From d68617f33b22015bc5af994fa099a5c340de7ced Mon Sep 17 00:00:00 2001 From: Cristiano Ferreira Date: Thu, 15 Aug 2024 13:58:07 +0100 Subject: [PATCH] Add regular ielts modules to custom level. --- app.py | 506 +++++++++++++++++++++----------------------- helper/exercises.py | 366 +++++++++++++++++++++++++++++--- 2 files changed, 573 insertions(+), 299 deletions(-) diff --git a/app.py b/app.py index b022293..a28fd30 100644 --- a/app.py +++ b/app.py @@ -65,25 +65,7 @@ def get_listening_section_1_question(): req_exercises = request.args.getlist('exercises') difficulty = request.args.get("difficulty", default=random.choice(difficulties)) - if (len(req_exercises) == 0): - req_exercises = random.sample(LISTENING_1_EXERCISE_TYPES, 1) - - number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_1_EXERCISES, len(req_exercises)) - - processed_conversation = generate_listening_1_conversation(topic) - - app.logger.info("Generated conversation: " + str(processed_conversation)) - - start_id = 1 - exercises = generate_listening_conversation_exercises(parse_conversation(processed_conversation), - req_exercises, - number_of_exercises_q, - start_id, difficulty) - return { - "exercises": exercises, - "text": processed_conversation, - "difficulty": difficulty - } + return gen_listening_section_1(topic, difficulty, req_exercises) except Exception as e: return str(e) @@ -98,22 +80,7 @@ def get_listening_section_2_question(): req_exercises = request.args.getlist('exercises') difficulty = request.args.get("difficulty", default=random.choice(difficulties)) - if (len(req_exercises) == 0): - req_exercises = random.sample(LISTENING_2_EXERCISE_TYPES, 2) - - number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_2_EXERCISES, len(req_exercises)) - - monologue = generate_listening_2_monologue(topic) - - app.logger.info("Generated monologue: " + str(monologue)) - start_id = 11 - exercises = generate_listening_monologue_exercises(str(monologue), req_exercises, number_of_exercises_q, - start_id, difficulty) - return { - "exercises": exercises, - "text": monologue, - "difficulty": difficulty - } + return gen_listening_section_2(topic, difficulty, req_exercises) except Exception as e: return str(e) @@ -128,24 +95,7 @@ def get_listening_section_3_question(): req_exercises = request.args.getlist('exercises') difficulty = request.args.get("difficulty", default=random.choice(difficulties)) - if (len(req_exercises) == 0): - req_exercises = random.sample(LISTENING_3_EXERCISE_TYPES, 1) - - number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_3_EXERCISES, len(req_exercises)) - - processed_conversation = generate_listening_3_conversation(topic) - - app.logger.info("Generated conversation: " + str(processed_conversation)) - - start_id = 21 - exercises = generate_listening_conversation_exercises(parse_conversation(processed_conversation), req_exercises, - number_of_exercises_q, - start_id, difficulty) - return { - "exercises": exercises, - "text": processed_conversation, - "difficulty": difficulty - } + return gen_listening_section_3(topic, difficulty, req_exercises) except Exception as e: return str(e) @@ -160,22 +110,7 @@ def get_listening_section_4_question(): req_exercises = request.args.getlist('exercises') difficulty = request.args.get("difficulty", default=random.choice(difficulties)) - if (len(req_exercises) == 0): - req_exercises = random.sample(LISTENING_EXERCISE_TYPES, 2) - - number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_4_EXERCISES, len(req_exercises)) - - monologue = generate_listening_4_monologue(topic) - - app.logger.info("Generated monologue: " + str(monologue)) - start_id = 31 - exercises = generate_listening_monologue_exercises(str(monologue), req_exercises, number_of_exercises_q, - start_id, difficulty) - return { - "exercises": exercises, - "text": monologue, - "difficulty": difficulty - } + return gen_listening_section_4(topic, difficulty, req_exercises) except Exception as e: return str(e) @@ -342,37 +277,7 @@ def get_writing_task_1_general_question(): difficulty = request.args.get("difficulty", default=random.choice(difficulties)) topic = request.args.get("topic", default=random.choice(mti_topics)) try: - messages = [ - { - "role": "system", - "content": ('You are a helpful assistant designed to output JSON on this format: ' - '{"prompt": "prompt content"}') - }, - { - "role": "user", - "content": ('Craft a prompt for an IELTS Writing Task 1 General Training exercise that instructs the ' - 'student to compose a letter. The prompt should present a specific scenario or situation, ' - 'based on the topic of "' + topic + '", requiring the student to provide information, ' - 'advice, or instructions within the letter. ' - 'Make sure that the generated prompt is ' - 'of ' + difficulty + 'difficulty and does not contain ' - 'forbidden subjects in muslim ' - 'countries.') - }, - { - "role": "user", - "content": 'The prompt should end with "In the letter you should" followed by 3 bullet points of what ' - 'the answer should include.' - } - ] - token_count = count_total_tokens(messages) - response = make_openai_call(GPT_3_5_TURBO, messages, token_count, "prompt", - GEN_QUESTION_TEMPERATURE) - return { - "question": add_newline_before_hyphen(response["prompt"].strip()), - "difficulty": difficulty, - "topic": topic - } + return gen_writing_task_1(topic, difficulty) except Exception as e: return str(e) @@ -507,32 +412,7 @@ def get_writing_task_2_general_question(): difficulty = request.args.get("difficulty", default=random.choice(difficulties)) topic = request.args.get("topic", default=random.choice(mti_topics)) try: - messages = [ - { - "role": "system", - "content": ('You are a helpful assistant designed to output JSON on this format: ' - '{"prompt": "prompt content"}') - }, - { - "role": "user", - "content": ( - 'Craft a comprehensive question of ' + difficulty + 'difficulty like the ones for IELTS Writing Task 2 General Training that directs the candidate ' - 'to delve into an in-depth analysis of contrasting perspectives on the topic of "' + topic + '". ' - 'The candidate should be asked to discuss the strengths and weaknesses of both viewpoints.') - }, - { - "role": "user", - "content": 'The question should lead to an answer with either "theories", "complicated information" or ' - 'be "very descriptive" on the topic.' - } - ] - token_count = count_total_tokens(messages) - response = make_openai_call(GPT_4_O, messages, token_count, "prompt", GEN_QUESTION_TEMPERATURE) - return { - "question": response["prompt"].strip(), - "difficulty": difficulty, - "topic": topic - } + return gen_writing_task_2(topic, difficulty) except Exception as e: return str(e) @@ -714,56 +594,8 @@ def get_speaking_task_1_question(): first_topic = request.args.get("first_topic", default=random.choice(mti_topics)) second_topic = request.args.get("second_topic", default=random.choice(mti_topics)) - json_format = { - "first_topic": "topic 1", - "second_topic": "topic 2", - "questions": [ - "Introductory question about the first topic, starting the topic with 'Let's talk about x' and then the " - "question.", - "Follow up question about the first topic", - "Follow up question about the first topic", - "Question about second topic", - "Follow up question about the second topic", - ] - } - try: - messages = [ - { - "role": "system", - "content": ( - 'You are a helpful assistant designed to output JSON on this format: ' + str(json_format)) - }, - { - "role": "user", - "content": ( - 'Craft 5 simple and single questions of easy difficulty for IELTS Speaking Part 1 ' - 'that encourages candidates to delve deeply into ' - 'personal experiences, preferences, or insights on the topic ' - 'of "' + first_topic + '" and the topic of "' + second_topic + '". ' - 'Make sure that the generated ' - 'question' - 'does not contain forbidden ' - 'subjects in' - 'muslim countries.') - }, - { - "role": "user", - "content": 'The questions should lead to the usage of 4 verb tenses (present perfect, present, ' - 'past and future).' - }, - { - "role": "user", - "content": 'They must be 1 single question each and not be double-barreled questions.' - - } - ] - token_count = count_total_tokens(messages) - response = make_openai_call(GPT_4_O, messages, token_count, ["first_topic"], - GEN_QUESTION_TEMPERATURE) - response["type"] = 1 - response["difficulty"] = difficulty - return response + return gen_speaking_part_1(first_topic, second_topic, difficulty) except Exception as e: return str(e) @@ -913,50 +745,8 @@ def get_speaking_task_2_question(): difficulty = request.args.get("difficulty", default=random.choice(difficulties)) topic = request.args.get("topic", default=random.choice(mti_topics)) - json_format = { - "topic": "topic", - "question": "question", - "prompts": [ - "prompt_1", - "prompt_2", - "prompt_3" - ], - "suffix": "And explain why..." - } - try: - messages = [ - { - "role": "system", - "content": 'You are a helpful assistant designed to output JSON on this format: ' + str(json_format) - }, - { - "role": "user", - "content": ( - 'Create a question of medium difficulty for IELTS Speaking Part 2 ' - 'that encourages candidates to narrate a ' - 'personal experience or story related to the topic ' - 'of "' + topic + '". Include 3 prompts that ' - 'guide the candidate to describe ' - 'specific aspects of the experience, ' - 'such as details about the situation, ' - 'their actions, and the reasons it left a ' - 'lasting impression. Make sure that the ' - 'generated question does not contain ' - 'forbidden subjects in muslim countries.') - }, - { - "role": "user", - "content": 'The prompts must not be questions. Also include a suffix like the ones in the IELTS exams ' - 'that start with "And explain why".' - } - ] - token_count = count_total_tokens(messages) - response = make_openai_call(GPT_4_O, messages, token_count, GEN_FIELDS, GEN_QUESTION_TEMPERATURE) - response["type"] = 2 - response["difficulty"] = difficulty - response["topic"] = topic - return response + return gen_speaking_part_2(topic, difficulty) except Exception as e: return str(e) @@ -967,47 +757,8 @@ def get_speaking_task_3_question(): difficulty = request.args.get("difficulty", default=random.choice(difficulties)) topic = request.args.get("topic", default=random.choice(mti_topics)) - json_format = { - "topic": "topic", - "questions": [ - "Introductory question about the topic.", - "Follow up question about the topic", - "Follow up question about the topic", - "Follow up question about the topic", - "Follow up question about the topic" - ] - } try: - messages = [ - { - "role": "system", - "content": ( - 'You are a helpful assistant designed to output JSON on this format: ' + str(json_format)) - }, - { - "role": "user", - "content": ( - 'Formulate a set of 5 single questions of hard difficulty for IELTS Speaking Part 3 that encourage candidates to engage in a ' - 'meaningful discussion on the topic of "' + topic + '". Provide inquiries, ensuring ' - 'they explore various aspects, perspectives, and implications related to the topic.' - 'Make sure that the generated question does not contain forbidden subjects in muslim countries.') - - }, - { - "role": "user", - "content": 'They must be 1 single question each and not be double-barreled questions.' - - } - ] - token_count = count_total_tokens(messages) - response = make_openai_call(GPT_4_O, messages, token_count, GEN_FIELDS, GEN_QUESTION_TEMPERATURE) - # Remove the numbers from the questions only if the string starts with a number - response["questions"] = [re.sub(r"^\d+\.