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Add endpoints to save questions to db.

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This commit is contained in:
Cristiano Ferreira
2023-09-06 22:53:09 +01:00
parent 680ec00885
commit 8f9b65281e
2 changed files with 196 additions and 89 deletions
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218
app.py
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@@ -2,11 +2,12 @@ from flask import Flask, request
from flask_jwt_extended import JWTManager, jwt_required
from functools import reduce
import firebase_admin
from firebase_admin import credentials
from firebase_admin import credentials, firestore
from helper.api_messages import QuestionType, get_grading_messages, get_question_gen_messages, get_question_tips
from helper.file_helper import delete_files_older_than_one_day
from helper.firebase_helper import download_firebase_file, upload_file_firebase, upload_file_firebase_get_url, \
save_to_db
from helper.heygen_api import create_video
from helper.speech_to_text_helper import speech_to_text, text_to_speech, has_words
from helper.token_counter import count_tokens
from helper.openai_interface import make_openai_call
@@ -16,7 +17,8 @@ import re
from dotenv import load_dotenv
from templates.question_templates import getListening1Template, getListening2Template
from templates.question_templates import getListening1Template, getListening2Template, getSpeaking1Template, \
getSpeaking2Template, getSpeaking3Template
load_dotenv()
@@ -42,6 +44,8 @@ FIREBASE_BUCKET = 'mti-ielts.appspot.com'
AUDIO_FILES_PATH = 'download-audio/'
FIREBASE_LISTENING_AUDIO_FILES_PATH = 'listening_recordings/'
VIDEO_FILES_PATH = 'download-video/'
FIREBASE_SPEAKING_VIDEO_FILES_PATH = 'speaking_videos/'
@app.route('/listening_section_1', methods=['GET'])
@jwt_required()
@@ -52,12 +56,6 @@ def get_listening_section_1_question():
map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
GEN_QUESTION_TEMPERATURE)
# file_name = str(uuid.uuid4()) + ".mp3"
# sound_file_path = AUDIO_FILES_PATH + file_name
# firebase_file_path = FIREBASE_LISTENING_AUDIO_FILES_PATH + file_name
# text_to_speech(response["transcript"], sound_file_path)
# upload_file_firebase(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
# response["audio_file"] = firebase_file_path
return response
except Exception as e:
return str(e)
@@ -94,13 +92,6 @@ def get_listening_section_2_question():
map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
GEN_QUESTION_TEMPERATURE)
# file_name = str(uuid.uuid4()) + ".mp3"
# sound_file_path = AUDIO_FILES_PATH + file_name
# firebase_file_path = FIREBASE_LISTENING_AUDIO_FILES_PATH + file_name
# text_to_speech(response["transcript"], sound_file_path)
# upload_file_firebase(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
# response["audio_file"] = firebase_file_path
return response
except Exception as e:
return str(e)
@@ -136,13 +127,6 @@ def get_listening_section_3_question():
map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
GEN_QUESTION_TEMPERATURE)
# file_name = str(uuid.uuid4()) + ".mp3"
# sound_file_path = AUDIO_FILES_PATH + file_name
# firebase_file_path = FIREBASE_LISTENING_AUDIO_FILES_PATH + file_name
# text_to_speech(response["transcript"], sound_file_path)
# upload_file_firebase(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
# response["audio_file"] = firebase_file_path
return response
except Exception as e:
return str(e)
@@ -178,13 +162,6 @@ def get_listening_section_4_question():
map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
GEN_QUESTION_TEMPERATURE)
# file_name = str(uuid.uuid4()) + ".mp3"
# sound_file_path = AUDIO_FILES_PATH + file_name
# firebase_file_path = FIREBASE_LISTENING_AUDIO_FILES_PATH + file_name
# text_to_speech(response["transcript"], sound_file_path)
# upload_file_firebase(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
# response["audio_file"] = firebase_file_path
return response
except Exception as e:
return str(e)
@@ -281,29 +258,6 @@ def grade_writing_task_2():
except Exception as e:
return str(e)
@app.route('/fetch_tips', methods=['POST'])
@jwt_required()
def fetch_answer_tips():
try:
data = request.get_json()
context = data.get('context')
question = data.get('question')
answer = data.get('answer')
correct_answer = data.get('correct_answer')
messages = get_question_tips(question, answer, correct_answer, context)
token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
response = make_openai_call(GPT_3_5_TURBO, messages, token_count, None, TIPS_TEMPERATURE)
if isinstance(response, str):
response = re.sub(r"^[a-zA-Z0-9_]+\:\s*", "", response)
return response
except Exception as e:
return str(e)
@app.route('/writing_task2', methods=['GET'])
@jwt_required()
def get_writing_task_2_question():
@@ -378,6 +332,52 @@ def get_speaking_task_1_question():
except Exception as e:
return str(e)
@app.route('/save_speaking_task_1', methods=['POST'])
@jwt_required()
def save_speaking_task_1_question():
try:
# data = request.get_json()
# question = data.get('question')
questions_json = getSpeaking1Template()
questions = []
for question in questions_json["questions"]:
result = create_video(question)
if result is not None:
sound_file_path = VIDEO_FILES_PATH + result
firebase_file_path = FIREBASE_SPEAKING_VIDEO_FILES_PATH + result
url = upload_file_firebase_get_url(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
video = {
"text": question,
"video_path": firebase_file_path,
"video_url": url
}
questions.append(video)
else:
print("Failed to create video for question: " + question)
if len(questions) == len(questions_json["questions"]):
speaking_pt1_to_insert = {
"exercises": [
{
"id": str(uuid.uuid4()),
"prompts": questions,
"text": "Listen carefully and respond.",
"title": questions_json["topic"],
"type": "speakingPart1"
}
],
"isDiagnostic": True,
"minTimer": 5,
"module": "speaking"
}
if save_to_db("speaking", speaking_pt1_to_insert):
return speaking_pt1_to_insert
else:
raise Exception("Failed to save question: " + speaking_pt1_to_insert)
else:
raise Exception("Array sizes do not match. Video uploading failing is probably the cause.")
