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version3.4
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version3.4
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5c0d34793e |
@@ -1,6 +1,8 @@
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> **Note**
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>
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> 2023.7.5: 对Gradio依赖进行了调整。请及时**更新代码**。安装依赖时,请严格选择`requirements.txt`中**指定的版本**:
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> 2023.7.5: Gradio依赖调整。请及时**更新代码**
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>
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> 2023.7.8: pydantic出现兼容问题,已修改 `requirements.txt`。安装依赖时,请严格选择`requirements.txt`中**指定的版本**
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>
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> `pip install -r requirements.txt`
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@@ -8,7 +8,7 @@
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"""
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# [step 1]>> 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
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API_KEY = "sk-此处填API密钥" # 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-api2dkey1,fkxxxx-api2dkey2"
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API_KEY = "此处填API密钥" # 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"
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# [step 2]>> 改为True应用代理,如果直接在海外服务器部署,此处不修改
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@@ -110,9 +110,8 @@ SLACK_CLAUDE_USER_TOKEN = ''
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# 如果需要使用AZURE 详情请见额外文档 docs\use_azure.md
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AZURE_ENDPOINT = "https://你亲手写的api名称.openai.azure.com/"
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AZURE_API_KEY = "填入azure openai api的密钥"
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AZURE_API_VERSION = "2023-05-15" # 一般不修改
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AZURE_ENGINE = "填入你亲手写的部署名" # 读 docs\use_azure.md
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AZURE_API_KEY = "填入azure openai api的密钥" # 建议直接在API_KEY处填写,该选项即将被弃用
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AZURE_ENGINE = "填入你亲手写的部署名" # 读 docs\use_azure.md
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# 使用Newbing
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@@ -352,6 +352,18 @@ def get_crazy_functions():
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})
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except:
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print('Load function plugin failed')
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try:
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from crazy_functions.交互功能函数模板 import 交互功能模板函数
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function_plugins.update({
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"交互功能模板函数": {
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"Color": "stop",
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"AsButton": False,
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"Function": HotReload(交互功能模板函数)
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}
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})
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except:
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print('Load function plugin failed')
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try:
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from crazy_functions.Latex输出PDF结果 import Latex英文纠错加PDF对比
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@@ -189,6 +189,18 @@ def rm_comments(main_file):
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main_file = re.sub(r'(?<!\\)%.*', '', main_file) # 使用正则表达式查找半行注释, 并替换为空字符串
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return main_file
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def find_tex_file_ignore_case(fp):
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dir_name = os.path.dirname(fp)
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base_name = os.path.basename(fp)
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if not base_name.endswith('.tex'): base_name+='.tex'
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if os.path.exists(pj(dir_name, base_name)): return pj(dir_name, base_name)
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# go case in-sensitive
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import glob
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for f in glob.glob(dir_name+'/*.tex'):
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base_name_s = os.path.basename(fp)
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if base_name_s.lower() == base_name.lower(): return f
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return None
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def merge_tex_files_(project_foler, main_file, mode):
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"""
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Merge Tex project recrusively
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@@ -197,15 +209,11 @@ def merge_tex_files_(project_foler, main_file, mode):
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for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
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f = s.group(1)
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fp = os.path.join(project_foler, f)
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if os.path.exists(fp):
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# e.g., \input{srcs/07_appendix.tex}
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with open(fp, 'r', encoding='utf-8', errors='replace') as fx:
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c = fx.read()
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else:
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# e.g., \input{srcs/07_appendix}
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assert os.path.exists(fp+'.tex'), f'即找不到{fp},也找不到{fp}.tex,Tex源文件缺失!'
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with open(fp+'.tex', 'r', encoding='utf-8', errors='replace') as fx:
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c = fx.read()
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fp = find_tex_file_ignore_case(fp)
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if fp:
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with open(fp, 'r', encoding='utf-8', errors='replace') as fx: c = fx.read()
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else:
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raise RuntimeError(f'找不到{fp},Tex源文件缺失!')
