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Add regular ielts modules to custom level.

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This commit is contained in:
Cristiano Ferreira
2024-08-15 13:58:07 +01:00
parent beccf8b501
commit d68617f33b
2 changed files with 573 additions and 299 deletions
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506
app.py
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@@ -65,25 +65,7 @@ def get_listening_section_1_question():
req_exercises = request.args.getlist('exercises') req_exercises = request.args.getlist('exercises')
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
if (len(req_exercises) == 0): return gen_listening_section_1(topic, difficulty, req_exercises)
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
}
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -98,22 +80,7 @@ def get_listening_section_2_question():
req_exercises = request.args.getlist('exercises') req_exercises = request.args.getlist('exercises')
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
if (len(req_exercises) == 0): return gen_listening_section_2(topic, difficulty, req_exercises)
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
}
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -128,24 +95,7 @@ def get_listening_section_3_question():
req_exercises = request.args.getlist('exercises') req_exercises = request.args.getlist('exercises')
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
if (len(req_exercises) == 0): return gen_listening_section_3(topic, difficulty, req_exercises)
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
}
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -160,22 +110,7 @@ def get_listening_section_4_question():
req_exercises = request.args.getlist('exercises') req_exercises = request.args.getlist('exercises')
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
if (len(req_exercises) == 0): return gen_listening_section_4(topic, difficulty, req_exercises)
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
}
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -342,37 +277,7 @@ def get_writing_task_1_general_question():
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
topic = request.args.get("topic", default=random.choice(mti_topics)) topic = request.args.get("topic", default=random.choice(mti_topics))
try: try:
messages = [ return gen_writing_task_1(topic, difficulty)
{
"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
}
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -507,32 +412,7 @@ def get_writing_task_2_general_question():
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
topic = request.args.get("topic", default=random.choice(mti_topics)) topic = request.args.get("topic", default=random.choice(mti_topics))
try: try:
messages = [ return gen_writing_task_2(topic, difficulty)
{
"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
}
except Exception as e: except Exception as e:
return str(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)) first_topic = request.args.get("first_topic", default=random.choice(mti_topics))
second_topic = request.args.get("second_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: try:
messages = [ return gen_speaking_part_1(first_topic, second_topic, difficulty)
{
"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
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -913,50 +745,8 @@ def get_speaking_task_2_question():
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
topic = request.args.get("topic", default=random.choice(mti_topics)) 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: try:
messages = [ return gen_speaking_part_2(topic, difficulty)
{
"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
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -967,47 +757,8 @@ def get_speaking_task_3_question():
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) difficulty = request.args.get("difficulty", default=random.choice(difficulties))
topic = request.args.get("topic", default=random.choice(mti_topics)) 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: try:
messages = [ return gen_speaking_part_3(topic, difficulty)
{
"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
except Exception as e: except Exception as e:
return str(e) return str(e)
@@ -1402,7 +1153,7 @@ def get_reading_passage_1_question():
topic = request.args.get('topic', default=random.choice(topics)) topic = request.args.get('topic', default=random.choice(topics))
req_exercises = request.args.getlist('exercises') req_exercises = request.args.getlist('exercises')
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) 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: except Exception as e:
return str(e) return str(e)
@@ -1415,7 +1166,7 @@ def get_reading_passage_2_question():
topic = request.args.get('topic', default=random.choice(topics)) topic = request.args.get('topic', default=random.choice(topics))
req_exercises = request.args.getlist('exercises') req_exercises = request.args.getlist('exercises')
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) 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: except Exception as e:
return str(e) return str(e)
@@ -1428,7 +1179,7 @@ def get_reading_passage_3_question():
topic = request.args.get('topic', default=random.choice(topics)) topic = request.args.get('topic', default=random.choice(topics))
req_exercises = request.args.getlist('exercises') req_exercises = request.args.getlist('exercises')
