version 3.6
This commit is contained in:
binary-husky
23
crazy_functions/agent_fns/auto_agent.py
Normal file
23
crazy_functions/agent_fns/auto_agent.py
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@@ -0,0 +1,23 @@
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from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
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from toolbox import report_exception, get_log_folder, update_ui_lastest_msg, Singleton
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from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
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from crazy_functions.agent_fns.general import AutoGenGeneral
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class AutoGenMath(AutoGenGeneral):
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def define_agents(self):
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from autogen import AssistantAgent, UserProxyAgent
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return [
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{
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"name": "assistant", # name of the agent.
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"cls": AssistantAgent, # class of the agent.
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},
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{
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"name": "user_proxy", # name of the agent.
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"cls": UserProxyAgent, # class of the agent.
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"human_input_mode": "ALWAYS", # always ask for human input.
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"llm_config": False, # disables llm-based auto reply.
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},
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]
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19
crazy_functions/agent_fns/echo_agent.py
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19
crazy_functions/agent_fns/echo_agent.py
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@@ -0,0 +1,19 @@
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from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
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class EchoDemo(PluginMultiprocessManager):
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def subprocess_worker(self, child_conn):
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# ⭐⭐ 子进程
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self.child_conn = child_conn
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while True:
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msg = self.child_conn.recv() # PipeCom
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if msg.cmd == "user_input":
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# wait futher user input
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self.child_conn.send(PipeCom("show", msg.content))
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wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.")
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if not wait_success:
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# wait timeout, terminate this subprocess_worker
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break
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elif msg.cmd == "terminate":
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self.child_conn.send(PipeCom("done", ""))
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break
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print('[debug] subprocess_worker terminated')
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134
crazy_functions/agent_fns/general.py
Normal file
134
crazy_functions/agent_fns/general.py
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@@ -0,0 +1,134 @@
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from toolbox import trimmed_format_exc, get_conf, ProxyNetworkActivate
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from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom
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from request_llms.bridge_all import predict_no_ui_long_connection
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import time
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def gpt_academic_generate_oai_reply(
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self,
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messages,
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sender,
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config,
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):
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llm_config = self.llm_config if config is None else config
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if llm_config is False:
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return False, None
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if messages is None:
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messages = self._oai_messages[sender]
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inputs = messages[-1]['content']
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history = []
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for message in messages[:-1]:
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history.append(message['content'])
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context=messages[-1].pop("context", None)
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assert context is None, "预留参数 context 未实现"
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reply = predict_no_ui_long_connection(
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inputs=inputs,
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llm_kwargs=llm_config,
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history=history,
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sys_prompt=self._oai_system_message[0]['content'],
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console_slience=True
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)
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assumed_done = reply.endswith('\nTERMINATE')
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return True, reply
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class AutoGenGeneral(PluginMultiprocessManager):
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def gpt_academic_print_override(self, user_proxy, message, sender):
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# ⭐⭐ run in subprocess
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self.child_conn.send(PipeCom("show", sender.name + "\n\n---\n\n" + message["content"]))
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def gpt_academic_get_human_input(self, user_proxy, message):
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# ⭐⭐ run in subprocess
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patience = 300
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begin_waiting_time = time.time()
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self.child_conn.send(PipeCom("interact", message))
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while True:
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time.sleep(0.5)
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if self.child_conn.poll():
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wait_success = True
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break
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if time.time() - begin_waiting_time > patience:
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self.child_conn.send(PipeCom("done", ""))
