Added new ideaMatch exercise type.

helper/constants.py

@@ -18,6 +18,7 @@ GEN_FIELDS = ['topic']
 GEN_TEXT_FIELDS = ['title']
 LISTENING_GEN_FIELDS = ['transcript', 'exercise']
 READING_EXERCISE_TYPES = ['fillBlanks', 'writeBlanks', 'trueFalse', 'paragraphMatch']
+READING_3_EXERCISE_TYPES = ['fillBlanks', 'writeBlanks', 'trueFalse', 'paragraphMatch', 'ideaMatch']
 LISTENING_EXERCISE_TYPES = ['multipleChoice', 'writeBlanksQuestions', 'writeBlanksFill', 'writeBlanksForm']
 LISTENING_1_EXERCISE_TYPES = ['multipleChoice', 'writeBlanksQuestions', 'writeBlanksFill', 'writeBlanksFill',
                               'writeBlanksForm', 'writeBlanksForm', 'writeBlanksForm', 'writeBlanksForm']

helper/exercises.py

@@ -7,7 +7,6 @@ import uuid
 import nltk
 from wonderwords import RandomWord
 
-from helper.api_messages import QuestionType
 from helper.constants import *
 from helper.firebase_helper import get_all
 from helper.openai_interface import make_openai_call, count_total_tokens
@@ -243,6 +242,7 @@ def build_write_blanks_solutions_listening(words: [], start_id):
         )
     return solutions
 
+
 def get_perfect_answer(question: str, size: int):
     messages = [
         {
@@ -291,7 +291,7 @@ def generate_reading_passage_1_text(topic: str):
         },
         {
             "role": "system",
-            "content": ('The generated text should be fairly easy to understand.')
+            "content": ('The generated text should be fairly easy to understand and have multiple paragraphs.')
         },
     ]
     token_count = count_total_tokens(messages)
@@ -323,12 +323,13 @@ def generate_reading_passage_2_text(topic: str):
         },
         {
             "role": "system",
-            "content": ('The generated text should be fairly hard to understand.')
+            "content": ('The generated text should be fairly hard to understand and have multiple paragraphs.')
         },
     ]
     token_count = count_total_tokens(messages)
     return make_openai_call(GPT_4_O, messages, token_count, GEN_TEXT_FIELDS, GEN_QUESTION_TEMPERATURE)
 
+
 def generate_reading_passage_3_text(topic: str):
     messages = [
         {
@@ -355,7 +356,8 @@ def generate_reading_passage_3_text(topic: str):
         {
             "role": "system",
             "content": ('The generated text should be very hard to understand and include different points, theories, '
-                        'subtle differences of opinions from people over the specified topic .')
+                        'subtle differences of opinions from people, correctly sourced to the person who said it, '
+                        'over the specified topic and have multiple paragraphs.')
         },
     ]
     token_count = count_total_tokens(messages)
@@ -547,6 +549,10 @@ def generate_reading_exercises(passage: str, req_exercises: list, number_of_exer
             question = gen_paragraph_match_exercise(passage, number_of_exercises, start_id)
             exercises.append(question)
             print("Added paragraph match: " + str(question))
+        elif req_exercise == "ideaMatch":
+            question = gen_idea_match_exercise(passage, number_of_exercises, start_id)
+            exercises.append(question)
+            print("Added idea match: " + str(question))
 
         start_id = start_id + number_of_exercises
 
@@ -693,7 +699,8 @@ def gen_summary_fill_blanks_exercise(text: str, quantity: int, start_id, difficu
         {
             "role": "user",
             "content": ('Select ' + str(quantity) + ' ' + difficulty + ' difficulty words, it must be words and not '
-                                                                       'expressions, from this:\n' + response["summary"])
+                                                                       'expressions, from this:\n' + response[
+                            "summary"])
 
         }
     ]
@@ -732,7 +739,8 @@ def gen_true_false_not_given_exercise(text: str, quantity: int, start_id, diffic
         {
             "role": "user",
             "content": (
-                    'Generate ' + str(quantity) + ' ' + difficulty + ' difficulty statements based on the provided text. '
+                    'Generate ' + str(
+                quantity) + ' ' + difficulty + ' difficulty statements based on the provided text. '
                                                'Ensure that your statements accurately represent '
                                                'information or inferences from the text, and '
                                                'provide a variety of responses, including, at '
@@ -802,7 +810,8 @@ def gen_paragraph_match_exercise(text: str, quantity: int, start_id):
         {
             "role": "user",
             "content": (
-                    'For every paragraph of the list generate a minimum 5 word heading for it. The paragraphs are these: ' + str(paragraphs))
+                    'For every paragraph of the list generate a minimum 5 word heading for it. The paragraphs are these: ' + str(
+                paragraphs))
 
