bug with file locations fixed

app.py

@@ -1,579 +1,25 @@
 import streamlit as st
-import torch
-from tqdm import tqdm
-from peft import PeftModel, PeftConfig
-from transformers import AutoModelForSeq2SeqLM, AutoModelForCausalLM
-from transformers import AutoTokenizer
-import numpy as np
-import time
-import string
 
-# JS
-import nltk
-nltk.download('wordnet')
-from nltk.corpus import wordnet as wn
-from nltk.tokenize import word_tokenize
-
-@st.cache_resource
-def get_models(llama=False):
-  st.write('Loading the model...')
-  # config = PeftConfig.from_pretrained("NursNurs/T5ForReverseDictionary")
-  # model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large")
-  # model = PeftModel.from_pretrained(model, "NursNurs/T5ForReverseDictionary")
-
-  config = PeftConfig.from_pretrained("YouNameIt/T5ForReverseDictionary_prefix_tuned")
-  model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large")
-  model = PeftModel.from_pretrained(model, "YouNameIt/T5ForReverseDictionary_prefix_tuned")
-
-  tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large")
-
-  # JS
-  if llama:
-    model_name = 'meta-llama/Llama-2-7b-chat-hf'
-    access_token = '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'
-    llama_tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=access_token, use_fast=True)#, use_fast=True)
-    llama_model = AutoModelForCausalLM.from_pretrained(model_name, use_auth_token=access_token, device_map={'':0})#, load_in_4bit=True)
-    st.write("The assistant is loaded and ready to use!")
-    return model, tokenizer, llama_model, llama_tokenizer 
-  
-  else:
-    st.write("_The assistant is loaded and ready to use! :tada:_")
-    return model, tokenizer
-
-model, tokenizer = get_models()
-
-def remove_punctuation(word):
-    # Create a translation table that maps all punctuation characters to None
-    translator = str.maketrans('', '', string.punctuation)
-    
-    # Use the translate method to remove punctuation from the word
-    word_without_punctuation = word.translate(translator)
-    
-    return word_without_punctuation
-
-def return_top_k(sentence, k=10, word=None, rels=False):
-
-  if sentence[-1] != ".":
-    sentence = sentence + "."
-
-  if rels:
-    inputs = [f"Description : It is related to '{word}' but not '{word}'. Word : "]
-  else:
-    inputs = [f"Description : {sentence} Word : "]
-
-  inputs = tokenizer(
-      inputs,
-      padding=True, truncation=True,
-      return_tensors="pt",
-  )
-  device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-  model.to(device)
-
-  with torch.no_grad():
-    inputs = {k: v.to(device) for k, v in inputs.items()}
-    output_sequences = model.generate(input_ids=inputs["input_ids"], max_new_tokens=10, num_beams=k+5, num_return_sequences=k+5, #max_length=3,
-                                              top_p = 50, output_scores=True, return_dict_in_generate=True) #repetition_penalty=10000.0
-
-    logits = output_sequences['sequences_scores'].clone().detach()
-    decoded_probabilities = torch.softmax(logits, dim=0)
-
-
-    #all word predictions
-    predictions = [tokenizer.decode(tokens, skip_special_tokens=True) for tokens in output_sequences['sequences']]
-    probabilities = [round(float(prob), 2) for prob in decoded_probabilities]
-
-    stripped_sent = [remove_punctuation(word.lower()) for word in sentence.split()]
-    for pred in predictions:
-      if (len(pred) < 2) | (pred in stripped_sent):
-        predictions.pop(predictions.index(pred))  
-     
-  return predictions[:10] 
-
-# JS 
-def get_related_words(word, num=5):
-  model.eval()
-  with torch.no_grad():
-      sentence = [f"Descripton : It is related to {word} but not {word}. Word : "]
-      #inputs = ["Description: It is something to cut stuff with. Word: "]
-      print(sentence)
-      inputs = tokenizer(sentence, padding=True, truncation=True, return_tensors="pt",)
-
-      device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-      model.to(device)
-
-      batch = {k: v.to(device) for k, v in inputs.items()}
