delete instructor tab

app.py

@@ -32,99 +32,73 @@ with gr.Blocks() as demo:
     #initialize tutor (with state)
     study_tutor = gr.State(SlightlyDelusionalTutor())
 
-    # Student interface
-    with gr.Tab("For Students"): 
-        
-        # Chatbot interface
-        gr.Markdown("""
-        ## Chat with the Model
-        Description here
-        """)
+    # Student chatbot interface
+    gr.Markdown("""
+    ## Chat with the Model
+    Description here
+    """)
     
-        with gr.Row(equal_height=True):
-            with gr.Column(scale=2):
-              chatbot = gr.Chatbot()
-              with gr.Row():
-                user_chat_input = gr.Textbox(label="User input", scale=9)
-                user_chat_submit = gr.Button("Ask/answer model", scale=1)
+    """
+    API Authentication functionality
+    Instead of ask students to provide key, the key is now provided by the instructor. 
+    To permanently set the key, go to Settings -> Variables and secrets -> Secrets, 
+    then replace OPENAI_API_KEY value with whatever openai key of the instructor.
+    """
+    api_input = gr.Textbox(show_label=False, type="password", visible=False, value=os.environ.get("OPENAI_API_KEY"))
 
-        # First add user's message to the conversation history
-        # Then get reply from the tutor and add that to the conversation history
-        user_chat_submit.click(
-            fn = add_user_message, inputs = [user_chat_input, study_tutor], outputs = [user_chat_input, chatbot, study_tutor], queue=False
-        ).then(
-            fn = get_tutor_reply, inputs = [study_tutor], outputs = [user_chat_input, chatbot, study_tutor], queue=True
-        )
+    # The instructor will provide a secret prompt/persona to the tutor
+    instructor_prompt = gr.Textbox(label="Verify your prompt content", value = os.environ.get("SECRET_PROMPT"), visible=False)
+    
+    # Placeholders components
+    text_input_none = gr.Textbox(visible=False)
+    file_input_none = gr.File(visible=False)
+    instructor_input_none = gr.TextArea(visible=False)
+    learning_objectives_none = gr.Textbox(visible=False)
 
-        # Testing the chat history storage, can be deleted at deployment
-        with gr.Blocks():
-            test_btn = gr.Button("View your chat history")
-            chat_history = gr.JSON(label = "conversation history")
-            test_btn.click(get_conversation_history, inputs=[study_tutor], outputs=[chat_history, study_tutor])
+    # Set the secret prompt in this session and embed it to the study tutor
+    prompt_submit_btn = gr.Button("Initialize Tutor")
+    prompt_submit_btn.click(
+        fn=create_reference_store, 
+        inputs=[study_tutor, prompt_submit_btn, instructor_prompt, file_input_none, instructor_input_none, api_input, instructor_prompt],
+        outputs=[study_tutor, prompt_submit_btn]
+    )
 
-        # Download conversation history file
-        with gr.Blocks():
-            gr.Markdown("""
-            ## Export Your Chat History
-            Export your chat history as a .json, .txt, or .csv file
-            """)
+    with gr.Row(equal_height=True):
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot()
             with gr.Row():
-                export_dialogue_button_json = gr.Button("JSON")
-                export_dialogue_button_txt = gr.Button("TXT")
-                export_dialogue_button_csv = gr.Button("CSV")
-        
-            file_download = gr.Files(label="Download here", file_types=['.json', '.txt', '.csv'], type="file", visible=False)
-        
-        export_dialogue_button_json.click(save_json, study_tutor, file_download, show_progress=True)
-        export_dialogue_button_txt.click(save_txt, study_tutor, file_download, show_progress=True)
-        export_dialogue_button_csv.click(save_csv, study_tutor, file_download, show_progress=True)
+            user_chat_input = gr.Textbox(label="User input", scale=9)
+            user_chat_submit = gr.Button("Ask/answer model", scale=1)
 