difficulty = request.args.get("difficulty", default=random.choice(difficulties)) 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: except Exception as e:
return str(e) return str(e)
@@ -1560,6 +1311,18 @@ class CustomLevelExerciseTypes(Enum):
MULTIPLE_CHOICE_UNDERLINED = "multiple_choice_underlined" MULTIPLE_CHOICE_UNDERLINED = "multiple_choice_underlined"
BLANK_SPACE_TEXT = "blank_space_text" BLANK_SPACE_TEXT = "blank_space_text"
READING_PASSAGE_UTAS = "reading_passage_utas" 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']) @app.route('/custom_level', methods=['GET'])
@@ -1574,11 +1337,24 @@ def get_custom_level():
} }
for i in range(1, nr_exercises + 1, 1): for i in range(1, nr_exercises + 1, 1):
exercise_type = request.args.get('exercise_' + str(i) + '_type') 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_qty = int(request.args.get('exercise_' + str(i) + '_qty', -1))
exercise_topic = request.args.get('exercise_' + str(i) + '_topic', random.choice(topics)) 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_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_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_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: if exercise_type == CustomLevelExerciseTypes.MULTIPLE_CHOICE_4.value:
response["exercises"]["exercise_" + str(i)] = {} response["exercises"]["exercise_" + str(i)] = {}
@@ -1592,7 +1368,7 @@ def get_custom_level():
response["exercises"]["exercise_" + str(i)]["questions"].extend( response["exercises"]["exercise_" + str(i)]["questions"].extend(
generate_level_mc(exercise_id, qty, 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_id = exercise_id + qty
exercise_qty = exercise_qty - qty exercise_qty = exercise_qty - qty
@@ -1608,7 +1384,8 @@ def get_custom_level():
response["exercises"]["exercise_" + str(i)]["questions"].extend( response["exercises"]["exercise_" + str(i)]["questions"].extend(
gen_multiple_choice_blank_space_utas(qty, exercise_id, 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_id = exercise_id + qty
exercise_qty = exercise_qty - qty exercise_qty = exercise_qty - qty
@@ -1624,7 +1401,8 @@ def get_custom_level():
response["exercises"]["exercise_" + str(i)]["questions"].extend( response["exercises"]["exercise_" + str(i)]["questions"].extend(
gen_multiple_choice_underlined_utas(qty, exercise_id, 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_id = exercise_id + qty
exercise_qty = exercise_qty - qty exercise_qty = exercise_qty - qty
@@ -1638,9 +1416,205 @@ def get_custom_level():
exercise_mc_qty, exercise_topic) exercise_mc_qty, exercise_topic)
response["exercises"]["exercise_" + str(i)]["type"] = "readingExercises" response["exercises"]["exercise_" + str(i)]["type"] = "readingExercises"
exercise_id = exercise_id + exercise_qty 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 return response
@app.route('/grade_short_answers', methods=['POST']) @app.route('/grade_short_answers', methods=['POST'])
@jwt_required() @jwt_required()
def grade_short_answers(): def grade_short_answers():
@@ -1665,7 +1639,8 @@ def grade_short_answers():
}, },
{ {
"role": "user", "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: except Exception as e:
return str(e) return str(e)
@app.route('/fetch_tips', methods=['POST']) @app.route('/fetch_tips', methods=['POST'])
@jwt_required() @jwt_required()
def fetch_answer_tips(): def fetch_answer_tips():

366
helper/exercises.py
View File

@@ -15,19 +15,19 @@ from helper.speech_to_text_helper import has_x_words
nltk.download('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): if (len(req_exercises) == 0):
req_exercises = random.sample(READING_EXERCISE_TYPES, 2) 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) passage = generate_reading_passage_1_text(topic)
if passage == "": if passage == "":
return gen_reading_passage_1(topic, req_exercises, difficulty) return gen_reading_passage_1(topic, difficulty, req_exercises, number_of_exercises_q, start_id)
start_id = 1
exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty) exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty)
if contains_empty_dict(exercises): 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 { return {
"exercises": exercises, "exercises": exercises,
"text": { "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): if (len(req_exercises) == 0):
req_exercises = random.sample(READING_EXERCISE_TYPES, 2) 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) passage = generate_reading_passage_2_text(topic)
if passage == "": if passage == "":
return gen_reading_passage_2(topic, req_exercises, difficulty) return gen_reading_passage_2(topic, difficulty, req_exercises, number_of_exercises_q, start_id)
start_id = 14
exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty) exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty)
if contains_empty_dict(exercises): 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 { return {
"exercises": exercises, "exercises": exercises,
"text": { "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): if (len(req_exercises) == 0):
req_exercises = random.sample(READING_EXERCISE_TYPES, 2) 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) passage = generate_reading_passage_3_text(topic)
if passage == "": if passage == "":
return gen_reading_passage_3(topic, req_exercises, difficulty) return gen_reading_passage_3(topic, difficulty, req_exercises, number_of_exercises_q, start_id)