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c = merge_tex_files_(project_foler, c, mode)
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main_file = main_file[:s.span()[0]] + c + main_file[s.span()[1]:]
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return main_file
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@@ -324,7 +332,7 @@ def split_subprocess(txt, project_folder, return_dict, opts):
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# 吸收在42行以内的begin-end组合
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text, mask = set_forbidden_text_begin_end(text, mask, r"\\begin\{([a-z\*]*)\}(.*?)\\end\{\1\}", re.DOTALL, limit_n_lines=42)
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# 吸收匿名公式
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text, mask = set_forbidden_text(text, mask, [ r"\$\$(.*?)\$\$", r"\\\[.*?\\\]" ], re.DOTALL)
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text, mask = set_forbidden_text(text, mask, [ r"\$\$([^$]+)\$\$", r"\\\[.*?\\\]" ], re.DOTALL)
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# 吸收其他杂项
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text, mask = set_forbidden_text(text, mask, [ r"\\section\{(.*?)\}", r"\\section\*\{(.*?)\}", r"\\subsection\{(.*?)\}", r"\\subsubsection\{(.*?)\}" ])
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text, mask = set_forbidden_text(text, mask, [ r"\\bibliography\{(.*?)\}", r"\\bibliographystyle\{(.*?)\}" ])
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63
crazy_functions/交互功能函数模板.py
Normal file
63
crazy_functions/交互功能函数模板.py
Normal file
@@ -0,0 +1,63 @@
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from toolbox import CatchException, update_ui
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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@CatchException
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def 交互功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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"""
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txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
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llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
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plugin_kwargs 插件模型的参数, 如温度和top_p等, 一般原样传递下去就行
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chatbot 聊天显示框的句柄,用于显示给用户
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history 聊天历史,前情提要
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system_prompt 给gpt的静默提醒
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web_port 当前软件运行的端口号
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"""
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history = [] # 清空历史,以免输入溢出
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chatbot.append(("这是什么功能?", "交互功能函数模板。在执行完成之后, 可以将自身的状态存储到cookie中, 等待用户的再次调用。"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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state = chatbot._cookies.get('plugin_state_0001', None) # 初始化插件状态
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if state is None:
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chatbot._cookies['lock_plugin'] = 'crazy_functions.交互功能函数模板->交互功能模板函数' # 赋予插件锁定 锁定插件回调路径,当下一次用户提交时,会直接转到该函数
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chatbot._cookies['plugin_state_0001'] = 'wait_user_keyword' # 赋予插件状态
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chatbot.append(("第一次调用:", "请输入关键词, 我将为您查找相关壁纸, 建议使用英文单词, 插件锁定中,请直接提交即可。"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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if state == 'wait_user_keyword':
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chatbot._cookies['lock_plugin'] = None # 解除插件锁定,避免遗忘导致死锁
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chatbot._cookies['plugin_state_0001'] = None # 解除插件状态,避免遗忘导致死锁
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# 解除插件锁定
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chatbot.append((f"获取关键词:{txt}", ""))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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page_return = get_image_page_by_keyword(txt)
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inputs=inputs_show_user=f"Extract all image urls in this html page, pick the first 5 images and show them with markdown format: \n\n {page_return}"
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=inputs, inputs_show_user=inputs_show_user,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt="When you want to show an image, use markdown format. e.g. . If there are no image url provided, answer 'no image url provided'"
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)
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chatbot[-1] = [chatbot[-1][0], gpt_say]
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# ---------------------------------------------------------------------------------
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def get_image_page_by_keyword(keyword):
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import requests
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from bs4 import BeautifulSoup
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response = requests.get(f'https://wallhaven.cc/search?q={keyword}', timeout=2)
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res = "image urls: \n"
