app.py

import streamlit as st
import openai

# Set up the OpenAI API key
openai.api_key = st.secrets['API_KEY']

# Define the models in order of preference
MODELS = ["gpt-4", "gpt-3.5-turbo", "gpt-3.5-turbo-16k"]

# Initialize session state to store conversation history
if "conversation" not in st.session_state:
    st.session_state.conversation = []

# Function to get a response from the OpenAI API
def get_chat_response(prompt, model_index=0):
    try:
        response = openai.ChatCompletion.create(
            model=MODELS[model_index],
            messages=[{"role": "user", "content": prompt}]
        )
        return response.choices[0].message['content']
    except openai.error.RateLimitError:
        if model_index + 1 < len(MODELS):
            st.warning(f"Quota exceeded for {MODELS[model_index]}. Switching to {MODELS[model_index + 1]}.")
            return get_chat_response(prompt, model_index + 1)
        else:
            st.error("All models have exceeded their quota. Please try again later.")
            return None
    except Exception as e:
        st.error(f"An error occurred: {e}")
        return None

# Streamlit UI
st.title("ChatGPT with Model Fallback")

# Display previous conversation
st.write("### Conversation History")
for message in st.session_state.conversation:
    st.write(f"**{message['role']}**: {message['content']}")

# User input
user_input = st.text_input("You: ", "")

if user_input:
    # Add user input to conversation history
    st.session_state.conversation.append({"role": "User", "content": user_input})
    
    # Get response from the model
    response = get_chat_response(user_input)
    
    if response:
        # Add model response to conversation history
        st.session_state.conversation.append({"role": "Assistant", "content": response})
        
        # Display the response
        st.write(f"**Assistant**: {response}")