87ed1c4425
- 升级Agent（chat_module=agent切换）：升级到langgraph react agent逻辑、集成到主分支fay中、基于自动决策工具调用机制、基于日程跟踪的主动沟通、支持外部观测数据传入； - 修复因线程同步问题导致的配置文件读写不稳定 - 聊天采纳功能的bug修复
100 lines
4.4 KiB
Python
100 lines
4.4 KiB
Python
import os
|
||
import time
|
||
from llm.agent.tools.MyTimer import MyTimer
|
||
from llm.agent.tools.Weather import Weather
|
||
from llm.agent.tools.QueryTimerDB import QueryTimerDB
|
||
from llm.agent.tools.DeleteTimer import DeleteTimer
|
||
from llm.agent.tools.QueryTime import QueryTime
|
||
from llm.agent.tools.PythonExecutor import PythonExecutor
|
||
from llm.agent.tools.WebPageRetriever import WebPageRetriever
|
||
from llm.agent.tools.WebPageScraper import WebPageScraper
|
||
from llm.agent.tools.ToRemind import ToRemind
|
||
from langgraph.prebuilt import create_react_agent
|
||
from langchain_openai import ChatOpenAI
|
||
from langgraph.checkpoint.memory import MemorySaver
|
||
import utils.config_util as cfg
|
||
from utils import util
|
||
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
|
||
from core import content_db
|
||
from core import member_db
|
||
|
||
class FayAgentCore():
|
||
def __init__(self, uid=0, observation=""):
|
||
self.observation=observation
|
||
cfg.load_config()
|
||
os.environ["OPENAI_API_KEY"] = cfg.key_gpt_api_key
|
||
os.environ["OPENAI_API_BASE"] = cfg.gpt_base_url
|
||
os.environ["LANGCHAIN_TRACING_V2"] = "true"
|
||
os.environ["LANGCHAIN_ENDPOINT"] = "https://api.smith.langchain.com"
|
||
os.environ["LANGCHAIN_API_KEY"] = "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"
|
||
os.environ["LANGCHAIN_PROJECT"] = "pr-best-artist-21"
|
||
|
||
#创建llm
|
||
self.llm = ChatOpenAI(model=cfg.gpt_model_engine)
|
||
|
||
#创建agent graph
|
||
my_timer = MyTimer(uid=uid)#传入uid
|
||
weather_tool = Weather()
|
||
query_timer_db_tool = QueryTimerDB()
|
||
delete_timer_tool = DeleteTimer()
|
||
python_executor = PythonExecutor()
|
||
web_page_retriever = WebPageRetriever()
|
||
web_page_scraper = WebPageScraper()
|
||
to_remind = ToRemind()
|
||
self.tools = [my_timer, weather_tool, query_timer_db_tool, delete_timer_tool, python_executor, web_page_retriever, web_page_scraper, to_remind]
|
||
self.attr_info = ", ".join(f"{key}: {value}" for key, value in cfg.config["attribute"].items())
|
||
self.prompt_template = """
|
||
现在时间是：{now_time}。你是一个数字人，负责协助主人处理问题和陪伴主人生活、工作。你的个人资料是：{attr_info}。通过外部设备观测到：{observation}。\n请依据以信息为主人服务。
|
||
""".format(now_time=QueryTime().run(""), attr_info=self.attr_info, observation=self.observation)
|
||
self.memory = MemorySaver()
|
||
self.agent = create_react_agent(self.llm, self.tools, checkpointer=self.memory)
|
||
|
||
self.total_tokens = 0
|
||
self.total_cost = 0
|
||
|
||
#载入记忆
|
||
def get_history_messages(self, uid):
|
||
chat_history = []
|
||
history = content_db.new_instance().get_list('all','desc', 100, uid)
|
||
if history and len(history) > 0:
|
||
i = 0
|
||
while i < len(history):
|
||
if history[i][0] == "member":
|
||
chat_history.append(HumanMessage(content=history[i][2], user=member_db.new_instance().find_username_by_uid(uid=uid)))
|
||
else:
|
||
chat_history.append(AIMessage(content=history[i][2]))
|
||
i += 1
|
||
return chat_history
|
||
|
||
|
||
def run(self, input_text, uid=0):
|
||
result = ""
|
||
messages = self.get_history_messages(uid)
|
||
messages.insert(0, SystemMessage(self.prompt_template))
|
||
messages.append(HumanMessage(content=input_text))
|
||
|
||
try:
|
||
for chunk in self.agent.stream(
|
||
{"messages": messages}, {"configurable": {"thread_id": "tid{}".format(uid)}}
|
||
):
|
||
if chunk.get("agent"):
|
||
if chunk['agent']['messages'][0].content:
|
||
result = chunk['agent']['messages'][0].content
|
||
cb = chunk['agent']['messages'][0].response_metadata['token_usage']['total_tokens']
|
||
self.total_tokens = self.total_tokens + cb
|
||
|
||
util.log(1, "本次消耗token:{}，共消耗token:{}".format(cb, self.total_tokens))
|
||
except Exception as e:
|
||
print(e)
|
||
return result
|
||
|
||
def question(cont, uid=0, observation=""):
|
||
starttime = time.time()
|
||
agent = FayAgentCore(uid=uid, observation=observation)
|
||
response_text = agent.run(cont, uid)
|
||
util.log(1, "接口调用耗时 :" + str(time.time() - starttime))
|
||
return response_text
|
||
if __name__ == "__main__":
|
||
agent = FayAgentCore()
|
||
print(agent.run("你好"))
|