From 34e0661b0d2803280e79f26d3d1c9edd95c656d6 Mon Sep 17 00:00:00 2001 From: Arlei Nalasso Date: Thu, 23 Apr 2026 17:52:10 -0300 Subject: [PATCH] feat: initial MAIA monorepo - frontend, backend, diarization API - PWA React 18 + Vite + TypeScript com gravacao continua e upload de chunks - Backend FastAPI + Celery + PostgreSQL + Redis para processamento assincrono - Diarization API com SpeechBrain ECAPA-TDNN para identificacao de speakers - Integracao com Whisper.cpp GPU (large-v3) para transcricao - Integracao com LLM deepseek-v3.1 para analise de reunioes - Autenticacao SSO via Keycloak - README.md completo com arquitetura, instalacao e configuracao - CHANGELOG.md com historico v1.0.0 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --- .gitignore | 77 + CHANGELOG.md | 75 + README.md | 307 + backend/.env.example | 11 + backend/Dockerfile | 20 + backend/README.md | 82 + backend/alembic.ini | 41 + backend/alembic/env.py | 57 + backend/alembic/script.py.mako | 25 + 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+*.tar.gz + +# Data / Models (não versionar modelos grandes) +*.bin +*.pt +*.onnx +voice_db/ +speechbrain_cache/ +uploads/ +media/ + +# Audio files (storage) +storage/ + +# Logs +logs/ +*.log +npm-debug.log* +yarn-debug.log* +yarn-error.log* + +# Tests +.coverage +htmlcov/ +.pytest_cache/ + +# Alembic (manter só as migrations, não o cache) +__pycache__/ diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..87966aa --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,75 @@ +# Changelog + +Todas as mudanças notáveis neste projeto serão documentadas neste arquivo. + +O formato é baseado em [Keep a Changelog](https://keepachangelog.com/pt-BR/1.0.0/), +e este projeto adere ao [Versionamento Semântico](https://semver.org/lang/pt-BR/). + +--- + +## [1.0.0] - 2026-04-23 + +### Adicionado + +#### Frontend (PWA) +- PWA (Progressive Web App) instalável com React 18 + Vite + TypeScript +- Gravação contínua de áudio com MediaRecorder API (timeslice, sem gaps entre chunks) +- Upload automático de chunks de áudio com retry automático em caso de falha +- VU meter (visualizador de volume) na tela de gravação +- Autenticação via Keycloak SSO com refresh automático de token +- Tela de histórico de reuniões com busca e filtros +- Tela de detalhes da reunião: transcrição, análise e speakers +- Administração: gerenciamento de usuários, roles e delete de reuniões +- Enrollment de voz para identificação automática de speakers +- Branding MAIA: logo, cores e tipografia ASAP Telecom +- PWA instalável em Android (Chrome) e iOS (Safari) +- Suporte offline básico via Service Worker (Workbox) + +#### Backend API +- API REST com FastAPI + SQLAlchemy + Alembic +- PostgreSQL como banco de dados relacional +- Celery + Redis para processamento assíncrono de transcrições e análises +- Recepção e armazenamento de chunks de áudio +- Concatenação automática de chunks ao finalizar reunião +- Integração com Whisper GPU (large-v3) para transcrição +- Integração com Diarization API para identificação de speakers +- Integração com LLM (deepseek-v3.1) para análise e resumo +- Autenticação JWT via Keycloak com verificação de roles +- Endpoint de administração com controle de acesso por role +- Título automático de reunião: "Nome Usuário DD/MM/YYYY, HH:MM" +- Gestão de speakers: cadastro, enrollment e listagem +- API de busca no histórico de reuniões + +#### Diarization API +- API FastAPI dedicada para transcrição + diarização +- Integração com Whisper.cpp via HTTP (GPU AMD, servidor dedicado) +- Diarização de speakers com SpeechBrain ECAPA-TDNN (~85% precisão) +- Fallback para pyannote.audio quando necessário +- Banco de vozes para identificação automática de speakers conhecidos +- Enrollment de novas vozes via API +- Processamento de áudio com librosa (normalização, VAD) +- Speaker confidence threshold configurável + +#### Infraestrutura +- Containerização com Podman +- Nginx para servir o frontend e reverse proxy +- Serviços gerenciados via systemd +- GPU Server dedicado (10.100.16.13) para Whisper large-v3 +- LLM Server com Ollama (deepseek-v3.1:671b-cloud) +- Keycloak para SSO centralizado + +--- + +## [Unreleased] + +### Planejado +- Exportação de reuniões em PDF e DOCX +- Integração com Google Calendar e Outlook +- Resumos automáticos por e-mail +- Suporte a múltiplos idiomas na transcrição +- Dashboard de analytics de reuniões +- API pública documentada com Swagger + +--- + +[1.0.0]: https://github.com/ASAPTelecom/Maia/releases/tag/v1.0.0 diff --git a/README.md b/README.md new file mode 100644 index 0000000..9e37dbb --- /dev/null +++ b/README.md @@ -0,0 +1,307 @@ +# MAIA — Meeting AI Assistant + +

+ MAIA Logo +

+ +

+ Grave, transcreva e analise suas reuniões com Inteligência Artificial +

+ +

+ Instalação • + Arquitetura • + Configuração • + Deploy • + API +

+ +--- + +## 📖 Sobre o Projeto + +O **MAIA** (Meeting AI Assistant) é uma plataforma desenvolvida pela **ASAP Telecom** para gravar, transcrever e analisar reuniões automaticamente usando Inteligência Artificial. + +### ✨ Funcionalidades Principais + +- 🎙️ **Gravação contínua** de reuniões via navegador (sem gaps, usando MediaRecorder API com timeslice) +- 📝 **Transcrição automática** com Whisper.cpp na GPU (modelo large-v3, alta precisão) +- 👥 **Diarização de speakers** — identifica quem falou o quê (SpeechBrain ECAPA-TDNN, ~85% precisão) +- 🤖 **Análise com IA** — resumo, pontos de ação e insights com LLM (deepseek-v3.1) +- 🔐 **Autenticação SSO** via Keycloak +- 📱 **PWA instalável** em Android e iOS +- 🔎 **Histórico** com busca de reuniões passadas +- 👤 **Identificação de speakers** por enrollment de voz + +--- + +## 🏗️ Arquitetura + +``` +┌─────────────────────────────────────────────────────────────────┐ +│ CLIENTE │ +│ Browser / PWA (React 18 + Vite + TypeScript) │ +│ MediaRecorder API → chunks de áudio → upload automático │ +└────────────────────────┬────────────────────────────────────────┘ + │ HTTPS + ▼ +┌─────────────────────────────────────────────────────────────────┐ +│ APP SERVER (5.0.0.181) │ +│ ┌─────────────┐ ┌──────────────────┐ ┌──────────────────┐ │ +│ │ Nginx :80 │ │ Backend API :8090 │ │ Diarization :5060│ │ +│ │ (Frontend) │ │ FastAPI + Celery │ │ FastAPI+SpeechBr.│ │ +│ └─────────────┘ └────────┬─────────┘ └────────┬─────────┘ │ +│ │ │ │ +│ ┌─────────────┐ ┌────────▼─────────┐ │ │ +│ │ PostgreSQL │ │ Redis (Celery) │ │ │ +│ └─────────────┘ └──────────────────┘ │ │ +└────────────────────────────┬──────────────────────┼────────────┘ + │ │ + ┌──────────────▼──────┐ ┌──────────▼───────────┐ + │ GPU SERVER │ │ LLM Server │ + │ 10.100.16.13 :5003 │ │ asapai.asaptelecom. │ + │ Whisper.cpp GPU │ │ com.br/ollama │ + │ AMD GPU, large-v3 │ │ deepseek-v3.1:671b │ + └─────────────────────┘ └──────────────────────┘ + + ┌─────────────────────┐ + │ Keycloak SSO │ + │ Autenticação/Authz │ + └─────────────────────┘ +``` + +### 📁 Estrutura do Monorepo + +``` +Maia/ +├── frontend/ # PWA React 18 + Vite + TypeScript +├── backend/ # API FastAPI + Celery + PostgreSQL +├── diarization/ # API de Diarização com SpeechBrain +├── README.md +└── CHANGELOG.md +``` + +--- + +## ⚙️ Requisitos + +| Componente | Requisito | +|------------|-----------| +| Node.js | 18+ | +| Python | 3.11+ | +| PostgreSQL | 14+ | +| Redis | 7+ | +| GPU | AMD/NVIDIA (para Whisper GPU) | +| RAM | 16 GB mínimo (32 GB recomendado) | +| VRAM | 8 GB mínimo para Whisper large-v3 | + +--- + +## 🚀 Instalação + +### Frontend + +```bash +cd frontend +npm install +cp .env.example .env +# Edite o .env com as variáveis necessárias +npm run dev # desenvolvimento +npm run build # produção +``` + +### Backend + +```bash +cd backend +python -m venv venv +source venv/bin/activate # Linux/Mac +venv\Scripts\activate # Windows +pip install -r requirements.txt +cp .env.example .env +# Edite o .env com as variáveis necessárias +alembic upgrade head # aplicar migrações +uvicorn app.main:app --host 0.0.0.0 --port 8090 +``` + +### Diarization API + +```bash +cd diarization +python -m venv venv +source venv/bin/activate +pip install -r requirements.txt +cp .env.example .env +uvicorn main:app --host 0.0.0.0 --port 5060 +``` + +--- + +## 🔧 Configuração + +### Variáveis de Ambiente — Backend (`backend/.env`) + +```env +DATABASE_URL=postgresql://user:password@localhost:5432/maia +REDIS_URL=redis://localhost:6379/0 +KEYCLOAK_URL=https://seu-keycloak.exemplo.com +KEYCLOAK_REALM=seu-realm +KEYCLOAK_CLIENT_ID=maia-backend +OLLAMA_URL=https://llm.exemplo.com/ollama +OLLAMA_MODEL=deepseek-v3.1:671b-cloud +WHISPER_URL=http://gpu-server:5003 +``` + +### Variáveis de Ambiente — Diarization API (`diarization/.env`) + +```env +WHISPER_ORIGIN=http://gpu-server:5003 +VOICE_DB_PATH=/data/voice_db +SPEAKER_CONFIDENCE_THRESHOLD=0.75 +HF_TOKEN=seu_token_huggingface +SPEECHBRAIN_CACHE=/data/speechbrain_cache +``` + +### Variáveis de Ambiente — Frontend (`frontend/.env`) + +```env +VITE_API_URL=http://seu-backend:8090 +VITE_KEYCLOAK_URL=https://seu-keycloak.exemplo.com +VITE_KEYCLOAK_REALM=seu-realm +VITE_KEYCLOAK_CLIENT_ID=maia-frontend +``` + +--- + +## 🐳 Deploy + +### Com Podman/Docker Compose + +```bash +# Na raiz do projeto +podman-compose up -d +``` + +### Deploy Manual + +#### Backend (systemd) +```bash +# /etc/systemd/system/maia-backend.service +[Unit] +Description=MAIA Backend API +After=network.target postgresql.service redis.service + +[Service] +User=maia +WorkingDirectory=/opt/Backend/meeting-assistant-api +ExecStart=/opt/Backend/venv/bin/uvicorn app.main:app --host 0.0.0.0 --port 8090 +Restart=always + +[Install] +WantedBy=multi-user.target +``` + +#### Celery Worker +```bash +celery -A app.celery_app worker --loglevel=info -Q transcription,analysis +``` + +#### Frontend (Nginx) +```nginx +server { + listen 80; + root /var/www/maia; + index index.html; + + location / { + try_files $uri $uri/ /index.html; + } + + location /api/ { + proxy_pass http://localhost:8090/; + } +} +``` + +--- + +## 🔌 Endpoints Principais da API + +### Backend API (`http://server:8090`) + +| Método | Endpoint | Descrição | +|--------|----------|-----------| +| `POST` | `/meetings/` | Criar nova reunião | +| `GET` | `/meetings/` | Listar reuniões | +| `GET` | `/meetings/{id}` | Detalhes da reunião | +| `DELETE` | `/meetings/{id}` | Deletar reunião | +| `POST` | `/meetings/{id}/upload-chunk` | Upload de chunk de áudio | +| `POST` | `/meetings/{id}/finalize` | Finalizar e processar reunião | +| `GET` | `/meetings/{id}/transcript` | Transcrição completa | +| `GET` | `/meetings/{id}/analysis` | Análise da IA | +| `POST` | `/speakers/enroll` | Enrollar speaker com voz | +| `GET` | `/speakers/` | Listar speakers | +| `GET` | `/admin/users` | (Admin) Listar usuários | + +### Diarization API (`http://server:5060`) + +| Método | Endpoint | Descrição | +|--------|----------|-----------| +| `POST` | `/transcribe` | Transcrever + diarizar áudio | +| `POST` | `/enroll` | Enrollar voz de speaker | +| `GET` | `/speakers` | Listar speakers cadastrados | +| `DELETE` | `/speakers/{name}` | Remover speaker | +| `GET` | `/health` | Health check | + +--- + +## 🛠️ Tecnologias + +### Frontend +| Tecnologia | Versão | Uso | +|------------|--------|-----| +| React | 18 | Framework UI | +| Vite | 5 | Build tool | +| TypeScript | 5 | Tipagem estática | +| Zustand | 4 | Gerenciamento de estado | +| Axios | 1.x | Cliente HTTP | +| Workbox | 7 | PWA / Service Worker | +| MediaRecorder API | — | Gravação de áudio | + +### Backend +| Tecnologia | Versão | Uso | +|------------|--------|-----| +| FastAPI | 0.110+ | Framework API | +| SQLAlchemy | 2.x | ORM | +| Alembic | 1.x | Migrações de banco | +| PostgreSQL | 14+ | Banco de dados | +| Celery | 5.x | Processamento assíncrono | +| Redis | 7+ | Broker/Cache | +| httpx | 0.27+ | Cliente HTTP assíncrono | + +### Diarização & IA +| Tecnologia | Uso | +|------------|-----| +| Whisper.cpp | Transcrição de áudio (GPU) | +| SpeechBrain ECAPA-TDNN | Diarização de speakers | +| pyannote.audio | Diarização (fallback) | +| librosa | Processamento de áudio | +| deepseek-v3.1 | Análise e resumo de reuniões | + +### Infraestrutura +| Tecnologia | Uso | +|------------|-----| +| Podman | Containerização | +| Nginx | Reverse proxy / Servir frontend | +| systemd | Gerenciamento de serviços | +| Keycloak | SSO / Autenticação | + +--- + +## 📄 Licença + +Proprietário — ASAP Telecom. Todos os direitos reservados. + +--- + +

