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app.py

@@ -1,50 +1,50 @@
-#!/usr/bin/env python3
-"""
-English Helper - HF Spaces Version (Simplified)
-Sistema de aprendizado de inglês sem autenticação para máxima compatibilidade
-"""
-
-import os
-import json
-from datetime import datetime
-
-def init_simple_storage():
-    """Inicializar armazenamento simples baseado em arquivos"""
-    try:
-        os.makedirs('hf_data', exist_ok=True)
-        os.makedirs('hf_data/flashcards', exist_ok=True)
-        os.makedirs('hf_data/conversations', exist_ok=True)
-        os.makedirs('hf_data/analytics', exist_ok=True)
-        print("✅ Sistema de armazenamento HF inicializado")
-        return True
-    except Exception as e:
-        print(f"❌ Erro na inicialização: {e}")
-        return False
-
-# Executar aplicação
-if __name__ == "__main__":
-    print("🎯 English Helper HF - Versão Simplificada")
-    
-    # Inicializar sistema
-    if not init_simple_storage():
-        print("❌ Falha na inicialização")
-        exit(1)
-    
-    try:
-        # Importar Flask app simplificado
-        import flask_app_hf
-        app = flask_app_hf.app
-        
-        print("🚀 Executando Flask na porta 7860 (HF Spaces)")
-        app.run(
-            host="0.0.0.0",
-            port=7860,
-            debug=False,
-            threaded=True,
-            use_reloader=False
-        )
-        
-    except Exception as e:
-        print(f"❌ Erro: {e}")
-        import traceback
+#!/usr/bin/env python3
+"""
+English Helper - HF Spaces Version (Simplified)
+Sistema de aprendizado de inglês sem autenticação para máxima compatibilidade
+"""
+
+import os
+import json
+from datetime import datetime
+
+def init_simple_storage():
+    """Inicializar armazenamento simples baseado em arquivos"""
+    try:
+        os.makedirs('hf_data', exist_ok=True)
+        os.makedirs('hf_data/flashcards', exist_ok=True)
+        os.makedirs('hf_data/conversations', exist_ok=True)
+        os.makedirs('hf_data/analytics', exist_ok=True)
+        print("✅ Sistema de armazenamento HF inicializado")
+        return True
+    except Exception as e:
+        print(f"❌ Erro na inicialização: {e}")
+        return False
+
+# Executar aplicação
+if __name__ == "__main__":
+    print("🎯 English Helper HF - Versão Simplificada")
+    
+    # Inicializar sistema
+    if not init_simple_storage():
+        print("❌ Falha na inicialização")
+        exit(1)
+    
+    try:
+        # Importar Flask app simplificado
+        import flask_app_hf
+        app = flask_app_hf.app
+        
+        print("🚀 Executando Flask na porta 7860 (HF Spaces)")
+        app.run(
+            host="0.0.0.0",
+            port=7860,
+            debug=False,
+            threaded=True,
+            use_reloader=False
+        )
+        
+    except Exception as e:
+        print(f"❌ Erro: {e}")
+        import traceback
         traceback.print_exc()

flask_app_hf.py

@@ -1,361 +1,361 @@
-# flask_app_hf.py - English Helper HF Spaces (Sem Autenticação)
-import os
-import io
-import json
-import base64
-from datetime import datetime
-from flask import Flask, request, jsonify, send_file, render_template_string, redirect, url_for, Response
-from gtts import gTTS
-from groq import Groq
-import google.generativeai as genai
-from google.generativeai.types import GenerationConfig
-
-# --- CONFIGURAÇÃO INICIAL ---
-app = Flask(__name__)
-
-# Configuração simplificada para HF Spaces
-app.config['SECRET_KEY'] = 'hf-simple-key-no-auth'
-app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 0
-
-print(f"✅ Flask HF app inicializado")
-print(f"✅ Working directory: {os.getcwd()}")
-
-# --- UTILITÁRIOS DE ARMAZENAMENTO ---
-
-def save_user_data(user_id, data_type, data):
-    """Salvar dados do usuário em arquivos JSON"""
-    try:
-        user_dir = f"hf_data/{data_type}"
-        os.makedirs(user_dir, exist_ok=True)
-        
-        file_path = f"{user_dir}/{user_id}.json"
-        
-        # Carregar dados existentes
-        existing_data = []
-        if os.path.exists(file_path):
-            with open(file_path, 'r', encoding='utf-8') as f:
-                existing_data = json.load(f)
-        
-        # Adicionar novos dados
-        data['timestamp'] = datetime.now().isoformat()
-        existing_data.append(data)
-        
-        # Manter apenas os últimos 100 itens
-        if len(existing_data) > 100:
-            existing_data = existing_data[-100:]
-        
-        # Salvar
-        with open(file_path, 'w', encoding='utf-8') as f:
-            json.dump(existing_data, f, ensure_ascii=False, indent=2)
-        
-        return True
-    except Exception as e:
-        print(f"Erro ao salvar dados: {e}")
-        return False
-
-def load_user_data(user_id, data_type):
-    """Carregar dados do usuário"""
-    try:
-        file_path = f"hf_data/{data_type}/{user_id}.json"
-        if os.path.exists(file_path):
-            with open(file_path, 'r', encoding='utf-8') as f:
-                return json.load(f)
-        return []
-    except Exception as e:
-        print(f"Erro ao carregar dados: {e}")
-        return []
-
-def get_all_users():
-    """Obter lista de todos os usuários"""
-    users = set()
-    for data_type in ['flashcards', 'conversations', 'analytics']:
-        data_dir = f"hf_data/{data_type}"
-        if os.path.exists(data_dir):
-            for filename in os.listdir(data_dir):
-                if filename.endswith('.json'):
-                    users.add(filename[:-5])  # Remove .json
-    return sorted(list(users))
-
-# --- CONFIGURAÇÃO DE APIs ---
-
-# Configurar APIs
-groq_client = None
-genai_client = None
-
-try:
-    groq_api_key = os.environ.get('GROQ_API_KEY')
-    if groq_api_key:
-        groq_client = Groq(api_key=groq_api_key)
-        print("✅ Groq API configurada")
-except Exception as e:
-    print(f"⚠️ Groq API não configurada: {e}")
-
-try:
-    gemini_api_key = os.environ.get('GEMINI_API_KEY')