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for image_element in BeautifulSoup(response.content, 'html.parser').findAll("img"):
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try:
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res += image_element["data-src"]
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res += "\n"
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except:
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pass
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return res
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@@ -14,17 +14,19 @@ def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot
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doc = Document(fp)
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file_content = "\n".join([para.text for para in doc.paragraphs])
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else:
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import win32com.client
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word = win32com.client.Dispatch("Word.Application")
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word.visible = False
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# 打开文件
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print('fp', os.getcwd())
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doc = word.Documents.Open(os.getcwd() + '/' + fp)
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# file_content = doc.Content.Text
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doc = word.ActiveDocument
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file_content = doc.Range().Text
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doc.Close()
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word.Quit()
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try:
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import win32com.client
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word = win32com.client.Dispatch("Word.Application")
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word.visible = False
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# 打开文件
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doc = word.Documents.Open(os.getcwd() + '/' + fp)
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# file_content = doc.Content.Text
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doc = word.ActiveDocument
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file_content = doc.Range().Text
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doc.Close()
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word.Quit()
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except:
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raise RuntimeError('请先将.doc文档转换为.docx文档。')
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print(file_content)
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# private_upload里面的文件名在解压zip后容易出现乱码(rar和7z格式正常),故可以只分析文章内容,不输入文件名
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@@ -100,10 +100,12 @@
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# 修改 config.py
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```
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AZURE_ENDPOINT = "填入终结点"
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LLM_MODEL = "azure-gpt-3.5" # 指定启动时的默认模型,当然事后从下拉菜单选也ok
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AZURE_ENDPOINT = "填入终结点" # 见上述图片
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AZURE_API_KEY = "填入azure openai api的密钥"
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AZURE_API_VERSION = "2023-05-15" # 默认使用 2023-05-15 版本,无需修改
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AZURE_ENGINE = "填入部署名" # 见上图
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AZURE_ENGINE = "填入部署名" # 见上述图片
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```
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39
main.py
39
main.py
@@ -4,10 +4,10 @@ def main():
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import gradio as gr
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if gr.__version__ not in ['3.28.3','3.32.2']: assert False, "需要特殊依赖,请务必用 pip install -r requirements.txt 指令安装依赖,详情信息见requirements.txt"
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from request_llm.bridge_all import predict
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from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
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from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, load_chat_cookies, DummyWith
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# 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
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proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = \
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get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
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proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = \
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get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
|
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|
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# 如果WEB_PORT是-1, 则随机选取WEB端口
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PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
