处理模型兼容的一些细节

crazy_functions/agent_fns/general.py

@@ -29,6 +29,7 @@ def gpt_academic_generate_oai_reply(
         sys_prompt=self._oai_system_message[0]['content'],
         console_slience=True
     )
+    assumed_done = reply.endswith('\nTERMINATE')
     return True, reply
 
 class AutoGenGeneral(PluginMultiprocessManager):

crazy_functions/agent_fns/pipe.py

@@ -21,7 +21,7 @@ class PluginMultiprocessManager:
         # self.web_port = web_port
         self.alive = True
         self.use_docker = get_conf("AUTOGEN_USE_DOCKER")
-
+        self.last_user_input = ""
         # create a thread to monitor self.heartbeat, terminate the instance if no heartbeat for a long time
         timeout_seconds = 5 * 60
         self.heartbeat_watchdog = WatchDog(timeout=timeout_seconds, bark_fn=self.terminate, interval=5)
@@ -55,6 +55,11 @@ class PluginMultiprocessManager:
 
     def send_command(self, cmd):
         # ⭐ run in main process
+        if cmd == self.last_user_input:
+            print('repeated input detected, ignore')
+            cmd = ""
+        else:
+            self.last_user_input = cmd
         self.parent_conn.send(PipeCom("user_input", cmd))
 
     def immediate_showoff_when_possible(self, fp):

crazy_functions/多智能体.py

@@ -48,11 +48,13 @@ def 多智能体终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
         "azure-gpt-4",
         "azure-gpt-4-32k",
     ]
-    if llm_kwargs['llm_model'] not in supported_llms:
+    from request_llms.bridge_all import model_info
-        chatbot.append([f"处理任务: {txt}", f"当前插件只支持{str(supported_llms)}, 当前模型{llm_kwargs['llm_model']}."])
+    if model_info[llm_kwargs['llm_model']]["max_token"] < 8000: # 至少是8k上下文的模型
+        chatbot.append([f"处理任务: {txt}", f"当前插件只支持{str(supported_llms)}, 当前模型{llm_kwargs['llm_model']}的最大上下文长度太短, 不能支撑AutoGen运行。"])
         yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
         return
-    llm_kwargs['api_key'] = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
+    if model_info[llm_kwargs['llm_model']]["endpoint"] is not None: # 如果不是本地模型，加载API_KEY
+        llm_kwargs['api_key'] = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
     
     # 检查当前的模型是否符合要求
     API_URL_REDIRECT = get_conf('API_URL_REDIRECT')

request_llms/bridge_all.py

@@ -242,6 +242,13 @@ for model in AVAIL_LLM_MODELS:
         mi.update({"endpoint": api2d_endpoint})
         model_info.update({model: mi})
 
+# -=-=-=-=-=-=- azure 对齐支持 -=-=-=-=-=-=-
+for model in AVAIL_LLM_MODELS:
+    if model.startswith('azure-') and (model.replace('azure-','') in model_info.keys()):
+        mi = model_info[model.replace('azure-','')]
+        mi.update({"endpoint": azure_endpoint})
+        model_info.update({model: mi})
+
 # -=-=-=-=-=-=- 以下部分是新加入的模型，可能附带额外依赖 -=-=-=-=-=-=-
 if "claude-1-100k" in AVAIL_LLM_MODELS or "claude-2" in AVAIL_LLM_MODELS:
     from .bridge_claude import predict_no_ui_long_connection as claude_noui