适配 google gemini 优化为从用户input中提取文件 (#1419)

适配 google gemini 优化为从用户input中提取文件

config.py

@@ -89,12 +89,14 @@ DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
 LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
 AVAIL_LLM_MODELS = ["gpt-3.5-turbo-1106","gpt-4-1106-preview","gpt-4-vision-preview",
                     "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
-                    "api2d-gpt-3.5-turbo", 'api2d-gpt-3.5-turbo-16k',
                     "gpt-4", "gpt-4-32k", "azure-gpt-4", "api2d-gpt-4",
-                    "chatglm3", "moss", "claude-2"]
+                    "gemini-pro", "chatglm3", "moss", "claude-2"]
-# P.S. 其他可用的模型还包括 ["zhipuai", "qianfan", "deepseekcoder", "llama2", "qwen-local", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613",  "gpt-3.5-random"
+# P.S. 其他可用的模型还包括 [
+# "qwen-turbo", "qwen-plus", "qwen-max"
+# "zhipuai", "qianfan", "deepseekcoder", "llama2", "qwen-local", "gpt-3.5-turbo-0613", 
+# "gpt-3.5-turbo-16k-0613",  "gpt-3.5-random", "api2d-gpt-3.5-turbo", 'api2d-gpt-3.5-turbo-16k',
 # "spark", "sparkv2", "sparkv3", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"
-# “qwen-turbo", "qwen-plus", "qwen-max"]
+# ]
 
 
 # 定义界面上“询问多个GPT模型”插件应该使用哪些模型，请从AVAIL_LLM_MODELS中选择，并在不同模型之间用`&`间隔，例如"gpt-3.5-turbo&chatglm3&azure-gpt-4"
@@ -204,6 +206,10 @@ ANTHROPIC_API_KEY = ""
 CUSTOM_API_KEY_PATTERN = ""
 
 
+# Google Gemini API-Key
+GEMINI_API_KEY = ''
+
+
 # HUGGINGFACE的TOKEN，下载LLAMA时起作用 https://huggingface.co/docs/hub/security-tokens
 HUGGINGFACE_ACCESS_TOKEN = "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"
 
@@ -292,6 +298,9 @@ NUM_CUSTOM_BASIC_BTN = 4
 ├── "qwen-turbo" 等通义千问大模型
 │   └──  DASHSCOPE_API_KEY
 │
+├── "Gemini"
+│   └──  GEMINI_API_KEY
+│
 └── "newbing" Newbing接口不再稳定，不推荐使用
     ├── NEWBING_STYLE
     └── NEWBING_COOKIES

request_llms/bridge_all.py

@@ -28,6 +28,9 @@ from .bridge_chatglm3 import predict as chatglm3_ui
 from .bridge_qianfan import predict_no_ui_long_connection as qianfan_noui
 from .bridge_qianfan import predict as qianfan_ui
 
+from .bridge_google_gemini import predict as genai_ui
+from .bridge_google_gemini import predict_no_ui_long_connection  as genai_noui
+
 colors = ['#FF00FF', '#00FFFF', '#FF0000', '#990099', '#009999', '#990044']
 
 class LazyloadTiktoken(object):
@@ -246,6 +249,22 @@ model_info = {
         "tokenizer": tokenizer_gpt35,
         "token_cnt": get_token_num_gpt35,
     },
+    "gemini-pro": {
+        "fn_with_ui": genai_ui,
+        "fn_without_ui": genai_noui,
+        "endpoint": None,
+        "max_token": 1024 * 32,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
+    "gemini-pro-vision": {
+        "fn_with_ui": genai_ui,
+        "fn_without_ui": genai_noui,
+        "endpoint": None,
+        "max_token": 1024 * 32,
+        "tokenizer": tokenizer_gpt35,
+        "token_cnt": get_token_num_gpt35,
+    },
 }
 