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@@ -45,23 +45,23 @@ def main():
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proxy_info = check_proxy(proxies)
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|
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gr_L1 = lambda: gr.Row().style()
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gr_L2 = lambda scale: gr.Column(scale=scale)
|
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gr_L2 = lambda scale, elem_id: gr.Column(scale=scale, elem_id=elem_id)
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if LAYOUT == "TOP-DOWN":
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gr_L1 = lambda: DummyWith()
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gr_L2 = lambda scale: gr.Row()
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gr_L2 = lambda scale, elem_id: gr.Row()
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CHATBOT_HEIGHT /= 2
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cancel_handles = []
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with gr.Blocks(title="ChatGPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
|
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gr.HTML(title_html)
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cookies = gr.State({'api_key': API_KEY, 'llm_model': LLM_MODEL})
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cookies = gr.State(load_chat_cookies())
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with gr_L1():
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with gr_L2(scale=2):
|
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chatbot = gr.Chatbot(label=f"当前模型:{LLM_MODEL}")
|
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chatbot.style(height=CHATBOT_HEIGHT)
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with gr_L2(scale=2, elem_id="gpt-chat"):
|
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chatbot = gr.Chatbot(label=f"当前模型:{LLM_MODEL}", elem_id="gpt-chatbot")
|
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if LAYOUT == "TOP-DOWN": chatbot.style(height=CHATBOT_HEIGHT)
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history = gr.State([])
|
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with gr_L2(scale=1):
|
||||
with gr.Accordion("输入区", open=True) as area_input_primary:
|
||||
with gr_L2(scale=1, elem_id="gpt-panel"):
|
||||
with gr.Accordion("输入区", open=True, elem_id="input-panel") as area_input_primary:
|
||||
with gr.Row():
|
||||
txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
|
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with gr.Row():
|
||||
@@ -71,14 +71,14 @@ def main():
|
||||
stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
|
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clearBtn = gr.Button("清除", variant="secondary", visible=False); clearBtn.style(size="sm")
|
||||
with gr.Row():
|
||||
status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}")
|
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with gr.Accordion("基础功能区", open=True) as area_basic_fn:
|
||||
status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}", elem_id="state-panel")
|
||||
with gr.Accordion("基础功能区", open=True, elem_id="basic-panel") as area_basic_fn:
|
||||
with gr.Row():
|
||||
for k in functional:
|
||||
if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
|
||||
variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
|
||||
functional[k]["Button"] = gr.Button(k, variant=variant)
|
||||
with gr.Accordion("函数插件区", open=True) as area_crazy_fn:
|
||||
with gr.Accordion("函数插件区", open=True, elem_id="plugin-panel") as area_crazy_fn:
|
||||
with gr.Row():
|
||||
gr.Markdown("注意:以下“红颜色”标识的函数插件需从输入区读取路径作为参数.")
|
||||
with gr.Row():
|
||||
@@ -100,7 +100,7 @@ def main():
|
||||
with gr.Row():
|
||||
with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
|
||||
file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
|
||||
with gr.Accordion("更换模型 & SysPrompt & 交互界面布局", open=(LAYOUT == "TOP-DOWN")):
|
||||
with gr.Accordion("更换模型 & SysPrompt & 交互界面布局", open=(LAYOUT == "TOP-DOWN"), elem_id="interact-panel"):
|
||||
system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
|
||||
top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
|
||||
temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
|
||||
@@ -109,7 +109,7 @@ def main():
|
||||
md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
|
||||
|
||||
gr.Markdown(description)
|
||||
with gr.Accordion("备选输入区", open=True, visible=False) as area_input_secondary:
|
||||
with gr.Accordion("备选输入区", open=True, visible=False, elem_id="input-panel2") as area_input_secondary:
|
||||
with gr.Row():
|
||||
txt2 = gr.Textbox(show_label=False, placeholder="Input question here.", label="输入区2").style(container=False)
|
||||
with gr.Row():
|
||||
@@ -176,16 +176,17 @@ def main():
|
||||
return {chatbot: gr.update(label="当前模型:"+k)}
|
||||
md_dropdown.select(on_md_dropdown_changed, [md_dropdown], [chatbot] )
|
||||
# 随变按钮的回调函数注册
|
||||
def route(k, *args, **kwargs):
|
||||
def route(request: gr.Request, k, *args, **kwargs):
|
||||
if k in [r"打开插件列表", r"请先从插件列表中选择"]: return
|
||||
yield from ArgsGeneralWrapper(crazy_fns[k]["Function"])(*args, **kwargs)
|
||||
yield from ArgsGeneralWrapper(crazy_fns[k]["Function"])(request, *args, **kwargs)
|
||||
