":
+    if exception != "":
+        if exception == "word":
             report_exception(
                 chatbot,
                 history,
@@ -341,7 +341,7 @@ def 生成多种Mermaid图表(
                 b=f"找到了.doc文件，但是该文件格式不被支持，请先转化为.docx格式。",
             )
 
-        elif excption == "pdf":
+        elif exception == "pdf":
             report_exception(
                 chatbot,
                 history,
@@ -349,7 +349,7 @@ def 生成多种Mermaid图表(
                 b=f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pymupdf```。",
             )
 
-        elif excption == "word_pip":
+        elif exception == "word_pip":
             report_exception(
                 chatbot,
                 history,

crazy_functions/知识库问答.py

@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_lastest_msg, get_log_folder, get_user
+from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_latest_msg, get_log_folder, get_user
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
 from loguru import logger
 install_msg ="""
@@ -42,14 +42,14 @@ def 知识库文件注入(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         # from crazy_functions.crazy_utils import try_install_deps
         # try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
-        # yield from update_ui_lastest_msg("安装完成，您可以再次重试。", chatbot, history)
+        # yield from update_ui_latest_msg("安装完成，您可以再次重试。", chatbot, history)
         return
 
     # < --------------------读取文件--------------- >
     file_manifest = []
     spl = ["txt", "doc", "docx", "email", "epub", "html", "json", "md", "msg", "pdf", "ppt", "pptx", "rtf"]
     for sp in spl:
-        _, file_manifest_tmp, _ = get_files_from_everything(txt, type=f'.{sp}')
+        _, file_manifest_tmp, _ = get_files_from_everything(txt, type=f'.{sp}', chatbot=chatbot)
         file_manifest += file_manifest_tmp
 
     if len(file_manifest) == 0:
@@ -95,7 +95,7 @@ def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         # from crazy_functions.crazy_utils import try_install_deps
         # try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
-        # yield from update_ui_lastest_msg("安装完成，您可以再次重试。", chatbot, history)
+        # yield from update_ui_latest_msg("安装完成，您可以再次重试。", chatbot, history)
         return
 
     # < -------------------  --------------- >

crazy_functions/虚空终端.py

@@ -47,7 +47,7 @@ explain_msg = """
 from pydantic import BaseModel, Field
 from typing import List
 from toolbox import CatchException, update_ui, is_the_upload_folder
-from toolbox import update_ui_lastest_msg, disable_auto_promotion
+from toolbox import update_ui_latest_msg, disable_auto_promotion
 from request_llms.bridge_all import predict_no_ui_long_connection
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from crazy_functions.crazy_utils import input_clipping
@@ -113,19 +113,19 @@ def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
     # 用简单的关键词检测用户意图
     is_certain, _ = analyze_intention_with_simple_rules(txt)
     if is_the_upload_folder(txt):
-        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=False)
+        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=False)
         appendix_msg = "\n\n**很好，您已经上传了文件**，现在请您描述您的需求。"
 
-    if is_certain or (state.has_provided_explaination):
+    if is_certain or (state.has_provided_explanation):
         # 如果意图明确，跳过提示环节
-        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
+        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
         state.unlock_plugin(chatbot=chatbot)
         yield from update_ui(chatbot=chatbot, history=history)
         yield from 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request)
         return
     else:
         # 如果意图模糊，提示
-        state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
+        state.set_state(chatbot=chatbot, key='has_provided_explanation', value=True)
         state.lock_plugin(chatbot=chatbot)
         chatbot.append(("虚空终端状态:", explain_msg+appendix_msg))
         yield from update_ui(chatbot=chatbot, history=history)
@@ -141,7 +141,7 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
     # ⭐ ⭐ ⭐ 分析用户意图
     is_certain, user_intention = analyze_intention_with_simple_rules(txt)
     if not is_certain:
-        yield from update_ui_lastest_msg(
+        yield from update_ui_latest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
         gpt_json_io = GptJsonIO(UserIntention)
         rf_req = "\nchoose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']"
@@ -154,13 +154,13 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
             user_intention = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
             lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
         except JsonStringError as e:
-            yield from update_ui_lastest_msg(
+            yield from update_ui_latest_msg(
                 lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型（{llm_kwargs['llm_model']}）不能理解您的意图", chatbot=chatbot, history=history, delay=0)
             return
     else:
         pass
 
-    yield from update_ui_lastest_msg(
+    yield from update_ui_latest_msg(
         lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
         chatbot=chatbot, history=history, delay=0)
 

crazy_functions/解析JupyterNotebook.py

@@ -126,6 +126,8 @@ def 解析ipynb文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
     import os
     if os.path.exists(txt):
         project_folder = txt
+        from shared_utils.fastapi_server import validate_path_safety
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "":
             txt = '空空如也的输入栏'

crazy_functions/语音助手.py

@@ -42,7 +42,7 @@ class AsyncGptTask():
             MAX_TOKEN_ALLO = 2560
             i_say, history = input_clipping(i_say, history, max_token_limit=MAX_TOKEN_ALLO)
             gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=history, sys_prompt=sys_prompt,
-                                                            observe_window=observe_window[index], console_slience=True)
+                                                            observe_window=observe_window[index], console_silence=True)
         except ConnectionAbortedError as token_exceed_err:
             logger.error('至少一个线程任务Token溢出而失败', e)
         except Exception as e:

crazy_functions/读文章写摘要.py

@@ -48,6 +48,8 @@ def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
     import glob, os
     if os.path.exists(txt):
         project_folder = txt
+        from shared_utils.fastapi_server import validate_path_safety
+        validate_path_safety(project_folder, chatbot.get_user())
     else:
         if txt == "": txt = '空空如也的输入栏'
         report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")

crazy_functions/谷歌检索小助手.py

@@ -1,6 +1,6 @@
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from toolbox import CatchException, report_exception, promote_file_to_downloadzone
-from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion, write_history_to_file
+from toolbox import update_ui, update_ui_latest_msg, disable_auto_promotion, write_history_to_file
 import logging
 import requests
 import time
@@ -156,7 +156,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
     history = []
     meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
     if len(meta_paper_info_list) == 0:
-        yield from update_ui_lastest_msg(lastmsg='获取文献失败，可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_latest_msg(lastmsg='获取文献失败，可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
         return
     batchsize = 5
     for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):

docs/translate_english.json

@@ -1141,7 +1141,7 @@
     "内容太长了都会触发token数量溢出的错误": "An error of token overflow will be triggered if the content is too long",
     "chatbot 为WebUI中显示的对话列表": "chatbot is the conversation list displayed in WebUI",
     "修改它": "Modify it",
-    "然后yeild出去": "Then yield it out",
+    "然后yield出去": "Then yield it out",
     "可以直接修改对话界面内容": "You can directly modify the conversation interface content",
     "additional_fn代表点击的哪个按钮": "additional_fn represents which button is clicked",
     "按钮见functional.py": "See functional.py for buttons",
@@ -1732,7 +1732,7 @@
     "或者重启之后再度尝试": "Or try again after restarting",
     "免费": "Free",
     "仅在Windows系统进行了测试": "Tested only on Windows system",
-    "欢迎加REAME中的QQ联系开发者": "Feel free to contact the developer via QQ in REAME",
+    "欢迎加README中的QQ联系开发者": "Feel free to contact the developer via QQ in README",
     "当前知识库内的有效文件": "Valid files in the current knowledge base",
     "您可以到Github Issue区": "You can go to the Github Issue area",
     "刷新Gradio前端界面": "Refresh the Gradio frontend interface",
@@ -1759,7 +1759,7 @@
     "报错信息如下. 如果是与网络相关的问题": "Error message as follows. If it is related to network issues",
     "功能描述": "Function description",
     "禁止移除或修改此警告": "Removal or modification of this warning is prohibited",
-    "Arixv翻译": "Arixv translation",
+    "ArXiv翻译": "ArXiv translation",
     "读取优先级": "Read priority",
     "包含documentclass关键字": "Contains the documentclass keyword",
     "根据文本使用GPT模型生成相应的图像": "Generate corresponding images using GPT model based on the text",
@@ -1998,7 +1998,7 @@
     "开始最终总结": "Start final summary",
     "openai的官方KEY需要伴随组织编码": "Openai's official KEY needs to be accompanied by organizational code",
     "将子线程的gpt结果写入chatbot": "Write the GPT result of the sub-thread into the chatbot",
-    "Arixv论文精细翻译": "Fine translation of Arixv paper",
+    "ArXiv论文精细翻译": "Fine translation of ArXiv paper",
     "开始接收chatglmft的回复": "Start receiving replies from chatglmft",
     "请先将.doc文档转换为.docx文档": "Please convert .doc documents to .docx documents first",
     "避免多用户干扰": "Avoid multiple user interference",
@@ -2360,7 +2360,7 @@
     "请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件": "Please set ALLOW_RESET_CONFIG=True in config.py and restart the software",
     "按照自然语言描述生成一个动画 | 输入参数是一段话": "Generate an animation based on natural language description | Input parameter is a sentence",
     "你的hf用户名如qingxu98": "Your hf username is qingxu98",
-    "Arixv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of Arixv paper | Input parameter is the ID of arxiv paper",
+    "ArXiv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of ArXiv paper | Input parameter is the ID of arxiv paper",
     "无法获取 abstract": "Unable to retrieve abstract",
     "尽可能地仅用一行命令解决我的要求": "Try to solve my request using only one command",
     "提取插件参数": "Extract plugin parameters",

docs/translate_japanese.json

@@ -753,7 +753,7 @@
     "手动指定和筛选源代码文件类型": "ソースコードファイルタイプを手動で指定およびフィルタリングする",
     "更多函数插件": "その他の関数プラグイン",
     "看门狗的耐心": "監視犬の忍耐力",
-    "然后yeild出去": "そして出力する",
+    "然后yield出去": "そして出力する",
     "拆分过长的IPynb文件": "長すぎるIPynbファイルを分割する",
     "1. 把input的余量留出来": "1. 入力の余裕を残す",
     "请求超时": "リクエストがタイムアウトしました",
@@ -1803,7 +1803,7 @@
     "默认值为1000": "デフォルト値は1000です",
     "写出文件": "ファイルに書き出す",
     "生成的视频文件路径": "生成されたビデオファイルのパス",
-    "Arixv论文精细翻译": "Arixv論文の詳細な翻訳",
+    "ArXiv论文精细翻译": "ArXiv論文の詳細な翻訳",
     "用latex编译为PDF对修正处做高亮": "LaTeXでコンパイルしてPDFに修正をハイライトする",
     "点击“停止”键可终止程序": "「停止」ボタンをクリックしてプログラムを終了できます",
     "否则将导致每个人的Claude问询历史互相渗透": "さもないと、各人のClaudeの問い合わせ履歴が相互に侵入します",
@@ -1987,7 +1987,7 @@
     "前面是中文逗号": "前面是中文逗号",
     "的依赖": "的依赖",
     "材料如下": "材料如下",
-    "欢迎加REAME中的QQ联系开发者": "欢迎加REAME中的QQ联系开发者",
+    "欢迎加README中的QQ联系开发者": "欢迎加README中的QQ联系开发者",
     "开始下载": "開始ダウンロード",
     "100字以内": "100文字以内",
     "创建request": "リクエストの作成",

docs/translate_traditionalchinese.json

@@ -771,7 +771,7 @@
     "查询代理的地理位置": "查詢代理的地理位置",
     "是否在输入过长时": "是否在輸入過長時",
     "chatGPT分析报告": "chatGPT分析報告",
-    "然后yeild出去": "然後yield出去",
+    "然后yield出去": "然後yield出去",
     "用户取消了程序": "使用者取消了程式",
     "琥珀色": "琥珀色",
     "这里是特殊函数插件的高级参数输入区": "這裡是特殊函數插件的高級參數輸入區",
@@ -1587,7 +1587,7 @@
     "否则将导致每个人的Claude问询历史互相渗透": "否則將導致每個人的Claude問詢歷史互相滲透",
     "提问吧! 但注意": "提問吧！但注意",
     "待处理的word文档路径": "待處理的word文檔路徑",
-    "欢迎加REAME中的QQ联系开发者": "歡迎加REAME中的QQ聯繫開發者",
+    "欢迎加README中的QQ联系开发者": "歡迎加README中的QQ聯繫開發者",
     "建议暂时不要使用": "建議暫時不要使用",
     "Latex没有安装": "Latex沒有安裝",
     "在这里放一些网上搜集的demo": "在這裡放一些網上搜集的demo",
@@ -1989,7 +1989,7 @@
     "请耐心等待": "請耐心等待",
     "在执行完成之后": "在執行完成之後",
     "参数简单": "參數簡單",
-    "Arixv论文精细翻译": "Arixv論文精細翻譯",
+    "ArXiv论文精细翻译": "ArXiv論文精細翻譯",
     "备份和下载": "備份和下載",
     "当前报错的latex代码处于第": "當前報錯的latex代碼處於第",
     "Markdown翻译": "Markdown翻譯",

main.py

@@ -34,7 +34,7 @@ def encode_plugin_info(k, plugin)->str:
 
 def main():
     import gradio as gr
-    if gr.__version__ not in ['3.32.12']:
+    if gr.__version__ not in ['3.32.14', '3.32.13']:
         raise ModuleNotFoundError("使用项目内置Gradio获取最优体验! 请运行 `pip install -r requirements.txt` 指令安装内置Gradio及其他依赖, 详情信息见requirements.txt.")
 