-    if gemini_api_key:
-        genai.configure(api_key=gemini_api_key)
-        genai_client = genai
-        print("✅ Gemini API configurada")
-except Exception as e:
-    print(f"⚠️ Gemini API não configurada: {e}")
-
-# --- ROTAS PRINCIPAIS ---
-
-@app.route('/')
-def index():
-    return send_file('templates/index.html')
-
-@app.route('/admin')
-def admin():
-    return send_file('templates/admin.html')
-
-@app.route('/status')
-def status():
-    return send_file('templates/status.html')
-
-# --- API ENDPOINTS ---
-
-@app.route('/list-models', methods=['GET'])
-def list_models():
-    """Listar modelos disponíveis"""
-    available_models = []
-    
-    if groq_client:
-        available_models.extend([
-            {"name": "Llama 3.2 90B (Ultra Fast)", "value": "groq:llama-3.2-90b-text-preview"},
-            {"name": "Llama 3.2 11B Vision (Fast)", "value": "groq:llama-3.2-11b-vision-preview"},
-            {"name": "Llama 3.1 70B (Fast)", "value": "groq:llama-3.1-70b-versatile"},
-            {"name": "Mixtral 8x7B (Fast)", "value": "groq:mixtral-8x7b-32768"}
-        ])
-    
-    if genai_client:
-        available_models.extend([
-            {"name": "Gemini 2.5 Flash (Recommended)", "value": "gemini:gemini-2.5-flash-latest"},
-            {"name": "Gemini 2.5 Pro Experimental", "value": "gemini:gemini-2.5-pro-exp"},
-            {"name": "Gemini 1.5 Flash", "value": "gemini:gemini-1.5-flash-latest"},
-            {"name": "Gemini 1.5 Pro", "value": "gemini:gemini-1.5-pro-latest"}
-        ])
-    
-    return jsonify(available_models)
-
-# Cache de áudio TTS em memória
-tts_cache = {}
-
-@app.route('/tts-proxy', methods=['POST'])
-def tts_proxy():
-    data = request.get_json()
-    text = data.get('text', '')
-    tld = data.get('tld', 'co.uk') 
-    if not text: return jsonify({"error": "No text provided"}), 400
-    
-    if len(text) > 10000:
-        return jsonify({"error": "Text is too long. Maximum 10,000 characters allowed."}), 400
-    
-    import hashlib
-    cache_key = hashlib.md5(f"{text}_{tld}".encode()).hexdigest()
-    
-    try:
-        if cache_key in tts_cache:
-            print(f"🎵 TTS Cache HIT: {len(text)} chars")
-            cached_audio = tts_cache[cache_key]
-            audio_fp = io.BytesIO(cached_audio)
-            return send_file(audio_fp, mimetype='audio/mpeg', as_attachment=False)
-        
-        print(f"🎵 TTS Cache MISS: Gerando áudio para {len(text)} chars, tld: {tld}")
-        
-        tts = gTTS(text=text, lang='en', tld=tld)
-        mp3_fp = io.BytesIO()
-        tts.write_to_fp(mp3_fp)
-        mp3_fp.seek(0)
-        
-        audio_data = mp3_fp.read()
-        tts_cache[cache_key] = audio_data
-        
-        if len(tts_cache) > 50:
-            oldest_key = next(iter(tts_cache))
-            del tts_cache[oldest_key]
-            
-        audio_fp = io.BytesIO(audio_data)
-        return send_file(audio_fp, mimetype='audio/mpeg', as_attachment=False)
-        
-    except Exception as e:
-        print(f"❌ TTS Error: {e}")
-        return jsonify({"error": f"Failed to generate audio via gTTS: {e}"}), 500
-
-@app.route('/explain-proxy', methods=['POST'])
-def explain_proxy():
-    """Gerar explicação/flashcard"""
-    data = request.get_json()
-    selected_text = data.get('selectedText', '')
-    model_info = data.get('model', 'gemini:gemini-2.5-flash-latest').split(':', 1)
-    
-    if len(model_info) != 2:
-        return jsonify({"error": "Invalid model format"}), 400
-    
-    model_provider, model_name = model_info
-    
-    if not selected_text:
-        return jsonify({"error": "No text selected"}), 400
-    
-    try:
-        prompt = f"""
-        Create a comprehensive flashcard for the English term/phrase: "{selected_text}"
-        
-        Provide:
-        1. Clear definition in English
-        2. Translation to Portuguese 
-        3. Example sentence using the term
-        4. Same sentence with the term replaced by "____" for practice
-        
-        Return as JSON with keys: definition, translation, context_sentence, gapped_sentence
-        """
-        
-        if model_provider == 'gemini' and genai_client:
-            model = genai_client.GenerativeModel(model_name)
-            response = model.generate_content(prompt)
-            
-            # Extrair JSON da resposta
-            response_text = response.text
-            if '```json' in response_text:
-                json_start = response_text.find('```json') + 7
-                json_end = response_text.find('```', json_start)
-                response_text = response_text[json_start:json_end].strip()
-            
-            result = json.loads(response_text)
-            result['term'] = selected_text
-            
-            return jsonify(result)
-            
-        elif model_provider == 'groq' and groq_client:
-            response = groq_client.chat.completions.create(
-                messages=[{"role": "user", "content": prompt}],
-                model=model_name,
-                temperature=0.3
-            )
-            
-            response_text = response.choices[0].message.content
-            if '```json' in response_text:
-                json_start = response_text.find('```json') + 7
-                json_end = response_text.find('```', json_start)
-                response_text = response_text[json_start:json_end].strip()
-            
-            result = json.loads(response_text)
-            result['term'] = selected_text
-            
-            return jsonify(result)
-        
-        else:
-            return jsonify({"error": f"{model_provider.upper()}_API_KEY not configured"}), 503
-            
-    except Exception as e:
-        print(f"AI ANALYSIS ERROR: {e}")
-        return jsonify({"error": str(e)}), 500
-
-# --- ROUTES DE DADOS (SEM AUTENTICAÇÃO) ---
-
-@app.route('/users', methods=['GET'])
-def get_users():
-    """Obter lista de usuários"""
-    users = get_all_users()
