细分代理场景

config.py

@@ -183,6 +183,9 @@ ALLOW_RESET_CONFIG = False
 PATH_PRIVATE_UPLOAD = "private_upload"
 # 日志文件夹的位置，请勿修改
 PATH_LOGGING = "gpt_log"
+# 除了连接OpenAI之外，还有哪些场合允许使用代理，请勿修改
+WHEN_TO_USE_PROXY = ["Download_LLM", "Download_Gradio_Theme"]
+
 
 """
 在线大模型配置关联关系示意图

crazy_functions/Langchain知识库.py

@@ -53,14 +53,14 @@ def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
     yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
     print('Checking Text2vec ...')
     from langchain.embeddings.huggingface import HuggingFaceEmbeddings
-    with ProxyNetworkActivate():    # 临时地激活代理网络
+    with ProxyNetworkActivate('Download_LLM'):    # 临时地激活代理网络
         HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
 
     # < -------------------构建知识库--------------- >
     chatbot.append(['<br/>'.join(file_manifest), "正在构建知识库..."])
     yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
     print('Establishing knowledge archive ...')
-    with ProxyNetworkActivate():    # 临时地激活代理网络
+    with ProxyNetworkActivate('Download_LLM'):    # 临时地激活代理网络
         kai = knowledge_archive_interface()
         kai.feed_archive(file_manifest=file_manifest, id=kai_id)
     kai_files = kai.get_loaded_file()

crazy_functions/crazy_utils.py

@@ -651,7 +651,7 @@ class knowledge_archive_interface():
             from toolbox import ProxyNetworkActivate
             print('Checking Text2vec ...')
             from langchain.embeddings.huggingface import HuggingFaceEmbeddings
-            with ProxyNetworkActivate():    # 临时地激活代理网络
+            with ProxyNetworkActivate('Download_LLM'):    # 临时地激活代理网络
                 self.text2vec_large_chinese = HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
 
         return self.text2vec_large_chinese

request_llm/bridge_chatglm.py

@@ -3,7 +3,7 @@ from transformers import AutoModel, AutoTokenizer
 import time
 import threading
 import importlib
-from toolbox import update_ui, get_conf
+from toolbox import update_ui, get_conf, ProxyNetworkActivate
 from multiprocessing import Process, Pipe
 
 load_message = "ChatGLM尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，ChatGLM消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……"
@@ -48,16 +48,17 @@ class GetGLMHandle(Process):
 
         while True:
             try:
-                if self.chatglm_model is None:
-                    self.chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
-                    if device=='cpu':
-                        self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).float()
+                with ProxyNetworkActivate('Download_LLM'):
+                    if self.chatglm_model is None:
+                        self.chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
+                        if device=='cpu':
+                            self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).float()
+                        else:
+                            self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).half().cuda()
+                        self.chatglm_model = self.chatglm_model.eval()
+                        break
                     else:
-                        self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).half().cuda()
-                    self.chatglm_model = self.chatglm_model.eval()
-                    break
-                else:
-                    break
+                        break
             except:
                 retry += 1
                 if retry > 3: 

request_llm/bridge_llama2.py

@@ -30,7 +30,7 @@ class GetONNXGLMHandle(LocalLLMHandle):
         with open(os.path.expanduser('~/.cache/huggingface/token'), 'w') as f:
             f.write(huggingface_token)
         model_id = 'meta-llama/Llama-2-7b-chat-hf'
-        with ProxyNetworkActivate():
+        with ProxyNetworkActivate('Download_LLM'):
             self._tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=huggingface_token)
             # use fp16
             model = AutoModelForCausalLM.from_pretrained(model_id, use_auth_token=huggingface_token).eval()

themes/gradios.py

@@ -5,7 +5,7 @@ CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAY
 
 def dynamic_set_theme(THEME):
     set_theme = gr.themes.ThemeClass()
-    with ProxyNetworkActivate():
+    with ProxyNetworkActivate('Download_Gradio_Theme'):
         logging.info('正在下载Gradio主题，请稍等。')
         if THEME.startswith('Huggingface-'): THEME = THEME.lstrip('Huggingface-')
         if THEME.startswith('huggingface-'): THEME = THEME.lstrip('huggingface-')
@@ -16,7 +16,7 @@ def adjust_theme():
 
     try:
         set_theme = gr.themes.ThemeClass()
-        with ProxyNetworkActivate():
+        with ProxyNetworkActivate('Download_Gradio_Theme'):
             logging.info('正在下载Gradio主题，请稍等。')
             THEME, = get_conf('THEME')
             if THEME.startswith('Huggingface-'): THEME = THEME.lstrip('Huggingface-')

toolbox.py

@@ -956,7 +956,19 @@ class ProxyNetworkActivate():
     """
     这段代码定义了一个名为TempProxy的空上下文管理器, 用于给一小段代码上代理
     """
+    def __init__(self, task=None) -> None:
+        self.task = task
+        if not task:
+            # 不给定task, 那么我们默认代理生效
+            self.valid = True
+        else:
+            # 给定了task, 我们检查一下
+            from toolbox import get_conf
+            WHEN_TO_USE_PROXY, = get_conf('WHEN_TO_USE_PROXY')
+            self.valid = (task in WHEN_TO_USE_PROXY)
+
     def __enter__(self):
+        if not self.valid: return self
         from toolbox import get_conf
         proxies, = get_conf('proxies')
         if 'no_proxy' in os.environ: os.environ.pop('no_proxy')