All tested except grading speaking.

helper/openai_interface.py

@@ -1,5 +1,6 @@
 import json
 import os
+import re
 
 from openai import OpenAI
 from dotenv import load_dotenv
@@ -63,10 +64,15 @@ def make_openai_call(model, messages, token_count, fields_to_check, temperature)
         response_format={"type": "json_object"}
     )
     result = result.choices[0].message.content
-    if has_blacklisted_words(result) and try_count < TRY_LIMIT:
+
+    found_blacklisted_word = get_found_blacklisted_words(result)
+
+    if found_blacklisted_word is not None and try_count < TRY_LIMIT:
+        from app import app
+        app.logger.warning("Result contains blacklisted words: " + str(found_blacklisted_word))
         try_count = try_count + 1
         return make_openai_call(model, messages, token_count, fields_to_check, temperature)
-    elif has_blacklisted_words(result) and try_count >= TRY_LIMIT:
+    elif found_blacklisted_word is not None and try_count >= TRY_LIMIT:
         return ""
 
     if fields_to_check is None:
@@ -83,11 +89,6 @@ def make_openai_call(model, messages, token_count, fields_to_check, temperature)
         return json.loads(result)
 
 
-def make_openai_instruct_call(model, message: str, token_count, fields_to_check, temperature):
-    global try_count
-    return ""
-
-
 # GRADING SUMMARY
 def calculate_grading_summary(body):
     extracted_sections = extract_existing_sections_from_body(body, section_keys)
@@ -210,6 +211,12 @@ def has_blacklisted_words(text: str):
     text_lower = text.lower()
     return any(word in text_lower for word in BLACKLISTED_WORDS)
 
+def get_found_blacklisted_words(text: str):
+    text_lower = text.lower()
+    for word in BLACKLISTED_WORDS:
+        if re.search(r'\b' + re.escape(word) + r'\b', text_lower):
+            return word
+    return None
 
 def remove_special_characters_from_beginning(string):
     cleaned_string = string.lstrip('\n')