fixed inputs to llama, added prints to debug

app.py

@@ -81,16 +81,16 @@ def gpt_respond(tab_name, message, chat_history, max_convo_length = 10):
 
 def vicuna_respond(tab_name, message, chat_history):
     formatted_prompt = f'''Generate the output only for the assistant. Please output any {tab_name} in the following sentence one per line without any additional text: {message}'''
-    # print('Vicuna - Prompt + Context:')
-    # print(formatted_prompt)
+    print('Vicuna Ling Ents Fn - Prompt + Context:')
+    print(formatted_prompt)
     input_ids = vicuna_tokenizer.encode(formatted_prompt, return_tensors="pt")
     output_ids = vicuna_model.generate(input_ids, do_sample=True, max_length=1024, num_beams=5, no_repeat_ngram_size=2)
     bot_message = vicuna_tokenizer.decode(output_ids[0], skip_special_tokens=True)
-    # print(bot_message)
+    print(bot_message)
     
     # Remove formatted prompt from bot_message
     bot_message = bot_message.replace(formatted_prompt, '')
-    # print(bot_message)
+    print(bot_message)
         
     chat_history.append((formatted_prompt, bot_message))
     time.sleep(2)
@@ -154,16 +154,16 @@ def vicuna_strategies_respond(strategy, task_name, task_ling_ent, message, chat_
         elif (strategy == "S3"):
             formatted_prompt = f'''Please chunk the following sentence in CoNLL 2000 format with BIO tags without outputing any additional text: {message}'''
     
-    # print('Vicuna - Prompt + Context:')
-    # print(formatted_prompt)
+    print('Vicuna Strategy Fn - Prompt + Context:')
+    print(formatted_prompt)
     input_ids = vicuna_tokenizer.encode(formatted_prompt, return_tensors="pt")
     output_ids = vicuna_model.generate(input_ids, do_sample=True, max_length=1024, num_beams=5, no_repeat_ngram_size=2)
     bot_message = vicuna_tokenizer.decode(output_ids[0], skip_special_tokens=True)
-    # print(bot_message)
+    print(bot_message)
     
     # Remove formatted prompt from bot_message
     bot_message = bot_message.replace(formatted_prompt, '')
-    # print(bot_message)
+    print(bot_message)
         
     chat_history.append((formatted_prompt, bot_message))
     time.sleep(2)
@@ -288,21 +288,21 @@ def interface():
                       outputs=[task, task_prompt, vicuna_S3_chatbot])
             
             # Event Handler for LLaMA Chatbot POS/Chunk
-            task_btn.click(llama_respond, inputs=[task, task_prompt, llama_S1_chatbot], 
+            task_btn.click(llama_respond, inputs=[strategy1, task, task_linguistic_entities, task_prompt, llama_S1_chatbot], 
                       outputs=[task, task_prompt, llama_S1_chatbot])
-            task_btn.click(llama_respond, inputs=[task, task_prompt, llama_S2_chatbot], 
+            task_btn.click(llama_respond, inputs=[strategy2, task, task_linguistic_entities, task_prompt, llama_S2_chatbot], 
                       outputs=[task, task_prompt, llama_S2_chatbot])
-            task_btn.click(llama_respond, inputs=[task, task_prompt, llama_S3_chatbot], 
+            task_btn.click(llama_respond, inputs=[strategy3, task, task_linguistic_entities, task_prompt, llama_S3_chatbot], 
                       outputs=[task, task_prompt, llama_S3_chatbot])
             
             # Event Handler for GPT 3.5 Chatbot, user must submit api key before submitting the prompt
             # Will activate after getting API key
             # task_apikey_btn.click(update_api_key, inputs=ling_ents_apikey_input)
-            # task_btn.click(gpt_respond, inputs=[task, task_prompt, gpt_S1_chatbot], 
+            # task_btn.click(gpt_strategies_respond, inputs=[strategy1, task, task_linguistic_entities, gpt_S1_chatbot], 
             #                     outputs=[task, task_prompt, gpt_S1_chatbot])
-            # task_btn.click(gpt_respond, inputs=[task, task_prompt, gpt_S2_chatbot], 
+            # task_btn.click(gpt_strategies_respond, inputs=[strategy1, task, task_linguistic_entities, gpt_S2_chatbot], 
             #                     outputs=[task, task_prompt, gpt_S2_chatbot])
-            # task_btn.click(gpt_respond, inputs=[task, task_prompt, gpt_S3_chatbot], 
+            # task_btn.click(gpt_strategies_respond, inputs=[strategy1, task, task_linguistic_entities, gpt_S3_chatbot], 
             #                     outputs=[task, task_prompt, gpt_S3_chatbot])