Merge remote-tracking branch 'upstream/master'

core_functional.py

@@ -31,6 +31,8 @@ def get_core_functions():
             "AutoClearHistory": True,
             # [6] 文本预处理 （可选参数，默认 None，举例：写个函数移除所有的换行符）
             "PreProcess": None,
+            # [7] 模型选择 （可选参数。如不设置，则使用当前全局模型；如设置，则用指定模型覆盖全局模型。）
+            # "ModelOverride": "gpt-3.5-turbo", # 主要用途：强制点击此基础功能按钮时，使用指定的模型。
         },
         "总结绘制脑图": {
             "Visible": False,

docs/translate_english.json

@@ -313,7 +313,7 @@
     "注意": "Attention",
     "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": "The function plugins marked in 'red' below need to read the path from the input area as a parameter",
     "更多函数插件": "More function plugins",
-    "打开插件列表": "Open plugin list",
+    "点击这里搜索插件列表": "Click Here to Search the Plugin List",
     "高级参数输入区": "Advanced parameter input area",
     "这里是特殊函数插件的高级参数输入区": "Here is the advanced parameter input area for special function plugins",
     "请先从插件列表中选择": "Please select from the plugin list first",

main.py

@@ -122,7 +122,7 @@ def main():
                             predefined_btns.update({k: functional[k]["Button"]})
                 with gr.Accordion("函数插件区", open=True, elem_id="plugin-panel") as area_crazy_fn:
                     with gr.Row():
-                        gr.Markdown("插件可读取“输入区”文本/路径作为参数（上传文件自动修正路径）")
+                        gr.Markdown("<small>插件可读取“输入区”文本/路径作为参数（上传文件自动修正路径）</small>")
                     with gr.Row(elem_id="input-plugin-group"):
                         plugin_group_sel = gr.Dropdown(choices=all_plugin_groups, label='', show_label=False, value=DEFAULT_FN_GROUPS,
                                                       multiselect=True, interactive=True, elem_classes='normal_mut_select').style(container=False)
@@ -142,7 +142,7 @@ def main():
                                 if not plugin.get("AsButton", True): dropdown_fn_list.append(k)     # 排除已经是按钮的插件
                                 elif plugin.get('AdvancedArgs', False): dropdown_fn_list.append(k)  # 对于需要高级参数的插件，亦在下拉菜单中显示
                             with gr.Row():
-                                dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="", show_label=False).style(container=False)
+                                dropdown = gr.Dropdown(dropdown_fn_list, value=r"点击这里搜索插件列表", label="", show_label=False).style(container=False)
                             with gr.Row():
                                 plugin_advanced_arg = gr.Textbox(show_label=True, label="高级参数输入区", visible=False,
                                                                  placeholder="这里是特殊函数插件的高级参数输入区").style(container=False)
@@ -314,7 +314,7 @@ def on_theme_dropdown_changed(theme, secret_css):
         )
         # 随变按钮的回调函数注册
         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
+            if k in [r"点击这里搜索插件列表", r"请先从插件列表中选择"]: return
             yield from ArgsGeneralWrapper(plugins[k]["Function"])(request, *args, **kwargs)
         click_handle = switchy_bt.click(route,[switchy_bt, *input_combo], output_combo)
         click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot]).then(None, [switchy_bt], None, _js=r"(fn)=>on_plugin_exe_complete(fn)")

request_llms/bridge_all.py

@@ -984,6 +984,14 @@ def decode(self, *args, **kwargs):
 for k,v in API_URL_REDIRECT.items():
     if k in model_info:
         model_info[k]['endpoint'] = v
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
+# -=-=-=-=-=-=-=-=-=- ☝️ 以上是模型路由 -=-=-=-=-=-=-=-=-=
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
+
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
+# -=-=-=-=-=-=-= 👇 以下是多模型路由切换函数 -=-=-=-=-=-=-=
+# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
+
 
 def LLM_CATCH_EXCEPTION(f):
     """
@@ -1019,13 +1027,11 @@ 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:
-
-        # 如果只询问1个大语言模型：
+        # 如果只询问“一个”大语言模型（多数情况）：
         method = model_info[model]["fn_without_ui"]
         return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_slience)
     else:
-
-        # 如果同时询问多个大语言模型，这个稍微啰嗦一点，但思路相同，您不必读这个else分支
+        # 如果同时询问“多个”大语言模型，这个稍微啰嗦一点，但思路相同，您不必读这个else分支
         executor = ThreadPoolExecutor(max_workers=4)
         models = model.split('&')
         n_model = len(models)
@@ -1078,8 +1084,26 @@ def mutex_manager(window_mutex, observe_window):
         res = '<br/><br/>\n\n---\n\n'.join(return_string_collect)
         return res
 
-
-def predict(inputs:str, llm_kwargs:dict, *args, **kwargs):
+# 根据基础功能区 ModelOverride 参数调整模型类型，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]:
+        # 热更新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"模型覆盖参数 '{model_override}' 指向一个暂不支持的模型，请检查配置文件。")
+        method = model_info[model_override]["fn_with_ui"]
+        llm_kwargs['llm_model'] = model_override
+        return llm_kwargs, additional_fn, method
+    # 默认返回原参数
+    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):
     """
     发送至LLM，流式获取输出。
     用于基础的对话功能。
@@ -1098,17 +1122,11 @@ def predict(inputs:str, llm_kwargs:dict, *args, **kwargs):
     """
 
     inputs = apply_gpt_academic_string_mask(inputs, mode="show_llm")
+
     method = model_info[llm_kwargs['llm_model']]["fn_with_ui"]  # 如果这里报错，检查config中的AVAIL_LLM_MODELS选项
 
-    if len(args) > 5 and isinstance(args[5],str):
-        additional_fn = args[5]
-        import core_functional
-        import importlib
-        importlib.reload(core_functional)    # 热更新prompt
-        core_functional = core_functional.get_core_functions()
-        if 'Model' in core_functional[additional_fn]:
-            method = model_info[core_functional[additional_fn]['Model']]["fn_with_ui"]
-            llm_kwargs['llm_model'] = core_functional[additional_fn]['Model']
-
-    yield from method(inputs, llm_kwargs, *args, **kwargs)
+    if additional_fn: # 根据基础功能区 ModelOverride 参数调整模型类型
+        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)