修复文心一言的接口问题

crazy_functions/vt_fns/vt_call_plugin.py

@@ -1,6 +1,6 @@
 from pydantic import BaseModel, Field
 from typing import List
-from toolbox import update_ui_lastest_msg, get_conf
+from toolbox import update_ui_lastest_msg, disable_auto_promotion
 from request_llm.bridge_all import predict_no_ui_long_connection
 from crazy_functions.json_fns.pydantic_io import GptJsonIO
 import copy, json, pickle, os, sys, time
@@ -13,11 +13,14 @@ def read_avail_plugin_enum():
     plugin_arr = {k:v for k, v in plugin_arr.items() if 'Info' in v}
     plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
     plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
+    plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
+    plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)})
     prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2)
     prompt = "\n\nThe defination of PluginEnum:\nPluginEnum=" + prompt
-    return prompt, plugin_arr_dict
+    return prompt, plugin_arr_dict, plugin_arr_dict_parse
 
 def wrap_code(txt):
+    txt = txt.replace('```','')
     return f"\n```\n{txt}\n```\n"
 
 def have_any_recent_upload_files(chatbot):
@@ -47,7 +50,7 @@ def get_inputs_show_user(inputs, plugin_arr_enum_prompt):
     return inputs_show_user
 
 def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
-    plugin_arr_enum_prompt, plugin_arr_dict = read_avail_plugin_enum()
+    plugin_arr_enum_prompt, plugin_arr_dict, plugin_arr_dict_parse = read_avail_plugin_enum()
     class Plugin(BaseModel):
         plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000")
         reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most")
@@ -67,17 +70,16 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
         gpt_reply = run_gpt_fn(inputs, "")
         plugin_sel = gpt_json_io.generate_output_auto_repair(gpt_reply, run_gpt_fn)
     except:
-        msg = "抱歉,当前的大语言模型无法理解您的需求。"
+        msg = f"抱歉, {llm_kwargs['llm_model']}无法理解您的需求。"
         msg += "请求的Prompt为：\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
         msg += "语言模型回复为：\n" + wrap_code(gpt_reply)
-        msg += "但您可以尝试再试一次\n"
+        msg += "\n但您可以尝试再试一次\n"
         yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
-    if plugin_sel.plugin_selection not in plugin_arr_dict:
-        msg = "抱歉, 找不到合适插件执行该任务, 当前的大语言模型可能无法理解您的需求。"
-        msg += "请求的Prompt为：\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
-        msg += "语言模型回复为：\n" + wrap_code(gpt_reply)
-        msg += "但您可以尝试再试一次\n"
+    if plugin_sel.plugin_selection not in plugin_arr_dict_parse:
+        msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。"
+        msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件：\n" + wrap_code(gpt_reply)
+        msg += "\n但您可以尝试再试一次\n"
         yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
         return
     
@@ -87,7 +89,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
     else:
         appendix_info = get_recent_file_prompt_support(chatbot)
 
-    plugin = plugin_arr_dict[plugin_sel.plugin_selection]
+    plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection]
     yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
     class PluginExplicit(BaseModel):
         plugin_selection: str = plugin_sel.plugin_selection
@@ -106,7 +108,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
     # ⭐ ⭐ ⭐ 执行插件
     fn = plugin['Function']
     fn_name = fn.__name__
-    msg = f'正在调用插件: {fn_name}\n\n插件说明：{plugin["Info"]}\n\n插件参数：{plugin_sel.plugin_arg}'
+    msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明：{plugin["Info"]}\n\n插件参数：{plugin_sel.plugin_arg}\n\n假如偏离了您的要求，按停止键终止。'
     yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
     yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1)
     return

crazy_functions/虚空终端.py

@@ -36,7 +36,7 @@ explain_msg = """
 
 2. 如果您使用「调用插件xxx」、「修改配置xxx」、「请问」等关键词，您的意图可以被识别的更准确。
 
-3. 使用GPT4等强力模型时，您的意图可以被识别的更准确。该插件诞生时间不长，欢迎您前往Github反馈问题。
+3. 建议使用 GPT3.5 或更强的模型，弱模型可能无法理解您的想法。该插件诞生时间不长，欢迎您前往Github反馈问题。
 
 4. 现在，如果需要处理文件，请您上传文件（将文件拖动到文件上传区），或者描述文件所在的路径。
 
@@ -46,7 +46,7 @@ explain_msg = """
 from pydantic import BaseModel, Field
 from typing import List
 from toolbox import CatchException, update_ui, gen_time_str
-from toolbox import update_ui_lastest_msg
+from toolbox import update_ui_lastest_msg, disable_auto_promotion
 from request_llm.bridge_all import predict_no_ui_long_connection
 from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
 from crazy_functions.crazy_utils import input_clipping
@@ -104,6 +104,7 @@ def analyze_intention_with_simple_rules(txt):
 
 @CatchException
 def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
+    disable_auto_promotion(chatbot=chatbot)
     # 获取当前虚空终端状态
     state = VoidTerminalState.get_state(chatbot)
     appendix_msg = ""
@@ -142,14 +143,17 @@ def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
         yield from update_ui_lastest_msg(
             lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
         gpt_json_io = GptJsonIO(UserIntention)
-        inputs = "Analyze the intention of the user according to following user input: \n\n" + txt + '\n\n' + gpt_json_io.format_instructions
+        rf_req = "\nchoose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']"
+        inputs = "Analyze the intention of the user according to following user input: \n\n" + \
+            ">> " + (txt+rf_req).rstrip('\n').replace('\n','\n>> ') + '\n\n' + gpt_json_io.format_instructions
         run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(
             inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
         try:
             user_intention = gpt_json_io.generate_output_auto_repair(run_gpt_fn(inputs, ""), run_gpt_fn)
+            lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}", 
         except:
             yield from update_ui_lastest_msg(
-                lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型不能理解您的意图", chatbot=chatbot, history=history, delay=0)
+                lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型（{llm_kwargs['llm_model']}）不能理解您的意图", chatbot=chatbot, history=history, delay=0)
             return
     else:
         pass

request_llm/bridge_qianfan.py

@@ -49,16 +49,17 @@ def get_access_token():
 
 def generate_message_payload(inputs, llm_kwargs, history, system_prompt):
     conversation_cnt = len(history) // 2
+    if system_prompt == "": system_prompt = "Hello"
     messages = [{"role": "user", "content": system_prompt}]
     messages.append({"role": "assistant", "content": 'Certainly!'})
     if conversation_cnt:
         for index in range(0, 2*conversation_cnt, 2):
             what_i_have_asked = {}
             what_i_have_asked["role"] = "user"
-            what_i_have_asked["content"] = history[index]
+            what_i_have_asked["content"] = history[index] if history[index]!="" else "Hello"
             what_gpt_answer = {}
             what_gpt_answer["role"] = "assistant"
-            what_gpt_answer["content"] = history[index+1]
+            what_gpt_answer["content"] = history[index+1] if history[index]!="" else "Hello"
             if what_i_have_asked["content"] != "":
                 if what_gpt_answer["content"] == "": continue
                 if what_gpt_answer["content"] == timeout_bot_msg: continue