click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
|
||||
click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot])
|
||||
cancel_handles.append(click_handle)
|
||||
# 终止按钮的回调函数注册
|
||||
stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
|
||||
stopBtn2.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
|
||||
|
||||
demo.load(lambda: 0, inputs=None, outputs=None, _js='()=>{ChatBotHeight();}')
|
||||
|
||||
# gradio的inbrowser触发不太稳定,回滚代码到原始的浏览器打开函数
|
||||
def auto_opentab_delay():
|
||||
import threading, webbrowser, time
|
||||
|
||||
@@ -16,9 +16,6 @@ from toolbox import get_conf, trimmed_format_exc
|
||||
from .bridge_chatgpt import predict_no_ui_long_connection as chatgpt_noui
|
||||
from .bridge_chatgpt import predict as chatgpt_ui
|
||||
|
||||
from .bridge_azure_test import predict_no_ui_long_connection as azure_noui
|
||||
from .bridge_azure_test import predict as azure_ui
|
||||
|
||||
from .bridge_chatglm import predict_no_ui_long_connection as chatglm_noui
|
||||
from .bridge_chatglm import predict as chatglm_ui
|
||||
|
||||
@@ -48,10 +45,11 @@ class LazyloadTiktoken(object):
|
||||
return encoder.decode(*args, **kwargs)
|
||||
|
||||
# Endpoint 重定向
|
||||
API_URL_REDIRECT, = get_conf("API_URL_REDIRECT")
|
||||
API_URL_REDIRECT, AZURE_ENDPOINT, AZURE_ENGINE = get_conf("API_URL_REDIRECT", "AZURE_ENDPOINT", "AZURE_ENGINE")
|
||||
openai_endpoint = "https://api.openai.com/v1/chat/completions"
|
||||
api2d_endpoint = "https://openai.api2d.net/v1/chat/completions"
|
||||
newbing_endpoint = "wss://sydney.bing.com/sydney/ChatHub"
|
||||
azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
|
||||
# 兼容旧版的配置
|
||||
try:
|
||||
API_URL, = get_conf("API_URL")
|
||||
@@ -122,9 +120,9 @@ model_info = {
|
||||
|
||||
# azure openai
|
||||
"azure-gpt-3.5":{
|
||||
"fn_with_ui": azure_ui,
|
||||
"fn_without_ui": azure_noui,
|
||||
"endpoint": get_conf("AZURE_ENDPOINT"),
|
||||
"fn_with_ui": chatgpt_ui,
|
||||
"fn_without_ui": chatgpt_noui,
|
||||
"endpoint": azure_endpoint,
|
||||
"max_token": 4096,
|
||||
"tokenizer": tokenizer_gpt35,
|
||||
"token_cnt": get_token_num_gpt35,
|
||||
|
||||
@@ -1,237 +0,0 @@
|
||||
"""
|
||||
该文件中主要包含三个函数
|
||||
|
||||
不具备多线程能力的函数:
|
||||
1. predict: 正常对话时使用,具备完备的交互功能,不可多线程
|
||||
|
||||
具备多线程调用能力的函数
|
||||
2. predict_no_ui:高级实验性功能模块调用,不会实时显示在界面上,参数简单,可以多线程并行,方便实现复杂的功能逻辑
|
||||
3. predict_no_ui_long_connection:在实验过程中发现调用predict_no_ui处理长文档时,和openai的连接容易断掉,这个函数用stream的方式解决这个问题,同样支持多线程
|
||||
"""
|
||||
|
||||
import logging
|
||||
import traceback
|
||||
import importlib
|
||||
import openai
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
|
||||
# 读取config.py文件中关于AZURE OPENAI API的信息
|
||||
from toolbox import get_conf, update_ui, clip_history, trimmed_format_exc
|
||||
TIMEOUT_SECONDS, MAX_RETRY, AZURE_ENGINE, AZURE_ENDPOINT, AZURE_API_VERSION, AZURE_API_KEY = \
|
||||
get_conf('TIMEOUT_SECONDS', 'MAX_RETRY',"AZURE_ENGINE","AZURE_ENDPOINT", "AZURE_API_VERSION", "AZURE_API_KEY")
|
||||
|
||||
|
||||
def get_full_error(chunk, stream_response):
|
||||
"""
|
||||
获取完整的从Openai返回的报错
|
||||
"""
|
||||
while True:
|
||||
try:
|
||||
chunk += next(stream_response)
|
||||
except:
|
||||
break
|
||||
return chunk
|
||||
|
||||
def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
|
||||
"""
|
||||
发送至azure openai api,流式获取输出。
|
||||
用于基础的对话功能。
|
||||
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
|
||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||
"""
|
||||
|
||||
if additional_fn is not None:
|
||||
import core_functional
|
||||
importlib.reload(core_functional) # 热更新prompt
|
||||
core_functional = core_functional.get_core_functions()
|
||||
if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数(如果有的话)
|
||||
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
|
||||
|
||||
raw_input = inputs
|
||||
logging.info(f'[raw_input] {raw_input}')
|
||||
chatbot.append((inputs, ""))
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
|
||||
|
||||
payload = generate_azure_payload(inputs, llm_kwargs, history, system_prompt, stream)
|
||||
|
||||
history.append(inputs); history.append("")
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
try:
|
||||
openai.api_type = "azure"
|
||||
openai.api_version = AZURE_API_VERSION
|
||||
openai.api_base = AZURE_ENDPOINT
|
||||
openai.api_key = AZURE_API_KEY
|
||||
response = openai.ChatCompletion.create(timeout=TIMEOUT_SECONDS, **payload);break
|
||||
except openai.error.AuthenticationError:
|
||||
tb_str = '```\n' + trimmed_format_exc() + '```'
|
||||
chatbot[-1] = [chatbot[-1][0], tb_str]
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="openai返回错误") # 刷新界面
|
||||
return
|
||||
except:
|
||||
retry += 1
|
||||
traceback.print_exc()
|
||||
if retry > MAX_RETRY: raise TimeoutError
|
||||
if MAX_RETRY!=0: print(f'请求超时,正在重试 ({retry}/{MAX_RETRY}) ……')
|
||||
|
||||
gpt_replying_buffer = ""
|
||||
is_head_of_the_stream = True
|
||||
if stream:
|
||||
|
||||
stream_response = response
|
||||
|
||||
while True:
|
||||
try:
|
||||
chunk = next(stream_response)
|
||||
|
||||
except StopIteration:
|
||||
from toolbox import regular_txt_to_markdown; tb_str = '```\n' + trimmed_format_exc() + '```'
|
||||
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 远程返回错误: \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk)}")
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="远程返回错误:" + chunk) # 刷新界面
|