         }
     ]
@@ -838,6 +847,83 @@ def gen_paragraph_match_exercise(text: str, quantity: int, start_id):
     }
 
 
+def gen_idea_match_exercise(text: str, quantity: int, start_id):
+    messages = [
+        {
+            "role": "system",
+            "content": (
+                'You are a helpful assistant designed to output JSON on this format: '
+                '{"ideas": [ '
+                '{"idea": "some idea or opinion", "from": "person, institution whose idea or opinion this is"}, '
+                '{"idea": "some other idea or opinion", "from": "person, institution whose idea or opinion this is"}'
+                ']}')
+        },
+        {
+            "role": "user",
+            "content": (
+                    'From the text extract ' + str(quantity) + ' ideas, theories, opinions and who they are from. The text: ' + str(text))
+
+        }
+    ]
+    token_count = count_total_tokens(messages)
+
+    ideas = make_openai_call(GPT_4_O, messages, token_count, ["ideas"], GEN_QUESTION_TEMPERATURE)["ideas"]
+    # options = [
+    #             {
+    #                 "id": "A",
+    #                 "sentence": "Cultural appropriation is a term that has gained significant traction in contemporary"
+    #             },
+    #             {
+    #                 "id": "B",
+    #                 "sentence": "Historically, cultural appropriation can be traced back to the era of colonialism"
+    #             }
+    #         ]
+
+    # sentences = [
+    #     {
+    #         "id": 21,
+    #         "sentence": "Concluding Thoughts on Cultural Appropriation",
+    #         "solution": "I"
+    #     },
+    #     {
+    #         "id": 22,
+    #         "sentence": "Understanding the Concept of Cultural Appropriation",
+    #         "solution": "A"
+    #     }
+    # ]
+    return {
+        "id": str(uuid.uuid4()),
+        "allowRepetition": False,
+        "options": build_options(ideas),
+        "prompt": "Choose the correct author for the ideas/opinions from the list of authors below.",
+        "sentences": build_sentences(ideas, start_id),
+        "type": "matchSentences"
+    }
+
+def build_options(ideas):
+    options = []
+    letters = iter(string.ascii_uppercase)
+    for idea in ideas:
+        options.append({
+            "id": next(letters),
+            "sentence": idea["from"]
+        })
+    return options
+
+def build_sentences(ideas, start_id):
+    sentences = []
+    letters = iter(string.ascii_uppercase)
+    for idea in ideas:
+        sentences.append({
+            "solution": next(letters),
+            "sentence": idea["idea"]
+        })
+
+    random.shuffle(sentences)
+    for i, sentence in enumerate(sentences, start=start_id):
+        sentence["id"] = i
+    return sentences
+
 def assign_letters_to_paragraphs(paragraphs):
     result = []
     letters = iter(string.ascii_uppercase)
@@ -861,7 +947,8 @@ def gen_multiple_choice_exercise_listening_conversation(text: str, quantity: int
         {
             "role": "user",
             "content": (
-                    'Generate ' + str(quantity) + ' ' + difficulty + ' difficulty multiple choice questions of ' + str(n_options) + ' options '
+                    'Generate ' + str(quantity) + ' ' + difficulty + ' difficulty multiple choice questions of ' + str(
+                n_options) + ' options '
                              'of for this conversation:\n"' + text + '"')
 
         }
@@ -892,7 +979,8 @@ def gen_multiple_choice_exercise_listening_monologue(text: str, quantity: int, s
             "role": "user",
             "content": (
                     'Generate ' + str(
-                quantity) + ' ' + difficulty + ' difficulty multiple choice questions of ' + str(n_options) + ' options '
+                quantity) + ' ' + difficulty + ' difficulty multiple choice questions of ' + str(
+                n_options) + ' options '
                              'of for this monologue:\n"' + text + '"')
 
         }
@@ -993,7 +1081,6 @@ def gen_write_blanks_notes_exercise_listening_conversation(text: str, quantity:
     questions = make_openai_call(GPT_4_O, messages, token_count, ["notes"],
                                  GEN_QUESTION_TEMPERATURE)["notes"][:quantity]
 