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wait_success = False
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break
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if wait_success:
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return self.child_conn.recv().content
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else:
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raise TimeoutError("等待用户输入超时")
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def define_agents(self):
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raise NotImplementedError
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def exe_autogen(self, input):
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# ⭐⭐ run in subprocess
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input = input.content
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with ProxyNetworkActivate("AutoGen"):
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code_execution_config = {"work_dir": self.autogen_work_dir, "use_docker": self.use_docker}
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agents = self.define_agents()
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user_proxy = None
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assistant = None
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for agent_kwargs in agents:
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agent_cls = agent_kwargs.pop('cls')
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kwargs = {
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'llm_config':self.llm_kwargs,
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'code_execution_config':code_execution_config
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}
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kwargs.update(agent_kwargs)
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agent_handle = agent_cls(**kwargs)
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agent_handle._print_received_message = lambda a,b: self.gpt_academic_print_override(agent_kwargs, a, b)
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for d in agent_handle._reply_func_list:
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if hasattr(d['reply_func'],'__name__') and d['reply_func'].__name__ == 'generate_oai_reply':
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d['reply_func'] = gpt_academic_generate_oai_reply
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if agent_kwargs['name'] == 'user_proxy':
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agent_handle.get_human_input = lambda a: self.gpt_academic_get_human_input(user_proxy, a)
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user_proxy = agent_handle
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if agent_kwargs['name'] == 'assistant': assistant = agent_handle
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try:
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if user_proxy is None or assistant is None: raise Exception("用户代理或助理代理未定义")
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user_proxy.initiate_chat(assistant, message=input)
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except Exception as e:
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tb_str = '```\n' + trimmed_format_exc() + '```'
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self.child_conn.send(PipeCom("done", "AutoGen 执行失败: \n\n" + tb_str))
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def subprocess_worker(self, child_conn):
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# ⭐⭐ run in subprocess
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self.child_conn = child_conn
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while True:
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msg = self.child_conn.recv() # PipeCom
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self.exe_autogen(msg)
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class AutoGenGroupChat(AutoGenGeneral):
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def exe_autogen(self, input):
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# ⭐⭐ run in subprocess
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import autogen
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input = input.content
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with ProxyNetworkActivate("AutoGen"):
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code_execution_config = {"work_dir": self.autogen_work_dir, "use_docker": self.use_docker}
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agents = self.define_agents()
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agents_instances = []
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for agent_kwargs in agents:
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agent_cls = agent_kwargs.pop("cls")
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kwargs = {"code_execution_config": code_execution_config}
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kwargs.update(agent_kwargs)
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agent_handle = agent_cls(**kwargs)
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agent_handle._print_received_message = lambda a, b: self.gpt_academic_print_override(agent_kwargs, a, b)
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agents_instances.append(agent_handle)
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if agent_kwargs["name"] == "user_proxy":
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user_proxy = agent_handle
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user_proxy.get_human_input = lambda a: self.gpt_academic_get_human_input(user_proxy, a)
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try:
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groupchat = autogen.GroupChat(agents=agents_instances, messages=[], max_round=50)
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manager = autogen.GroupChatManager(groupchat=groupchat, **self.define_group_chat_manager_config())
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manager._print_received_message = lambda a, b: self.gpt_academic_print_override(agent_kwargs, a, b)
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manager.get_human_input = lambda a: self.gpt_academic_get_human_input(manager, a)
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if user_proxy is None:
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raise Exception("user_proxy is not defined")
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user_proxy.initiate_chat(manager, message=input)
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except Exception:
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tb_str = "```\n" + trimmed_format_exc() + "```"
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self.child_conn.send(PipeCom("done", "AutoGen exe failed: \n\n" + tb_str))
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def define_group_chat_manager_config(self):
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raise NotImplementedError
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16
crazy_functions/agent_fns/persistent.py
Normal file
16
crazy_functions/agent_fns/persistent.py
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@@ -0,0 +1,16 @@
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from toolbox import Singleton
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@Singleton
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class GradioMultiuserManagerForPersistentClasses():
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def __init__(self):
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self.mapping = {}
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def already_alive(self, key):