-    return jsonify({'users': users, 'total': len(users)})
-
-@app.route('/user/<user_id>/flashcards', methods=['GET', 'POST'])
-def user_flashcards(user_id):
-    """Gerenciar flashcards do usuário"""
-    if request.method == 'POST':
-        data = request.get_json()
-        if save_user_data(user_id, 'flashcards', data):
-            return jsonify({'success': True, 'message': 'Flashcard saved'})
-        else:
-            return jsonify({'success': False, 'message': 'Failed to save flashcard'}), 500
-    else:
-        flashcards = load_user_data(user_id, 'flashcards')
-        return jsonify({'flashcards': flashcards})
-
-@app.route('/user/<user_id>/conversations', methods=['GET', 'POST'])
-def user_conversations(user_id):
-    """Gerenciar conversas do usuário"""
-    if request.method == 'POST':
-        data = request.get_json()
-        if save_user_data(user_id, 'conversations', data):
-            return jsonify({'success': True, 'message': 'Conversation saved'})
-        else:
-            return jsonify({'success': False, 'message': 'Failed to save conversation'}), 500
-    else:
-        conversations = load_user_data(user_id, 'conversations')
-        return jsonify({'conversations': conversations})
-
-@app.route('/user/<user_id>/analytics', methods=['GET'])
-def user_analytics(user_id):
-    """Obter analytics do usuário"""
-    analytics = load_user_data(user_id, 'analytics')
-    flashcards = load_user_data(user_id, 'flashcards')
-    conversations = load_user_data(user_id, 'conversations')
-    
-    return jsonify({
-        'total_flashcards': len(flashcards),
-        'total_conversations': len(conversations),
-        'total_sessions': len(analytics),
-        'recent_activity': analytics[-10:] if analytics else []
-    })
-
-# --- STATUS E ADMIN ---
-
-@app.route('/admin/stats', methods=['GET'])
-def admin_stats():
-    """Estatísticas do sistema"""
-    users = get_all_users()
-    stats = {
-        'total_users': len(users),
-        'users': []
-    }
-    
-    for user_id in users:
-        flashcards = len(load_user_data(user_id, 'flashcards'))
-        conversations = len(load_user_data(user_id, 'conversations'))
-        stats['users'].append({
-            'user_id': user_id,
-            'flashcards': flashcards,
-            'conversations': conversations
-        })
-    
-    return jsonify(stats)
-
-@app.route('/system/status', methods=['GET'])
-def system_status():
-    """Status do sistema"""
-    return jsonify({
-        'status': 'running',
-        'version': 'HF-Simplified-1.0',
-        'apis': {
-            'groq': groq_client is not None,
-            'gemini': genai_client is not None
-        },
-        'storage': 'file_based',
-        'auth': 'disabled'
-    })
-
-from study_plan import save_study_plan, load_study_plan, generate_study_plan
-
-@app.route('/study-plan', methods=['GET', 'POST'])
-def study_plan():
-    """Salvar ou carregar plano de estudos global (sem autenticação)"""
-    if request.method == 'POST':
-        try:
-            data = request.get_json()
-            plan = generate_study_plan(data)
-            save_study_plan(plan)
-            return jsonify({'success': True, 'message': 'Study plan generated and saved', 'plan': plan})
-        except Exception as e:
-            print(f"Erro ao salvar study plan: {e}")
-            return jsonify({'success': False, 'message': 'Failed to save study plan'}), 500
-    else:
-        try:
-            plan = load_study_plan()
-            return jsonify({'success': True, 'plan': plan})
-        except Exception as e:
-            print(f"Erro ao carregar study plan: {e}")
-            return jsonify({'success': False, 'message': 'Failed to load study plan'}), 500
-
-if __name__ == '__main__':
+# flask_app_hf.py - English Helper HF Spaces (Sem Autenticação)
+import os
+import io
+import json
+import base64
+from datetime import datetime
+from flask import Flask, request, jsonify, send_file, render_template, render_template_string, redirect, url_for, Response
+from gtts import gTTS
+from groq import Groq
+import google.generativeai as genai
+from google.generativeai.types import GenerationConfig
+
+# --- CONFIGURAÇÃO INICIAL ---
+app = Flask(__name__)
+
+# Configuração simplificada para HF Spaces
+app.config['SECRET_KEY'] = 'hf-simple-key-no-auth'
+app.config['SEND_FILE_MAX_AGE_DEFAULT'] = 0
+
+print(f"✅ Flask HF app inicializado")
+print(f"✅ Working directory: {os.getcwd()}")
+
+# --- UTILITÁRIOS DE ARMAZENAMENTO ---
+
+def save_user_data(user_id, data_type, data):
+    """Salvar dados do usuário em arquivos JSON"""
+    try:
+        user_dir = f"hf_data/{data_type}"
+        os.makedirs(user_dir, exist_ok=True)
+        
+        file_path = f"{user_dir}/{user_id}.json"
+        
+        # Carregar dados existentes
+        existing_data = []
+        if os.path.exists(file_path):
+            with open(file_path, 'r', encoding='utf-8') as f:
+                existing_data = json.load(f)
+        
+        # Adicionar novos dados
+        data['timestamp'] = datetime.now().isoformat()
+        existing_data.append(data)
+        
+        # Manter apenas os últimos 100 itens
+        if len(existing_data) > 100:
+            existing_data = existing_data[-100:]
+        
+        # Salvar
+        with open(file_path, 'w', encoding='utf-8') as f:
+            json.dump(existing_data, f, ensure_ascii=False, indent=2)
+        
+        return True
+    except Exception as e:
+        print(f"Erro ao salvar dados: {e}")
+        return False
+
+def load_user_data(user_id, data_type):
+    """Carregar dados do usuário"""
+    try:
+        file_path = f"hf_data/{data_type}/{user_id}.json"
+        if os.path.exists(file_path):
+            with open(file_path, 'r', encoding='utf-8') as f:
+                return json.load(f)
+        return []
+    except Exception as e:
+        print(f"Erro ao carregar dados: {e}")
+        return []
+
+def get_all_users():
+    """Obter lista de todos os usuários"""