     # 一些基础工具
@@ -184,7 +184,7 @@ def main():
         from themes.gui_floating_menu import define_gui_floating_menu
         area_input_secondary, txt2, area_customize, _, resetBtn2, clearBtn2, stopBtn2 = \
             define_gui_floating_menu(customize_btns, functional, predefined_btns, cookies, web_cookie_cache)
-        
+
         # 浮动时间线定义
         gr.Spark()
 
@@ -217,7 +217,7 @@ def main():
         input_combo_order = ["cookies", "max_length_sl", "md_dropdown", "txt", "txt2", "top_p", "temperature", "chatbot", "history", "system_prompt", "plugin_advanced_arg"]
         output_combo = [cookies, chatbot, history, status]
         predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True)], outputs=output_combo)
-        
+
         # 提交按钮、重置按钮
         multiplex_submit_btn.click(
             None, [multiplex_sel], None, _js="""(multiplex_sel)=>multiplex_function_begin(multiplex_sel)""")

request_llms/bridge_all.py

@@ -80,6 +80,7 @@ ollama_endpoint = "http://localhost:11434/api/chat"
 yimodel_endpoint = "https://api.lingyiwanwu.com/v1/chat/completions"
 deepseekapi_endpoint = "https://api.deepseek.com/v1/chat/completions"
 grok_model_endpoint = "https://api.x.ai/v1/chat/completions"
+volcengine_endpoint = "https://ark.cn-beijing.volces.com/api/v3/chat/completions"
 
 if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
 azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
@@ -102,6 +103,7 @@ if ollama_endpoint in API_URL_REDIRECT: ollama_endpoint = API_URL_REDIRECT[ollam
 if yimodel_endpoint in API_URL_REDIRECT: yimodel_endpoint = API_URL_REDIRECT[yimodel_endpoint]
 if deepseekapi_endpoint in API_URL_REDIRECT: deepseekapi_endpoint = API_URL_REDIRECT[deepseekapi_endpoint]
 if grok_model_endpoint in API_URL_REDIRECT: grok_model_endpoint = API_URL_REDIRECT[grok_model_endpoint]
+if volcengine_endpoint in API_URL_REDIRECT: volcengine_endpoint = API_URL_REDIRECT[volcengine_endpoint]
 
 # 获取tokenizer
 tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
@@ -280,6 +282,7 @@ model_info = {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
         "endpoint": openai_endpoint,
+        "can_multi_thread": True,
         "max_token": 128000,
         "tokenizer": tokenizer_gpt4,
         "token_cnt": get_token_num_gpt4,
@@ -312,6 +315,50 @@ model_info = {
         "openai_force_temperature_one": True,
     },
 
+    "gpt-4.1":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
+    "gpt-4.1-mini":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
+    "o3":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+        "openai_disable_system_prompt": True,
+        "openai_disable_stream": True,
+        "openai_force_temperature_one": True,
+    },
+
+    "o4-mini":{
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "has_multimodal_capacity": True,
+        "can_multi_thread": True,
+        "endpoint": openai_endpoint,
+        "max_token": 828000,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+
     "gpt-4-turbo": {
         "fn_with_ui": chatgpt_ui,
         "fn_without_ui": chatgpt_noui,
@@ -528,6 +575,15 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "gemini-2.0-flash": {
+        "fn_with_ui": genai_ui,
+        "fn_without_ui": genai_noui,
+        "endpoint": gemini_endpoint,
+        "has_multimodal_capacity": True,
+        "max_token": 1024 * 204800,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
 
     # cohere
     "cohere-command-r-plus": {
@@ -811,8 +867,12 @@ if "qwen-local" in AVAIL_LLM_MODELS:
         })
     except:
         logger.error(trimmed_format_exc())
-# -=-=-=-=-=-=- 通义-在线模型 -=-=-=-=-=-=-
-qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus"]
+
+# -=-=-=-=-=-=- 阿里云百炼（通义）-在线模型 -=-=-=-=-=-=-
+qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus",
+               "dashscope-deepseek-r1","dashscope-deepseek-v3",
+               "dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-qwen3-32b",
+               ]
 if any(item in qwen_models for item in AVAIL_LLM_MODELS):
     try:
         from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
@@ -862,10 +922,58 @@ if any(item in qwen_models for item in AVAIL_LLM_MODELS):
                 "max_token": 30720,
                 "tokenizer": tokenizer_gpt35,
                 "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-deepseek-r1": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "enable_reasoning": True,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 57344,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-deepseek-v3": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 57344,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-14b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "enable_reasoning": True,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-235b-a22b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
+            },
+            "dashscope-qwen3-32b": {
+                "fn_with_ui": qwen_ui,
+                "fn_without_ui": qwen_noui,
+                "can_multi_thread": True,
+                "endpoint": None,
+                "max_token": 129024,
+                "tokenizer": tokenizer_gpt35,
+                "token_cnt": get_token_num_gpt35,
             }
         })
     except:
         logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 零一万物模型 -=-=-=-=-=-=-
 yi_models = ["yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview"]
 if any(item in yi_models for item in AVAIL_LLM_MODELS):
@@ -954,7 +1062,7 @@ if any(item in grok_models for item in AVAIL_LLM_MODELS):
     try:
         grok_beta_128k_noui, grok_beta_128k_ui = get_predict_function(
             api_key_conf_name="GROK_API_KEY", max_output_token=8192, disable_proxy=False
-            )
+        )
         
         model_info.update({
             "grok-beta": {
@@ -1072,7 +1180,7 @@ if "zhipuai" in AVAIL_LLM_MODELS:   # zhipuai 是glm-4的别名，向后兼容
         })
     except:
         logger.error(trimmed_format_exc())
-# -=-=-=-=-=-=- 幻方-深度求索大模型 -=-=-=-=-=-=-
+# -=-=-=-=-=-=- 幻方-深度求索本地大模型 -=-=-=-=-=-=-
 if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
     try:
         from .bridge_deepseekcoder import predict_no_ui_long_connection as deepseekcoder_noui
@@ -1089,8 +1197,10 @@ if "deepseekcoder" in AVAIL_LLM_MODELS:   # deepseekcoder
         })
     except:
         logger.error(trimmed_format_exc())
+
 # -=-=-=-=-=-=- 幻方-深度求索大模型在线API -=-=-=-=-=-=-
-if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS or "deepseek-reasoner" in AVAIL_LLM_MODELS:
+claude_models = ["deepseek-chat", "deepseek-coder", "deepseek-reasoner"]
+if any(item in claude_models for item in AVAIL_LLM_MODELS):
     try:
         deepseekapi_noui, deepseekapi_ui = get_predict_function(
             api_key_conf_name="DEEPSEEK_API_KEY", max_output_token=4096, disable_proxy=False
@@ -1127,6 +1237,60 @@ if "deepseek-chat" in AVAIL_LLM_MODELS or "deepseek-coder" in AVAIL_LLM_MODELS o
         })
     except:
         logger.error(trimmed_format_exc())
+
+# -=-=-=-=-=-=- 火山引擎 对齐支持 -=-=-=-=-=-=-
+for model in [m for m in AVAIL_LLM_MODELS if m.startswith("volcengine-")]:
+    # 为了更灵活地接入volcengine多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["volcengine-deepseek-r1-250120(max_token=6666)"]
+    # 其中
+    #   "volcengine-"          是前缀（必要）
+    #   "deepseek-r1-250120"   是模型名（必要）
+    #   "(max_token=6666)"     是配置（非必要）
+    model_info_extend = model_info
+    model_info_extend.update({
+        "deepseek-r1-250120": {
+            "max_token": 16384,
+            "enable_reasoning": True,
+            "can_multi_thread": True,
+            "endpoint": volcengine_endpoint,
+            "tokenizer": tokenizer_gpt35,
+            "token_cnt": get_token_num_gpt35,
+        },
+        "deepseek-v3-241226": {
+            "max_token": 16384,
+            "enable_reasoning": False,
+            "can_multi_thread": True,
+            "endpoint": volcengine_endpoint,
+            "tokenizer": tokenizer_gpt35,
+            "token_cnt": get_token_num_gpt35,
+        },
+    })
+    try:
+        origin_model_name, max_token_tmp = read_one_api_model_name(model)
+        # 如果是已知模型，则尝试获取其信息
+        original_model_info = model_info_extend.get(origin_model_name.replace("volcengine-", "", 1), None)
+    except:
+        logger.error(f"volcengine模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
+        continue
+
+    volcengine_noui, volcengine_ui = get_predict_function(api_key_conf_name="ARK_API_KEY", max_output_token=8192, disable_proxy=True, model_remove_prefix = ["volcengine-"])
+
+    this_model_info = {
+        "fn_with_ui": volcengine_ui,
+        "fn_without_ui": volcengine_noui,
+        "endpoint": volcengine_endpoint,
+        "can_multi_thread": True,
+        "max_token": 64000,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    }
+
+    # 同步已知模型的其他信息
+    attribute = "has_multimodal_capacity"
+    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
+    attribute = "enable_reasoning"
+    if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
+    model_info.update({model: this_model_info})
+
 # -=-=-=-=-=-=- one-api 对齐支持 -=-=-=-=-=-=-
 for model in [m for m in AVAIL_LLM_MODELS if m.startswith("one-api-")]:
     # 为了更灵活地接入one-api多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["one-api-mixtral-8x7b(max_token=6666)"]
@@ -1265,9 +1429,9 @@ def LLM_CATCH_EXCEPTION(f):
     """
     装饰器函数，将错误显示出来
     """
-    def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_slience:bool):
+    def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_silence:bool):
         try:
-            return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
+            return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
         except Exception as e:
             tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
             observe_window[0] = tb_str
@@ -1275,7 +1439,7 @@ def LLM_CATCH_EXCEPTION(f):
     return decorated
 
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_slience:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_silence:bool=False):
     """
     发送至LLM，等待回复，一次性完成，不显示中间过程。但内部（尽可能地）用stream的方法避免中途网线被掐。
     inputs：
@@ -1297,7 +1461,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
     if '&' not in model:
         # 如果只询问“一个”大语言模型（多数情况）：
         method = model_info[model]["fn_without_ui"]
-        return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
+        return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
     else:
         # 如果同时询问“多个”大语言模型，这个稍微啰嗦一点，但思路相同，您不必读这个else分支
         executor = ThreadPoolExecutor(max_workers=4)
@@ -1314,7 +1478,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
             method = model_info[model]["fn_without_ui"]
             llm_kwargs_feedin = copy.deepcopy(llm_kwargs)
             llm_kwargs_feedin['llm_model'] = model
-            future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_slience)
+            future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_silence)
             futures.append(future)
 
         def mutex_manager(window_mutex, observe_window):

request_llms/bridge_chatglmft.py

@@ -139,7 +139,7 @@ global glmft_handle
 glmft_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_chatgpt.py

@@ -125,7 +125,7 @@ def verify_endpoint(endpoint):
         raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
     return endpoint
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=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：
@@ -203,7 +203,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
         if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口："+delta)
         if has_content: # has_role = True/False
             result += delta["content"]
-            if not console_slience: print(delta["content"], end='')
+            if not console_silence: 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:
@@ -231,7 +231,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     from request_llms.bridge_all import model_info
@@ -368,12 +368,12 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                             log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
                             break # 对于符合规范的接口，这里可以break
                         else:
-                            continue # 对于不符合规范的狗屎接口，这里需要继续
+                            continue # 对于不符合规范的接口，这里需要继续
                     # 到这里，我们已经可以假定必须包含choice了
                     try:
                         status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
                     except:
-                        logger.error(f"一些垃圾第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
+                        logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
                     # 处理数据流的主体
                     if has_content:
                         # 正常情况
@@ -382,9 +382,9 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
                         # 一些第三方接口的出现这样的错误，兼容一下吧
                         continue
                     else:
-                        # 至此已经超出了正常接口应该进入的范围，一些垃圾第三方接口会出现这样的错误
+                        # 至此已经超出了正常接口应该进入的范围，一些第三方接口会出现这样的错误
                         if chunkjson['choices'][0]["delta"].get("content", None) is None:
-                            logger.error(f"一些垃圾第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
+                            logger.error(f"一些第三方接口出现这样的错误，兼容一下吧: {chunk_decoded}")
                             continue
                         gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
 

request_llms/bridge_chatgpt_vision.py

@@ -16,7 +16,7 @@ import base64
 import glob
 from loguru import logger
 from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder, \
-    update_ui_lastest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
+    update_ui_latest_msg, get_max_token, encode_image, have_any_recent_upload_image_files, log_chat
 
 
 proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
@@ -67,7 +67,7 @@ def verify_endpoint(endpoint):
     """
     return endpoint
 
-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=[], sys_prompt="", observe_window=None, console_silence=False):
     raise NotImplementedError
 
 
@@ -183,7 +183,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                     if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
                         # 判定为数据流的结束，gpt_replying_buffer也写完了
                         lastmsg = chatbot[-1][-1] + f"\n\n\n\n「{llm_kwargs['llm_model']}调用结束，该模型不具备上下文对话能力，如需追问，请及时切换模型。」"
-                        yield from update_ui_lastest_msg(lastmsg, chatbot, history, delay=1)
+                        yield from update_ui_latest_msg(lastmsg, chatbot, history, delay=1)
                         log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_replying_buffer)
                         break
                     # 处理数据流的主体

request_llms/bridge_claude.py

@@ -69,7 +69,7 @@ def decode_chunk(chunk):
     return need_to_pass, chunkjson, is_last_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=[], sys_prompt="", observe_window=None, console_silence=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：
@@ -151,7 +151,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     if inputs == "":     inputs = "空空如也的输入栏"

request_llms/bridge_cohere.py

@@ -68,7 +68,7 @@ def verify_endpoint(endpoint):
         raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
     return endpoint
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=False):
     """
     发送，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：
@@ -111,7 +111,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
         if chunkjson['event_type'] == 'stream-start': continue
         if chunkjson['event_type'] == 'text-generation':
             result += chunkjson["text"]
-            if not console_slience: print(chunkjson["text"], end='')
+            if not console_silence: print(chunkjson["text"], 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:
@@ -132,7 +132,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     # if is_any_api_key(inputs):

request_llms/bridge_deepseekcoder.py

@@ -6,7 +6,6 @@ from toolbox import get_conf
 from request_llms.local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
 from threading import Thread
 from loguru import logger
-import torch
 import os
 
 def download_huggingface_model(model_name, max_retry, local_dir):
@@ -29,6 +28,7 @@ class GetCoderLMHandle(LocalLLMHandle):
         self.cmd_to_install = cmd_to_install
 
     def load_model_and_tokenizer(self):
+        import torch
         # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行
         with ProxyNetworkActivate('Download_LLM'):
             from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer

request_llms/bridge_google_gemini.py

@@ -8,7 +8,7 @@ import os
 import time
 from request_llms.com_google import GoogleChatInit
 from toolbox import ChatBotWithCookies
-from toolbox import get_conf, update_ui, update_ui_lastest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat, encode_image
+from toolbox import get_conf, update_ui, update_ui_latest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat, encode_image
 
 proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY')
 timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
@@ -16,7 +16,7 @@ timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check
 