 # -=-=-=-=-=-=- api2d 对齐支持 -=-=-=-=-=-=-

request_llms/bridge_google_gemini.py

@@ -0,0 +1,101 @@
+# encoding: utf-8
+# @Time   : 2023/12/21
+# @Author : Spike
+# @Descr   :
+import json
+import re
+import time
+from request_llms.com_google import GoogleChatInit
+from toolbox import get_conf, update_ui, update_ui_lastest_msg
+
+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.' + \
+                  '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
+
+
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None,
+                                  console_slience=False):
+    # 检查API_KEY
+    if get_conf("GEMINI_API_KEY") == "":
+        raise ValueError(f"请配置 GEMINI_API_KEY。")
+    
+    genai = GoogleChatInit()
+    watch_dog_patience = 5  # 看门狗的耐心, 设置5秒即可
+    gpt_replying_buffer = ''
+    stream_response = genai.generate_chat(inputs, llm_kwargs, history, sys_prompt)
+    for response in stream_response:
+        results = response.decode()
+        match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL)
+        error_match = re.search(r'\"message\":\s*\"(.*?)\"', results, flags=re.DOTALL)
+        if match:
+            try:
+                paraphrase = json.loads('{"text": "%s"}' % match.group(1))
+            except:
+                raise ValueError(f"解析GEMINI消息出错。")
+            buffer = paraphrase['text']
+            gpt_replying_buffer += buffer
+            if len(observe_window) >= 1:
+                observe_window[0] = gpt_replying_buffer
+            if len(observe_window) >= 2:
+                if (time.time() - observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。")
+        if error_match:
+            raise RuntimeError(f'{gpt_replying_buffer} 对话错误')
+    return gpt_replying_buffer
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream=True, additional_fn=None):
+    # 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)
+        return
+    
+    chatbot.append((inputs, ""))
+    yield from update_ui(chatbot=chatbot, history=history)
+    genai = GoogleChatInit()
+    retry = 0
+    while True:
+        try:
+            stream_response = genai.generate_chat(inputs, llm_kwargs, history, system_prompt)
+            break
+        except Exception as e:
+            retry += 1
+            chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
+            retry_msg = f"，正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else ""
+            yield from update_ui(chatbot=chatbot, history=history, msg="请求超时" + retry_msg)  # 刷新界面
+            if retry > MAX_RETRY: raise TimeoutError
+    gpt_replying_buffer = ""
+    gpt_security_policy = ""
+    history.extend([inputs, ''])
+    for response in stream_response:
+        results = response.decode("utf-8")    # 被这个解码给耍了。。
+        gpt_security_policy += results
+        match = re.search(r'"text":\s*"((?:[^"\\]|\\.)*)"', results, flags=re.DOTALL)
+        error_match = re.search(r'\"message\":\s*\"(.*)\"', results, flags=re.DOTALL)
+        if match:
+            try:
+                paraphrase = json.loads('{"text": "%s"}' % match.group(1))
+            except:
+                raise ValueError(f"解析GEMINI消息出错。")
+            gpt_replying_buffer += paraphrase['text']    # 使用 json 解析库进行处理
+            chatbot[-1] = (inputs, gpt_replying_buffer)
+            history[-1] = gpt_replying_buffer
+            yield from update_ui(chatbot=chatbot, history=history)
+        if error_match:
+            history = history[-2]  # 错误的不纳入对话
+            chatbot[-1] = (inputs, gpt_replying_buffer + f"对话错误，请查看message\n\n```\n{error_match.group(1)}\n```")
+            yield from update_ui(chatbot=chatbot, history=history)
+            raise RuntimeError('对话错误')
+    if not gpt_replying_buffer:
+        history = history[-2]  # 错误的不纳入对话
+        chatbot[-1] = (inputs, gpt_replying_buffer + f"触发了Google的安全访问策略，没有回答\n\n```\n{gpt_security_policy}\n```")
+        yield from update_ui(chatbot=chatbot, history=history)
+
+
+
+if __name__ == '__main__':
+    import sys
+
+    llm_kwargs = {'llm_model': 'gemini-pro'}
+    result = predict('Write long a story about a magic backpack.', llm_kwargs, llm_kwargs, [])
+    for i in result:
+        print(i)

