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Update study_plan.py
Browse files- study_plan.py +203 -203
study_plan.py
CHANGED
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@@ -1,203 +1,203 @@
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import logging
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try:
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from groq import Groq
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except ImportError:
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Groq = None
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try:
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import google.generativeai as genai
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except ImportError:
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genai = None
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logger = logging.getLogger(__name__)
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groq_client = None
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genai_client = None
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try:
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GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
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if GROQ_API_KEY and Groq:
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groq_client = Groq(api_key=GROQ_API_KEY)
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except Exception as e:
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logger.warning(f"Groq client not available: {e}")
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try:
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GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
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if GEMINI_API_KEY and genai:
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genai.configure(api_key=GEMINI_API_KEY)
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genai_client = genai
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except Exception as e:
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logger.warning(f"Gemini client not available: {e}")
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def generate_study_plan(user_data):
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"""Gera um plano de estudos estruturado a partir dos dados do usuΓ‘rio (sem IA)."""
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from datetime import timedelta
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current_level = user_data.get('english_level', 'B1')
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target_level = user_data.get('target_level', 'B2')
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weekly_hours = user_data.get('weekly_hours', 5)
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interests = user_data.get('interests', {})
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context_focus = user_data.get('context_focus', 'General/Social')
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study_goals = user_data.get('study_goals', [])
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# ProgressΓ£o de nΓveis
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level_progression = {
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'A1': {'next': 'A2', 'weeks': 12},
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'A2': {'next': 'B1', 'weeks': 16},
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'B1': {'next': 'B2', 'weeks': 20},
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'B2': {'next': 'C1', 'weeks': 24},
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'C1': {'next': 'C2', 'weeks': 28},
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'C2': {'next': 'C2', 'weeks': 32}
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}
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# Timeline
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base_weeks = level_progression.get(current_level, level_progression['B1'])['weeks']
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hour_multiplier = 5 / max(weekly_hours, 1)
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adjusted_weeks = int(base_weeks * hour_multiplier)
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from datetime import datetime
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completion_date = (datetime.now() + timedelta(weeks=adjusted_weeks)).date().isoformat()
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# Estrutura semanal
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distributions = {
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'A1': {'reading': 0.25, 'flashcards': 0.30, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
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'A2': {'reading': 0.30, 'flashcards': 0.25, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
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'B1': {'reading': 0.30, 'flashcards': 0.20, 'conversation': 0.25, 'writing': 0.20, 'listening': 0.05},
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'B2': {'reading': 0.25, 'flashcards': 0.15, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
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'C1': {'reading': 0.30, 'flashcards': 0.10, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
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'C2': {'reading': 0.35, 'flashcards': 0.05, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10}
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}
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base_dist = distributions.get(current_level, distributions['B1'])
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total_minutes = weekly_hours * 60
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weekly_structure = {}
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for activity, percentage in base_dist.items():
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minutes = int(total_minutes * percentage)
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if minutes >= 10:
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weekly_structure[activity] = {
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'minutes_per_week': minutes,
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'sessions_per_week': max(1, minutes // 30),
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'minutes_per_session': minutes // max(1, minutes // 30)
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}
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# Dicas de estudo (IA se disponΓvel)
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def get_default_tips(level):
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tips_by_level = {
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'A1': [
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"π Start with basic vocabulary - 10 new words daily",
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"π― Focus on present tense in daily conversations",
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"π‘ Use picture dictionaries for visual learning",
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"β Practice pronunciation with simple audio materials",
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"π Don't worry about mistakes - communication is key!"
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],
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'A2': [
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"π Read simple news articles and stories",
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"π― Practice past and future tenses regularly",
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"π‘ Join basic English conversation groups",
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"β Use language learning apps for daily practice",
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"π Watch movies with subtitles in your language"
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],
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'B1': [
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"π Read intermediate articles on topics you enjoy",
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"π― Practice expressing opinions and preferences",
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"π‘ Start writing short paragraphs daily",
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"β Listen to podcasts at normal speed",
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"π Try to think in English for simple tasks"
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],
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'B2': [
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"π Read longer articles and opinion pieces",
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"π― Practice formal and informal writing styles",
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"π‘ Engage in debates and discussions",
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"β Watch news programs without subtitles",
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"π Set specific goals for each study session"
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],
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'C1': [
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"π Read academic and professional texts",
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"π― Practice nuanced expressions and idioms",
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"π‘ Write formal reports and presentations",
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| 109 |
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"β Listen to academic lectures and conferences",
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"π Focus on specialized vocabulary for your field"
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],
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'C2': [
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"π Read literature and complex analytical texts",
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"π― Master subtle language differences",
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"π‘ Write with stylistic sophistication",
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"β Engage with native speakers in professional contexts",
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"π Aim for native-like fluency in all skills"
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]
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}
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return tips_by_level.get(level, tips_by_level['B1'])
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def generate_ai_tips(user_data):
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prompt = f"""
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Generate 5 personalized English study tips for a user with these characteristics:
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- Current Level: {user_data.get('english_level', 'B1')}
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- Target Level: {user_data.get('target_level', 'B2')}
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- Weekly Study Time: {user_data.get('weekly_hours', 5)} hours
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- Context Focus: {user_data.get('context_focus', 'General/Social')}
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- Interests: {', '.join(user_data.get('interests', {}).keys())}
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Provide practical, actionable tips that are specific to their level and interests. Format as a simple list of tips, each starting with an emoji.