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[],
-                                  console_slience:bool=False):
+                                  console_silence:bool=False):
     # 检查API_KEY
     if get_conf("GEMINI_API_KEY") == "":
         raise ValueError(f"请配置 GEMINI_API_KEY。")
@@ -60,7 +60,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
 
     # 检查API_KEY
     if get_conf("GEMINI_API_KEY") == "":
-        yield from update_ui_lastest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_latest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
         return
 
     # 适配润色区域

request_llms/bridge_jittorllms_llama.py

@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
                 if self.jittorllms_model is None:
                     device = get_conf('LOCAL_MODEL_DEVICE')
                     from .jittorllms.models import get_model
-                    # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
+                    # available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
                     args_dict = {'model': 'llama'}
                     print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
                     self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
@@ -107,7 +107,7 @@ global llama_glm_handle
 llama_glm_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_jittorllms_pangualpha.py

@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
                 if self.jittorllms_model is None:
                     device = get_conf('LOCAL_MODEL_DEVICE')
                     from .jittorllms.models import get_model
-                    # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
+                    # available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
                     args_dict = {'model': 'pangualpha'}
                     print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
                     self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
@@ -107,7 +107,7 @@ global pangu_glm_handle
 pangu_glm_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_jittorllms_rwkv.py

@@ -55,7 +55,7 @@ class GetGLMHandle(Process):
                 if self.jittorllms_model is None:
                     device = get_conf('LOCAL_MODEL_DEVICE')
                     from .jittorllms.models import get_model
-                    # availabel_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
+                    # available_models = ["chatglm", "pangualpha", "llama", "chatrwkv"]
                     args_dict = {'model': 'chatrwkv'}
                     print('self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))')
                     self.jittorllms_model = get_model(types.SimpleNamespace(**args_dict))
@@ -107,7 +107,7 @@ global rwkv_glm_handle
 rwkv_glm_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_llama2.py

@@ -46,8 +46,8 @@ class GetLlamaHandle(LocalLLMHandle):
             top_p = kwargs['top_p']
             temperature = kwargs['temperature']
             history = kwargs['history']
-            console_slience = kwargs.get('console_slience', True)
-            return query, max_length, top_p, temperature, history, console_slience
+            console_silence = kwargs.get('console_silence', True)
+            return query, max_length, top_p, temperature, history, console_silence
 
         def convert_messages_to_prompt(query, history):
             prompt = ""
@@ -57,7 +57,7 @@ class GetLlamaHandle(LocalLLMHandle):
             prompt += f"\n[INST]{query}[/INST]"
             return prompt
 
-        query, max_length, top_p, temperature, history, console_slience = adaptor(kwargs)
+        query, max_length, top_p, temperature, history, console_silence = adaptor(kwargs)
         prompt = convert_messages_to_prompt(query, history)
         # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-
         # code from transformers.llama
@@ -72,9 +72,9 @@ class GetLlamaHandle(LocalLLMHandle):
         generated_text = ""
         for new_text in streamer:
             generated_text += new_text
-            if not console_slience: print(new_text, end='')
+            if not console_silence: print(new_text, end='')
             yield generated_text.lstrip(prompt_tk_back).rstrip("</s>")
-        if not console_slience: print()
+        if not console_silence: print()
         # =-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=--=-=-
 
     def try_to_import_special_deps(self, **kwargs):

request_llms/bridge_moonshot.py

@@ -169,7 +169,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=gpt_bro_result)
 
 def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None,
-                                  console_slience=False):
+                                  console_silence=False):
     gpt_bro_init = MoonShotInit()
     watch_dog_patience = 60  # 看门狗的耐心, 设置10秒即可
     stream_response = gpt_bro_init.generate_messages(inputs, llm_kwargs, history, sys_prompt, True)

request_llms/bridge_moss.py

@@ -95,7 +95,7 @@ class GetGLMHandle(Process):
         - Its responses must not be vague, accusatory, rude, controversial, off-topic, or defensive.
         - It should avoid giving subjective opinions but rely on objective facts or phrases like \"in this context a human might say...\", \"some people might think...\", etc.
         - Its responses must also be positive, polite, interesting, entertaining, and engaging.
-        - It can provide additional relevant details to answer in-depth and comprehensively covering mutiple aspects.
+        - It can provide additional relevant details to answer in-depth and comprehensively covering multiple aspects.
         - It apologizes and accepts the user's suggestion if the user corrects the incorrect answer generated by MOSS.
         Capabilities and tools that MOSS can possess.
         """
@@ -172,7 +172,7 @@ global moss_handle
 moss_handle = None
 #################################################################################
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_newbingfree.py

@@ -209,7 +209,7 @@ def predict_no_ui_long_connection(
     history=[],
     sys_prompt="",
     observe_window=[],
-    console_slience=False,
+    console_silence=False,
 ):
     """
     多线程方法

request_llms/bridge_ollama.py

@@ -52,7 +52,7 @@ def decode_chunk(chunk):
         pass
     return chunk_decoded, chunkjson, is_last_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=[], sys_prompt="", observe_window=None, console_silence=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：
@@ -99,7 +99,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
                     logger.info(f'[response] {result}')
                     break
                 result += chunkjson['message']["content"]
-                if not console_slience: print(chunkjson['message']["content"], end='')
+                if not console_silence: print(chunkjson['message']["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:
@@ -124,7 +124,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     if inputs == "":     inputs = "空空如也的输入栏"

request_llms/bridge_openrouter.py

@@ -119,7 +119,7 @@ def verify_endpoint(endpoint):
         raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
     return endpoint
 
-def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_slience:bool=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=None, console_silence:bool=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：
@@ -188,7 +188,7 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[],
         if (not has_content) and (not has_role): continue # raise RuntimeError("发现不标准的第三方接口："+delta)
         if has_content: # has_role = True/False
             result += delta["content"]
-            if not console_slience: print(delta["content"], end='')
+            if not console_silence: 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:
@@ -213,7 +213,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     inputs 是本次问询的输入
     top_p, temperature是chatGPT的内部调优参数
     history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-    chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+    chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
     additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     from request_llms.bridge_all import model_info
@@ -512,7 +512,7 @@ def generate_payload(inputs:str, llm_kwargs:dict, history:list, system_prompt:st
         model, _ = read_one_api_model_name(model)
     if llm_kwargs['llm_model'].startswith('openrouter-'):
         model = llm_kwargs['llm_model'][len('openrouter-'):]
-        model= read_one_api_model_name(model)
+        model, _= read_one_api_model_name(model)
     if model == "gpt-3.5-random": # 随机选择, 绕过openai访问频率限制
         model = random.choice([
             "gpt-3.5-turbo",

request_llms/bridge_qianfan.py

@@ -121,7 +121,7 @@ def generate_from_baidu_qianfan(inputs, llm_kwargs, history, system_prompt):
 
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         ⭐多线程方法
         函数的说明请见 request_llms/bridge_all.py

request_llms/bridge_qwen.py

@@ -1,12 +1,12 @@
 import time
 import os
-from toolbox import update_ui, get_conf, update_ui_lastest_msg
+from toolbox import update_ui, get_conf, update_ui_latest_msg
 from toolbox import check_packages, report_exception, log_chat
 
 model_name = 'Qwen'
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         ⭐多线程方法
         函数的说明请见 request_llms/bridge_all.py
@@ -35,13 +35,13 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     try:
         check_packages(["dashscope"])
     except:
-        yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade dashscope```。",
+        yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade dashscope```。",
                                          chatbot=chatbot, history=history, delay=0)
         return
 
     # 检查DASHSCOPE_API_KEY
     if get_conf("DASHSCOPE_API_KEY") == "":
-        yield from update_ui_lastest_msg(f"请配置 DASHSCOPE_API_KEY。",
+        yield from update_ui_latest_msg(f"请配置 DASHSCOPE_API_KEY。",
                                          chatbot=chatbot, history=history, delay=0)
         return
 

request_llms/bridge_skylark2.py

@@ -1,5 +1,5 @@
 import time
-from toolbox import update_ui, get_conf, update_ui_lastest_msg
+from toolbox import update_ui, get_conf, update_ui_latest_msg
 from toolbox import check_packages, report_exception
 
 model_name = '云雀大模型'
@@ -10,7 +10,7 @@ def validate_key():
     return True
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         ⭐ 多线程方法
         函数的说明请见 request_llms/bridge_all.py
@@ -42,12 +42,12 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     try:
         check_packages(["zhipuai"])
     except:
-        yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。",
+        yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。",
                                          chatbot=chatbot, history=history, delay=0)
         return
 
     if validate_key() is False:
-        yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", chatbot=chatbot, history=history, delay=0)
         return
 
     if additional_fn is not None:

request_llms/bridge_spark.py

@@ -2,7 +2,7 @@
 import time
 import threading
 import importlib
-from toolbox import update_ui, get_conf, update_ui_lastest_msg
+from toolbox import update_ui, get_conf, update_ui_latest_msg
 from multiprocessing import Process, Pipe
 
 model_name = '星火认知大模型'
@@ -14,7 +14,7 @@ def validate_key():
     return True
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         ⭐多线程方法
         函数的说明请见 request_llms/bridge_all.py
@@ -43,7 +43,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     yield from update_ui(chatbot=chatbot, history=history)
 
     if validate_key() is False:
-        yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0)
         return
 
     if additional_fn is not None:

request_llms/bridge_stackclaude.py

@@ -225,7 +225,7 @@ def predict_no_ui_long_connection(
     history=[],
     sys_prompt="",
     observe_window=None,
-    console_slience=False,
+    console_silence=False,
 ):
     """
     多线程方法

request_llms/bridge_taichu.py

@@ -1,6 +1,6 @@
 import time
 import os
-from toolbox import update_ui, get_conf, update_ui_lastest_msg, log_chat
+from toolbox import update_ui, get_conf, update_ui_latest_msg, log_chat
 from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
 from toolbox import ChatBotWithCookies
 
@@ -13,7 +13,7 @@ def validate_key():
     return True
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         ⭐多线程方法
         函数的说明请见 request_llms/bridge_all.py
@@ -49,7 +49,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     yield from update_ui(chatbot=chatbot, history=history)
 
     if validate_key() is False:
-        yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
         return
 
     if additional_fn is not None:

request_llms/bridge_tgui.py

@@ -91,7 +91,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
         inputs 是本次问询的输入
         top_p, temperature是chatGPT的内部调优参数
         history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-        chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+        chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
         additional_fn代表点击的哪个按钮，按钮见functional.py
     """
     if additional_fn is not None:
@@ -112,7 +112,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
 
 
     mutable = ["", time.time()]
-    def run_coorotine(mutable):
+    def run_coroutine(mutable):
         async def get_result(mutable):
             # "tgui:galactica-1.3b@localhost:7860"
 
@@ -126,7 +126,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
                     break
         asyncio.run(get_result(mutable))
 
-    thread_listen = threading.Thread(target=run_coorotine, args=(mutable,), daemon=True)
+    thread_listen = threading.Thread(target=run_coroutine, args=(mutable,), daemon=True)
     thread_listen.start()
 
     while thread_listen.is_alive():
@@ -142,7 +142,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
 
 
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience=False):
+def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence=False):
     raw_input = "What I would like to say is the following: " + inputs
     prompt = raw_input
     tgui_say = ""
@@ -151,7 +151,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
     addr, port = addr_port.split(':')
 
 
-    def run_coorotine(observe_window):
+    def run_coroutine(observe_window):
         async def get_result(observe_window):
             async for response in run(context=prompt, max_token=llm_kwargs['max_length'],
                                       temperature=llm_kwargs['temperature'],
@@ -162,6 +162,6 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
                     print('exit when no listener')
                     break
         asyncio.run(get_result(observe_window))
-    thread_listen = threading.Thread(target=run_coorotine, args=(observe_window,))
+    thread_listen = threading.Thread(target=run_coroutine, args=(observe_window,))
     thread_listen.start()
     return observe_window[0]

request_llms/bridge_zhipu.py

@@ -1,6 +1,6 @@
 import time
 import os
-from toolbox import update_ui, get_conf, update_ui_lastest_msg, log_chat
+from toolbox import update_ui, get_conf, update_ui_latest_msg, log_chat
 from toolbox import check_packages, report_exception, have_any_recent_upload_image_files
 from toolbox import ChatBotWithCookies
 
@@ -18,7 +18,7 @@ def make_media_input(inputs, image_paths):
     return inputs
 
 def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="",
-                                  observe_window:list=[], console_slience:bool=False):
+                                  observe_window:list=[], console_silence:bool=False):
     """
         ⭐多线程方法
         函数的说明请见 request_llms/bridge_all.py
@@ -57,12 +57,12 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     try:
         check_packages(["zhipuai"])
     except:
-        yield from update_ui_lastest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。",
+        yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。",
             chatbot=chatbot, history=history, delay=0)
         return
 
     if validate_key() is False:
-        yield from update_ui_lastest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
+        yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0)
         return
 
     if additional_fn is not None:

request_llms/com_qwenapi.py

@@ -3,6 +3,7 @@ from toolbox import get_conf
 import threading
 
 timeout_bot_msg = '[Local Message] Request timeout. Network error.'
+model_prefix_to_remove = 'dashscope-'
 
 class QwenRequestInstance():
     def __init__(self):
@@ -20,6 +21,13 @@ class QwenRequestInstance():
             raise RuntimeError('请配置 DASHSCOPE_API_KEY')
         dashscope.api_key = get_conf("DASHSCOPE_API_KEY")
 
