app.py

# Import the necessary libraries
import streamlit as st
from openai import OpenAI  # TODO: Install the OpenAI library using pip install openai

st.title("Mini Project 2: Streamlit Chatbot")

# TODO: Replace with your actual OpenAI API key
openai_key = "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"
client = OpenAI(api_key=openai_key)

# Define a function to get the conversation history (Not required for Part-2, will be useful in Part-3)
def get_conversation() -> str:
    # return: A formatted string representation of the conversation.
    conversation = ""
    for message in st.session_state.messages:
        role = message["role"]
        content = message["content"]
        conversation += f"{role}: {content}\n"
    return conversation

# Check for existing session state variables
if "openai_model" not in st.session_state:
    st.session_state["openai_model"] = "gpt-3.5-turbo"  # Initialize model

if "messages" not in st.session_state:
    st.session_state.messages = []  # Initialize messages as an empty list

# Display existing chat messages
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# Wait for user input
if prompt := st.chat_input("What would you like to chat about?"):
    # Append user message to messages
    st.session_state.messages.append({"role": "user", "content": prompt})

    # Display user message
    with st.chat_message("user"):
        st.markdown(prompt)

    # Generate AI response
    with st.chat_message("assistant"):
        # Send request to OpenAI API
        response = client.chat.completions.create(
            model=st.session_state["openai_model"],
            messages=[{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]
        )
        ai_response = response.choices[0].message.content

        # Display AI response
        st.markdown(ai_response)

    # Append AI response to messages
    st.session_state.messages.append({"role": "assistant", "content": ai_response})