-      beam_outputs = model.generate(
-          input_ids=batch['input_ids'], max_new_tokens=10, num_beams=num+2, num_return_sequences=num+2, early_stopping=True
-      )
-      
-      #beam_preds = [tokenizer.decode(beam_output.detach().cpu().numpy(), skip_special_tokens=True) for beam_output in beam_outputs if ]
-      beam_preds = []
-      for beam_output in beam_outputs:
-          prediction = tokenizer.decode(beam_output.detach().cpu().numpy(), skip_special_tokens=True).strip()
-          if prediction not in " ".join(sentence):
-            beam_preds.append(prediction)
-      
-      return ", ".join(beam_preds[:num])
-
-#if 'messages' not in st.session_state:
-
-def get_text():
-  input_text = st.chat_input()
-  return input_text
-
-def write_bot(input, remember=True, blink=True):
-    with st.chat_message('assistant'):
-      message_placeholder = st.empty()
-      full_response = input
-      if blink == True:
-        response = ''
-        for chunk in full_response.split():
-          response += chunk + " "
-          time.sleep(0.05)
-          # Add a blinking cursor to simulate typing
-          message_placeholder.markdown(response + "▌") 
-        time.sleep(0.5)
-      message_placeholder.markdown(full_response)
-    if remember == True:
-      st.session_state.messages.append({'role': 'assistant', 'content': full_response})
-    
-def ask_if_helped():
-  y = st.button('Yes!', key=60)
-  n = st.button('No...', key=61)
-  new = st.button('I have a new word', key=62)
-  if y:
-    write_bot("I am happy to help!")
-    again = st.button('Play again')
-    if again:
-      write_bot("Please describe your word!")
-    st.session_state.is_helpful['ask'] = False
-  elif n:
-    st.session_state.actions.append('cue')
-    st.session_state.is_helpful['ask'] = False
-    #cue_generation()
-  elif new:
-    write_bot("Please describe your word!")
-    st.session_state.is_helpful['ask'] = False
-
-## removed: if st.session_state.actions[-1] == "result":
-
-# JS
-def get_related_words_llama(relation, target, device, num=5):
-    prompt = f"Provide {num} {relation}s for the word '{target}'. Your answer consists of these {num} words only. Do not include the word '{target}' itself in your answer"
-
-    inputs = tokenizer([prompt], return_tensors='pt').to(device)
-    output = model.generate(
-        **inputs, max_new_tokens=40, temperature=.75, early_stopping=True, 
-        )
-    chatbot_response = tokenizer.decode(output[:, inputs['input_ids'].shape[-1]:][0], skip_special_tokens=True).strip()
-
-    postproc = [word for word in word_tokenize(chatbot_response) if len(word)>=3]
-
-    return postproc[-num:] if len(postproc)>=num else postproc
-
-
-def postproc_wn(related_words, syns=False):
-    if syns:
-        related_words = [word.split('.')[0] if word[0] != "." else word.split('.')[1] for word in related_words]
-    else:
-        related_words = [word.name().split('.')[0] if word.name()[0] != "." else word.name().split('.')[1] for word in related_words]
-    related_words = [word.replace("_", " ") for word in related_words]
-
-    return related_words
-
-# JS
-def get_available_cues(target):
-    wn_nouns = [word.name() for word in wn.all_synsets(pos='n')]
-    wn_nouns = [word.split('.')[0] if word[0] != "." else word.split('.')[1] for word in wn_nouns]
-
-    if target in wn_nouns:
-      available_cues = {}
-      synset_target = wn.synsets(target, pos=wn.NOUN)[0]
-
-      #if wn.synonyms(target)[0]:
-       #   available_cues['Synonyms'] = postproc_wn(wn.synonyms(target)[0], syns=True)
-      
-      #if synset_target.hypernyms():
-       #   available_cues['Hypernyms'] = postproc_wn(synset_target.hypernyms())
-
-
-      #if synset_target.hyponyms():
-        #  available_cues['Hyponyms'] = postproc_wn(synset_target.hyponyms())
-
-      if synset_target.examples():
-          examples = []
-          
-          for example in synset_target.examples():
-              examples.append(example.replace(target, "..."))
