267 lines
11 KiB
Python
267 lines
11 KiB
Python
from flask import Flask, request
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from flask_jwt_extended import JWTManager, jwt_required
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from functools import reduce
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import firebase_admin
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from firebase_admin import credentials
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from helper.api_messages import QuestionType, get_grading_messages, get_question_gen_messages, get_question_tips
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from helper.file_helper import delete_files_older_than_one_day
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from helper.firebase_helper import download_firebase_file, upload_file_firebase
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from helper.speech_to_text_helper import speech_to_text, text_to_speech
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from helper.token_counter import count_tokens
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from helper.openai_interface import make_openai_call
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import os
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import uuid
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import re
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from dotenv import load_dotenv
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load_dotenv()
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app = Flask(__name__)
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app.config['JWT_SECRET_KEY'] = os.getenv("JWT_SECRET_KEY")
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jwt = JWTManager(app)
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# Initialize Firebase Admin SDK
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cred = credentials.Certificate(os.getenv("GOOGLE_APPLICATION_CREDENTIALS"))
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firebase_admin.initialize_app(cred)
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GRADING_TEMPERATURE = 0.1
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TIPS_TEMPERATURE = 0.2
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GEN_QUESTION_TEMPERATURE = 0.9
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GPT_3_5_TURBO = "gpt-3.5-turbo"
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GPT_3_5_TURBO_16K = "gpt-3.5-turbo-16k"
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GRADING_FIELDS = ['comment', 'overall', 'task_response']
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GEN_FIELDS = ['question']
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LISTENING_GEN_FIELDS = ['transcript', 'exercise']
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FIREBASE_BUCKET = 'mti-ielts.appspot.com'
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AUDIO_FILES_PATH = 'download-audio/'
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FIREBASE_LISTENING_AUDIO_FILES_PATH = 'listening_recordings/'
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@app.route('/listening_section_1', methods=['GET'])
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@jwt_required()
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def get_listening_section_1_question():
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try:
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messages = get_question_gen_messages(QuestionType.LISTENING_SECTION_1)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
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GEN_QUESTION_TEMPERATURE)
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return response
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except Exception as e:
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return str(e)
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@app.route('/listening_section_2', methods=['GET'])
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@jwt_required()
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def get_listening_section_2_question():
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try:
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delete_files_older_than_one_day(AUDIO_FILES_PATH)
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messages = get_question_gen_messages(QuestionType.LISTENING_SECTION_2)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
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GEN_QUESTION_TEMPERATURE)
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# file_name = str(uuid.uuid4()) + ".mp3"
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# sound_file_path = AUDIO_FILES_PATH + file_name
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# firebase_file_path = FIREBASE_LISTENING_AUDIO_FILES_PATH + file_name
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# text_to_speech(response["transcript"], sound_file_path)
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# upload_file_firebase(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
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# response["audio_file"] = firebase_file_path
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return response
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except Exception as e:
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return str(e)
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@app.route('/listening_section_3', methods=['GET'])
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@jwt_required()
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def get_listening_section_3_question():
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try:
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delete_files_older_than_one_day(AUDIO_FILES_PATH)
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messages = get_question_gen_messages(QuestionType.LISTENING_SECTION_3)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
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GEN_QUESTION_TEMPERATURE)
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# file_name = str(uuid.uuid4()) + ".mp3"
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# sound_file_path = AUDIO_FILES_PATH + file_name
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# firebase_file_path = FIREBASE_LISTENING_AUDIO_FILES_PATH + file_name
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# text_to_speech(response["transcript"], sound_file_path)
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# upload_file_firebase(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
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# response["audio_file"] = firebase_file_path
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return response
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except Exception as e:
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return str(e)
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@app.route('/listening_section_4', methods=['GET'])
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@jwt_required()
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def get_listening_section_4_question():
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try:
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delete_files_older_than_one_day(AUDIO_FILES_PATH)
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messages = get_question_gen_messages(QuestionType.LISTENING_SECTION_4)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO_16K, messages, token_count, LISTENING_GEN_FIELDS,
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GEN_QUESTION_TEMPERATURE)
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# file_name = str(uuid.uuid4()) + ".mp3"
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# sound_file_path = AUDIO_FILES_PATH + file_name
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# firebase_file_path = FIREBASE_LISTENING_AUDIO_FILES_PATH + file_name
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# text_to_speech(response["transcript"], sound_file_path)
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# upload_file_firebase(FIREBASE_BUCKET, firebase_file_path, sound_file_path)
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# response["audio_file"] = firebase_file_path
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return response
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except Exception as e:
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return str(e)
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@app.route('/writing_task1', methods=['POST'])
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@jwt_required()