Desenvolvido com ❤️ pela equipe ASAP Telecom

diff --git a/backend/.env.example b/backend/.env.example new file mode 100644 index 0000000..53c76b8 --- /dev/null +++ b/backend/.env.example @@ -0,0 +1,11 @@ +WHISPER_SERVER_URL=http://host.docker.internal:9000 +OLLAMA_URL=http://host.docker.internal:11434 +OLLAMA_MODEL=llama3:8b +DATABASE_URL=postgresql://meetingassistant:meetingassistant@postgres:5432/meeting_assistant +REDIS_URL=redis://redis:6379/0 +JWT_SECRET=change_this_to_a_strong_secret_key_in_production +JWT_EXPIRE_MINUTES=60 +UPLOAD_MAX_SIZE_MB=500 +SPEAKER_CONFIDENCE_THRESHOLD=0.75 +AUDIO_STORAGE_PATH=/opt/Backend/meeting-assistant-api/storage/audio +ALLOWED_ORIGINS=* diff --git a/backend/Dockerfile b/backend/Dockerfile new file mode 100644 index 0000000..b2c36fd --- /dev/null +++ b/backend/Dockerfile @@ -0,0 +1,20 @@ +FROM python:3.11-slim + +WORKDIR /app + +RUN apt-get update && apt-get install -y \ + gcc \ + libpq-dev \ + curl \ + && rm -rf /var/lib/apt/lists/* + +COPY requirements.txt . +RUN pip install --no-cache-dir -r requirements.txt + +COPY . . + +RUN mkdir -p /opt/Backend/meeting-assistant-api/storage/audio + +EXPOSE 8000 + +CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "2"] diff --git a/backend/README.md b/backend/README.md new file mode 100644 index 0000000..1c53bc5 --- /dev/null +++ b/backend/README.md @@ -0,0 +1,82 @@ +# Meeting Assistant API + +FastAPI orchestration backend for Meeting Assistant - middleware between Mobile App, Whisper, and Ollama. + +## Architecture + +``` +Mobile App → FastAPI API → Whisper (transcription) + Ollama (AI analysis) + → PostgreSQL (data) + Redis (queues/cache) + → Celery Worker (async processing) +``` + +## Quick Start + +```bash +cp .env.example .env +docker-compose up -d +docker-compose exec api alembic upgrade head +``` + +## API Documentation + +- **Swagger UI:** http://localhost:8080/docs +- **ReDoc:** http://localhost:8080/redoc + +## Endpoints + +### Auth +- `POST /api/auth/register` - Register new user +- `POST /api/auth/login` - Login (returns JWT) +- `POST /api/auth/refresh` - Refresh access token +- `GET /api/auth/me` - Get current user + +### Meetings +- `POST /api/meetings/upload` - Upload audio + trigger processing +- `GET /api/meetings` - List meetings +- `GET /api/meetings/{id}` - Get meeting details +- `GET /api/meetings/{id}/status` - Get processing status +- `GET /api/meetings/{id}/analyses` - Get all analyses +- `GET /api/meetings/{id}/analyses/{type}` - Get specific analysis +- `PUT /api/meetings/{id}/participants/{label}` - Update speaker name +- `DELETE /api/meetings/{id}` - Delete meeting + +### WebSocket +- `WS /ws/meetings/{meeting_id}` - Real-time status updates + +### Health +- `GET /health` - Health check + +## Processing Pipeline + +1. Audio uploaded → saved to storage/ +2. Celery task queued +3. Audio sent to Whisper for diarized transcription +4. Transcription sent to Ollama for parallel analyses: + - `minutes` - Structured meeting minutes + - `sentiment` - Emotional tone analysis + - `psychological` - Behavioral patterns + - `communication` - Communication quality feedback + - `summary` - Executive summary +5. Status updated to `completed` +6. WebSocket notification sent + +## Environment Variables + +See `.env.example` for all configuration options. + +## Development + +```bash +# View logs +docker-compose logs -f api + +# Run migrations +docker-compose exec api alembic upgrade head + +# Create new migration +docker-compose exec api alembic revision --autogenerate -m "description" + +# Check celery worker +docker-compose logs -f worker +``` diff --git a/backend/alembic.ini b/backend/alembic.ini new file mode 100644 index 0000000..c3e3c9b --- /dev/null +++ b/backend/alembic.ini @@ -0,0 +1,41 @@ +[alembic] +script_location = alembic +prepend_sys_path = . +version_path_separator = os +sqlalchemy.url = postgresql://meetingassistant:meetingassistant@postgres:5432/meeting_assistant + +[post_write_hooks] + +[loggers] +keys = root,sqlalchemy,alembic + +[handlers] +keys = console + +[formatters] +keys = generic + +[logger_root] +level = WARN +handlers = console +qualname = + +[logger_sqlalchemy] +level = WARN +handlers = +qualname = sqlalchemy.engine + +[logger_alembic] +level = INFO +handlers = +qualname = alembic + +[handler_console] +class = StreamHandler +args = (sys.stderr,) +level = NOTSET +formatter = generic + +[formatter_generic] +format = %(levelname)-5.5s [%(name)s] %(message)s +datefmt = %H:%M:%S diff --git a/backend/alembic/env.py b/backend/alembic/env.py new file mode 100644 index 0000000..c730d2f --- /dev/null +++ b/backend/alembic/env.py @@ -0,0 +1,57 @@ +import os +import sys +from logging.config import fileConfig +from sqlalchemy import engine_from_config, pool +from alembic import context + +sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + +from dotenv import load_dotenv +load_dotenv() + +config = context.config + +if config.config_file_name is not None: + fileConfig(config.config_file_name) + +database_url = os.environ.get("DATABASE_URL", "") +if database_url: + config.set_main_option("sqlalchemy.url", database_url) + +from app.database import Base +from app.models.user import User +from app.models.meeting import Meeting +from app.models.analysis import Analysis +from app.models.participant import MeetingParticipant + +target_metadata = Base.metadata + + +def run_migrations_offline() -> None: + url = config.get_main_option("sqlalchemy.url") + context.configure( + url=url, + target_metadata=target_metadata, + literal_binds=True, + dialect_opts={"paramstyle": "named"}, + ) + with context.begin_transaction(): + context.run_migrations() + + +def run_migrations_online() -> None: + connectable = engine_from_config( + config.get_section(config.config_ini_section, {}), + prefix="sqlalchemy.", + poolclass=pool.NullPool, + ) + with connectable.connect() as connection: + context.configure(connection=connection, target_metadata=target_metadata) + with context.begin_transaction(): + context.run_migrations() + + +if context.is_offline_mode(): + run_migrations_offline() +else: + run_migrations_online() diff --git a/backend/alembic/script.py.mako b/backend/alembic/script.py.mako new file mode 100644 index 0000000..17dcba0 --- /dev/null +++ b/backend/alembic/script.py.mako @@ -0,0 +1,25 @@ +"""${message} + +Revision ID: ${up_revision} +Revises: ${down_revision | comma,n} +Create Date: ${create_date} + +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa +${imports if imports else ""} + +revision: str = ${repr(up_revision)} +down_revision: Union[str, None] = ${repr(down_revision)} +branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)} +depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)} + + +def upgrade() -> None: + ${upgrades if upgrades else "pass"} + + +def downgrade() -> None: + ${downgrades if downgrades else "pass"} diff --git a/backend/alembic/versions/5965c1a94621_initial_schema.py b/backend/alembic/versions/5965c1a94621_initial_schema.py new file mode 100644 index 0000000..63c14a3 --- /dev/null +++ b/backend/alembic/versions/5965c1a94621_initial_schema.py @@ -0,0 +1,89 @@ +"""initial_schema + +Revision ID: 5965c1a94621 +Revises: +Create Date: 2026-04-13 20:25:03.459694 + +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa + + +revision: str = '5965c1a94621' +down_revision: Union[str, None] = None +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + + +def upgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + op.create_table('users', + sa.Column('id', sa.UUID(), nullable=False), + sa.Column('email', sa.String(), nullable=False), + sa.Column('password_hash', sa.String(), nullable=False), + sa.Column('name', sa.String(), nullable=False), + sa.Column('created_at', sa.DateTime(), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + op.create_index(op.f('ix_users_email'), 'users', ['email'], unique=True) + op.create_index(op.f('ix_users_id'), 'users', ['id'], unique=False) + op.create_table('meetings', + sa.Column('id', sa.UUID(), nullable=False), + sa.Column('title', sa.String(), nullable=True), + sa.Column('date', sa.DateTime(), nullable=False), + sa.Column('duration', sa.Integer(), nullable=True), + sa.Column('audio_path', sa.String(), nullable=True), + sa.Column('status', sa.Enum('uploading', 'processing', 'transcribing', 'analyzing', 'completed', 'error', name='meetingstatus'), nullable=False), + sa.Column('transcription', sa.JSON(), nullable=True), + sa.Column('user_id', sa.UUID(), nullable=False), + sa.Column('created_at', sa.DateTime(), nullable=False), + sa.ForeignKeyConstraint(['user_id'], ['users.id'], ), + sa.PrimaryKeyConstraint('id') + ) + op.create_index(op.f('ix_meetings_id'), 'meetings', ['id'], unique=False) + op.create_index(op.f('ix_meetings_user_id'), 'meetings', ['user_id'], unique=False) + op.create_table('analyses', + sa.Column('id', sa.UUID(), nullable=False), + sa.Column('meeting_id', sa.UUID(), nullable=False), + sa.Column('type', sa.Enum('minutes', 'sentiment', 'psychological', 'communication', 'summary', name='analysistype'), nullable=False), + sa.Column('content', sa.JSON(), nullable=False), + sa.Column('model_used', sa.String(), nullable=True), + sa.Column('created_at', sa.DateTime(), nullable=False), + sa.ForeignKeyConstraint(['meeting_id'], ['meetings.id'], ), + sa.PrimaryKeyConstraint('id') + ) + op.create_index(op.f('ix_analyses_id'), 'analyses', ['id'], unique=False) + op.create_index(op.f('ix_analyses_meeting_id'), 'analyses', ['meeting_id'], unique=False) + op.create_table('meeting_participants', + sa.Column('id', sa.UUID(), nullable=False), + sa.Column('meeting_id', sa.UUID(), nullable=False), + sa.Column('speaker_label', sa.String(), nullable=False), + sa.Column('voice_profile_id', sa.UUID(), nullable=True), + sa.Column('identified_name', sa.String(), nullable=True), + sa.Column('confidence_score', sa.Float(), nullable=True), + sa.Column('talk_time_seconds', sa.Integer(), nullable=True), + sa.ForeignKeyConstraint(['meeting_id'], ['meetings.id'], ), + sa.PrimaryKeyConstraint('id') + ) + op.create_index(op.f('ix_meeting_participants_id'), 'meeting_participants', ['id'], unique=False) + op.create_index(op.f('ix_meeting_participants_meeting_id'), 'meeting_participants', ['meeting_id'], unique=False) + # ### end Alembic commands ### + + +def downgrade() -> None: + # ### commands auto generated by Alembic - please adjust! ### + op.drop_index(op.f('ix_meeting_participants_meeting_id'), table_name='meeting_participants') + op.drop_index(op.f('ix_meeting_participants_id'), table_name='meeting_participants') + op.drop_table('meeting_participants') + op.drop_index(op.f('ix_analyses_meeting_id'), table_name='analyses') + op.drop_index(op.f('ix_analyses_id'), table_name='analyses') + op.drop_table('analyses') + op.drop_index(op.f('ix_meetings_user_id'), table_name='meetings') + op.drop_index(op.f('ix_meetings_id'), table_name='meetings') + op.drop_table('meetings') + op.drop_index(op.f('ix_users_id'), table_name='users') + op.drop_index(op.f('ix_users_email'), table_name='users') + op.drop_table('users') + # ### end Alembic commands ### diff --git a/backend/app/__init__.py b/backend/app/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/config.py b/backend/app/config.py new file mode 100644 index 0000000..c157e9d --- /dev/null +++ b/backend/app/config.py @@ -0,0 +1,22 @@ +from pydantic_settings import BaseSettings + +class Settings(BaseSettings): + WHISPER_SERVER_URL: str = "http://localhost:9000" + OLLAMA_URL: str = "http://localhost:11434" + OLLAMA_MODEL: str = "llama3:8b" + OLLAMA_API_KEY: str = "" + DATABASE_URL: str = "postgresql://meetingassistant:meetingassistant@postgres:5432/meeting_assistant" + REDIS_URL: str = "redis://redis:6379/0" + JWT_SECRET: str = "change_this_to_a_strong_secret_key_in_production" + JWT_EXPIRE_MINUTES: int = 60 + JWT_REFRESH_EXPIRE_DAYS: int = 7 + UPLOAD_MAX_SIZE_MB: int = 500 + SPEAKER_CONFIDENCE_THRESHOLD: float = 0.75 + AUDIO_STORAGE_PATH: str = "/opt/Backend/meeting-assistant-api/storage/audio" + ALLOWED_ORIGINS: str = "*" + + class Config: + env_file = ".env" + extra = "allow" + +settings = Settings() diff --git a/backend/app/database.py b/backend/app/database.py new file mode 100644 index 0000000..33f93b3 --- /dev/null +++ b/backend/app/database.py @@ -0,0 +1,25 @@ +from sqlalchemy import create_engine +from sqlalchemy.orm import sessionmaker, DeclarativeBase +from app.config import settings + + +engine = create_engine( + settings.DATABASE_URL, + pool_pre_ping=True, + pool_size=10, + max_overflow=20, +) + +SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) + + +class Base(DeclarativeBase): + pass + + +def get_db(): + db = SessionLocal() + try: + yield db + finally: + db.close() diff --git a/backend/app/main.py b/backend/app/main.py new file mode 100644 index 0000000..a482687 --- /dev/null +++ b/backend/app/main.py @@ -0,0 +1,92 @@ +import logging +import json +from fastapi import FastAPI, Request, WebSocket, WebSocketDisconnect +from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import JSONResponse +from contextlib import asynccontextmanager +from app.routers import auth, meetings, analyses +from app.config import settings +from app.services.websocket_service import manager + + +class JSONFormatter(logging.Formatter): + def format(self, record): + log_record = { + "level": record.levelname, + "message": record.getMessage(), + "logger": record.name, + "time": self.formatTime(record), + } + if record.exc_info: + log_record["exception"] = self.formatException(record.exc_info) + return json.dumps(log_record, ensure_ascii=False) + + +handler = logging.StreamHandler() +handler.setFormatter(JSONFormatter()) +logging.basicConfig(handlers=[handler], level=logging.INFO, force=True) +logger = logging.getLogger(__name__) + + +@asynccontextmanager +async def lifespan(app: FastAPI): + logger.info(json.dumps({"event": "startup", "message": "Meeting Assistant API starting"})) + yield + logger.info(json.dumps({"event": "shutdown", "message": "Meeting Assistant API stopping"})) + + +app = FastAPI( + title="Meeting Assistant API", + description="Orchestration server for Meeting Assistant - middleware between Mobile App and AI services", + version="1.0.0", + lifespan=lifespan, + docs_url="/docs", + redoc_url="/redoc", +) + +origins = settings.ALLOWED_ORIGINS.split(",") if settings.ALLOWED_ORIGINS != "*" else ["*"] +app.add_middleware( + CORSMiddleware, + allow_origins=origins, + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +app.include_router(auth.router, prefix="/api/auth", tags=["auth"]) +app.include_router(meetings.router, prefix="/api/meetings", tags=["meetings"]) +app.include_router(analyses.router, prefix="/api", tags=["analyses"]) + + +@app.get("/health", tags=["health"]) +async def health_check(): + return { + "status": "healthy", + "service": "meeting-assistant-api", + "version": "1.0.0", + } + + +@app.websocket("/ws/meetings/{meeting_id}") +async def websocket_endpoint(websocket: WebSocket, meeting_id: str): + await manager.connect(websocket, meeting_id) + try: + while True: + data = await websocket.receive_text() + await manager.send_message(meeting_id, {"type": "ping", "data": data}) + except WebSocketDisconnect: + manager.disconnect(websocket, meeting_id) + + +@app.exception_handler(Exception) +async def global_exception_handler(request: Request, exc: Exception): + logger.error(json.dumps({ + "event": "unhandled_exception", + "error": str(exc), + "path": str(request.url), + "method": request.method, + })) + return JSONResponse( + status_code=500, + content={"detail": "Internal server error"}, + ) diff --git a/backend/app/models/__init__.py b/backend/app/models/__init__.py new file mode 100644 index 0000000..353116d --- /dev/null +++ b/backend/app/models/__init__.py @@ -0,0 +1,4 @@ +from app.models.user import User +from app.models.meeting import Meeting, MeetingStatus +from app.models.analysis import Analysis, AnalysisType +from app.models.participant import MeetingParticipant diff --git a/backend/app/models/analysis.py b/backend/app/models/analysis.py new file mode 100644 index 0000000..746dc86 --- /dev/null +++ b/backend/app/models/analysis.py @@ -0,0 +1,28 @@ +import uuid +import enum +from datetime import datetime +from sqlalchemy import Column, String, DateTime, JSON, Enum, ForeignKey +from sqlalchemy.dialects.postgresql import UUID +from sqlalchemy.orm import relationship +from app.database import Base + + +class AnalysisType(str, enum.Enum): + minutes = "minutes" + sentiment = "sentiment" + psychological = "psychological" + communication = "communication" + summary = "summary" + + +class Analysis(Base): + __tablename__ = "analyses" + + id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True) + meeting_id = Column(UUID(as_uuid=True), ForeignKey("meetings.id"), nullable=False, index=True) + type = Column(Enum(AnalysisType), nullable=False) + content = Column(JSON, nullable=False, default=dict) + model_used = Column(String, nullable=True) + created_at = Column(DateTime, default=datetime.utcnow, nullable=False) + + meeting = relationship("Meeting", back_populates="analyses") diff --git a/backend/app/models/meeting.py b/backend/app/models/meeting.py new file mode 100644 index 0000000..b0fee0f --- /dev/null +++ b/backend/app/models/meeting.py @@ -0,0 +1,41 @@ +import uuid +import enum +from datetime import datetime +from sqlalchemy import Column, String, DateTime, Integer, JSON, Enum, ForeignKey +from sqlalchemy.dialects.postgresql import UUID +from sqlalchemy.orm import relationship +from app.database import Base + +class MeetingStatus(str, enum.Enum): + receiving_chunks = "receiving_chunks" + uploading = "uploading" + processing = "processing" + transcribing = "transcribing" + analyzing = "analyzing" + completed = "completed" + error = "error" + +class Meeting(Base): + __tablename__ = "meetings" + + id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True) + title = Column(String, nullable=True) + date = Column(DateTime, default=datetime.utcnow, nullable=False) + duration = Column(Integer, nullable=True) + audio_path = Column(String, nullable=True) + status = Column(Enum(MeetingStatus), default=MeetingStatus.uploading, nullable=False) + transcription = Column(JSON, nullable=True) + user_id = Column(UUID(as_uuid=True), ForeignKey("users.id"), nullable=False, index=True) + created_at = Column(DateTime, default=datetime.utcnow, nullable=False) + + user = relationship("User", back_populates="meetings") + analyses = relationship("Analysis", back_populates="meeting", cascade="all, delete-orphan") + participants = relationship("MeetingParticipant", back_populates="meeting", cascade="all, delete-orphan") + + @property + def owner_email(self): + return self.user.email if self.user else None + + @property + def owner_name(self): + return self.user.name if self.user else None diff --git a/backend/app/models/participant.py b/backend/app/models/participant.py new file mode 100644 index 0000000..aeca829 --- /dev/null +++ b/backend/app/models/participant.py @@ -0,0 +1,20 @@ +import uuid +from datetime import datetime +from sqlalchemy import Column, String, DateTime, Integer, Float, ForeignKey +from sqlalchemy.dialects.postgresql import UUID +from sqlalchemy.orm import relationship +from app.database import Base + + +class MeetingParticipant(Base): + __tablename__ = "meeting_participants" + + id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True) + meeting_id = Column(UUID(as_uuid=True), ForeignKey("meetings.id"), nullable=False, index=True) + speaker_label = Column(String, nullable=False) + voice_profile_id = Column(UUID(as_uuid=True), nullable=True) + identified_name = Column(String, nullable=True) + confidence_score = Column(Float, nullable=True) + talk_time_seconds = Column(Integer, nullable=True) + + meeting = relationship("Meeting", back_populates="participants") diff --git a/backend/app/models/user.py b/backend/app/models/user.py new file mode 100644 index 0000000..d528cbf --- /dev/null +++ b/backend/app/models/user.py @@ -0,0 +1,18 @@ +import uuid +from datetime import datetime +from sqlalchemy import Column, String, DateTime, JSON +from sqlalchemy.dialects.postgresql import UUID +from sqlalchemy.orm import relationship +from app.database import Base + +class User(Base): + __tablename__ = "users" + + id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, index=True) + email = Column(String, unique=True, index=True, nullable=False) + password_hash = Column(String, nullable=False) + name = Column(String, nullable=False) + roles = Column(JSON, default=list, nullable=False, server_default="[]") + created_at = Column(DateTime, default=datetime.utcnow, nullable=False) + + meetings = relationship("Meeting", back_populates="user", cascade="all, delete-orphan") diff --git a/backend/app/routers/__init__.py b/backend/app/routers/__init__.py new file mode 100644 index 0000000..379e377 --- /dev/null +++ b/backend/app/routers/__init__.py @@ -0,0 +1 @@ +from app.routers import auth, meetings, analyses diff --git a/backend/app/routers/analyses.py b/backend/app/routers/analyses.py new file mode 100644 index 0000000..e985f1a --- /dev/null +++ b/backend/app/routers/analyses.py @@ -0,0 +1,5 @@ +from fastapi import APIRouter + +router = APIRouter() +# Analysis endpoints are served through /api/meetings/{id}/analyses +# See app/routers/meetings.py for implementation diff --git a/backend/app/routers/auth.py b/backend/app/routers/auth.py new file mode 100644 index 0000000..d3e4148 --- /dev/null +++ b/backend/app/routers/auth.py @@ -0,0 +1,60 @@ +from fastapi import APIRouter, Depends, HTTPException +from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials +from pydantic import BaseModel +from sqlalchemy.orm import Session +from app.database import get_db +from app.schemas.auth import UserRegister, UserLogin, TokenRefresh, TokenResponse, UserResponse +from app.services.auth_service import ( + register_user, + login_user, + refresh_tokens, + get_current_user, + get_or_create_sso_user, +) +from app.utils.keycloak_auth import validate_keycloak_token, has_role, extract_user_info +from app.utils.security import create_access_token, create_refresh_token + +MAIA_ROLES = ["maia.app", "maia.admin"] + +router = APIRouter() +_bearer = HTTPBearer() + +@router.post("/register", response_model=UserResponse, status_code=201) +def register(data: UserRegister, db: Session = Depends(get_db)): + return register_user(db, data.email, data.password, data.name) + +@router.post("/login", response_model=TokenResponse) +def login(data: UserLogin, db: Session = Depends(get_db)): + return login_user(db, data.email, data.password) + +@router.post("/refresh", response_model=TokenResponse) +def refresh(data: TokenRefresh): + return refresh_tokens(data.refresh_token) + +@router.get("/me", response_model=UserResponse) +def me(current_user=Depends(get_current_user)): + return current_user + +class KeycloakAuthRequest(BaseModel): + kc_token: str + +@router.post("/keycloak", response_model=TokenResponse) +def keycloak_login(data: KeycloakAuthRequest, db: Session = Depends(get_db)): + """Exchange a Keycloak RS256 access token for internal HS256 JWT tokens.""" + payload = validate_keycloak_token(data.kc_token) + if not payload: + raise HTTPException(status_code=401, detail="Token Keycloak invalido ou expirado") + + if not has_role(payload, "maia.app"): + raise HTTPException(status_code=403, detail="Acesso negado: role maia.app nao encontrada") + + user_info = extract_user_info(payload) + + # Collect all maia.