\s*", "", question) if re.match(r"^\d+\.", question) else question for - question in response["questions"]] - response["type"] = 3 - response["difficulty"] = difficulty - response["topic"] = topic - return response + return gen_speaking_part_3(topic, difficulty) except Exception as e: return str(e) @@ -1402,7 +1153,7 @@ def get_reading_passage_1_question(): topic = request.args.get('topic', default=random.choice(topics)) req_exercises = request.args.getlist('exercises') difficulty = request.args.get("difficulty", default=random.choice(difficulties)) - return gen_reading_passage_1(topic, req_exercises, difficulty) + return gen_reading_passage_1(topic, difficulty, req_exercises) except Exception as e: return str(e) @@ -1415,7 +1166,7 @@ def get_reading_passage_2_question(): topic = request.args.get('topic', default=random.choice(topics)) req_exercises = request.args.getlist('exercises') difficulty = request.args.get("difficulty", default=random.choice(difficulties)) - return gen_reading_passage_2(topic, req_exercises, difficulty) + return gen_reading_passage_2(topic, difficulty, req_exercises) except Exception as e: return str(e) @@ -1428,7 +1179,7 @@ def get_reading_passage_3_question(): topic = request.args.get('topic', default=random.choice(topics)) req_exercises = request.args.getlist('exercises') difficulty = request.args.get("difficulty", default=random.choice(difficulties)) - return gen_reading_passage_3(topic, req_exercises, difficulty) + return gen_reading_passage_3(topic, difficulty, req_exercises) except Exception as e: return str(e) @@ -1560,6 +1311,18 @@ class CustomLevelExerciseTypes(Enum): MULTIPLE_CHOICE_UNDERLINED = "multiple_choice_underlined" BLANK_SPACE_TEXT = "blank_space_text" READING_PASSAGE_UTAS = "reading_passage_utas" + WRITING_LETTER = "writing_letter" + WRITING_2 = "writing_2" + SPEAKING_1 = "speaking_1" + SPEAKING_2 = "speaking_2" + SPEAKING_3 = "speaking_3" + READING_1 = "reading_1" + READING_2 = "reading_2" + READING_3 = "reading_3" + LISTENING_1 = "listening_1" + LISTENING_2 = "listening_2" + LISTENING_3 = "listening_3" + LISTENING_4 = "listening_4" @app.route('/custom_level', methods=['GET']) @@ -1574,11 +1337,24 @@ def get_custom_level(): } for i in range(1, nr_exercises + 1, 1): exercise_type = request.args.get('exercise_' + str(i) + '_type') + exercise_difficulty = request.args.get('exercise_' + str(i) + '_difficulty', + random.choice(['easy', 'medium', 'hard'])) exercise_qty = int(request.args.get('exercise_' + str(i) + '_qty', -1)) exercise_topic = request.args.get('exercise_' + str(i) + '_topic', random.choice(topics)) + exercise_topic_2 = request.args.get('exercise_' + str(i) + '_topic_2', random.choice(topics)) exercise_text_size = int(request.args.get('exercise_' + str(i) + '_text_size', 700)) exercise_sa_qty = int(request.args.get('exercise_' + str(i) + '_sa_qty', -1)) exercise_mc_qty = int(request.args.get('exercise_' + str(i) + '_mc_qty', -1)) + exercise_mc3_qty = int(request.args.get('exercise_' + str(i) + '_mc3_qty', -1)) + exercise_fillblanks_qty = int(request.args.get('exercise_' + str(i) + '_fillblanks_qty', -1)) + exercise_writeblanks_qty = int(request.args.get('exercise_' + str(i) + '_writeblanks_qty', -1)) + exercise_writeblanksquestions_qty = int( + request.args.get('exercise_' + str(i) + '_writeblanksquestions_qty', -1)) + exercise_writeblanksfill_qty = int(request.args.get('exercise_' + str(i) + '_writeblanksfill_qty', -1)) + exercise_writeblanksform_qty = int(request.args.get('exercise_' + str(i) + '_writeblanksform_qty', -1)) + exercise_truefalse_qty = int(request.args.get('exercise_' + str(i) + '_truefalse_qty', -1)) + exercise_paragraphmatch_qty = int(request.args.get('exercise_' + str(i) + '_paragraphmatch_qty', -1)) + exercise_ideamatch_qty = int(request.args.get('exercise_' + str(i) + '_ideamatch_qty', -1)) if exercise_type == CustomLevelExerciseTypes.MULTIPLE_CHOICE_4.value: response["exercises"]["exercise_" + str(i)] = {} @@ -1592,7 +1368,7 @@ def get_custom_level(): response["exercises"]["exercise_" + str(i)]["questions"].extend( generate_level_mc(exercise_id, qty, - response["exercises"]["exercise_" + str(i)]["questions"])["questions"]) + response["exercises"]["exercise_" + str(i)]["questions"])["questions"]) exercise_id = exercise_id + qty exercise_qty = exercise_qty - qty @@ -1608,7 +1384,8 @@ def get_custom_level(): response["exercises"]["exercise_" + str(i)]["questions"].extend( gen_multiple_choice_blank_space_utas(qty, exercise_id, - response["exercises"]["exercise_" + str(i)]["questions"])["questions"]) + response["exercises"]["exercise_" + str(i)]["questions"])[ + "questions"]) exercise_id = exercise_id + qty exercise_qty = exercise_qty - qty @@ -1624,7 +1401,8 @@ def get_custom_level(): response["exercises"]["exercise_" + str(i)]["questions"].extend( gen_multiple_choice_underlined_utas(qty, exercise_id, - response["exercises"]["exercise_" + str(i)]["questions"])["questions"]) + response["exercises"]["exercise_" + str(i)]["questions"])[ + "questions"]) exercise_id = exercise_id + qty exercise_qty = exercise_qty - qty @@ -1638,9 +1416,205 @@ def get_custom_level(): exercise_mc_qty, exercise_topic) response["exercises"]["exercise_" + str(i)]["type"] = "readingExercises" exercise_id = exercise_id + exercise_qty + elif exercise_type == CustomLevelExerciseTypes.WRITING_LETTER.value: + response["exercises"]["exercise_" + str(i)] = gen_writing_task_1(exercise_topic, exercise_difficulty) + response["exercises"]["exercise_" + str(i)]["type"] = "writing" + exercise_id = exercise_id + 1 + elif exercise_type == CustomLevelExerciseTypes.WRITING_2.value: + response["exercises"]["exercise_" + str(i)] = gen_writing_task_2(exercise_topic, exercise_difficulty) + response["exercises"]["exercise_" + str(i)]["type"] = "writing" + exercise_id = exercise_id + 1 + elif exercise_type == CustomLevelExerciseTypes.SPEAKING_1.value: + response["exercises"]["exercise_" + str(i)] = ( + gen_speaking_part_1(exercise_topic, exercise_topic_2, exercise_difficulty)) + response["exercises"]["exercise_" + str(i)]["type"] = "interactiveSpeaking" + exercise_id = exercise_id + 1 + elif exercise_type == CustomLevelExerciseTypes.SPEAKING_2.value: + response["exercises"]["exercise_" + str(i)] = gen_speaking_part_2(exercise_topic, exercise_difficulty) + response["exercises"]["exercise_" + str(i)]["type"] = "speaking" + exercise_id = exercise_id + 1 + elif exercise_type == CustomLevelExerciseTypes.SPEAKING_3.value: + response["exercises"]["exercise_" + str(i)] = gen_speaking_part_3(exercise_topic, exercise_difficulty) + response["exercises"]["exercise_" + str(i)]["type"] = "interactiveSpeaking" + exercise_id = exercise_id + 1 + elif exercise_type == CustomLevelExerciseTypes.READING_1.value: + exercises = [] + exercise_qty_q = queue.Queue() + total_qty = 0 + if exercise_fillblanks_qty != -1: + exercises.append('fillBlanks') + exercise_qty_q.put(exercise_fillblanks_qty) + total_qty = total_qty + exercise_fillblanks_qty + if exercise_writeblanks_qty != -1: + exercises.append('writeBlanks') + exercise_qty_q.put(exercise_writeblanks_qty) + total_qty = total_qty + exercise_writeblanks_qty + if exercise_truefalse_qty != -1: + exercises.append('trueFalse') + exercise_qty_q.put(exercise_truefalse_qty) + total_qty = total_qty + exercise_truefalse_qty + if exercise_paragraphmatch_qty != -1: + exercises.append('paragraphMatch') + exercise_qty_q.put(exercise_paragraphmatch_qty) + total_qty = total_qty + exercise_paragraphmatch_qty + + response["exercises"]["exercise_" + str(i)] = gen_reading_passage_1(exercise_topic, exercise_difficulty, + exercises, exercise_qty_q, exercise_id) + response["exercises"]["exercise_" + str(i)]["type"] = "reading" + + exercise_id = exercise_id + total_qty + elif exercise_type == CustomLevelExerciseTypes.READING_2.value: + exercises = [] + exercise_qty_q = queue.Queue() + total_qty = 0 + if exercise_fillblanks_qty != -1: + exercises.append('fillBlanks') + exercise_qty_q.put(exercise_fillblanks_qty) + total_qty = total_qty + exercise_fillblanks_qty + if exercise_writeblanks_qty != -1: + exercises.append('writeBlanks') + exercise_qty_q.put(exercise_writeblanks_qty) + total_qty = total_qty + exercise_writeblanks_qty + if exercise_truefalse_qty != -1: + exercises.append('trueFalse') + exercise_qty_q.put(exercise_truefalse_qty) + total_qty = total_qty + exercise_truefalse_qty + if exercise_paragraphmatch_qty != -1: + exercises.append('paragraphMatch') + exercise_qty_q.put(exercise_paragraphmatch_qty) + total_qty = total_qty + exercise_paragraphmatch_qty + + response["exercises"]["exercise_" + str(i)] = gen_reading_passage_2(exercise_topic, exercise_difficulty, + exercises, exercise_qty_q, exercise_id) + response["exercises"]["exercise_" + str(i)]["type"] = "reading" + + exercise_id = exercise_id + total_qty + elif exercise_type == CustomLevelExerciseTypes.READING_3.value: + exercises = [] + exercise_qty_q = queue.Queue() + total_qty = 0 + if exercise_fillblanks_qty != -1: + exercises.append('fillBlanks') + exercise_qty_q.put(exercise_fillblanks_qty) + total_qty = total_qty + exercise_fillblanks_qty + if exercise_writeblanks_qty != -1: + exercises.append('writeBlanks') + exercise_qty_q.put(exercise_writeblanks_qty) + total_qty = total_qty + exercise_writeblanks_qty + if exercise_truefalse_qty != -1: + exercises.append('trueFalse') + exercise_qty_q.put(exercise_truefalse_qty) + total_qty = total_qty + exercise_truefalse_qty + if exercise_paragraphmatch_qty != -1: + exercises.append('paragraphMatch') + exercise_qty_q.put(exercise_paragraphmatch_qty) + total_qty = total_qty + exercise_paragraphmatch_qty + if exercise_ideamatch_qty != -1: + exercises.append('ideaMatch') + exercise_qty_q.put(exercise_ideamatch_qty) + total_qty = total_qty + exercise_ideamatch_qty + + response["exercises"]["exercise_" + str(i)] = gen_reading_passage_3(exercise_topic, exercise_difficulty, + exercises, exercise_qty_q, exercise_id) + response["exercises"]["exercise_" + str(i)]["type"] = "reading" + + exercise_id = exercise_id + total_qty + elif exercise_type == CustomLevelExerciseTypes.LISTENING_1.value: + exercises = [] + exercise_qty_q = queue.Queue() + total_qty = 0 + if exercise_mc_qty != -1: + exercises.append('multipleChoice') + exercise_qty_q.put(exercise_mc_qty) + total_qty = total_qty + exercise_mc_qty + if exercise_writeblanksquestions_qty != -1: + exercises.append('writeBlanksQuestions') + exercise_qty_q.put(exercise_writeblanksquestions_qty) + total_qty = total_qty + exercise_writeblanksquestions_qty + if exercise_writeblanksfill_qty != -1: + exercises.append('writeBlanksFill') + exercise_qty_q.put(exercise_writeblanksfill_qty) + total_qty = total_qty + exercise_writeblanksfill_qty + if exercise_writeblanksform_qty != -1: + exercises.append('writeBlanksForm') + exercise_qty_q.put(exercise_writeblanksform_qty) + total_qty = total_qty + exercise_writeblanksform_qty + + response["exercises"]["exercise_" + str(i)] = gen_listening_section_1(exercise_topic, exercise_difficulty, + exercises, exercise_qty_q, + exercise_id) + response["exercises"]["exercise_" + str(i)]["type"] = "listening" + + exercise_id = exercise_id + total_qty + elif exercise_type == CustomLevelExerciseTypes.LISTENING_2.value: + exercises = [] + exercise_qty_q = queue.Queue() + total_qty = 0 + if exercise_mc_qty != -1: + exercises.append('multipleChoice') + exercise_qty_q.put(exercise_mc_qty) + total_qty = total_qty + exercise_mc_qty + if exercise_writeblanksquestions_qty != -1: + exercises.append('writeBlanksQuestions') + exercise_qty_q.put(exercise_writeblanksquestions_qty) + total_qty = total_qty + exercise_writeblanksquestions_qty + + response["exercises"]["exercise_" + str(i)] = gen_listening_section_2(exercise_topic, exercise_difficulty, + exercises, exercise_qty_q, + exercise_id) + response["exercises"]["exercise_" + str(i)]["type"] = "listening" + + exercise_id = exercise_id + total_qty + elif exercise_type == CustomLevelExerciseTypes.LISTENING_3.value: + exercises = [] + exercise_qty_q = queue.Queue() + total_qty = 0 + if exercise_mc3_qty != -1: + exercises.append('multipleChoice3Options') + exercise_qty_q.put(exercise_mc3_qty) + total_qty = total_qty + exercise_mc3_qty + if exercise_writeblanksquestions_qty != -1: + exercises.append('writeBlanksQuestions') + exercise_qty_q.put(exercise_writeblanksquestions_qty) + total_qty = total_qty + exercise_writeblanksquestions_qty + + response["exercises"]["exercise_" + str(i)] = gen_listening_section_3(exercise_topic, exercise_difficulty, + exercises, exercise_qty_q, + exercise_id) + response["exercises"]["exercise_" + str(i)]["type"] = "listening" + + exercise_id = exercise_id + total_qty + elif exercise_type == CustomLevelExerciseTypes.LISTENING_4.value: + exercises = [] + exercise_qty_q = queue.Queue() + total_qty = 0 + if exercise_mc_qty != -1: + exercises.append('multipleChoice') + exercise_qty_q.put(exercise_mc_qty) + total_qty = total_qty + exercise_mc_qty + if exercise_writeblanksquestions_qty != -1: + exercises.append('writeBlanksQuestions') + exercise_qty_q.put(exercise_writeblanksquestions_qty) + total_qty = total_qty + exercise_writeblanksquestions_qty + if exercise_writeblanksfill_qty != -1: + exercises.append('writeBlanksFill') + exercise_qty_q.put(exercise_writeblanksfill_qty) + total_qty = total_qty + exercise_writeblanksfill_qty + if exercise_writeblanksform_qty != -1: + exercises.append('writeBlanksForm') + exercise_qty_q.put(exercise_writeblanksform_qty) + total_qty = total_qty + exercise_writeblanksform_qty + + response["exercises"]["exercise_" + str(i)] = gen_listening_section_4(exercise_topic, exercise_difficulty, + exercises, exercise_qty_q, + exercise_id) + response["exercises"]["exercise_" + str(i)]["type"] = "listening" + + exercise_id = exercise_id + total_qty return response + @app.route('/grade_short_answers', methods=['POST']) @jwt_required() def grade_short_answers(): @@ -1665,7 +1639,8 @@ def grade_short_answers(): }, { "role": "user", - "content": 'Grade these answers according to the text content and write a correct answer if they are wrong. Text, questions and answers:\n ' + str(data) + "content": 'Grade these answers according to the text content and write a correct answer if they are ' + 'wrong. Text, questions and answers:\n ' + str(data) } ] @@ -1675,6 +1650,7 @@ def grade_short_answers(): except Exception as e: return str(e) + @app.route('/fetch_tips', methods=['POST']) @jwt_required() def fetch_answer_tips(): diff --git a/helper/exercises.py b/helper/exercises.py index 53321c4..b3f22c5 100644 --- a/helper/exercises.py +++ b/helper/exercises.py @@ -15,19 +15,19 @@ from helper.speech_to_text_helper import has_x_words nltk.download('words') -def gen_reading_passage_1(topic, req_exercises, difficulty): +def gen_reading_passage_1(topic, difficulty, req_exercises, number_of_exercises_q=queue.Queue(), start_id=1): if (len(req_exercises) == 0): req_exercises = random.sample(READING_EXERCISE_TYPES, 2) - number_of_exercises_q = divide_number_into_parts(TOTAL_READING_PASSAGE_1_EXERCISES, len(req_exercises)) + if (number_of_exercises_q.empty()): + number_of_exercises_q = divide_number_into_parts(TOTAL_READING_PASSAGE_1_EXERCISES, len(req_exercises)) passage = generate_reading_passage_1_text(topic) if passage == "": - return gen_reading_passage_1(topic, req_exercises, difficulty) - start_id = 1 + return gen_reading_passage_1(topic, difficulty, req_exercises, number_of_exercises_q, start_id) exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty) if contains_empty_dict(exercises): - return gen_reading_passage_1(topic, req_exercises, difficulty) + return gen_reading_passage_1(topic, difficulty, req_exercises, number_of_exercises_q, start_id) return { "exercises": exercises, "text": { @@ -38,19 +38,19 @@ def gen_reading_passage_1(topic, req_exercises, difficulty): } -def gen_reading_passage_2(topic, req_exercises, difficulty): +def gen_reading_passage_2(topic, difficulty, req_exercises, number_of_exercises_q=queue.Queue(), start_id=14): if (len(req_exercises) == 0): req_exercises = random.sample(READING_EXERCISE_TYPES, 2) - number_of_exercises_q = divide_number_into_parts(TOTAL_READING_PASSAGE_2_EXERCISES, len(req_exercises)) + if (number_of_exercises_q.empty()): + number_of_exercises_q = divide_number_into_parts(TOTAL_READING_PASSAGE_2_EXERCISES, len(req_exercises)) passage = generate_reading_passage_2_text(topic) if passage == "": - return