+    users = set()
+    for data_type in ['flashcards', 'conversations', 'analytics']:
+        data_dir = f"hf_data/{data_type}"
+        if os.path.exists(data_dir):
+            for filename in os.listdir(data_dir):
+                if filename.endswith('.json'):
+                    users.add(filename[:-5])  # Remove .json
+    return sorted(list(users))
+
+# --- CONFIGURAÇÃO DE APIs ---
+
+# Configurar APIs
+groq_client = None
+genai_client = None
+
+try:
+    groq_api_key = os.environ.get('GROQ_API_KEY')
+    if groq_api_key:
+        groq_client = Groq(api_key=groq_api_key)
+        print("✅ Groq API configurada")
+except Exception as e:
+    print(f"⚠️ Groq API não configurada: {e}")
+
+try:
+    gemini_api_key = os.environ.get('GEMINI_API_KEY')
+    if gemini_api_key:
+        genai.configure(api_key=gemini_api_key)
+        genai_client = genai
+        print("✅ Gemini API configurada")
+except Exception as e:
+    print(f"⚠️ Gemini API não configurada: {e}")
+
+# --- ROTAS PRINCIPAIS ---
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/admin')
+def admin():
+    return render_template('admin.html')
+
+@app.route('/status')
+def status():
+    return render_template('status.html')
+
+# --- API ENDPOINTS ---
+
+@app.route('/list-models', methods=['GET'])
+def list_models():
+    """Listar modelos disponíveis"""
+    available_models = []
+    
+    if groq_client:
+        available_models.extend([
+            {"name": "Llama 3.2 90B (Ultra Fast)", "value": "groq:llama-3.2-90b-text-preview"},
+            {"name": "Llama 3.2 11B Vision (Fast)", "value": "groq:llama-3.2-11b-vision-preview"},
+            {"name": "Llama 3.1 70B (Fast)", "value": "groq:llama-3.1-70b-versatile"},
+            {"name": "Mixtral 8x7B (Fast)", "value": "groq:mixtral-8x7b-32768"}
+        ])
+    
+    if genai_client:
+        available_models.extend([
+            {"name": "Gemini 2.5 Flash (Recommended)", "value": "gemini:gemini-2.5-flash-latest"},
+            {"name": "Gemini 2.5 Pro Experimental", "value": "gemini:gemini-2.5-pro-exp"},
+            {"name": "Gemini 1.5 Flash", "value": "gemini:gemini-1.5-flash-latest"},
+            {"name": "Gemini 1.5 Pro", "value": "gemini:gemini-1.5-pro-latest"}
+        ])
+    
+    return jsonify(available_models)
+
+# Cache de áudio TTS em memória
+tts_cache = {}
+
+@app.route('/tts-proxy', methods=['POST'])
+def tts_proxy():
+    data = request.get_json()
+    text = data.get('text', '')
+    tld = data.get('tld', 'co.uk') 
+    if not text: return jsonify({"error": "No text provided"}), 400
+    
+    if len(text) > 10000:
+        return jsonify({"error": "Text is too long. Maximum 10,000 characters allowed."}), 400
+    
+    import hashlib
+    cache_key = hashlib.md5(f"{text}_{tld}".encode()).hexdigest()
+    
+    try:
+        if cache_key in tts_cache:
+            print(f"🎵 TTS Cache HIT: {len(text)} chars")
+            cached_audio = tts_cache[cache_key]
+            audio_fp = io.BytesIO(cached_audio)
+            return send_file(audio_fp, mimetype='audio/mpeg', as_attachment=False)
+        
+        print(f"🎵 TTS Cache MISS: Gerando áudio para {len(text)} chars, tld: {tld}")
+        
+        tts = gTTS(text=text, lang='en', tld=tld)
+        mp3_fp = io.BytesIO()
+        tts.write_to_fp(mp3_fp)
+        mp3_fp.seek(0)
+        
+        audio_data = mp3_fp.read()
+        tts_cache[cache_key] = audio_data
+        
+        if len(tts_cache) > 50:
+            oldest_key = next(iter(tts_cache))
+            del tts_cache[oldest_key]
+            
+        audio_fp = io.BytesIO(audio_data)
+        return send_file(audio_fp, mimetype='audio/mpeg', as_attachment=False)
+        
+    except Exception as e:
+        print(f"❌ TTS Error: {e}")
+        return jsonify({"error": f"Failed to generate audio via gTTS: {e}"}), 500
+
+@app.route('/explain-proxy', methods=['POST'])
+def explain_proxy():
+    """Gerar explicação/flashcard"""
+    data = request.get_json()
+    selected_text = data.get('selectedText', '')
+    model_info = data.get('model', 'gemini:gemini-2.5-flash-latest').split(':', 1)
+    
+    if len(model_info) != 2:
+        return jsonify({"error": "Invalid model format"}), 400
+    
+    model_provider, model_name = model_info
+    
+    if not selected_text:
+        return jsonify({"error": "No text selected"}), 400
+    
+    try:
+        prompt = f"""
+        Create a comprehensive flashcard for the English term/phrase: "{selected_text}"
+        
+        Provide:
+        1. Clear definition in English
+        2. Translation to Portuguese 
+        3. Example sentence using the term
+        4. Same sentence with the term replaced by "____" for practice
+        
+        Return as JSON with keys: definition, translation, context_sentence, gapped_sentence
+        """
+        
+        if model_provider == 'gemini' and genai_client:
+            model = genai_client.GenerativeModel(model_name)
+            response = model.generate_content(prompt)
+            
+            # Extrair JSON da resposta
+            response_text = response.text
+            if '```json' in response_text:
+                json_start = response_text.find('```json') + 7
+                json_end = response_text.find('```', json_start)
+                response_text = response_text[json_start:json_end].strip()
+            
+            result = json.loads(response_text)
+            result['term'] = selected_text
+            
+            return jsonify(result)
+            
+        elif model_provider == 'groq' and groq_client:
+            response = groq_client.chat.completions.create(
+                messages=[{"role": "user", "content": prompt}],
+                model=model_name,
+                temperature=0.3
+            )
+            
+            response_text = response.choices[0].message.content
+            if '```json' in response_text:
+                json_start = response_text.find('```json') + 7