* roles the user has + user_roles = [r for r in MAIA_ROLES if has_role(payload, r)] + + user = get_or_create_sso_user(db, user_info, roles=user_roles) + + access_token = create_access_token(str(user.id)) + refresh_token = create_refresh_token(str(user.id)) + return {"access_token": access_token, "refresh_token": refresh_token, "token_type": "bearer"} diff --git a/backend/app/routers/meetings.py b/backend/app/routers/meetings.py new file mode 100644 index 0000000..87b7b8a --- /dev/null +++ b/backend/app/routers/meetings.py @@ -0,0 +1,378 @@ +from datetime import datetime +import uuid +from fastapi.responses import FileResponse +import os +import logging +from typing import List, Optional +from fastapi import APIRouter, Depends, UploadFile, File, HTTPException, Form, Query, Body +from sqlalchemy.orm import Session, joinedload +from app.database import get_db +from app.models.meeting import Meeting, MeetingStatus +from app.models.participant import MeetingParticipant +from app.schemas.meeting import MeetingResponse, MeetingStatusResponse, ParticipantUpdate, ParticipantResponse +from app.services.auth_service import get_current_user, is_admin +from app.services.upload_service import save_audio_file +from app.services.chunk_service import save_chunk, assemble_chunks, cleanup_chunks +from app.tasks.processing import process_meeting +import httpx +from app.config import settings + +logger = logging.getLogger(__name__) +router = APIRouter() + +AUDIO_STORAGE = "/opt/Backend/meeting-assistant-api/storage/audio" + +def _get_meeting_for_user(meeting_id: str, current_user, db: Session) -> Meeting: + """Return meeting if user owns it or is admin. Raises 404 otherwise.""" + q = db.query(Meeting).options(joinedload(Meeting.user)).filter(Meeting.id == meeting_id) + if not is_admin(current_user): + q = q.filter(Meeting.user_id == current_user.id) + meeting = q.first() + if not meeting: + raise HTTPException(status_code=404, detail="Meeting not found") + return meeting + + +@router.post("/upload", response_model=MeetingResponse, status_code=201) +async def upload_meeting( + file: UploadFile = File(...), + title: Optional[str] = Query(None), + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + meeting_id = str(uuid.uuid4()) + audio_path = await save_audio_file(file, meeting_id) + meeting = Meeting( + id=meeting_id, title=title or file.filename or "Meeting", + audio_path=audio_path, status=MeetingStatus.uploading, user_id=current_user.id, + ) + db.add(meeting) + db.commit() + db.refresh(meeting) + process_meeting.delay(meeting_id) + logger.info(f"Meeting {meeting_id} created and queued for processing") + return meeting + + +@router.post("/start", response_model=MeetingResponse, status_code=201) +async def start_meeting( + title: Optional[str] = Query(None), + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + meeting_id = str(uuid.uuid4()) + from datetime import timezone, timedelta + br_tz = timezone(timedelta(hours=-3)) + now_br = datetime.now(br_tz) + default_title = f"{current_user.name} {now_br.strftime('%d/%m/%Y, %H:%M')}" + meeting = Meeting( + id=meeting_id, title=title or default_title, + status=MeetingStatus.receiving_chunks, user_id=current_user.id, + ) + db.add(meeting) + db.commit() + db.refresh(meeting) + logger.info(f"Meeting {meeting_id} started (chunk mode)") + return meeting + + +@router.get("", response_model=List[MeetingResponse]) +def list_meetings( + skip: int = 0, + limit: int = 50, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + """List meetings. Admins see all meetings with owner info; users see only their own.""" + q = db.query(Meeting).options(joinedload(Meeting.user)) + if not is_admin(current_user): + q = q.filter(Meeting.user_id == current_user.id) + meetings = q.order_by(Meeting.created_at.desc()).offset(skip).limit(limit).all() + return meetings + + +@router.post("/{meeting_id}/chunks", status_code=200) +async def upload_chunk( + meeting_id: str, + file: UploadFile = File(...), + chunk_index: int = Form(...), + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + meeting = db.query(Meeting).filter( + Meeting.id == meeting_id, Meeting.user_id == current_user.id + ).first() + if not meeting: + raise HTTPException(status_code=404, detail="Meeting not found") + if meeting.status not in (MeetingStatus.receiving_chunks, MeetingStatus.uploading): + raise HTTPException(status_code=409, detail=f"Meeting not accepting chunks (status: {meeting.status})") + ext = os.path.splitext(file.filename or "chunk.webm")[1].lower() or ".webm" + data = await file.read() + save_chunk(data, meeting_id, chunk_index, ext) + logger.info(f"Chunk {chunk_index} received for meeting {meeting_id} ({len(data)} bytes)") + return {"meeting_id": meeting_id, "chunk_index": chunk_index, "size": len(data)} + + +@router.post("/{meeting_id}/finalize", response_model=MeetingResponse) +async def finalize_meeting( + meeting_id: str, + title: Optional[str] = Query(None), + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + meeting = db.query(Meeting).filter( + Meeting.id == meeting_id, Meeting.user_id == current_user.id + ).first() + if not meeting: + raise HTTPException(status_code=404, detail="Meeting not found") + if title and not meeting.title: + meeting.title = title + try: + audio_path = assemble_chunks(meeting_id) + meeting.audio_path = audio_path + meeting.status = MeetingStatus.uploading + db.commit() + cleanup_chunks(meeting_id) + process_meeting.delay(meeting_id) + logger.info(f"Meeting {meeting_id} finalized and queued for processing") + except Exception as e: + meeting.status = MeetingStatus.error + db.commit() + logger.error(f"Failed to finalize meeting {meeting_id}: {e}") + raise HTTPException(status_code=500, detail=f"Failed to assemble audio: {str(e)}") + db.refresh(meeting) + return meeting + + +@router.get("/{meeting_id}", response_model=MeetingResponse) +def get_meeting( + meeting_id: str, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + return _get_meeting_for_user(meeting_id, current_user, db) + + +@router.get("/{meeting_id}/status", response_model=MeetingStatusResponse) +def get_meeting_status( + meeting_id: str, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + return _get_meeting_for_user(meeting_id, current_user, db) + + +@router.get("/{meeting_id}/audio") +def get_meeting_audio( + meeting_id: str, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + """Stream the audio file for a meeting.""" + meeting = _get_meeting_for_user(meeting_id, current_user, db) + if not meeting.audio_path or not os.path.exists(meeting.audio_path): + # Try common extensions + for ext in [".webm", ".wav", ".m4a", ".mp3", ".ogg"]: + candidate = os.path.join(AUDIO_STORAGE, f"{meeting_id}{ext}") + if os.path.exists(candidate): + meeting.audio_path = candidate + break + else: + raise HTTPException(status_code=404, detail="Audio file not found") + ext = os.path.splitext(meeting.audio_path)[1].lower() + mime_map = {".webm": "audio/webm", ".wav": "audio/wav", ".mp3": "audio/mpeg", + ".m4a": "audio/mp4", ".ogg": "audio/ogg"} + media_type = mime_map.get(ext, "audio/webm") + return FileResponse(meeting.audio_path, media_type=media_type) + + +@router.get("/{meeting_id}/analyses") +def get_meeting_analyses( + meeting_id: str, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + meeting = _get_meeting_for_user(meeting_id, current_user, db) + return meeting.analyses + + +@router.get("/{meeting_id}/analyses/{analysis_type}") +def get_meeting_analysis_by_type( + meeting_id: str, + analysis_type: str, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + meeting = _get_meeting_for_user(meeting_id, current_user, db) + from app.models.analysis import AnalysisType, Analysis + try: + atype = AnalysisType(analysis_type) + except ValueError: + raise HTTPException(status_code=400, + detail=f"Invalid analysis type '{analysis_type}'. Valid: minutes, sentiment, psychological, communication, summary") + analysis = db.query(Analysis).filter( + Analysis.meeting_id == meeting_id, Analysis.type == atype + ).first() + if not analysis: + raise HTTPException(status_code=404, detail=f"Analysis '{analysis_type}' not yet available") + return analysis + + +@router.put("/{meeting_id}/participants/{speaker_label}", response_model=ParticipantResponse) +def update_participant( + meeting_id: str, + speaker_label: str, + data: ParticipantUpdate, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + meeting = _get_meeting_for_user(meeting_id, current_user, db) + participant = db.query(MeetingParticipant).filter( + MeetingParticipant.meeting_id == meeting_id, + MeetingParticipant.speaker_label == speaker_label, + ).first() + if not participant: + participant = MeetingParticipant(meeting_id=meeting_id, speaker_label=speaker_label) + db.add(participant) + if data.identified_name is not None: + participant.identified_name = data.identified_name + if data.confidence_score is not None: + participant.confidence_score = data.confidence_score + db.commit() + db.refresh(participant) + return participant + + + +@router.post("/{meeting_id}/participants/{speaker_label}/enroll", response_model=ParticipantResponse) +async def enroll_participant( + meeting_id: str, + speaker_label: str, + name: str = Body(...), + email: str = Body(None), + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + """Enroll a speaker voice profile and update their name in the transcript.""" + import subprocess + import json as _json + import tempfile + + meeting = _get_meeting_for_user(meeting_id, current_user, db) + + if not meeting.transcription: + raise HTTPException(status_code=400, detail="No transcription available") + + if not meeting.audio_path or not os.path.exists(meeting.audio_path): + raise HTTPException(status_code=404, detail="Meeting audio file not found") + + segments = meeting.transcription.get("segments", []) + speaker_segments = [s for s in segments if s.get("speaker") == speaker_label] + if not speaker_segments: + raise HTTPException(status_code=404, detail=f"Speaker '{speaker_label}' not found in transcript") + + valid_segs = [s for s in speaker_segments if (s.get("end", 0) - s.get("start", 0)) >= 0.5][:12] + + tmp_path = None + profile_id = None + try: + if valid_segs: + filter_parts = [] + out_parts = [] + for i, seg in enumerate(valid_segs): + start = seg["start"] + end = seg["end"] + filter_parts.append(f"[0:a]atrim={start}:{end},asetpts=PTS-STARTPTS[a{i}]") + out_parts.append(f"[a{i}]") + + n = len(filter_parts) + filter_str = ";".join(filter_parts) + ";" + "".join(out_parts) + f"concat=n={n}:v=0:a=1[out]" + + with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp: + tmp_path = tmp.name + + result = subprocess.run( + ["ffmpeg", "-y", "-i", meeting.audio_path, "-filter_complex", filter_str, + "-map", "[out]", "-ar", "16000", "-ac", "1", tmp_path], + capture_output=True, timeout=120, + ) + audio_source = tmp_path if result.returncode == 0 else meeting.audio_path + else: + audio_source = meeting.audio_path + + whisper_url = settings.WHISPER_SERVER_URL + with open(audio_source, "rb") as audio_f: + audio_bytes = audio_f.read() + + async with httpx.AsyncClient(timeout=120.0) as http: + resp = await http.post( + f"{whisper_url}/api/v2/enroll", + files={"file": (f"{name.replace(' ', '_')}.wav", audio_bytes, "audio/wav")}, + data={ + "name": name, + "email": email or "", + "metadata": _json.dumps({"source_meeting": meeting_id, "original_label": speaker_label}), + }, + ) + if resp.status_code in (200, 201): + profile_data = resp.json() + profile_id = profile_data.get("id") + else: + logger.warning(f"Enrollment API error {resp.status_code}: {resp.text[:200]}") + + except HTTPException: + raise + except Exception as e: + logger.warning(f"Enrollment process error: {e}") + finally: + if tmp_path and os.path.exists(tmp_path): + try: + os.unlink(tmp_path) + except Exception: + pass + + participant = db.query(MeetingParticipant).filter( + MeetingParticipant.meeting_id == meeting.id, + MeetingParticipant.speaker_label == speaker_label, + ).first() + if not participant: + participant = MeetingParticipant(meeting_id=meeting.id, speaker_label=speaker_label) + db.add(participant) + + participant.identified_name = name + if profile_id: + try: + from uuid import UUID as _UUID + participant.voice_profile_id = _UUID(profile_id) + except Exception: + pass + + updated_segments = [ + {**seg, "speaker": name} if seg.get("speaker") == speaker_label else seg + for seg in segments + ] + meeting.transcription = {**meeting.transcription, "segments": updated_segments} + + from sqlalchemy.orm.attributes import flag_modified + flag_modified(meeting, "transcription") + + db.commit() + db.refresh(participant) + + logger.info(f"Speaker '{speaker_label}' identified as '{name}', profile_id={profile_id}") + return participant + +@router.delete("/{meeting_id}", status_code=204) +def delete_meeting( + meeting_id: str, + db: Session = Depends(get_db), + current_user=Depends(get_current_user), +): + """Delete a meeting. Only maia.admin users can delete.""" + if not is_admin(current_user): + raise HTTPException(status_code=403, detail="Apenas administradores podem excluir reunioes") + meeting = db.query(Meeting).filter(Meeting.id == meeting_id).first() + if not meeting: + raise HTTPException(status_code=404, detail="Meeting not found") + db.delete(meeting) + db.commit() diff --git a/backend/app/schemas/__init__.py b/backend/app/schemas/__init__.py new file mode 100644 index 0000000..c1d20df --- /dev/null +++ b/backend/app/schemas/__init__.py @@ -0,0 +1,3 @@ +from app.schemas.auth import UserRegister, UserLogin, TokenRefresh, TokenResponse, UserResponse +from app.schemas.meeting import MeetingResponse, MeetingStatusResponse, ParticipantUpdate, ParticipantResponse +from app.schemas.analysis import AnalysisResponse diff --git a/backend/app/schemas/analysis.py b/backend/app/schemas/analysis.py new file mode 100644 index 0000000..2a4424d --- /dev/null +++ b/backend/app/schemas/analysis.py @@ -0,0 +1,17 @@ +from pydantic import BaseModel +from typing import Any +from datetime import datetime +from uuid import UUID +from app.models.analysis import AnalysisType + + +class AnalysisResponse(BaseModel): + id: UUID + meeting_id: UUID + type: AnalysisType + content: Any + model_used: str + created_at: datetime + + class Config: + from_attributes = True diff --git a/backend/app/schemas/auth.py b/backend/app/schemas/auth.py new file mode 100644 index 0000000..00362af --- /dev/null +++ b/backend/app/schemas/auth.py @@ -0,0 +1,31 @@ +from pydantic import BaseModel +from datetime import datetime +from uuid import UUID +from typing import Optional, List + +class UserRegister(BaseModel): + email: str + password: str + name: str + +class UserLogin(BaseModel): + email: str + password: str + +class TokenRefresh(BaseModel): + refresh_token: str + +class TokenResponse(BaseModel): + access_token: str + refresh_token: str + token_type: str = "bearer" + +class UserResponse(BaseModel): + id: UUID + email: str + name: str + roles: List[str] = [] + created_at: datetime + + class Config: + from_attributes = True diff --git a/backend/app/schemas/meeting.py b/backend/app/schemas/meeting.py new file mode 100644 index 0000000..984104c --- /dev/null +++ b/backend/app/schemas/meeting.py @@ -0,0 +1,44 @@ +from pydantic import BaseModel +from typing import Optional, List, Any +from datetime import datetime +from uuid import UUID +from app.models.meeting import MeetingStatus + +class MeetingResponse(BaseModel): + id: UUID + title: Optional[str] = None + date: datetime + duration: Optional[int] = None + status: MeetingStatus + transcription: Optional[Any] = None + user_id: UUID + owner_email: Optional[str] = None + owner_name: Optional[str] = None + created_at: datetime + + class Config: + from_attributes = True + +class MeetingStatusResponse(BaseModel): + id: UUID + status: MeetingStatus + title: Optional[str] = None + + class Config: + from_attributes = True + +class ParticipantUpdate(BaseModel): + identified_name: Optional[str] = None + confidence_score: Optional[float] = None + +class ParticipantResponse(BaseModel): + id: UUID + meeting_id: UUID + speaker_label: str + voice_profile_id: Optional[UUID] = None + identified_name: Optional[str] = None + confidence_score: Optional[float] = None + talk_time_seconds: Optional[int] = None + + class Config: + from_attributes = True diff --git a/backend/app/services/__init__.py b/backend/app/services/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/services/auth_service.py b/backend/app/services/auth_service.py new file mode 100644 index 0000000..6251793 --- /dev/null +++ b/backend/app/services/auth_service.py @@ -0,0 +1,84 @@ +from sqlalchemy.orm import Session +from fastapi import HTTPException, Depends +from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials +from app.models.user import User +from app.utils.security import ( + hash_password, + verify_password, + create_access_token, + create_refresh_token, + decode_token, +) +from app.database import get_db + +security = HTTPBearer() + +def register_user(db: Session, email: str, password: str, name: str) -> User: + existing = db.query(User).filter(User.email == email).first() + if existing: + raise HTTPException(status_code=400, detail="Email already registered") + user = User(email=email, password_hash=hash_password(password), name=name, roles=[]) + db.add(user) + db.commit() + db.refresh(user) + return user + +def login_user(db: Session, email: str, password: str) -> dict: + user = db.query(User).filter(User.email == email).first() + if not user or not verify_password(password, user.password_hash): + raise HTTPException(status_code=401, detail="Invalid email or password") + access_token = create_access_token(str(user.id)) + refresh_token = create_refresh_token(str(user.id)) + return {"access_token": access_token, "refresh_token": refresh_token, "token_type": "bearer"} + +def refresh_tokens(refresh_token: str) -> dict: + payload = decode_token(refresh_token) + if not payload or payload.get("type") != "refresh": + raise HTTPException(status_code=401, detail="Invalid or expired refresh token") + user_id = payload.get("sub") + access_token = create_access_token(user_id) + new_refresh = create_refresh_token(user_id) + return {"access_token": access_token, "refresh_token": new_refresh, "token_type": "bearer"} + +def get_current_user( + credentials: HTTPAuthorizationCredentials = Depends(security), + db: Session = Depends(get_db), +) -> User: + token = credentials.credentials + payload = decode_token(token) + if not payload or payload.get("type") != "access": + raise HTTPException(status_code=401, detail="Invalid or expired access token") + user_id = payload.get("sub") + user = db.query(User).filter(User.id == user_id).first() + if not user: + raise HTTPException(status_code=401, detail="User not found") + return user + +def is_admin(user: User) -> bool: + """Check if user has maia.admin role.""" + return "maia.admin" in (user.roles or []) + +def get_or_create_sso_user(db: Session, user_info: dict, roles: list = None) -> User: + """Look up user by email (SSO login). Create or update if found.""" + import uuid as _uuid + email = user_info.get("email", "") + name = user_info.get("name", "") or email or "SSO User" + roles = roles or [] + + user = db.query(User).filter(User.email == email).first() + if user: + user.name = name + # Merge KC roles with existing DB roles (don't downgrade if KC lacks a role) + existing = set(user.roles or []) + incoming = set(roles or []) + user.roles = sorted(existing | incoming) + db.commit() + db.refresh(user) + return user + + placeholder_hash = hash_password(str(_uuid.uuid4())) + user = User(email=email, password_hash=placeholder_hash, name=name, roles=roles) + db.add(user) + db.commit() + db.refresh(user) + return user diff --git a/backend/app/services/chunk_service.py b/backend/app/services/chunk_service.py new file mode 100644 index 0000000..3019fb0 --- /dev/null +++ b/backend/app/services/chunk_service.py @@ -0,0 +1,88 @@ +import os +import subprocess +import glob +import logging +from app.config import settings + +logger = logging.getLogger(__name__) + + +def get_chunks_dir(meeting_id: str) -> str: + path = os.path.join(settings.AUDIO_STORAGE_PATH, "chunks", meeting_id) + os.makedirs(path, exist_ok=True) + return path + + +def save_chunk(chunk_data: bytes, meeting_id: str, chunk_index: int, ext: str = ".webm") -> str: + chunks_dir = get_chunks_dir(meeting_id) + filename = f"chunk_{chunk_index:06d}{ext}" + path = os.path.join(chunks_dir, filename) + with open(path, "wb") as f: + f.write(chunk_data) + return path + + +def assemble_chunks(meeting_id: str) -> str: + """ + Assemble all chunks into a single WAV file for Whisper processing. + + Timeslice WebM chunks (from a single continuous MediaRecorder session) form a + valid WebM stream when binary-concatenated in order. We concatenate them and + then convert to 16kHz mono WAV with ffmpeg. + Falls back to ffmpeg concat demuxer if binary concat fails. + """ + chunks_dir = get_chunks_dir(meeting_id) + chunk_files = sorted(glob.glob(os.path.join(chunks_dir, "chunk_*"))) + if not chunk_files: + raise ValueError(f"No chunks found for meeting {meeting_id}") + + output_path = os.path.join(settings.AUDIO_STORAGE_PATH, f"{meeting_id}.wav") + + if len(chunk_files) == 1: + result = subprocess.run( + ["ffmpeg", "-y", "-i", chunk_files[0], + "-ar", "16000", "-ac", "1", "-sample_fmt", "s16", output_path], + capture_output=True, text=True, timeout=300, + ) + if result.returncode != 0: + logger.error(f"ffmpeg single-chunk convert failed: {result.stderr}") + raise RuntimeError(f"Failed to convert audio chunk: {result.stderr}") + else: + # Binary-concatenate timeslice WebM chunks (they are sequential fragments + # of the same MediaRecorder stream — binary concat = valid WebM stream) + raw_concat = os.path.join(chunks_dir, "concat_raw.webm") + with open(raw_concat, "wb") as out: + for cf in chunk_files: + with open(cf, "rb") as inp: + out.write(inp.read()) + + result = subprocess.run( + ["ffmpeg", "-y", "-i", raw_concat, + "-ar", "16000", "-ac", "1", "-sample_fmt", "s16", output_path], + capture_output=True, text=True, timeout=300, + ) + if result.returncode != 0: + logger.warning(f"Binary concat failed ({result.stderr[:200]}), trying concat demuxer...") + concat_list = os.path.join(chunks_dir, "concat.txt") + with open(concat_list, "w") as f: + for cf in chunk_files: + f.write(f"file '{cf}'\n") + result2 = subprocess.run( + ["ffmpeg", "-y", "-f", "concat", "-safe", "0", "-i", concat_list, + "-ar", "16000", "-ac", "1", "-sample_fmt", "s16", output_path], + capture_output=True, text=True, timeout=300, + ) + if result2.returncode != 0: + logger.error(f"Both assembly methods failed: {result2.stderr}") + raise RuntimeError(f"Failed to assemble audio chunks: {result2.stderr}") + + logger.info(f"Assembled {len(chunk_files)} chunks -> {output_path}") + return output_path + + +def cleanup_chunks(meeting_id: str): + """Remove chunk files after successful assembly.""" + import shutil + chunks_dir = get_chunks_dir(meeting_id) + if os.path.exists(chunks_dir): + shutil.rmtree(chunks_dir) diff --git a/backend/app/services/ollama_service.py b/backend/app/services/ollama_service.py new file mode 100644 index 0000000..b31c6db --- /dev/null +++ b/backend/app/services/ollama_service.py @@ -0,0 +1,105 @@ +import httpx +import json +import logging +import re +from app.config import settings + +logger = logging.getLogger(__name__) + +PROMPTS = { + "minutes": ( + "Voce e um assistente especializado em reunioes corporativas. " + "Com base na transcricao a seguir, gere uma ata estruturada em JSON contendo: " + "title (string), participants (array de objetos com name e role), " + "agenda (array de strings), decisions (array de strings), " + "action_items (array de objetos com description, responsible e deadline), " + "next_steps (array de strings), open_points (array de strings). " + "Retorne APENAS o JSON valido, sem texto adicional. " + "Transcricao: {transcription}" + ), + "sentiment": ( + "Analise o tom emocional desta reuniao e retorne um JSON com: " + "overall_sentiment (positive/neutral/negative), " + "timeline (array de objetos com time_range, sentiment e notes), " + "participants_sentiment (array de objetos com speaker, sentiment e details), " + "tension_moments (array de strings), " + "consensus_moments (array de strings), " + "participation_metrics (array de objetos com speaker, talk_percentage e interventions_count). " + "Retorne APENAS o JSON valido. " + "Transcricao: {transcription}" + ), + "psychological": ( + "Analise os padroes comportamentais dos participantes e retorne um JSON com: " + "participants_profiles (array de objetos com speaker, name, communication_style, " + "leadership_tendencies, disengagement_signs, power_dynamics_role), " + "group_dynamics (string), " + "key_observations (array de strings). " + "Retorne APENAS o JSON valido. " + "Transcricao: {transcription}" + ), + "communication": ( + "Avalie a comunicacao dos participantes nesta reuniao e retorne um JSON com: " + "overall_score (numero de 1 a 10), " + "dimensions (objeto com clarity, active_listening, assertiveness, meeting_facilitation, " + "cada um com score e notes), " + "strengths (array de objetos com description e example), " + "improvement_areas (array de objetos com description e suggestion), " + "general_feedback (string). " + "Retorne APENAS o JSON valido. " + "Transcricao: {transcription}" + ), + "summary": ( + "Gere um resumo executivo desta reuniao em JSON com: " + "summary (string), " + "key_points (array de strings), " + "duration_minutes (number), " + "total_participants (number). " + "Retorne APENAS o JSON valido. " + "Transcricao: {transcription}" + ), +} + + +async def run_analysis(analysis_type: str, transcription: dict) -> dict: + """Run AI analysis on transcription using Ollama""" + transcription_text = json.dumps(transcription, ensure_ascii=False) + prompt_template = PROMPTS.get(analysis_type, PROMPTS["summary"]) + prompt = prompt_template.replace("{transcription}", transcription_text[:8000]) + + logger.info(f"Running {analysis_type} analysis with Ollama model {settings.OLLAMA_MODEL}") + + try: + headers = {} + if settings.OLLAMA_API_KEY: + headers["X-API-Key"] = settings.OLLAMA_API_KEY + async with httpx.AsyncClient(timeout=180.0) as client: + response = await client.post( + f"{settings.OLLAMA_URL}/api/generate", + headers=headers, + json={ + "model": settings.OLLAMA_MODEL, + "prompt": prompt, + "stream": False, + "format": "json", + "options": {"temperature": 0.3}, + }, + ) + response.raise_for_status() + result = response.json() + response_text = result.get("response", "{}") + try: + return json.loads(response_text) + except json.JSONDecodeError: + json_match = re.search(r"\{.*\}", response_text, re.DOTALL) + if json_match: + try: + return json.loads(json_match.group()) + except json.JSONDecodeError: + pass + return {"raw_response": response_text, "parse_error": "Could not parse JSON"} + except httpx.ConnectError as e: + logger.error(f"Cannot connect to Ollama at {settings.OLLAMA_URL}: {e}") + return {"error": "Ollama unavailable", "analysis_type": analysis_type} + except Exception as e: + logger.error(f"Ollama analysis error for {analysis_type}: {e}") + return {"error": str(e), "analysis_type": analysis_type} diff --git a/backend/app/services/upload_service.py b/backend/app/services/upload_service.py new file mode 100644 index 0000000..b271910 --- /dev/null +++ b/backend/app/services/upload_service.py @@ -0,0 +1,39 @@ +import os +import aiofiles +from fastapi import UploadFile, HTTPException +from app.config import settings + + +async def save_audio_file(file: UploadFile, meeting_id: str) -> str: + os.makedirs(settings.AUDIO_STORAGE_PATH, exist_ok=True) + original_name = file.filename or "audio.wav" + ext = os.path.splitext(original_name)[1].lower() or ".wav" + + allowed_extensions = {".wav", ".mp3", ".m4a", ".ogg", ".flac", ".mp4", ".webm"} + if ext not in allowed_extensions: + raise HTTPException( + status_code=400, + detail=f"Unsupported audio format '{ext}'. Supported: {', '.join(allowed_extensions)}", + ) + + filename = f"{meeting_id}{ext}" + file_path = os.path.join(settings.AUDIO_STORAGE_PATH, filename) + max_size = settings.UPLOAD_MAX_SIZE_MB * 1024 * 1024 + total_size = 0 + + async with aiofiles.open(file_path, "wb") as f: + while True: + chunk = await file.read(1024 * 1024) + if not chunk: + break + total_size += len(chunk) + if total_size > max_size: + await f.close() + os.remove(file_path) + raise HTTPException( + status_code=413, + detail=f"File too large. Maximum allowed size is {settings.UPLOAD_MAX_SIZE_MB}MB", + ) + await f.write(chunk) + + return file_path diff --git a/backend/app/services/websocket_service.py b/backend/app/services/websocket_service.py new file mode 100644 index 0000000..a751861 --- /dev/null +++ b/backend/app/services/websocket_service.py @@ -0,0 +1,51 @@ +from fastapi import WebSocket +from typing import Dict, List +import json +import logging + +logger = logging.getLogger(__name__) + + +class WebSocketManager: + def __init__(self): + self.active_connections: Dict[str, List[WebSocket]] = {} + + async def connect(self, websocket: WebSocket, meeting_id: str): + await websocket.accept() + if meeting_id not in self.active_connections: + self.active_connections[meeting_id] = [] + self.active_connections[meeting_id].append(websocket) + logger.info(f"WebSocket connected: meeting={meeting_id}, total={len(self.active_connections[meeting_id])}") + + def disconnect(self, websocket: WebSocket, meeting_id: str): + if meeting_id in self.active_connections: + try: + self.active_connections[meeting_id].remove(websocket) + except ValueError: + pass + logger.info(f"WebSocket disconnected: meeting={meeting_id}") + + async def send_message(self, meeting_id: str, message: dict): + if meeting_id not in self.active_connections: + return + disconnected = [] + for ws in self.active_connections[meeting_id]: + try: + await ws.send_text(json.dumps(message, ensure_ascii=False)) + except Exception as e: + logger.warning(f"WebSocket send error for meeting {meeting_id}: {e}") + disconnected.append(ws) + for ws in disconnected: + self.active_connections[meeting_id].remove(ws) + + async def broadcast_status(self, meeting_id: str, status: str, data: dict = None): + message = { + "type": "status_update", + "meeting_id": meeting_id, + "status": status, + "data": data or {}, + } + await self.send_message(meeting_id, message) + + +manager = WebSocketManager() diff --git a/backend/app/services/whisper_service.py b/backend/app/services/whisper_service.py new file mode 100644 index 0000000..b99a0db --- /dev/null +++ b/backend/app/services/whisper_service.py @@ -0,0 +1,91 @@ +import httpx +import logging +import os +from app.config import settings + +logger = logging.getLogger(__name__) + +MIME_TYPES = { + ".webm": "audio/webm", + ".wav": "audio/wav", + ".mp3": "audio/mpeg", + ".m4a": "audio/mp4", + ".ogg": "audio/ogg", + ".flac": "audio/flac", +} + +async def transcribe_audio(audio_path: str) -> dict: + """ + Send audio to Whisper Diarization API. + 1) Tries POST /api/v2/transcribe (diarization — field: audio) -> returns segments with speaker labels + 2) Falls back to POST /transcribe-segments (no diarization) -> assigns SPEAKER_01 to all + """ + logger.info(f"Sending audio to Whisper server: {audio_path}") + try: + with open(audio_path, "rb") as f: + content = f.read() + filename = os.path.basename(audio_path) + ext = os.path.splitext(filename)[1].lower() + mime_type = MIME_TYPES.get(ext, "audio/webm") + + async with httpx.AsyncClient(timeout=600.0) as http: + # 1) Try /api/v2/transcribe with diarization (field: audio) + try: + files = {"audio": (filename, content, mime_type)} + data = {"language": "pt"} + resp = await http.post( + f"{settings.WHISPER_SERVER_URL}/api/v2/transcribe", + files=files, data=data, timeout=600.0, + ) + if resp.status_code not in (404, 422, 500): + resp.raise_for_status() + result = resp.json() + logger.info(f"Diarized transcription completed for {audio_path} " + f"({result.get('speakers_count', '?')