Add new writing question on generate questions
This commit is contained in:
Cristiano Ferreira
@@ -1926,7 +1926,6 @@ listening_section_2_to_insert_5 = {
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"section": 2
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"section": 2
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}
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}
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# NEW
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# NEW
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reading_to_insert_1 = {
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reading_to_insert_1 = {
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"parts": [
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"parts": [
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@@ -2587,6 +2586,43 @@ reading_to_insert_1 = {
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"type": "academic"
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"type": "academic"
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}
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}
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new_writing_to_insert_1 = {
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"exercises": [
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{
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"id": str(uuid.uuid4()),
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"prefix": "You should spend about 20 minutes on this task. \\nWrite a letter to your friend who is planning to "
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"visit your city:",
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"prompt": "Recommend places to visit and things to do, mention any local events or festivals happening during "
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"their visit and offer to meet and show them around.",
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"suffix": "You should write at least 100 words.",
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"type": "writing",
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"wordCounter": {
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"limit": 100,
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"type": "min"
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}
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},
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{
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"id": str(uuid.uuid4()),
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"prefix": "You should spend about 40 minutes on this task.\nPresent a written argument or case to an educated "
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"reader with no specialist knowledge of the following topic:",
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"prompt": "Some people believe that technology has made communication between individuals less personal and "
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"more impersonal. Others argue that technology has improved communication by making it more accessible. "
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"Discuss both viewpoints and give your own opinion.",
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"suffix": "You should write at least 250 words.\nUse your own ideas, knowledge and experience and support "
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"your arguments with examples and relevant evidence.",
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"type": "writing",
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"wordCounter": {
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"limit": 250,
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"type": "min"
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}
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}
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],
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"isDiagnostic": True,
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"minTimer": 60,
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"module": "writing",
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"type": "general"
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}
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# Falta section 3 e 4 do listening
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# Falta section 3 e 4 do listening
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# writing task 1 com imagens ...
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# writing task 1 com imagens ...
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# speaking 3 é discussao lol
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# speaking 3 é discussao lol
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@@ -2597,6 +2633,6 @@ db = firestore.client()
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# JSON data to insert
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# JSON data to insert
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# Add the JSON data to Firestore
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# Add the JSON data to Firestore
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collection_ref = db.collection('reading')
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collection_ref = db.collection('writing')
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document_ref = collection_ref.add(reading_to_insert_1)
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document_ref = collection_ref.add(new_writing_to_insert_1)
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print(f"Document added with ID: {document_ref}")
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print(f"Document added with ID: {document_ref}")
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@@ -1,102 +1,174 @@
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import random
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from functools import reduce
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import openai
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import openai
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import os
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import os
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from dotenv import load_dotenv
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from dotenv import load_dotenv
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from app import GRADING_FIELDS, GRADING_TEMPERATURE
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from helper.api_messages import get_grading_messages, QuestionType
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from helper.openai_interface import make_openai_call, process_response
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from helper.token_counter import count_tokens
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load_dotenv()
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load_dotenv()
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openai.api_key = os.getenv("OPENAI_API_KEY")
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openai.api_key = os.getenv("OPENAI_API_KEY")
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question = "The average standard of people's health is likely to be lower in the future than it is now. To what extent do " \
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"you agree or disagree with this statement?"
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answer = "I completely disagree with the written statement. I believe that most of the people in the world have more information " \
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"about their health and also about how they can improve their healthy conditions. Nowadays, information about " \
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"how harmful is to smoke for our bodies can be seen in many packets of cigars. This is a clear example how " \
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"things can change from our recent past. There is a clear trend in the diminishing of smokers and if this " \
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"continues it will have a positive impact in our health. On the other hand, the alimentation habbits are " \
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"changing all over the world and this can affect people’s health. However every one can choose what to eat " \
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"every day. Mostly everybody, from developed societies, know the importance of having a healthy diet. Advances " \
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"such as the information showed in the menus of fast food restaurants will help people to have a clever choice " \
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"before they choose what to eat. Another important issue that I would like to mention is how medicine is changing. " \
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"There are new discovers and treatments almost every week and that is an inequivoque sintom of how things are " \
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"changing in order to improve the world’s health."