+                json_end = response_text.find('```', json_start)
+                response_text = response_text[json_start:json_end].strip()
+            
+            result = json.loads(response_text)
+            result['term'] = selected_text
+            
+            return jsonify(result)
+        
+        else:
+            return jsonify({"error": f"{model_provider.upper()}_API_KEY not configured"}), 503
+            
+    except Exception as e:
+        print(f"AI ANALYSIS ERROR: {e}")
+        return jsonify({"error": str(e)}), 500
+
+# --- ROUTES DE DADOS (SEM AUTENTICAÇÃO) ---
+
+@app.route('/users', methods=['GET'])
+def get_users():
+    """Obter lista de usuários"""
+    users = get_all_users()
+    return jsonify({'users': users, 'total': len(users)})
+
+@app.route('/user/<user_id>/flashcards', methods=['GET', 'POST'])
+def user_flashcards(user_id):
+    """Gerenciar flashcards do usuário"""
+    if request.method == 'POST':
+        data = request.get_json()
+        if save_user_data(user_id, 'flashcards', data):
+            return jsonify({'success': True, 'message': 'Flashcard saved'})
+        else:
+            return jsonify({'success': False, 'message': 'Failed to save flashcard'}), 500
+    else:
+        flashcards = load_user_data(user_id, 'flashcards')
+        return jsonify({'flashcards': flashcards})
+
+@app.route('/user/<user_id>/conversations', methods=['GET', 'POST'])
+def user_conversations(user_id):
+    """Gerenciar conversas do usuário"""
+    if request.method == 'POST':
+        data = request.get_json()
+        if save_user_data(user_id, 'conversations', data):
+            return jsonify({'success': True, 'message': 'Conversation saved'})
+        else:
+            return jsonify({'success': False, 'message': 'Failed to save conversation'}), 500
+    else:
+        conversations = load_user_data(user_id, 'conversations')
+        return jsonify({'conversations': conversations})
+
+@app.route('/user/<user_id>/analytics', methods=['GET'])
+def user_analytics(user_id):
+    """Obter analytics do usuário"""
+    analytics = load_user_data(user_id, 'analytics')
+    flashcards = load_user_data(user_id, 'flashcards')
+    conversations = load_user_data(user_id, 'conversations')
+    
+    return jsonify({
+        'total_flashcards': len(flashcards),
+        'total_conversations': len(conversations),
+        'total_sessions': len(analytics),
+        'recent_activity': analytics[-10:] if analytics else []
+    })
+
+# --- STATUS E ADMIN ---
+
+@app.route('/admin/stats', methods=['GET'])
+def admin_stats():
+    """Estatísticas do sistema"""
+    users = get_all_users()
+    stats = {
+        'total_users': len(users),
+        'users': []
+    }
+    
+    for user_id in users:
+        flashcards = len(load_user_data(user_id, 'flashcards'))
+        conversations = len(load_user_data(user_id, 'conversations'))
+        stats['users'].append({
+            'user_id': user_id,
+            'flashcards': flashcards,
+            'conversations': conversations
+        })
+    
+    return jsonify(stats)
+
+@app.route('/system/status', methods=['GET'])
+def system_status():
+    """Status do sistema"""
+    return jsonify({
+        'status': 'running',
+        'version': 'HF-Simplified-1.0',
+        'apis': {
+            'groq': groq_client is not None,
+            'gemini': genai_client is not None
+        },
+        'storage': 'file_based',
+        'auth': 'disabled'
+    })
+
+from study_plan import save_study_plan, load_study_plan, generate_study_plan
+
+@app.route('/study-plan', methods=['GET', 'POST'])
+def study_plan():
+    """Salvar ou carregar plano de estudos global (sem autenticação)"""
+    if request.method == 'POST':
+        try:
+            data = request.get_json()
+            plan = generate_study_plan(data)
+            save_study_plan(plan)
+            return jsonify({'success': True, 'message': 'Study plan generated and saved', 'plan': plan})
+        except Exception as e:
+            print(f"Erro ao salvar study plan: {e}")
+            return jsonify({'success': False, 'message': 'Failed to save study plan'}), 500
+    else:
+        try:
+            plan = load_study_plan()
+            return jsonify({'success': True, 'plan': plan})
+        except Exception as e:
+            print(f"Erro ao carregar study plan: {e}")
+            return jsonify({'success': False, 'message': 'Failed to load study plan'}), 500
+
+if __name__ == '__main__':
     app.run(host='0.0.0.0', port=7860, debug=True)

requirements.txt

@@ -1,16 +1,16 @@
-flask>=2.3.0
-gtts>=2.3.0
-google-generativeai>=0.3.0
-groq>=0.4.0
-requests>=2.31.0
-Pillow>=9.5.0
-werkzeug>=2.3.0
-email-validator>=2.0.0
-beautifulsoup4>=4.12.0
-feedparser>=6.0.0
-matplotlib>=3.7.0
-plotly>=5.15.0
-pandas>=2.0.0
-numpy>=1.24.0
-psutil>=5.9.0
+flask>=2.3.0
+gtts>=2.3.0
+google-generativeai>=0.3.0
+groq>=0.4.0
+requests>=2.31.0
+Pillow>=9.5.0
+werkzeug>=2.3.0
+email-validator>=2.0.0
+beautifulsoup4>=4.12.0
+feedparser>=6.0.0
+matplotlib>=3.7.0
+plotly>=5.15.0
+pandas>=2.0.0
+numpy>=1.24.0
+psutil>=5.9.0
 gradio>=4.0.0

study_plan.py

@@ -1,203 +1,203 @@
-import logging
-try:
-    from groq import Groq
-except ImportError:
-    Groq = None
-try:
-    import google.generativeai as genai
-except ImportError:
-    genai = None
-
-logger = logging.getLogger(__name__)
-groq_client = None
-genai_client = None
-try:
-    GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
-    if GROQ_API_KEY and Groq:
-        groq_client = Groq(api_key=GROQ_API_KEY)
-except Exception as e:
-    logger.warning(f"Groq client not available: {e}")
-try:
-    GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
-    if GEMINI_API_KEY and genai:
-        genai.configure(api_key=GEMINI_API_KEY)
-        genai_client = genai
-except Exception as e:
-    logger.warning(f"Gemini client not available: {e}")
-def generate_study_plan(user_data):
-    """Gera um plano de estudos estruturado a partir dos dados do usuário (sem IA)."""