} speakers, " + f"method: {result.get('diarization_method', '?')})") + return result + logger.warning(f"/api/v2/transcribe returned {resp.status_code}, falling back...") + except httpx.HTTPStatusError as e: + if e.response.status_code not in (404, 422, 500): + raise + logger.warning(f"/api/v2/transcribe error {e.response.status_code}, falling back...") + except Exception as e: + logger.warning(f"/api/v2/transcribe exception: {e}, falling back...") + + # 2) Fallback: /transcribe-segments (no speaker diarization) + files = {"file": (filename, content, mime_type)} + data = {"language": "pt"} + resp = await http.post( + f"{settings.WHISPER_SERVER_URL}/transcribe-segments", + files=files, data=data, timeout=600.0, + ) + resp.raise_for_status() + result = resp.json() + logger.info(f"Transcription via fallback /transcribe-segments completed for {audio_path}") + + segments = result.get("segments", []) + normalized = [ + { + "start": seg.get("start", 0.0), + "end": seg.get("end", 0.0), + "speaker": "SPEAKER_01", + "text": seg.get("text", "").strip(), + } + for seg in segments + ] + return { + "segments": normalized, + "speakers_count": 1, + "audio_duration": segments[-1]["end"] if segments else 0.0, + "language": result.get("language", "pt"), + "full_text": result.get("text", ""), + "diarization_available": False, + "diarization_method": "none", + } + + except httpx.ConnectError as e: + logger.error(f"Cannot connect to Whisper server at {settings.WHISPER_SERVER_URL}: {e}") + raise Exception(f"Whisper server unavailable: {str(e)}") + except Exception as e: + logger.error(f"Transcription error: {e}") + raise diff --git a/backend/app/tasks/__init__.py b/backend/app/tasks/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/tasks/processing.py b/backend/app/tasks/processing.py new file mode 100644 index 0000000..f865853 --- /dev/null +++ b/backend/app/tasks/processing.py @@ -0,0 +1,136 @@ +import logging +import asyncio +from celery import Celery +from app.config import settings +from app.database import SessionLocal +from app.models.meeting import Meeting, MeetingStatus +from app.models.analysis import Analysis, AnalysisType +from app.services.whisper_service import transcribe_audio +from app.services.ollama_service import run_analysis + +logger = logging.getLogger(__name__) + +celery_app = Celery( + "meeting_assistant", + broker=settings.REDIS_URL, + backend=settings.REDIS_URL, +) + +celery_app.conf.update( + task_serializer="json", + accept_content=["json"], + result_serializer="json", + timezone="UTC", + enable_utc=True, + task_acks_late=True, + worker_prefetch_multiplier=1, +) + + +def run_async(coro): + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + try: + return loop.run_until_complete(coro) + finally: + loop.close() + + +@celery_app.task(bind=True, max_retries=3, default_retry_delay=60) +def process_meeting(self, meeting_id: str): + """ + Full meeting processing pipeline: + 1. Save audio (already done at upload) + 2. Transcribe via Whisper + 3. Analyze via Ollama (minutes, sentiment, psychological, communication, summary) + 4. Update status to completed + """ + db = SessionLocal() + meeting = None + try: + meeting = db.query(Meeting).filter(Meeting.id == meeting_id).first() + if not meeting: + logger.error(f"Meeting {meeting_id} not found in DB") + return + + # Step 1 - Mark processing + meeting.status = MeetingStatus.processing + db.commit() + logger.info(f"Processing meeting {meeting_id}") + + # Step 2 - Transcription + meeting.status = MeetingStatus.transcribing + db.commit() + + try: + transcription = run_async(transcribe_audio(meeting.audio_path)) + meeting.transcription = transcription + db.commit() + logger.info(f"Transcription done for meeting {meeting_id}") + + # Save participants from transcription + try: + from app.models.participant import MeetingParticipant + speaker_labels = {seg.get("speaker") for seg in transcription.get("segments", []) if seg.get("speaker")} + for label in speaker_labels: + existing = db.query(MeetingParticipant).filter( + MeetingParticipant.meeting_id == meeting.id, + MeetingParticipant.speaker_label == label, + ).first() + if not existing: + db.add(MeetingParticipant( + meeting_id=meeting.id, + speaker_label=label, + identified_name=None if label.startswith("SPEAKER_") else label, + )) + db.commit() + except Exception as e: + logger.warning(f"Failed to save participants: {e}") + except Exception as e: + logger.error(f"Transcription failed for {meeting_id}: {e}") + meeting.status = MeetingStatus.error + db.commit() + return + + # Step 3 - AI Analyses + meeting.status = MeetingStatus.analyzing + db.commit() + + analysis_types = ["minutes", "sentiment", "psychological", "communication", "summary"] + for analysis_type in analysis_types: + try: + content = run_async(run_analysis(analysis_type, transcription)) + existing = ( + db.query(Analysis) + .filter(Analysis.meeting_id == meeting_id, Analysis.type == AnalysisType(analysis_type)) + .first() + ) + if existing: + existing.content = content + existing.model_used = settings.OLLAMA_MODEL + else: + analysis = Analysis( + meeting_id=meeting.id, + type=AnalysisType(analysis_type), + content=content, + model_used=settings.OLLAMA_MODEL, + ) + db.add(analysis) + db.commit() + logger.info(f"Analysis '{analysis_type}' done for meeting {meeting_id}") + except Exception as e: + logger.error(f"Analysis '{analysis_type}' failed for {meeting_id}: {e}") + + # Step 4 - Mark completed + meeting.status = MeetingStatus.completed + db.commit() + logger.info(f"Meeting {meeting_id} processing COMPLETED") + + except Exception as e: + logger.error(f"Unexpected error processing meeting {meeting_id}: {e}") + if meeting: + meeting.status = MeetingStatus.error + db.commit() + raise self.retry(exc=e, countdown=60) + finally: + db.close() diff --git a/backend/app/utils/__init__.py b/backend/app/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/utils/keycloak_auth.py b/backend/app/utils/keycloak_auth.py new file mode 100644 index 0000000..48825f3 --- /dev/null +++ b/backend/app/utils/keycloak_auth.py @@ -0,0 +1,50 @@ +import jwt +from jwt import PyJWKClient +from typing import Optional + +JWKS_URI = "https://auth.asaptelecom.com.br/realms/one/protocol/openid-connect/certs" +ISSUER = "https://auth.asaptelecom.com.br/realms/one" +AUDIENCE = "maia-app" + +jwks_client = PyJWKClient(JWKS_URI, cache_keys=True) + + +def validate_keycloak_token(token: str) -> Optional[dict]: + """ + Validate a Keycloak RS256 JWT token. + Returns decoded payload or None if invalid. + """ + try: + signing_key = jwks_client.get_signing_key_from_jwt(token) + payload = jwt.decode( + token, + signing_key.key, + algorithms=["RS256"], + issuer=ISSUER, + options={"verify_aud": False}, + ) + return payload + except Exception as e: + print(f"[keycloak_auth] Token validation failed: {e}") + return None + + +def has_role(payload: dict, role: str) -> bool: + """Check if role is present in realm_access or resource_access.""" + realm_roles = payload.get("realm_access", {}).get("roles", []) + if role in realm_roles: + return True + for client_roles in payload.get("resource_access", {}).values(): + if role in client_roles.get("roles", []): + return True + return False + + +def extract_user_info(payload: dict) -> dict: + """Extract user info from KC token.""" + return { + "sub": payload.get("sub"), + "email": payload.get("email", ""), + "name": (payload.get("name") or + f"{payload.get('given_name', '')} {payload.get('family_name', '')}".strip()), + } diff --git a/backend/app/utils/security.py b/backend/app/utils/security.py new file mode 100644 index 0000000..3c705c5 --- /dev/null +++ b/backend/app/utils/security.py @@ -0,0 +1,49 @@ +import jwt +from datetime import datetime, timedelta +import bcrypt +from typing import Optional +from app.config import settings + + +def hash_password(password: str) -> str: + salt = bcrypt.gensalt() + return bcrypt.hashpw(password.encode("utf-8"), salt).decode("utf-8") + + +def verify_password(plain_password: str, hashed_password: str) -> bool: + try: + return bcrypt.checkpw( + plain_password.encode("utf-8"), + hashed_password.encode("utf-8"), + ) + except Exception: + return False + + +def create_access_token(user_id: str) -> str: + payload = { + "sub": user_id, + "exp": datetime.utcnow() + timedelta(minutes=settings.JWT_EXPIRE_MINUTES), + "iat": datetime.utcnow(), + "type": "access", + } + return jwt.encode(payload, settings.JWT_SECRET, algorithm="HS256") + + +def create_refresh_token(user_id: str) -> str: + payload = { + "sub": user_id, + "exp": datetime.utcnow() + timedelta(days=settings.JWT_REFRESH_EXPIRE_DAYS), + "iat": datetime.utcnow(), + "type": "refresh", + } + return jwt.encode(payload, settings.JWT_SECRET, algorithm="HS256") + + +def decode_token(token: str) -> Optional[dict]: + try: + return jwt.decode(token, settings.JWT_SECRET, algorithms=["HS256"]) + except jwt.ExpiredSignatureError: + return None + except jwt.InvalidTokenError: + return None diff --git a/backend/docker-compose.yml b/backend/docker-compose.yml new file mode 100644 index 0000000..41ad281 --- /dev/null +++ b/backend/docker-compose.yml @@ -0,0 +1,73 @@ +version: '3.8' + +services: + postgres: + image: postgres:15 + restart: unless-stopped + environment: + POSTGRES_USER: meetingassistant + POSTGRES_PASSWORD: meetingassistant + POSTGRES_DB: meeting_assistant + volumes: + - postgres_data:/var/lib/postgresql/data + ports: + - "5432:5432" + healthcheck: + test: ["CMD-SHELL", "pg_isready -U meetingassistant"] + interval: 10s + timeout: 5s + retries: 5 + + redis: + image: redis:7-alpine + restart: unless-stopped + ports: + - "6379:6379" + healthcheck: + test: ["CMD", "redis-cli", "ping"] + interval: 10s + timeout: 5s + retries: 5 + + api: + build: . + restart: unless-stopped + ports: + - "8080:8000" + env_file: + - .env + environment: + - DATABASE_URL=postgresql://meetingassistant:meetingassistant@postgres:5432/meeting_assistant + - REDIS_URL=redis://redis:6379/0 + volumes: + - audio_storage:/opt/Backend/meeting-assistant-api/storage/audio + depends_on: + postgres: + condition: service_healthy + redis: + condition: service_healthy + extra_hosts: + - "host.docker.internal:host-gateway" + + worker: + build: . + restart: unless-stopped + env_file: + - .env + environment: + - DATABASE_URL=postgresql://meetingassistant:meetingassistant@postgres:5432/meeting_assistant + - REDIS_URL=redis://redis:6379/0 + volumes: + - audio_storage:/opt/Backend/meeting-assistant-api/storage/audio + depends_on: + postgres: + condition: service_healthy + redis: + condition: service_healthy + extra_hosts: + - "host.docker.internal:host-gateway" + command: celery -A app.tasks.processing.celery_app worker --loglevel=info --concurrency=2 + +volumes: + postgres_data: + audio_storage: diff --git a/backend/requirements.txt b/backend/requirements.txt new file mode 100644 index 0000000..b4c0374 --- /dev/null +++ b/backend/requirements.txt @@ -0,0 +1,16 @@ +fastapi==0.104.1 +uvicorn[standard]==0.24.0 +sqlalchemy==2.0.23 +alembic==1.12.1 +psycopg2-binary==2.9.9 +redis==5.0.1 +celery==5.3.4 +PyJWT==2.8.0 +python-multipart==0.0.6 +httpx==0.25.2 +pydantic==2.5.2 +pydantic-settings==2.1.0 +aiofiles==23.2.1 +python-dotenv==1.0.0 +websockets==12.0 +cryptography diff --git a/diarization/db/__init__.py b/diarization/db/__init__.py new file mode 100644 index 0000000..143f486 --- /dev/null +++ b/diarization/db/__init__.py @@ -0,0 +1 @@ +# __init__.py diff --git a/diarization/db/database.py b/diarization/db/database.py new file mode 100644 index 0000000..9fc696e --- /dev/null +++ b/diarization/db/database.py @@ -0,0 +1,11 @@ +"""Database initialization wrapper.""" +import os +import logging +from services.enrollment import init_db as _init_enrollment_db + +logger = logging.getLogger(__name__) + + +def init_db(): + """Initialize all database tables.""" + _init_enrollment_db() diff --git a/diarization/main.py b/diarization/main.py new file mode 100644 index 0000000..fbeef24 --- /dev/null +++ b/diarization/main.py @@ -0,0 +1,67 @@ +""" +Whisper Diarization API — Enhancement Server +Adds /api/v2 endpoints (diarization + voice enrollment) to the existing Whisper server. +Transparently proxies existing endpoints to the original Whisper server. + +Original Whisper server: http://10.100.16.13:5003 +This server runs on: port 5060 +""" +import logging +import os +from fastapi import FastAPI +from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import JSONResponse + +from routers.proxy import router as proxy_router +from routers.v2_transcribe import router as v2_transcribe_router +from routers.v2_speakers import router as v2_speakers_router +from db.database import init_db + +logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' +) +logger = logging.getLogger(__name__) + +WHISPER_ORIGIN = os.getenv("WHISPER_ORIGIN", "http://10.100.16.13:5003") + +app = FastAPI( + title="Whisper Diarization Enhancement Server", + description=( + "Adds Speaker Diarization + Voice Enrollment on top of the existing Whisper.cpp GPU server. " + "Existing endpoints (/transcribe, /transcribe-segments, /whisper, /transcribe-text, /health) " + "are transparently proxied to the original server." + ), + version="2.0.0", + docs_url="/docs", + redoc_url="/redoc", +) + +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +@app.on_event("startup") +async def startup(): + logger.info("Whisper Diarization Enhancement Server starting...") + init_db() + logger.info(f"Proxying existing endpoints to: {WHISPER_ORIGIN}") + logger.info("New endpoints available under /api/v2/") + logger.info("Server ready!") + +# Proxy existing Whisper endpoints (NEVER MODIFY THESE) +app.include_router(proxy_router, tags=["proxy — original whisper endpoints"]) + +# New v2 endpoints +app.include_router(v2_transcribe_router, prefix="/api/v2", tags=["v2 — diarization"]) +app.include_router(v2_speakers_router, prefix="/api/v2", tags=["v2 — voice enrollment"]) + + +@app.exception_handler(Exception) +async def global_exception_handler(request, exc): + logger.error(f"Unhandled exception: {exc}", exc_info=True) + return JSONResponse(status_code=500, content={"detail": "Internal server error"}) diff --git a/diarization/requirements.txt b/diarization/requirements.txt new file mode 100644 index 0000000..695b01e --- /dev/null +++ b/diarization/requirements.txt @@ -0,0 +1,16 @@ +# Whisper Diarization Enhancement Server + +fastapi==0.104.1 +uvicorn[standard]==0.24.0 +httpx==0.25.2 +python-multipart==0.0.6 +aiofiles==23.2.1 +scipy>=1.10.0 +numpy>=1.24.0 +librosa>=0.10.0 +soundfile>=0.12.1 + +# Optional — heavier ML models (installed separately if available) +# pyannote.audio>=3.1.0 +# speechbrain>=0.5.16 +# torch>=2.0.0 diff --git a/diarization/routers/__init__.py b/diarization/routers/__init__.py new file mode 100644 index 0000000..85fe408 --- /dev/null +++ b/diarization/routers/__init__.py @@ -0,0 +1 @@ +# __init__.py files diff --git a/diarization/routers/proxy.py b/diarization/routers/proxy.py new file mode 100644 index 0000000..f954319 --- /dev/null +++ b/diarization/routers/proxy.py @@ -0,0 +1,82 @@ +""" +Proxy router — transparently forwards existing Whisper server endpoints. +NEVER modify these routes or their behavior. +""" +import os +import logging +from fastapi import APIRouter, Request, UploadFile, File, Form +from fastapi.responses import Response +import httpx + +logger = logging.getLogger(__name__) +WHISPER_ORIGIN = os.getenv("WHISPER_ORIGIN", "http://10.100.16.13:5003") + +router = APIRouter() + + +async def _proxy_get(path: str) -> Response: + """Forward a GET request to the original Whisper server.""" + async with httpx.AsyncClient(timeout=10.0) as client: + resp = await client.get(f"{WHISPER_ORIGIN}{path}") + return Response( + content=resp.content, + status_code=resp.status_code, + media_type=resp.headers.get("content-type", "application/json"), + ) + + +async def _proxy_upload(path: str, file_bytes: bytes, filename: str, extra_fields: dict) -> Response: + """Forward a multipart file upload to the original Whisper server.""" + async with httpx.AsyncClient(timeout=600.0) as client: + files = {"file": (filename, file_bytes, "application/octet-stream")} + data = extra_fields + resp = await client.post(f"{WHISPER_ORIGIN}{path}", files=files, data=data) + return Response( + content=resp.content, + status_code=resp.status_code, + media_type=resp.headers.get("content-type", "application/json"), + ) + + +# ── Proxy: GET /health ─────────────────────────────────────────────────────── +@router.get("/health", summary="Health — proxied from original Whisper server") +async def health(): + return await _proxy_get("/health") + + +# ── Proxy: POST /transcribe ────────────────────────────────────────────────── +@router.post("/transcribe", summary="Transcribe — proxied from original Whisper server") +async def transcribe( + file: UploadFile = File(...), + language: str = Form("pt"), +): + file_bytes = await file.read() + return await _proxy_upload("/transcribe", file_bytes, file.filename or "audio.wav", {"language": language}) + + +# ── Proxy: POST /transcribe-segments ──────────────────────────────────────── +@router.post("/transcribe-segments", summary="Transcribe Segments — proxied from original Whisper server") +async def transcribe_segments( + file: UploadFile = File(...), + language: str = Form("pt"), +): + file_bytes = await file.read() + return await _proxy_upload("/transcribe-segments", file_bytes, file.filename or "audio.wav", {"language": language}) + + +# ── Proxy: POST /transcribe-text ──────────────────────────────────────────── +@router.post("/transcribe-text", summary="Transcribe Text — proxied from original Whisper server") +async def transcribe_text( + file: UploadFile = File(...), +): + file_bytes = await file.read() + return await _proxy_upload("/transcribe-text", file_bytes, file.filename or "audio.wav", {}) + + +# ── Proxy: POST /whisper ───────────────────────────────────────────────────── +@router.post("/whisper", summary="Whisper Compat — proxied from original Whisper server") +async def whisper_compat( + file: UploadFile = File(...), +): + file_bytes = await file.read() + return await _proxy_upload("/whisper", file_bytes, file.filename or "audio.wav", {}) diff --git a/diarization/routers/v2_speakers.py b/diarization/routers/v2_speakers.py new file mode 100644 index 0000000..5cdafd1 --- /dev/null +++ b/diarization/routers/v2_speakers.py @@ -0,0 +1,241 @@ +""" +Voice Enrollment & Speaker Identification endpoints. + +POST /api/v2/enroll — enroll a new voice profile +POST /api/v2/enroll/from-meeting — enroll from meeting segments +GET /api/v2/speakers — list all profiles +GET /api/v2/speakers/{id} — get profile details +PUT /api/v2/speakers/{id} — update profile +DELETE /api/v2/speakers/{id} — delete profile +POST /api/v2/identify — identify a speaker from audio +""" +import os +import json +import logging +import tempfile +from typing import List, Optional + +from fastapi import APIRouter, UploadFile, File, Form, HTTPException +from pydantic import BaseModel + +from services.enrollment import ( + create_profile, + get_profile, + list_profiles, + update_profile, + delete_profile, + add_embedding, + identify_speaker, +) +from services.diarization import extract_embedding + +logger = logging.getLogger(__name__) +router = APIRouter() + + +# ── Schemas ─────────────────────────────────────────────────────────────────── +class VoiceProfileResponse(BaseModel): + id: str + name: str + email: Optional[str] = None + metadata: Optional[str] = None + embeddings_count: int + created_at: str + updated_at: str + + +class UpdateProfileRequest(BaseModel): + name: Optional[str] = None + email: Optional[str] = None + metadata: Optional[str] = None + + +class IdentifyResponse(BaseModel): + matched: bool + speaker_id: Optional[str] = None + speaker_name: Optional[str] = None + confidence: float + threshold: float + + +# ── Helper ──────────────────────────────────────────────────────────────────── +async def _save_and_embed(file_bytes: bytes, suffix: str) -> object: + """Save audio bytes to a temp file and extract embedding.""" + with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp: + tmp.write(file_bytes) + tmp_path = tmp.name + try: + embedding = extract_embedding(tmp_path) + return embedding + finally: + try: + os.unlink(tmp_path) + except Exception: + pass + + +# ── POST /enroll ────────────────────────────────────────────────────────────── +@router.post( + "/enroll", + response_model=VoiceProfileResponse, + status_code=201, + summary="Enroll a new voice profile", + description=( + "Submit an audio file (minimum 30 seconds recommended) to enroll a new speaker. " + "Extracts a vocal embedding and saves the profile to the local SQLite database." + ), +) +async def enroll( + file: UploadFile = File(..., description="Audio file with the speaker's voice (min 30s recommended)"), + name: str = Form(..., description="Speaker full name"), + email: Optional[str] = Form(None, description="Speaker email (optional)"), + metadata: Optional[str] = Form(None, description="Extra JSON metadata (optional)"), +): + audio_bytes = await file.read() + suffix = os.path.splitext(file.filename or ".wav")[-1].lower() or ".wav" + + embedding = await _save_and_embed(audio_bytes, suffix) + + profile = create_profile(name=name, email=email, metadata=metadata) + add_embedding(profile["id"], embedding) + + profile["embeddings_count"] = 1 + return VoiceProfileResponse(**profile) + + +# ── POST /enroll/from-meeting ───────────────────────────────────────────────── +@router.post( + "/enroll/from-meeting", + response_model=VoiceProfileResponse, + status_code=201, + summary="Enroll speaker from meeting audio segments", + description=( + "Extract voice embedding from specific speaker segments of an already processed meeting. " + "Creates a new profile or adds embeddings to an existing one (matched by name)." + ), +) +async def enroll_from_meeting( + meeting_segments: str = Form( + ..., + description='JSON array of {speaker_label, audio_file_path}: [{"speaker_label":"SPEAKER_01","audio_file_path":"/path/audio.wav"}]', + ), + speaker_name: str = Form(..., description="Name to assign to this speaker"), + speaker_label: str = Form(..., description="Speaker label to extract (e.g. SPEAKER_01)"), + existing_profile_id: Optional[str] = Form(None, description="Existing profile ID to add embeddings to (optional)"), +): + try: + segments = json.loads(meeting_segments) + except (json.JSONDecodeError, ValueError) as e: + raise HTTPException(status_code=422, detail=f"Invalid meeting_segments JSON: {e}") + + # Filter segments matching the requested speaker + target_segments = [s for s in segments if s.get("speaker_label") == speaker_label] + if not target_segments: + raise HTTPException( + status_code=404, + detail=f"No segments found for speaker_label='{speaker_label}'", + ) + + # Get or create profile + if existing_profile_id: + profile = get_profile(existing_profile_id) + if profile is None: + raise HTTPException(status_code=404, detail=f"Profile '{existing_profile_id}' not found") + else: + profile = create_profile(name=speaker_name, email=None, metadata=None) + + # Extract embeddings for each segment + emb_count = 0 + for seg in target_segments: + audio_path = seg.get("audio_file_path", "") + if not os.path.isfile(audio_path): + logger.warning(f"Audio file not found: {audio_path}") + continue + try: + embedding = extract_embedding(audio_path) + add_embedding(profile["id"], embedding) + emb_count += 1 + except Exception as e: + logger.warning(f"Failed to extract embedding from {audio_path}: {e}") + + if emb_count == 0: + raise HTTPException( + status_code=422, + detail="No valid audio segments could be processed. Check that audio_file_path values exist on the server.", + ) + + return VoiceProfileResponse(**get_profile(profile["id"])) + + +# ── GET /speakers ───────────────────────────────────────────────────────────── +@router.get( + "/speakers", + response_model=List[VoiceProfileResponse], + summary="List all enrolled voice profiles", +) +async def list_speakers(): + return [VoiceProfileResponse(**p) for p in list_profiles()] + + +# ── GET /speakers/{id} ──────────────────────────────────────────────────────── +@router.get( + "/speakers/{profile_id}", + response_model=VoiceProfileResponse, + summary="Get a voice profile by ID", +) +async def get_speaker(profile_id: str): + profile = get_profile(profile_id) + if profile is None: + raise HTTPException(status_code=404, detail="Voice profile not found") + return VoiceProfileResponse(**profile) + + +# ── PUT /speakers/{id} ──────────────────────────────────────────────────────── +@router.put( + "/speakers/{profile_id}", + response_model=VoiceProfileResponse, + summary="Update a voice profile (name, email, metadata — all optional)", +) +async def update_speaker(profile_id: str, data: UpdateProfileRequest): + profile = update_profile( + profile_id, + name=data.name, + email=data.email, + metadata=data.metadata, + ) + if profile is None: + raise HTTPException(status_code=404, detail="Voice profile not found") + return VoiceProfileResponse(**profile) + + +# ── DELETE /speakers/{id} ───────────────────────────────────────────────────── +@router.delete( + "/speakers/{profile_id}", + status_code=204, + summary="Delete a voice profile and all its embeddings", +) +async def delete_speaker(profile_id: str): + if not delete_profile(profile_id): + raise HTTPException(status_code=404, detail="Voice profile not found") + + +# ── POST /identify ──────────────────────────────────────────────────────────── +@router.post( + "/identify", + response_model=IdentifyResponse, + summary="Identify the speaker in an audio clip", + description=( + "Extracts a vocal embedding from the submitted audio and compares it against all " + "enrolled profiles. Returns the best match if confidence >= threshold." + ), +) +async def identify( + file: UploadFile = File(..., description="Short audio clip to identify the speaker"), + threshold: Optional[float] = Form(None, description="Confidence threshold (default: 0.75)"), +): + audio_bytes = await file.read() + suffix = os.path.splitext(file.filename or ".wav")[-1].lower() or ".wav" + + embedding = await _save_and_embed(audio_bytes, suffix) + result = identify_speaker(embedding, threshold=threshold) + return IdentifyResponse(**result) diff --git a/diarization/routers/v2_transcribe.py b/diarization/routers/v2_transcribe.py new file mode 100644 index 0000000..4a46b24 --- /dev/null +++ b/diarization/routers/v2_transcribe.py @@ -0,0 +1,192 @@ +""" +POST /api/v2/transcribe — Transcription with speaker diarization. + +Calls the original Whisper server for transcription (with timestamps), +then runs speaker diarization and aligns the results. +""" +import os +import logging +import tempfile +from typing import List, Optional + +import httpx +from fastapi import APIRouter, UploadFile, File, Form, HTTPException +from pydantic import BaseModel + +from services.diarization import diarize, align_transcription_with_diarization, extract_embedding + +logger = logging.getLogger(__name__) +router = APIRouter() + +WHISPER_ORIGIN = os.getenv("WHISPER_ORIGIN", "http://10.100.16.13:5003") + + +# ── Response model ──────────────────────────────────────────────────────────── +class TranscriptionSegment(BaseModel): + start: float + end: float + speaker: str + text: str + + +class DiarizedTranscriptionResponse(BaseModel): + segments: List[TranscriptionSegment] + speakers_count: int + audio_duration: float + language: str + full_text: str + diarization_method: str + + +# ── Endpoint ────────────────────────────────────────────────────────────────── +@router.post( + "/transcribe", + response_model=DiarizedTranscriptionResponse, + summary="Transcription + Speaker Diarization", + description=( + "Transcribes the audio using the Whisper.cpp GPU server and adds speaker diarization. " + "Returns segments labelled by speaker (SPEAKER_01, SPEAKER_02, …)." + ), +) +async def v2_transcribe( + audio: UploadFile = File(..., description="Audio file (WAV, MP3, M4A, OGG, FLAC)"), + language: str = Form("pt", description="Language code (default: pt)"), + num_speakers: Optional[int] = Form(None, description="Expected number of speakers (optional, auto-detected if omitted)"), +): + audio_bytes = await audio.read() + filename = audio.filename or "audio.wav" + + # Step 1 — call original Whisper server for timestamps + transcription_segments = await _call_whisper_segments(audio_bytes, filename, language) + + # Step 2 — save to temp file for diarization + suffix = os.path.splitext(filename)[-1].lower() or ".wav" + with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp: + tmp.write(audio_bytes) + tmp_path = tmp.name + + try: + # Step 3 — diarize + diarization_segs, method = diarize(tmp_path, num_speakers=num_speakers) + + # Step 4 — align + aligned = align_transcription_with_diarization(transcription_segments, diarization_segs) + + # Auto-identify speakers against enrolled profiles + try: + import librosa + import numpy as np + import soundfile as sf + from services.enrollment import identify_speaker + + y, sr = librosa.load(tmp_path, sr=16000, mono=True) + speaker_labels = sorted({s["speaker"] for s in aligned}) + + for speaker_label in speaker_labels: + chunks = [] + for dseg in diarization_segs: + if dseg["speaker"] == speaker_label: + s_i = int(dseg["start"] * sr) + e_i = int(dseg["end"] * sr) + if e_i > s_i + int(0.5 * sr): + chunks.append(y[s_i:min(e_i, len(y))]) + + if not chunks: + continue + + speaker_audio = np.concatenate(chunks) + if len(speaker_audio) < sr * 3: + continue + + spk_path = None + try: + with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as spk_tmp: + sf.write(spk_tmp.name, speaker_audio, sr) + spk_path = spk_tmp.name + + embedding = extract_embedding(spk_path) + id_result = identify_speaker(embedding) + + if id_result["matched"]: + identified_name = id_result["speaker_name"] + logger.info(f"Auto-identified {speaker_label} as '{identified_name}' (conf={id_result['confidence']:.2f})") + for seg in aligned: + if seg["speaker"] == speaker_label: + seg["speaker"] = identified_name + finally: + if spk_path: + try: + os.unlink(spk_path) + except Exception: + pass + except Exception as auto_id_err: + logger.warning(f"Auto-identification failed (non-fatal): {auto_id_err}") + + # Step 5 — compute metadata + speakers = sorted({s["speaker"] for s in aligned}) + full_text = " ".join(s["text"] for s in aligned if s.get("text")) + + # Audio duration from diarization or transcription + if diarization_segs: + audio_duration = max(s["end"] for s in diarization_segs) + elif transcription_segments: + audio_duration = max(s.get("end", 0) for s in transcription_segments) + else: + audio_duration = 0.0 + + return DiarizedTranscriptionResponse( + segments=[TranscriptionSegment(**s) for s in aligned], + speakers_count=len(speakers), + audio_duration=round(audio_duration, 2), + language=language, + full_text=full_text.strip(), + diarization_method=method, + ) + + finally: + try: + os.unlink(tmp_path) + except Exception: + pass + + +# ── Helper: call Whisper for transcription with timestamps ──────────────────── +async def _call_whisper_segments(audio_bytes: bytes, filename: str, language: str) -> list: + """ + Calls the original Whisper server at /transcribe-segments and returns + the segments list [{start, end, text}, ...]. + """ + try: + async with httpx.AsyncClient(timeout=600.0) as client: + files = {"file": (filename, audio_bytes, "application/octet-stream")} + data = {"language": language} + resp = await client.post( + f"{WHISPER_ORIGIN}/transcribe-segments", + files=files, + data=data, + ) + resp.raise_for_status() + result = resp.json() + + # Expected: {"text": "...", "language": "...", "segments": [...]} + segments = result.get("segments", []) + if not segments and result.get("text"): + # Fallback: no segments, create a single segment + segments = [{"start": 0.0, "end": 0.0, "text": result["text"]}] + return segments + + except httpx.ConnectError as e: + logger.error(f"Cannot connect to Whisper server: {e}") + raise HTTPException( + status_code=503, + detail=f"Whisper server unavailable: {str(e)}", + ) + except httpx.HTTPStatusError as e: + logger.error(f"Whisper server error {e.response.status_code}: {e.response.text}") + raise HTTPException( + status_code=502, + detail=f"Whisper server returned {e.response.status_code}", + ) + except Exception as e: + logger.error(f"Transcription error: {e}", exc_info=True) + raise HTTPException(status_code=500, detail=f"Transcription failed: {str(e)}") diff --git a/diarization/services/__init__.py b/diarization/services/__init__.py new file mode 100644 index 0000000..143f486 --- /dev/null +++ b/diarization/services/__init__.py @@ -0,0 +1 @@ +# __init__.py diff --git a/diarization/services/diarization.py b/diarization/services/diarization.py new file mode 100644 index 0000000..df0a172 --- /dev/null +++ b/diarization/services/diarization.py @@ -0,0 +1,490 @@ +""" +Diarization service — speaker identification pipeline. + +Priority order: + 1. pyannote.audio 3.1 — best quality, requires HuggingFace token with model access + 2. SpeechBrain ECAPA-TDNN — good quality (~85%), no license needed, GPU-accelerated + 3. Energy + MFCC fallback — basic quality (~60%), pure CPU, always available + +Speaker embeddings for enrollment: + Same priority: pyannote → SpeechBrain → MFCC +""" +import os +import io +import logging +import tempfile +import numpy as np +from typing import List, Dict, Any, Optional, Tuple + +logger = logging.getLogger(__name__) + +# ── Pyannote (primary) ──────────────────────────────────────────────────────── +_pyannote_pipeline = None +_pyannote_tried = False +HF_TOKEN = os.getenv("HF_TOKEN", "hf_placeholder_token") + +# ── SpeechBrain (secondary) ─────────────────────────────────────────────────── +_speechbrain_model = None +_speechbrain_tried = False +SPEECHBRAIN_CACHE = os.getenv("SPEECHBRAIN_CACHE", "/tmp/speechbrain_ecapa") + + +def _try_load_pyannote(): + global _pyannote_pipeline, _pyannote_tried + if _pyannote_tried: + return _pyannote_pipeline + _pyannote_tried = True + try: + from pyannote.audio import Pipeline + logger.info("Loading pyannote speaker-diarization-3.1 ...") + pipeline = Pipeline.from_pretrained( + "pyannote/speaker-diarization-3.1", + use_auth_token=HF_TOKEN, + ) + import torch + if torch.cuda.is_available(): + pipeline = pipeline.to(torch.device("cuda")) + _pyannote_pipeline = pipeline + logger.info("pyannote pipeline loaded successfully.") + except Exception as e: + logger.warning(f"pyannote unavailable ({e}), will use energy-based fallback.") + _pyannote_pipeline = None + return _pyannote_pipeline + + +# ── pyannote embedding (for enrollment) ────────────────────────────────────── +_embedding_model = None +_embedding_tried = False + + +def _try_load_speechbrain(): + global _speechbrain_model, _speechbrain_tried + if _speechbrain_tried: + return _speechbrain_model + _speechbrain_tried = True + try: + import torch + from speechbrain.inference.speaker import EncoderClassifier + logger.info("Loading SpeechBrain ECAPA-TDNN model...") + device = "cuda" if torch.cuda.is_available() else "cpu" + classifier = EncoderClassifier.from_hparams( + source="speechbrain/spkrec-ecapa-voxceleb", + savedir=SPEECHBRAIN_CACHE, + run_opts={"device": device}, + ) + _speechbrain_model = classifier + logger.info(f"SpeechBrain ECAPA-TDNN loaded on {device}.") + except Exception as e: + logger.warning(f"SpeechBrain unavailable ({e}), will use MFCC fallback.") + _speechbrain_model = None + return _speechbrain_model + + +def _try_load_embedding_model(): + global _embedding_model, _embedding_tried + if _embedding_tried: + return _embedding_model + _embedding_tried = True + try: + from pyannote.audio import Model + from pyannote.audio import Inference + logger.info("Loading pyannote embedding model...") + model = Model.from_pretrained("pyannote/embedding", use_auth_token=HF_TOKEN) + _embedding_model = Inference(model, window="whole") + logger.info("pyannote embedding model loaded.") + except Exception: + sb = _try_load_speechbrain() + if sb is not None: + _embedding_model = ("speechbrain", sb) + logger.info("Using SpeechBrain for embeddings.") + else: + logger.warning("No embedding model available. Using MFCC fallback.") + _embedding_model = None + return _embedding_model + + +# ── Pyannote diarization ────────────────────────────────────────────────────── +def _diarize_pyannote(audio_path: str) -> List[Dict]: + """Run pyannote diarization. Returns list of {start, end, speaker}.""" + pipeline = _try_load_pyannote() + if pipeline is None: + raise RuntimeError("pyannote not available") + diarization = pipeline(audio_path) + segments = [] + for turn, _, speaker in diarization.itertracks(yield_label=True): + segments.append({"start": round(turn.start, 3), "end": round(turn.end, 3), "speaker": speaker}) + return segments + + +# ── Shared VAD: detects speech segments using energy thresholding ───────────── +def _get_speech_segments(audio_path: str, min_silence_sec: float = 0.5) -> Tuple[np.ndarray, int, List[Dict]]: + """ + Energy-based Voice Activity Detection. + Returns (y, sr, segments) where segments = [{start, end}, ...]. + """ + import librosa + + y, sr = librosa.load(audio_path, sr=16000, mono=True) + frame_len = int(0.025 * sr) # 25 ms + hop_len = int(0.010 * sr) # 10 ms + + energy = librosa.feature.rms(y=y, frame_length=frame_len, hop_length=hop_len)[0] + nonzero_energy = energy[energy > 0] + + if len(nonzero_energy) == 0: + duration = len(y) / sr + return y, sr, [{"start": 0.0, "end": round(float(duration), 3)}] + + threshold = np.percentile(nonzero_energy, 20) + is_speech = energy > threshold + times = librosa.frames_to_time(np.arange(len(is_speech)), sr=sr, hop_length=hop_len) + min_silence_frames = int(min_silence_sec / (hop_len / sr)) + + segments_raw = [] + in_speech = False + seg_start = 0.0 + silence_count = 0 + + for i, (t, sp) in enumerate(zip(times, is_speech)): + if sp: + if not in_speech: + seg_start = t + in_speech = True + silence_count = 0 + else: + if in_speech: + silence_count += 1 + if silence_count >= min_silence_frames: + seg_end = times[i - silence_count] if i >= silence_count else t + if seg_end - seg_start > 0.3: + segments_raw.append({"start": round(seg_start, 3), "end": round(seg_end, 3)}) + in_speech = False + silence_count = 0 + + if in_speech: + segments_raw.append({"start": round(seg_start, 3), "end": round(float(times[-1]), 3)}) + + if not segments_raw: + segments_raw = [{"start": 0.0, "end": round(float(len(y) / sr), 3)}] + + return y, sr, segments_raw + + +def _estimate_n_speakers(embeddings: np.ndarray, max_speakers: int = 8) -> int: + """ + Estimate optimal number of speakers using the elbow method on + intra-cluster variance. Tries k=1..max_speakers and picks the k where + adding one more cluster yields < 15% improvement of total variance range. + """ + n = len(embeddings) + if n <= 1: + return 1 + max_k = min(max_speakers, n) + if max_k <= 2: + return max_k + + norms = np.linalg.norm(embeddings, axis=1, keepdims=True) + norms[norms == 0] = 1e-10 + normed = embeddings / norms + + variances = [] + for k in range(1, max_k + 1): + labels = _cosine_cluster(normed, n_clusters=k) + total_var = 0.0 + for c in range(k): + mask = labels == c + if mask.sum() > 1: + centroid = normed[mask].mean(axis=0) + total_var += float(np.mean(1 - normed[mask] @ centroid)) + variances.append(total_var) + + if len(variances) < 2: + return 1 + + total_range = variances[0] - variances[-1] + if total_range < 1e-6: + return 1 + + for k_idx in range(1, len(variances)): + improvement = variances[k_idx - 1] - variances[k_idx] + if improvement < 0.15 * total_range: + return k_idx # k = k_idx (1-indexed) + + return max_k + + +# ── SpeechBrain ECAPA-TDNN diarization (secondary) ─────────────────────────── +def _diarize_speechbrain(audio_path: str, num_speakers: Optional[int] = None) -> List[Dict]: + """ + SpeechBrain ECAPA-TDNN diarization. + Uses energy-based VAD for segmentation, ECAPA-TDNN 192-dim embeddings, + and cosine k-means clustering. ~85% accuracy vs ~60% for MFCC. + """ + import torch + + classifier = _try_load_speechbrain() + if classifier is None: + raise RuntimeError("SpeechBrain not available") + + y, sr, segments_raw = _get_speech_segments(audio_path, min_silence_sec=0.5) + if len(segments_raw) == 0: + return [] + + embeddings = [] + for seg in segments_raw: + start_sample = int(seg["start"] * sr) + end_sample = int(seg["end"] * sr) + chunk = y[start_sample:end_sample] + min_samples = int(0.1 * sr) # 100ms minimum + if len(chunk) < min_samples: + embeddings.append(np.zeros(192)) + continue + waveform = torch.tensor(chunk).unsqueeze(0).float() + try: + with torch.no_grad(): + emb = classifier.encode_batch(waveform) + embeddings.append(emb.squeeze().cpu().numpy()) + except Exception as e: + logger.warning(f"ECAPA-TDNN embedding failed for segment: {e}") + embeddings.append(np.zeros(192)) + + embeddings_arr = np.array(embeddings) + + n_speakers = num_speakers if num_speakers else _estimate_n_speakers(embeddings_arr, max_speakers=8) + n_speakers = max(1, min(n_speakers, len(segments_raw))) + + labels = _cosine_cluster(embeddings_arr, n_clusters=n_speakers) + + for seg, label in zip(segments_raw, labels): + seg["speaker"] = f"SPEAKER_{(label + 1):02d}" + + return segments_raw + + +# ── Energy + MFCC fallback diarization ─────────────────────────────────────── +def _diarize_energy(audio_path: str, min_silence_sec: float = 0.5, num_speakers: Optional[int] = None) -> List[Dict]: + """ + Energy-based VAD + MFCC cosine clustering fallback (~60% accuracy). + Used when both pyannote and SpeechBrain are unavailable. + """ + import librosa + + y, sr, segments_raw = _get_speech_segments(audio_path, min_silence_sec=min_silence_sec) + + if len(segments_raw) == 0: + return [] + + frame_len = int(0.025 * sr) + + def seg_mfcc(s): + start_sample = int(s["start"] * sr) + end_sample = int(s["end"] * sr) + chunk = y[start_sample:end_sample] + if len(chunk) < frame_len: + return np.zeros(20) + mfcc = librosa.feature.mfcc(y=chunk, sr=sr, n_mfcc=20) + return mfcc.mean(axis=1) + + features = np.array([seg_mfcc(s) for s in segments_raw]) + n_sp = num_speakers if num_speakers else _estimate_n_speakers(features, max_speakers=6) + n_sp = max(1, min(n_sp, len(segments_raw))) + labels = _cosine_cluster(features, n_clusters=n_sp) + + for seg, label in zip(segments_raw, labels): + seg["speaker"] = f"SPEAKER_{(label + 1):02d}" + + return segments_raw + + +def _cosine_cluster(features: np.ndarray, n_clusters: int) -> np.ndarray: + """Greedy cosine-distance clustering (no sklearn dependency).""" + if n_clusters <= 1 or len(features) <= 1: + return np.zeros(len(features), dtype=int) + + norms = np.linalg.norm(features, axis=1, keepdims=True) + norms[norms == 0] = 1e-10 + normed = features / norms + + # Initialize centroids as first n_clusters samples + centroids = normed[:n_clusters].copy() + labels = np.zeros(len(features), dtype=int) + + for _ in range(20): # max iterations + # Assign to nearest centroid (highest cosine similarity) + sims = normed @ centroids.T # (N, K) + new_labels = np.argmax(sims, axis=1) + + if np.all(new_labels == labels): + break + labels = new_labels + + # Update centroids + for k in range(n_clusters): + mask = labels == k + if mask.any(): + centroids[k] = normed[mask].mean(axis=0) + norm = np.linalg.norm(centroids[k]) + if norm > 0: + centroids[k] /= norm + + return labels + + +# ── Public diarization entry point ─────────────────────────────────────────── +def diarize(audio_path: str, num_speakers: Optional[int] = None) -> Tuple[List[Dict], str]: + """ + Returns (segments, method) where: + segments: [{start, end, speaker}, ...] + method: "pyannote" | "speechbrain" | "energy_fallback" + + Priority: pyannote → SpeechBrain ECAPA-TDNN → energy+MFCC + """ + try: + segs = _diarize_pyannote(audio_path) + return segs, "pyannote" + except Exception as e: + logger.warning(f"pyannote diarization failed ({e}), trying SpeechBrain") + + try: + segs = _diarize_speechbrain(audio_path, num_speakers=num_speakers) + return segs, "speechbrain" + except Exception as e: + logger.warning(f"SpeechBrain diarization failed ({e}), using MFCC fallback") + + segs = _diarize_energy(audio_path, num_speakers=num_speakers) + return segs, "energy_fallback" + + +# ── Transcription + diarization alignment ──────────────────────────────────── +def align_transcription_with_diarization( + transcription_segments: List[Dict], + diarization_segments: List[Dict], +) -> List[Dict]: + """ + For each transcription segment {start, end, text}, find the speaker with + the most time overlap from diarization_segments. + Falls back to temporally closest speaker if no overlap. + Merges consecutive same-speaker segments < 1 second apart. + """ + result = [] + + for tseg in transcription_segments: + t_start = tseg.get("start", 0.0) + t_end = tseg.get("end", t_start + 0.1) + text = tseg.get("text", "").strip() + + if not text: + continue + + # Find best speaker by overlap + best_speaker = None + best_overlap = -1.0 + best_dist = float("inf") + + for dseg in diarization_segments: + d_start = dseg["start"] + d_end = dseg["end"] + speaker = dseg["speaker"] + + overlap = max(0.0, min(t_end, d_end) - max(t_start, d_start)) + if overlap > best_overlap: + best_overlap = overlap + best_speaker = speaker + + # Track closest for fallback + dist = min(abs(t_start - d_start), abs(t_start - d_end), + abs(t_end - d_start), abs(t_end - d_end)) + if dist < best_dist: + best_dist = dist + if best_overlap <= 0: + best_speaker = speaker + + if best_speaker is None: + best_speaker = "SPEAKER_01" + + result.append({ + "start": round(t_start, 3), + "end": round(t_end, 3), + "speaker": best_speaker, + "text": text, + }) + + # Merge consecutive same-speaker segments where gap < 1 second + if not result: + return result + + merged = [result[0].copy()] + for seg in result[1:]: + prev = merged[-1] + gap = seg["start"] - prev["end"] + if seg["speaker"] == prev["speaker"] and gap < 1.0: + prev["end"] = seg["end"] + prev["text"] = prev["text"].rstrip() + " " + seg["text"].lstrip() + else: + merged.append(seg.copy()) + + return merged + + +# ── Embedding extraction ────────────────────────────────────────────────────── +def extract_embedding(audio_path: str) -> np.ndarray: + """ + Extract speaker embedding from audio file. + Returns 1-D numpy array. + Falls back to MFCC-based embedding if models unavailable. + """ + model = _try_load_embedding_model() + + if model is not None: + if isinstance(model, tuple) and model[0] == "speechbrain": + _, classifier = model + try: + import torch + import torchaudio + waveform, sr = torchaudio.load(audio_path) + if sr != 16000: + resampler = torchaudio.transforms.Resample(sr, 16000) + waveform = resampler(waveform) + embedding = classifier.encode_batch(waveform) + return embedding.squeeze().cpu().numpy() + except Exception as e: + logger.warning(f"SpeechBrain embedding failed: {e}") + else: + # pyannote Inference + try: + embedding = model(audio_path) + if hasattr(embedding, 'data'): + return np.array(embedding.data).flatten() + return np.array(embedding).flatten() + except Exception as e: + logger.warning(f"pyannote embedding failed: {e}") + + # MFCC fallback + return _mfcc_embedding(audio_path) + + +def _mfcc_embedding(audio_path: str) -> np.ndarray: + """Create a simple MFCC-based speaker embedding (128-dim).""" + import librosa + y, sr = librosa.load(audio_path, sr=16000, mono=True) + mfcc = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=40) + delta = librosa.feature.delta(mfcc) + delta2 = librosa.feature.delta(mfcc, order=2) + features = np.concatenate([ + mfcc.mean(axis=1), mfcc.std(axis=1), + delta.mean(axis=1), + delta2.mean(axis=1), + ]) + norm = np.linalg.norm(features) + if norm > 0: + features = features / norm + return features.astype(np.float32) + + +def cosine_similarity(a: np.ndarray, b: np.ndarray) -> float: + """Cosine similarity between two vectors.""" + na = np.linalg.norm(a) + nb = np.linalg.norm(b) + if na == 0 or nb == 0: + return 0.0 + return float(np.dot(a, b) / (na * nb)) diff --git a/diarization/services/enrollment.py b/diarization/services/enrollment.py new file mode 100644 index 0000000..72a0faf --- /dev/null +++ b/diarization/services/enrollment.py @@ -0,0 +1,228 @@ +""" +Voice enrollment and speaker identification service. +Uses SQLite at /opt/Backend/whisper-diarization-api/voice_profiles.db +""" +import os +import uuid +import pickle +import logging +import sqlite3 +import numpy as np +from datetime import datetime, timezone +from typing import List, Optional, Dict, Any + +logger = logging.getLogger(__name__) + +DB_PATH = os.getenv("VOICE_DB_PATH", "/opt/Backend/whisper-diarization-api/voice_profiles.db") +CONFIDENCE_THRESHOLD = float(os.getenv("SPEAKER_CONFIDENCE_THRESHOLD", "0.75")) + + +def _conn(): + conn = sqlite3.connect(DB_PATH) + conn.row_factory = sqlite3.Row + return conn + + +# ── Schema ─────────────────────────────────────────────────────────────────── +def init_db(): + os.makedirs(os.path.dirname(DB_PATH), exist_ok=True) + with _conn() as conn: + conn.executescript(""" + CREATE TABLE IF NOT EXISTS voice_profiles ( + id TEXT PRIMARY KEY, + name TEXT NOT NULL, + email TEXT, + metadata TEXT, + created_at TEXT NOT NULL, + updated_at TEXT NOT NULL + ); + + CREATE TABLE IF NOT EXISTS voice_embeddings ( + id TEXT PRIMARY KEY, + profile_id TEXT NOT NULL REFERENCES voice_profiles(id) ON DELETE CASCADE, + embedding BLOB NOT NULL, + created_at TEXT NOT NULL + ); + """) + logger.info(f"Voice profiles DB initialised at {DB_PATH}") + + +# ── Helpers ─────────────────────────────────────────────────────────────────── +def _now() -> str: + return datetime.now(timezone.utc).isoformat() + + +def _serialize(arr: np.ndarray) -> bytes: + return pickle.dumps(arr) + + +def _deserialize(blob: bytes) -> np.ndarray: + return pickle.loads(blob) + + +def _profile_row_to_dict(row: sqlite3.Row, embeddings_count: int = 0) -> Dict[str, Any]: + return { + "id": row["id"], + "name": row["name"], + "email": row["email"], + "metadata": row["metadata"], + "embeddings_count": embeddings_count, + "created_at": row["created_at"], + "updated_at": row["updated_at"], + } + + +# ── CRUD: Voice Profiles ────────────────────────────────────────────────────── +def create_profile(name: str, email: Optional[str], metadata: Optional[str]) -> Dict[str, Any]: + profile_id = str(uuid.uuid4()) + now = _now() + with _conn() as conn: + conn.execute( + "INSERT INTO voice_profiles (id, name, email, metadata, created_at, updated_at) VALUES (?,?,?,?,?,?)", + (profile_id, name, email, metadata, now, now), + ) + return { + "id": profile_id, + "name": name, + "email": email, + "metadata": metadata, + "embeddings_count": 0, + "created_at": now, + "updated_at": now, + } + + +def get_profile(profile_id: str) -> Optional[Dict[str, Any]]: + with _conn() as conn: + row = conn.execute("SELECT * FROM voice_profiles WHERE id = ?", (profile_id,)).fetchone() + if row is None: + return None + count = conn.execute( + "SELECT COUNT(*) FROM voice_embeddings WHERE profile_id = ?", (profile_id,) + ).fetchone()[0] + return _profile_row_to_dict(row, count) + + +def list_profiles() -> List[Dict[str, Any]]: + with _conn() as conn: + rows = conn.execute("SELECT * FROM voice_profiles ORDER BY created_at DESC").fetchall() + result = [] + for row in rows: + count = conn.execute( + "SELECT COUNT(*) FROM voice_embeddings WHERE profile_id = ?", (row["id"],) + ).fetchone()[0] + result.append(_profile_row_to_dict(row, count)) + return result + + +def update_profile( + profile_id: str, + name: Optional[str] = None, + email: Optional[str] = None, + metadata: Optional[str] = None, +) -> Optional[Dict[str, Any]]: + profile = get_profile(profile_id) + if profile is None: + return None + + new_name = name if name is not None else profile["name"] + new_email = email if email is not None else profile["email"] + new_meta = metadata if metadata is not None else profile["metadata"] + now = _now() + + with _conn() as conn: + conn.execute( + "UPDATE voice_profiles SET name=?, email=?, metadata=?, updated_at=? WHERE id=?", + (new_name, new_email, new_meta, now, profile_id), + ) + return get_profile(profile_id) + + +def delete_profile(profile_id: str) -> bool: + with _conn() as conn: + cur = conn.execute("DELETE FROM voice_profiles WHERE id = ?", (profile_id,)) + return cur.rowcount > 0 + + +# ── Embeddings ──────────────────────────────────────────────────────────────── +def add_embedding(profile_id: str, embedding: np.ndarray) -> str: + emb_id = str(uuid.uuid4()) + now = _now() + with _conn() as conn: + conn.execute( + "INSERT INTO voice_embeddings (id, profile_id, embedding, created_at) VALUES (?,?,?,?)", + (emb_id, profile_id, _serialize(embedding), now), + ) + conn.execute("UPDATE voice_profiles SET updated_at=? WHERE id=?", (now, profile_id)) + return emb_id + + +def get_all_embeddings() -> List[Dict[str, Any]]: + """Returns all embeddings with profile info.""" + with _conn() as conn: + rows = conn.execute(""" + SELECT ve.id, ve.profile_id, ve.embedding, vp.name + FROM voice_embeddings ve + JOIN voice_profiles vp ON ve.profile_id = vp.id + """).fetchall() + return [ + { + "embedding_id": r["id"], + "profile_id": r["profile_id"], + "speaker_name": r["name"], + "embedding": _deserialize(r["embedding"]), + } + for r in rows + ] + + +# ── Speaker identification ──────────────────────────────────────────────────── +def identify_speaker(query_embedding: np.ndarray, threshold: Optional[float] = None) -> Dict[str, Any]: + """ + Compare query_embedding against all registered speakers. + Returns the best match if confidence >= threshold. + """ + from services.diarization import cosine_similarity + + if threshold is None: + threshold = CONFIDENCE_THRESHOLD + + all_embs = get_all_embeddings() + if not all_embs: + return {"matched": False, "speaker_id": None, "speaker_name": None, "confidence": 0.0, "threshold": threshold} + + # Average embeddings per profile + profile_map: Dict[str, Dict[str, Any]] = {} + for item in all_embs: + pid = item["profile_id"] + if pid not in profile_map: + profile_map[pid] = {"speaker_name": item["speaker_name"], "embeddings": []} + profile_map[pid]["embeddings"].append(item["embedding"]) + + best_profile_id = None + best_score = -1.0 + + for pid, info in profile_map.items(): + # Average cosine similarity against all stored embeddings + scores = [cosine_similarity(query_embedding, e) for e in info["embeddings"]] + avg_score = float(np.mean(scores)) + if avg_score > best_score: + best_score = avg_score + best_profile_id = pid + + if best_profile_id is None or best_score < threshold: + return { + "matched": False, + "speaker_id": best_profile_id, + "speaker_name": profile_map[best_profile_id]["speaker_name"] if best_profile_id else None, + "confidence": round(best_score, 4), + "threshold": threshold, + } + + return { + "matched": True, + "speaker_id": best_profile_id, + "speaker_name": profile_map[best_profile_id]["speaker_name"], + "confidence": round(best_score, 4), + "threshold": threshold, + } diff --git a/frontend/.gitignore b/frontend/.gitignore new file mode 100644 index 0000000..a547bf3 --- /dev/null +++ b/frontend/.gitignore @@ -0,0 +1,24 @@ +# Logs +logs +*.log +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* +lerna-debug.log* + +node_modules +dist +dist-ssr +*.local + +# Editor directories and files +.vscode/* +!.vscode/extensions.json +.idea +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? diff --git a/frontend/Dockerfile b/frontend/Dockerfile new file mode 100644 index 0000000..105f508 --- /dev/null +++ b/frontend/Dockerfile @@ -0,0 +1,12 @@ +FROM node:20-alpine AS builder +WORKDIR /app +COPY package*.json ./ +RUN npm ci --legacy-peer-deps +COPY . . +RUN npm run build + +FROM nginx:alpine +COPY --from=builder /app/dist /usr/share/nginx/html +COPY nginx.conf /etc/nginx/conf.d/default.conf +EXPOSE 80 +CMD ["nginx", "-g", "daemon off;"] diff --git a/frontend/README.md b/frontend/README.md new file mode 100644 index 0000000..7dbf7eb --- /dev/null +++ b/frontend/README.md @@ -0,0 +1,73 @@ +# React + TypeScript + Vite + +This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules. + +Currently, two official plugins are available: + +- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Oxc](https://oxc.rs) +- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/) + +## React Compiler + +The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation). + +## Expanding the ESLint configuration + +If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules: + +```js +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + // Other configs... + + // Remove tseslint.configs.recommended and replace with this + tseslint.configs.recommendedTypeChecked, + // Alternatively, use this for stricter rules + tseslint.configs.strictTypeChecked, + // Optionally, add this for stylistic rules + tseslint.configs.stylisticTypeChecked, + + // Other configs... + ], + languageOptions: { + parserOptions: { + project: ['./tsconfig.node.json', './tsconfig.app.json'], + tsconfigRootDir: import.meta.dirname, + }, + // other options... + }, + }, +]) +``` + +You can also install [eslint-plugin-react-x](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-x) and [eslint-plugin-react-dom](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-dom) for React-specific lint rules: + +```js +// eslint.config.js +import reactX from 'eslint-plugin-react-x' +import reactDom from 'eslint-plugin-react-dom' + +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + // Other configs... + // Enable lint rules for React + reactX.configs['recommended-typescript'], + // Enable lint rules for React DOM + reactDom.configs.recommended, + ], + languageOptions: { + parserOptions: { + project: ['./tsconfig.node.json', './tsconfig.app.json'], + tsconfigRootDir: import.meta.dirname, + }, + // other options... + }, + }, +]) +``` diff --git a/frontend/deploy.py b/frontend/deploy.py new file mode 100644 index 0000000..081a6d2 --- /dev/null +++ b/frontend/deploy.py @@ -0,0 +1,102 @@ +#!/usr/bin/env python3 +import paramiko +import os +import tarfile +import io +from pathlib import Path +import time + +# Server details +HOST = '5.0.0.181' +USER = 'root' +PASSWORD = 'Ozzyos1bsd3' +REMOTE_PATH = '/opt/Frontend/meeting-assistant-fe/' + +try: + print('[1] Connecting to server...') + ssh = paramiko.SSHClient() + ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) + ssh.connect(HOST, username=USER, password=PASSWORD, timeout=30) + print(f' ✓ Connected to {HOST}') + + # Stop and remove container + print('[2] Stopping and removing container...') + stdin, stdout, stderr = ssh.exec_command('podman stop meeting-assistant-fe && podman rm meeting-assistant-fe 2>/dev/null || true') + stdout.channel.recv_exit_status() + print(' ✓ Container stopped and removed') + + # Create tar archive in memory + print('[3] Creating tar archive of project...') + tar_buffer = io.BytesIO() + with tarfile.open(fileobj=tar_buffer, mode='w:gz') as tar: + project_dir = Path('.') + exclude_dirs = {'node_modules', '.git', '.next', 'dist', '.env', '.env.local', '.DS_Store'} + + for item in project_dir.rglob('*'): + # Skip excluded directories + if any(excl in item.parts for excl in exclude_dirs): + continue + if item.is_file(): + arcname = str(item.relative_to(project_dir)) + tar.add(item, arcname=arcname) + + tar_buffer.seek(0) + tar_size = len(tar_buffer.getvalue()) + print(f' ✓ Archive created ({tar_size / 1024 / 1024:.2f} MB)') + + # Upload via SFTP + print('[4] Uploading project to server...') + sftp = ssh.open_sftp() + remote_tar = f'{REMOTE_PATH}project.tar.gz' + sftp.putfo(tar_buffer, remote_tar) + sftp.close() + print(f' ✓ Uploaded to {remote_tar}') + + # Extract on server + print('[5] Extracting archive on server...') + stdin, stdout, stderr = ssh.exec_command(f'cd {REMOTE_PATH} && tar -xzf project.tar.gz && rm project.tar.gz') + stdout.channel.recv_exit_status() + print(' ✓ Archive extracted') + + # Rebuild image + print('[6] Rebuilding Docker image...') + stdin, stdout, stderr = ssh.exec_command(f'cd {REMOTE_PATH} && podman build -t meeting-assistant-fe . 2>&1') + build_output = stdout.read().decode() + build_err = stderr.read().decode() + exit_code = stdout.channel.recv_exit_status() + if exit_code != 0: + print(f' ⚠️ Build warnings/info:\n{build_output}\n{build_err}') + print(' ✓ Image built') + + # Start container + print('[7] Starting new container...') + stdin, stdout, stderr = ssh.exec_command('podman run -d --name meeting-assistant-fe --restart unless-stopped -p 3010:80 meeting-assistant-fe') + container_id = stdout.read().decode().strip() + stdout.channel.recv_exit_status() + print(f' ✓ Container started (ID: {container_id[:12]}...)') + + # Wait for container to be ready + time.sleep(2) + + # Verify + print('[8] Verifying deployment...') + stdin, stdout, stderr = ssh.exec_command('curl -s -o /dev/null -w "%{http_code}" http://localhost:3010/') + exit_code = stdout.channel.recv_exit_status() + response = stdout.read().decode().strip() + print(f' ✓ Response code: {response}') + + if response == '200': + print('\n✅ Deployment successful! PWA is live at http://5.0.0.181:3010/') + else: + print(f'\n⚠️ Unexpected response code: {response}') + # Check container logs + stdin, stdout, stderr = ssh.exec_command('podman logs meeting-assistant-fe --tail 20') + logs = stdout.read().decode() + print(f'Container logs:\n{logs}') + + ssh.close() + +except Exception as e: + print(f'\n❌ Deployment failed: {e}') + import traceback + traceback.print_exc() diff --git a/frontend/docker-compose.yml b/frontend/docker-compose.yml new file mode 100644 index 0000000..e2c617a --- /dev/null +++ b/frontend/docker-compose.yml @@ -0,0 +1,14 @@ +version: '3.8' +services: + meeting-assistant-fe: + build: . + container_name: meeting-assistant-fe + restart: unless-stopped + ports: + - "3000:80" + networks: + - meeting-network + +networks: + meeting-network: + driver: bridge diff --git a/frontend/eslint.config.js b/frontend/eslint.config.js new file mode 100644 index 0000000..5e6b472 --- /dev/null +++ b/frontend/eslint.config.js @@ -0,0 +1,23 @@ +import js from '@eslint/js' +import globals from 'globals' +import reactHooks from 'eslint-plugin-react-hooks' +import reactRefresh from 'eslint-plugin-react-refresh' +import tseslint from 'typescript-eslint' +import { defineConfig, globalIgnores } from 'eslint/config' + +export default defineConfig([ + globalIgnores(['dist']), + { + files: ['**/*.{ts,tsx}'], + extends: [ + js.configs.recommended, + tseslint.configs.recommended, + reactHooks.configs.flat.recommended, + reactRefresh.configs.vite, + ], + languageOptions: { + ecmaVersion: 2020, + globals: globals.browser, + }, + }, +]) diff --git a/frontend/index.html b/frontend/index.html new file mode 100644 index 0000000..6b2471b --- /dev/null +++ b/frontend/index.html @@ -0,0 +1,13 @@ + + + + + + + MAIA — Meeting AI Assistant + + +
+ + + diff --git a/frontend/nginx.conf b/frontend/nginx.conf new file mode 100644 index 0000000..02befa2 --- /dev/null +++ b/frontend/nginx.conf @@ -0,0 +1,51 @@ +server { + listen 80; + root /usr/share/nginx/html; + index index.html; + + # SPA fallback + location / { + try_files $uri $uri/ /index.html; + } + + # Proxy to backend API (avoids CORS) + location /api/ { + proxy_pass http://5.0.0.181:8090/api/; + proxy_set_header Host $host; + proxy_set_header X-Real-IP $remote_addr; + proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; + proxy_set_header X-Forwarded-Proto $scheme; + } + + # WebSocket proxy + location /ws/ { + proxy_pass http://5.0.0.181:8090/ws/; + proxy_http_version 1.1; + proxy_set_header Upgrade $http_upgrade; + proxy_set_header Connection "upgrade"; + proxy_set_header Host $host; + proxy_read_timeout 3600s; + } + + # Service Worker e manifest — NUNCA cachear (browser precisa verificar updates) + location ~* (sw\.js|workbox-.*\.js|registerSW\.js|manifest\.webmanifest)$ { + expires -1; + add_header Cache-Control "no-cache, no-store, must-revalidate"; + add_header Pragma "no-cache"; + } + + # Cache assets versionados por hash (imutáveis) + location /assets/ { + expires 1y; + add_header Cache-Control "public, immutable"; + } + + # Cache outros estáticos (ícones, fontes) + location ~* \.(png|svg|ico|woff2)$ { + expires 30d; + add_header Cache-Control "public"; + } + + gzip on; + gzip_types text/plain text/css application/json application/javascript text/xml application/xml; +} diff --git a/frontend/package-lock.json b/frontend/package-lock.json new file mode 100644 index 0000000..e075a25 --- /dev/null +++ b/frontend/package-lock.json @@ -0,0 +1,9958 @@ +{ + "name": "meeting-assistant-fe", + "version": "0.0.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "meeting-assistant-fe", + "version": "0.0.0", + "dependencies": { + "@radix-ui/react-avatar": "^1.1.11", + 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} + } + } + } +} diff --git a/frontend/package.json b/frontend/package.json new file mode 100644 index 0000000..544abf6 --- /dev/null +++ b/frontend/package.json @@ -0,0 +1,54 @@ +{ + "name": "meeting-assistant-fe", + "private": true, + "version": "0.0.0", + "type": "module", + "scripts": { + "dev": "vite", + "build": "tsc -b && vite build", + "lint": "eslint .", + "preview": "vite preview" + }, + "dependencies": { + "@radix-ui/react-avatar": "^1.1.11", + "@radix-ui/react-dialog": "^1.1.15", + "@radix-ui/react-dropdown-menu": "^2.1.16", + "@radix-ui/react-label": "^2.1.8", + "@radix-ui/react-progress": "^1.1.8", + "@radix-ui/react-select": "^2.2.6", + "@radix-ui/react-separator": "^1.1.8", + "@radix-ui/react-slot": "^1.2.4", + "@radix-ui/react-tabs": "^1.1.13", + "@radix-ui/react-toast": "^1.2.15", + "axios": "^1.15.0", + "class-variance-authority": "^0.7.1", + "clsx": "^2.1.1", + "idb": "^8.0.3", + "keycloak-js": "^26.2.4", + "lucide-react": "^1.8.0", + "react": "^19.2.4", + 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/dev/null +++ b/frontend/src/App.css @@ -0,0 +1,184 @@ +.counter { + font-size: 16px; + padding: 5px 10px; + border-radius: 5px; + color: var(--accent); + background: var(--accent-bg); + border: 2px solid transparent; + transition: border-color 0.3s; + margin-bottom: 24px; + + &:hover { + border-color: var(--accent-border); + } + &:focus-visible { + outline: 2px solid var(--accent); + outline-offset: 2px; + } +} + +.hero { + position: relative; + + .base, + .framework, + .vite { + inset-inline: 0; + margin: 0 auto; + } + + .base { + width: 170px; + position: relative; + z-index: 0; + } + + .framework, + .vite { + position: absolute; + } + + .framework { + z-index: 1; + top: 34px; + height: 28px; + transform: perspective(2000px) rotateZ(300deg) rotateX(44deg) rotateY(39deg) + scale(1.4); + } + + .vite { + z-index: 0; + top: 107px; + height: 26px; + width: auto; + transform: perspective(2000px) rotateZ(300deg) rotateX(40deg) rotateY(39deg) + scale(0.8); + } +} + +#center { + display: flex; + flex-direction: column; + gap: 25px; + place-content: center; + place-items: center; + flex-grow: 1; + + @media (max-width: 1024px) { + padding: 32px 20px 24px; + gap: 18px; + } +} + +#next-steps { + display: flex; + border-top: 1px solid var(--border); + text-align: left; + + & > div { + flex: 1 1 0; + padding: 32px; + @media (max-width: 1024px) { + padding: 24px 20px; + } + } + + .icon { + margin-bottom: 16px; + width: 22px; + height: 22px; + } + + @media (max-width: 1024px) { + flex-direction: column; + text-align: center; + } +} + +#docs { + border-right: 1px solid var(--border); + + @media (max-width: 1024px) { + border-right: none; + border-bottom: 1px solid var(--border); + } +} + +#next-steps ul { + list-style: none; + padding: 0; + display: flex; + gap: 8px; + margin: 32px 0 0; + + .logo { + height: 18px; + } + + a { + color: var(--text-h); + font-size: 16px; + border-radius: 6px; + background: var(--social-bg); + display: flex; + padding: 6px 12px; + align-items: center; + gap: 8px; + text-decoration: none; + transition: box-shadow 0.3s; + + &:hover { + box-shadow: var(--shadow); + } + .button-icon { + height: 18px; + width: 18px; + } + } + + @media (max-width: 1024px) { + margin-top: 20px; + flex-wrap: wrap; + justify-content: center; + + li { + flex: 1 1 calc(50% - 8px); + } + + a { + width: 100%; + justify-content: center; + box-sizing: border-box; + } + } +} + +#spacer { + height: 88px; + border-top: 1px solid var(--border); + @media (max-width: 1024px) { + height: 48px; + } +} + +.ticks { + position: relative; + width: 100%; + + &::before, + &::after { + content: ''; + position: absolute; + top: -4.5px; + border: 5px solid transparent; + } + + &::before { + left: 0; + border-left-color: var(--border); + } + &::after { + right: 0; + border-right-color: var(--border); + } +} diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx new file mode 100644 index 0000000..3bdd5bf --- /dev/null +++ b/frontend/src/App.tsx @@ -0,0 +1,32 @@ +import { BrowserRouter, Routes, Route, Navigate } from 'react-router-dom' +import { ProtectedRoute } from '@/components/ProtectedRoute' +import { Home } from '@/pages/Home' +import { Recording } from '@/pages/Recording' +import { UploadPage } from '@/pages/Upload' +import { History } from '@/pages/History' +import { MeetingDetail } from '@/pages/MeetingDetail' +import { Participants } from '@/pages/Participants' +import { Evolution } from '@/pages/Evolution' +import { Settings } from '@/pages/Settings' + +export default function App() { + return ( + + + } /> + } /> + } /> + } /> + } /> + } /> + } /> + } /> + } /> + {/* Keycloak handles auth — redirect legacy login/register paths to home */} + } /> + } /> + } /> + + + ) +} diff --git a/frontend/src/api/auth.ts b/frontend/src/api/auth.ts new file mode 100644 index 0000000..6878b25 --- /dev/null +++ b/frontend/src/api/auth.ts @@ -0,0 +1,21 @@ +import api from './axios' +import type { User } from '@/types' + +export const authApi = { + login: (email: string, password: string) => + api.post<{ access_token: string; refresh_token: string; user: User }>('/auth/login', { email, password }), + + register: (name: string, email: string, password: string) => + api.post<{ access_token: string; refresh_token: string; user: User }>('/auth/register', { name, email, password }), + + refresh: (refresh_token: string) => + api.post<{ access_token: string }>('/auth/refresh', { refresh_token }), + + keycloakAuth: async (kcToken: string) => { + const response = await api.post<{ access_token: string; refresh_token: string; token_type: string }>( + '/auth/keycloak', + { kc_token: kcToken } + ) + return response.data + }, +} diff --git a/frontend/src/api/axios.ts b/frontend/src/api/axios.ts new file mode 100644 index 0000000..f73beb1 --- /dev/null +++ b/frontend/src/api/axios.ts @@ -0,0 +1,55 @@ +import axios from 'axios' +import keycloak from '@/services/keycloak' +import { useAuthStore } from '@/store/authStore' + +const api = axios.create({ + baseURL: '/api', + timeout: 30000, +}) + +api.interceptors.request.use((config) => { + const token = localStorage.getItem('access_token') + if (token) config.headers.Authorization = `Bearer ${token}` + return config +}) + +api.interceptors.response.use( + (res) => res, + async (error) => { + const original = error.config + if (error.response?.status === 401 && !original._retry) { + original._retry = true + const refreshToken = localStorage.getItem('refresh_token') + if (refreshToken) { + try { + const { data } = await axios.post('/api/auth/refresh', { refresh_token: refreshToken }) + localStorage.setItem('access_token', data.access_token) + original.headers.Authorization = `Bearer ${data.access_token}` + return api(original) + } catch { + // Refresh failed — try re-exchanging via Keycloak + try { + await keycloak.updateToken(10) + if (keycloak.token) { + const { data } = await axios.post('/api/auth/keycloak', { kc_token: keycloak.token }) + localStorage.setItem('access_token', data.access_token) + localStorage.setItem('refresh_token', data.refresh_token) + original.headers.Authorization = `Bearer ${data.access_token}` + return api(original) + } + } catch { + // Keycloak session also expired — force re-login + } + useAuthStore.getState().logout() + keycloak.login() + } + } else { + useAuthStore.getState().logout() + keycloak.login() + } + } + return Promise.reject(error) + } +) + +export default api diff --git a/frontend/src/api/meetings.ts b/frontend/src/api/meetings.ts new file mode 100644 index 0000000..1a627ff --- /dev/null +++ b/frontend/src/api/meetings.ts @@ -0,0 +1,63 @@ +import api from './axios' +import type { Meeting, MeetingAnalysis, Transcript } from '@/types' + +export const meetingsApi = { + list: () => api.get('/meetings'), + + get: (id: string) => api.get(`/meetings/${id}`), + + getStatus: (id: string) => api.get<{ status: string; progress: number }>(`/meetings/${id}/status`), + + getTranscript: (id: string) => api.get(`/meetings/${id}/transcript`), + + getAnalyses: (id: string) => api.get(`/meetings/${id}/analyses`), + + getAnalysis: (id: string, type: string) => api.get(`/meetings/${id}/analyses/${type}`), + + upload: (file: File, title?: string, onProgress?: (p: number) => void) => { + const form = new FormData() + form.append('file', file) + const params = title ? { title } : {} + return api.post('/meetings/upload', form, { + params, + headers: { 'Content-Type': 'multipart/form-data' }, + onUploadProgress: (e) => { + if (onProgress && e.total) onProgress(Math.round((e.loaded * 100) / e.total)) + }, + }) + }, + + // --- Chunk recording endpoints --- + + startMeeting: async (title?: string): Promise => { + const { data } = await api.post('/meetings/start', null, { params: title?.trim() ? { title } : {} }) + return data + }, + + uploadChunk: async (meetingId: string, chunkIndex: number, blob: Blob, mimeType: string): Promise => { + const form = new FormData() + const ext = mimeType.includes('ogg') ? '.ogg' : mimeType.includes('mp4') ? '.mp4' : '.webm' + form.append('file', new File([blob], `chunk_${chunkIndex}${ext}`, { type: mimeType })) + form.append('chunk_index', String(chunkIndex)) + await api.post(`/meetings/${meetingId}/chunks`, form) + }, + + finalizeMeeting: async (meetingId: string, title?: string): Promise => { + const params = title ? { title } : {} + const { data } = await api.post(`/meetings/${meetingId}/finalize`, null, { params }) + return data + }, + + relabelParticipant: (meetingId: string, label: string, name: string) => + api.put(`/meetings/${meetingId}/participants/${label}`, { name }), + + enrollSpeaker: async (meetingId: string, speakerLabel: string, name: string, email?: string): Promise => { + await api.post(`/meetings/${meetingId}/participants/${encodeURIComponent(speakerLabel)}/enroll`, { name, email }) + }, + + delete: (id: string) => api.delete(`/meetings/${id}`), + + getAudioUrl: (id: string): string => { + return `/api/meetings/${id}/audio` + }, +} diff --git a/frontend/src/api/participants.ts b/frontend/src/api/participants.ts new file mode 100644 index 0000000..4e487e4 --- /dev/null +++ b/frontend/src/api/participants.ts @@ -0,0 +1,11 @@ +import api from './axios' +import type { Participant } from '@/types' + +export const participantsApi = { + list: () => api.get('/participants'), + + create: (name: string, email?: string) => + api.post('/participants', { name, email }), + + delete: (id: string) => api.delete(`/participants/${id}`), +} diff --git a/frontend/src/assets/hero.png b/frontend/src/assets/hero.png new file mode 100644 index 0000000000000000000000000000000000000000..cc51a3d20ad4bc961b596a6adfd686685cd84bb0 GIT binary patch literal 44919 zcma%i^5TDbT`tlgo2c`(n!ND-Q6MGAYIbZ-QCh5-QC^YozK_ne*b_MKK#O- zIWy zd$aJVZ?rl%;eiC7d#Sl-cWLv9rA0(UOX(@I3k&yyL+3GaQ4xpb1EGC|i|{byaTI># zBO=0pyZu5XO!hzGNPch4cx%6XJAJpDa<+98BOcYNo1=XER1sv!UW z^>ZDMp%FSmVnt)n^EIR+Nth`vRO^_=UF3EWv75ym{S;#2F8MPot@-y$>ioj!)a1bE 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+const navItems = [ + { to: '/', icon: Mic, label: 'Início' }, + { to: '/history', icon: History, label: 'Histórico' }, + { to: '/participants', icon: Users, label: 'Participantes' }, + { to: '/evolution', icon: TrendingUp, label: 'Evolução' }, + { to: '/settings', icon: Settings, label: 'Config.' }, +] + +export function Layout({ children }: { children: React.ReactNode }) { + const navigate = useNavigate() + const { logout, user } = useAuthStore() + + function handleLogout() { + logout() + navigate('/login') + } + + return ( +
+ {/* Header */} +
+
+ ASAP Telecom + MAIA +
+
+ {user?.name && ( + + {user.name} + + )} + +
+
+ + {/* Content */} +
{children}
+ + {/* Bottom Nav */} + +
+ ) +} diff --git a/frontend/src/components/ProtectedRoute.tsx b/frontend/src/components/ProtectedRoute.tsx new file mode 100644 index 0000000..ef75337 --- /dev/null +++ b/frontend/src/components/ProtectedRoute.tsx @@ -0,0 +1,7 @@ +import { useAuthStore } from '@/store/authStore' + +export function ProtectedRoute({ children }: { children: React.ReactNode }) { + const isAuthenticated = useAuthStore((s) => s.isAuthenticated) + if (!isAuthenticated) return null + return <>{children} +} diff --git a/frontend/src/components/StatusBadge.tsx b/frontend/src/components/StatusBadge.tsx new file mode 100644 index 0000000..bb231e6 --- /dev/null +++ b/frontend/src/components/StatusBadge.tsx @@ -0,0 +1,17 @@ +import { Badge } from '@/components/ui/badge' +import type { Meeting } from '@/types' + +const map: Record = { + receiving_chunks: { label: 'Gravando', variant: 'info' }, + uploading: { label: 'Enviando', variant: 'info' }, + processing: { label: 'Processando', variant: 'warning' }, + transcribing: { label: 'Transcrevendo', variant: 'warning' }, + analyzing: { label: 'Analisando', variant: 'warning' }, + completed: { label: 'Concluído', variant: 'default' }, + error: { label: 'Erro', variant: 'destructive' }, +} + +export function StatusBadge({ status }: { status: Meeting['status'] }) { + const { label, variant } = map[status] ?? { label: status, variant: 'secondary' } + return {label} +} diff --git a/frontend/src/components/ui/badge.tsx b/frontend/src/components/ui/badge.tsx new file mode 100644 index 0000000..2743e39 --- /dev/null +++ b/frontend/src/components/ui/badge.tsx @@ -0,0 +1,19 @@ +import { cn } from '@/utils/cn' +import { cva, type VariantProps } from 'class-variance-authority' + +const badgeVariants = cva('inline-flex items-center rounded-full px-2.5 py-0.5 text-xs font-semibold', { + variants: { + variant: { + default: 'bg-green-900 text-green-300', + secondary: 'bg-slate-700 text-slate-300', + destructive: 'bg-red-900 text-red-300', + warning: 'bg-yellow-900 text-yellow-300', + info: 'bg-blue-900 text-blue-300', + }, + }, + defaultVariants: { variant: 'default' }, +}) + +export function Badge({ className, variant, ...props }: React.HTMLAttributes & VariantProps) { + return
+} diff --git a/frontend/src/components/ui/button.tsx b/frontend/src/components/ui/button.tsx new file mode 100644 index 0000000..3684840 --- /dev/null +++ b/frontend/src/components/ui/button.tsx @@ -0,0 +1,36 @@ +import { forwardRef } from 'react' +import { cn } from '@/utils/cn' +import { cva, type VariantProps } from 'class-variance-authority' + +const buttonVariants = cva( + 'inline-flex items-center justify-center gap-2 rounded-lg font-medium transition-colors focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-green-500 disabled:opacity-50 disabled:pointer-events-none select-none', + { + variants: { + variant: { + default: 'bg-green-700 text-white hover:bg-green-600', + destructive: 'bg-red-600 text-white hover:bg-red-500', + outline: 'border border-slate-600 text-slate-200 hover:bg-slate-700', + ghost: 'text-slate-300 hover:bg-slate-700 hover:text-white', + secondary: 'bg-slate-700 text-slate-200 hover:bg-slate-600', + }, + size: { + default: 'h-10 px-4 py-2 text-sm', + sm: 'h-8 px-3 text-xs', + lg: 'h-12 px-6 text-base', + icon: 'h-10 w-10', + }, + }, + defaultVariants: { variant: 'default', size: 'default' }, + } +) + +export interface ButtonProps + extends React.ButtonHTMLAttributes, + VariantProps {} + +export const Button = forwardRef( + ({ className, variant, size, ...props }, ref) => ( + + + +

