allow model mutex override

binary-husky · binary-husky · May 17, 2024 · Apr 13, 2024 · Apr 14, 2024 · Apr 14, 2024
commit 6a8329c74ff25cd6a7da0b06e3422be470c2c26f
diff --git a/request_llms/bridge_all.py b/request_llms/bridge_all.py
@@ -852,6 +852,13 @@ def decode(self, *args, **kwargs):
             AVAIL_LLM_MODELS += [azure_model_name]
 
 
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
+# -=-=-=-=-=-=-=-=-=- ?? 以上是模型路由 -=-=-=-=-=-=-=-=-=
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
+
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
+# -=-=-=-=-=-=-= ?? 以下是多模型路由切?函? -=-=-=-=-=-=-=
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
 
 
 def LLM_CATCH_EXCEPTION(f):
@@ -888,13 +895,11 @@ def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys
     model = llm_kwargs['llm_model']
     n_model = 1
     if '&' not in model:
-
-        # 如果只??1?大?言模型：
+        # 如果只??“一?”大?言模型（多?情?）：
         method = model_info[model]["fn_without_ui"]
         return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
     else:
-
-        # 如果同???多?大?言模型，??稍微??一点，但思路相同，?不必???else分支
+        # 如果同???“多?”大?言模型，??稍微??一点，但思路相同，?不必???else分支
         executor = ThreadPoolExecutor(max_workers=4)
         models = model.split('&')
         n_model = len(models)
@@ -947,8 +952,23 @@ def mutex_manager(window_mutex, observe_window):
         res = '<br/><br/>\n\n---\n\n'.join(return_string_collect)
         return res
 
-import core_functional
+# 根据基?功能? ModelOverride ???整模型?型，用于 `predict` 中
 import importlib
+import core_functional
+def execute_model_override(llm_kwargs, additional_fn, method):
+    functional = core_functional.get_core_functions()
+    if 'ModelOverride' in functional[additional_fn]:
+        # ?更新Prompt & ModelOverride
+        importlib.reload(core_functional)
+        functional = core_functional.get_core_functions()
+        model_override = functional[additional_fn]['ModelOverride']
+        if model_override not in model_info:
+            raise ValueError(f"模型覆盖?? '{model_override}' 指向一??不支持的模型，???配置文件。")
+        method = model_info[model_override]["fn_with_ui"]
+        llm_kwargs['llm_model'] = model_override
+        return llm_kwargs, additional_fn, method
+    # 默?返回原??
+    return llm_kwargs, additional_fn, method
 
 def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot,
             history:list=[], system_prompt:str='', stream:bool=True, additional_fn:str=None):
@@ -970,16 +990,11 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot,
     """
 
     inputs = apply_gpt_academic_string_mask(inputs, mode="show_llm")
+
     method = model_info[llm_kwargs['llm_model']]["fn_with_ui"]  # 如果?里??，??config中的AVAIL_LLM_MODELS??
 
-    importlib.reload(core_functional)    # ?更新prompt
-    functional = core_functional.get_core_functions()
-    if 'ModelOverride' in functional[additional_fn]:
-        model_override = functional[additional_fn]['ModelOverride']
-        if model_override not in model_info:
-            raise ValueError(f"模型覆盖?? '{model_override}' 指向一??不支持的模型，???配置文件。")
-        method = model_info[model_override]["fn_with_ui"]
-        llm_kwargs['llm_model'] = model_override
+    if additional_fn: # 根据基?功能? ModelOverride ???整模型?型
+        llm_kwargs, additional_fn, method = execute_model_override(llm_kwargs, additional_fn, method)
 
     yield from method(inputs, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, stream, additional_fn)