request_llms/com_google.py

@@ -0,0 +1,198 @@
+# encoding: utf-8
+# @Time   : 2023/12/25
+# @Author : Spike
+# @Descr   :
+import json
+import os
+import re
+import requests
+from typing import List, Dict, Tuple
+from toolbox import get_conf, encode_image
+
+proxies, TIMEOUT_SECONDS = get_conf('proxies', 'TIMEOUT_SECONDS')
+
+"""
+========================================================================
+第五部分 一些文件处理方法
+files_filter_handler 根据type过滤文件
+input_encode_handler 提取input中的文件，并解析
+file_manifest_filter_html 根据type过滤文件, 并解析为html or md 文本
+link_mtime_to_md 文件增加本地时间参数，避免下载到缓存文件
+html_view_blank 超链接
+html_local_file 本地文件取相对路径
+to_markdown_tabs 文件list 转换为 md tab
+"""
+
+
+def files_filter_handler(file_list):
+    new_list = []
+    filter_ = ['png', 'jpg', 'jpeg', 'bmp', 'svg', 'webp', 'ico', 'tif', 'tiff', 'raw', 'eps']
+    for file in file_list:
+        file = str(file).replace('file=', '')
+        if os.path.exists(file):
+            if str(os.path.basename(file)).split('.')[-1] in filter_:
+                new_list.append(file)
+    return new_list
+
+
+def input_encode_handler(inputs):
+    md_encode = []
+    pattern_md_file = r"(!?\[[^\]]+\]\([^\)]+\))"
+    matches_path = re.findall(pattern_md_file, inputs)
+    for md_path in matches_path:
+        pattern_file = r"\((file=.*)\)"
+        matches_path = re.findall(pattern_file, md_path)
+        encode_file = files_filter_handler(file_list=matches_path)
+        if encode_file:
+            md_encode.extend([{
+                "data": encode_image(i),
+                "type": os.path.splitext(i)[1].replace('.', '')
+            } for i in encode_file])
+            inputs = inputs.replace(md_path, '')
+    return inputs, md_encode
+
+
+def file_manifest_filter_html(file_list, filter_: list = None, md_type=False):
+    new_list = []
+    if not filter_:
+        filter_ = ['png', 'jpg', 'jpeg', 'bmp', 'svg', 'webp', 'ico', 'tif', 'tiff', 'raw', 'eps']
+    for file in file_list:
+        if str(os.path.basename(file)).split('.')[-1] in filter_:
+            new_list.append(html_local_img(file, md=md_type))
+        elif os.path.exists(file):
+            new_list.append(link_mtime_to_md(file))
+        else:
+            new_list.append(file)
+    return new_list
+
+
+def link_mtime_to_md(file):
+    link_local = html_local_file(file)
+    link_name = os.path.basename(file)
+    a = f"[{link_name}]({link_local}?{os.path.getmtime(file)})"
+    return a
+
+
+def html_local_file(file):
+    base_path = os.path.dirname(__file__)  # 项目目录
+    if os.path.exists(str(file)):
+        file = f'file={file.replace(base_path, ".")}'
+    return file
+
+
+def html_local_img(__file, layout='left', max_width=None, max_height=None, md=True):
+    style = ''
+    if max_width is not None:
+        style += f"max-width: {max_width};"
+    if max_height is not None:
+        style += f"max-height: {max_height};"
+    __file = html_local_file(__file)
+    a = f'<div align="{layout}"><img src="{__file}" style="{style}"></div>'
+    if md:
+        a = f'![{__file}]({__file})'
+    return a
+
+
+def to_markdown_tabs(head: list, tabs: list, alignment=':---:', column=False):
+    """
+    Args:
+        head: 表头：[]
+        tabs: 表值：[[列1], [列2], [列3], [列4]]
+        alignment: :--- 左对齐， :---: 居中对齐， ---: 右对齐
+        column: True to keep data in columns, False to keep data in rows (default).
+    Returns:
+        A string representation of the markdown table.
+    """
+    if column:
+        transposed_tabs = list(map(list, zip(*tabs)))
+    else:
+        transposed_tabs = tabs
+    # Find the maximum length among the columns
+    max_len = max(len(column) for column in transposed_tabs)
+
+    tab_format = "| %s "
+    tabs_list = "".join([tab_format % i for i in head]) + '|\n'
+    tabs_list += "".join([tab_format % alignment for i in head]) + '|\n'
+
+    for i in range(max_len):
+        row_data = [tab[i] if i < len(tab) else '' for tab in transposed_tabs]
+        row_data = file_manifest_filter_html(row_data, filter_=None)
+        tabs_list += "".join([tab_format % i for i in row_data]) + '|\n'
+
+    return tabs_list
+
+
+class GoogleChatInit:
+
+    def __init__(self):
+        self.url_gemini = 'https://generativelanguage.googleapis.com/v1beta/models/%m:streamGenerateContent?key=%k'
+
+    def __conversation_user(self, user_input):
+        what_i_have_asked = {"role": "user", "parts": []}
+        if 'vision' not in self.url_gemini:
+            input_ = user_input
+            encode_img = []
+        else:
+            input_, encode_img = input_encode_handler(user_input)
+        what_i_have_asked['parts'].append({'text': input_})
+        if encode_img:
+            for data in encode_img:
+                what_i_have_asked['parts'].append(
+                    {'inline_data': {
+                        "mime_type": f"image/{data['type']}",
+                        "data": data['data']
+                    }})
+        return what_i_have_asked
+
+    def __conversation_history(self, history):
+        messages = []
+        conversation_cnt = len(history) // 2
+        if conversation_cnt:
+            for index in range(0, 2 * conversation_cnt, 2):
+                what_i_have_asked = self.__conversation_user(history[index])
+                what_gpt_answer = {
+                    "role": "model",
+                    "parts": [{"text": history[index + 1]}]
+                }
+                messages.append(what_i_have_asked)
+                messages.append(what_gpt_answer)
+        return messages
+
+    def generate_chat(self, inputs, llm_kwargs, history, system_prompt):
+        headers, payload = self.generate_message_payload(inputs, llm_kwargs, history, system_prompt)
+        response = requests.post(url=self.url_gemini, headers=headers, data=json.dumps(payload),
+                                 stream=True, proxies=proxies, timeout=TIMEOUT_SECONDS)
+        return response.iter_lines()
+
+    def generate_message_payload(self, inputs, llm_kwargs, history, system_prompt) -> Tuple[Dict, Dict]:
+        messages = [
+            # {"role": "system", "parts": [{"text": system_prompt}]},  # gemini 不允许对话轮次为偶数，所以这个没有用，看后续支持吧。。。
+            # {"role": "user", "parts": [{"text": ""}]},
+            # {"role": "model", "parts": [{"text": ""}]}
+        ]
+        self.url_gemini = self.url_gemini.replace(
+            '%m', llm_kwargs['llm_model']).replace(
+            '%k', get_conf('GEMINI_API_KEY')
+        )
+        header = {'Content-Type': 'application/json'}
+        if 'vision' not in self.url_gemini:  # 不是vision 才处理history
+            messages.extend(self.__conversation_history(history))  # 处理 history
+        messages.append(self.__conversation_user(inputs))  # 处理用户对话
+        payload = {
+            "contents": messages,
+            "generationConfig": {
+                "stopSequences": str(llm_kwargs.get('stop', '')).split(' '),
+                "temperature": llm_kwargs.get('temperature', 1),
+                # "maxOutputTokens": 800,
+                "topP": llm_kwargs.get('top_p', 0.8),
+                "topK": 10
+            }
+        }
+        return header, payload
+
+
+if __name__ == '__main__':
+    google = GoogleChatInit()
+    # print(gootle.generate_message_payload('你好呀', {},
+    #                                                 ['123123', '3123123'], ''))
+    # gootle.input_encode_handle('123123[123123](./123123), ![53425](./asfafa/fff.jpg)')

