Update app.py

app.py

@@ -1,81 +1,56 @@
 import streamlit as st
 import openai
-import os
 
-# Function to get the API key from Streamlit secrets
-def get_api_key():
-    try:
-        return st.secrets["API_KEY"]
-    except KeyError:
-        st.error("API_KEY not found in Streamlit secrets. Please add it.")
-        return None
+# 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 interact with the OpenAI API
-def generate_response(prompt, model_name, api_key):
-    openai.api_key = api_key
+# Function to get a response from the OpenAI API
+def get_chat_response(prompt, model_index=0):
     try:
-        completion = openai.ChatCompletion.create(
-            model=model_name,
+        response = openai.ChatCompletion.create(
+            model=MODELS[model_index],
             messages=[{"role": "user", "content": prompt}]
         )
-        return completion.choices[0].message.content
-    except openai.APIError as e:  # Corrected error handling
-        st.error(f"OpenAI API Error with {model_name}: {e}")
-        return None
-    except openai.RateLimitError as e:
-        st.error(f"OpenAI Rate Limit Error with {model_name}: {e}")
-        return None
-    except openai.AuthenticationError as e:
-        st.error(f"OpenAI Authentication Error with {model_name}: {e}")
-        return None
-    except openai.ServiceUnavailableError as e:
-        st.error(f"OpenAI Service Unavailable Error with {model_name}: {e}")
-        return None
-    except Exception as e:  # Catch any other exception
-        st.error(f"An unexpected error occurred with {model_name}: {e}")
+        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
 
-# Main Streamlit app
-def main():
-    st.title("Chatbot with Model Switching")
-
-    # Initialize conversation history in session state
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-
-    # Display previous messages
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    # Get user input
-    prompt = st.chat_input("Say something")
-
-    if prompt:
-        # Add user message to the state
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        with st.chat_message("user"):
-            st.markdown(prompt)
-
-        # Define model priority
-        models = ["gpt-4", "gpt-3.5-turbo"]  # Add more models as needed
-
-        # Get API key
-        api_key = get_api_key()
-        if not api_key:
-            return
-
-        response = None
-        for model in models:
-            response = generate_response(prompt, model, api_key)
-            if response:
-                break # If a response is generated, break out of loop.
+# 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})
         
-        if response:
-            # Add bot message to state
-            st.session_state.messages.append({"role": "assistant", "content": response})
-            with st.chat_message("assistant"):
-                st.markdown(response)
-
-if __name__ == "__main__":
-    main()
+        # Display the response
+        st.write(f"**Assistant**: {response}")