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return (key in self.mapping) and (self.mapping[key].is_alive())
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def set(self, key, x):
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self.mapping[key] = x
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return self.mapping[key]
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def get(self, key):
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return self.mapping[key]
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194
crazy_functions/agent_fns/pipe.py
Normal file
194
crazy_functions/agent_fns/pipe.py
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@@ -0,0 +1,194 @@
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from toolbox import get_log_folder, update_ui, gen_time_str, get_conf, promote_file_to_downloadzone
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from crazy_functions.agent_fns.watchdog import WatchDog
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import time, os
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class PipeCom:
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def __init__(self, cmd, content) -> None:
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self.cmd = cmd
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self.content = content
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class PluginMultiprocessManager:
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def __init__(self, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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# ⭐ run in main process
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self.autogen_work_dir = os.path.join(get_log_folder("autogen"), gen_time_str())
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self.previous_work_dir_files = {}
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self.llm_kwargs = llm_kwargs
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self.plugin_kwargs = plugin_kwargs
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self.chatbot = chatbot
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self.history = history
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self.system_prompt = system_prompt
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# self.web_port = web_port
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self.alive = True
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self.use_docker = get_conf("AUTOGEN_USE_DOCKER")
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self.last_user_input = ""
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# create a thread to monitor self.heartbeat, terminate the instance if no heartbeat for a long time
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timeout_seconds = 5 * 60
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self.heartbeat_watchdog = WatchDog(timeout=timeout_seconds, bark_fn=self.terminate, interval=5)
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self.heartbeat_watchdog.begin_watch()
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def feed_heartbeat_watchdog(self):
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# feed this `dog`, so the dog will not `bark` (bark_fn will terminate the instance)
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self.heartbeat_watchdog.feed()
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def is_alive(self):
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return self.alive
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def launch_subprocess_with_pipe(self):
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# ⭐ run in main process
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from multiprocessing import Process, Pipe
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parent_conn, child_conn = Pipe()
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self.p = Process(target=self.subprocess_worker, args=(child_conn,))
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self.p.daemon = True
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self.p.start()
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return parent_conn
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def terminate(self):
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self.p.terminate()
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self.alive = False
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print("[debug] instance terminated")
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def subprocess_worker(self, child_conn):
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# ⭐⭐ run in subprocess
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raise NotImplementedError
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def send_command(self, cmd):
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# ⭐ run in main process
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repeated = False
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if cmd == self.last_user_input:
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repeated = True
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cmd = ""
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else:
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self.last_user_input = cmd
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self.parent_conn.send(PipeCom("user_input", cmd))
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return repeated, cmd
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def immediate_showoff_when_possible(self, fp):
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# ⭐ 主进程
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# 获取fp的拓展名
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file_type = fp.split('.')[-1]
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# 如果是文本文件, 则直接显示文本内容
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if file_type.lower() in ['png', 'jpg']:
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image_path = os.path.abspath(fp)
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self.chatbot.append([
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'检测到新生图像:',
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f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
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])
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yield from update_ui(chatbot=self.chatbot, history=self.history)
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def overwatch_workdir_file_change(self):
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# ⭐ 主进程 Docker 外挂文件夹监控
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path_to_overwatch = self.autogen_work_dir
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change_list = []
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# 扫描路径下的所有文件, 并与self.previous_work_dir_files中所记录的文件进行对比，
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# 如果有新文件出现，或者文件的修改时间发生变化，则更新self.previous_work_dir_files中
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# 把新文件和发生变化的文件的路径记录到 change_list 中
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for root, dirs, files in os.walk(path_to_overwatch):
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for file in files:
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file_path = os.path.join(root, file)
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if file_path not in self.previous_work_dir_files.keys():
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last_modified_time = os.stat(file_path).st_mtime
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self.previous_work_dir_files.update({file_path: last_modified_time})
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change_list.append(file_path)
