updated strategy 3 prompt for vicuna and llama

app.py

@@ -132,14 +132,18 @@ def vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_
         elif (strategy == "S2"):
             formatted_prompt = f'''POS tag the following sentence using Universal POS tag set: "{message}"'''
         elif (strategy == "S3"):
-            formatted_prompt = f'''POS tag the following sentence using Universal POS tag set: "{message}"'''
+            with open('demonstration_3_42_pos.txt', 'r') as f:
+                demon_pos = f.read()
+            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 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"):
-            formatted_prompt = f'''Chunk the following sentence in CoNLL 2000 format with BIO tags: "{message}"'''
+            with open('demonstration_3_42_chunk.txt', 'r') as f:
+                demon_chunk = f.read()
+            formatted_prompt = f'''"{demon_chunk}". Using the Chunking structure above, Chunk the following sentence: "{message}"'''
     
     print('Vicuna Strategy Fn - Prompt + Context:')
     print(formatted_prompt)
@@ -152,7 +156,7 @@ def vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_
     bot_message = bot_message.replace(formatted_prompt, '')
     print(bot_message)
         
-    chat_history.append(0, (formatted_prompt, bot_message))
+    chat_history.insert(0, (formatted_prompt, bot_message))
     time.sleep(2)
     return task_name, "", chat_history
 
@@ -164,14 +168,18 @@ def llama_strategies_respond(strategy, task_name, task_ling_ent, message, chat_h
         elif (strategy == "S2"):
             formatted_prompt = f'''POS tag the following sentence using Universal POS tag set: "{message}"'''
         elif (strategy == "S3"):
-            formatted_prompt = f'''POS tag the following sentence using Universal POS tag set: "{message}"'''
+            with open('demonstration_3_42_pos.txt', 'r') as f:
+                demon_pos = f.read()
+            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 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"):
-            formatted_prompt = f'''Chunk the following sentence in CoNLL 2000 format with BIO tags: "{message}"'''
+            with open('demonstration_3_42_chunk.txt', 'r') as f:
+                demon_chunk = f.read()
+            formatted_prompt = f'''"{demon_chunk}". Using the Chunking structure above, Chunk the following sentence: "{message}"'''
     
     # print('Llama Strategies - Prompt + Context:')
     # print(formatted_prompt)
@@ -346,10 +354,10 @@ def interface():
             
             # vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_history):
             # Event Handlers for Vicuna Chatbot POS/Chunk
-            task_btn.click(vicuna_strategies_respond, inputs=[strategy1, task, task_linguistic_entities, task_prompt, vicuna_S1_chatbot], 
-                      outputs=[task, task_prompt, vicuna_S1_chatbot])
-            task_btn.click(vicuna_strategies_respond, inputs=[strategy2, task, task_linguistic_entities, task_prompt, vicuna_S2_chatbot], 
-                      outputs=[task, task_prompt, vicuna_S2_chatbot])
+            # task_btn.click(vicuna_strategies_respond, inputs=[strategy1, task, task_linguistic_entities, task_prompt, vicuna_S1_chatbot], 
+            #           outputs=[task, task_prompt, vicuna_S1_chatbot])
+            # task_btn.click(vicuna_strategies_respond, inputs=[strategy2, task, task_linguistic_entities, task_prompt, vicuna_S2_chatbot], 
+            #           outputs=[task, task_prompt, vicuna_S2_chatbot])
             task_btn.click(vicuna_strategies_respond, inputs=[strategy3, task, task_linguistic_entities, task_prompt, vicuna_S3_chatbot], 
                       outputs=[task, task_prompt, vicuna_S3_chatbot])