+    def format_reasoning(self, reasoning_content:str, main_content:str):
+        if reasoning_content:
+            reasoning_content_paragraphs = ''.join([f'<p style="margin: 1.25em 0;">{line}</p>' for line in reasoning_content.split('\n')])
+            formatted_reasoning_content = f'<div class="reasoning_process">{reasoning_content_paragraphs}</div>\n\n---\n\n'
+            return formatted_reasoning_content + main_content
+        else:
+            return main_content
 
     def generate(self, inputs, llm_kwargs, history, system_prompt):
         # import _thread as thread
@@ -28,9 +36,13 @@ class QwenRequestInstance():
         if top_p == 0: top_p += 1e-5
         if top_p == 1: top_p -= 1e-5
 
+        model_name = llm_kwargs['llm_model']
+        if model_name.startswith(model_prefix_to_remove): model_name = model_name[len(model_prefix_to_remove):]
+
+        self.reasoning_buf = ""
         self.result_buf = ""
         responses = Generation.call(
-            model=llm_kwargs['llm_model'],
+            model=model_name,
             messages=generate_message_payload(inputs, llm_kwargs, history, system_prompt),
             top_p=top_p,
             temperature=llm_kwargs.get('temperature', 1.0),
@@ -46,18 +58,24 @@ class QwenRequestInstance():
                         self.result_buf += response.output.choices[0].message.content
                     except:
                         pass
-                    yield self.result_buf
+                    yield self.format_reasoning(self.reasoning_buf, self.result_buf)
                     break
                 elif response.output.choices[0].finish_reason == 'length':
                     self.result_buf += "[Local Message] 生成长度过长，后续输出被截断"
-                    yield self.result_buf
+                    yield self.format_reasoning(self.reasoning_buf, self.result_buf)
                     break
                 else:
+                    try:
+                        contain_reasoning = hasattr(response.output.choices[0].message, 'reasoning_content')
+                    except:
+                        contain_reasoning = False
+                    if contain_reasoning:
+                        self.reasoning_buf += response.output.choices[0].message.reasoning_content
                     self.result_buf += response.output.choices[0].message.content
-                    yield self.result_buf
+                    yield self.format_reasoning(self.reasoning_buf, self.result_buf)
             else:
                 self.result_buf += f"[Local Message] 请求错误：状态码：{response.status_code}，错误码:{response.code}，消息：{response.message}"
-                yield self.result_buf
+                yield self.format_reasoning(self.reasoning_buf, self.result_buf)
                 break
 
         # 耗尽generator避免报错

request_llms/local_llm_class.py

@@ -216,7 +216,7 @@ class LocalLLMHandle(Process):
 def get_local_llm_predict_fns(LLMSingletonClass, model_name, history_format='classic'):
     load_message = f"{model_name}尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，{model_name}消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……"
 
-    def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[], console_slience:bool=False):
+    def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[], console_silence:bool=False):
         """
             refer to request_llms/bridge_all.py
         """

request_llms/oai_std_model_template.py

@@ -2,15 +2,9 @@ import json
 import time
 import traceback
 import requests
-from loguru import logger
 
-# config_private.py放自己的秘密如API和代理网址
-# 读取时首先看是否存在私密的config_private配置文件（不受git管控），如果有，则覆盖原config文件
-from toolbox import (
-    get_conf,
-    update_ui,
-    is_the_upload_folder,
-)
+from loguru import logger
+from toolbox import get_conf, is_the_upload_folder, update_ui, update_ui_latest_msg
 
 proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf(
     "proxies", "TIMEOUT_SECONDS", "MAX_RETRY"
@@ -39,27 +33,35 @@ def decode_chunk(chunk):
     用于解读"content"和"finish_reason"的内容（如果支持思维链也会返回"reasoning_content"内容）
     """
     chunk = chunk.decode()
-    respose = ""
+    response = ""
     reasoning_content = ""
     finish_reason = "False"
+
+    # 考虑返回类型是 text/json 和 text/event-stream 两种
+    if chunk.startswith("data: "):
+        chunk = chunk[6:]
+    else:
+        chunk = chunk
+    
     try:
-        chunk = json.loads(chunk[6:])
+        chunk = json.loads(chunk)
     except:
-        respose = ""
+        response = ""
         finish_reason = chunk
+
     # 错误处理部分
     if "error" in chunk:
-        respose = "API_ERROR"
+        response = "API_ERROR"
         try:
             chunk = json.loads(chunk)
             finish_reason = chunk["error"]["code"]
         except:
             finish_reason = "API_ERROR"
-        return respose, finish_reason
+        return response, reasoning_content, finish_reason, str(chunk)
 
     try:
         if chunk["choices"][0]["delta"]["content"] is not None:
-            respose = chunk["choices"][0]["delta"]["content"]
+            response = chunk["choices"][0]["delta"]["content"]
     except:
         pass
     try:
@@ -71,7 +73,7 @@ def decode_chunk(chunk):
         finish_reason = chunk["choices"][0]["finish_reason"]
     except:
         pass
-    return respose, reasoning_content, finish_reason
+    return response, reasoning_content, finish_reason, str(chunk)
 
 
 def generate_message(input, model, key, history, max_output_token, system_prompt, temperature):
@@ -106,7 +108,7 @@ def generate_message(input, model, key, history, max_output_token, system_prompt
     what_i_ask_now["role"] = "user"
     what_i_ask_now["content"] = input
     messages.append(what_i_ask_now)
-    playload = {
+    payload = {
         "model": model,
         "messages": messages,
         "temperature": temperature,
@@ -114,13 +116,14 @@ def generate_message(input, model, key, history, max_output_token, system_prompt
         "max_tokens": max_output_token,
     }
 
-    return headers, playload
+    return headers, payload
 
 
 def get_predict_function(
         api_key_conf_name,
         max_output_token,
-        disable_proxy = False
+        disable_proxy = False,
+        model_remove_prefix = [],
     ):
     """
     为openai格式的API生成响应函数，其中传入参数：
@@ -135,13 +138,23 @@ def get_predict_function(
 
     APIKEY = get_conf(api_key_conf_name)
 
+    def remove_prefix(model_name):
+        # 去除模型名字的前缀，输入 volcengine-deepseek-r1-250120 会返回 deepseek-r1-250120
+        if not model_remove_prefix:
+            return model_name
+        model_without_prefix = model_name
+        for prefix in model_remove_prefix:
+            if model_without_prefix.startswith(prefix):
+                model_without_prefix = model_without_prefix[len(prefix):]
+        return model_without_prefix
+
     def predict_no_ui_long_connection(
         inputs,
         llm_kwargs,
         history=[],
         sys_prompt="",
         observe_window=None,
-        console_slience=False,
+        console_silence=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。
@@ -157,14 +170,16 @@ def get_predict_function(
             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
         """
         from .bridge_all import model_info
-        watch_dog_patience = 5  # 看门狗的耐心，设置5秒不准咬人(咬的也不是人
+        watch_dog_patience = 5  # 看门狗的耐心，设置5秒不准咬人 (咬的也不是人)
         if len(APIKEY) == 0:
             raise RuntimeError(f"APIKEY为空,请检查配置文件的{APIKEY}")
         if inputs == "":
             inputs = "你好👋"
-        headers, playload = generate_message(
+
+
+        headers, payload = generate_message(
             input=inputs,
-            model=llm_kwargs["llm_model"],
+            model=remove_prefix(llm_kwargs["llm_model"]),
             key=APIKEY,
             history=history,
             max_output_token=max_output_token,
@@ -182,7 +197,7 @@ def get_predict_function(
                     endpoint,
                     headers=headers,
                     proxies=None if disable_proxy else proxies,
-                    json=playload,
+                    json=payload,
                     stream=True,
                     timeout=TIMEOUT_SECONDS,
                 )
@@ -198,7 +213,7 @@ def get_predict_function(
         result = ""
         finish_reason = ""
         if reasoning:
-            resoning_buffer = ""
+            reasoning_buffer = ""
         
         stream_response = response.iter_lines()
         while True:
@@ -210,7 +225,7 @@ def get_predict_function(
                 break
             except requests.exceptions.ConnectionError:
                 chunk = next(stream_response)  # 失败了，重试一次？再失败就没办法了。
-            response_text, reasoning_content, finish_reason = decode_chunk(chunk)
+            response_text, reasoning_content, finish_reason, decoded_chunk = decode_chunk(chunk)
             # 返回的数据流第一次为空，继续等待
             if response_text == "" and (reasoning == False or reasoning_content == "") and finish_reason != "False":
                 continue
@@ -226,12 +241,12 @@ def get_predict_function(
             if chunk:
                 try:
                     if finish_reason == "stop":
-                        if not console_slience:
+                        if not console_silence:
                             print(f"[response] {result}")
                         break
                     result += response_text
                     if reasoning:
-                        resoning_buffer += reasoning_content
+                        reasoning_buffer += reasoning_content
                     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:
@@ -247,9 +262,8 @@ def get_predict_function(
                     logger.error(error_msg)
                     raise RuntimeError("Json解析不合常规")
         if reasoning:
-            # reasoning 的部分加上框 (>)
-            return '\n'.join(map(lambda x: '> ' + x, resoning_buffer.split('\n'))) + \
-                   '\n\n' + result
+            paragraphs = ''.join([f'<p style="margin: 1.25em 0;">{line}</p>' for line in reasoning_buffer.split('\n')])
+            return f'''<div class="reasoning_process" >{paragraphs}</div>\n\n''' + result
         return result
 
     def predict(
@@ -268,7 +282,7 @@ def get_predict_function(
         inputs 是本次问询的输入
         top_p, temperature是chatGPT的内部调优参数
         history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
-        chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+        chatbot 为WebUI中显示的对话列表，修改它，然后yield出去，可以直接修改对话界面内容
         additional_fn代表点击的哪个按钮，按钮见functional.py
         """
         from .bridge_all import model_info
@@ -299,9 +313,9 @@ def get_predict_function(
             )  # 刷新界面
             time.sleep(2)
 
-        headers, playload = generate_message(
+        headers, payload = generate_message(
             input=inputs,
-            model=llm_kwargs["llm_model"],
+            model=remove_prefix(llm_kwargs["llm_model"]),
             key=APIKEY,
             history=history,
             max_output_token=max_output_token,
@@ -321,7 +335,7 @@ def get_predict_function(
                     endpoint,
                     headers=headers,
                     proxies=None if disable_proxy else proxies,
-                    json=playload,
+                    json=payload,
                     stream=True,
                     timeout=TIMEOUT_SECONDS,
                 )
@@ -343,14 +357,21 @@ def get_predict_function(
             gpt_reasoning_buffer = ""
 
         stream_response = response.iter_lines()
+        wait_counter = 0
         while True:
             try:
                 chunk = next(stream_response)
             except StopIteration:
+                if wait_counter != 0 and gpt_replying_buffer == "":
+                    yield from update_ui_latest_msg(lastmsg="模型调用失败 ...", chatbot=chatbot, history=history, msg="failed")
                 break
             except requests.exceptions.ConnectionError:
                 chunk = next(stream_response)  # 失败了，重试一次？再失败就没办法了。
-            response_text, reasoning_content, finish_reason = decode_chunk(chunk)
+            response_text, reasoning_content, finish_reason, decoded_chunk = decode_chunk(chunk)
+            if decoded_chunk == ': keep-alive':
+                wait_counter += 1
+                yield from update_ui_latest_msg(lastmsg="等待中 " + "".join(["."] * (wait_counter%10)), chatbot=chatbot, history=history, msg="waiting ...")
+                continue
             # 返回的数据流第一次为空，继续等待
             if response_text == "" and (reasoning == False or reasoning_content == "") and finish_reason != "False":
                 status_text = f"finish_reason: {finish_reason}"
@@ -367,7 +388,7 @@ def get_predict_function(
                         chunk_decoded = chunk.decode()
                         chatbot[-1] = (
                             chatbot[-1][0],
-                            "[Local Message] {finish_reason},获得以下报错信息：\n"
+                            f"[Local Message] {finish_reason}, 获得以下报错信息：\n"
                             + chunk_decoded,
                         )
                         yield from update_ui(
@@ -385,7 +406,8 @@ def get_predict_function(
                     if reasoning:
                         gpt_replying_buffer += response_text
                         gpt_reasoning_buffer += reasoning_content
-                        history[-1] = '\n'.join(map(lambda x: '> ' + x, gpt_reasoning_buffer.split('\n'))) + '\n\n' + gpt_replying_buffer
+                        paragraphs = ''.join([f'<p style="margin: 1.25em 0;">{line}</p>' for line in gpt_reasoning_buffer.split('\n')])
+                        history[-1] = f'<div class="reasoning_process">{paragraphs}</div>\n\n---\n\n' + gpt_replying_buffer
                     else:
                         gpt_replying_buffer += response_text
                         # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出

requirements.txt

@@ -1,4 +1,4 @@
-https://public.agent-matrix.com/publish/gradio-3.32.12-py3-none-any.whl
+https://public.agent-matrix.com/publish/gradio-3.32.14-py3-none-any.whl
 fastapi==0.110
 gradio-client==0.8
 pypdf2==2.12.1

shared_utils/advanced_markdown_format.py

@@ -3,7 +3,8 @@ import re
 import os
 import math
 import html
-
+import base64
+import gzip
 from loguru import logger
 from textwrap import dedent
 from functools import lru_cache
@@ -325,6 +326,14 @@ def markdown_convertion_for_file(txt):
     # cat them together
     return pre + convert_stage_5 + suf
 
+def compress_string(s):
+    compress_string = gzip.compress(s.encode('utf-8'))
+    return base64.b64encode(compress_string).decode()
+
+def decompress_string(s):
+    decoded_string = base64.b64decode(s)
+    return gzip.decompress(decoded_string).decode('utf-8')
+
 @lru_cache(maxsize=128)  # 使用 lru缓存 加快转换速度
 def markdown_convertion(txt):
     """
@@ -336,6 +345,12 @@ def markdown_convertion(txt):
         # print('警告，输入了已经经过转化的字符串，二次转化可能出问题')
         return txt  # 已经被转化过，不需要再次转化
 
