2_Chatbot_Agent.py

import utils
import streamlit as st
from langchain.agents import AgentType
from langchain.chat_models import ChatOpenAI
from langchain.tools import DuckDuckGoSearchRun
from langchain.agents import initialize_agent, Tool
from langchain.callbacks import StreamlitCallbackHandler

from langchain.tools import WikipediaQueryRun
from langchain.utilities import WikipediaAPIWrapper

from langchain.tools import PythonREPLToo

st.set_page_config(page_title="ChatWeb", page_icon="🌐")
st.header('Chatbot with Web Browser Access')
st.write('Equipped with internet agent, enables users to ask questions about recent events')


class ChatbotTools:

    def __init__(self):
        utils.configure_openai_api_key()
        self.openai_model = "gpt-3.5-turbo"

    # def setup_agent(self):
    #     # Define tool
    #     ddg_search = DuckDuckGoSearchRun()
    #     tools = [
    #         Tool(
    #             name="DuckDuckGoSearch",
    #             func=ddg_search.run,
    #             description="Useful for when you need to answer questions about current events. You should ask targeted questions",
    #         )
    #     ]

    # # 1 a)
    # def setup_agent(self):
    #     # Define tool
    #     ddg_search = DuckDuckGoSearchRun()
    #     wiki_agent = WikipediaQueryRun(api_wrapper =
    #     WikipediaAPIWrapper())
    #     tools = [
    #         Tool(
    #         name="DuckDuckGoSearch",
    #         func=ddg_search.run,
    #         description="Useful for when you need to answer questions about current events. You should ask targeted questions",),
    #         Tool(
    #         name="Wikipedia",
    #         func=wiki_agent.run,
    #         description="Useful for when you need to query about a specific topic, person, or event. You should ask targeted questions",)
    #         ]
    #     # Setup LLM and Agent
    #     llm = ChatOpenAI(model_name=self.openai_model, streaming=True)
    #     agent = initialize_agent(
    #     tools=tools,
    #     llm=llm,
    #     agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
    #     handle_parsing_errors=True,
    #     verbose=True
    #     )
    #     return agent
       
    #     # Setup LLM and Agent
    #     llm = ChatOpenAI(model_name=self.openai_model, streaming=True)
    #     agent = initialize_agent(
    #         tools=tools,
    #         llm=llm,
    #         agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
    #         handle_parsing_errors=True,
    #         verbose=True
    #     )
    #     return agent

# 1 b) Second Shiba
def setup_agent(self):
        # Define tool
        ddg_search = DuckDuckGoSearchRun()
        wiki_agent = WikipediaQueryRun(api_wrapper =
        WikipediaAPIWrapper())
        python_repl = PythonREPLTool()
        tools = [
            Tool(
            name="DuckDuckGoSearch",
            func=ddg_search.run,
            description="Useful for when you need to answer questions about current events. You should ask targeted questions",),
            Tool(
            name="Wikipedia",
            func=wiki_agent.run,
            description="Useful for when you need to query about a specific topic, person, or event. You should ask targeted questions",),
            
            Tool(
            name="Python REPL",
            func=python_repl.run,
            description="A Python shell. Use this to execute python commands. Input should be a valid python command. If you expect output it should be printed out.",)
        ]
        # Setup LLM and Agent
        llm = ChatOpenAI(model_name=self.openai_model, streaming=True)
        agent = initialize_agent(
        tools=tools,
        llm=llm,
        agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
        handle_parsing_errors=True,
        verbose=True
        )
        return agent




    @utils.enable_chat_history
    def main(self):
        agent = self.setup_agent()
        user_query = st.chat_input(placeholder="Ask me anything!")
        if user_query:
            utils.display_msg(user_query, 'user')
            with st.chat_message("assistant"):
                try:
                    st_cb = StreamlitCallbackHandler(st.container())
                    response = agent.run(user_query, callbacks=[st_cb])
                    st.session_state.messages.append(
                        {"role": "assistant", "content": response})
                    st.write(response)
                except Exception as e:
                    print(e)



if __name__ == "__main__":
    obj = ChatbotTools()
    obj.main()