随机选择, 绕过openai访问频率限制

config.py

@@ -85,7 +85,7 @@ 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-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo",
                     "gpt-4", "gpt-4-32k", "azure-gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
-# P.S. 其他可用的模型还包括 ["qianfan", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", 
+# P.S. 其他可用的模型还包括 ["qianfan", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613",  "gpt-3.5-random"
 # "spark", "sparkv2", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
 
 

request_llm/bridge_all.py

@@ -135,6 +135,15 @@ model_info = {
         "token_cnt": get_token_num_gpt4,
     },
 
+    "gpt-3.5-random": {
+        "fn_with_ui": chatgpt_ui,
+        "fn_without_ui": chatgpt_noui,
+        "endpoint": openai_endpoint,
+        "max_token": 4096,
+        "tokenizer": tokenizer_gpt4,
+        "token_cnt": get_token_num_gpt4,
+    },
+    
     # azure openai
     "azure-gpt-3.5":{
         "fn_with_ui": chatgpt_ui,

request_llm/bridge_chatgpt.py

@@ -18,6 +18,7 @@ import logging
 import traceback
 import requests
 import importlib
+import random
 
 # 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
@@ -288,9 +289,19 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
     what_i_ask_now["role"] = "user"
     what_i_ask_now["content"] = inputs
     messages.append(what_i_ask_now)
+    model = llm_kwargs['llm_model'].strip('api2d-')
+    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", 
+            "gpt-3.5-turbo-16k",
+            "gpt-3.5-turbo-0613",
+            "gpt-3.5-turbo-16k-0613",
+            "gpt-3.5-turbo-0301",
+        ])
+        logging.info("Random select model:" + model)
 
     payload = {
-        "model": llm_kwargs['llm_model'].strip('api2d-'),
+        "model": model,
         "messages": messages, 
         "temperature": llm_kwargs['temperature'],  # 1.0,
         "top_p": llm_kwargs['top_p'],  # 1.0,