-    from datetime import timedelta
-    current_level = user_data.get('english_level', 'B1')
-    target_level = user_data.get('target_level', 'B2')
-    weekly_hours = user_data.get('weekly_hours', 5)
-    interests = user_data.get('interests', {})
-    context_focus = user_data.get('context_focus', 'General/Social')
-    study_goals = user_data.get('study_goals', [])
-
-    # Progressão de níveis
-    level_progression = {
-        'A1': {'next': 'A2', 'weeks': 12},
-        'A2': {'next': 'B1', 'weeks': 16},
-        'B1': {'next': 'B2', 'weeks': 20},
-        'B2': {'next': 'C1', 'weeks': 24},
-        'C1': {'next': 'C2', 'weeks': 28},
-        'C2': {'next': 'C2', 'weeks': 32}
-    }
-    # Timeline
-    base_weeks = level_progression.get(current_level, level_progression['B1'])['weeks']
-    hour_multiplier = 5 / max(weekly_hours, 1)
-    adjusted_weeks = int(base_weeks * hour_multiplier)
-    from datetime import datetime
-    completion_date = (datetime.now() + timedelta(weeks=adjusted_weeks)).date().isoformat()
-
-    # Estrutura semanal
-    distributions = {
-        'A1': {'reading': 0.25, 'flashcards': 0.30, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
-        'A2': {'reading': 0.30, 'flashcards': 0.25, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
-        'B1': {'reading': 0.30, 'flashcards': 0.20, 'conversation': 0.25, 'writing': 0.20, 'listening': 0.05},
-        'B2': {'reading': 0.25, 'flashcards': 0.15, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
-        'C1': {'reading': 0.30, 'flashcards': 0.10, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
-        'C2': {'reading': 0.35, 'flashcards': 0.05, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10}
-    }
-    base_dist = distributions.get(current_level, distributions['B1'])
-    total_minutes = weekly_hours * 60
-    weekly_structure = {}
-    for activity, percentage in base_dist.items():
-        minutes = int(total_minutes * percentage)
-        if minutes >= 10:
-            weekly_structure[activity] = {
-                'minutes_per_week': minutes,
-                'sessions_per_week': max(1, minutes // 30),
-                'minutes_per_session': minutes // max(1, minutes // 30)
-            }
-
-    # Dicas de estudo (IA se disponível)
-    def get_default_tips(level):
-        tips_by_level = {
-            'A1': [
-                "📚 Start with basic vocabulary - 10 new words daily",
-                "🎯 Focus on present tense in daily conversations",
-                "💡 Use picture dictionaries for visual learning",
-                "⭐ Practice pronunciation with simple audio materials",
-                "🚀 Don't worry about mistakes - communication is key!"
-            ],
-            'A2': [
-                "📚 Read simple news articles and stories",
-                "🎯 Practice past and future tenses regularly",
-                "💡 Join basic English conversation groups",
-                "⭐ Use language learning apps for daily practice",
-                "🚀 Watch movies with subtitles in your language"
-            ],
-            'B1': [
-                "📚 Read intermediate articles on topics you enjoy",
-                "🎯 Practice expressing opinions and preferences",
-                "💡 Start writing short paragraphs daily",
-                "⭐ Listen to podcasts at normal speed",
-                "🚀 Try to think in English for simple tasks"
-            ],
-            'B2': [
-                "📚 Read longer articles and opinion pieces",
-                "🎯 Practice formal and informal writing styles",
-                "💡 Engage in debates and discussions",
-                "⭐ Watch news programs without subtitles",
-                "🚀 Set specific goals for each study session"
-            ],
-            'C1': [
-                "📚 Read academic and professional texts",
-                "🎯 Practice nuanced expressions and idioms",
-                "💡 Write formal reports and presentations",
-                "⭐ Listen to academic lectures and conferences",
-                "🚀 Focus on specialized vocabulary for your field"
-            ],
-            'C2': [
-                "📚 Read literature and complex analytical texts",
-                "🎯 Master subtle language differences",
-                "💡 Write with stylistic sophistication",
-                "⭐ Engage with native speakers in professional contexts",
-                "🚀 Aim for native-like fluency in all skills"
-            ]
-        }
-        return tips_by_level.get(level, tips_by_level['B1'])
-
-    def generate_ai_tips(user_data):
-        prompt = f"""
-        Generate 5 personalized English study tips for a user with these characteristics:
-        - Current Level: {user_data.get('english_level', 'B1')}
-        - Target Level: {user_data.get('target_level', 'B2')}
-        - Weekly Study Time: {user_data.get('weekly_hours', 5)} hours
-        - Context Focus: {user_data.get('context_focus', 'General/Social')}
-        - Interests: {', '.join(user_data.get('interests', {}).keys())}
-        Provide practical, actionable tips that are specific to their level and interests. Format as a simple list of tips, each starting with an emoji.