gen_reading_passage_2(topic, req_exercises, difficulty) - start_id = 14 + return gen_reading_passage_2(topic, difficulty, req_exercises, number_of_exercises_q, start_id) exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty) if contains_empty_dict(exercises): - return gen_reading_passage_2(topic, req_exercises, difficulty) + return gen_reading_passage_2(topic, difficulty, req_exercises, number_of_exercises_q, start_id) return { "exercises": exercises, "text": { @@ -61,19 +61,19 @@ def gen_reading_passage_2(topic, req_exercises, difficulty): } -def gen_reading_passage_3(topic, req_exercises, difficulty): +def gen_reading_passage_3(topic, difficulty, req_exercises, number_of_exercises_q=queue.Queue(), start_id=27): if (len(req_exercises) == 0): req_exercises = random.sample(READING_EXERCISE_TYPES, 2) - number_of_exercises_q = divide_number_into_parts(TOTAL_READING_PASSAGE_3_EXERCISES, len(req_exercises)) + if (number_of_exercises_q.empty()): + number_of_exercises_q = divide_number_into_parts(TOTAL_READING_PASSAGE_3_EXERCISES, len(req_exercises)) passage = generate_reading_passage_3_text(topic) if passage == "": - return gen_reading_passage_3(topic, req_exercises, difficulty) - start_id = 27 + return gen_reading_passage_3(topic, difficulty, req_exercises, number_of_exercises_q, start_id) exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty) if contains_empty_dict(exercises): - return gen_reading_passage_3(topic, req_exercises, difficulty) + return gen_reading_passage_3(topic, difficulty, req_exercises, number_of_exercises_q, start_id) return { "exercises": exercises, "text": { @@ -865,7 +865,8 @@ def gen_idea_match_exercise(text: str, quantity: int, start_id): { "role": "user", "content": ( - 'From the text extract ' + str(quantity) + ' ideas, theories, opinions and who they are from. The text: ' + str(text)) + 'From the text extract ' + str( + quantity) + ' ideas, theories, opinions and who they are from. The text: ' + str(text)) } ] @@ -882,6 +883,7 @@ def gen_idea_match_exercise(text: str, quantity: int, start_id): "type": "matchSentences" } + def build_options(ideas): options = [] letters = iter(string.ascii_uppercase) @@ -892,6 +894,7 @@ def build_options(ideas): }) return options + def build_sentences(ideas, start_id): sentences = [] letters = iter(string.ascii_uppercase) @@ -906,6 +909,7 @@ def build_sentences(ideas, start_id): sentence["id"] = i return sentences + def assign_letters_to_paragraphs(paragraphs): result = [] letters = iter(string.ascii_uppercase) @@ -1272,7 +1276,8 @@ def replace_exercise_if_exists(all_exams, current_exercise, current_exam, seen_k current_exercise["options"]) for exercise in exercise_dict.get("exercises", [])[0]["questions"] ): - return replace_exercise_if_exists(all_exams, generate_single_mc_level_question(), current_exam, seen_keys) + return replace_exercise_if_exists(all_exams, generate_single_mc_level_question(), current_exam, + seen_keys) return current_exercise, seen_keys @@ -1302,7 +1307,8 @@ def replace_blank_space_exercise_if_exists_utas(all_exams, current_exercise, cur key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options']))) # Check if the key is in the set if key in seen_keys: - return replace_exercise_if_exists_utas(all_exams, generate_single_mc_blank_space_level_question(), current_exam, seen_keys) + return replace_exercise_if_exists_utas(all_exams, generate_single_mc_blank_space_level_question(), current_exam, + seen_keys) else: seen_keys.add(key) @@ -1313,7 +1319,8 @@ def replace_blank_space_exercise_if_exists_utas(all_exams, current_exercise, cur current_exercise["options"]) for exercise in exam.get("questions", []) ): - return replace_exercise_if_exists_utas(all_exams, generate_single_mc_blank_space_level_question(), current_exam, + return replace_exercise_if_exists_utas(all_exams, generate_single_mc_blank_space_level_question(), + current_exam, seen_keys) return current_exercise, seen_keys @@ -1323,7 +1330,8 @@ def replace_underlined_exercise_if_exists_utas(all_exams, current_exercise, curr key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options']))) # Check if the key is in the set if key in seen_keys: - return replace_exercise_if_exists_utas(all_exams, generate_single_mc_underlined_level_question(), current_exam, seen_keys) + return replace_exercise_if_exists_utas(all_exams, generate_single_mc_underlined_level_question(), current_exam, + seen_keys) else: seen_keys.add(key) @@ -1334,7 +1342,8 @@ def replace_underlined_exercise_if_exists_utas(all_exams, current_exercise, curr current_exercise["options"]) for exercise in exam.get("questions", []) ): - return replace_exercise_if_exists_utas(all_exams, generate_single_mc_underlined_level_question(), current_exam, + return replace_exercise_if_exists_utas(all_exams, generate_single_mc_underlined_level_question(), + current_exam, seen_keys) return current_exercise, seen_keys @@ -1376,8 +1385,8 @@ def generate_single_mc_blank_space_level_question(): }, { "role": "user", - "content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, it can be easy, ' - 'intermediate or advanced.') + "content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, ' + 'it can be easy, intermediate or advanced.') } ] @@ -1401,8 +1410,8 @@ def generate_single_mc_underlined_level_question(): }, { "role": "user", - "content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, it can be easy, ' - 'intermediate or advanced.') + "content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, ' + 'it can be easy, intermediate or advanced.') }, { @@ -1469,9 +1478,9 @@ def