+    # 在文本中插入一个base64编码的原始文本，以便在复制时能够获得原始文本
+    raw_text_encoded = compress_string(txt)
+    raw_text_node = f'<div class="raw_text" style="display:none">{raw_text_encoded}</div><div class="message_tail" style="display:none"/>'
+    suf = raw_text_node + "</div>"
+
+    # 用于查找数学公式的正则表达式
     find_equation_pattern = r'<script type="math/tex(?:.*?)>(.*?)</script>'
 
     txt = fix_markdown_indent(txt)
@@ -493,6 +508,7 @@ def simple_markdown_convertion(text):
     suf = "</div>"
     if text.startswith(pre) and text.endswith(suf):
         return text  # 已经被转化过，不需要再次转化
+
     text = compat_non_markdown_input(text)    # 兼容非markdown输入
     text = markdown.markdown(
         text,

shared_utils/char_visual_effect.py

@@ -8,7 +8,7 @@ def is_full_width_char(ch):
         return True  # CJK标点符号
     return False
 
-def scolling_visual_effect(text, scroller_max_len):
+def scrolling_visual_effect(text, scroller_max_len):
     text = text.\
             replace('\n', '').replace('`', '.').replace(' ', '.').replace('<br/>', '.....').replace('$', '.')
     place_take_cnt = 0

shared_utils/connect_void_terminal.py

@@ -85,7 +85,7 @@ def get_chat_default_kwargs():
         "history": [],
         "sys_prompt": "You are AI assistant",
         "observe_window": None,
-        "console_slience": False,
+        "console_silence": False,
     }
 
     return default_chat_kwargs

shared_utils/context_clip_policy.py

@@ -0,0 +1,296 @@
+import copy
+from shared_utils.config_loader import get_conf
+
+def get_token_num(txt, tokenizer):
+    return len(tokenizer.encode(txt, disallowed_special=()))
+
+def get_model_info():
+    from request_llms.bridge_all import model_info
+    return model_info
+
+def clip_history(inputs, history, tokenizer, max_token_limit):
+    """
+    reduce the length of history by clipping.
+    this function search for the longest entries to clip, little by little,
+    until the number of token of history is reduced under threshold.
+
+    通过裁剪来缩短历史记录的长度。
+    此函数逐渐地搜索最长的条目进行剪辑，
+    直到历史记录的标记数量降低到阈值以下。
+
+    被动触发裁剪
+    """
+    import numpy as np
+
+    input_token_num = get_token_num(inputs)
+
+    if max_token_limit < 5000:
+        output_token_expect = 256  # 4k & 2k models
+    elif max_token_limit < 9000:
+        output_token_expect = 512  # 8k models
+    else:
+        output_token_expect = 1024  # 16k & 32k models
+
+    if input_token_num < max_token_limit * 3 / 4:
+        # 当输入部分的token占比小于限制的3/4时，裁剪时
+        # 1. 把input的余量留出来
+        max_token_limit = max_token_limit - input_token_num
+        # 2. 把输出用的余量留出来
+        max_token_limit = max_token_limit - output_token_expect
+        # 3. 如果余量太小了，直接清除历史
+        if max_token_limit < output_token_expect:
+            history = []
+            return history
+    else:
+        # 当输入部分的token占比 > 限制的3/4时，直接清除历史
+        history = []
+        return history
+
+    everything = [""]
+    everything.extend(history)
+    n_token = get_token_num("\n".join(everything))
+    everything_token = [get_token_num(e) for e in everything]
+
+    # 截断时的颗粒度
+    delta = max(everything_token) // 16
+
+    while n_token > max_token_limit:
+        where = np.argmax(everything_token)
+        encoded = tokenizer.encode(everything[where], disallowed_special=())
+        clipped_encoded = encoded[: len(encoded) - delta]
+        everything[where] = tokenizer.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))
+
+    history = everything[1:]
+    return history
+
+
+
+def auto_context_clip_each_message(current, history):
+    """
+    clip_history 是被动触发的
+
+    主动触发裁剪
+    """
+    context = history + [current]
+    trigger_clip_token_len = get_conf('AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN')
+    model_info = get_model_info()
+    tokenizer = model_info['gpt-4']['tokenizer']
+    # 只保留最近的128条记录，无论token长度，防止计算token时计算过长的时间
+    max_round = get_conf('AUTO_CONTEXT_MAX_ROUND')
+    char_len = sum([len(h) for h in context])
+    if char_len < trigger_clip_token_len*2:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    if len(context) > max_round:
+        context = context[-max_round:]
+    # 计算各个历史记录的token长度
+    context_token_num = [get_token_num(h, tokenizer) for h in context]
+    context_token_num_old = copy.copy(context_token_num)
+    total_token_num = total_token_num_old = sum(context_token_num)
+    if total_token_num < trigger_clip_token_len:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    clip_token_len = trigger_clip_token_len * 0.85
+    # 越长越先被裁，越靠后越先被裁
+    max_clip_ratio: list[float] = get_conf('AUTO_CONTEXT_MAX_CLIP_RATIO')
+    max_clip_ratio = list(reversed(max_clip_ratio))
+    if len(context) > len(max_clip_ratio):
+        # give up the oldest context
+        context = context[-len(max_clip_ratio):]
+        context_token_num = context_token_num[-len(max_clip_ratio):]
+    if len(context) < len(max_clip_ratio):
+        # match the length of two array
+        max_clip_ratio = max_clip_ratio[-len(context):]
+    
+    # compute rank
+    clip_prior_weight = [(token_num/clip_token_len + (len(context) - index)*0.1) for index, token_num in enumerate(context_token_num)]
+    # print('clip_prior_weight', clip_prior_weight)
+    # get sorted index of context_token_num, from largest to smallest
+    sorted_index = sorted(range(len(context_token_num)), key=lambda k: clip_prior_weight[k], reverse=True)
+
+    # pre compute space yield
+    for index in sorted_index:
+        print('index', index, f'current total {total_token_num}, target {clip_token_len}')
+        if total_token_num < clip_token_len:
+            # no need to clip
+            break
+        # clip room left
+        clip_room_left = total_token_num - clip_token_len
+        # get the clip ratio
+        allowed_token_num_this_entry = max_clip_ratio[index] * clip_token_len
+        if context_token_num[index] < allowed_token_num_this_entry:
+            print('index', index, '[allowed] before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+
+        token_to_clip = context_token_num[index] - allowed_token_num_this_entry
+        if token_to_clip*0.85 > clip_room_left:
+            print('index', index, '[careful clip] token_to_clip', token_to_clip, 'clip_room_left', clip_room_left)
+            token_to_clip = clip_room_left
+
+        token_percent_to_clip = token_to_clip / context_token_num[index]
+        char_percent_to_clip = token_percent_to_clip
+        text_this_entry = context[index]
+        char_num_to_clip = int(len(text_this_entry) * char_percent_to_clip)
+        if char_num_to_clip < 500:
+            # 如果裁剪的字符数小于500，则不裁剪
+            print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+        char_num_to_clip += 200 # 稍微多加一点
+        char_to_preseve = len(text_this_entry) - char_num_to_clip
+        _half = int(char_to_preseve / 2)
+        # 前半 + ... (content clipped because token overflows) ... + 后半
+        text_this_entry_clip = text_this_entry[:_half] + \
+                             " ... (content clipped because token overflows) ... " \
+                             + text_this_entry[-_half:]
+        context[index] = text_this_entry_clip
+        post_clip_token_cnt = get_token_num(text_this_entry_clip, tokenizer)
+        print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry, 'after', post_clip_token_cnt)
+        context_token_num[index] = post_clip_token_cnt
+        total_token_num = sum(context_token_num)
+    context_token_num_final = [get_token_num(h, tokenizer) for h in context]
+    print('context_token_num_old', context_token_num_old)
+    print('context_token_num_final', context_token_num_final)
+    print('token change from', total_token_num_old, 'to', sum(context_token_num_final), 'target', clip_token_len)
+    history = context[:-1]
+    current = context[-1]
+    return current, history
+
+
+
+def auto_context_clip_search_optimal(current, history, promote_latest_long_message=False):
+    """
+    current: 当前消息
+    history: 历史消息列表
+    promote_latest_long_message: 是否特别提高最后一条长message的权重，避免过度裁剪
+
+    主动触发裁剪
+    """
+    context = history + [current]
+    trigger_clip_token_len = get_conf('AUTO_CONTEXT_CLIP_TRIGGER_TOKEN_LEN')
+    model_info = get_model_info()
+    tokenizer = model_info['gpt-4']['tokenizer']
+    # 只保留最近的128条记录，无论token长度，防止计算token时计算过长的时间
+    max_round = get_conf('AUTO_CONTEXT_MAX_ROUND')
+    char_len = sum([len(h) for h in context])
+    if char_len < trigger_clip_token_len:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    if len(context) > max_round:
+        context = context[-max_round:]
+    # 计算各个历史记录的token长度
+    context_token_num = [get_token_num(h, tokenizer) for h in context]
+    context_token_num_old = copy.copy(context_token_num)
+    total_token_num = total_token_num_old = sum(context_token_num)
+    if total_token_num < trigger_clip_token_len:
+        # 不需要裁剪
+        history = context[:-1]
+        current = context[-1]
+        return current, history
+    clip_token_len = trigger_clip_token_len * 0.90
+    max_clip_ratio: list[float] = get_conf('AUTO_CONTEXT_MAX_CLIP_RATIO')
+    max_clip_ratio = list(reversed(max_clip_ratio))
+    if len(context) > len(max_clip_ratio):
+        # give up the oldest context
+        context = context[-len(max_clip_ratio):]
+        context_token_num = context_token_num[-len(max_clip_ratio):]
+    if len(context) < len(max_clip_ratio):
+        # match the length of two array
+        max_clip_ratio = max_clip_ratio[-len(context):]
+
+    _scale = _scale_init = 1.25
+    token_percent_arr = [(token_num/clip_token_len) for index, token_num in enumerate(context_token_num)]
+
+    # promote last long message, avoid clipping it too much
+    if promote_latest_long_message:
+        promote_weight_constant = 1.6
+        promote_index = -1
+        threshold = 0.50
+        for index, token_percent in enumerate(token_percent_arr):
+            if token_percent > threshold:
+                promote_index = index
+        if promote_index >= 0:
+            max_clip_ratio[promote_index] = promote_weight_constant
+
+    max_clip_ratio_arr = max_clip_ratio
+    step = 0.05
+    for i in range(int(_scale_init / step) - 1):
+        _take = 0
+        for max_clip, token_r in zip(max_clip_ratio_arr, token_percent_arr):
+            _take += min(max_clip * _scale, token_r)
+        if _take < 1.0:
+            break
+        _scale -= 0.05
+
+    # print('optimal scale', _scale)
+    # print([_scale * max_clip for max_clip in max_clip_ratio_arr])
+    # print([token_r for token_r in token_percent_arr])
+    # print([min(token_r, _scale * max_clip) for token_r, max_clip in zip(token_percent_arr, max_clip_ratio_arr)])
+    eps = 0.05
+    max_clip_ratio = [_scale * max_clip + eps for max_clip in max_clip_ratio_arr]
+
+    # compute rank
+    # clip_prior_weight_old = [(token_num/clip_token_len + (len(context) - index)*0.1) for index, token_num in enumerate(context_token_num)]
+    clip_prior_weight = [ token_r / max_clip  for max_clip, token_r in zip(max_clip_ratio_arr, token_percent_arr)]
+
+    # sorted_index_old = sorted(range(len(context_token_num)), key=lambda k: clip_prior_weight_old[k], reverse=True)
+    # print('sorted_index_old', sorted_index_old)
+    sorted_index = sorted(range(len(context_token_num)), key=lambda k: clip_prior_weight[k], reverse=True)
+    # print('sorted_index', sorted_index)
+
+    # pre compute space yield
+    for index in sorted_index:
+        # print('index', index, f'current total {total_token_num}, target {clip_token_len}')
+        if total_token_num < clip_token_len:
+            # no need to clip
+            break
+        # clip room left
+        clip_room_left = total_token_num - clip_token_len
+        # get the clip ratio
+        allowed_token_num_this_entry = max_clip_ratio[index] * clip_token_len
+        if context_token_num[index] < allowed_token_num_this_entry:
+            # print('index', index, '[allowed] before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+
+        token_to_clip = context_token_num[index] - allowed_token_num_this_entry
+        if token_to_clip*0.85 > clip_room_left:
+            # print('index', index, '[careful clip] token_to_clip', token_to_clip, 'clip_room_left', clip_room_left)
+            token_to_clip = clip_room_left
+
+        token_percent_to_clip = token_to_clip / context_token_num[index]
+        char_percent_to_clip = token_percent_to_clip
+        text_this_entry = context[index]
+        char_num_to_clip = int(len(text_this_entry) * char_percent_to_clip)
+        if char_num_to_clip < 500:
+            # 如果裁剪的字符数小于500，则不裁剪
+            # print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry)
+            continue
+        eps = 200
+        char_num_to_clip = char_num_to_clip + eps # 稍微多加一点
+        char_to_preseve = len(text_this_entry) - char_num_to_clip
+        _half = int(char_to_preseve / 2)
+        # 前半 + ... (content clipped because token overflows) ... + 后半
+        text_this_entry_clip = text_this_entry[:_half] + \
+                             " ... (content clipped because token overflows) ... " \
+                             + text_this_entry[-_half:]
+        context[index] = text_this_entry_clip
+        post_clip_token_cnt = get_token_num(text_this_entry_clip, tokenizer)
+        # print('index', index, 'before', context_token_num[index], 'allowed', allowed_token_num_this_entry, 'after', post_clip_token_cnt)
+        context_token_num[index] = post_clip_token_cnt
+        total_token_num = sum(context_token_num)
+    context_token_num_final = [get_token_num(h, tokenizer) for h in context]
+    # print('context_token_num_old', context_token_num_old)
+    # print('context_token_num_final', context_token_num_final)
+    # print('token change from', total_token_num_old, 'to', sum(context_token_num_final), 'target', clip_token_len)
+    history = context[:-1]
+    current = context[-1]
+    return current, history

shared_utils/fastapi_server.py

@@ -51,7 +51,7 @@ def validate_path_safety(path_or_url, user):
     from toolbox import get_conf, default_user_name
     from toolbox import FriendlyException
     PATH_PRIVATE_UPLOAD, PATH_LOGGING = get_conf('PATH_PRIVATE_UPLOAD', 'PATH_LOGGING')
-    sensitive_path = None
+    sensitive_path = None   # 必须不能包含 '/'，即不能是多级路径
     path_or_url = os.path.relpath(path_or_url)
     if path_or_url.startswith(PATH_LOGGING):    # 日志文件（按用户划分）
         sensitive_path = PATH_LOGGING

shared_utils/handle_upload.py

@@ -88,6 +88,32 @@ def zip_extract_member_new(self, member, targetpath, pwd):
     return targetpath
 
