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Can now generate lots of mc in level custom.

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This commit is contained in:
Cristiano Ferreira
2024-07-28 14:33:08 +01:00
parent adfc027458
commit a1ee7e47da
2 changed files with 164 additions and 13 deletions
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47
app.py
View File

@@ -361,9 +361,11 @@ def get_writing_task_1_general_question():
except Exception as e:
return str(e)
def add_newline_before_hyphen(s):
return s.replace(" -", "\n-")
@app.route('/writing_task2', methods=['POST'])
@jwt_required()
def grade_writing_task_2():
@@ -1535,18 +1537,53 @@ def get_custom_level():
exercise_mc_qty = int(request.args.get('exercise_' + str(i) + '_mc_qty', -1))
if exercise_type == CustomLevelExerciseTypes.MULTIPLE_CHOICE_4.value:
response["exercises"]["exercise_" + str(i)] = generate_level_mc(exercise_id, exercise_qty)
response["exercises"]["exercise_" + str(i)] = {}
response["exercises"]["exercise_" + str(i)]["questions"] = []
response["exercises"]["exercise_" + str(i)]["type"] = "multipleChoice"
exercise_id = exercise_id + exercise_qty
while exercise_qty > 0:
if exercise_qty - 15 > 0:
qty = 15
else:
qty = exercise_qty
response["exercises"]["exercise_" + str(i)]["questions"].extend(
generate_level_mc(exercise_id, qty,
response["exercises"]["exercise_" + str(i)]["questions"])["questions"])
exercise_id = exercise_id + qty
exercise_qty = exercise_qty - qty
elif exercise_type == CustomLevelExerciseTypes.MULTIPLE_CHOICE_BLANK_SPACE.value:
response["exercises"]["exercise_" + str(i)] = gen_multiple_choice_blank_space_utas(exercise_qty,
exercise_id)
response["exercises"]["exercise_" + str(i)] = {}
response["exercises"]["exercise_" + str(i)]["questions"] = []
response["exercises"]["exercise_" + str(i)]["type"] = "multipleChoice"
while exercise_qty > 0:
if exercise_qty - 15 > 0:
qty = 15
else:
qty = exercise_qty
response["exercises"]["exercise_" + str(i)]["questions"].extend(
gen_multiple_choice_blank_space_utas(qty, exercise_id,
response["exercises"]["exercise_" + str(i)]["questions"])["questions"])
exercise_id = exercise_id + exercise_qty
exercise_qty = exercise_qty - qty
elif exercise_type == CustomLevelExerciseTypes.MULTIPLE_CHOICE_UNDERLINED.value:
response["exercises"]["exercise_" + str(i)] = gen_multiple_choice_underlined_utas(exercise_qty, exercise_id)
response["exercises"]["exercise_" + str(i)] = {}
response["exercises"]["exercise_" + str(i)]["questions"] = []
response["exercises"]["exercise_" + str(i)]["type"] = "multipleChoice"
while exercise_qty > 0:
if exercise_qty - 15 > 0:
qty = 15
else:
qty = exercise_qty
response["exercises"]["exercise_" + str(i)]["questions"].extend(
gen_multiple_choice_underlined_utas(qty, exercise_id,
response["exercises"]["exercise_" + str(i)]["questions"])["questions"])
exercise_id = exercise_id + exercise_qty
exercise_qty = exercise_qty - qty
elif exercise_type == CustomLevelExerciseTypes.BLANK_SPACE_TEXT.value:
response["exercises"]["exercise_" + str(i)] = gen_blank_space_text_utas(exercise_qty, exercise_id,
exercise_text_size)