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def generate_summarizer(
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# messages = get_grading_messages(QuestionType.WRITING_TASK_2, question, answer)
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max_tokens,
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# token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
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temperature,
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# map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
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top_p,
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# response = make_openai_call("gpt-4", messages, token_count, GRADING_FIELDS, GRADING_TEMPERATURE)
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frequency_penalty,
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question_type,
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grade_wt2_message = "You are a IELTS examiner. " \
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question,
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"The question you have to grade is of type Writing Task 2 and is the following:" + question + \
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answer
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"Assess this answer according to the IELTS grading system. It is mandatory for you to provide your response" \
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):
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" with the overall grade and breakdown grades, with just the following json format: {'comment': 'Comment about " \
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res = openai.ChatCompletion.create(
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"answer quality will go here', 'overall': 7.0, 'task_response': {'Task Achievement': 8.0, " \
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model="gpt-3.5-turbo",
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"'Coherence and Cohesion': 6.5, 'Lexical Resource': 7.5, 'Grammatical Range and Accuracy': 6.0}} " \
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max_tokens=int(max_tokens),
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"Evaluate this answer according to ielts grading system: " + answer
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temperature=float(temperature),
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top_p=float(top_p),
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frequency_penalty=float(frequency_penalty),
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messages=
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[
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{
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"role": "user",
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"content": "You are a IELTS examiner.",
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},
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{
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"role": "user",
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"content": f"The question you have to grade is of type {question_type} and is the following: {question}",
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},
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{
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"role": "user",
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"content": "Please provide a JSON object response with the overall grade and breakdown grades, "
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"formatted as follows: {'overall': 7.0, 'task_response': {'Task Achievement': 8.0, "
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"'Coherence and Cohesion': 6.5, 'Lexical Resource': 7.5, 'Grammatical Range and Accuracy': "
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"6.0}}",
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},
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{
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"role": "user",
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"content": "Don't give explanations for the grades, just provide the json with the grades.",
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},
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{
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"role": "user",
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"content": f"Evaluate this answer according to ielts grading system: {answer}",
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},
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],
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)
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return res["choices"][0]["message"]["content"]
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import streamlit as st
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topics = [
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"Art and Creativity",
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"History of Ancient Civilizations",
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"Environmental Conservation",
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"Space Exploration",
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"Artificial Intelligence",
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"Climate Change",
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"World Religions",
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"The Human Brain",
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"Renewable Energy",
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"Cultural Diversity",
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"Modern Technology Trends",
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"Women's Rights",
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"Sustainable Agriculture",
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"Globalization",
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"Natural Disasters",
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"Cybersecurity",
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"Philosophy of Ethics",
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"Robotics",
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"Health and Wellness",
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"Literature and Classics",
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"World Geography",
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"Music and Its Influence",
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"Human Rights",
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"Social Media Impact",
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"Food Sustainability",
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"Economics and Markets",
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"Human Evolution",
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"Political Systems",
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"Mental Health Awareness",
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"Quantum Physics",
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"Biodiversity",
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"Education Reform",
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"Animal Rights",
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"The Industrial Revolution",
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"Future of Work",
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"Film and Cinema",
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"Genetic Engineering",
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"Ancient Mythology",
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"Climate Policy",
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"Space Travel",
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"Renewable Energy Sources",
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"Cultural Heritage Preservation",
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"Modern Art Movements",
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"Immigration Issues",
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"Sustainable Transportation",
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"The History of Medicine",
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"Artificial Neural Networks",
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"Climate Adaptation",
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"Philosophy of Existence",
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"Augmented Reality",
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"Yoga and Meditation",
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"Literary Genres",
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"World Oceans",
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"Gender Equality",
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"Social Networking",
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"Sustainable Fashion",
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"International Trade",
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"Prehistoric Era",
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"Democracy and Governance",
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"Postcolonial Literature",
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"Geopolitics",
