File size: 1,786 Bytes
9c400b9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 |
from dotenv import load_dotenv
from langchain.chains import LLMMathChain
from langchain.llms.openai import OpenAI
from langchain.chat_models import ChatOpenAI
from langchain.utilities.serpapi import SerpAPIWrapper
from langchain.agents import initialize_agent, Tool, AgentExecutor
import chainlit as cl
from src.tools.crypto_coin_price_tool import CryptoCoinPriceTool
load_dotenv()
@cl.on_chat_start
def start():
llm = ChatOpenAI(temperature=0, streaming=True)
llm1 = OpenAI(temperature=0, streaming=True)
search = SerpAPIWrapper()
get_crypto_coin_price = CryptoCoinPriceTool()
llm_math_chain = LLMMathChain.from_llm(llm=llm, verbose=True)
tools = [
Tool(
name="Search",
func=search.run,
description="useful for when you need to answer questions about current events. You should ask targeted questions",
handle_tool_error=True,
),
Tool(
name="Calculator",
func=llm_math_chain.run,
description="useful for when you need to answer questions about math",
handle_tool_error=True,
),
Tool(
name=get_crypto_coin_price.name,
func=get_crypto_coin_price.run,
description=get_crypto_coin_price.description,
handle_tool_error=True,
),
]
agent = initialize_agent(
tools, llm1, agent="chat-zero-shot-react-description", verbose=True, handle_parsing_errors=True
)
cl.user_session.set("agent", agent)
@cl.on_message
async def main(message: cl.Message):
agent = cl.user_session.get("agent") # type: AgentExecutor
cb = cl.LangchainCallbackHandler(stream_final_answer=True)
await cl.make_async(agent.run)(message.content, callbacks=[cb])
|