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else:
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last_modified_time = os.stat(file_path).st_mtime
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if last_modified_time != self.previous_work_dir_files[file_path]:
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self.previous_work_dir_files[file_path] = last_modified_time
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change_list.append(file_path)
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if len(change_list) > 0:
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file_links = ""
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for f in change_list:
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res = promote_file_to_downloadzone(f)
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file_links += f'<br/><a href="file={res}" target="_blank">{res}</a>'
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yield from self.immediate_showoff_when_possible(f)
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self.chatbot.append(['检测到新生文档.', f'文档清单如下: {file_links}'])
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yield from update_ui(chatbot=self.chatbot, history=self.history)
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return change_list
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def main_process_ui_control(self, txt, create_or_resume) -> str:
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# ⭐ 主进程
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if create_or_resume == 'create':
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self.cnt = 1
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self.parent_conn = self.launch_subprocess_with_pipe() # ⭐⭐⭐
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repeated, cmd_to_autogen = self.send_command(txt)
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if txt == 'exit':
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self.chatbot.append([f"结束", "结束信号已明确，终止AutoGen程序。"])
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yield from update_ui(chatbot=self.chatbot, history=self.history)
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self.terminate()
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return "terminate"
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# patience = 10
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while True:
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time.sleep(0.5)
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if not self.alive:
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# the heartbeat watchdog might have it killed
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self.terminate()
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return "terminate"
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if self.parent_conn.poll():
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self.feed_heartbeat_watchdog()
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if "[GPT-Academic] 等待中" in self.chatbot[-1][-1]:
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self.chatbot.pop(-1) # remove the last line
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if "等待您的进一步指令" in self.chatbot[-1][-1]:
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self.chatbot.pop(-1) # remove the last line
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if '[GPT-Academic] 等待中' in self.chatbot[-1][-1]:
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self.chatbot.pop(-1) # remove the last line
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msg = self.parent_conn.recv() # PipeCom
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if msg.cmd == "done":
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self.chatbot.append([f"结束", msg.content])
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self.cnt += 1
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yield from update_ui(chatbot=self.chatbot, history=self.history)
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self.terminate()
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break
|
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if msg.cmd == "show":
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yield from self.overwatch_workdir_file_change()
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notice = ""
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if repeated: notice = "（自动忽略重复的输入）"
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self.chatbot.append([f"运行阶段-{self.cnt}（上次用户反馈输入为: 「{cmd_to_autogen}」{notice}", msg.content])
|
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self.cnt += 1
|
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yield from update_ui(chatbot=self.chatbot, history=self.history)
|
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if msg.cmd == "interact":
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yield from self.overwatch_workdir_file_change()
|
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self.chatbot.append([f"程序抵达用户反馈节点.", msg.content +
|
||||
"\n\n等待您的进一步指令." +
|
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"\n\n(1) 一般情况下您不需要说什么, 清空输入区, 然后直接点击“提交”以继续. " +
|
||||
"\n\n(2) 如果您需要补充些什么, 输入要反馈的内容, 直接点击“提交”以继续. " +
|
||||
"\n\n(3) 如果您想终止程序, 输入exit, 直接点击“提交”以终止AutoGen并解锁. "
|
||||
])
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yield from update_ui(chatbot=self.chatbot, history=self.history)
|
||||
# do not terminate here, leave the subprocess_worker instance alive
|
||||
return "wait_feedback"
|
||||
else:
|
||||
self.feed_heartbeat_watchdog()
|
||||
if '[GPT-Academic] 等待中' not in self.chatbot[-1][-1]:
|
||||
# begin_waiting_time = time.time()
|
||||
self.chatbot.append(["[GPT-Academic] 等待AutoGen执行结果 ...", "[GPT-Academic] 等待中"])
|
||||
self.chatbot[-1] = [self.chatbot[-1][0], self.chatbot[-1][1].replace("[GPT-Academic] 等待中", "[GPT-Academic] 等待中.")]
|
||||
yield from update_ui(chatbot=self.chatbot, history=self.history)
|
||||
# if time.time() - begin_waiting_time > patience:
|
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# self.chatbot.append([f"结束", "等待超时, 终止AutoGen程序。"])
|
||||
# yield from update_ui(chatbot=self.chatbot, history=self.history)
|
||||
# self.terminate()
|
||||
# return "terminate"
|
||||
|
||||
self.terminate()
|
||||
return "terminate"
|
||||
|
||||
def subprocess_worker_wait_user_feedback(self, wait_msg="wait user feedback"):
|
||||
# ⭐⭐ run in subprocess
|
||||
patience = 5 * 60
|
||||
begin_waiting_time = time.time()
|
||||
self.child_conn.send(PipeCom("interact", wait_msg))
|
||||
while True:
|
||||
time.sleep(0.5)
|
||||
if self.child_conn.poll():
|
||||
wait_success = True
|
||||
break
|
||||
if time.time() - begin_waiting_time > patience:
|
||||
self.child_conn.send(PipeCom("done", ""))
|
||||
wait_success = False
|
||||
break
|
||||
return wait_success
|
||||
28
crazy_functions/agent_fns/watchdog.py
Normal file
28
crazy_functions/agent_fns/watchdog.py
Normal file
@@ -0,0 +1,28 @@
|
||||
import threading, time
|
||||
|
||||
class WatchDog():
|
||||
def __init__(self, timeout, bark_fn, interval=3, msg="") -> None:
|
||||
self.last_feed = None
|
||||
self.timeout = timeout
|
||||
self.bark_fn = bark_fn
|
||||
self.interval = interval
|
||||
self.msg = msg
|
||||
self.kill_dog = False
|
||||
|
||||
def watch(self):
|
||||
while True:
|
||||
if self.kill_dog: break
|
||||
if time.time() - self.last_feed > self.timeout:
|
||||
if len(self.msg) > 0: print(self.msg)
|
||||
self.bark_fn()
|
||||
break
|
||||
time.sleep(self.interval)
|
||||
|
||||
def begin_watch(self):
|
||||
self.last_feed = time.time()
|
||||
th = threading.Thread(target=self.watch)
|
||||
th.daemon = True
|
||||
th.start()
|
||||
|
||||
def feed(self):
|
||||
self.last_feed = time.time()
|
||||
Reference in New Issue
Block a user