124
helper/exercises.py
View File

@@ -1297,6 +1297,48 @@ def replace_exercise_if_exists_utas(all_exams, current_exercise, current_exam, s
return current_exercise, seen_keys
def replace_blank_space_exercise_if_exists_utas(all_exams, current_exercise, current_exam, seen_keys):
# Extracting relevant fields for comparison
key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options'])))
# 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)
else:
seen_keys.add(key)
for exam in all_exams:
if any(
exercise["prompt"] == current_exercise["prompt"] and
any(exercise["options"][0]["text"] == current_option["text"] for current_option in
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,
seen_keys)
return current_exercise, seen_keys
def replace_underlined_exercise_if_exists_utas(all_exams, current_exercise, current_exam, seen_keys):
# Extracting relevant fields for comparison
key = (current_exercise['prompt'], tuple(sorted(option['text'] for option in current_exercise['options'])))
# 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)
else:
seen_keys.add(key)
for exam in all_exams:
if any(
exercise["prompt"] == current_exercise["prompt"] and
any(exercise["options"][0]["text"] == current_option["text"] for current_option in
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,
seen_keys)
return current_exercise, seen_keys
def generate_single_mc_level_question():
messages = [
{
@@ -1322,6 +1364,64 @@ def generate_single_mc_level_question():
return question
def generate_single_mc_blank_space_level_question():
messages = [
{
"role": "system",
"content": (
'You are a helpful assistant designed to output JSON on this format: '
'{"id": "9", "options": [{"id": "A", "text": "And"}, {"id": "B", "text": "Cat"}, {"id": "C", "text": '
'"Happy"}, {"id": "D", "text": "Jump"}], "prompt": "Which of the following is a conjunction?", '
'"solution": "A", "variant": "text"}')
},
{
"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.')
}
]
token_count = count_total_tokens(messages)
question = make_openai_call(GPT_4_O, messages, token_count, ["options"],
GEN_QUESTION_TEMPERATURE)
return question
def generate_single_mc_underlined_level_question():
messages = [
{
"role": "system",
"content": (
'You are a helpful assistant designed to output JSON on this format: '
'{"id": "9", "options": [{"id": "A", "text": "And"}, {"id": "B", "text": "Cat"}, {"id": "C", "text": '
'"Happy"}, {"id": "D", "text": "Jump"}], "prompt": "Which of the following is a conjunction?", '
'"solution": "A", "variant": "text"}')
},
{
"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.')
},
{
"role": "user",
"content": (
'The type of multiple choice is the prompt has wrong words or group of words and the options are to '
'find the wrong word or group of words that are underlined in the prompt. \nExample:\n'
'Prompt: "I <u>complain</u> about my boss <u>all the time</u>, but my colleagues <u>thinks</u> the boss <u>is</u> nice."\n'
'Options:\na: "complain"\nb: "all the time"\nc: "thinks"\nd: "is"')
}
]
token_count = count_total_tokens(messages)
question = make_openai_call(GPT_4_O, messages, token_count, ["options"],
GEN_QUESTION_TEMPERATURE)
return question
def parse_conversation(conversation_data):
conversation_list = conversation_data.get('conversation', [])
readable_text = []
@@ -1364,12 +1464,12 @@ def gen_multiple_choice_blank_space_utas(quantity: int, start_id: int, all_exams
GEN_QUESTION_TEMPERATURE)
if len(question["questions"]) != quantity:
return gen_multiple_choice_level(quantity, start_id)
return gen_multiple_choice_blank_space_utas(quantity, start_id)
else:
if all_exams is not None:
seen_keys = set()
for i in range(len(question["questions"])):
question["questions"][i], seen_keys = replace_exercise_if_exists_utas(all_exams, question["questions"][i],
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)
@@ -1377,7 +1477,7 @@ def gen_multiple_choice_blank_space_utas(quantity: int, start_id: int, all_exams
return response
def gen_multiple_choice_underlined_utas(quantity: int, start_id: int):
def gen_multiple_choice_underlined_utas(quantity: int, start_id: int, all_exams=None):
json_format = {
"questions": [
{
@@ -1441,8 +1541,16 @@ def gen_multiple_choice_underlined_utas(quantity: int, start_id: int):
GEN_QUESTION_TEMPERATURE)
if len(question["questions"]) != quantity:
return gen_multiple_choice_level(quantity, start_id)
return gen_multiple_choice_underlined_utas(quantity, start_id)
else:
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)
response = fix_exercise_ids(question, start_id)
response["questions"] = randomize_mc_options_order(response["questions"])
return response
@@ -1603,7 +1711,7 @@ def gen_text_multiple_choice_utas(text: str, start_id: int, mc_quantity: int):
return response
def generate_level_mc(start_id: int, quantity: int):
def generate_level_mc(start_id: int, quantity: int, all_questions=None):
json_format = {
"questions": [
{
@@ -1654,6 +1762,12 @@ def generate_level_mc(start_id: int, quantity: int):
question = make_openai_call(GPT_4_O, messages, token_count, ["questions"],
GEN_QUESTION_TEMPERATURE)
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,
seen_keys)
response = fix_exercise_ids(question, start_id)
response["questions"] = randomize_mc_options_order(response["questions"])
return response