start_id = 27
exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty) exercises = generate_reading_exercises(passage["text"], req_exercises, number_of_exercises_q, start_id, difficulty)
if contains_empty_dict(exercises): 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 { return {
"exercises": exercises, "exercises": exercises,
"text": { "text": {
@@ -865,7 +865,8 @@ def gen_idea_match_exercise(text: str, quantity: int, start_id):
{ {
"role": "user", "role": "user",
"content": ( "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" "type": "matchSentences"
} }
def build_options(ideas): def build_options(ideas):
options = [] options = []
letters = iter(string.ascii_uppercase) letters = iter(string.ascii_uppercase)
@@ -892,6 +894,7 @@ def build_options(ideas):
}) })
return options return options
def build_sentences(ideas, start_id): def build_sentences(ideas, start_id):
sentences = [] sentences = []
letters = iter(string.ascii_uppercase) letters = iter(string.ascii_uppercase)
@@ -906,6 +909,7 @@ def build_sentences(ideas, start_id):
sentence["id"] = i sentence["id"] = i
return sentences return sentences
def assign_letters_to_paragraphs(paragraphs): def assign_letters_to_paragraphs(paragraphs):
result = [] result = []
letters = iter(string.ascii_uppercase) 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"]) current_exercise["options"])
for exercise in exercise_dict.get("exercises", [])[0]["questions"] 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 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']))) key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options'])))
# Check if the key is in the set # Check if the key is in the set
if key in seen_keys: 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: else:
seen_keys.add(key) seen_keys.add(key)
@@ -1313,7 +1319,8 @@ def replace_blank_space_exercise_if_exists_utas(all_exams, current_exercise, cur
current_exercise["options"]) current_exercise["options"])
for exercise in exam.get("questions", []) 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) seen_keys)
return current_exercise, 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']))) key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options'])))
# Check if the key is in the set # Check if the key is in the set
if key in seen_keys: 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: else:
seen_keys.add(key) seen_keys.add(key)
@@ -1334,7 +1342,8 @@ def replace_underlined_exercise_if_exists_utas(all_exams, current_exercise, curr
current_exercise["options"]) current_exercise["options"])
for exercise in exam.get("questions", []) 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) seen_keys)
return current_exercise, seen_keys return current_exercise, seen_keys
@@ -1376,8 +1385,8 @@ def generate_single_mc_blank_space_level_question():
}, },
{ {
"role": "user", "role": "user",
"content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, it can be easy, ' "content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, '
'intermediate or advanced.') 'it can be easy, intermediate or advanced.')
} }
] ]
@@ -1401,8 +1410,8 @@ def generate_single_mc_underlined_level_question():
}, },
{ {
"role": "user", "role": "user",
"content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, it can be easy, ' "content": ('Generate 1 multiple choice blank space question of 4 options for an english level exam, '
'intermediate or advanced.') '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: if all_exams is not None:
seen_keys = set() seen_keys = set()
for i in range(len(question["questions"])): 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["questions"][i], seen_keys = (
question, replace_blank_space_exercise_if_exists_utas(all_exams, question["questions"][i], question,
seen_keys) seen_keys))
response = fix_exercise_ids(question, start_id) response = fix_exercise_ids(question, start_id)
response["questions"] = randomize_mc_options_order(response["questions"]) response["questions"] = randomize_mc_options_order(response["questions"])
return response 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: if all_exams is not None:
seen_keys = set() seen_keys = set()
for i in range(len(question["questions"])): for i in range(len(question["questions"])):
question["questions"][i], seen_keys = replace_underlined_exercise_if_exists_utas(all_exams, question["questions"][i], seen_keys = (
question["questions"][ replace_underlined_exercise_if_exists_utas(all_exams, question["questions"][i], question,
i], seen_keys))
question,
seen_keys)
response = fix_exercise_ids(question, start_id) response = fix_exercise_ids(question, start_id)
response["questions"] = randomize_mc_options_order(response["questions"]) response["questions"] = randomize_mc_options_order(response["questions"])
return response return response
@@ -1765,7 +1772,8 @@ def generate_level_mc(start_id: int, quantity: int, all_questions=None):
if all_questions is not None: if all_questions is not None:
seen_keys = set() seen_keys = set()
for i in range(len(question["questions"])): 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, question,
seen_keys) seen_keys)
response = fix_exercise_ids(question, start_id) response = fix_exercise_ids(question, start_id)
@@ -1791,3 +1799,293 @@ def randomize_mc_options_order(questions):
question['solution'] = option['id'] question['solution'] = option['id']
return questions 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
}