ENCOA-311

ielts_be/services/impl/exam/level/exercises/fill_blanks.py

@@ -11,12 +11,10 @@ class FillBlanks:
 
 
     async def gen_fill_blanks(
-            self, start_id: int, quantity: int, size: int = 300, topic=None
+            self, start_id: int, quantity: int, difficulty: str, size: int = 300, topic=None
     ):
         if not topic:
             topic = random.choice(EducationalContent.MTI_TOPICS)
-        print(quantity)
-        print(start_id)
         messages = [
             {
                 "role": "system",
@@ -34,8 +32,15 @@ class FillBlanks:
                     'JSON object containing: the modified text, a solutions array with each word\'s correct '
                     'letter (A-D), and a words array containing each id with four options where one is '
                     'the original word (matching the solution) and three are plausible but incorrect '
-                    'alternatives that maintain grammatical consistency. '
-                    'You cannot use repeated words!' #TODO: Solve this after
+                    f'alternatives that maintain grammatical consistency and {difficulty} CEFR level complexity. '
+                    'You cannot use repeated words!'
+                    # TODO: Solve this after -> forgot about this TODO just saw now in
+                    #   1/11/25 what I meant by this is gpt still sometimes returns repeated
+                    #   words even with explicit instructions to not do so, this is a general problem
+                    #   for all exercises, for more robust validation use self._llm.pydantic_prediction
+                    #   or implement a method that calls a mapper, catches validation error messages
+                    #   from that mapper and asks gpt to retry if creating a pydantic model for each
+                    #   operation proves to be unsustainable
                 )
             }
         ]

ielts_be/services/impl/exam/level/exercises/multiple_choice.py

@@ -10,16 +10,16 @@ class MultipleChoice:
         self._mc_variants = mc_variants
 
     async def gen_multiple_choice(
-            self, mc_variant: str, quantity: int, start_id: int = 1
+            self, mc_variant: str, quantity: int, difficulty: str, start_id: int = 1
     ):
         mc_template = self._mc_variants[mc_variant]
         blank_mod = " blank space " if mc_variant == "blank_space" else " "
 
         gen_multiple_choice_for_text: str = (
-            'Generate {quantity} multiple choice{blank}questions of 4 options for an english level exam, some easy '
-            'questions, some intermediate questions and some advanced questions. Ensure that the questions cover '
-            'a range of topics such as verb tense, subject-verb agreement, pronoun usage, sentence structure, and '
-            'punctuation. Make sure every question only has 1 correct answer.'
+            'Generate {quantity} multiple choice{blank}questions of 4 options for an english level exam of {difficulty} '
+            'CEFR level, some easy questions, some intermediate questions and some advanced questions. Ensure that '
+            'the questions cover a range of topics such as verb tense, subject-verb agreement, pronoun usage, sentence '
+            'structure, and punctuation. Make sure every question only has 1 correct answer.'
         )
 
         messages = [
@@ -31,7 +31,7 @@ class MultipleChoice:
             },
             {
                 "role": "user",
-                "content": gen_multiple_choice_for_text.format(quantity=str(quantity), blank=blank_mod)
+                "content": gen_multiple_choice_for_text.format(quantity=str(quantity), blank=blank_mod, difficulty=difficulty)
             }
         ]
 

ielts_be/services/impl/exam/level/exercises/passage_utas.py

@@ -13,11 +13,11 @@ class PassageUtas:
         self._mc_variants = mc_variants
 
     async def gen_reading_passage_utas(
-            self, start_id, mc_quantity: int, topic: Optional[str], word_size: Optional[int] # sa_quantity: int,
+            self, start_id, mc_quantity: int, difficulty: str, topic: Optional[str] = None, word_size: Optional[int] = None# sa_quantity: int,
     ):
 
         passage = await self._reading_service.generate_reading_passage(1, topic, word_size)
-        mc_exercises = await self._gen_text_multiple_choice_utas(passage["text"], start_id, mc_quantity)
+        mc_exercises = await self._gen_text_multiple_choice_utas(passage["text"], start_id, mc_quantity, difficulty)
         mc_exercises["type"] = "multipleChoice"
         """
             exercises: {
@@ -61,7 +61,7 @@ class PassageUtas:
 
         return question["questions"]
 
-    async def _gen_text_multiple_choice_utas(self, text: str, start_id: int, mc_quantity: int):
+    async def _gen_text_multiple_choice_utas(self, text: str, start_id: int, mc_quantity: int, difficulty: str):
         json_template = self._mc_variants["text_mc_utas"]
 
         messages = [
@@ -71,7 +71,9 @@ class PassageUtas:
             },
             {
                 "role": "user",
-                "content": f'Generate {mc_quantity} multiple choice questions of 4 options for this text:\n{text}'
+                "content": (
+                    f'Generate {mc_quantity} multiple choice questions of 4 options, {difficulty} CEFR '
+                    f'level difficulty, for this text:\n{text}')
             },
             {
                 "role": "user",