import os
from langchain import OpenAI 
from langchain.chat_models import ChatOpenAI
from langchain.chains.conversation.memory import ConversationBufferWindowMemory

turbo_llm = ChatOpenAI(
    temperature=0,
    model_name='gpt-3.5-turbo'
)

from langchain.tools import DuckDuckGoSearchTool
from langchain.agents import Tool
from langchain.tools import BaseTool

search = DuckDuckGoSearchTool()
# defining a single tool
tools = [
    Tool(
        name = "search",
        func=search.run,
        description="useful for when you need to answer questions about current events. You should ask targeted questions"
    )
]

def meaning_of_life(input=""):
    return 'The meaning of life is 42 if rounded but is actually 42.17658'
life_tool = Tool(
    name='Meaning of Life',
    func= meaning_of_life,
    description="Useful for when you need to answer questions about the meaning of life. input should be MOL "
)

import random
def random_num(input=""):
    return random.randint(0,5)
#random_num()
random_tool = Tool(
    name='Random number',
    func= random_num,
    description="Useful for when you need to get a random number. input should be 'random'"
)

from langchain.agents import initialize_agent

tools = [search, random_tool, life_tool]

# conversational agent memory
memory = ConversationBufferWindowMemory(
    memory_key='chat_history',
    k=3,
    return_messages=True
)

# create our agent
conversational_agent = initialize_agent(
    agent='chat-conversational-react-description',
    tools=tools,
    llm=turbo_llm,
    verbose=True,
    max_iterations=3,
    early_stopping_method='generate',
    memory=memory
)

ai_res=conversational_agent("What time is it in Beijing China?")
print(ai_res)