added corenlp tab

app.py

@@ -47,7 +47,10 @@ def format_chat_prompt(message, chat_history, max_convo_length):
     prompt = f"{prompt}\nUser: {message}\nAssistant:"
     return prompt
 
-def gpt_respond(tab_name, message, chat_history, max_convo_length = 10):
+def gpt_respond(have_key, tab_name, message, chat_history, max_convo_length = 10):
+    if (have_key == "No"):
+        return "", chat_history
+    
     formatted_prompt = format_chat_prompt(message, chat_history, max_convo_length)
     print('Prompt + Context:')
     print(formatted_prompt)
@@ -183,6 +186,61 @@ def llama_strategies_respond(strategy, task_name, task_ling_ent, message, chat_h
 
 def interface():
         with gr.Tab("Linguistic Entities"):
+            gr.Markdown("""
+                        ## 📜 Step-By-Step Instructions
+
+                        - Enter a sentence for three models to process (Vicuna-7b, LLaMA-7b and GPT-3.5).
+                        - If you own an OpenAI API key, select 'Yes' in the dropdown. If you don't own one, select 'No'.
+                            - If you selected 'Yes', enter your OpenAI API Key [Link to your OpenAI keys](https://platform.openai.com/api-keys).
+                            - If you selected 'No', leave the 'OpenAI Key' field blank and continue with the rest.
+                        - Select a Linguistic Entity from the Dropdown.
+                        - Click 'Submit' to send your inputs to the models.
+                        - To enter a new prompt, scroll to the bottom and click 'Clear' to start again.
+
+                        ### ⏳ After you click 'Submit', the models will take a couple seconds to process your inputs. 
+                        ### 🤖 Then, the models will output the linguistic entity found in your prompt based on your selection!
+
+                        Note: If you get an 'Error' in the gpt-3.5 model, check the following:
+                        - Check that you entered your key correctly without any extra characters.
+                        - If you used a free key, it means you exceeded your quota from the free API Key.
+                        """)
+
+            # Inputs
+            ling_ents_prompt = gr.Textbox(show_label=False, placeholder="Write a prompt and press enter")
+            with gr.Row():
+                # Will activate after getting API key
+                have_key2 = gr.Dropdown(["Yes", "No"], label="Do you own an API Key?", scale=0.5)
+                ling_ents_apikey_input = gr.Textbox(label="Open AI Key", placeholder="Enter your Openai key here", type="password")
+            linguistic_entities = gr.Dropdown(["Noun", "Determiner", "Noun phrase", "Verb phrase", "Dependent clause", "T-units"], label="Linguistic Entity")
+            ling_ents_btn = gr.Button(value="Submit")
+
+            # Outputs
+            gr.Markdown("Strategy 1 QA-Based Prompting")
+
+            # linguistic_features_textbox = gr.Textbox(label="Linguistic Features", disabled=True)
+
+            with gr.Row():
+                gpt_ling_ents_chatbot = gr.Chatbot(label="gpt-3.5")
+                llama_ling_ents_chatbot = gr.Chatbot(label="llama-7b")
+                vicuna_ling_ents_chatbot = gr.Chatbot(label="vicuna-7b")
+            clear = gr.ClearButton(components=[ling_ents_prompt, ling_ents_apikey_input, vicuna_ling_ents_chatbot, llama_ling_ents_chatbot, gpt_ling_ents_chatbot])
+
+            # Event Handler for API Key
+            ling_ents_btn.click(update_api_key, inputs=ling_ents_apikey_input)
+
+            # Event Handler for GPT 3.5 Chatbot
+            ling_ents_btn.click(gpt_respond, inputs=[have_key2, linguistic_entities, ling_ents_prompt, gpt_ling_ents_chatbot], 
+                                outputs=[task_prompt, gpt_ling_ents_chatbot])
+            
+            # Event Handler for LLaMA Chatbot
+            ling_ents_btn.click(llama_respond, inputs=[linguistic_entities, ling_ents_prompt, llama_ling_ents_chatbot], 
+                      outputs=[linguistic_entities, ling_ents_prompt, llama_ling_ents_chatbot])
+            
+            # Event Handler for Vicuna Chatbot
+            ling_ents_btn.click(vicuna_respond, inputs=[linguistic_entities, ling_ents_prompt, vicuna_ling_ents_chatbot], 
+                      outputs=[linguistic_entities, ling_ents_prompt, vicuna_ling_ents_chatbot])
+
+        with gr.Tab("CoreNLP"):
             gr.Markdown("""
                         ## 📜 Step-By-Step Instructions