-                  
-          available_cues['Examples'] = examples
-
-      return available_cues
-
-    else:
-      return None 
-
-# JS: moved the cue generation further down
-#def cue_generation():
- # if st.session_state.actions[-1] == 'cue':
-
-if 'messages' not in st.session_state:
-  st.session_state.messages = []
-  
-if 'results' not in st.session_state:
-  st.session_state.results = {'results': False, 'results_print': False}
-  
-if 'actions' not in st.session_state:
-  st.session_state.actions = [""]
-  
-if 'counters' not in st.session_state:
-  st.session_state.counters = {"letter_count": 0, "word_count": 0}
-  
-if 'is_helpful' not in st.session_state:
-  st.session_state.is_helpful = {'ask':False}
-  
-if 'descriptions' not in st.session_state:
-  st.session_state.descriptions = []
-  
-st.title("You name it! 🗣")
-
-# JS: would remove Simon by some neutral avatar
-with st.chat_message('user'):
-  st.write("Hey assistant!")
-  
-bot = st.chat_message('assistant')
-bot.write("Hello human! Wanna practice naming some words?")
-
-#for showing history of messages
-for message in st.session_state.messages:
-  if message['role'] == 'user':
-    with st.chat_message(message['role']):
-      st.markdown(message['content'])
-  else:
-    with st.chat_message(message['role']):
-      st.markdown(message['content'])
-  
-#display user message in chat message container
-prompt = get_text() 
-if prompt:
-  #JS: would replace Simon by some neutral character 
-  with st.chat_message('user'):
-    st.markdown(prompt)
-  #add to history
-  st.session_state.messages.append({'role': 'user', 'content': prompt})
-  #TODO: replace it with zero-shot classifier
-  yes = ['yes', 'again', 'Yes', 'sure', 'new word', 'yes!', 'yep', 'yeah']
-  if prompt in yes:
-    write_bot("Please describe your word!")
-  elif prompt == 'It is similar to the best place on earth':
-    write_bot("Great! Let me think what it could be...")
-    time.sleep(3)
-    write_bot("Do you mean Saarland?")
-  #if previously we asked to give a prompt
-  elif (st.session_state.messages[-2]['content'] == "Please describe your word!") & (st.session_state.messages[-1]['content'] != "no"):
-    write_bot("Great! Let me think what it could be...")
-    st.session_state.descriptions.append(prompt)
-    st.session_state.results['results'] = return_top_k(st.session_state.descriptions[-1])
-    st.session_state.results['results_print'] = dict(zip(range(1, 11), st.session_state.results['results']))
-    write_bot("I think I have some ideas. Do you want to see my guesses or do you want a cue?")
-    st.session_state.actions.append("result")
-
-if st.session_state.actions[-1] == "result":
-  col1, col2, col3, col4, col5 = st.columns(5)
-  with col1:
-    a1 = st.button('Results', key=10)
-  with col2:
-    a2 = st.button('Cue', key=11)
-  if a1:
-    write_bot("Here are my guesses about your word:")
-    st.write(st.session_state.results['results_print'])
-    time.sleep(1)
-    write_bot('Does it help you remember the word?', remember=False)
-    st.session_state.is_helpful['ask'] = True
-  elif a2:
-    #write_bot(f'The first letter is {st.session_state.results["results"][0][0]}.')