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"""
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try:
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if groq_client:
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response = groq_client.chat.completions.create(
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model="llama-3.1-8b-instant",
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messages=[{"role": "user", "content": prompt}],
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temperature=0.7
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)
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response_text = response.choices[0].message.content
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elif genai_client:
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model = genai_client.GenerativeModel('gemini-2.5-flash-latest')
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response = model.generate_content(prompt)
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response_text = response.text
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else:
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return get_default_tips(user_data.get('english_level', 'B1'))
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tips = [line.strip() for line in response_text.split('\n') if line.strip() and any(e in line for e in ['π','π‘','π―','β','π'])]
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return tips[:5] if tips else get_default_tips(user_data.get('english_level', 'B1'))
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except Exception as e:
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logger.warning(f"AI study tips error: {e}")
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return get_default_tips(user_data.get('english_level', 'B1'))
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study_tips = generate_ai_tips(user_data)
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# Milestones
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milestones = []
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milestone_intervals = max(2, adjusted_weeks // 4)
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for i in range(1, 5):
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week = milestone_intervals * i
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if week <= adjusted_weeks:
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milestones.append({
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'week': week,
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'title': f"Milestone {i}",
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'description': f"Progress checkpoint {i}",
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'target_date': (datetime.now() + timedelta(weeks=week)).date().isoformat(),
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'completed': False
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})
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plan = {
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'id': f"plan_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
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'created_at': datetime.now().isoformat(),
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'current_level': current_level,
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'target_level': target_level,
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'weekly_hours': weekly_hours,
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'estimated_weeks': adjusted_weeks,
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'completion_date': completion_date,
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'weekly_structure': weekly_structure,
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'study_tips': study_tips,
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'milestones': milestones,
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'interests': interests,
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'context_focus': context_focus,
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'study_goals': study_goals
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}
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return plan
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import os
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import json
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from datetime import datetime
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STUDY_PLAN_PATH = 'hf_data/study_plan.json'
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def save_study_plan(plan_data):
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"""Salva o plano de estudos em JSON."""
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os.makedirs(os.path.dirname(STUDY_PLAN_PATH), exist_ok=True)
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plan_data['saved_at'] = datetime.now().isoformat()
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with open(STUDY_PLAN_PATH, 'w', encoding='utf-8') as f:
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json.dump(plan_data, f, ensure_ascii=False, indent=2)
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return True
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def load_study_plan():
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"""Carrega o plano de estudos do JSON."""
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if os.path.exists(STUDY_PLAN_PATH):
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with open(STUDY_PLAN_PATH, 'r', encoding='utf-8') as f:
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return json.load(f)
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return None
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import logging
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try:
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from groq import Groq
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except ImportError:
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Groq = None
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try:
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import google.generativeai as genai
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except ImportError:
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genai = None
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logger = logging.getLogger(__name__)
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groq_client = None
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genai_client = None
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try:
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GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
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if GROQ_API_KEY and Groq:
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groq_client = Groq(api_key=GROQ_API_KEY)
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except Exception as e:
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logger.warning(f"Groq client not available: {e}")
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try:
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GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
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if GEMINI_API_KEY and genai:
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genai.configure(api_key=GEMINI_API_KEY)
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genai_client = genai
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except Exception as e:
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logger.warning(f"Gemini client not available: {e}")
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def generate_study_plan(user_data):
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"""Gera um plano de estudos estruturado a partir dos dados do usuΓ‘rio (sem IA)."""