 
+
+def safe_extract_rar(file_path, dest_dir):
+    import rarfile
+    import posixpath
+    with rarfile.RarFile(file_path) as rf:
+        os.makedirs(dest_dir, exist_ok=True)
+        base_path = os.path.abspath(dest_dir)
+        for file_info in rf.infolist():
+            orig_filename = file_info.filename
+            filename = posixpath.normpath(orig_filename).lstrip('/')
+            # 路径遍历防护
+            if '..' in filename or filename.startswith('../'):
+                raise Exception(f"Attempted Path Traversal in {orig_filename}")
+            # 符号链接防护
+            if hasattr(file_info, 'is_symlink') and file_info.is_symlink():
+                raise Exception(f"Attempted Symlink in {orig_filename}")
+            # 构造完整目标路径
+            target_path = os.path.join(base_path, filename)
+            final_path = os.path.normpath(target_path)
+            # 最终路径校验
+            if not final_path.startswith(base_path):
+                raise Exception(f"Attempted Path Traversal in {orig_filename}")
+        rf.extractall(dest_dir)
+
+
+
 def extract_archive(file_path, dest_dir):
     import zipfile
     import tarfile
@@ -111,6 +137,8 @@ def extract_archive(file_path, dest_dir):
                     member_path = os.path.normpath(member.name)
                     full_path = os.path.join(dest_dir, member_path)
                     full_path = os.path.abspath(full_path)
+                    if member.islnk() or member.issym():
+                        raise Exception(f"Attempted Symlink in {member.name}")
                     if not full_path.startswith(os.path.abspath(dest_dir) + os.sep):
                         raise Exception(f"Attempted Path Traversal in {member.name}")
 
@@ -130,14 +158,11 @@ def extract_archive(file_path, dest_dir):
     # 此外，Windows上还需要安装winrar软件，配置其Path环境变量，如"C:\Program Files\WinRAR"才可以
     elif file_extension == ".rar":
         try:
-            import rarfile
-
-            with rarfile.RarFile(file_path) as rf:
-                rf.extractall(path=dest_dir)
-                logger.info("Successfully extracted rar archive to {}".format(dest_dir))
+            import rarfile  # 用来检查rarfile是否安装，不要删除
+            safe_extract_rar(file_path, dest_dir)
         except:
             logger.info("Rar format requires additional dependencies to install")
-            return "\n\n解压失败! 需要安装pip install rarfile来解压rar文件。建议：使用zip压缩格式。"
+            return "<br/><br/>解压失败! 需要安装pip install rarfile来解压rar文件。建议：使用zip压缩格式。"
 
     # 第三方库，需要预先pip install py7zr
     elif file_extension == ".7z":
@@ -149,7 +174,7 @@ def extract_archive(file_path, dest_dir):
                 logger.info("Successfully extracted 7z archive to {}".format(dest_dir))
         except:
             logger.info("7z format requires additional dependencies to install")
-            return "\n\n解压失败! 需要安装pip install py7zr来解压7z文件"
+            return "<br/><br/>解压失败! 需要安装pip install py7zr来解压7z文件"
     else:
         return ""
     return ""

shared_utils/key_pattern_manager.py

@@ -4,7 +4,6 @@ from functools import wraps, lru_cache
 from shared_utils.advanced_markdown_format import format_io
 from shared_utils.config_loader import get_conf as get_conf
 
-
 pj = os.path.join
 default_user_name = 'default_user'
 
@@ -12,11 +11,13 @@ default_user_name = 'default_user'
 openai_regex = re.compile(
     r"sk-[a-zA-Z0-9_-]{48}$|" +
     r"sk-[a-zA-Z0-9_-]{92}$|" +
-    r"sk-proj-[a-zA-Z0-9_-]{48}$|"+
-    r"sk-proj-[a-zA-Z0-9_-]{124}$|"+
-    r"sk-proj-[a-zA-Z0-9_-]{156}$|"+ #新版apikey位数不匹配故修改此正则表达式
+    r"sk-proj-[a-zA-Z0-9_-]{48}$|" +
+    r"sk-proj-[a-zA-Z0-9_-]{124}$|" +
+    r"sk-proj-[a-zA-Z0-9_-]{156}$|" +  #新版apikey位数不匹配故修改此正则表达式
     r"sess-[a-zA-Z0-9]{40}$"
 )
+
+
 def is_openai_api_key(key):
     CUSTOM_API_KEY_PATTERN = get_conf('CUSTOM_API_KEY_PATTERN')
     if len(CUSTOM_API_KEY_PATTERN) != 0:
@@ -27,7 +28,7 @@ def is_openai_api_key(key):
 
 
 def is_azure_api_key(key):
-    API_MATCH_AZURE = re.match(r"[a-zA-Z0-9]{32}$", key)
+    API_MATCH_AZURE = re.match(r"^[a-zA-Z0-9]{32}$|^[a-zA-Z0-9]{84}", key)
     return bool(API_MATCH_AZURE)
 
 
@@ -35,10 +36,12 @@ def is_api2d_key(key):
     API_MATCH_API2D = re.match(r"fk[a-zA-Z0-9]{6}-[a-zA-Z0-9]{32}$", key)
     return bool(API_MATCH_API2D)
 
+
 def is_openroute_api_key(key):
     API_MATCH_OPENROUTE = re.match(r"sk-or-v1-[a-zA-Z0-9]{64}$", key)
     return bool(API_MATCH_OPENROUTE)
 
+
 def is_cohere_api_key(key):
     API_MATCH_AZURE = re.match(r"[a-zA-Z0-9]{40}$", key)
     return bool(API_MATCH_AZURE)
@@ -79,6 +82,14 @@ def what_keys(keys):
 
     return f"检测到： OpenAI Key {avail_key_list['OpenAI Key']} 个, Azure Key {avail_key_list['Azure Key']} 个, API2D Key {avail_key_list['API2D Key']} 个"
 
+def is_o_family_for_openai(llm_model):
+    if not llm_model.startswith('o'):
+        return False
+    if llm_model in ['o1', 'o2', 'o3', 'o4', 'o5', 'o6', 'o7', 'o8']:
+        return True
+    if llm_model[:3] in ['o1-', 'o2-', 'o3-', 'o4-', 'o5-', 'o6-', 'o7-', 'o8-']:
+        return True
+    return False
 
 def select_api_key(keys, llm_model):
     import random
@@ -86,7 +97,7 @@ def select_api_key(keys, llm_model):
     key_list = keys.split(',')
 
     if llm_model.startswith('gpt-') or llm_model.startswith('chatgpt-') or \
-       llm_model.startswith('one-api-') or llm_model == 'o1' or llm_model.startswith('o1-'):
+       llm_model.startswith('one-api-') or is_o_family_for_openai(llm_model):
         for k in key_list:
             if is_openai_api_key(k): avail_key_list.append(k)
 
@@ -101,7 +112,7 @@ def select_api_key(keys, llm_model):
     if llm_model.startswith('cohere-'):
         for k in key_list:
             if is_cohere_api_key(k): avail_key_list.append(k)
-    
+
     if llm_model.startswith('openrouter-'):
         for k in key_list:
             if is_openroute_api_key(k): avail_key_list.append(k)
@@ -109,7 +120,7 @@ def select_api_key(keys, llm_model):
     if len(avail_key_list) == 0:
         raise RuntimeError(f"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。您可能选择了错误的模型或请求源（左上角更换模型菜单中可切换openai,azure,claude,cohere等请求源）。")
 
-    api_key = random.choice(avail_key_list) # 随机负载均衡
+    api_key = random.choice(avail_key_list)  # 随机负载均衡
     return api_key
 
 
@@ -125,5 +136,5 @@ def select_api_key_for_embed_models(keys, llm_model):
     if len(avail_key_list) == 0:
         raise RuntimeError(f"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。您可能选择了错误的模型或请求源。")
 
-    api_key = random.choice(avail_key_list) # 随机负载均衡
+    api_key = random.choice(avail_key_list)  # 随机负载均衡
     return api_key

tests/test_markdown.py

@@ -45,28 +45,161 @@ Any folded content here. It requires an empty line just above it.
 
 md ="""
 
-在这种场景中，您希望机器 B 能够通过轮询机制来间接地“请求”机器 A，而实际上机器 A 只能主动向机器 B 发出请求。这是一种典型的客户端-服务器轮询模式。下面是如何实现这种机制的详细步骤：
+<details>
+<summary>第0份搜索结果 [源自google搜索] （汤姆·赫兰德）：</summary>
+<div class="search_result">https://baike.baidu.com/item/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7/3687216</div>
+<div class="search_result">Title: 汤姆·赫兰德
 
-### 机器 B 的实现
+URL Source: https://baike.baidu.com/item/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7/3687216
 
-1. **安装 FastAPI 和必要的依赖库**：
-   ```bash
-   pip install fastapi uvicorn
-   ```
+Markdown Content:
+网页新闻贴吧知道网盘图片视频地图文库资讯采购百科
+百度首页
+登录
+注册
+进入词条
+全站搜索
+帮助
+首页
+秒懂百科
+特色百科
+知识专题
+加入百科
+百科团队
+权威合作
+个人中心
+汤姆·赫兰德
+播报
+讨论
+上传视频
+英国男演员
+汤姆·赫兰德（Tom Holland），1996年6月1日出生于英国英格兰泰晤士河畔金斯顿，英国男演员。2008年，出演音乐剧《跳出我天地》而崭露头角。2010年，作为主演参加音乐剧《跳出我天地》的五周年特别演出。2012年10月11日，主演的个人首部电影《海啸奇迹》上映，并凭该电影获得第84届美国国家评论协会奖最具突破男演员奖。2016年10月15日，与查理·汉纳姆、西耶娜·米勒合作出演的电影《 ... >>>
 