-    # Instructor interface
-    with gr.Tab("Instructor Only"):
-        """
-        API Authentication functionality
-        Instead of ask students to provide key, the key is now provided by the instructor. 
-        To permanently set the key, go to Settings -> Variables and secrets -> Secrets, 
-        then replace OPENAI_API_KEY value with whatever openai key of the instructor.
-        """
-        api_input = gr.Textbox(show_label=False, type="password", visible=False, value=os.environ.get("OPENAI_API_KEY"))
-
-        # Upload secret prompt functionality
-        # The instructor will provide a secret prompt/persona to the tutor
-        with gr.Blocks():
-            # testing purpose, change visible to False at deployment
-            view_secret = gr.Textbox(label="Current secret prompt", value=os.environ.get("SECRET_PROMPT"), visible=False)
-
-            # Prompt instructor to upload the secret file
-            file_input = gr.File(label="Load a .txt or .py file", file_types=['.py', '.txt'], type="file", elem_classes="short-height")
-            
-            # Verify prompt content
-            instructor_prompt = gr.Textbox(label="Verify your prompt content", visible=True)
-            file_input.upload(fn=get_instructor_prompt, inputs=file_input, outputs=instructor_prompt)
+    # First add user's message to the conversation history
+    # Then get reply from the tutor and add that to the conversation history
+    user_chat_submit.click(
+        fn = add_user_message, inputs = [user_chat_input, study_tutor], outputs = [user_chat_input, chatbot, study_tutor], queue=False
+    ).then(
+        fn = get_tutor_reply, inputs = [study_tutor], outputs = [user_chat_input, chatbot, study_tutor], queue=True
+    )
 
-            # Placeholders components
-            text_input_none = gr.Textbox(visible=False)
-            file_input_none = gr.File(visible=False)
-            instructor_input_none = gr.TextArea(visible=False)
-            learning_objectives_none = gr.Textbox(visible=False)
+    # Testing the chat history storage, can be deleted at deployment
+    with gr.Blocks():
+        test_btn = gr.Button("View your chat history")
+        chat_history = gr.JSON(label = "conversation history")
+        test_btn.click(get_conversation_history, inputs=[study_tutor], outputs=[chat_history, study_tutor])
 
-            # Set the secret prompt in this session and embed it to the study tutor
-            prompt_submit_btn = gr.Button("Submit")
-            prompt_submit_btn.click(
-                fn=embed_prompt, inputs=[instructor_prompt, study_tutor], outputs=[view_secret, study_tutor]
-            ).then(
-                fn=create_reference_store, 
-                inputs=[study_tutor, prompt_submit_btn, instructor_prompt, file_input_none, instructor_input_none, api_input, instructor_prompt],
-                outputs=[study_tutor, prompt_submit_btn]
-            )
-            
-            # TODO: The instructor prompt is now only set in session if not go to Settings/secret, 
-            # to "permanently" set the secret prompt not seen by the students who use this space, 
-            # one possible way is to recreate the instructor interface in another space, 
-            # and load it here to chain with the student interface
-            
-            # TODO: Currently, the instructor prompt is handled as text input and stored in the vector store (and in the learning objective),
-            # which means the tutor now is still a question-answering tutor who viewed the prompt as context (but not really acting based on it). 
-            # We need to find a way to provide the prompt directly to the model and set its status. 
+    # Download conversation history file
+    with gr.Blocks():
+        gr.Markdown("""
+        ## Export Your Chat History
+        Export your chat history as a .json, .txt, or .csv file
+        """)
+        with gr.Row():
+            export_dialogue_button_json = gr.Button("JSON")
+            export_dialogue_button_txt = gr.Button("TXT")
+            export_dialogue_button_csv = gr.Button("CSV")
+    
+        file_download = gr.Files(label="Download here", file_types=['.json', '.txt', '.csv'], type="file", visible=False)
     
+    export_dialogue_button_json.click(save_json, study_tutor, file_download, show_progress=True)
+    export_dialogue_button_txt.click(save_txt, study_tutor, file_download, show_progress=True)
+    export_dialogue_button_csv.click(save_csv, study_tutor, file_download, show_progress=True)
+            
 demo.queue().launch(server_name='0.0.0.0', server_port=7860)