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from datetime import timedelta
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current_level = user_data.get('english_level', 'B1')
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target_level = user_data.get('target_level', 'B2')
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weekly_hours = user_data.get('weekly_hours', 5)
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interests = user_data.get('interests', {})
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context_focus = user_data.get('context_focus', 'General/Social')
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study_goals = user_data.get('study_goals', [])
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# ProgressΓ£o de nΓveis
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level_progression = {
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'A1': {'next': 'A2', 'weeks': 12},
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'A2': {'next': 'B1', 'weeks': 16},
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'B1': {'next': 'B2', 'weeks': 20},
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'B2': {'next': 'C1', 'weeks': 24},
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'C1': {'next': 'C2', 'weeks': 28},
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'C2': {'next': 'C2', 'weeks': 32}
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}
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# Timeline
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base_weeks = level_progression.get(current_level, level_progression['B1'])['weeks']
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hour_multiplier = 5 / max(weekly_hours, 1)
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adjusted_weeks = int(base_weeks * hour_multiplier)
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from datetime import datetime
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completion_date = (datetime.now() + timedelta(weeks=adjusted_weeks)).date().isoformat()
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# Estrutura semanal
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distributions = {
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'A1': {'reading': 0.25, 'flashcards': 0.30, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
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'A2': {'reading': 0.30, 'flashcards': 0.25, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
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'B1': {'reading': 0.30, 'flashcards': 0.20, 'conversation': 0.25, 'writing': 0.20, 'listening': 0.05},
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'B2': {'reading': 0.25, 'flashcards': 0.15, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
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'C1': {'reading': 0.30, 'flashcards': 0.10, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
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'C2': {'reading': 0.35, 'flashcards': 0.05, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10}
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}
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base_dist = distributions.get(current_level, distributions['B1'])
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total_minutes = weekly_hours * 60
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weekly_structure = {}
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for activity, percentage in base_dist.items():
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minutes = int(total_minutes * percentage)
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if minutes >= 10:
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weekly_structure[activity] = {
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'minutes_per_week': minutes,
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'sessions_per_week': max(1, minutes // 30),
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'minutes_per_session': minutes // max(1, minutes // 30)
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}
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+
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# Dicas de estudo (IA se disponΓvel)
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| 75 |
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def get_default_tips(level):
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| 76 |
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tips_by_level = {
|
| 77 |
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'A1': [
|
| 78 |
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"π Start with basic vocabulary - 10 new words daily",
|
| 79 |
+
"π― Focus on present tense in daily conversations",
|
| 80 |
+
"π‘ Use picture dictionaries for visual learning",
|
| 81 |
+
"β Practice pronunciation with simple audio materials",
|
| 82 |
+
"π Don't worry about mistakes - communication is key!"
|
| 83 |
+
],
|
| 84 |
+
'A2': [
|
| 85 |
+
"π Read simple news articles and stories",
|
| 86 |
+
"π― Practice past and future tenses regularly",
|
| 87 |
+
"π‘ Join basic English conversation groups",
|
| 88 |
+
"β Use language learning apps for daily practice",
|
| 89 |
+
"π Watch movies with subtitles in your language"
|
| 90 |
+
],
|
| 91 |
+
'B1': [
|
| 92 |
+
"π Read intermediate articles on topics you enjoy",
|
| 93 |
+
"π― Practice expressing opinions and preferences",
|
| 94 |
+
"π‘ Start writing short paragraphs daily",
|
| 95 |
+
"β Listen to podcasts at normal speed",
|
| 96 |
+
"π Try to think in English for simple tasks"
|
| 97 |
+
],
|
| 98 |
+
'B2': [
|
| 99 |
+
"π Read longer articles and opinion pieces",
|
| 100 |
+
"π― Practice formal and informal writing styles",
|
| 101 |
+
"π‘ Engage in debates and discussions",
|
| 102 |
+
"β Watch news programs without subtitles",
|
| 103 |
+
"π Set specific goals for each study session"
|
| 104 |
+
],
|
| 105 |
+
'C1': [
|
| 106 |
+
"π Read academic and professional texts",
|
| 107 |
+
"π― Practice nuanced expressions and idioms",
|
| 108 |
+
"π‘ Write formal reports and presentations",
|
| 109 |
+
"β Listen to academic lectures and conferences",
|
| 110 |
+
"π Focus on specialized vocabulary for your field"
|
| 111 |
+
],
|
| 112 |
+
'C2': [
|
| 113 |
+
"π Read literature and complex analytical texts",
|
| 114 |
+
"π― Master subtle language differences",
|
| 115 |
+
"π‘ Write with stylistic sophistication",
|
| 116 |
+
"β Engage with native speakers in professional contexts",
|
| 117 |
+
"π Aim for native-like fluency in all skills"
|
| 118 |
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]
|
| 119 |
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}
|
| 120 |
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return tips_by_level.get(level, tips_by_level['B1'])
|
| 121 |
+
|
| 122 |
+
def generate_ai_tips(user_data):
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| 123 |
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prompt = f"""
|
| 124 |
+
Generate 5 personalized English study tips for a user with these characteristics:
|
| 125 |
+
- Current Level: {user_data.get('english_level', 'B1')}
|
| 126 |
+
- Target Level: {user_data.get('target_level', 'B2')}
|
| 127 |
+
- Weekly Study Time: {user_data.get('weekly_hours', 5)} hours
|
| 128 |
+
- Context Focus: {user_data.get('context_focus', 'General/Social')}
|
| 129 |
+
- Interests: {', '.join(user_data.get('interests', {}).keys())}
|
| 130 |
+
Provide practical, actionable tips that are specific to their level and interests. Format as a simple list of tips, each starting with an emoji.