-
     formatted_phrases = "\n".join([f"{i + 1}. {phrase}" for i, phrase in enumerate(questions)])
 
     word_messages = [
@@ -1204,6 +1291,7 @@ def replace_exercise_if_exists(all_exams, current_exercise, current_exam, seen_k
             return replace_exercise_if_exists(all_exams, generate_single_mc_level_question(), current_exam, seen_keys)
     return current_exercise, seen_keys
 
+
 def replace_exercise_if_exists_utas(all_exams, current_exercise, current_exam, seen_keys):
     # Extracting relevant fields for comparison
     key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options'])))
@@ -1220,7 +1308,8 @@ def replace_exercise_if_exists_utas(all_exams, current_exercise, current_exam, s
                     current_exercise["options"])
                 for exercise in exam.get("questions", [])
         ):
-            return replace_exercise_if_exists_utas(all_exams, generate_single_mc_level_question(), current_exam, seen_keys)
+            return replace_exercise_if_exists_utas(all_exams, generate_single_mc_level_question(), current_exam,
+                                                   seen_keys)
     return current_exercise, seen_keys
 
 
@@ -1331,7 +1420,8 @@ def gen_multiple_choice_underlined_utas(quantity: int, start_id: int):
         ]
     }
 
-    gen_multiple_choice_for_text = 'Generate ' + str(quantity) + (' multiple choice questions of 4 options for an english '
+    gen_multiple_choice_for_text = 'Generate ' + str(quantity) + (
+        ' multiple choice 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 '
@@ -1368,6 +1458,7 @@ def gen_multiple_choice_underlined_utas(quantity: int, start_id: int):
     else:
         return fix_exercise_ids(question, start_id)["questions"]
 
+
 def gen_blank_space_text_utas(quantity: int, start_id: int, size: int, topic=random.choice(mti_topics)):
     json_format = {
         "question": {
@@ -1406,7 +1497,8 @@ def gen_blank_space_text_utas(quantity: int, start_id: int, size: int, topic=ran
         {
             "role": "user",
             "content": (
-                'From the generated text choose ' + str(quantity) + ' words (cannot be sequential words) to replace '
+                    'From the generated text choose ' + str(
+                quantity) + ' words (cannot be sequential words) to replace '
                             'once with {{id}} where id starts on ' + str(start_id) + ' and is '
                                                                                      'incremented for each word. The ids must be ordered throughout the text and the words must be '
                                                                                      'replaced only once. Put the removed words and respective ids on the words array of the json in the correct order.')
@@ -1420,8 +1512,8 @@ def gen_blank_space_text_utas(quantity: int, start_id: int, size: int, topic=ran
 
     return question["question"]
 
-def gen_reading_passage_utas(start_id, sa_quantity: int, mc_quantity: int, topic=random.choice(mti_topics)):
 
+def gen_reading_passage_utas(start_id, sa_quantity: int, mc_quantity: int, topic=random.choice(mti_topics)):
     passage = generate_reading_passage_1_text(topic)
     short_answer = gen_short_answer_utas(passage["text"], start_id, sa_quantity)
     mc_exercises = gen_text_multiple_choice_utas(passage["text"], start_id + sa_quantity, mc_quantity)
@@ -1436,6 +1528,7 @@ def gen_reading_passage_utas(start_id, sa_quantity: int, mc_quantity: int, topic
         }
     }
 
+
 def gen_short_answer_utas(text: str, start_id: int, sa_quantity: int):
     json_format = {"questions": [{"id": 1, "question": "question", "possible_answers": ["answer_1", "answer_2"]}]}
 
@@ -1460,6 +1553,8 @@ def gen_short_answer_utas(text: str, start_id: int, sa_quantity: int):
     return make_openai_call(GPT_4_O, messages, token_count,
                             ["questions"],
                             GEN_QUESTION_TEMPERATURE)["questions"]
+
+
 def gen_text_multiple_choice_utas(text: str, start_id: int, mc_quantity: int):
     json_format = {
         "questions": [
@@ -1497,7 +1592,8 @@ def gen_text_multiple_choice_utas(text: str, start_id: int, mc_quantity: int):
         },
         {
             "role": "user",
-            "content": 'Generate ' + str(mc_quantity) + ' multiple choice questions of 4 options for this text:\n' + text
+            "content": 'Generate ' + str(
+                mc_quantity) + ' multiple choice questions of 4 options for this text:\n' + text
         },
         {
             "role": "user",