-2. **创建 FastAPI 服务**：
-   ```python
-   from fastapi import FastAPI
-   from fastapi.responses import JSONResponse
-   from uuid import uuid4
-   from threading import Lock
-   import time
+目录
+1早年经历
+2演艺经历
+▪影坛新星
+▪角色多变
+▪跨界翘楚
+3个人生活
+▪家庭
+▪恋情
+▪社交
+4主要作品
+▪参演电影
+▪参演电视剧
+▪配音作品
+▪导演作品
+▪杂志写真
+5社会活动
+6获奖记录
+7人物评价
+基本信息
+汤姆·赫兰德（Tom Holland），1996年6月1日出生于英国英格兰泰晤士河畔金斯顿，英国男演员。 [67]
+2008年，出演音乐剧《跳出我天地》而崭露头角 [1]。2010年，作为主演参加音乐剧《跳出我天地》的五周年特别演出 [2]。2012年10月11日，主演的个人首部电影《海啸奇迹》上映，并凭该电影获得第84届美国国家评论协会奖最具突破男演员奖 [3]。2016年10月15日，与查理·汉纳姆、西耶娜·米勒合作出演的电影《迷失Z城》在纽约电影节首映 [17]；2017年，主演的《蜘蛛侠：英雄归来》上映，他凭该电影获得第19届青少年选择奖最佳暑期电影男演员奖，以及第70届英国电影和电视艺术学院奖最佳新星奖。 [72]2019年，主演的电影《蜘蛛侠：英雄远征》上映 [5]；同年，凭借该电影获得第21届青少年选择奖最佳夏日电影男演员奖 [6]。2024年4月，汤姆·霍兰德主演的伦敦西区新版舞台剧《罗密欧与朱丽叶》公布演员名单。 [66]
+2024年，......</div>
+</details>
 
-   app = FastAPI()
+<details>
+<summary>第1份搜索结果 [源自google搜索] （汤姆·霍兰德）：</summary>
+<div class="search_result">https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7</div>
+<div class="search_result">Title: 汤姆·赫兰德
 
-   # 字典用于存储请求和状态
-   requests = {}
-   process_lock = Lock()
+URL Source: https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7
+
+Published Time: 2015-06-24T01:08:01Z
+
+Markdown Content:
+| 汤姆·霍兰德
+Tom Holland |
+| --- |
+| [![Image 19](https://upload.wikimedia.org/wikipedia/commons/thumb/3/3c/Tom_Holland_by_Gage_Skidmore.jpg/220px-Tom_Holland_by_Gage_Skidmore.jpg)](https://zh.wikipedia.org/wiki/File:Tom_Holland_by_Gage_Skidmore.jpg)
+
+2016年在[圣地牙哥国际漫画展](https://zh.wikipedia.org/wiki/%E8%81%96%E5%9C%B0%E7%89%99%E5%93%A5%E5%9C%8B%E9%9A%9B%E6%BC%AB%E7%95%AB%E5%B1%95 "圣地牙哥国际漫画展")的霍兰德
+
+
+
+ |
+| 男演员 |
+| 昵称 | 荷兰弟[\[1\]](https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7#cite_note-1) |
+| 出生 | 汤玛斯·史丹利·霍兰德  
+（Thomas Stanley Holland）[\[2\]](https://zh.wikipedia.org/zh-hans/%E6%B1%A4%E5%A7%86%C2%B7%E8%B5%AB%E5%85%B0%E5%BE%B7#cite_note-2)
+
+  
+1996年6月1日（28岁）  
+
+英国[英格兰](https://zh.wikipedia.org/wiki/%E8%8B%B1%E6%A0%BC%E8%98%AD "英格兰")[泰晤士河畔金斯顿](https://zh.wikipedia.org/wiki/%E6%B3%B0%E6%99%A4......</div>
+</details>
+
+<details>
+<summary>第2份搜索结果 [源自google搜索] （为什么汤姆赫兰德被称为荷兰弟？）：</summary>
+<div class="search_result">https://www.zhihu.com/question/363988307</div>
+<div class="search_result">Title: 为什么汤姆赫兰德被称为荷兰弟？ - 知乎
+
+URL Source: https://www.zhihu.com/question/363988307
+
+Markdown Content:
+要说漫威演员里面，谁是最牛的存在，不好说，各有各的看法，但要说谁是最能剧透的，毫无疑问，是我们的汤姆赫兰德荷兰弟，可以说，他算得上是把剧透给玩明白了，先后剧透了不少的电影桥段，以至于漫威后面像防贼一样防着人家荷兰弟，可大家知道吗？你永远想象不到荷兰弟的嘴巴到底有多能漏风？
+
+![Image 9](https://pica.zhimg.com/50/v2-a0aa9972315519ec4975f974f01fc6ca_720w.jpg?source=1def8aca)
+
+故事要回到《侏罗纪世界2》的筹备期间，当时，荷兰弟也参与了面试，计划在剧中饰演一个角色，原本，这也没啥，这都是好莱坞的传统了，可是，当时的导演胡安根本不知道荷兰弟的“风光伟绩”，于是乎，人家便屁颠屁颠把侏罗纪世界2的资料拿过来给荷兰弟，虽然，后面没有让荷兰弟出演这部电影，但导演似乎忘了他的嘴巴是开过光的。
+
+![Image 10](https://picx.zhimg.com/50/v2-1da72b482c6a44e1826abb430d95a062_720w.jpg?source=1def8aca)
+
+荷兰弟把剧情刻在了脑子
+......</div>
+</details>
+
+<details>
+<summary>第3份搜索结果 [源自google搜索] （爱戴名表被喷配不上赞达亚，荷兰弟曝近照气质大变，2）：</summary>
+<div class="search_result">https://www.sohu.com/a/580380519_120702487</div>
+<div class="search_result">Title: 爱戴名表被喷配不上赞达亚，荷兰弟曝近照气质大变，26岁资产惊人_蜘蛛侠_手表_罗伯特·唐尼
+
+URL Source: https://www.sohu.com/a/580380519_120702487
+
+Markdown Content:
+2022-08-27 19:00 来源: [BEGEEL宾爵表](https://www.sohu.com/a/580380519_120702487?spm=smpc.content-abroad.content.1.1739375950559fBhgNpP)
+
+发布于：广东省
+
+近日，大家熟悉的荷兰弟，也就演漫威超级英雄“蜘蛛侠”而走红的英国男星汤姆·赫兰德（Tom Holland），最近在没有任何预警的情况下宣布自己暂停使用社交媒体，原因网络暴力已经严重影响到他的心理健康了。虽然自出演蜘蛛侠以来，对荷兰弟的骂声就没停过，但不可否认他确实是一位才貌双全的好演员，同时也是一位拥有高雅品味的地道英伦绅士，从他近年名表收藏的趋势也能略知一二。
+
+![Image 37](https://p5.itc.cn/q_70/images03/20220827/86aca867047b4119ba96a59e33d2d387.jpeg)
+
+2016年，《美国队长3：内战》上映，汤姆·赫兰德扮演的“史上最嫩”蜘蛛侠也正式登场。这个美国普通学生，由于意外被一只受过放射性感染的蜘蛛咬到，并因此获得超能力，化身邻居英雄蜘蛛侠警恶惩奸。和蜘蛛侠彼得·帕克一样，当时年仅20岁的荷兰弟无论戏里戏外的穿搭都是少年感十足，走的阳光邻家大男孩路线，手上戴的最多的就是来自卡西欧的电子表，还有来自Nixon sentry的手表，千元级别甚至是百元级。
+
+20岁的荷兰弟走的是邻家大男孩路线
+
+![Image 38](https://p3.itc.cn/q_70/images03/20220827/aded82ecfb1d439a8fd4741b49a8eb9b.png)
+
+随着荷兰弟主演的《蜘蛛侠：英雄归来》上演，第三代蜘蛛侠的话痨性格和年轻活力的形象瞬间圈粉无数。荷兰弟的知名度和演艺收入都大幅度增长，他的穿衣品味也渐渐从稚嫩少年风转变成轻熟绅士风。从简单的T恤短袖搭配牛仔裤，开始向更加丰富的造型发展，其中变化最明显的就是他手腕上的表。
+
+荷兰弟的衣品日......</div>
+</details>
+
+<details>
+<summary>第4份搜索结果 [源自google搜索] （荷兰弟居然要休息一年，因演戏演到精神分裂…）：</summary>
+<div class="search_result">https://www.sohu.com/a/683718058_544020</div>
+<div class="search_result">Title: 荷兰弟居然要休息一年，因演戏演到精神分裂…_Holland_Tom_工作
+
+URL Source: https://www.sohu.com/a/683718058_544020
+
+Markdown Content:
+荷兰弟居然要休息一年，因演戏演到精神分裂…\_Holland\_Tom\_工作
+=============== 
+
+*   [](http://www.sohu.com/?spm=smpc.content-abroad.nav.1.1739375954055TcEvWsY)
+*   [新闻](http://news.sohu.com/?spm=smpc.content-abroad.nav.2.1739375954055TcEvWsY)
+*   [体育](http://sports.sohu.com/?spm=smpc.content-abroad.nav.3.1739375954055TcEvWsY)
+*   [汽车](http://auto.sohu.com/?spm=smpc.content-abroad.nav.4.1739375954055TcEvWsY)
+*   [房产](http://www.focus.cn/?spm=smpc.content-abroad.nav.5.1739375954055TcEvWsY)
+*   [旅游](http://travel.sohu.com/?spm=smpc.content-abroad.nav.6.1739375954055TcEvWsY)
+*   [教育](http://learning.sohu.com/?spm=smpc.content-abroad.nav.7.1739375954055TcEvWsY)
+*   [时尚](http://fashion.sohu.com/?spm=smpc.content-abroad.nav.8.1739375954055TcEvWsY)
+*   [科技](http://it.sohu.com/?spm=smpc.content-abroad.nav.9.1739375954055TcEvWsY)
+*   [财经](http://business.sohu.com/?spm=smpc.content-abroad.nav.10.17393759......</div>
+</details>
 
 """
 def validate_path():

tests/test_media.py

@@ -48,8 +48,6 @@ if __name__ == "__main__":
 
     # plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
 
-    # plugin_test(plugin='crazy_functions.联网的ChatGPT->连接网络回答问题', main_input="谁是应急食品？")
-
     # plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
 
     # plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")

tests/test_plugins.py

@@ -48,8 +48,6 @@ if __name__ == "__main__":
 
     # plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695")
 
-    # plugin_test(plugin='crazy_functions.联网的ChatGPT->连接网络回答问题', main_input="谁是应急食品？")
-
     # plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples")
 
     # plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.")

tests/test_python_auto_docstring.py

@@ -9,7 +9,7 @@ from textwrap import dedent
 # TODO: 解决缩进问题
 
 find_function_end_prompt = '''
-Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to sperate functions, class functions etc.
+Below is a page of code that you need to read. This page may not yet complete, you job is to split this page to separate functions, class functions etc.
 - Provide the line number where the first visible function ends.
 - Provide the line number where the next visible function begins.
 - If there are no other functions in this page, you should simply return the line number of the last line.
@@ -58,7 +58,7 @@ OUTPUT:
 
 
 
-revise_funtion_prompt = '''
+revise_function_prompt = '''
 You need to read the following code, and revise the code according to following instructions:
 1. You should analyze the purpose of the functions (if there are any).
 2. You need to add docstring for the provided functions (if there are any).
@@ -147,7 +147,7 @@ class ContextWindowManager():
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_slience=True
+            console_silence=True
         )
 
         def extract_number(text):
@@ -240,15 +240,15 @@ class ContextWindowManager():
     def tag_code(self, fn):
         code = ''.join(fn)
         _, n_indent = self.dedent(code)
-        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preseve them in the OUTPUT.)"
+        indent_reminder = "" if n_indent == 0 else "(Reminder: as you can see, this piece of code has indent made up with {n_indent} whitespace, please preserve them in the OUTPUT.)"
         self.llm_kwargs['temperature'] = 0
         result = predict_no_ui_long_connection(
-            inputs=revise_funtion_prompt.format(THE_CODE=code, INDENT_REMINDER=indent_reminder),
+            inputs=revise_function_prompt.format(THE_CODE=code, INDENT_REMINDER=indent_reminder),
             llm_kwargs=self.llm_kwargs,
             history=[],
             sys_prompt="",
             observe_window=[],
-            console_slience=True
+            console_silence=True
         )
 
         def get_code_block(reply):

themes/common.css

@@ -311,3 +311,98 @@
     backdrop-filter: blur(10px);
     background-color: rgba(var(--block-background-fill), 0.5);
 }
+
+
+.reasoning_process {
+    font-size: smaller;
+    font-style: italic;
+    margin: 0px;
+    padding: 1em;
+    line-height: 1.5;
+    text-wrap: wrap;
+    opacity: 0.8;
+}
+
+.search_result {
+    font-size: smaller;
+    font-style: italic;
+    margin: 0px;
+    padding: 1em;
+    line-height: 1.5;
+    text-wrap: wrap;
+    opacity: 0.8;
+}
+
+.raw_text {
+    display: none;
+}
+
+.message_tail {
+    justify-content: center;
+    align-items: center;
+}
+.message_tail_stop {
+    border: dotted !important;
+    margin-top: 5px !important;
+    padding-left: 8px !important;
+    padding-top: 1px !important;
+    padding-bottom: 1px !important;
+    padding-right: 12px !important;
+}
+
+/* ant 开始 */
+
+/* 通用按钮样式 */
+.ant-btn {
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+    padding: 8px 16px;
+    font-size: 14px;
+    font-weight: bold;
+    border-radius: 4px;
+    cursor: pointer;
+    transition: background-color 0.3s;
+}
+
+/* 按钮颜色和状态 */
+.ant-btn-primary {
+    background-color: #1890ff;
+    color: white;
+    border: none;
+}
+
+.ant-btn-primary:hover {
+    background-color: #40a9ff;
+}
+
+.ant-btn-loading {
+    pointer-events: none;
+    opacity: 0.7;
+}
+
+/* 图标样式 */
+.ant-btn-icon {
+    display: inline-flex;
+    margin-right: 8px;
+}
+
+.anticon {
+    width: 1em;
+    height: 1em;
+    fill: currentColor;
+}
+
+.anticon-spin {
+    animation: spin 1s linear infinite;
+}
+
+/* 动画效果 */
+@keyframes spin {
+    from {
+        transform: rotate(0deg);
+    }
+    to {
+        transform: rotate(360deg);
+    }
+}

themes/common.js

@@ -259,7 +259,24 @@ function cancel_loading_status() {
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
 //  第 2 部分: 复制按钮
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
+// 解压缩函数
+function decompressString(compressedString) {
+    // 第1步：Base64解码
+    const binaryString = atob(compressedString);
 
+    // 第2步：将二进制字符串转换为Uint8Array
+    const bytes = new Uint8Array(binaryString.length);
+    for (let i = 0; i < binaryString.length; i++) {
+        bytes[i] = binaryString.charCodeAt(i);
+    }
+
+    // 第3步：使用DecompressionStream (基于Web Streams API)进行gzip解压缩
+    const ds = new DecompressionStream('gzip');
+    const decompressedStream = new Response(new Blob([bytes])).body.pipeThrough(ds);
+
+    // 第4步：获取解压后的数据并转换为字符串
+    return new Response(decompressedStream).text();
+}
 
 var allow_auto_read_continously = true;
 var allow_auto_read_tts_flag = false;
@@ -272,7 +289,7 @@ function addCopyButton(botElement, index, is_last_in_arr) {
     const audioIcon = '<span><svg t="1713628577799" fill="currentColor" class="icon" viewBox="0 0 1024 1024" version="1.1" xmlns="http://www.w3.org/2000/svg" p-id="4587" width=".9em" height=".9em"><path d="M113.7664 540.4672c0-219.9552 178.2784-398.2336 398.2336-398.2336S910.2336 320.512 910.2336 540.4672v284.4672c0 31.4368-25.4976 56.9344-56.9344 56.9344h-56.9344c-31.4368 0-56.9344-25.4976-56.9344-56.9344V597.2992c0-31.4368 25.4976-56.9344 56.9344-56.9344h56.9344c0-188.5184-152.7808-341.2992-341.2992-341.2992S170.7008 351.9488 170.7008 540.4672h56.9344c31.4368 0 56.9344 25.4976 56.9344 56.9344v227.5328c0 31.4368-25.4976 56.9344-56.9344 56.9344h-56.9344c-31.4368 0-56.9344-25.4976-56.9344-56.9344V540.4672z" p-id="4588"></path></svg></span>';
     // const cancelAudioIcon = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"></rect><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"></path></svg></span>';
 
-    // 此功能没准备好
+    // audio functionality
     if (allow_auto_read_continously && is_last_in_arr && allow_auto_read_tts_flag) {
         process_latest_text_output(botElement.innerText, index);
     }
@@ -283,19 +300,21 @@ function addCopyButton(botElement, index, is_last_in_arr) {
         return;
     }
 
-    var copyButton = document.createElement('button');
-    copyButton.classList.add('copy-bot-btn');
-    copyButton.setAttribute('aria-label', 'Copy');
-    copyButton.innerHTML = copyIcon;
-    copyButton.addEventListener('click', async () => {
-        const textToCopy = botElement.innerText;
+    // 原始文本拷贝
+    var copyButtonOrig = document.createElement('button');
+    copyButtonOrig.classList.add('copy-bot-btn');
+    copyButtonOrig.setAttribute('aria-label', 'Copy');
+    copyButtonOrig.innerHTML = copyIcon;
+    copyButtonOrig.addEventListener('click', async () => {
         try {
+            const base64gzipcode = botElement.getElementsByClassName('raw_text')[0].innerText;
+            const textToCopy = await decompressString(base64gzipcode);
             // push_text_to_audio(textToCopy).catch(console.error);
             if ("clipboard" in navigator) {
                 await navigator.clipboard.writeText(textToCopy);
-                copyButton.innerHTML = copiedIcon;
+                copyButtonOrig.innerHTML = copiedIcon;
                 setTimeout(() => {
-                    copyButton.innerHTML = copyIcon;
+                    copyButtonOrig.innerHTML = copyIcon;