||||
return
|
||||
|
||||
if is_head_of_the_stream and (r'"object":"error"' not in chunk):
|
||||
# 数据流的第一帧不携带content
|
||||
is_head_of_the_stream = False; continue
|
||||
|
||||
if chunk:
|
||||
#print(chunk)
|
||||
try:
|
||||
if "delta" in chunk["choices"][0]:
|
||||
if chunk["choices"][0]["finish_reason"] == "stop":
|
||||
logging.info(f'[response] {gpt_replying_buffer}')
|
||||
break
|
||||
status_text = f"finish_reason: {chunk['choices'][0]['finish_reason']}"
|
||||
gpt_replying_buffer = gpt_replying_buffer + chunk["choices"][0]["delta"]["content"]
|
||||
|
||||
history[-1] = gpt_replying_buffer
|
||||
chatbot[-1] = (history[-2], history[-1])
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
|
||||
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面
|
||||
chunk = get_full_error(chunk, stream_response)
|
||||
|
||||
error_msg = chunk
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
|
||||
return
|
||||
|
||||
|
||||
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
|
||||
"""
|
||||
发送至AZURE OPENAI API,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:
|
||||
是本次问询的输入
|
||||
sys_prompt:
|
||||
系统静默prompt
|
||||
llm_kwargs:
|
||||
chatGPT的内部调优参数
|
||||
history:
|
||||
是之前的对话列表
|
||||
observe_window = None:
|
||||
用于负责跨越线程传递已经输出的部分,大部分时候仅仅为了fancy的视觉效果,留空即可。observe_window[0]:观测窗。observe_window[1]:看门狗
|
||||
"""
|
||||
watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可
|
||||
payload = generate_azure_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True)
|
||||
retry = 0
|
||||
while True:
|
||||
try:
|
||||
openai.api_type = "azure"
|
||||
openai.api_version = AZURE_API_VERSION
|
||||
openai.api_base = AZURE_ENDPOINT
|
||||
openai.api_key = AZURE_API_KEY
|
||||
response = openai.ChatCompletion.create(timeout=TIMEOUT_SECONDS, **payload);break
|
||||
except:
|
||||
retry += 1
|
||||
traceback.print_exc()
|
||||
if retry > MAX_RETRY: raise TimeoutError
|
||||
if MAX_RETRY!=0: print(f'请求超时,正在重试 ({retry}/{MAX_RETRY}) ……')
|
||||
|
||||
stream_response = response
|
||||
result = ''
|
||||
while True:
|
||||
try: chunk = next(stream_response)
|
||||
except StopIteration:
|
||||
break
|
||||
except:
|
||||
chunk = next(stream_response) # 失败了,重试一次?再失败就没办法了。
|
||||
if len(chunk)==0: continue
|
||||
|
||||
json_data = json.loads(str(chunk))['choices'][0]
|
||||
delta = json_data["delta"]
|
||||
if len(delta) == 0:
|
||||
break
|
||||
if "role" in delta:
|
||||
continue
|
||||
if "content" in delta:
|
||||
result += delta["content"]
|
||||
if not console_slience: print(delta["content"], end='')
|
||||
if observe_window is not None:
|
||||
# 观测窗,把已经获取的数据显示出去
|
||||
if len(observe_window) >= 1: observe_window[0] += delta["content"]
|
||||
# 看门狗,如果超过期限没有喂狗,则终止
|
||||
if len(observe_window) >= 2000:
|
||||
if (time.time()-observe_window[1]) > watch_dog_patience:
|
||||
raise RuntimeError("用户取消了程序。")
|
||||
else:
|
||||
raise RuntimeError("意外Json结构:"+delta)
|
||||
if json_data['finish_reason'] == 'content_filter':
|
||||
raise RuntimeError("由于提问含不合规内容被Azure过滤。")
|
||||
if json_data['finish_reason'] == 'length':
|
||||
raise ConnectionAbortedError("正常结束,但显示Token不足,导致输出不完整,请削减单次输入的文本量。")
|
||||
return result
|
||||
|
||||
|
||||
def generate_azure_payload(inputs, llm_kwargs, history, system_prompt, stream):
|
||||
"""
|
||||
整合所有信息,选择LLM模型,生成 azure openai api请求,为发送请求做准备
|
||||
"""
|
||||
|
||||
conversation_cnt = len(history) // 2
|
||||
|
||||
messages = [{"role": "system", "content": system_prompt}]
|
||||
if conversation_cnt:
|
||||
for index in range(0, 2*conversation_cnt, 2):
|
||||
what_i_have_asked = {}
|
||||
what_i_have_asked["role"] = "user"
|
||||
what_i_have_asked["content"] = history[index]
|
||||
what_gpt_answer = {}
|
||||
what_gpt_answer["role"] = "assistant"
|
||||
what_gpt_answer["content"] = history[index+1]
|
||||
if what_i_have_asked["content"] != "":
|
||||
if what_gpt_answer["content"] == "": continue
|
||||
messages.append(what_i_have_asked)
|
||||
messages.append(what_gpt_answer)
|
||||
else:
|
||||
messages[-1]['content'] = what_gpt_answer['content']
|
||||
|
||||
what_i_ask_now = {}
|
||||
what_i_ask_now["role"] = "user"
|
||||
what_i_ask_now["content"] = inputs
|
||||
messages.append(what_i_ask_now)
|
||||
|
||||
payload = {
|
||||
"model": llm_kwargs['llm_model'],
|
||||
"messages": messages,
|
||||
"temperature": llm_kwargs['temperature'], # 1.0,
|
||||
"top_p": llm_kwargs['top_p'], # 1.0,
|
||||
"n": 1,
|
||||
"stream": stream,
|
||||
"presence_penalty": 0,
|
||||
"frequency_penalty": 0,
|
||||
"engine": AZURE_ENGINE
|
||||
}
|
||||
try:
|
||||
print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........")
|
||||
except:
|
||||
print('输入中可能存在乱码。')
|
||||
return payload
|
||||
|
||||
|
||||
@@ -22,8 +22,8 @@ import importlib
|
||||
# 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_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc
|
||||
proxies, API_KEY, TIMEOUT_SECONDS, MAX_RETRY, API_ORG = \
|
||||
get_conf('proxies', 'API_KEY', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG')
|
||||
proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG = \
|
||||
get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG')
|
||||
|
||||
timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
|
||||
'网络错误,检查代理服务器是否可用,以及代理设置的格式是否正确,格式须是[协议]://[地址]:[端口],缺一不可。'
|
||||
@@ -101,6 +101,8 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