-        """
-        try:
-            if groq_client:
-                response = groq_client.chat.completions.create(
-                    model="llama-3.1-8b-instant",
-                    messages=[{"role": "user", "content": prompt}],
-                    temperature=0.7
-                )
-                response_text = response.choices[0].message.content
-            elif genai_client:
-                model = genai_client.GenerativeModel('gemini-2.5-flash-latest')
-                response = model.generate_content(prompt)
-                response_text = response.text
-            else:
-                return get_default_tips(user_data.get('english_level', 'B1'))
-            tips = [line.strip() for line in response_text.split('\n') if line.strip() and any(e in line for e in ['📚','💡','🎯','⭐','🚀'])]
-            return tips[:5] if tips else get_default_tips(user_data.get('english_level', 'B1'))
-        except Exception as e:
-            logger.warning(f"AI study tips error: {e}")
-            return get_default_tips(user_data.get('english_level', 'B1'))
-
-    study_tips = generate_ai_tips(user_data)
-
-    # Milestones
-    milestones = []
-    milestone_intervals = max(2, adjusted_weeks // 4)
-    for i in range(1, 5):
-        week = milestone_intervals * i
-        if week <= adjusted_weeks:
-            milestones.append({
-                'week': week,
-                'title': f"Milestone {i}",
-                'description': f"Progress checkpoint {i}",
-                'target_date': (datetime.now() + timedelta(weeks=week)).date().isoformat(),
-                'completed': False
-            })
-
-    plan = {
-        'id': f"plan_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
-        'created_at': datetime.now().isoformat(),
-        'current_level': current_level,
-        'target_level': target_level,
-        'weekly_hours': weekly_hours,
-        'estimated_weeks': adjusted_weeks,
-        'completion_date': completion_date,
-        'weekly_structure': weekly_structure,
-        'study_tips': study_tips,
-        'milestones': milestones,
-        'interests': interests,
-        'context_focus': context_focus,
-        'study_goals': study_goals
-    }
-    return plan
-import os
-import json
-from datetime import datetime
-
-STUDY_PLAN_PATH = 'hf_data/study_plan.json'
-
-def save_study_plan(plan_data):
-    """Salva o plano de estudos em JSON."""
-    os.makedirs(os.path.dirname(STUDY_PLAN_PATH), exist_ok=True)
-    plan_data['saved_at'] = datetime.now().isoformat()
-    with open(STUDY_PLAN_PATH, 'w', encoding='utf-8') as f:
-        json.dump(plan_data, f, ensure_ascii=False, indent=2)
-    return True
-
-def load_study_plan():
-    """Carrega o plano de estudos do JSON."""
-    if os.path.exists(STUDY_PLAN_PATH):
-        with open(STUDY_PLAN_PATH, 'r', encoding='utf-8') as f:
-            return json.load(f)
-    return None
+import logging
+try:
+    from groq import Groq
+except ImportError:
+    Groq = None
+try:
+    import google.generativeai as genai
+except ImportError:
+    genai = None
+
+logger = logging.getLogger(__name__)
+groq_client = None
+genai_client = None
+try:
+    GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
+    if GROQ_API_KEY and Groq:
+        groq_client = Groq(api_key=GROQ_API_KEY)
+except Exception as e:
+    logger.warning(f"Groq client not available: {e}")
+try:
+    GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
+    if GEMINI_API_KEY and genai:
+        genai.configure(api_key=GEMINI_API_KEY)
+        genai_client = genai
+except Exception as e:
+    logger.warning(f"Gemini client not available: {e}")
+def generate_study_plan(user_data):
+    """Gera um plano de estudos estruturado a partir dos dados do usuário (sem IA)."""
+    from datetime import timedelta
+    current_level = user_data.get('english_level', 'B1')
+    target_level = user_data.get('target_level', 'B2')
+    weekly_hours = user_data.get('weekly_hours', 5)
+    interests = user_data.get('interests', {})
+    context_focus = user_data.get('context_focus', 'General/Social')
+    study_goals = user_data.get('study_goals', [])
+
+    # Progressão de níveis
+    level_progression = {
+        'A1': {'next': 'A2', 'weeks': 12},
+        'A2': {'next': 'B1', 'weeks': 16},
+        'B1': {'next': 'B2', 'weeks': 20},
+        'B2': {'next': 'C1', 'weeks': 24},
+        'C1': {'next': 'C2', 'weeks': 28},
+        'C2': {'next': 'C2', 'weeks': 32}
+    }
+    # Timeline
+    base_weeks = level_progression.get(current_level, level_progression['B1'])['weeks']
+    hour_multiplier = 5 / max(weekly_hours, 1)
+    adjusted_weeks = int(base_weeks * hour_multiplier)
+    from datetime import datetime
+    completion_date = (datetime.now() + timedelta(weeks=adjusted_weeks)).date().isoformat()
+
+    # Estrutura semanal
+    distributions = {
+        'A1': {'reading': 0.25, 'flashcards': 0.30, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
+        'A2': {'reading': 0.30, 'flashcards': 0.25, 'conversation': 0.20, 'writing': 0.15, 'grammar': 0.10},
+        'B1': {'reading': 0.30, 'flashcards': 0.20, 'conversation': 0.25, 'writing': 0.20, 'listening': 0.05},
+        'B2': {'reading': 0.25, 'flashcards': 0.15, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
+        'C1': {'reading': 0.30, 'flashcards': 0.10, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10},
+        'C2': {'reading': 0.35, 'flashcards': 0.05, 'conversation': 0.25, 'writing': 0.25, 'listening': 0.10}
+    }
+    base_dist = distributions.get(current_level, distributions['B1'])
+    total_minutes = weekly_hours * 60
+    weekly_structure = {}
+    for activity, percentage in base_dist.items():
+        minutes = int(total_minutes * percentage)
+        if minutes >= 10:
+            weekly_structure[activity] = {
+                'minutes_per_week': minutes,
+                'sessions_per_week': max(1, minutes // 30),
+                'minutes_per_session': minutes // max(1, minutes // 30)
+            }
+
+    # Dicas de estudo (IA se disponível)
+    def get_default_tips(level):
+        tips_by_level = {
+            'A1': [
+                "📚 Start with basic vocabulary - 10 new words daily",
+                "🎯 Focus on present tense in daily conversations",
+                "💡 Use picture dictionaries for visual learning",
+                "⭐ Practice pronunciation with simple audio materials",
+                "🚀 Don't worry about mistakes - communication is key!"