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"Psychology and Behavior",
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"Nanotechnology",
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"Endangered Species",
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"Education Technology",
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"Renaissance Art",
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"Renewable Energy Policy",
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"Cultural Festivals",
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"Modern Architecture",
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"Climate Resilience",
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"Artificial Life",
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"Fitness and Nutrition",
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"Classic Literature Adaptations",
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"World History Wars",
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"Ethical Dilemmas",
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"Internet of Things (IoT)",
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"Meditation Practices",
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"Literary Symbolism",
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"Marine Conservation",
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"Social Justice Movements",
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"Sustainable Tourism",
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"International Finance",
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"Ancient Philosophy",
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"Cold War Era",
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"Behavioral Economics",
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"Space Colonization",
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"Clean Energy Initiatives",
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"Cultural Exchange",
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"Modern Sculpture",
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"Climate Mitigation",
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"Artificial Intelligence Ethics",
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"Mindfulness",
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"Literary Criticism",
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"Wildlife Conservation",
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"Political Activism",
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"Renewable Energy Innovations",
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"History of Mathematics",
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"Human-Computer Interaction",
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"Global Health",
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"Cultural Appropriation"
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]
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# Set the application title
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gen_listening2_message = "You are an IELTS program designed to assist with language learning. Your task is to provide a detailed " \
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st.title("GPT-3.5 IELTS Examiner")
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"transcript of a monologue on the subject of " + random.choice(topics) + ". Ensure that the transcript is comprehensive " \
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"and covers the topic " \
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"thoroughly.After the transcript, you should generate a fill in the blanks " \
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"exercise with six statements related to the content of the monologue. The blank spaces in the exercise should " \
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"be identified by {{number}}. Finally, provide the answers for the exercise." \
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"Response Format (JSON): { 'transcript': 'Transcript of the monologue on a specific subject with a minimum of 500 words.', 'exercise': {" \
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"'statements': { '1': 'Statement 1 with a blank space to fill.', '2': 'Statement 2 with a blank space to fill.'," \
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"'3': 'Statement 3 with a blank space to fill.', '4': 'Statement 4 with a blank space to fill.', " \
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"'5': 'Statement 5 with a blank space to fill.', '6': 'Statement 6 with a blank space to fill.' }, " \
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"'answers': { '1': 'Answer to fill the blank space in statement 1.', " \
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"'2': 'Answer to fill the blank space in statement 2.', '3': 'Answer to fill the blank space in statement 3.'," \
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"'4': 'Answer to fill the blank space in statement 4.', '5': 'Answer to fill the blank space in statement 5.'," \
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"'6': 'Answer to fill the blank space in statement 6.' } } }"
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# qt_col, q_col = st.columns(2)
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token_count = count_tokens(gen_listening2_message)["n_tokens"]
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# Selection box to select the question type
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response = openai.Completion.create(
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# with qt_col:
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model="gpt-3.5-turbo-instruct",
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question_type = st.selectbox(
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prompt=gen_listening2_message,
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"What is the question type?",
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max_tokens=int(4097 - token_count - 300),
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(
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temperature=0.7
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"Listening",
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)["choices"][0]["text"]
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"Reading",
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"Writing Task 1",
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"Writing Task 2",
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"Speaking Part 1",
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"Speaking Part 2"
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),
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)
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# Provide the input area for question to be answered
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# processed = process_response(response, "comment")
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# with q_col:
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processed = process_response(response, "transcript")
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question = st.text_area("Enter the question:", height=100)
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print(processed)
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# Provide the input area for text to be summarized
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answer = st.text_area("Enter the answer:", height=100)
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# Initiate two columns for section to be side-by-side
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# col1, col2 = st.columns(2)
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# Slider to control the model hyperparameter
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# with col1:
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token = st.slider("Token", min_value=0.0, max_value=2000.0, value=1000.0, step=1.0)
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temp = st.slider("Temperature", min_value=0.0, max_value=1.0, value=0.7, step=0.01)
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top_p = st.slider("Top_p", min_value=0.0, max_value=1.0, value=0.9, step=0.01)
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f_pen = st.slider("Frequency Penalty", min_value=-1.0, max_value=1.0, value=0.5, step=0.01)
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# Showing the current parameter used for the model
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# with col2:
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with st.expander("Current Parameter"):
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st.write("Current Token :", token)
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st.write("Current Temperature :", temp)
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st.write("Current Nucleus Sampling :", top_p)
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st.write("Current Frequency Penalty :", f_pen)
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# Creating button for execute the text summarization
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if st.button("Grade"):
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st.write(generate_summarizer(token, temp, top_p, f_pen, question_type, question, answer))
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