EnCoach Odoo 19 custom modules
Full backend implementation with custom Odoo modules: - encoach_api: Core API, user management, JWT auth - encoach_exam: Exam generation (reading, writing, listening, speaking) - encoach_evaluate: AI-powered evaluation (writing, speaking) - encoach_training: Training tips and walkthrough - encoach_storage: File storage management - encoach_payment: Stripe, PayPal, Paymob integration - encoach_mail: Email notifications Made-with: Cursor
This commit is contained in:
Talal Sharabi
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encoach_ai_generation/__init__.py
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encoach_ai_generation/__init__.py
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from . import services
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encoach_ai_generation/__manifest__.py
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encoach_ai_generation/__manifest__.py
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{
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"name": "EnCoach AI Generation",
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"version": "19.0.1.0.0",
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"category": "Education",
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"summary": "AI-powered IELTS exam content generation",
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"description": "Reading passages, listening dialogs, writing/speaking tasks, level exercises.",
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"depends": ["encoach_ai", "encoach_exam"],
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"data": [
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"security/ir.model.access.csv",
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],
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"installable": True,
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"license": "LGPL-3",
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}
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encoach_ai_generation/security/ir.model.access.csv
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encoach_ai_generation/security/ir.model.access.csv
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id,name,model_id:id,group_id:id,perm_read,perm_write,perm_create,perm_unlink
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encoach_ai_generation/services/__init__.py
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encoach_ai_generation/services/__init__.py
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from . import generation_service
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encoach_ai_generation/services/generation_service.py
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encoach_ai_generation/services/generation_service.py
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import json
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import logging
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import random
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from odoo.addons.encoach_ai.models.constants import (
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CEFR_LEVELS,
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GPT_MODELS,
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TEMPERATURE,
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TOPICS,
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)
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from odoo.addons.encoach_ai.services.openai_service import EncoachOpenAIService
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_logger = logging.getLogger(__name__)
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PASSAGE_DIFFICULTY = {
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1: "fairly easy and consist of multiple paragraphs",
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2: "fairly hard and consist of multiple paragraphs",
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3: (
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"very hard, present different points or theories, "
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"cite different sources, and consist of multiple paragraphs"
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),
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}
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LISTENING_SECTION_CONFIG = {
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1: {
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"type": "conversation",
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"format": '{"conversation": [{"name": "name", "gender": "gender", "text": "text"}]}',
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"prompt": (
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"Compose an authentic conversation between two individuals "
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'on the topic of "{topic}". Please include random names and genders. '
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"Include misleading discourse (dates, colors, etc.) and spelling of names. "
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"Make sure that the generated conversation does not contain "
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"forbidden subjects in muslim countries."
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),
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},
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2: {
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"type": "monologue",
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"format": '{"monologue": "monologue"}',
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"prompt": (
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"Generate a comprehensive monologue set in the social context "
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'of "{topic}". Make sure that the generated monologue does not '
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"contain forbidden subjects in muslim countries."
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),
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},
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3: {
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"type": "conversation",
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"format": '{"conversation": [{"name": "name", "gender": "gender", "text": "text"}]}',
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"prompt": (
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"Compose an authentic and elaborate conversation between "
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'up to four individuals on the topic of "{topic}". '
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"Please include random names and genders. Make sure that the "
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"generated conversation does not contain forbidden subjects "
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"in muslim countries."
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),
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},
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4: {
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"type": "monologue",
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"format": '{"monologue": "monologue"}',
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"prompt": (
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"Generate a comprehensive and complex monologue on the academic "
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'subject of "{topic}". Make sure that the generated monologue '
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"does not contain forbidden subjects in muslim countries."
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),
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},
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}
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class EncoachGenerationService:
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def __init__(self, env):
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self.env = env
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self.ai = EncoachOpenAIService(env)
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# ------------------------------------------------------------------
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# Reading
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# ------------------------------------------------------------------
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def generate_reading_passage(self, passage_num, topic=None, word_count=500):
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"""Generate an IELTS reading passage (passage 1, 2, or 3)."""
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topic = topic or random.choice(TOPICS)
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difficulty = PASSAGE_DIFFICULTY.get(passage_num, PASSAGE_DIFFICULTY[1])
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system_msg = (
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"You are a helpful assistant designed to output JSON on this format: "
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'{"title": "title of the text", "text": "generated text"}'
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)
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user_msg = (
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f"Generate an extensive text for IELTS Reading Passage {passage_num}, "
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f'of at least {word_count} words, on the topic of "{topic}". '
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"The passage should offer a substantial amount of information "
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f"relevant to the chosen subject matter. It should be {difficulty}. "
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"Make sure that the generated text does not contain forbidden "
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"subjects in muslim countries."