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def grade_writing_task_1():
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try:
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data = request.get_json()
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question = data.get('question')
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context = data.get('context')
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answer = data.get('answer')
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messages = get_grading_messages(QuestionType.WRITING_TASK_1, question, answer, context)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
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return response
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except Exception as e:
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return str(e)
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@app.route('/writing_task2', methods=['POST'])
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@jwt_required()
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def grade_writing_task_2():
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try:
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data = request.get_json()
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question = data.get('question')
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answer = data.get('answer')
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messages = get_grading_messages(QuestionType.WRITING_TASK_2, question, answer)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
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return response
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except Exception as e:
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return str(e)
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@app.route('/fetch_tips', methods=['POST'])
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@jwt_required()
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def fetch_answer_tips():
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try:
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data = request.get_json()
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context = data.get('context')
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question = data.get('question')
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answer = data.get('answer')
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correct_answer = data.get('correct_answer')
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messages = get_question_tips(question, answer, correct_answer, context)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, None, TIPS_TEMPERATURE)
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if isinstance(response, str):
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response = re.sub(r"^[a-zA-Z0-9_]+\:\s*", "", response)
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return response
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except Exception as e:
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return str(e)
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@app.route('/writing_task2', methods=['GET'])
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@jwt_required()
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def get_writing_task_2_question():
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try:
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messages = get_question_gen_messages(QuestionType.WRITING_TASK_2)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GEN_FIELDS, GEN_QUESTION_TEMPERATURE)
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return response
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except Exception as e:
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return str(e)
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@app.route('/speaking_task_1', methods=['POST'])
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@jwt_required()
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def grade_speaking_task_1():
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delete_files_older_than_one_day(AUDIO_FILES_PATH)
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sound_file_name = AUDIO_FILES_PATH + str(uuid.uuid4())
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try:
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data = request.get_json()
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question = data.get('question')
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answer_firebase_path = data.get('answer')
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download_firebase_file(FIREBASE_BUCKET, answer_firebase_path, sound_file_name)
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answer = speech_to_text(sound_file_name)
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messages = get_grading_messages(QuestionType.SPEAKING_1, question, answer)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
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os.remove(sound_file_name)
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return response
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except Exception as e:
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os.remove(sound_file_name)
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return str(e)
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@app.route('/speaking_task_1', methods=['GET'])
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@jwt_required()
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def get_speaking_task_1_question():
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try:
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messages = get_question_gen_messages(QuestionType.SPEAKING_1)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GEN_FIELDS, GEN_QUESTION_TEMPERATURE)
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return response
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except Exception as e:
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return str(e)
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@app.route('/speaking_task_2', methods=['POST'])
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@jwt_required()
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def grade_speaking_task_2():
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delete_files_older_than_one_day(AUDIO_FILES_PATH)
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sound_file_name = AUDIO_FILES_PATH + str(uuid.uuid4())
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try:
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data = request.get_json()
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question = data.get('question')
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answer_firebase_path = data.get('answer')
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download_firebase_file(FIREBASE_BUCKET, answer_firebase_path, sound_file_name)
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answer = speech_to_text(sound_file_name)
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messages = get_grading_messages(QuestionType.SPEAKING_2, question, answer)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
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os.remove(sound_file_name)
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return response
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except Exception as e:
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os.remove(sound_file_name)
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return str(e)
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@app.route('/speaking_task_2', methods=['GET'])
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@jwt_required()
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def get_speaking_task_2_question():
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try:
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messages = get_question_gen_messages(QuestionType.SPEAKING_2)
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token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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response = make_openai_call(GPT_3_5_TURBO, messages, token_count, GEN_FIELDS, GEN_QUESTION_TEMPERATURE)
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return response
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except Exception as e:
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return str(e)
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if __name__ == '__main__':
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app.run()
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