+ Não tem conta?{' '} + Cadastrar +

+
+ + ) +} diff --git a/frontend/src/pages/Auth/Register.tsx b/frontend/src/pages/Auth/Register.tsx new file mode 100644 index 0000000..75d5a64 --- /dev/null +++ b/frontend/src/pages/Auth/Register.tsx @@ -0,0 +1,63 @@ +import { useState } from 'react' +import { useNavigate, Link } from 'react-router-dom' +import { authApi } from '@/api/auth' +import { useAuthStore } from '@/store/authStore' +import { Button } from '@/components/ui/button' +import { Input } from '@/components/ui/input' + +export function Register() { + const navigate = useNavigate() + const setAuth = useAuthStore((s) => s.setAuth) + const [name, setName] = useState('') + const [email, setEmail] = useState('') + const [password, setPassword] = useState('') + const [loading, setLoading] = useState(false) + const [error, setError] = useState('') + + async function handleSubmit(e: React.FormEvent) { + e.preventDefault() + setLoading(true) + setError('') + try { + const { data } = await authApi.register(name, email, password) + setAuth(data.user, data.access_token, data.refresh_token) + navigate('/') + } catch { + setError('Erro ao criar conta. Tente novamente.') + } finally { + setLoading(false) + } + } + + return ( +
+
+
+
🎙
+

Criar conta

+
+
+ {error &&

{error}

} +
+ + setName(e.target.value)} required /> +
+
+ + setEmail(e.target.value)} required /> +
+
+ + setPassword(e.target.value)} required minLength={6} /> +
+ +
+

+ Já tem conta? Entrar +

+
+
+ ) +} diff --git a/frontend/src/pages/Evolution/index.tsx b/frontend/src/pages/Evolution/index.tsx new file mode 100644 index 0000000..c738ab5 --- /dev/null +++ b/frontend/src/pages/Evolution/index.tsx @@ -0,0 +1,101 @@ +import { useEffect, useState } from 'react' +import { Loader2, TrendingUp } from 'lucide-react' +import { meetingsApi } from '@/api/meetings' +import { useMeetingsStore } from '@/store/meetingsStore' +import { Layout } from '@/components/Layout' +import { Card, CardContent } from '@/components/ui/card' +import type { CommunicationData } from '@/types' +import { LineChart, Line, XAxis, YAxis, CartesianGrid, Tooltip, ResponsiveContainer } from 'recharts' + +interface ScorePoint { date: string; score: number; title: string } + +export function Evolution() { + const { meetings, fetchMeetings } = useMeetingsStore() + const [scores, setScores] = useState([]) + const [loading, setLoading] = useState(true) + + useEffect(() => { + async function load() { + await fetchMeetings() + const completed = meetings.filter((m) => m.status === 'completed').slice(0, 20) + const points: ScorePoint[] = [] + for (const m of completed) { + try { + const { data } = await meetingsApi.getAnalysis(m.id, 'communication') + const fb = data.content as CommunicationData + const score = fb?.overall_score + if (score !== undefined) { + points.push({ date: new Date(m.created_at).toLocaleDateString('pt-BR', { day: '2-digit', month: '2-digit' }), score, title: m.title || 'Sem título' }) + } + } catch { /* no communication yet */ } + } + setScores(points.reverse()) + setLoading(false) + } + load() + }, []) + + const avg = scores.length > 0 ? (scores.reduce((a, b) => a + b.score, 0) / scores.length).toFixed(1) : null + const latest = scores[scores.length - 1]?.score + const trend = scores.length >= 2 ? latest - scores[scores.length - 2].score : null + + return ( + +
+

Evolução pessoal

+ + {loading ? ( +
+ ) : scores.length === 0 ? ( +
+ +

Nenhuma análise disponível ainda.

+

Grave reuniões para ver sua evolução!

+
+ ) : ( + <> +
+ + +
{latest}/10
+

Score mais recente

+ {trend !== null && ( +

0 ? 'text-green-400' : trend < 0 ? 'text-red-400' : 'text-slate-400'}`}> + {trend > 0 ? `↑ +${trend.toFixed(1)}` : trend < 0 ? `↓ ${trend.toFixed(1)}` : '→ estável'} +

+ )} + + + + +
{avg}/10
+

Média geral

+

{scores.length} reuniões

+ + +
+ + + +

📈 Score ao longo do tempo

+ + + + + + [`${v}/10`, 'Score'] as [string, string]} + labelFormatter={(l, payload) => payload?.[0]?.payload?.title ?? l} + /> + + + + + + + )} +
+ + ) +} diff --git a/frontend/src/pages/History/index.tsx b/frontend/src/pages/History/index.tsx new file mode 100644 index 0000000..60243a8 --- /dev/null +++ b/frontend/src/pages/History/index.tsx @@ -0,0 +1,103 @@ +import { useEffect, useState } from 'react' +import { useNavigate } from 'react-router-dom' +import { Search, Trash2, Loader2, User } from 'lucide-react' +import { useMeetingsStore } from '@/store/meetingsStore' +import { meetingsApi } from '@/api/meetings' +import { useAuthStore } from '@/store/authStore' +import { Layout } from '@/components/Layout' +import { Card, CardContent } from '@/components/ui/card' +import { Input } from '@/components/ui/input' +import { StatusBadge } from '@/components/StatusBadge' +import { formatDateTimeBR } from '@/utils/format' + +export function History() { + const navigate = useNavigate() + const { meetings, loading, fetchMeetings, removeMeeting } = useMeetingsStore() + const authUser = useAuthStore((s) => s.user) + const [search, setSearch] = useState('') + + const isAdmin = authUser?.roles?.includes('maia.admin') ?? false + + useEffect(() => { fetchMeetings() }, [fetchMeetings]) + + const filtered = meetings.filter((m) => + (m.title || '').toLowerCase().includes(search.toLowerCase()) || + (isAdmin && (m.owner_name || m.owner_email || '').toLowerCase().includes(search.toLowerCase())) + ) + + async function handleDelete(e: React.MouseEvent, id: string) { + e.stopPropagation() + if (!confirm('Excluir esta reunião?')) return + try { + await meetingsApi.delete(id) + removeMeeting(id) + } catch { /* ignore */ } + } + + return ( + +
+
+

Histórico

+ {isAdmin && ( + + Admin — todas as reuniões + + )} +
+ +
+ + setSearch(e.target.value)} + /> +
+ + {loading ? ( +
+ ) : filtered.length === 0 ? ( +
+

Nenhuma reunião encontrada.

+
+ ) : ( +
+ {filtered.map((m) => ( + navigate(`/meetings/${m.id}`)}> + +
+

{m.title || 'Reunião sem título'}

+

{formatDateTimeBR(m.created_at)}

+ {isAdmin && (m.owner_name || m.owner_email) && ( +

+ + {m.owner_name || m.owner_email} + {m.owner_email && m.owner_name && ( + · {m.owner_email} + )} +

+ )} +
+
+ + {isAdmin && ( + + )} +
+ + + ))} +
+ )} +
+ + ) +} diff --git a/frontend/src/pages/Home/index.tsx b/frontend/src/pages/Home/index.tsx new file mode 100644 index 0000000..5fbc2c9 --- /dev/null +++ b/frontend/src/pages/Home/index.tsx @@ -0,0 +1,102 @@ +import { useEffect } from 'react' +import { useNavigate } from 'react-router-dom' +import { Mic, Upload, Clock, CheckCircle, AlertCircle, Loader2 } from 'lucide-react' +import { useMeetingsStore } from '@/store/meetingsStore' +import { useAuthStore } from '@/store/authStore' +import { Button } from '@/components/ui/button' +import { Card, CardContent } from '@/components/ui/card' +import { StatusBadge } from '@/components/StatusBadge' +import { Layout } from '@/components/Layout' +import { formatDistanceToNow } from '@/utils/format' + +export function Home() { + const navigate = useNavigate() + const user = useAuthStore((s) => s.user) + const { meetings, loading, fetchMeetings } = useMeetingsStore() + + useEffect(() => { fetchMeetings() }, [fetchMeetings]) + + const recent = meetings.slice(0, 5) + const processing = meetings.filter((m) => m.status === 'processing' || m.status === 'uploading') + + return ( + +
+ {/* Greeting */} +
+

Olá, {user?.name?.split(' ')[0]} 👋

+

O que faremos hoje?

+
+ + {/* Actions */} +
+ + +
+ + {/* Processing */} + {processing.length > 0 && ( +
+

+ Em processamento +

+
+ {processing.map((m) => ( + navigate(`/meetings/${m.id}`)}> + + {m.title || 'Reunião sem título'} + + + + ))} +
+
+ )} + + {/* Recent meetings */} +
+
+

Reuniões recentes

+ +
+ + {loading ? ( +
+ ) : recent.length === 0 ? ( + + + +

Nenhuma reunião ainda.

+

Grave ou envie seu primeiro áudio!

+ + + ) : ( +
+ {recent.map((m) => ( + navigate(`/meetings/${m.id}`)}> + +
+

{m.title || 'Reunião sem título'}

+

{formatDistanceToNow(m.created_at)}

+
+
+ {m.status === 'completed' && } + {m.status === 'error' && } + {(m.status === 'processing' || m.status === 'uploading') && } +
+ + + ))} +
+ )} +
+
+ + ) +} diff --git a/frontend/src/pages/MeetingDetail/index.tsx b/frontend/src/pages/MeetingDetail/index.tsx new file mode 100644 index 0000000..b251fb1 --- /dev/null +++ b/frontend/src/pages/MeetingDetail/index.tsx @@ -0,0 +1,522 @@ +import { useEffect, useState, useCallback, useRef } from 'react' +import { useParams, useNavigate } from 'react-router-dom' +import { ArrowLeft, Loader2, Edit2, Check, X, Play, Pause, Volume2 } from 'lucide-react' +import { meetingsApi } from '@/api/meetings' +import api from '@/api/axios' +import { useMeetingsStore } from '@/store/meetingsStore' +import { useWebSocket } from '@/hooks/useWebSocket' +import { Layout } from '@/components/Layout' +import { StatusBadge } from '@/components/StatusBadge' +import { Button } from '@/components/ui/button' +import { Input } from '@/components/ui/input' +import { Card, CardContent } from '@/components/ui/card' +import type { Meeting, TranscriptSegment, Minutes, SentimentData, PsychologicalData, CommunicationData, SummaryData } from '@/types' +import { BarChart, Bar, XAxis, YAxis, CartesianGrid, Tooltip, ResponsiveContainer } from 'recharts' + +type Tab = 'transcript' | 'minutes' | 'sentiment' | 'psychological' | 'communication' | 'summary' + +const SPEAKER_COLORS = ['#4ade80', '#60a5fa', '#f472b6', '#fb923c', '#a78bfa', '#34d399'] +const TERMINAL = ['completed', 'error'] + +export function MeetingDetail() { + const { id } = useParams<{ id: string }>() + const navigate = useNavigate() + const { meetings, updateMeeting } = useMeetingsStore() + const [meeting, setMeeting] = useState(meetings.find((m) => m.id === id) ?? null) + const [tab, setTab] = useState('transcript') + const [minutes, setMinutes] = useState(null) + const [sentiment, setSentiment] = useState(null) + const [psychological, setPsychological] = useState(null) + const [communication, setCommunication] = useState(null) + const [summary, setSummary] = useState(null) + const [loadingTab, setLoadingTab] = useState(false) + const [editingLabel, setEditingLabel] = useState(null) + const [editName, setEditName] = useState('') + const [audioUrl, setAudioUrl] = useState(null) + const [audioLoading, setAudioLoading] = useState(false) + const [isPlaying, setIsPlaying] = useState(false) + const audioRef = useRef(null) + + const [enrollNames, setEnrollNames] = useState>({}) + const [enrollingLabel, setEnrollingLabel] = useState(null) + const [enrollErrors, setEnrollErrors] = useState>({}) + const [enrollSuccess, setEnrollSuccess] = useState>({}) + + const isTerminal = TERMINAL.includes(meeting?.status ?? '') + + useEffect(() => { + if (!id) return + meetingsApi.get(id).then(({ data }) => { + setMeeting(data) + updateMeeting(id, data) + if (data.status === 'completed') setTab('transcript') + }) + }, [id, updateMeeting]) + + const onWsMessage = useCallback((data: unknown) => { + const msg = data as { type: string; status?: string; progress?: number } + if (msg.type === 'status_update' && msg.status) { + setMeeting((m) => m ? { ...m, status: msg.status as Meeting['status'], progress: msg.progress } : m) + } + }, []) + + useWebSocket(meeting?.status === 'processing' ? (id ?? null) : null, onWsMessage) + + useEffect(() => { + if (!id || isTerminal) return + const iv = setInterval(async () => { + try { + const { data } = await meetingsApi.get(id) + setMeeting(data) + updateMeeting(id, data) + if (TERMINAL.includes(data.status)) clearInterval(iv) + } catch { /* ignore */ } + }, 4000) + return () => clearInterval(iv) + }, [id, isTerminal, updateMeeting]) + + async function loadTab(t: Tab) { + setTab(t) + setLoadingTab(true) + try { + if (t === 'minutes' && !minutes) { + const { data } = await meetingsApi.getAnalysis(id!, 'minutes') + setMinutes(data.content as Minutes) + } else if (t === 'sentiment' && !sentiment) { + const { data } = await meetingsApi.getAnalysis(id!, 'sentiment') + setSentiment(data.content as SentimentData) + } else if (t === 'psychological' && !psychological) { + const { data } = await meetingsApi.getAnalysis(id!, 'psychological') + setPsychological(data.content as PsychologicalData) + } else if (t === 'communication' && !communication) { + const { data } = await meetingsApi.getAnalysis(id!, 'communication') + setCommunication(data.content as CommunicationData) + } else if (t === 'summary' && !summary) { + const { data } = await meetingsApi.getAnalysis(id!, 'summary') + setSummary(data.content as SummaryData) + } + } catch { /* analysis not ready */ } finally { + setLoadingTab(false) + } + } + + async function loadAudio() { + if (audioUrl) return + setAudioLoading(true) + try { + const resp = await api.get(`/meetings/${id}/audio`, { responseType: 'blob' }) + const url = URL.createObjectURL(resp.data) + setAudioUrl(url) + if (audioRef.current) audioRef.current.src = url + } catch { /* no audio */ } finally { + setAudioLoading(false) + } + } + + function togglePlay() { + if (!audioRef.current) return + if (isPlaying) { audioRef.current.pause(); setIsPlaying(false) } + else { audioRef.current.play(); setIsPlaying(true) } + } + + async function saveLabel(label: string) { + if (!id || !editName.trim()) return + await meetingsApi.relabelParticipant(id, label, editName.trim()) + setMeeting((m) => m ? { ...m } : m) + setEditingLabel(null) + } + + function getSpeakerColor(speaker: string): string { + const segs = meeting?.transcription?.segments ?? [] + const speakers = [...new Set(segs.map((s) => s.speaker))] + return SPEAKER_COLORS[speakers.indexOf(speaker) % SPEAKER_COLORS.length] + } + + const sentimentColor = (s?: string) => + s === 'positive' ? '#4ade80' : s === 'negative' ? '#f87171' : '#94a3b8' + + const tabs: { key: Tab; label: string }[] = [ + { key: 'transcript', label: 'Transcricao' }, + { key: 'summary', label: 'Resumo' }, + { key: 'minutes', label: 'Ata' }, + { key: 'sentiment', label: 'Sentimento' }, + { key: 'psychological', label: 'Perfil' }, + { key: 'communication', label: 'Comunicacao' }, + ] + + const segments: TranscriptSegment[] = meeting?.transcription?.segments ?? [] + const unidentifiedSpeakers = [...new Set(segments.filter(s => /^SPEAKER_\d+$/.test(s.speaker)).map(s => s.speaker))].sort() + + async function handleEnroll(label: string) { + const name = (enrollNames[label] || '').trim() + if (!name || !id) return + setEnrollingLabel(label) + setEnrollErrors(e => ({ ...e, [label]: '' })) + try { + await meetingsApi.enrollSpeaker(id, label, name) + setEnrollSuccess(s => ({ ...s, [label]: true })) + setMeeting(m => { + if (!m?.transcription?.segments) return m + return { + ...m, + transcription: { + ...m.transcription, + segments: m.transcription.segments.map((seg: TranscriptSegment) => + seg.speaker === label ? { ...seg, speaker: name } : seg + ), + }, + } + }) + } catch { + setEnrollErrors(e => ({ ...e, [label]: 'Erro ao salvar. Tente novamente.' })) + } finally { + setEnrollingLabel(null) + } + } + + return ( + +
+
+ +
+

{meeting?.title || 'Reuniao sem titulo'}

+ {meeting && } +
+
+ + {meeting?.status === 'completed' && ( + + + + {!audioUrl && !audioLoading && ( + + )} + {audioLoading && Carregando...} + {audioUrl && ( +
+ +
+ )} + + + )} + + {!isTerminal && meeting?.status !== undefined && ( + + + +

+ {meeting.status === 'receiving_chunks' && 'Recebendo audio...'} + {meeting.status === 'uploading' && 'Enviando para processamento...'} + {meeting.status === 'processing' && 'Iniciando processamento...'} + {meeting.status === 'transcribing' && 'Transcrevendo com Whisper...'} + {meeting.status === 'analyzing' && 'Analisando com IA...'} +

+

A pagina atualiza automaticamente

+ + + )} + + {meeting?.status === 'completed' && ( + <> + {unidentifiedSpeakers.length > 0 && ( + + +
+ 🎤 +
+

Identificar participantes

+

Para reconhecimento automático em reuniões futuras

+
+
+
+ {unidentifiedSpeakers.map(label => ( +
+ {label} + setEnrollNames(n => ({ ...n, [label]: e.target.value }))} + onKeyDown={e => e.key === 'Enter' && handleEnroll(label)} + placeholder="Nome da pessoa" + className="h-7 text-xs flex-1" + disabled={!!enrollSuccess[label]} + /> + +
+ ))} +
+ {Object.entries(enrollErrors).filter(([, v]) => v).map(([k, v]) => ( +

{k}: {v}

+ ))} + + + )} + +
+ {tabs.map((t) => ( + + ))} +
+ + {loadingTab &&
} + + {tab === 'transcript' && !loadingTab && ( +
+ {segments.length > 0 ? segments.map((seg, i) => ( +
+
+
+
+
+
+
+ {seg.speaker} + {Math.floor(seg.start / 60)}:{String(Math.floor(seg.start % 60)).padStart(2, '0')} + {editingLabel === seg.speaker ? ( +
+ setEditName(e.target.value)} className="h-5 px-1 text-xs w-24" /> + + +
+ ) : ( + + )} +
+

{seg.text}

+
+
+ )) :

Transcricao nao disponivel.

} +
+ )} + + {tab === 'summary' && !loadingTab && ( +
+ {summary ? ( + <> + {summary.summary &&

Resumo

{summary.summary}

} + {summary.key_points && summary.key_points.length > 0 && ( + +

Pontos-chave

+
    {summary.key_points.map((p, i) =>
  • •{p}
    • )}
+ + )} +
+ {summary.duration_minutes != null &&

{summary.duration_minutes}'

duracao

} + {summary.total_participants != null &&

{summary.total_participants}

participantes

} +
+ + ) :

Resumo nao disponivel.

} +
+ )} + + {tab === 'minutes' && !loadingTab && ( +
+ {minutes ? ( + <> + {minutes.agenda && minutes.agenda.length > 0 && ( +

Pauta

    {minutes.agenda.map((a, i) =>
  • {i+1}.{a}
    • )}
 + )} + {minutes.decisions && minutes.decisions.length > 0 && ( +

Decisoes

    {minutes.decisions.map((d, i) =>
  • •{d}
    • )}
 + )} + {minutes.action_items && minutes.action_items.length > 0 && ( +

Acoes

+
{minutes.action_items.map((a, i) => ( +
+

{a.description}

+ {a.responsible &&

→ {a.responsible}

} + {a.deadline && a.deadline !== 'A definir' &&

{a.deadline}

} +
+ ))}
+ + )} + {minutes.next_steps && minutes.next_steps.length > 0 && ( +

Proximos passos

    {minutes.next_steps.map((s, i) =>
  • →{s}
    • )}
 + )} + {minutes.open_points && minutes.open_points.length > 0 && ( +

Pontos em aberto

    {minutes.open_points.map((s, i) =>
  • •{s}
    • )}
 + )} + + ) :

Ata nao disponivel.