-    #time.sleep(1)
-    st.session_state.actions.append('cue')
-    #cue_generation()
-    #write_bot('Does it help you remember the word?', remember=False)
-    #st.session_state.is_helpful['ask'] = True
-    
-if st.session_state.is_helpful['ask']:
-    ask_if_helped()
-
-if st.session_state.actions[-1] == 'cue':
-  guessed = False
-  write_bot('What do you want to see?', remember=False, blink=False)
-
-  while guessed == False:
-    # JS
-    word_count = st.session_state.counters["word_count"]
-    target = st.session_state.results["results"][word_count]
-    
-    col1, col2, col3, col4, col5 = st.columns(5)
-  
-
-    with col1:
-      b1 = st.button("Next letter", key="1")
-    with col2:
-      b2 = st.button("Related words")
-    with col3:
-      b3 = st.button("Next word", key="2")
-    with col4:
-      b4 = st.button("All words", key="3")
-
-    # JS
-    #if get_available_cues(target):
-     # avail_cues = get_available_cues(target)
-      #cues_buttons = {cue_type: st.button(cue_type) for cue_type in avail_cues}
-
-    b5 = st.button("I remembered the word!", key="4", type='primary')
-    b6 = st.button("Exit", key="5", type='primary')
-    new = st.button('Play again', key=64, type='primary')
-
-    if b1:
-      st.session_state.counters["letter_count"] += 1
-      #word_count = st.session_state.counters["word_count"]
-      letter_count = st.session_state.counters["letter_count"]
-      if letter_count < len(target):
-        write_bot(f'The word starts with {st.session_state.results["results"][word_count][:letter_count]}. \n Does this help you remember the word?', remember=False)
-        #ask_if_helped()
-        st.session_state.is_helpful['ask'] = True
-      else:
-        write_bot(f'This is my predicted word: "{target}". Does this match your query?')
-        #ask_if_helped()
-        st.session_state.is_helpful['ask'] = True
-
-    elif b2:
-      rels = return_top_k(st.session_state.descriptions[-1], word=target, rels=True)
-      write_bot(f'Here are words that are related to your word: {", ".join(rels)}. \n Does this help you remember the word?', remember=False)
-      #ask_if_helped()
-      st.session_state.is_helpful['ask'] = True
-
-    elif b3:
-      st.session_state.counters["letter_count"] = 1
-      letter_count = st.session_state.counters["letter_count"]
-      st.session_state.counters["word_count"] += 1
-      word_count = st.session_state.counters["word_count"]
-      #write_bot(f'The next word starts with {st.session_state.results["results"][word_count][:letter_count]}', remember=False)
-      if letter_count < len(target):
-        write_bot(f'The next word starts with {st.session_state.results["results"][word_count][:letter_count]}. \n Does this help you remember the word?', remember=False)
-        #ask_if_helped()
-        st.session_state.is_helpful['ask'] = True
-      else:
-        write_bot(f'This is my predicted word: "{target}". Does this match your query?')
-        #ask_if_helped()
-        st.session_state.is_helpful['ask'] = True
-
-    #elif get_available_cues(target) and "Synonyms" in cues_buttons and cues_buttons['Synonyms']:
-      #write_bot(f'Here are synonyms for the current word: {", ".join(avail_cues["Synonyms"])}', remember=False)
-
-    #elif get_available_cues(target) and "Hypernyms" in cues_buttons and cues_buttons['Hypernyms']:
-      #write_bot(f'Here are hypernyms for the current word: {", ".join(avail_cues["Hypernyms"])}', remember=False)
-
-    #elif get_available_cues(target) and "Hyponyms" in cues_buttons and cues_buttons['Hyponyms']:
-      #write_bot(f'Here are hyponyms for the current word: {", ".join(avail_cues["Hyponyms"])}', remember=False)
-
-    #elif get_available_cues(target) and "Examples" in cues_buttons and cues_buttons['Examples']:   
-      #write_bot(f'Here are example contexts for the current word: {", ".join(avail_cues["Examples"])}', remember=False)
-
-    elif b4:
-      write_bot(f"Here are all my guesses about your word: {st.session_state.results['results_print']}")
-
-    elif b5:
-      write_bot("Yay! I am happy I could be of help!")
-      st.session_state.counters["word_count"] = 0
-      st.session_state.counters["letter_count"] = 0
-      new = st.button('Play again', key=63)
-      if new:
-        write_bot("Please describe your word!")
-      guessed = True
-    
-      break
-    
-    elif b6:
-      write_bot("I am sorry I couldn't help you this time. See you soon!")
-      st.session_state.counters["word_count"] = 0
-      st.session_state.counters["letter_count"] = 0
-    st.session_state.actions.append('cue')
-    
-    if new:
-      write_bot("Please describe your word!")