toolbox.py

@@ -11,8 +11,10 @@ import glob
 import math
 from latex2mathml.converter import convert as tex2mathml
 from functools import wraps, lru_cache
+
 pj = os.path.join
 default_user_name = 'default_user'
+
 """
 ========================================================================
 第一部分
@@ -26,6 +28,7 @@ default_user_name = 'default_user'
 ========================================================================
 """
 
+
 class ChatBotWithCookies(list):
     def __init__(self, cookie):
         """
@@ -67,18 +70,18 @@ def ArgsGeneralWrapper(f):
         else:
             user_name = default_user_name
         cookies.update({
-            'top_p':top_p,
+            'top_p': top_p,
             'api_key': cookies['api_key'],
             'llm_model': llm_model,
-            'temperature':temperature,
+            'temperature': temperature,
             'user_name': user_name,
         })
         llm_kwargs = {
             'api_key': cookies['api_key'],
             'llm_model': llm_model,
-            'top_p':top_p,
+            'top_p': top_p,
             'max_length': max_length,
-            'temperature':temperature,
+            'temperature': temperature,
             'client_ip': request.client.host,
             'most_recent_uploaded': cookies.get('most_recent_uploaded')
         }
@@ -103,8 +106,10 @@ def ArgsGeneralWrapper(f):
             final_cookies = chatbot_with_cookie.get_cookies()
             # len(args) != 0 代表“提交”键对话通道，或者基础功能通道
             if len(args) != 0 and 'files_to_promote' in final_cookies and len(final_cookies['files_to_promote']) > 0:
-                chatbot_with_cookie.append(["检测到**滞留的缓存文档**，请及时处理。", "请及时点击“**保存当前对话**”获取所有滞留文档。"])
+                chatbot_with_cookie.append(
+                    ["检测到**滞留的缓存文档**，请及时处理。", "请及时点击“**保存当前对话**”获取所有滞留文档。"])
                 yield from update_ui(chatbot_with_cookie, final_cookies['history'], msg="检测到被滞留的缓存文档")
+
     return decorated
 
 
@@ -129,6 +134,7 @@ def update_ui(chatbot, history, msg='正常', **kwargs):  # 刷新界面
 
     yield cookies, chatbot_gr, history, msg
 
+
 def update_ui_lastest_msg(lastmsg, chatbot, history, delay=1):  # 刷新界面
     """
     刷新用户界面
@@ -147,6 +153,7 @@ def trimmed_format_exc():
     replace_path = "."
     return str.replace(current_path, replace_path)
 