+            ],
+            'A2': [
+                "📚 Read simple news articles and stories",
+                "🎯 Practice past and future tenses regularly",
+                "💡 Join basic English conversation groups",
+                "⭐ Use language learning apps for daily practice",
+                "🚀 Watch movies with subtitles in your language"
+            ],
+            'B1': [
+                "📚 Read intermediate articles on topics you enjoy",
+                "🎯 Practice expressing opinions and preferences",
+                "💡 Start writing short paragraphs daily",
+                "⭐ Listen to podcasts at normal speed",
+                "🚀 Try to think in English for simple tasks"
+            ],
+            'B2': [
+                "📚 Read longer articles and opinion pieces",
+                "🎯 Practice formal and informal writing styles",
+                "💡 Engage in debates and discussions",
+                "⭐ Watch news programs without subtitles",
+                "🚀 Set specific goals for each study session"
+            ],
+            'C1': [
+                "📚 Read academic and professional texts",
+                "🎯 Practice nuanced expressions and idioms",
+                "💡 Write formal reports and presentations",
+                "⭐ Listen to academic lectures and conferences",
+                "🚀 Focus on specialized vocabulary for your field"
+            ],
+            'C2': [
+                "📚 Read literature and complex analytical texts",
+                "🎯 Master subtle language differences",
+                "💡 Write with stylistic sophistication",
+                "⭐ Engage with native speakers in professional contexts",
+                "🚀 Aim for native-like fluency in all skills"
+            ]
+        }
+        return tips_by_level.get(level, tips_by_level['B1'])
+
+    def generate_ai_tips(user_data):
+        prompt = f"""
+        Generate 5 personalized English study tips for a user with these characteristics:
+        - Current Level: {user_data.get('english_level', 'B1')}
+        - Target Level: {user_data.get('target_level', 'B2')}
+        - Weekly Study Time: {user_data.get('weekly_hours', 5)} hours
+        - Context Focus: {user_data.get('context_focus', 'General/Social')}
+        - Interests: {', '.join(user_data.get('interests', {}).keys())}
+        Provide practical, actionable tips that are specific to their level and interests. Format as a simple list of tips, each starting with an emoji.
+        """
+        try:
+            if groq_client:
+                response = groq_client.chat.completions.create(
+                    model="llama-3.1-8b-instant",
+                    messages=[{"role": "user", "content": prompt}],
+                    temperature=0.7
+                )
+                response_text = response.choices[0].message.content
+            elif genai_client:
+                model = genai_client.GenerativeModel('gemini-2.5-flash-latest')
+                response = model.generate_content(prompt)
+                response_text = response.text
+            else:
+                return get_default_tips(user_data.get('english_level', 'B1'))
+            tips = [line.strip() for line in response_text.split('\n') if line.strip() and any(e in line for e in ['📚','💡','🎯','⭐','🚀'])]
+            return tips[:5] if tips else get_default_tips(user_data.get('english_level', 'B1'))
+        except Exception as e:
+            logger.warning(f"AI study tips error: {e}")
+            return get_default_tips(user_data.get('english_level', 'B1'))
+
+    study_tips = generate_ai_tips(user_data)
+
+    # Milestones
+    milestones = []
+    milestone_intervals = max(2, adjusted_weeks // 4)
+    for i in range(1, 5):
+        week = milestone_intervals * i
+        if week <= adjusted_weeks:
+            milestones.append({
+                'week': week,
+                'title': f"Milestone {i}",
+                'description': f"Progress checkpoint {i}",
+                'target_date': (datetime.now() + timedelta(weeks=week)).date().isoformat(),
+                'completed': False
+            })
+
+    plan = {
+        'id': f"plan_{datetime.now().strftime('%Y%m%d_%H%M%S')}",
+        'created_at': datetime.now().isoformat(),
+        'current_level': current_level,
+        'target_level': target_level,
+        'weekly_hours': weekly_hours,
+        'estimated_weeks': adjusted_weeks,
+        'completion_date': completion_date,
+        'weekly_structure': weekly_structure,
+        'study_tips': study_tips,
+        'milestones': milestones,
+        'interests': interests,
+        'context_focus': context_focus,
+        'study_goals': study_goals
+    }
+    return plan
+import os
+import json
+from datetime import datetime
+
+STUDY_PLAN_PATH = 'hf_data/study_plan.json'
+
+def save_study_plan(plan_data):
+    """Salva o plano de estudos em JSON."""
+    os.makedirs(os.path.dirname(STUDY_PLAN_PATH), exist_ok=True)
+    plan_data['saved_at'] = datetime.now().isoformat()
+    with open(STUDY_PLAN_PATH, 'w', encoding='utf-8') as f:
+        json.dump(plan_data, f, ensure_ascii=False, indent=2)
+    return True
+
+def load_study_plan():
+    """Carrega o plano de estudos do JSON."""
+    if os.path.exists(STUDY_PLAN_PATH):
+        with open(STUDY_PLAN_PATH, 'r', encoding='utf-8') as f:
+            return json.load(f)
+    return None