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autogen plugin bug fix

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This commit is contained in:
binary-husky 2024-01-22 00:08:04 +08:00
parent 08b4e9796e
commit a6fdc493b7
2 changed files with 32 additions and 35 deletions
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58
crazy_functions/agent_fns/general.py
View File

@ -35,7 +35,11 @@ def gpt_academic_generate_oai_reply(
class AutoGenGeneral(PluginMultiprocessManager): class AutoGenGeneral(PluginMultiprocessManager):
def gpt_academic_print_override(self, user_proxy, message, sender): def gpt_academic_print_override(self, user_proxy, message, sender):
# ⭐⭐ run in subprocess # ⭐⭐ run in subprocess
self.child_conn.send(PipeCom("show", sender.name + "\n\n---\n\n" + message["content"])) try:
print_msg = sender.name + "\n\n---\n\n" + message["content"]
except:
print_msg = sender.name + "\n\n---\n\n" + message
self.child_conn.send(PipeCom("show", print_msg))
def gpt_academic_get_human_input(self, user_proxy, message): def gpt_academic_get_human_input(self, user_proxy, message):
# ⭐⭐ run in subprocess # ⭐⭐ run in subprocess
@ -62,33 +66,33 @@ class AutoGenGeneral(PluginMultiprocessManager):
def exe_autogen(self, input): def exe_autogen(self, input):
# ⭐⭐ run in subprocess # ⭐⭐ run in subprocess
input = input.content input = input.content
with ProxyNetworkActivate("AutoGen"): code_execution_config = {"work_dir": self.autogen_work_dir, "use_docker": self.use_docker}
code_execution_config = {"work_dir": self.autogen_work_dir, "use_docker": self.use_docker} agents = self.define_agents()
agents = self.define_agents() user_proxy = None
user_proxy = None assistant = None
assistant = None for agent_kwargs in agents:
for agent_kwargs in agents: agent_cls = agent_kwargs.pop('cls')
agent_cls = agent_kwargs.pop('cls') kwargs = {
kwargs = { 'llm_config':self.llm_kwargs,
'llm_config':self.llm_kwargs, 'code_execution_config':code_execution_config
'code_execution_config':code_execution_config }
} kwargs.update(agent_kwargs)
kwargs.update(agent_kwargs) agent_handle = agent_cls(**kwargs)
agent_handle = agent_cls(**kwargs) agent_handle._print_received_message = lambda a,b: self.gpt_academic_print_override(agent_kwargs, a, b)
agent_handle._print_received_message = lambda a,b: self.gpt_academic_print_override(agent_kwargs, a, b) for d in agent_handle._reply_func_list:
for d in agent_handle._reply_func_list: if hasattr(d['reply_func'],'__name__') and d['reply_func'].__name__ == 'generate_oai_reply':
if hasattr(d['reply_func'],'__name__') and d['reply_func'].__name__ == 'generate_oai_reply': d['reply_func'] = gpt_academic_generate_oai_reply
d['reply_func'] = gpt_academic_generate_oai_reply if agent_kwargs['name'] == 'user_proxy':
if agent_kwargs['name'] == 'user_proxy': agent_handle.get_human_input = lambda a: self.gpt_academic_get_human_input(user_proxy, a)
agent_handle.get_human_input = lambda a: self.gpt_academic_get_human_input(user_proxy, a) user_proxy = agent_handle
user_proxy = agent_handle if agent_kwargs['name'] == 'assistant': assistant = agent_handle
if agent_kwargs['name'] == 'assistant': assistant = agent_handle try:
try: if user_proxy is None or assistant is None: raise Exception("用户代理或助理代理未定义")
if user_proxy is None or assistant is None: raise Exception("用户代理或助理代理未定义") with ProxyNetworkActivate("AutoGen"):
user_proxy.initiate_chat(assistant, message=input) user_proxy.initiate_chat(assistant, message=input)
except Exception as e: except Exception as e:
tb_str = '```\n' + trimmed_format_exc() + '```' tb_str = '```\n' + trimmed_format_exc() + '```'
self.child_conn.send(PipeCom("done", "AutoGen 执行失败: \n\n" + tb_str)) self.child_conn.send(PipeCom("done", "AutoGen 执行失败: \n\n" + tb_str))
def subprocess_worker(self, child_conn): def subprocess_worker(self, child_conn):
# ⭐⭐ run in subprocess # ⭐⭐ run in subprocess

7
crazy_functions/多智能体.py
View File

@ -51,13 +51,6 @@ def 多智能体终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
if model_info[llm_kwargs['llm_model']]["endpoint"] is not None: # 如果不是本地模型，加载API_KEY 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']) 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')
if len(API_URL_REDIRECT) > 0:
chatbot.append([f"处理任务: {txt}", f"暂不支持中转."])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 尝试导入依赖，如果缺少依赖，则给出安装建议 # 尝试导入依赖，如果缺少依赖，则给出安装建议
try: try:
import autogen import autogen