+
 def CatchException(f):
     """
     装饰器函数，捕捉函数f中的异常并封装到一个生成器中返回，并显示到聊天当中。
@@ -164,9 +171,9 @@ def CatchException(f):
             if len(chatbot_with_cookie) == 0:
                 chatbot_with_cookie.clear()
                 chatbot_with_cookie.append(["插件调度异常", "异常原因"])
-            chatbot_with_cookie[-1] = (chatbot_with_cookie[-1][0],
+            chatbot_with_cookie[-1] = (chatbot_with_cookie[-1][0], f"[Local Message] 插件调用出错: \n\n{tb_str} \n")
-                           f"[Local Message] 插件调用出错: \n\n{tb_str} \n\n当前代理可用性: \n\n{check_proxy(proxies)}")
             yield from update_ui(chatbot=chatbot_with_cookie, history=history, msg=f'异常 {e}')  # 刷新界面
+
     return decorated
 
 
@@ -209,6 +216,7 @@ def HotReload(f):
 ========================================================================
 """
 
+
 def get_reduce_token_percent(text):
     """
         * 此函数未来将被弃用
@@ -220,9 +228,9 @@ def get_reduce_token_percent(text):
         EXCEED_ALLO = 500  # 稍微留一点余地，否则在回复时会因余量太少出问题
         max_limit = float(match[0]) - EXCEED_ALLO
         current_tokens = float(match[1])
-        ratio = max_limit/current_tokens
+        ratio = max_limit / current_tokens
         assert ratio > 0 and ratio < 1
-        return ratio, str(int(current_tokens-max_limit))
+        return ratio, str(int(current_tokens - max_limit))
     except:
         return 0.5, '不详'
 
@@ -268,8 +276,6 @@ def regular_txt_to_markdown(text):
     return text
 
 
-
-
 def report_exception(chatbot, history, a, b):
     """
     向chatbot中添加错误信息
@@ -352,7 +358,8 @@ def markdown_convertion(txt):
         """
         解决一个mdx_math的bug（单$包裹begin命令时多余<script>）
         """
-        content = content.replace('<script type="math/tex">\n<script type="math/tex; mode=display">', '<script type="math/tex; mode=display">')
+        content = content.replace('<script type="math/tex">\n<script type="math/tex; mode=display">',
+                                  '<script type="math/tex; mode=display">')
         content = content.replace('</script>\n</script>', '</script>')
         return content
 
@@ -372,7 +379,7 @@ def markdown_convertion(txt):
         }
         matches = []
         for pattern, property in mathpatterns.items():
-            flags = re.ASCII|re.DOTALL if property['allow_multi_lines'] else re.ASCII
+            flags = re.ASCII | re.DOTALL if property['allow_multi_lines'] else re.ASCII
             matches.extend(re.findall(pattern, txt, flags))
         if len(matches) == 0: return False
         contain_any_eq = False
@@ -401,7 +408,7 @@ def markdown_convertion(txt):
                 stripped_string = line.lstrip()
                 num_spaces = len(line) - len(stripped_string)
                 if (num_spaces % 4) == 3:
-                    num_spaces_should_be = math.ceil(num_spaces/4) * 4
+                    num_spaces_should_be = math.ceil(num_spaces / 4) * 4
                     lines[i] = ' ' * num_spaces_should_be + stripped_string
         return '\n'.join(lines)
 
@@ -409,7 +416,8 @@ def markdown_convertion(txt):
     if is_equation(txt):  # 有$标识的公式符号，且没有代码段```的标识
         # convert everything to html format
         split = markdown.markdown(text='---')
-        convert_stage_1 = markdown.markdown(text=txt, extensions=['sane_lists', 'tables', 'mdx_math', 'fenced_code'], extension_configs=markdown_extension_configs)
+        convert_stage_1 = markdown.markdown(text=txt, extensions=['sane_lists', 'tables', 'mdx_math', 'fenced_code'],
+                                            extension_configs=markdown_extension_configs)
         convert_stage_1 = markdown_bug_hunt(convert_stage_1)
         # 1. convert to easy-to-copy tex (do not render math)
         convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)
@@ -441,8 +449,7 @@ def close_up_code_segment_during_stream(gpt_reply):
     segments = gpt_reply.split('```')
     n_mark = len(segments) - 1
     if n_mark % 2 == 1:
-        # print('输出代码片段中！')
+        return gpt_reply + '\n```' # 输出代码片段中！
-        return gpt_reply+'\n```'
     else:
         return gpt_reply
 
@@ -559,6 +566,7 @@ def file_already_in_downloadzone(file, user_path):
     except:
         return False
 
