# !pip install -U langchain
# !pip install -U langchainhub
# !pip install -U langchain_openai
# !pip install -U dashscope

from langchain.chains import LLMChain
from langchain_community.llms import Tongyi

import ChatGLM
from langchain.agents import AgentExecutor, create_structured_chat_agent, load_tools

from langchain import hub
import os

from langchain.prompts import PromptTemplate
os.environ["DASHSCOPE_API_KEY"] = "sk-cc1c8314fdbd43ceaf26ec1824d5dd3b"
os.environ["SERPAPI_API_KEY"] = "sk-cc1c8314fdbd43ceaf26ec1824d5dd3b"

# llm = Tongyi()
llm = ChatGLM.ChatGLM_LLM()

from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI
from langchain.agents import load_tools

from langchain_community.tools.tavily_search import TavilySearchResults
os.environ["TAVILY_API_KEY"] = "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"
os.environ["SERPAPI_API_KEY"] = "378cc16ff5396044a3a85721dc492f3d26a69e20"
prompt = hub.pull("hwchase17/structured-chat-agent")


tools = load_tools(["requests_all"])
agent = create_structured_chat_agent(llm, tools, prompt)
agent_executor = AgentExecutor(
    agent=agent, tools=tools
)
output = agent_executor.invoke({"input": "孙悟空是谁?"})
print(output["output"])