gen_multiple_choice_blank_space_utas(quantity: int, start_id: int, all_exams if all_exams is not None: seen_keys = set() for i in range(len(question["questions"])): - question["questions"][i], seen_keys = replace_blank_space_exercise_if_exists_utas(all_exams, question["questions"][i], - question, - seen_keys) + question["questions"][i], seen_keys = ( + replace_blank_space_exercise_if_exists_utas(all_exams, question["questions"][i], question, + seen_keys)) response = fix_exercise_ids(question, start_id) response["questions"] = randomize_mc_options_order(response["questions"]) return response @@ -1546,11 +1555,9 @@ def gen_multiple_choice_underlined_utas(quantity: int, start_id: int, all_exams= if all_exams is not None: seen_keys = set() for i in range(len(question["questions"])): - question["questions"][i], seen_keys = replace_underlined_exercise_if_exists_utas(all_exams, - question["questions"][ - i], - question, - seen_keys) + question["questions"][i], seen_keys = ( + replace_underlined_exercise_if_exists_utas(all_exams, question["questions"][i], question, + seen_keys)) response = fix_exercise_ids(question, start_id) response["questions"] = randomize_mc_options_order(response["questions"]) return response @@ -1765,7 +1772,8 @@ def generate_level_mc(start_id: int, quantity: int, all_questions=None): if all_questions is not None: seen_keys = set() for i in range(len(question["questions"])): - question["questions"][i], seen_keys = replace_exercise_if_exists_utas(all_questions, question["questions"][i], + question["questions"][i], seen_keys = replace_exercise_if_exists_utas(all_questions, + question["questions"][i], question, seen_keys) response = fix_exercise_ids(question, start_id) @@ -1791,3 +1799,293 @@ def randomize_mc_options_order(questions): question['solution'] = option['id'] return questions + + +def gen_writing_task_1(topic, difficulty): + messages = [ + { + "role": "system", + "content": ('You are a helpful assistant designed to output JSON on this format: ' + '{"prompt": "prompt content"}') + }, + { + "role": "user", + "content": ('Craft a prompt for an IELTS Writing Task 1 General Training exercise that instructs the ' + 'student to compose a letter. The prompt should present a specific scenario or situation, ' + 'based on the topic of "' + topic + '", requiring the student to provide information, ' + 'advice, or instructions within the letter. ' + 'Make sure that the generated prompt is ' + 'of ' + difficulty + 'difficulty and does not contain ' + 'forbidden subjects in muslim ' + 'countries.') + }, + { + "role": "user", + "content": 'The prompt should end with "In the letter you should" followed by 3 bullet points of what ' + 'the answer should include.' + } + ] + token_count = count_total_tokens(messages) + response = make_openai_call(GPT_3_5_TURBO, messages, token_count, "prompt", + GEN_QUESTION_TEMPERATURE) + return { + "question": add_newline_before_hyphen(response["prompt"].strip()), + "difficulty": difficulty, + "topic": topic + } + + +def add_newline_before_hyphen(s): + return s.replace(" -", "\n-") + + +def gen_writing_task_2(topic, difficulty): + messages = [ + { + "role": "system", + "content": ('You are a helpful assistant designed to output JSON on this format: ' + '{"prompt": "prompt content"}') + }, + { + "role": "user", + "content": ( + 'Craft a comprehensive question of ' + difficulty + 'difficulty like the ones for IELTS Writing ' + 'Task 2 General Training that directs the ' + 'candidate' + 'to delve into an in-depth analysis of ' + 'contrasting perspectives on the topic ' + 'of "' + topic + '". The candidate should be ' + 'asked to discuss the ' + 'strengths and weaknesses of ' + 'both viewpoints.') + }, + { + "role": "user", + "content": 'The question should lead to an answer with either "theories", "complicated information" or ' + 'be "very descriptive" on the topic.' + } + ] + token_count = count_total_tokens(messages) + response = make_openai_call(GPT_4_O, messages, token_count, "prompt", GEN_QUESTION_TEMPERATURE) + return { + "question": response["prompt"].strip(), + "difficulty": difficulty, + "topic": topic + } + + +def gen_speaking_part_1(first_topic: str, second_topic: str, difficulty): + json_format = { + "first_topic": "topic 1", + "second_topic": "topic 2", + "questions": [ + "Introductory question about the first topic, starting the topic with 'Let's talk about x' and then the " + "question.", + "Follow up question about the first topic", + "Follow up question about the first topic", + "Question about second topic", + "Follow up question about the second topic", + ] + } + + messages = [ + { + "role": "system", + "content": ( + 'You are a helpful assistant designed to output JSON on this format: ' + str(json_format)) + }, + { + "role": "user", + "content": ( + 'Craft 5 simple and single questions of easy difficulty for IELTS Speaking Part 1 ' + 'that encourages candidates to delve deeply into ' + 'personal experiences, preferences, or insights on the topic ' + 'of "' + first_topic + '" and the topic of "' + second_topic + '". ' + 'Make sure that the generated ' + 'question' + 'does not contain forbidden ' + 'subjects in' + 'muslim countries.') + }, + { + "role": "user", + "content": 'The questions should lead to the usage of 4 verb tenses (present perfect, present, ' + 'past and future).' + }, + { + "role": "user", + "content": 'They must be 1 single question each and not be double-barreled questions.' + + } + ] + token_count = count_total_tokens(messages) + response = make_openai_call(GPT_4_O, messages, token_count, ["first_topic"], + GEN_QUESTION_TEMPERATURE) + response["type"] = 