+
 def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
     # 将文件复制一份到下载区
     import shutil
@@ -581,8 +589,10 @@ def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
         if not os.path.exists(new_path): shutil.copyfile(file, new_path)
     # 将文件添加到chatbot cookie中
     if chatbot is not None:
-        if 'files_to_promote' in chatbot._cookies: current = chatbot._cookies['files_to_promote']
+        if 'files_to_promote' in chatbot._cookies:
-        else: current = []
+            current = chatbot._cookies['files_to_promote']
+        else:
+            current = []
         if new_path not in current: # 避免把同一个文件添加多次
             chatbot._cookies.update({'files_to_promote': [new_path] + current})
     return new_path
@@ -605,8 +615,10 @@ def del_outdated_uploads(outdate_time_seconds, target_path_base=None):
     for subdirectory in glob.glob(f'{user_upload_dir}/*'):
         subdirectory_time = os.path.getmtime(subdirectory)
         if subdirectory_time < one_hour_ago:
-            try: shutil.rmtree(subdirectory)
+            try:
-            except: pass
+                shutil.rmtree(subdirectory)
+            except:
+                pass
     return
 
 
@@ -690,12 +702,7 @@ def on_file_uploaded(request: gradio.Request, files, chatbot, txt, txt2, checkbo
         file_origin_name = os.path.basename(file.orig_name)
         this_file_path = pj(target_path_base, file_origin_name)
         shutil.move(file.name, this_file_path)
-        upload_msg += extract_archive(file_path=this_file_path, dest_dir=this_file_path+'.extract')
+        upload_msg += extract_archive(file_path=this_file_path, dest_dir=this_file_path + '.extract')
-
-    if "浮动输入区" in checkboxes: 
-        txt, txt2 = "", target_path_base
-    else:
-        txt, txt2 = target_path_base, ""
 
     # 整理文件集合 输出消息
     moved_files = [fp for fp in glob.glob(f'{target_path_base}/**/*', recursive=True)]
@@ -703,7 +710,11 @@ def on_file_uploaded(request: gradio.Request, files, chatbot, txt, txt2, checkbo
     chatbot.append(['我上传了文件，请查收',
                     f'[Local Message] 收到以下文件: \n\n{moved_files_str}' +
                     f'\n\n调用路径参数已自动修正到: \n\n{txt}' +
-                    f'\n\n现在您点击任意函数插件时，以上文件将被作为输入参数'+upload_msg])
+                    f'\n\n现在您点击任意函数插件时，以上文件将被作为输入参数' + upload_msg])
+
+    txt, txt2 = target_path_base, ""
+    if "浮动输入区" in checkboxes:
+        txt, txt2 = txt2, txt
 
     # 记录近期文件
     cookies.update({
@@ -732,22 +743,27 @@ 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')
     AZURE_CFG_ARRAY, NUM_CUSTOM_BASIC_BTN = get_conf('AZURE_CFG_ARRAY', 'NUM_CUSTOM_BASIC_BTN')
 
     # deal with azure openai key
     if is_any_api_key(AZURE_API_KEY):
-        if is_any_api_key(API_KEY): API_KEY = API_KEY + ',' + AZURE_API_KEY
+        if is_any_api_key(API_KEY):
-        else: API_KEY = AZURE_API_KEY
+            API_KEY = API_KEY + ',' + AZURE_API_KEY
+        else:
+            API_KEY = AZURE_API_KEY
     if len(AZURE_CFG_ARRAY) > 0:
         for azure_model_name, azure_cfg_dict in AZURE_CFG_ARRAY.items():
             if not azure_model_name.startswith('azure'):
                 raise ValueError("AZURE_CFG_ARRAY中配置的模型必须以azure开头")
             AZURE_API_KEY_ = azure_cfg_dict["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_
+                if is_any_api_key(API_KEY):
-                else: API_KEY = AZURE_API_KEY_
+                    API_KEY = API_KEY + ',' + AZURE_API_KEY_
+                else:
+                    API_KEY = AZURE_API_KEY_
 
     customize_fn_overwrite_ = {}
     for k in range(NUM_CUSTOM_BASIC_BTN):
@@ -760,6 +776,7 @@ def load_chat_cookies():
         })
     return {'api_key': API_KEY, 'llm_model': LLM_MODEL, 'customize_fn_overwrite': customize_fn_overwrite_}
 
+
 def is_openai_api_key(key):
     CUSTOM_API_KEY_PATTERN = get_conf('CUSTOM_API_KEY_PATTERN')
     if len(CUSTOM_API_KEY_PATTERN) != 0:
@@ -768,14 +785,17 @@ 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_AZURE)
 
+
 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_any_api_key(key):
     if ',' in key:
         keys = key.split(',')
@@ -785,8 +805,9 @@ def is_any_api_key(key):
     else:
         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, "Azure 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:
@@ -803,6 +824,7 @@ 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 select_api_key(keys, llm_model):
     import random
     avail_key_list = []
@@ -826,6 +848,7 @@ def select_api_key(keys, llm_model):
     api_key = random.choice(avail_key_list) # 随机负载均衡
     return api_key
 