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)
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return self.ai.prediction(
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model=GPT_MODELS["generation"],
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messages=[
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{"role": "system", "content": system_msg},
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{"role": "user", "content": user_msg},
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],
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temperature=TEMPERATURE["generation"],
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fields_to_check=["title", "text"],
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)
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def generate_reading_exercises(self, text, exercises_config, difficulty):
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"""Generate exercises for a reading passage.
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exercises_config: list of dicts with 'type' and 'quantity' keys.
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difficulty: CEFR level string.
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"""
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system_msg = (
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"You are a helpful assistant designed to output JSON. "
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"Generate reading comprehension exercises based on the given text."
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)
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config_str = json.dumps(exercises_config)
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user_msg = (
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f"Based on the following text, generate exercises according to this "
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f"configuration: {config_str}. Target CEFR level: {difficulty}.\n\n"
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f'Text: "{text}"'
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)
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return self.ai.prediction(
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model=GPT_MODELS["generation"],
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messages=[
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{"role": "system", "content": system_msg},
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{"role": "user", "content": user_msg},
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],
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temperature=TEMPERATURE["generation"],
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)
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# ------------------------------------------------------------------
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# Listening
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# ------------------------------------------------------------------
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def generate_listening_dialog(self, section, topic=None, difficulty=None):
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"""Generate a listening dialog/monologue for the given section (1-4)."""
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topic = topic or random.choice(TOPICS)
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config = LISTENING_SECTION_CONFIG.get(section, LISTENING_SECTION_CONFIG[1])
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system_msg = (
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"You are a helpful assistant designed to output JSON on this format: "
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+ config["format"]
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)
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user_msg = config["prompt"].format(topic=topic)
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if difficulty:
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user_msg += f" Target CEFR level: {difficulty}."
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return self.ai.prediction(
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model=GPT_MODELS["generation"],
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messages=[
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{"role": "system", "content": system_msg},
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{"role": "user", "content": user_msg},
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],
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temperature=TEMPERATURE["generation"],
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)
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def generate_listening_exercises(self, text, exercises_config, difficulty):
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"""Generate exercises for a listening transcript."""
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system_msg = (
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"You are a helpful assistant designed to output JSON. "
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"Generate listening comprehension exercises based on the given transcript."
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)
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config_str = json.dumps(exercises_config)
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user_msg = (
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f"Based on the following transcript, generate exercises according to "
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f"this configuration: {config_str}. Target CEFR level: {difficulty}.\n\n"
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f'Transcript: "{text}"'
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)
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return self.ai.prediction(
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model=GPT_MODELS["generation"],
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messages=[
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{"role": "system", "content": system_msg},
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{"role": "user", "content": user_msg},
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],
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temperature=TEMPERATURE["generation"],
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)
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# ------------------------------------------------------------------
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# Writing
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# ------------------------------------------------------------------
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def generate_writing_task(
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self, task, topic=None, difficulty=None, task_type="general"
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):
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"""Generate a writing task prompt.
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task: 1 or 2
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task_type: 'general' or 'academic'
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"""
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topic = topic or random.choice(TOPICS)
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difficulty = difficulty or random.choice(CEFR_LEVELS)
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system_msg = (
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"You are a helpful assistant designed to output JSON on this format: "
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'{"question": "the generated writing task prompt"}'
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)
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if task == 1 and task_type == "general":
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user_msg = (
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"Craft a prompt for an IELTS Writing Task 1 General Training "
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"exercise that instructs the student to compose a letter based "
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f'on the topic of "{topic}" of {difficulty} CEFR level difficulty. '
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'The prompt should end with "In the letter you should" followed '
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"by 3 bullet points. Make sure it does not contain forbidden "
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"subjects in muslim countries."
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)
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elif task == 2:
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user_msg = (
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f"Craft a comprehensive question of {difficulty} CEFR level "
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"difficulty like the ones for IELTS Writing Task 2 General "
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"Training that directs the candidate to delve into an in-depth "
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"analysis of contrasting perspectives on the topic of "
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f'"{topic}". The question should lead to an answer with either '
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'"theories", "complicated information" or be "very descriptive" '
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"on the topic."
