Update app.py

app.py

@@ -20,7 +20,15 @@ def get_api_key():
     api_key = os.getenv("OPENAI_API_KEY")
     return api_key
 
-def respond(message, chat_history, model_type):
+def set_model(model):
+    os.environ["model_type"] = model
+    return f"Your API Key has been set to: {model}"
+
+def get_model():
+    model = os.getenv("model_type")
+    return model    
+
+def respond(message, chat_history):
 
     # Get embeddings
     embeddings = OpenAIEmbeddings()
@@ -37,7 +45,7 @@ def respond(message, chat_history, model_type):
         chat_history = [(chat_history[0][0], chat_history[0][1])]
     
     # Create ChatOpenAI and ConversationalRetrievalChain
-    model = ChatOpenAI(model=model_type)
+    model = ChatOpenAI(model=get_model())
     qa = ConversationalRetrievalChain.from_llm(model, retriever)
 
     bot_message = qa({"question": message, "chat_history": chat_history})
@@ -67,15 +75,17 @@ with gr.Blocks() as demo:
         model_selection = gr.Dropdown(
             ["gpt-3.5-turbo", "gpt-4"], label="Model Selection", info="Please ensure you provide the API Key that corresponds to the Model you select!"
         ),
+        model_submit_button = gr.Button("Submit Model Selection")
         api_print = gr.Textbox(label = "OpenAI API Key - Please ensure the API Key is set correctly")
         chatbot = gr.Chatbot(label="ChatGPT Powered Coding Assistant")
         msg = gr.Textbox(label="User Prompt", placeholder="Your Query Here")
         clear = gr.Button("Clear")
         
-    api_submit_button.click(set_api_key, inputs=api_input, outputs=api_key_status)
+    api_submit_button.click(set_api_key, inputs=model_selection)
+    model_submit_button.click(set_model, inputs=api_input, outputs=api_key_status)
     api_reset_button.click(reset_api_key, outputs=api_key_status)
     api_check_button.click(get_api_key, outputs=api_print)
-    msg.submit(respond, inputs = [msg, chatbot, model_selection], outputs = [msg, chatbot])
+    msg.submit(respond, inputs = [msg, chatbot], outputs = [msg, chatbot])
     clear.click(lambda: None, None, chatbot, queue=False)
     
 demo.launch()