+
 def read_env_variable(arg, default_value):
     """
     环境变量可以是 `GPT_ACADEMIC_CONFIG`(优先)，也可以直接是`CONFIG`
@@ -856,7 +879,7 @@ def read_env_variable(arg, default_value):
             env_arg = env_arg.strip()
             if env_arg == 'True': r = True
             elif env_arg == 'False': r = False
-            else: print('enter True or False, but have:', env_arg); r = default_value
+            else: print('Enter True or False, but have:', env_arg); r = default_value
         elif isinstance(default_value, int):
             r = int(env_arg)
         elif isinstance(default_value, float):
@@ -880,6 +903,7 @@ def read_env_variable(arg, default_value):
     print亮绿(f"[ENV_VAR] 成功读取环境变量{arg}")
     return r
 
+
 @lru_cache(maxsize=128)
 def read_single_conf_with_lru_cache(arg):
     from colorful import print亮红, print亮绿, print亮蓝
@@ -899,7 +923,7 @@ def read_single_conf_with_lru_cache(arg):
     if arg == 'API_URL_REDIRECT':
         oai_rd = r.get("https://api.openai.com/v1/chat/completions", None) # API_URL_REDIRECT填写格式是错误的，请阅读`https://github.com/binary-husky/gpt_academic/wiki/项目配置说明`
         if oai_rd and not oai_rd.endswith('/completions'):
-            print亮红( "\n\n[API_URL_REDIRECT] API_URL_REDIRECT填错了。请阅读`https://github.com/binary-husky/gpt_academic/wiki/项目配置说明`。如果您确信自己没填错，无视此消息即可。")
+            print亮红("\n\n[API_URL_REDIRECT] API_URL_REDIRECT填错了。请阅读`https://github.com/binary-husky/gpt_academic/wiki/项目配置说明`。如果您确信自己没填错，无视此消息即可。")
             time.sleep(5)
     if arg == 'API_KEY':
         print亮蓝(f"[API_KEY] 本项目现已支持OpenAI和Azure的api-key。也支持同时填写多个api-key，如API_KEY=\"openai-key1,openai-key2,azure-key3\"")
@@ -907,7 +931,7 @@ def read_single_conf_with_lru_cache(arg):
         if is_any_api_key(r):
             print亮绿(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
         else:
-            print亮红( "[API_KEY] 您的 API_KEY 不满足任何一种已知的密钥格式，请在config文件中修改API密钥之后再运行。")
+            print亮红("[API_KEY] 您的 API_KEY 不满足任何一种已知的密钥格式，请在config文件中修改API密钥之后再运行。")
     if arg == 'proxies':
         if not read_single_conf_with_lru_cache('USE_PROXY'): r = None # 检查USE_PROXY，防止proxies单独起作用
         if r is None:
@@ -953,17 +977,20 @@ class DummyWith():
     在上下文执行开始的情况下，__enter__()方法会在代码块被执行前被调用，
     而在上下文执行结束时，__exit__()方法则会被调用。
     """
+
     def __enter__(self):
         return self
 
     def __exit__(self, exc_type, exc_value, traceback):
         return
 
+
 def run_gradio_in_subpath(demo, auth, port, custom_path):
     """
     把gradio的运行地址更改到指定的二次路径上
     """
-    def is_path_legal(path: str)->bool:
+
+    def is_path_legal(path: str) -> bool:
         '''
         check path for sub url
         path: path to check
@@ -1039,7 +1066,7 @@ def clip_history(inputs, history, tokenizer, max_token_limit):
     while n_token > max_token_limit:
         where = np.argmax(everything_token)
         encoded = tokenizer.encode(everything[where], disallowed_special=())
-        clipped_encoded = encoded[:len(encoded)-delta]
+        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))
@@ -1047,6 +1074,7 @@ def clip_history(inputs, history, tokenizer, max_token_limit):
     history = everything[1:]
     return history
 
+
 """
 ========================================================================
 第三部分
@@ -1058,6 +1086,7 @@ def clip_history(inputs, history, tokenizer, max_token_limit):
 ========================================================================
 """
 
+
 def zip_folder(source_folder, dest_folder, zip_name):
     import zipfile
     import os
@@ -1089,15 +1118,18 @@ def zip_folder(source_folder, dest_folder, zip_name):
 
     print(f"Zip file created at {zip_file}")
 
+
 def zip_result(folder):
     t = gen_time_str()
     zip_folder(folder, get_log_folder(), f'{t}-result.zip')
     return pj(get_log_folder(), f'{t}-result.zip')
 
+
 def gen_time_str():
     import time
     return time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
 
+
 def get_log_folder(user=default_user_name, plugin_name='shared'):
     if user is None: user = default_user_name
     PATH_LOGGING = get_conf('PATH_LOGGING')
@@ -1108,29 +1140,36 @@ def get_log_folder(user=default_user_name, plugin_name='shared'):
     if not os.path.exists(_dir): os.makedirs(_dir)
     return _dir
 