-      st.session_state.counters["word_count"] = 0
-      st.session_state.counters["letter_count"] = 0
-
-    break
-
-  # elif prompt == 'results':
-  #   st.text("results")
-  #   st.write("results")
-  #   st.session_state.actions.append({'result': True})
-  #   st.write(st.session_state.actions)
-  #     with st.chat_message('user'):
-  #       custom_response = "Results"
-  #       st.markdown(custom_response)
-  #     st.session_state.messages.append({'role': 'user', 'content': custom_response})
-
-  #     with st.chat_message('assistant'):
-  #       message_placeholder = st.empty()
-  #       response = f"Here are my guesses about your word: {result_print}"
-  #       message_placeholder.markdown(response + "|")
-  #     st.session_state.messages.append({'role': 'assistant', 'content': response})
-  #   elif st.button('Cue'):
-  #     response = "Cue"
-  #     with st.chat_message('user'):
-  #       st.markdown(response)
-  #     st.session_state.messages.append({'role': 'user', 'content': response})
-  #     text = f'The first letter is {result[0][0]}.'
-  #     bot.write(text)
-  #     st.session_state.messages.append({'role': 'assistant', 'content': text})
-  #     letter_count = 1
-  #     word_count = 0
-  # elif prompt == 'Results':
-  #   with st.chat_message('assistant'):
-  #       message_placeholder = st.empty()
-  #       response = f"Here are my guesses about your word: {result_print}"
-  #       message_placeholder.markdown(response + "|")
-  #   st.session_state.messages.append({'role': 'assistant', 'content': response})
-
-  # #if you don't wanna practice word naming
-  # else:  
-  #     with st.chat_message('assistant'):
-  #       message_placeholder = st.empty()
-  #       response = "See you next time!"
-  #       message_placeholder.markdown(response + "|")
-  #     st.session_state.messages.append({'role': 'assistant', 'content': response})
-      
-
-  
-      # if st.button('Results'):
-      #   bot.write("Here are my guesses about your word:")
-      #   bot.write(result_print)
-      # elif st.button('Cue'):
-      #   bot.write(f'The first letter is {result[0][0]}.')
-      #   letter_count = 1
-      #   word_count = 0
-      #   answer = st.chat_input('Does it help you remember the word? Type yes or no')
-      #   if answer == "no":
-      #     bot.write("What do you want to see?")
-      #     if st.button('Next letter'):
-      #       letter_count += 1
-      #       bot.write(f'The word starts with {result[word_count][:letter_count]}')
-      #     elif st.button('Next word'):
-      #       letter_count = 1
-      #       bot.write(f'The next word starts with {result[word_count][:letter_count]}')
-      #       word_count += 1
-      #     elif st.button('All words'):
-      #       bot.write("Here are all my guesses about your word:")
-      #       bot.write(result_print)
-      #   bot.write("Does this help you remember your word?")
-      #   answer = st.chat_input('Type yes/no/exit')
-      #   if answer == 'Exit':
-      #     st.write("I am sorry I couldn't help you. See you next time!")
-
-      
-  #write down assistant's responses
-  #response = f'Echo: {prompt}' #echoes prompt
-  # with st.chat_message('assistant'):
-  #   message_placeholder = st.empty()
-  #   full_response = "yeee"
-  #   #here insert the loop with the model answers (for response in...)
-  #   #this to imitate a cursor
-  #   message_placeholder.markdown(full_response + "|")
-    
-  # #add to history
-  # st.session_state.messages.append({'role': 'assistant', 'content': full_response})
-  
-  
-  
-##TODO: a button to delete history
-# if prompt == 'Yes':
-#   bot.write("Great! Please describe the word you have in mind.")
-#   sent = st.chat_input('Description of your word')
-
-
-# # adding the text that will show in the text box as default
-# default_value = "Type the description of the word you have in mind!"
-
-# sent = st.text_area("Text", default_value, height = 50)
-# result = return_top_k(sent)
-# result = ['animal', 'monster', 'creature', 'bird', 'cat', 'human', 'dog', 'spider', 'alien', 'meow']
-# result = return_top_k(sent)
-# result_print = dict(zip(range(1, 11), result))
-
-# if st.button('Results'):
-#   st.write("Here are my guesses about your word:")
-#   st.write(result_print)
-# elif st.button('Cue'):
-#   st.write(f'The first letter is {result[0][0]}.')
