import streamlit as st
from langchain_groq import ChatGroq
from langchain_community.utilities import ArxivAPIWrapper,WikipediaAPIWrapper
from langchain_community.tools import ArxivQueryRun, WikipediaQueryRun, DuckDuckGoSearchRun
from langchain.agents import initialize_agent, AgentType
from langchain.callbacks import StreamlitCallbackHandler
from dotenv import load_dotenv
import os

load_dotenv()

groq_api_key = os.getenv("GROQ_API_KEY")

arxiv_wrapper = ArxivAPIWrapper(top_k_results=3, doc_content_char_max = 200)
arxiv = ArxivQueryRun(api_wrapper=arxiv_wrapper)

wiki_wrapper = WikipediaAPIWrapper(top_k_results=3, doc_content_char_max = 200)
wiki = WikipediaQueryRun(api_wrapper=wiki_wrapper)

search = DuckDuckGoSearchRun(name="Search")

tools = [arxiv, wiki, search]
llm = ChatGroq(groq_api_key=groq_api_key, model="Llama3-8b-8192", streaming=True)

search_agent = initialize_agent(
    tools=tools,
    llm=llm,
    agent_type=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
    handle_parsing_errors=True
)

st.title("Search Engine with Agents")
st.write("This is a search engine that uses agents to search for information.")
st.write("You can search for information using Arxiv, Wikipedia, or DuckDuckGo.")

if "messages" not in st.session_state:
    st.session_state.messages = [
        {"role": "assistant", "content": "Hello! How can I assist you today?"}
    ]

for message in st.session_state.messages:
        st.chat_message(message["role"]).markdown(message["content"])

prompt = st.chat_input("Enter your question:")

if prompt:
    st.session_state.messages.append({"role": "user", "content": prompt})
    st.chat_message("user").markdown(prompt)

    with st.chat_message("assistant"):
        st_cb = StreamlitCallbackHandler(st.container(),expand_new_thoughts=False)
        response = search_agent.run(st.session_state.messages, callbacks=[st_cb])
        st.session_state.messages.append({"role": "assistant", "content": response})
        st.write(response)