Function use_llms_with_web

app.py:287–348

()

# Function to use LLMs with web search
def use_llms_with_web():
    from langchain.agents import ConversationalChatAgent, AgentExecutor
    from langchain.callbacks import StreamlitCallbackHandler
    from langchain.chat_models import ChatOpenAI
    from langchain.memory import ConversationBufferMemory
    from langchain.memory.chat_message_histories import StreamlitChatMessageHistory
    from langchain.tools import DuckDuckGoSearchRun
    import streamlit as st


    st.title("Use web search with LLMs")
    # Taking OpenAI API key input from the user
    openai_api_key = st.sidebar.text_input("OpenAI API Key", type="password")
    # Initializing message history and memory
    msgs = StreamlitChatMessageHistory()
    memory = ConversationBufferMemory(
        chat_memory=msgs, return_messages=True, memory_key="chat_history", output_key="output"
    )
    # Resetting chat history logic
    if len(msgs.messages) == 0 or st.sidebar.button("Reset chat history"):
        msgs.clear()
        msgs.add_ai_message("How can I help you?")
        st.session_state.steps = {}

    # Defining avatars for chat messages
    avatars = {"human": "user", "ai": "assistant"}
    for idx, msg in enumerate(msgs.messages):
        with st.chat_message(avatars[msg.type]):
            # Render intermediate steps if any were saved
            for step in st.session_state.steps.get(str(idx), []):
                if step[0].tool == "_Exception":
                    continue
                with st.status(f"**{step[0].tool}**: {step[0].tool_input}", state="complete"):
                    st.write(step[0].log)
                    st.write(step[1])
            st.write(msg.content)

    # Taking new input from the user
    if prompt := st.chat_input(placeholder="Who won the 2022 Cricket World Cup?"):
        st.chat_message("user").write(prompt)
        # Checking if OpenAI API key is provided
        if not openai_api_key:
            st.info("Please add your OpenAI API key to continue.")
            st.stop()
        # Initializing LLM and tools for web search
        llm = ChatOpenAI(model_name="gpt-3.5-turbo", openai_api_key=openai_api_key, streaming=True)
        tools = [DuckDuckGoSearchRun(name="Search")]
        chat_agent = ConversationalChatAgent.from_llm_and_tools(llm=llm, tools=tools)

        executor = AgentExecutor.from_agent_and_tools(
            agent=chat_agent,
            tools=tools,
            memory=memory,
            return_intermediate_steps=True,
            handle_parsing_errors=True,
        )

        with st.chat_message("assistant"):