                 }, 1500);
             } else {
                 const textArea = document.createElement("textarea");
@@ -304,9 +323,9 @@ function addCopyButton(botElement, index, is_last_in_arr) {
                 textArea.select();
                 try {
                     document.execCommand('copy');
-                    copyButton.innerHTML = copiedIcon;
+                    copyButtonOrig.innerHTML = copiedIcon;
                     setTimeout(() => {
-                        copyButton.innerHTML = copyIcon;
+                        copyButtonOrig.innerHTML = copyIcon;
                     }, 1500);
                 } catch (error) {
                     console.error("Copy failed: ", error);
@@ -345,7 +364,8 @@ function addCopyButton(botElement, index, is_last_in_arr) {
 
     var messageBtnColumn = document.createElement('div');
     messageBtnColumn.classList.add('message-btn-row');
-    messageBtnColumn.appendChild(copyButton);
+    // messageBtnColumn.appendChild(copyButton);
+    messageBtnColumn.appendChild(copyButtonOrig);
     if (enable_tts) {
         messageBtnColumn.appendChild(audioButton);
     }
@@ -381,7 +401,6 @@ function do_something_but_not_too_frequently(min_interval, func) {
 
 
 function chatbotContentChanged(attempt = 1, force = false) {
-    // https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
     for (var i = 0; i < attempt; i++) {
         setTimeout(() => {
             const messages = gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot');
@@ -392,6 +411,9 @@ function chatbotContentChanged(attempt = 1, force = false) {
                 // Now pass both the message element and the is_last_in_arr boolean to addCopyButton
                 addCopyButton(message, index, is_last_in_arr);
 
+                // if last message, add stop btn link
+                addStopButton(message, index, is_last_in_arr);
+
                 // save_conversation_history
                 save_conversation_history_slow_down();
             });
@@ -402,6 +424,79 @@ function chatbotContentChanged(attempt = 1, force = false) {
 
 }
 
+function addStopButton(botElement, index, is_last_in_arr) {
+    function is_generating() {
+        var statePanelElement = document.getElementById("state-panel");
+        var generatingElement = statePanelElement.querySelector(".generating");
+        if (generatingElement) {
+            return true;
+        } else {
+            return false;
+        }
+    }
+    function on_stop_btn_click() {
+        let stopButton = document.getElementById("elem_stop");
+        stopButton.click();
+    }
+    function remove_stop_generate_btn(messageTailElement) {
+        // remove all child elements of messageTailElement
+        while (messageTailElement.firstChild) {
+            messageTailElement.removeChild(messageTailElement.firstChild);
+        }
+        messageTailElement.style.display = 'none';
+        messageTailElement.classList.add('removed');
+    }
+    function add_stop_generate_btn() {
+        // write here: add a beautiful stop btn `bottomElement` as child, when clicked execute on_stop_btn_click
+        console.log("get_gradio_component")
+        const bottomElement = document.createElement('button');
+        bottomElement.className = 'ant-btn ant-btn-primary';
+        bottomElement.innerHTML = `
+            <span class="ant-btn-icon">
+                <svg viewBox="64 64 896 896" focusable="false" data-icon="sync" width="1em" height="1em" fill="currentColor" aria-hidden="true" class="anticon anticon-sync anticon-spin">
+                <path d="M168 504.2c1-43.7 10-86.1 26.9-126 17.3-41 42.1-77.7 73.7-109.4S337 212.3 378 195c42.4-17.9 87.4-27 133.9-27s91.5 9.1 133.8 27A341.5 341.5 0 01755 268.8c9.9 9.9 19.2 20.4 27.8 31.4l-60.2 47a8 8 0 003 14.1l175.7 43c5 1.2 9.9-2.6 9.9-7.7l.8-180.9c0-6.7-7.7-10.5-12.9-6.3l-56.4 44.1C765.8 155.1 646.2 92 511.8 92 282.7 92 96.3 275.6 92 503.8a8 8 0 008 8.2h60c4.4 0 7.9-3.5 8-7.8zm756 7.8h-60c-4.4 0-7.9 3.5-8 7.8-1 43.7-10 86.1-26.9 126-17.3 41-42.1 77.8-73.7 109.4A342.45 342.45 0 01512.1 856a342.24 342.24 0 01-243.2-100.8c-9.9-9.9-19.2-20.4-27.8-31.4l60.2-47a8 8 0 00-3-14.1l-175.7-43c-5-1.2-9.9 2.6-9.9 7.7l-.7 181c0 6.7 7.7 10.5 12.9 6.3l56.4-44.1C258.2 868.9 377.8 932 512.2 932c229.2 0 415.5-183.7 419.8-411.8a8 8 0 00-8-8.2z"></path>
+                </svg>
+            </span>
+            <span>终止</span>
+        `;
+        bottomElement.classList.add('message_tail_stop');
+        bottomElement.addEventListener('click', on_stop_btn_click);
+        messageTailElement.appendChild(bottomElement);
+    }
+
+    // find a sub element of class `message_tail`
+    const messageTailElement = botElement.querySelector('.message_tail');
+    // if not is_last_in_arr, hide this elem (display none)
+    if (!messageTailElement) {
+        return;
+    }
+    if (messageTailElement.classList.contains('removed')) {
+        return;
+    }
+    if (!is_last_in_arr) {
+        remove_stop_generate_btn(messageTailElement);
+        return;
+    }
+    messageTailElement.style.display = 'flex';
+    const messageTailStopElem = messageTailElement.querySelector('.message_tail_stop');
+    if(!is_generating()) {
+        setTimeout(() => {
+            if(!is_generating()) {
+                remove_stop_generate_btn(messageTailElement);
+                return;
+            } else {
+                if (!messageTailStopElem) {
+                    add_stop_generate_btn()
+                }
+            }
+        }, 500);
+    } else {
+        if (!messageTailStopElem) {
+            add_stop_generate_btn()
+        }
+    }
+
+}
 
 
 // -=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
@@ -1089,6 +1184,15 @@ async function clear_conversation(a, b, c) {
     update_conversation_metadata();
     let stopButton = document.getElementById("elem_stop");
     stopButton.click();
+    // Save back to local storage
+    try {
+        const EVENT_NAME = "gptac_reset_btn_clicked";
+        window.dispatchEvent(
+            new CustomEvent(EVENT_NAME, {
+                detail: ""
+            })
+        );
+    } catch (e) {}
     return reset_conversation(a, b);
 }
 

themes/waifu_plugin/live2d.js

@@ -598,7 +598,7 @@ function(t) {
 	default.VIEW_LOGICAL_MAX_BOTTOM, w.
 	default.VIEW_LOGICAL_MAX_TOP), B.setMaxScale(w.
 	default.VIEW_MAX_SCALE), B.setMinScale(w.
-	default.VIEW_MIN_SCALE), U = new M.L2DMatrix44, U.multScale(1, i / e), G = new M.L2DMatrix44, G.multTranslate(-i / 2, -e / 2), G.multScale(2 / i, -2 / i), F = v(), (0, D.setContext)(F), !F) return console.error("Failed to create WebGL context."), void(window.WebGLRenderingContext && console.error("Your browser don't support WebGL, check https://get.webgl.org/ for futher information."));
+	default.VIEW_MIN_SCALE), U = new M.L2DMatrix44, U.multScale(1, i / e), G = new M.L2DMatrix44, G.multTranslate(-i / 2, -e / 2), G.multScale(2 / i, -2 / i), F = v(), (0, D.setContext)(F), !F) return console.error("Failed to create WebGL context."), void(window.WebGLRenderingContext && console.error("Your browser don't support WebGL, check https://get.webgl.org/ for further information."));
 		window.Live2D.setGL(F), F.clearColor(0, 0, 0, 0), a(t), s()
 	}
 	function s() {

toolbox.py

@@ -37,6 +37,9 @@ from shared_utils.handle_upload import html_local_file
 from shared_utils.handle_upload import html_local_img
 from shared_utils.handle_upload import file_manifest_filter_type
 from shared_utils.handle_upload import extract_archive
+from shared_utils.context_clip_policy import clip_history
+from shared_utils.context_clip_policy import auto_context_clip_each_message
+from shared_utils.context_clip_policy import auto_context_clip_search_optimal
 from typing import List
 pj = os.path.join
 default_user_name = "default_user"
@@ -133,6 +136,9 @@ def ArgsGeneralWrapper(f):
             if len(args) == 0:  # 插件通道
                 yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, request)
             else:               # 对话通道，或者基础功能通道
+                # 基础对话通道，或者基础功能通道
+                if get_conf('AUTO_CONTEXT_CLIP_ENABLE'):
+                    txt_passon, history = auto_context_clip(txt_passon, history)
                 yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
         else:
             # 处理少数情况下的特殊插件的锁定状态
@@ -183,7 +189,7 @@ def update_ui(chatbot:ChatBotWithCookies, history:list, msg:str="正常", **kwar
     yield cookies, chatbot_gr, json_history, msg
 
 
-def update_ui_lastest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay:float=1, msg:str="正常"):  # 刷新界面
+def update_ui_latest_msg(lastmsg:str, chatbot:ChatBotWithCookies, history:list, delay:float=1, msg:str="正常"):  # 刷新界面
     """
     刷新用户界面
     """
@@ -499,6 +505,22 @@ def to_markdown_tabs(head: list, tabs: list, alignment=":---:", column=False, om
 
     return tabs_list
 
+def validate_file_size(files, max_size_mb=500):
+    """
+    验证文件大小是否在允许范围内。
+    :param files: 文件的完整路径的列表
+    :param max_size_mb: 最大文件大小，单位为MB（默认500MB）
+    :return: True 如果文件大小有效，否则抛出异常
+    """
+    # 获取文件大小（字节）
+    total_size = 0
+    max_size_bytes = max_size_mb * 1024 * 1024
+    for file in files:
+        total_size  += os.path.getsize(file.name)
+        if total_size > max_size_bytes:
+            raise ValueError(f"File size exceeds the allowed limit of {max_size_mb} MB. "
+                            f"Current size: {total_size / (1024 * 1024):.2f} MB")
+    return True
 
 def on_file_uploaded(
     request: gradio.Request, files:List[str], chatbot:ChatBotWithCookies,
@@ -510,6 +532,7 @@ def on_file_uploaded(
     if len(files) == 0:
         return chatbot, txt
 
+    validate_file_size(files, max_size_mb=500)
     # 创建工作路径
     user_name = default_user_name if not request.username else request.username
     time_tag = gen_time_str()
@@ -679,7 +702,7 @@ def run_gradio_in_subpath(demo, auth, port, custom_path):
             return True
         if len(path) == 0:
             logger.info(
-                "ilegal custom path: {}\npath must not be empty\ndeploy on root url".format(
+                "illegal custom path: {}\npath must not be empty\ndeploy on root url".format(
                     path
                 )
             )
@@ -690,14 +713,14 @@ def run_gradio_in_subpath(demo, auth, port, custom_path):
                 return True
             return False
         logger.info(
-            "ilegal custom path: {}\npath should begin with '/'\ndeploy on root url".format(
+            "illegal custom path: {}\npath should begin with '/'\ndeploy on root url".format(
                 path
             )
         )
         return False
 
     if not is_path_legal(custom_path):
-        raise RuntimeError("Ilegal custom path")
+        raise RuntimeError("Illegal custom path")
     import uvicorn
     import gradio as gr
     from fastapi import FastAPI
@@ -712,66 +735,14 @@ def run_gradio_in_subpath(demo, auth, port, custom_path):
     app = gr.mount_gradio_app(app, demo, path=custom_path)
     uvicorn.run(app, host="0.0.0.0", port=port)  # , auth=auth
 
-
-def clip_history(inputs, history, tokenizer, max_token_limit):
-    """
-    reduce the length of history by clipping.
-    this function search for the longest entries to clip, little by little,
-    until the number of token of history is reduced under threshold.
-    通过裁剪来缩短历史记录的长度。
-    此函数逐渐地搜索最长的条目进行剪辑，
-    直到历史记录的标记数量降低到阈值以下。
-    """
-    import numpy as np
-    from request_llms.bridge_all import model_info
-
-    def get_token_num(txt):
-        return len(tokenizer.encode(txt, disallowed_special=()))
-
-    input_token_num = get_token_num(inputs)
-
-    if max_token_limit < 5000:
-        output_token_expect = 256  # 4k & 2k models
-    elif max_token_limit < 9000:
-        output_token_expect = 512  # 8k models
+def auto_context_clip(current, history, policy='search_optimal'):
+    if policy == 'each_message':
+        return auto_context_clip_each_message(current, history)
+    elif policy == 'search_optimal':
+        return auto_context_clip_search_optimal(current, history)
     else:
-        output_token_expect = 1024  # 16k & 32k models
+        raise RuntimeError(f"未知的自动上下文裁剪策略: {policy}。")
 
-    if input_token_num < max_token_limit * 3 / 4:
-        # 当输入部分的token占比小于限制的3/4时，裁剪时
-        # 1. 把input的余量留出来
-        max_token_limit = max_token_limit - input_token_num
-        # 2. 把输出用的余量留出来
-        max_token_limit = max_token_limit - output_token_expect
-        # 3. 如果余量太小了，直接清除历史
-        if max_token_limit < output_token_expect:
-            history = []
-            return history
-    else:
-        # 当输入部分的token占比 > 限制的3/4时，直接清除历史
-        history = []
-        return history
-
-    everything = [""]
-    everything.extend(history)
-    n_token = get_token_num("\n".join(everything))
-    everything_token = [get_token_num(e) for e in everything]
-
-    # 截断时的颗粒度
-    delta = max(everything_token) // 16
-
-    while n_token > max_token_limit:
-        where = np.argmax(everything_token)
-        encoded = tokenizer.encode(everything[where], disallowed_special=())
-        clipped_encoded = encoded[: len(encoded) - delta]
-        everything[where] = tokenizer.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))
-
-    history = everything[1:]
-    return history
 
 
 """