reverted changes

app.py

@@ -75,12 +75,12 @@ def gpt_respond(have_key, tab_name, message, chat_history, max_convo_length = 10
     formatted_prompt = format_chat_prompt(message, chat_history, max_convo_length)
     print('GPT ling ents Prompt + Context:')
     print(formatted_prompt)
-    bot_message = chat(user_prompt = f'''Output any <{tab_name}> in the following sentence: "{formatted_prompt}"''')
+    bot_message = chat(user_prompt = f'''Output any <{tab_name}> in the following sentence one per line: "{formatted_prompt}"''')
     chat_history.insert(0, (message, bot_message))
     return "", chat_history
 
 def vicuna_respond(tab_name, message, chat_history):
-    formatted_prompt = f'''Output any {tab_name} in the following sentence: "{message}"'''
+    formatted_prompt = f'''Output any {tab_name} in the following sentence one per line: "{message}"'''
     print('Vicuna Ling Ents Fn - Prompt + Context:')
     print(formatted_prompt)
     input_ids = vicuna_tokenizer.encode(formatted_prompt, return_tensors="pt")
@@ -97,7 +97,7 @@ def vicuna_respond(tab_name, message, chat_history):
     return tab_name, "", chat_history
 
 def llama_respond(tab_name, message, chat_history):
-    formatted_prompt = f'''Output any {tab_name} in the following sentence: "{message}"'''
+    formatted_prompt = f'''Output any {tab_name} in the following sentence one per line: "{message}"'''
     # print('Llama - Prompt + Context:')
     # print(formatted_prompt)
     input_ids = llama_tokenizer.encode(formatted_prompt, return_tensors="pt")
@@ -119,7 +119,7 @@ def gpt_strategies_respond(have_key, strategy, task_name, task_ling_ent, message
     formatted_system_prompt = ""
     if (task_name == "POS Tagging"):
         if (strategy == "S1"):
-            formatted_system_prompt = f'''Output any {task_ling_ent} in the following sentence: "{message}"'''
+            formatted_system_prompt = f'''Output any {task_ling_ent} in the following sentence one per line: "{message}"'''
         elif (strategy == "S2"):
             formatted_system_prompt = f'''POS tag the following sentence using Universal POS tag set: "{message}"'''
         elif (strategy == "S3"):
@@ -128,7 +128,7 @@ def gpt_strategies_respond(have_key, strategy, task_name, task_ling_ent, message
             formatted_system_prompt = f'''"{demon_pos}". Using the POS tag structure above, POS tag the following sentence: "{message}"'''
     elif (task_name == "Chunking"):
         if (strategy == "S1"):
-            formatted_system_prompt = f'''Output any {task_ling_ent} in the following sentence: "{message}"'''
+            formatted_system_prompt = f'''Output any {task_ling_ent} in the following sentence one per line: "{message}"'''
         elif (strategy == "S2"):
             formatted_system_prompt = f'''Chunk the following sentence in CoNLL 2000 format with BIO tags: "{message}"'''
         elif (strategy == "S3"):
@@ -147,7 +147,7 @@ def vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_
     formatted_prompt = ""
     if (task_name == "POS Tagging"):
         if (strategy == "S1"):
-            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence: "{message}"'''
+            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence one per line: "{message}"'''
         elif (strategy == "S2"):
             formatted_prompt = f'''POS tag the following sentence using Universal POS tag set: "{message}"'''
         elif (strategy == "S3"):
@@ -156,7 +156,7 @@ def vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_
             formatted_prompt = f'''"{demon_pos}". Using the POS tag structure above, POS tag the following sentence: "{message}"'''
     elif (task_name == "Chunking"):
         if (strategy == "S1"):
-            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence: "{message}"'''
+            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence one per line: "{message}"'''
         elif (strategy == "S2"):
             formatted_prompt = f'''Chunk the following sentence in CoNLL 2000 format with BIO tags: "{message}"'''
         elif (strategy == "S3"):
@@ -183,7 +183,7 @@ def llama_strategies_respond(strategy, task_name, task_ling_ent, message, chat_h
     formatted_prompt = ""
     if (task_name == "POS Tagging"):
         if (strategy == "S1"):
-            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence: "{message}"'''
+            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence one per line: "{message}"'''
         elif (strategy == "S2"):
             formatted_prompt = f'''POS tag the following sentence using Universal POS tag set: "{message}"'''
         elif (strategy == "S3"):
@@ -192,7 +192,7 @@ def llama_strategies_respond(strategy, task_name, task_ling_ent, message, chat_h
             formatted_prompt = f'''"{demon_pos}". Using the POS tag structure above, POS tag the following sentence: "{message}"'''
     elif (task_name == "Chunking"):
         if (strategy == "S1"):
-            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence: "{message}"'''
+            formatted_prompt = f'''Output any {task_ling_ent} in the following sentence one per line: "{message}"'''
         elif (strategy == "S2"):
             formatted_prompt = f'''Chunk the following sentence in CoNLL 2000 format with BIO tags: "{message}"'''
         elif (strategy == "S3"):
@@ -256,7 +256,7 @@ def interface():
             # Outputs
 
             user_prompt_1 = gr.Textbox(label="Original prompt")
-            linguistic_features_textbox = gr.Textbox(label="Linguistic Complexity", disabled=True, info="[Definitions for Complexity Indices](https://docs.google.com/spreadsheets/d/1uXtQ1ah0OL9cmHp2Hey0QcHb4bifJcQFLvYlVIAWWwQ/edit#gid=693915416)")
+            linguistic_features_textbox = gr.Textbox(label="Linguistic Complexity", disabled=True)
 
             with gr.Row():
                 gpt_ling_ents_chatbot = gr.Chatbot(label="gpt-3.5")
@@ -340,7 +340,7 @@ def interface():
 
             # Outputs
             user_prompt_2 = gr.Textbox(label="Original prompt", )
-            linguistic_features_textbox_2 = gr.Textbox(label="Linguistic Complexity", disabled=True, info="[Definitions for Complexity Indices](https://docs.google.com/spreadsheets/d/1uXtQ1ah0OL9cmHp2Hey0QcHb4bifJcQFLvYlVIAWWwQ/edit#gid=693915416)")
+            linguistic_features_textbox_2 = gr.Textbox(label="Linguistic Complexity", disabled=True)
 
             gr.Markdown("### Strategy 1 - QA-Based Prompting")
             strategy1 = gr.Markdown("S1", visible=False)