+
 def get_upload_folder(user=default_user_name, tag=None):
     PATH_PRIVATE_UPLOAD = get_conf('PATH_PRIVATE_UPLOAD')
     if user is None: user = default_user_name
-    if tag is None or len(tag)==0:
+    if tag is None or len(tag) == 0:
         target_path_base = pj(PATH_PRIVATE_UPLOAD, user)
     else:
         target_path_base = pj(PATH_PRIVATE_UPLOAD, user, tag)
     return target_path_base
 
+
 def is_the_upload_folder(string):
     PATH_PRIVATE_UPLOAD = get_conf('PATH_PRIVATE_UPLOAD')
     pattern = r'^PATH_PRIVATE_UPLOAD[\\/][A-Za-z0-9_-]+[\\/]\d{4}-\d{2}-\d{2}-\d{2}-\d{2}-\d{2}$'
     pattern = pattern.replace('PATH_PRIVATE_UPLOAD', PATH_PRIVATE_UPLOAD)
-    if re.match(pattern, string): return True
+    if re.match(pattern, string):
-    else: return False
+        return True
+    else:
+        return False
+
 
 def get_user(chatbotwithcookies):
     return chatbotwithcookies._cookies.get('user_name', default_user_name)
 
+
 class ProxyNetworkActivate():
     """
     这段代码定义了一个名为ProxyNetworkActivate的空上下文管理器, 用于给一小段代码上代理
     """
+
     def __init__(self, task=None) -> None:
         self.task = task
         if not task:
@@ -1158,12 +1197,14 @@ class ProxyNetworkActivate():
         if 'HTTPS_PROXY' in os.environ: os.environ.pop('HTTPS_PROXY')
         return
 
+
 def objdump(obj, file='objdump.tmp'):
     import pickle
     with open(file, 'wb+') as f:
         pickle.dump(obj, f)
     return
 
+
 def objload(file='objdump.tmp'):
     import pickle, os
     if not os.path.exists(file):
@@ -1171,6 +1212,7 @@ def objload(file='objdump.tmp'):
     with open(file, 'rb') as f:
         return pickle.load(f)
 
+
 def Singleton(cls):
     """
     一个单实例装饰器
@@ -1184,6 +1226,7 @@ def Singleton(cls):
 
     return _singleton
 
+
 """
 ========================================================================
 第四部分
@@ -1197,6 +1240,7 @@ def Singleton(cls):
 ========================================================================
 """
 
+
 def set_conf(key, value):
     from toolbox import read_single_conf_with_lru_cache, get_conf
     read_single_conf_with_lru_cache.cache_clear()
@@ -1205,10 +1249,12 @@ def set_conf(key, value):
     altered = get_conf(key)
     return altered
 
+
 def set_multi_conf(dic):
     for k, v in dic.items(): set_conf(k, v)
     return
 
+
 def get_plugin_handle(plugin_name):
     """
     e.g. plugin_name = 'crazy_functions.批量Markdown翻译->Markdown翻译指定语言'
@@ -1220,12 +1266,14 @@ def get_plugin_handle(plugin_name):
     f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name)
     return f_hot_reload
 
+
 def get_chat_handle():
     """
     """
     from request_llms.bridge_all import predict_no_ui_long_connection
     return predict_no_ui_long_connection
 
+
 def get_plugin_default_kwargs():
     """
     """
@@ -1234,9 +1282,9 @@ def get_plugin_default_kwargs():
     llm_kwargs = {
         'api_key': cookies['api_key'],
         'llm_model': cookies['llm_model'],
-        'top_p':1.0, 
+        'top_p': 1.0,
         'max_length': None,
-        'temperature':1.0,
+        'temperature': 1.0,
     }
     chatbot = ChatBotWithCookies(llm_kwargs)
 
@@ -1252,6 +1300,7 @@ def get_plugin_default_kwargs():
     }
     return DEFAULT_FN_GROUPS_kwargs
 
+
 def get_chat_default_kwargs():
     """
     """
@@ -1259,9 +1308,9 @@ def get_chat_default_kwargs():
     llm_kwargs = {
         'api_key': cookies['api_key'],
         'llm_model': cookies['llm_model'],
-        'top_p':1.0, 
+        'top_p': 1.0,
         'max_length': None,
-        'temperature':1.0,
+        'temperature': 1.0,
     }
     default_chat_kwargs = {
         "inputs": "Hello there, are you ready?",
@@ -1307,6 +1356,7 @@ def get_max_token(llm_kwargs):
     from request_llms.bridge_all import model_info
     return model_info[llm_kwargs['llm_model']]['max_token']
 
+
 def check_packages(packages=[]):
     import importlib.util
     for p in packages: