Update app.py

app.py

@@ -107,10 +107,28 @@ def FrontRevSentChunk (Chunkmode, Translate, Text, langdest):
     FinalOutput += "\n" + translated.text
   return FinalOutput
 
+# Define a function to filter out non-verb, noun, or adjective words
+def filter_words(words):
+    # Use NLTK to tag each word with its part of speech
+    tagged_words = nltk.pos_tag(words)
+
+    # Define a set of parts of speech to keep (verbs, nouns, adjectives)
+    keep_pos = {'VB', 'VBD', 'VBG', 'VBN', 'VBP', 'VBZ', 'NN', 'NNS', 'NNP', 'NNPS', 'JJ', 'JJR', 'JJS'}
+
+    # Filter the list to only include words with the desired parts of speech
+    filtered_words = [word for word, pos in tagged_words if pos in keep_pos]
+
+    return filtered_words
+
+# Call the function to get the filtered list of words
+filtered_words = filter_words(words)
+
+print(filtered_words)
+
 def SepHypandSynExpansion(text):
   # Tokenize the text
   tokens = nltk.word_tokenize(text)
-  NoHits = "Words to pay special attention to: "
+  NoHits = ""
   FinalOutput = ""
 
   # Find synonyms and hypernyms of each word in the text
@@ -121,11 +139,13 @@ def SepHypandSynExpansion(text):
           synonyms += synset.lemma_names()
           hypernyms += [hypernym.name() for hypernym in synset.hypernyms()]
       if not synonyms and not hypernyms:
-          NoHits += token + " "  # f"{token} | "
-          NoHits = set(NoHits)
+          NoHits += f"{token} | "
       else:
-          FinalOutput += "\n" f"{token}: hypernyms={hypernyms}, synonyms={synonyms}"
-  return NoHits, FinalOutput  
+          FinalOutput += "\n" f"{token}: hypernyms={hypernyms}, synonyms={synonyms} \n"
+  NoHits = set(NoHits.split(" | "))  
+  NoHits = filter_words(NoHits)
+  NoHits = "Words to pay special attention to: \n" + str(NoHits)
+  return NoHits, FinalOutput
 
 
 def WikiSearch(term):