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app.py updated
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import streamlit as st
from langchain_groq import ChatGroq
from langchain_community.utilities import ArxivAPIWrapper, WikipediaAPIWrapper
from langchain_community.tools import ArxivQueryRun, WikipediaQueryRun
from langchain.agents import initialize_agent, AgentType
from langchain.callbacks import StreamlitCallbackHandler
## Initialize Tools
arxiv_wrapper = ArxivAPIWrapper(top_k_results=1, doc_content_chars_max=200)
arxiv = ArxivQueryRun(api_wrapper=arxiv_wrapper)
wiki_wrapper = WikipediaAPIWrapper(top_k_results=1, doc_content_chars_max=200)
wiki = WikipediaQueryRun(api_wrapper=wiki_wrapper)
## Streamlit UI
st.title("πŸ”Ž LangChain - Chat with search")
st.sidebar.title("Settings")
api_key = st.sidebar.text_input("Enter your Groq API Key:", type="password")
if "messages" not in st.session_state:
st.session_state["messages"] = [
{"role": "assistant", "content": "Hi, I'm a chatbot who can search the web. How can I help you?"}
]
for msg in st.session_state.messages:
st.chat_message(msg["role"]).write(msg['content'])
if prompt := st.chat_input(placeholder="What is machine learning?"):
st.session_state.messages.append({"role": "user", "content": prompt})
st.chat_message("user").write(prompt)
llm = ChatGroq(groq_api_key=api_key, model_name="Llama3-8b-8192", streaming=True)
tools = [search, arxiv, wiki]
search_agent = initialize_agent(
tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, handle_parsing_errors=True
)
with st.chat_message("assistant"):
st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False)
user_query = st.session_state.messages[-1]["content"]
try:
response = search_agent.run(user_query, callbacks=[st_cb])
response = response if response else "Sorry, I couldn't find any relevant information."
except Exception as e:
response = f"An error occurred: {str(e)}"
st.session_state.messages.append({'role': 'assistant', "content": response})
st.write(response)