autogen plugin bug fix

这个提交包含在:
binary-husky
2024-01-22 00:08:04 +08:00
父节点 08b4e9796e
当前提交 a6fdc493b7
共有 2 个文件被更改,包括 32 次插入35 次删除

查看文件

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