|
| 131 |
+
"""
|
| 132 |
+
try:
|
| 133 |
+
if groq_client:
|
| 134 |
+
response = groq_client.chat.completions.create(
|
| 135 |
+
model="llama-3.1-8b-instant",
|
| 136 |
+
messages=[{"role": "user", "content": prompt}],
|
| 137 |
+
temperature=0.7
|
| 138 |
+
)
|
| 139 |
+
response_text = response.choices[0].message.content
|
| 140 |
+
elif genai_client:
|
| 141 |
+
model = genai_client.GenerativeModel('gemini-2.5-flash-latest')
|
| 142 |
+
response = model.generate_content(prompt)
|
| 143 |
+
response_text = response.text
|
| 144 |
+
else:
|
| 145 |
+
return get_default_tips(user_data.get('english_level', 'B1'))
|
| 146 |
+
tips = [line.strip() for line in response_text.split('\n') if line.strip() and any(e in line for e in ['π','π‘','π―','β','π'])]
|
| 147 |
+
return tips[:5] if tips else get_default_tips(user_data.get('english_level', 'B1'))
|
| 148 |
+
except Exception as e:
|
| 149 |
+
logger.warning(f"AI study tips error: {e}")
|
| 150 |
+
return get_default_tips(user_data.get('english_level', 'B1'))
|
| 151 |
+
|
| 152 |
+
study_tips = generate_ai_tips(user_data)
|
| 153 |
+
|
| 154 |
+
# Milestones
|
| 155 |
+
milestones = []
|
| 156 |
+
milestone_intervals = max(2, adjusted_weeks // 4)
|
| 157 |
+
for i in range(1, 5):
|
| 158 |
+
week = milestone_intervals * i
|
| 159 |
+
if week <= adjusted_weeks:
|
| 160 |
+
milestones.append({
|
| 161 |
+
'week': week,
|
| 162 |
+
'title': f"Milestone {i}",
|
| 163 |
+
'description': f"Progress checkpoint {i}",
|
| 164 |
+
'target_date': (datetime.now() + timedelta(weeks=week)).date().isoformat(),
|
| 165 |
+
'completed': False
|
| 166 |
+
})
|
| 167 |
+
|
| 168 |
+
plan = {
|
| 169 |
+
'id': f"plan_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
|
| 170 |
+
'created_at': datetime.now().isoformat(),
|
| 171 |
+
'current_level': current_level,
|
| 172 |
+
'target_level': target_level,
|
| 173 |
+
'weekly_hours': weekly_hours,
|
| 174 |
+
'estimated_weeks': adjusted_weeks,
|
| 175 |
+
'completion_date': completion_date,
|
| 176 |
+
'weekly_structure': weekly_structure,
|
| 177 |
+
'study_tips': study_tips,
|
| 178 |
+
'milestones': milestones,
|
| 179 |
+
'interests': interests,
|
| 180 |
+
'context_focus': context_focus,
|
| 181 |
+
'study_goals': study_goals
|
| 182 |
+
}
|
| 183 |
+
return plan
|
| 184 |
+
import os
|
| 185 |
+
import json
|
| 186 |
+
from datetime import datetime
|
| 187 |
+
|
| 188 |
+
STUDY_PLAN_PATH = 'hf_data/study_plan.json'
|
| 189 |
+
|
| 190 |
+
def save_study_plan(plan_data):
|
| 191 |
+
"""Salva o plano de estudos em JSON."""
|
| 192 |
+
os.makedirs(os.path.dirname(STUDY_PLAN_PATH), exist_ok=True)
|
| 193 |
+
plan_data['saved_at'] = datetime.now().isoformat()
|
| 194 |
+
with open(STUDY_PLAN_PATH, 'w', encoding='utf-8') as f:
|
| 195 |
+
json.dump(plan_data, f, ensure_ascii=False, indent=2)
|
| 196 |
+
return True
|
| 197 |
+
|
| 198 |
+
def load_study_plan():
|
| 199 |
+
"""Carrega o plano de estudos do JSON."""
|
| 200 |
+
if os.path.exists(STUDY_PLAN_PATH):
|
| 201 |
+
with open(STUDY_PLAN_PATH, 'r', encoding='utf-8') as f:
|
| 202 |
+
return json.load(f)
|
| 203 |
+
return None
|