|
||||
if (time.time()-observe_window[1]) > watch_dog_patience:
|
||||
raise RuntimeError("用户取消了程序。")
|
||||
else: raise RuntimeError("意外Json结构:"+delta)
|
||||
if json_data['finish_reason'] == 'content_filter':
|
||||
raise RuntimeError("由于提问含不合规内容被Azure过滤。")
|
||||
if json_data['finish_reason'] == 'length':
|
||||
raise ConnectionAbortedError("正常结束,但显示Token不足,导致输出不完整,请削减单次输入的文本量。")
|
||||
return result
|
||||
@@ -247,6 +249,7 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
|
||||
"Authorization": f"Bearer {api_key}"
|
||||
}
|
||||
if API_ORG.startswith('org-'): headers.update({"OpenAI-Organization": API_ORG})
|
||||
if llm_kwargs['llm_model'].startswith('azure-'): headers.update({"api-key": api_key})
|
||||
|
||||
conversation_cnt = len(history) // 2
|
||||
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
./docs/gradio-3.32.2-py3-none-any.whl
|
||||
pydantic==1.10.11
|
||||
tiktoken>=0.3.3
|
||||
requests[socks]
|
||||
transformers
|
||||
@@ -15,4 +16,4 @@ pymupdf
|
||||
openai
|
||||
numpy
|
||||
arxiv
|
||||
rich
|
||||
rich
|
||||
|
||||
74
theme.py
74
theme.py
@@ -1,6 +1,6 @@
|
||||
import gradio as gr
|
||||
from toolbox import get_conf
|
||||
CODE_HIGHLIGHT, ADD_WAIFU = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU')
|
||||
CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAYOUT')
|
||||
# gradio可用颜色列表
|
||||
# gr.themes.utils.colors.slate (石板色)
|
||||
# gr.themes.utils.colors.gray (灰色)
|
||||
@@ -82,20 +82,76 @@ def adjust_theme():
|
||||
button_cancel_text_color_dark="white",
|
||||
)
|
||||
|
||||
# Layout = "LEFT-RIGHT"
|
||||
js = """
|
||||
<script>
|
||||
function ChatBotHeight() {
|
||||
function update_height(){
|
||||
var { panel_height_target, chatbot_height, chatbot } = get_elements();
|
||||
if (panel_height_target!=chatbot_height)
|
||||
{
|
||||
var pixelString = panel_height_target.toString() + 'px';
|
||||
chatbot.style.maxHeight = pixelString; chatbot.style.height = pixelString;
|
||||
}
|
||||
}
|
||||
|
||||
function update_height_slow(){
|
||||
var { panel_height_target, chatbot_height, chatbot } = get_elements();
|
||||
if (panel_height_target!=chatbot_height)
|
||||
{
|
||||
new_panel_height = (panel_height_target - chatbot_height)*0.5 + chatbot_height;
|
||||
if (Math.abs(new_panel_height - panel_height_target) < 10){
|
||||
new_panel_height = panel_height_target;
|
||||
}
|
||||
// console.log(chatbot_height, panel_height_target, new_panel_height);
|
||||
var pixelString = new_panel_height.toString() + 'px';
|
||||
chatbot.style.maxHeight = pixelString; chatbot.style.height = pixelString;
|
||||
}
|
||||
}
|
||||
|
||||
update_height();
|
||||
setInterval(function() {
|
||||
update_height_slow()
|
||||
}, 50); // 每100毫秒执行一次
|
||||
}
|
||||
|
||||
function get_elements() {
|
||||
var chatbot = document.querySelector('#gpt-chatbot > div.wrap.svelte-18telvq');
|
||||
if (!chatbot) {
|
||||
chatbot = document.querySelector('#gpt-chatbot');
|
||||
}
|
||||
const panel1 = document.querySelector('#input-panel');
|
||||
const panel2 = document.querySelector('#basic-panel');
|
||||
const panel3 = document.querySelector('#plugin-panel');
|
||||
const panel4 = document.querySelector('#interact-panel');
|
||||
const panel5 = document.querySelector('#input-panel2');
|
||||
const panel_active = document.querySelector('#state-panel');
|
||||
var panel_height_target = (20-panel_active.offsetHeight) + panel1.offsetHeight + panel2.offsetHeight + panel3.offsetHeight + panel4.offsetHeight + panel5.offsetHeight + 21;
|
||||
var panel_height_target = parseInt(panel_height_target);
|
||||
var chatbot_height = chatbot.style.height;
|
||||
var chatbot_height = parseInt(chatbot_height);
|
||||
return { panel_height_target, chatbot_height, chatbot };
|
||||
}
|
||||
</script>
|
||||
"""
|
||||
|
||||
if LAYOUT=="TOP-DOWN":
|
||||
js = ""
|
||||
|
||||
# 添加一个萌萌的看板娘
|
||||
if ADD_WAIFU:
|
||||
js = """
|
||||
js += """
|
||||
<script src="file=docs/waifu_plugin/jquery.min.js"></script>
|
||||
<script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
|
||||
<script src="file=docs/waifu_plugin/autoload.js"></script>
|
||||
"""
|
||||
gradio_original_template_fn = gr.routes.templates.TemplateResponse
|
||||
def gradio_new_template_fn(*args, **kwargs):
|
||||
res = gradio_original_template_fn(*args, **kwargs)
|
||||
res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
|
||||
res.init_headers()
|
||||
return res
|
||||
gr.routes.templates.TemplateResponse = gradio_new_template_fn # override gradio template
|
||||
gradio_original_template_fn = gr.routes.templates.TemplateResponse
|
||||
def gradio_new_template_fn(*args, **kwargs):
|
||||
res = gradio_original_template_fn(*args, **kwargs)
|
||||
res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
|
||||
res.init_headers()
|
||||
return res
|
||||
gr.routes.templates.TemplateResponse = gradio_new_template_fn # override gradio template
|
||||
except:
|
||||
set_theme = None
|
||||
print('gradio版本较旧, 不能自定义字体和颜色')
|
||||
|
||||
64
toolbox.py
64
toolbox.py
@@ -4,6 +4,7 @@ import time
|
||||
import inspect
|
||||
import re
|
||||
import os
|
||||
import gradio
|
||||
from latex2mathml.converter import convert as tex2mathml
|
||||
from functools import wraps, lru_cache
|
||||
pj = os.path.join
|
||||
@@ -40,7 +41,7 @@ def ArgsGeneralWrapper(f):
|
||||
"""
|
||||
装饰器函数,用于重组输入参数,改变输入参数的顺序与结构。
|
||||
"""
|
||||