-#   letter_count = 1
-#   word_count = 0
-#   answer = st.text_area("Text", 'Does it help you remember the word? Type yes or no', height = 50)
-#   if answer == 'No':
-#     while answer == 'No':
-#       option = st.selectbox(
-#       'What do you want to see?',
-#       ('Next letter', 'Next word', 'All words'))
-#       if option == 'Next letter':
-#         letter_count += 1
-#         st.write(f'The word starts with {result[word_count][:letter_count]}')
-#       elif option == 'Next word':
-#         letter_count = 1
-#         st.write(f'The next word starts with {result[word_count][:letter_count]}')
-#         word_count += 1
-#       else:
-#         st.write("Here are all my guesses about your word:")
-#         st.write(result_print)
-#       answer = st.selectbox(
-#         'Does it help you remember the word??',
-#         ('Yes', 'No', 'Exit'))
-#       if answer == 'Exit':
-#         st.write("I am sorry I couldn't help you. See you next time!")
-#         break
-#   else:
-#      st.write("I am happy I could be of help!")
-# else:
-#   st.write('Do you want to see my guesses or do you want a cue?')
-
-
-#2
-
-# option = st.selectbox(
-#     'Do you want to see my guesses or do you want a cue?',
-#     ('Results', 'Cue'))
-
-# st.write('You selected:', option)
-
-# if option == 'Results':
-#   st.write("Here are my guesses about your word:")
-#   st.write(result_print)
-# elif option == 'Cue':
-#   st.write(f'The first letter is {result[0][0]}.')
-#   letter_count = 1
-#   word_count = 0
-#   answer = st.selectbox(
-#     'Does it help you remember the word??',
-#     ('Yes', 'No'))
-#   if answer == 'No':
-#     while answer == 'No':
-#       option = st.selectbox(
-#       'What do you want to see?',
-#       ('Next letter', 'Next word', 'All words'))
-#       if option == 'Next letter':
-#         letter_count += 1
-#         st.write(f'The word starts with {result[word_count][:letter_count]}')
-#       elif option == 'Next word':
-#         letter_count = 1
-#         st.write(f'The next word starts with {result[word_count][:letter_count]}')
-#         word_count += 1
-#       else:
-#         st.write("Here are all my guesses about your word:")
-#         st.write(result_print)
-#       answer = st.selectbox(
-#         'Does it help you remember the word??',
-#         ('Yes', 'No', 'Exit'))
-#       if answer == 'Exit':
-#         st.write("I am sorry I couldn't help you. See you next time!")
-#         break
-#   else:
-#     st.write("I am happy I could be of help!")
+st.set_page_config(
+    page_title="You Name It!",
+    page_icon="👋",
+)
+
+st.write("# Welcome to YouNameIt chatbot! 👋")
+
+st.sidebar.success("Select a chatbot mode above.")
+
+st.markdown(
+    """
+    YouNameIt is a project helping people with aphasia practice their word retrieval skill and assisting them to remember words on a daily basis.
+    **👈 Select a chatbot mode from the sidebar** to test our app!
+    ### What new features are planned?
+    - Adaptation to German language and more;
+    - Speech-to-text suppport;
+    - Android & IOS mobile apps.
+    ### For any suggestions or ideas please contact us.
+    - Julian []()
+    - Nursulu []()
+"""
+)
+ 

pages/App.py

@@ -1,25 +0,0 @@
-import streamlit as st
-
-st.set_page_config(
-    page_title="You Name It!",
-    page_icon="👋",
-)
-
-st.write("# Welcome to YouNameIt chatbot! 👋")
-
-st.sidebar.success("Select a chatbot mode above.")
-
-st.markdown(
-    """
-    YouNameIt is a project helping people with aphasia practice their word retrieval skill and assisting them to remember words on a daily basis.
-    **👈 Select a chatbot mode from the sidebar** to test our app!
-    ### What new features are planned?
-    - Adaptation to German language and more;
-    - Speech-to-text suppport;
-    - Android & IOS mobile apps.
-    ### For any suggestions or ideas please contact us.
-    - Julian []()
-    - Nursulu []()
-"""
-)
-