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)
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else:
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user_msg = (
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"Analyze the uploaded image and create a detailed IELTS Writing "
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"Task 1 Academic prompt. Describe the visual type, context, and "
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f"create a prompt at {difficulty} CEFR level."
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)
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return self.ai.prediction(
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model=GPT_MODELS["generation"],
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messages=[
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{"role": "system", "content": system_msg},
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{"role": "user", "content": user_msg},
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],
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temperature=TEMPERATURE["generation"],
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fields_to_check=["question"],
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)
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# ------------------------------------------------------------------
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# Speaking
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# ------------------------------------------------------------------
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def generate_speaking_task(
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self,
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part,
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topic=None,
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first_topic=None,
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second_topic=None,
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difficulty=None,
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):
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"""Generate a speaking task for the given part (1, 2, or 3)."""
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system_msg = (
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"You are a helpful assistant designed to output JSON. "
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"Generate IELTS speaking task questions."
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)
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if part == 1:
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first_topic = first_topic or random.choice(TOPICS)
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second_topic = second_topic or random.choice(TOPICS)
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user_msg = (
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"Craft 5 simple and single questions of easy difficulty for "
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"IELTS Speaking Part 1 that encourages candidates to delve "
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"deeply into personal experiences, preferences, or insights "
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f'on the topic of "{first_topic}" and the topic of '
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f'"{second_topic}". The questions should lead to the usage '
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"of 4 verb tenses (present perfect, present, past and future). "
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"Make sure that the generated question does not contain "
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"forbidden subjects in muslim countries."
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)
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elif part == 2:
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topic = topic or random.choice(TOPICS)
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user_msg = (
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"Create a question of medium difficulty for IELTS Speaking "
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"Part 2 that encourages candidates to narrate a personal "
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f'experience or story related to the topic of "{topic}". '
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"Include 3 prompts that guide the candidate. The prompts "
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"must not be questions. Also include a suffix like the ones "
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'in the IELTS exams that start with "And explain why". '
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"Make sure that the generated question does not contain "
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"forbidden subjects in muslim countries."
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)
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else:
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topic = topic or random.choice(TOPICS)
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user_msg = (
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"Formulate a set of 5 single questions of hard difficulty "
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"for IELTS Speaking Part 3 that encourage candidates to "
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"engage in a meaningful discussion on the topic of "
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f'"{topic}". They must be 1 single question each and not '
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"be double-barreled questions. Make sure that the generated "
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"question does not contain forbidden subjects in muslim countries."
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)
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if difficulty:
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user_msg += f" Target CEFR level: {difficulty}."
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return self.ai.prediction(
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model=GPT_MODELS["generation"],
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messages=[
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{"role": "system", "content": system_msg},
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{"role": "user", "content": user_msg},
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],
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temperature=TEMPERATURE["generation"],
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)
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# ------------------------------------------------------------------
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# Level exercises
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# ------------------------------------------------------------------
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def generate_level_exercises(self, exercises_config, difficulty):
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"""Generate level-exam exercises (multiple choice, fill-blanks, etc.).
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exercises_config: list of dicts with 'type', 'quantity', and optional
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'topic', 'size' keys.
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difficulty: CEFR level string.
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"""
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system_msg = (
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"You are a helpful assistant designed to output JSON. "
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"Generate English level exam exercises."
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)
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prompts = []
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for cfg in exercises_config:
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ex_type = cfg.get("type", "multiple_choice")
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quantity = cfg.get("quantity", 5)
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topic = cfg.get("topic") or random.choice(TOPICS)
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size = cfg.get("size", 200)
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if ex_type == "multiple_choice":
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prompts.append(
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f"Generate {quantity} multiple choice questions of 4 options "
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f"for an english level exam of {difficulty} CEFR level. "
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"Ensure that the questions cover a range of topics such as "
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"verb tense, subject-verb agreement, pronoun usage, sentence "
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"structure, and punctuation. Make sure every question only has "
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"1 correct answer."
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)
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elif ex_type == "fill_blanks":
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prompts.append(
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f"Generate a text of at least {size} words about the topic "
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f"{topic}. From the generated text choose exactly {quantity} "
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"words (cannot be sequential words), replace each with "
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"{id}, and generate a JSON object containing: the modified "
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"text, solutions array, words array with four options per blank."
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)
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user_msg = "\n\n".join(prompts)
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return self.ai.prediction(
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model=GPT_MODELS["generation"],
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messages=[
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{"role": "system", "content": system_msg},
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{"role": "user", "content": user_msg},
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],
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temperature=TEMPERATURE["generation"],
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)
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