def decorated(cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg, *args):
|
||||
def decorated(request: gradio.Request, cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg, *args):
|
||||
txt_passon = txt
|
||||
if txt == "" and txt2 != "": txt_passon = txt2
|
||||
# 引入一个有cookie的chatbot
|
||||
@@ -54,13 +55,21 @@ def ArgsGeneralWrapper(f):
|
||||
'top_p':top_p,
|
||||
'max_length': max_length,
|
||||
'temperature':temperature,
|
||||
'client_ip': request.client.host,
|
||||
}
|
||||
plugin_kwargs = {
|
||||
"advanced_arg": plugin_advanced_arg,
|
||||
}
|
||||
chatbot_with_cookie = ChatBotWithCookies(cookies)
|
||||
chatbot_with_cookie.write_list(chatbot)
|
||||
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
if cookies.get('lock_plugin', None) is None:
|
||||
# 正常状态
|
||||
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
else:
|
||||
# 处理个别特殊插件的锁定状态
|
||||
module, fn_name = cookies['lock_plugin'].split('->')
|
||||
f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name)
|
||||
yield from f_hot_reload(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
return decorated
|
||||
|
||||
|
||||
@@ -68,8 +77,21 @@ def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
|
||||
"""
|
||||
刷新用户界面
|
||||
"""
|
||||
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时,可用clear将其清空,然后用for+append循环重新赋值。"
|
||||
yield chatbot.get_cookies(), chatbot, history, msg
|
||||
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时, 可用clear将其清空, 然后用for+append循环重新赋值。"
|
||||
cookies = chatbot.get_cookies()
|
||||
|
||||
# 解决插件锁定时的界面显示问题
|
||||
if cookies.get('lock_plugin', None):
|
||||
label = cookies.get('llm_model', "") + " | " + "正在锁定插件" + cookies.get('lock_plugin', None)
|
||||
chatbot_gr = gradio.update(value=chatbot, label=label)
|
||||
if cookies.get('label', "") != label: cookies['label'] = label # 记住当前的label
|
||||
elif cookies.get('label', None):
|
||||
chatbot_gr = gradio.update(value=chatbot, label=cookies.get('llm_model', ""))
|
||||
cookies['label'] = None # 清空label
|
||||
else:
|
||||
chatbot_gr = chatbot
|
||||
|
||||
yield cookies, chatbot_gr, history, msg
|
||||
|
||||
def update_ui_lastest_msg(lastmsg, chatbot, history, delay=1): # 刷新界面
|
||||
"""
|
||||
@@ -505,16 +527,24 @@ def on_report_generated(cookies, files, chatbot):
|
||||
chatbot.append(['报告如何远程获取?', f'报告已经添加到右侧“文件上传区”(可能处于折叠状态),请查收。{file_links}'])
|
||||
return cookies, report_files, chatbot
|
||||
|
||||
def load_chat_cookies():
|
||||
API_KEY, LLM_MODEL, AZURE_API_KEY = get_conf('API_KEY', 'LLM_MODEL', 'AZURE_API_KEY')
|
||||
if is_any_api_key(AZURE_API_KEY):
|
||||
if is_any_api_key(API_KEY): API_KEY = API_KEY + ',' + AZURE_API_KEY
|
||||
else: API_KEY = AZURE_API_KEY
|
||||
return {'api_key': API_KEY, 'llm_model': LLM_MODEL}
|
||||
|
||||
def is_openai_api_key(key):
|
||||
API_MATCH_ORIGINAL = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
|
||||
return bool(API_MATCH_ORIGINAL)
|
||||
|
||||
def is_azure_api_key(key):
|
||||
API_MATCH_AZURE = re.match(r"[a-zA-Z0-9]{32}$", key)
|
||||
return bool(API_MATCH_ORIGINAL) or bool(API_MATCH_AZURE)
|
||||
return bool(API_MATCH_AZURE)
|
||||
|
||||
def is_api2d_key(key):
|
||||
if key.startswith('fk') and len(key) == 41:
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
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_any_api_key(key):
|
||||
if ',' in key:
|
||||
@@ -523,10 +553,10 @@ def is_any_api_key(key):
|
||||
if is_any_api_key(k): return True
|
||||
return False
|
||||
else:
|
||||
return is_openai_api_key(key) or is_api2d_key(key)
|
||||
return is_openai_api_key(key) or is_api2d_key(key) or is_azure_api_key(key)
|
||||
|
||||
def what_keys(keys):
|
||||
avail_key_list = {'OpenAI Key':0, "API2D Key":0}
|
||||
avail_key_list = {'OpenAI Key':0, "Azure Key":0, "API2D Key":0}
|
||||
key_list = keys.split(',')
|
||||
|
||||
for k in key_list:
|
||||
@@ -537,7 +567,11 @@ def what_keys(keys):
|
||||
if is_api2d_key(k):
|
||||
avail_key_list['API2D Key'] += 1
|
||||
|
||||
return f"检测到: OpenAI Key {avail_key_list['OpenAI Key']} 个,API2D Key {avail_key_list['API2D Key']} 个"
|
||||
for k in key_list:
|
||||
if is_azure_api_key(k):
|
||||
avail_key_list['Azure Key'] += 1
|
||||
|
||||
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 select_api_key(keys, llm_model):
|
||||
import random
|
||||
@@ -552,8 +586,12 @@ def select_api_key(keys, llm_model):
|
||||
for k in key_list:
|
||||
if is_api2d_key(k): avail_key_list.append(k)
|
||||
|
||||
if llm_model.startswith('azure-'):
|
||||
for k in key_list:
|
||||
if is_azure_api_key(k): avail_key_list.append(k)
|
||||
|
||||
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。")
|
||||
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(右下角更换模型菜单中可切换openai,azure和api2d请求源)")
|
||||
|
||||
api_key = random.choice(avail_key_list) # 随机负载均衡
|
||||
return api_key
|
||||
|
||||
4
version
4
version
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"version": 3.43,
|
||||
"version": 3.44,
|
||||
"show_feature": true,
|
||||
"new_feature": "修复Azure接口的BUG <-> 完善多语言模块 <-> 完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持 <-> 新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件"
|
||||
"new_feature": "改善UI <-> 修复Azure接口的BUG <-> 完善多语言模块 <-> 完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持 <-> 新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件"
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user