1 + response["difficulty"] = difficulty + return response + + +def gen_speaking_part_2(topic: str, difficulty): + json_format = { + "topic": "topic", + "question": "question", + "prompts": [ + "prompt_1", + "prompt_2", + "prompt_3" + ], + "suffix": "And explain why..." + } + + messages = [ + { + "role": "system", + "content": 'You are a helpful assistant designed to output JSON on this format: ' + str(json_format) + }, + { + "role": "user", + "content": ( + 'Create a question of medium difficulty for IELTS Speaking Part 2 ' + 'that encourages candidates to narrate a ' + 'personal experience or story related to the topic ' + 'of "' + topic + '". Include 3 prompts that ' + 'guide the candidate to describe ' + 'specific aspects of the experience, ' + 'such as details about the situation, ' + 'their actions, and the reasons it left a ' + 'lasting impression. Make sure that the ' + 'generated question does not contain ' + 'forbidden subjects in muslim countries.') + }, + { + "role": "user", + "content": 'The prompts must not be questions. Also include a suffix like the ones in the IELTS exams ' + 'that start with "And explain why".' + } + ] + token_count = count_total_tokens(messages) + response = make_openai_call(GPT_4_O, messages, token_count, GEN_FIELDS, GEN_QUESTION_TEMPERATURE) + response["type"] = 2 + response["difficulty"] = difficulty + response["topic"] = topic + return response + + +def gen_speaking_part_3(topic: str, difficulty): + json_format = { + "topic": "topic", + "questions": [ + "Introductory question about the topic.", + "Follow up question about the topic", + "Follow up question about the topic", + "Follow up question about the topic", + "Follow up question about the topic" + ] + } + + messages = [ + { + "role": "system", + "content": ( + 'You are a helpful assistant designed to output JSON on this format: ' + str(json_format)) + }, + { + "role": "user", + "content": ( + 'Formulate a set of 5 single questions of hard difficulty for IELTS Speaking Part 3 that encourage candidates to engage in a ' + 'meaningful discussion on the topic of "' + topic + '". Provide inquiries, ensuring ' + 'they explore various aspects, perspectives, and implications related to the topic.' + 'Make sure that the generated question does not contain forbidden subjects in muslim countries.') + + }, + { + "role": "user", + "content": 'They must be 1 single question each and not be double-barreled questions.' + + } + ] + token_count = count_total_tokens(messages) + response = make_openai_call(GPT_4_O, messages, token_count, GEN_FIELDS, GEN_QUESTION_TEMPERATURE) + # Remove the numbers from the questions only if the string starts with a number + response["questions"] = [re.sub(r"^\d+\.\s*", "", question) if re.match(r"^\d+\.", question) else question for + question in response["questions"]] + response["type"] = 3 + response["difficulty"] = difficulty + response["topic"] = topic + return response + + +def gen_listening_section_1(topic, difficulty, req_exercises, number_of_exercises_q=queue.Queue(), start_id=1): + if (len(req_exercises) == 0): + req_exercises = random.sample(LISTENING_1_EXERCISE_TYPES, 1) + + if (number_of_exercises_q.empty()): + number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_1_EXERCISES, len(req_exercises)) + + processed_conversation = generate_listening_1_conversation(topic) + + exercises = generate_listening_conversation_exercises(parse_conversation(processed_conversation), + req_exercises, + number_of_exercises_q, + start_id, difficulty) + return { + "exercises": exercises, + "text": processed_conversation, + "difficulty": difficulty + } + + +def gen_listening_section_2(topic, difficulty, req_exercises, number_of_exercises_q=queue.Queue(), start_id=11): + if (len(req_exercises) == 0): + req_exercises = random.sample(LISTENING_2_EXERCISE_TYPES, 2) + + if (number_of_exercises_q.empty()): + number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_2_EXERCISES, len(req_exercises)) + + monologue = generate_listening_2_monologue(topic) + + exercises = generate_listening_monologue_exercises(str(monologue), req_exercises, number_of_exercises_q, + start_id, difficulty) + return { + "exercises": exercises, + "text": monologue, + "difficulty": difficulty + } + + +def gen_listening_section_3(topic, difficulty, req_exercises, number_of_exercises_q=queue.Queue(), start_id=21): + if (len(req_exercises) == 0): + req_exercises = random.sample(LISTENING_3_EXERCISE_TYPES, 1) + + if (number_of_exercises_q.empty()): + number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_3_EXERCISES, len(req_exercises)) + + processed_conversation = generate_listening_3_conversation(topic) + + exercises = generate_listening_conversation_exercises(parse_conversation(processed_conversation), req_exercises, + number_of_exercises_q, + start_id, difficulty) + return { + "exercises": exercises, + "text": processed_conversation, + "difficulty": difficulty + } + + +def gen_listening_section_4(topic, difficulty, req_exercises, number_of_exercises_q=queue.Queue(), start_id=31): + if (len(req_exercises) == 0): + req_exercises = random.sample(LISTENING_EXERCISE_TYPES, 2) + + if (number_of_exercises_q.empty()): + number_of_exercises_q = divide_number_into_parts(TOTAL_LISTENING_SECTION_4_EXERCISES, len(req_exercises)) + + monologue = generate_listening_4_monologue(topic) + + exercises = generate_listening_monologue_exercises(str(monologue), req_exercises, number_of_exercises_q, + start_id, difficulty) + return { + "exercises": exercises, + "text": monologue, + "difficulty": difficulty + }