except Exception as e:
return str(e)
@app.route('/speaking_task_2', methods=['POST'])
@jwt_required()
@@ -426,6 +426,120 @@ def get_speaking_task_2_question():
except Exception as e:
return str(e)
@app.route('/save_speaking_task_2', methods=['POST'])
@jwt_required()
def save_speaking_task_2_question():
try:
# data = request.get_json()
# question = data.get('question')
questions_json = getSpeaking2Template()
questions = []
for question in questions_json["questions"]:
result = create_video(question)
if result is not None:
sound_file_path = VIDEO_FILES_PATH + result
firebase_file_path = FIREBASE_SPEAKING_VIDEO_FILES_PATH + result
url = upload_file_firebase_get_url(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
video = {
"text": question,
"video_path": firebase_file_path,
"video_url": url
}
questions.append(video)
else:
print("Failed to create video for question: " + question)
if len(questions) == len(questions_json["questions"]):
speaking_pt2_to_insert = {
"exercises": [
{
"id": str(uuid.uuid4()),
"prompts": questions,
"text": "Listen carefully and respond.",
"title": questions_json["topic"],
"type": "speakingPart2"
}
],
"isDiagnostic": True,
"minTimer": 5,
"module": "speaking"
}
if save_to_db("speaking", speaking_pt2_to_insert):
return speaking_pt2_to_insert
else:
raise Exception("Failed to save question: " + str(speaking_pt2_to_insert))
else:
raise Exception("Array sizes do not match. Video uploading failing is probably the cause.")
except Exception as e:
return str(e)
@app.route('/save_speaking_task_3', methods=['POST'])
@jwt_required()
def save_speaking_task_3_question():
try:
# data = request.get_json()
# question = data.get('question')
questions_json = getSpeaking3Template()
questions = []
for question in questions_json["questions"]:
result = create_video(question)
if result is not None:
sound_file_path = VIDEO_FILES_PATH + result
firebase_file_path = FIREBASE_SPEAKING_VIDEO_FILES_PATH + result
url = upload_file_firebase_get_url(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
video = {
"text": question,
"video_path": firebase_file_path,
"video_url": url
}
questions.append(video)
else:
print("Failed to create video for question: " + question)
if len(questions) == len(questions_json["questions"]):
speaking_pt3_to_insert = {
"exercises": [
{
"id": str(uuid.uuid4()),
"prompts": questions,
"text": "Listen carefully and respond.",
"title": questions_json["topic"],
"type": "speakingPart3"
}
],
"isDiagnostic": True,
"minTimer": 5,
"module": "speaking"
}
if save_to_db("speaking", speaking_pt3_to_insert):
return speaking_pt3_to_insert
else:
raise Exception("Failed to save question: " + str(speaking_pt3_to_insert))
else:
raise Exception("Array sizes do not match. Video uploading failing is probably the cause.")
except Exception as e:
return str(e)
@app.route('/fetch_tips', methods=['POST'])
@jwt_required()
def fetch_answer_tips():
try:
data = request.get_json()
context = data.get('context')
question = data.get('question')
answer = data.get('answer')
correct_answer = data.get('correct_answer')
messages = get_question_tips(question, answer, correct_answer, context)
token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
response = make_openai_call(GPT_3_5_TURBO, messages, token_count, None, TIPS_TEMPERATURE)
if isinstance(response, str):
response = re.sub(r"^[a-zA-Z0-9_]+\:\s*", "", response)
return response
except Exception as e:
return str(e)
if __name__ == '__main__':
app.run()