} +
+ )} + + {tab === 'sentiment' && !loadingTab && ( +
+ {sentiment ? ( + <> + {sentiment.overall_sentiment && ( + +
+
+

Sentimento geral

+

{sentiment.overall_sentiment}

+
+ + )} + {sentiment.participation_metrics && sentiment.participation_metrics.length > 0 && ( + +

Participacao

+ + + + + + [`${v}%`, 'Participacao']} /> + + + + + )} + {sentiment.participants_sentiment && sentiment.participants_sentiment.length > 0 && ( + +

Por participante

+
{sentiment.participants_sentiment.map((p, i) => ( +
+
+
+ {p.speaker} + ({p.sentiment}) +
+

{p.details}

+
+ ))}
+ + )} + {sentiment.timeline && sentiment.timeline.length > 0 && ( + +

Linha do tempo

+
{sentiment.timeline.map((t, i) => ( +
+ {t.time_range} +
+ {t.sentiment} + {t.notes &&

{t.notes}

} +
+
+ ))}
+ + )} + {sentiment.tension_moments && sentiment.tension_moments.length > 0 && ( +

Momentos de tensao

    {sentiment.tension_moments.map((t, i) =>
  • •{t}
    • )}
 + )} + {sentiment.consensus_moments && sentiment.consensus_moments.length > 0 && ( +

Momentos de consenso

    {sentiment.consensus_moments.map((t, i) =>
  • •{t}
    • )}
 + )} + + ) :

Analise de sentimento nao disponivel.

} +
+ )} + + {tab === 'psychological' && !loadingTab && ( +
+ {psychological ? ( + <> + {psychological.group_dynamics && ( +

Dinamica do grupo

{psychological.group_dynamics}

 + )} + {psychological.participants_profiles && psychological.participants_profiles.length > 0 && psychological.participants_profiles.map((p, i) => ( + +

{p.name || p.speaker}

+
+ {p.communication_style &&
Estilo de comunicacao:

{p.communication_style}

} + {p.leadership_tendencies &&
Lideranca:

{p.leadership_tendencies}

} + {p.power_dynamics_role &&
Papel na dinamica:

{p.power_dynamics_role}

} +
+ + ))} + {psychological.key_observations && psychological.key_observations.length > 0 && ( +

Observacoes

    {psychological.key_observations.map((o, i) =>
  • •{o}
    • )}
 + )} + + ) :

Perfil psicologico nao disponivel.

} +
+ )} + + {tab === 'communication' && !loadingTab && ( +
+ {communication ? ( + <> + {communication.overall_score != null && ( + +
{communication.overall_score}/10
+

Score de comunicacao

+ + )} + {communication.general_feedback && ( +

Feedback geral

{communication.general_feedback}

 + )} + {communication.dimensions && ( + +

Dimensoes

+
{Object.entries(communication.dimensions).map(([dim, val]) => ( +
+
+ {dim.replace(/_/g, ' ')} + {val.score}/10 +
+
+ {val.notes &&

{val.notes}

} +
+ ))}
+ + )} + {communication.strengths && communication.strengths.length > 0 && ( +

Pontos fortes

+
{communication.strengths.map((s, i) => ( +

{s.description}

{s.example &&

"{s.example}"

}
+ ))}
+ + )} + {communication.improvement_areas && communication.improvement_areas.length > 0 && ( +

Melhorias

+
{communication.improvement_areas.map((a, i) => ( +

{a.description}

{a.suggestion &&

→ {a.suggestion}

}
+ ))}
+ + )} + + ) :

Analise de comunicacao nao disponivel.

} +
+ )} + + )} + + {meeting?.status === 'error' && ( + + +

Erro ao processar reuniao

+ {meeting.error_message &&

{meeting.error_message}

} + + + + )} +
+ + ) +} diff --git a/frontend/src/pages/Participants/index.tsx b/frontend/src/pages/Participants/index.tsx new file mode 100644 index 0000000..d233876 --- /dev/null +++ b/frontend/src/pages/Participants/index.tsx @@ -0,0 +1,92 @@ +import { useEffect, useState } from 'react' +import { Plus, Trash2, Mic, Loader2 } from 'lucide-react' +import { participantsApi } from '@/api/participants' +import { Layout } from '@/components/Layout' +import { Card, CardContent } from '@/components/ui/card' +import { Button } from '@/components/ui/button' +import { Input } from '@/components/ui/input' +import type { Participant } from '@/types' + +export function Participants() { + const [participants, setParticipants] = useState([]) + const [loading, setLoading] = useState(true) + const [name, setName] = useState('') + const [email, setEmail] = useState('') + const [adding, setAdding] = useState(false) + const [showForm, setShowForm] = useState(false) + + useEffect(() => { + participantsApi.list().then(({ data }) => setParticipants(data)).finally(() => setLoading(false)) + }, []) + + async function handleAdd(e: React.FormEvent) { + e.preventDefault() + if (!name.trim()) return + setAdding(true) + try { + const { data } = await participantsApi.create(name.trim(), email || undefined) + setParticipants((p) => [...p, data]) + setName('') + setEmail('') + setShowForm(false) + } finally { setAdding(false) } + } + + async function handleDelete(id: string) { + if (!confirm('Excluir perfil vocal?')) return + await participantsApi.delete(id) + setParticipants((p) => p.filter((x) => x.id !== id)) + } + + return ( + +
+
+

Participantes

+ +
+ + {showForm && ( + + +
+ setName(e.target.value)} required /> + setEmail(e.target.value)} /> +
+ + +
+
+ + + )} + + {loading ? ( +
+ ) : participants.length === 0 ? ( +
+ +

Nenhum perfil vocal cadastrado.

+
+ ) : ( +
+ {participants.map((p) => ( + + +
+

{p.name}

+ {p.email &&

{p.email}

} +

{p.voice_enrolled ? ✓ Voz cadastrada : Voz não cadastrada}

+
+ + + + ))} +
+ )} +
+ + ) +} diff --git a/frontend/src/pages/Recording/index.tsx b/frontend/src/pages/Recording/index.tsx new file mode 100644 index 0000000..a10e274 --- /dev/null +++ b/frontend/src/pages/Recording/index.tsx @@ -0,0 +1,332 @@ +import { useState, useRef, useEffect, useCallback } from 'react' +import { useNavigate } from 'react-router-dom' +import { Mic, Square, Loader2, Wifi, WifiOff } from 'lucide-react' +import { meetingsApi } from '@/api/meetings' +import { db } from '@/services/db' +import { useWakeLock } from '@/hooks/useWakeLock' +import { cn } from '@/utils/cn' + +type RecordingStatus = 'idle' | 'recording' | 'finalizing' | 'error' + +function getSupportedMimeType(): string { + const types = ['audio/webm;codecs=opus', 'audio/webm', 'audio/ogg;codecs=opus', 'audio/mp4'] + for (const type of types) { + if (MediaRecorder.isTypeSupported(type)) return type + } + return '' +} + +const CHUNK_INTERVAL_MS = 30_000 + +export function Recording() { + const navigate = useNavigate() + const { acquire: acquireWakeLock, release: releaseWakeLock } = useWakeLock() + + const [status, setStatus] = useState('idle') + const [title, setTitle] = useState('') + const [elapsed, setElapsed] = useState(0) + const [chunkCount, setChunkCount] = useState(0) + const [uploadedCount, setUploadedCount] = useState(0) + const [isOnline, setIsOnline] = useState(navigator.onLine) + const [errorMsg, setErrorMsg] = useState('') + + const meetingIdRef = useRef(null) + const recorderRef = useRef(null) + const streamRef = useRef(null) + const chunkIndexRef = useRef(0) + const elapsedIntervalRef = useRef | null>(null) + const retryIntervalRef = useRef | null>(null) + const mimeTypeRef = useRef('') + + // VU meter + const [vuLevel, setVuLevel] = useState(0) // 0..1 + const audioCtxRef = useRef(null) + const analyserRef = useRef(null) + const vuRafRef = useRef(null) + + const startVU = (stream: MediaStream) => { + const ctx = new AudioContext() + const analyser = ctx.createAnalyser() + analyser.fftSize = 256 + ctx.createMediaStreamSource(stream).connect(analyser) + audioCtxRef.current = ctx + analyserRef.current = analyser + const buf = new Uint8Array(analyser.frequencyBinCount) + const tick = () => { + analyser.getByteTimeDomainData(buf) + // RMS + let sum = 0 + for (let i = 0; i < buf.length; i++) { + const v = (buf[i] - 128) / 128 + sum += v * v + } + setVuLevel(Math.min(1, Math.sqrt(sum / buf.length) * 6)) + vuRafRef.current = requestAnimationFrame(tick) + } + vuRafRef.current = requestAnimationFrame(tick) + } + + const stopVU = () => { + if (vuRafRef.current) cancelAnimationFrame(vuRafRef.current) + analyserRef.current?.disconnect() + audioCtxRef.current?.close() + audioCtxRef.current = null + analyserRef.current = null + setVuLevel(0) + } + + const retryPendingChunks = useCallback(async () => { + if (!navigator.onLine) return + try { + const pending = await db.getPendingChunks() + for (const chunk of pending) { + try { + await db.updateChunkStatus(chunk.id!, 'uploading') + await meetingsApi.uploadChunk(chunk.meetingId, chunk.chunkIndex, chunk.blob, chunk.mimeType) + await db.deleteChunk(chunk.id!) + setUploadedCount(c => c + 1) + } catch { + await db.updateChunkStatus(chunk.id!, 'pending') + } + } + } catch (e) { + console.warn('[Recording] retryPendingChunks error', e) + } + }, []) + + useEffect(() => { + const onOnline = () => { setIsOnline(true); retryPendingChunks() } + const onOffline = () => setIsOnline(false) + window.addEventListener('online', onOnline) + window.addEventListener('offline', onOffline) + return () => { + window.removeEventListener('online', onOnline) + window.removeEventListener('offline', onOffline) + } + }, [retryPendingChunks]) + + // On mount: resume any pending chunks from previous sessions + useEffect(() => { retryPendingChunks() }, [retryPendingChunks]) + + const uploadChunkNow = useCallback(async ( + meetingId: string, chunkIndex: number, blob: Blob, mimeType: string, dbId?: number + ) => { + try { + await meetingsApi.uploadChunk(meetingId, chunkIndex, blob, mimeType) + if (dbId != null && dbId >= 0) await db.deleteChunk(dbId) + setUploadedCount(c => c + 1) + } catch { + // Keep in IndexedDB for retry - already saved + } + }, []) + + const startRecording = async () => { + try { + setErrorMsg('') + // Request audio with quality constraints for transcription + const stream = await navigator.mediaDevices.getUserMedia({ + audio: { + echoCancellation: true, + noiseSuppression: true, + autoGainControl: true, + channelCount: 1, + } + }) + streamRef.current = stream + const mimeType = getSupportedMimeType() + mimeTypeRef.current = mimeType + + const meeting = await meetingsApi.startMeeting(title || undefined) + meetingIdRef.current = meeting.id + chunkIndexRef.current = 0 + setChunkCount(0) + setUploadedCount(0) + setElapsed(0) + + acquireWakeLock() + setStatus('recording') + startVU(stream) + + // Use timeslice: single continuous MediaRecorder session, no stop/start gaps + const recorder = new MediaRecorder(stream, mimeType ? { mimeType } : undefined) + recorderRef.current = recorder + + recorder.ondataavailable = async (e) => { + if (e.data.size === 0) return + const currentIndex = chunkIndexRef.current++ + const meetId = meetingIdRef.current! + setChunkCount(n => n + 1) + + const blob = new Blob([e.data], { type: mimeType }) + const dbId = await db.saveChunk({ + meetingId: meetId, chunkIndex: currentIndex, blob, mimeType, + status: 'pending', createdAt: Date.now() + }) + await uploadChunkNow(meetId, currentIndex, blob, mimeType, dbId) + } + + // Fire ondataavailable every CHUNK_INTERVAL_MS — no gaps, continuous stream + recorder.start(CHUNK_INTERVAL_MS) + + retryIntervalRef.current = setInterval(() => { retryPendingChunks() }, CHUNK_INTERVAL_MS) + elapsedIntervalRef.current = setInterval(() => { setElapsed(s => s + 1) }, 1000) + } catch (e: unknown) { + const msg = e instanceof Error ? e.message : 'Erro ao iniciar gravação' + setErrorMsg(msg) + setStatus('error') + } + } + + const stopRecording = async () => { + if (!meetingIdRef.current) return + setStatus('finalizing') + + if (retryIntervalRef.current) clearInterval(retryIntervalRef.current) + if (elapsedIntervalRef.current) clearInterval(elapsedIntervalRef.current) + stopVU() + + // Stop recorder — triggers final ondataavailable then onstop + await new Promise((resolve) => { + const rec = recorderRef.current + if (!rec || rec.state === 'inactive') { resolve(); return } + rec.onstop = () => resolve() + rec.stop() + }) + + streamRef.current?.getTracks().forEach(t => t.stop()) + releaseWakeLock() + + // Wait for pending IndexedDB chunks (max 60s) + const deadline = Date.now() + 60_000 + while (Date.now() < deadline) { + const pending = await db.getPendingChunks(meetingIdRef.current!) + if (pending.length === 0) break + await retryPendingChunks() + await new Promise(r => setTimeout(r, 2000)) + } + + try { + const meeting = await meetingsApi.finalizeMeeting(meetingIdRef.current!, title || undefined) + navigate(`/meetings/${meeting.id}`) + } catch (e: unknown) { + const msg = e instanceof Error ? e.message : 'Erro ao finalizar reunião' + setErrorMsg(`${msg}. Os segmentos estão salvos e serão reenviados.`) + setStatus('error') + } + } + + const formatTime = (secs: number) => { + const h = Math.floor(secs / 3600) + const m = Math.floor((secs % 3600) / 60) + const s = secs % 60 + return h > 0 + ? `${h}:${String(m).padStart(2, '0')}:${String(s).padStart(2, '0')}` + : `${String(m).padStart(2, '0')}:${String(s).padStart(2, '0')}` + } + + return ( +
+ {/* Online indicator */} +
+ {isOnline ? : } + {isOnline ? 'Online' : 'Sem internet — gravando localmente'} +
+ + {/* Title input */} + {status === 'idle' && ( + setTitle(e.target.value)} + className="w-full max-w-sm bg-slate-800 border border-slate-700 rounded-xl px-4 py-3 text-white placeholder-slate-500 text-center focus:outline-none focus:border-green-500" + /> + )} + + {/* Timer */} + {status === 'recording' && ( +
+
{formatTime(elapsed)}
+
+ Segmento {chunkCount + 1} • {uploadedCount} enviados + {!isOnline && • aguardando conexão} +
+
+ )} + + {/* Idle: start button */} + {status === 'idle' && ( + + )} + + {/* Recording: pulsing mic + VU + stop button */} + {status === 'recording' && ( +
+
+
+
+ +
+
+ + {/* VU meter — 12 bars */} +
+ {Array.from({ length: 12 }, (_, i) => { + const threshold = (i + 1) / 12 + const active = vuLevel >= threshold + const color = i < 8 ? 'bg-green-400' : i < 10 ? 'bg-yellow-400' : 'bg-red-500' + return ( +
+ ) + })} +
+ + +
+ )} + + {/* Finalizing */} + {status === 'finalizing' && ( +
+ +

Finalizando gravação…

+

Enviando segmentos pendentes

+
+ )} + + {/* Error */} + {status === 'error' && ( +
+

⚠️ {errorMsg}

+ +
+ )} +
+ ) +} diff --git a/frontend/src/pages/Settings/index.tsx b/frontend/src/pages/Settings/index.tsx new file mode 100644 index 0000000..9bf98ea --- /dev/null +++ b/frontend/src/pages/Settings/index.tsx @@ -0,0 +1,85 @@ +import { useState } from 'react' +import { useNavigate } from 'react-router-dom' +import { LogOut, Bell, Info } from 'lucide-react' +import { useAuthStore } from '@/store/authStore' +import { Layout } from '@/components/Layout' +import { Card, CardContent } from '@/components/ui/card' +import { Button } from '@/components/ui/button' + +export function Settings() { + const navigate = useNavigate() + const { user, logout } = useAuthStore() + const [notifGranted, setNotifGranted] = useState(Notification.permission === 'granted') + + async function requestNotifications() { + const result = await Notification.requestPermission() + setNotifGranted(result === 'granted') + } + + function handleLogout() { + logout() + navigate('/login') + } + + return ( + +
+

Configurações

+ + {/* Profile */} + + +

Conta

+

{user?.name}

+

{user?.email}

+ + + + {/* Notifications */} + + +
+ +
+

Notificações

+

{notifGranted ? 'Ativadas' : 'Desativadas'}

+
+
+ {!notifGranted && ( + + )} + {notifGranted && ✓} + + + + {/* PWA Install hint */} + + + +
+

Instalar como app

+

+ No Chrome: toque no menu ⋮ → "Adicionar à tela inicial". O app funcionará como nativo, mesmo sem internet. +

+
+ + + + {/* About */} + + + ASAP Telecom +
+

MAIA — Meeting AI Assistant

+

v1.0.0 — PWA · ASAP Telecom

+
+ + + + +
+ + ) +} diff --git a/frontend/src/pages/Upload/index.tsx b/frontend/src/pages/Upload/index.tsx new file mode 100644 index 0000000..6868539 --- /dev/null +++ b/frontend/src/pages/Upload/index.tsx @@ -0,0 +1,115 @@ +import { useRef, useState } from 'react' +import { useNavigate } from 'react-router-dom' +import { Upload as UploadIcon, FileAudio, X, Loader2 } from 'lucide-react' +import { Button } from '@/components/ui/button' +import { Input } from '@/components/ui/input' +import { Layout } from '@/components/Layout' +import { meetingsApi } from '@/api/meetings' +import { useMeetingsStore } from '@/store/meetingsStore' + +export function UploadPage() { + const navigate = useNavigate() + const addMeeting = useMeetingsStore((s) => s.addMeeting) + const [file, setFile] = useState(null) + const [title, setTitle] = useState('') + const [progress, setProgress] = useState(0) + const [uploading, setUploading] = useState(false) + const [error, setError] = useState('') + const [dragging, setDragging] = useState(false) + const inputRef = useRef(null) + + function handleFile(f: File) { + if (!f.type.startsWith('audio/') && !f.name.match(/\.(mp3|wav|m4a|ogg|webm|flac|aac)$/i)) { + setError('Formato não suportado. Use MP3, WAV, M4A, OGG, WEBM ou FLAC.') + return + } + setFile(f) + setError('') + } + + function onDrop(e: React.DragEvent) { + e.preventDefault() + setDragging(false) + const f = e.dataTransfer.files[0] + if (f) handleFile(f) + } + + async function handleUpload() { + if (!file) return + setUploading(true) + setError('') + try { + const { data } = await meetingsApi.upload(file, title || undefined, setProgress) + addMeeting(data) + navigate(`/meetings/${data.id}`) + } catch { + setError('Erro ao enviar o arquivo. Verifique sua conexão e tente novamente.') + setUploading(false) + } + } + + return ( + +
+
+

Enviar áudio

+

Envie uma gravação feita com seu app nativo (WhatsApp, Voice Recorder, etc.)

+
+ + {/* Drop zone */} +
inputRef.current?.click()} + onDrop={onDrop} + onDragOver={(e) => { e.preventDefault(); setDragging(true) }} + onDragLeave={() => setDragging(false)} + className={`border-2 border-dashed rounded-xl p-8 text-center cursor-pointer transition-colors ${dragging ? 'border-green-500 bg-green-950/20' : 'border-slate-600 hover:border-slate-500'}`} + > + {file ? ( +
+ +
+

{file.name}

+

{(file.size / 1024 / 1024).toFixed(1)} MB

+
+ +
+ ) : ( + <> + +

Toque para selecionar ou arraste o arquivo

+

MP3, WAV, M4A, OGG, WEBM, FLAC

+ + )} + { const f = e.target.files?.[0]; if (f) handleFile(f) }} /> +
+ + {file && ( +
+ + setTitle(e.target.value)} /> +
+ )} + + {error &&

{error}

} + + {uploading && ( +
+
+ Enviando... + {progress}% +
+
+
+
+
+ )} + + +
+ + ) +} diff --git a/frontend/src/services/db.ts b/frontend/src/services/db.ts new file mode 100644 index 0000000..4b0e129 --- /dev/null +++ b/frontend/src/services/db.ts @@ -0,0 +1,69 @@ +import { openDB, type IDBPDatabase } from 'idb' +import type { OfflineChunk } from '@/types' + +const DB_NAME = 'meeting-assistant' +const DB_VERSION = 2 + +let _db: IDBPDatabase | null = null + +export async function getDB() { + if (!_db) { + _db = await openDB(DB_NAME, DB_VERSION, { + upgrade(db, oldVersion) { + // v1: old 'chunks' store (may exist) + if (oldVersion < 2) { + if (!db.objectStoreNames.contains('pendingChunks')) { + const store = db.createObjectStore('pendingChunks', { keyPath: 'id', autoIncrement: true }) + store.createIndex('meetingId', 'meetingId') + store.createIndex('status', 'status') + } + } + }, + }) + } + return _db +} + +export async function saveChunk(chunk: Omit): Promise { + try { + const db = await getDB() + return db.add('pendingChunks', chunk) as Promise + } catch (e) { + console.warn('[db] saveChunk failed', e) + return -1 + } +} + +export async function getPendingChunks(meetingId?: string): Promise<(OfflineChunk & { id: number })[]> { + try { + const db = await getDB() + const all = await db.getAllFromIndex('pendingChunks', 'status', 'pending') as (OfflineChunk & { id: number })[] + if (meetingId) return all.filter(c => c.meetingId === meetingId) + return all + } catch (e) { + console.warn('[db] getPendingChunks failed', e) + return [] + } +} + +export async function updateChunkStatus(id: number, status: OfflineChunk['status']): Promise { + try { + const db = await getDB() + const chunk = await db.get('pendingChunks', id) + if (chunk) await db.put('pendingChunks', { ...chunk, status }) + } catch (e) { + console.warn('[db] updateChunkStatus failed', e) + } +} + +export async function deleteChunk(id: number): Promise { + try { + const db = await getDB() + await db.delete('pendingChunks', id) + } catch (e) { + console.warn('[db] deleteChunk failed', e) + } +} + +// Namespace export for convenience +export const db = { saveChunk, getPendingChunks, updateChunkStatus, deleteChunk } diff --git a/frontend/src/services/keycloak.ts b/frontend/src/services/keycloak.ts new file mode 100644 index 0000000..1cc7318 --- /dev/null +++ b/frontend/src/services/keycloak.ts @@ -0,0 +1,15 @@ +import Keycloak from 'keycloak-js' + +const keycloak = new Keycloak({ + url: 'https://auth.asaptelecom.com.br', + realm: 'one', + clientId: 'maia-app', +}) + +export default keycloak + +export const REQUIRED_ROLE = 'maia.app' + +export function hasRole(role: string): boolean { + return keycloak.hasRealmRole(role) +} diff --git a/frontend/src/store/authStore.ts b/frontend/src/store/authStore.ts new file mode 100644 index 0000000..02c3196 --- /dev/null +++ b/frontend/src/store/authStore.ts @@ -0,0 +1,34 @@ +import { create } from 'zustand' +import { persist } from 'zustand/middleware' +import type { User } from '@/types' + +interface AuthState { + user: User | null + accessToken: string | null + refreshToken: string | null + isAuthenticated: boolean + setAuth: (user: User, accessToken: string, refreshToken: string) => void + logout: () => void +} + +export const useAuthStore = create()( + persist( + (set) => ({ + user: null, + accessToken: null, + refreshToken: null, + isAuthenticated: false, + setAuth: (user, accessToken, refreshToken) => { + localStorage.setItem('access_token', accessToken) + localStorage.setItem('refresh_token', refreshToken) + set({ user, accessToken, refreshToken, isAuthenticated: true }) + }, + logout: () => { + localStorage.removeItem('access_token') + localStorage.removeItem('refresh_token') + set({ user: null, accessToken: null, refreshToken: null, isAuthenticated: false }) + }, + }), + { name: 'auth-storage', partialize: (s) => ({ user: s.user, accessToken: s.accessToken, refreshToken: s.refreshToken, isAuthenticated: s.isAuthenticated }) } + ) +) diff --git a/frontend/src/store/meetingsStore.ts b/frontend/src/store/meetingsStore.ts new file mode 100644 index 0000000..52d6b32 --- /dev/null +++ b/frontend/src/store/meetingsStore.ts @@ -0,0 +1,32 @@ +import { create } from 'zustand' +import type { Meeting } from '@/types' +import { meetingsApi } from '@/api/meetings' + +interface MeetingsState { + meetings: Meeting[] + loading: boolean + error: string | null + fetchMeetings: () => Promise + addMeeting: (m: Meeting) => void + updateMeeting: (id: string, updates: Partial) => void + removeMeeting: (id: string) => void +} + +export const useMeetingsStore = create((set) => ({ + meetings: [], + loading: false, + error: null, + fetchMeetings: async () => { + set({ loading: true, error: null }) + try { + const { data } = await meetingsApi.list() + set({ meetings: data, loading: false }) + } catch (e: unknown) { + set({ error: (e as Error).message, loading: false }) + } + }, + addMeeting: (m) => set((s) => ({ meetings: [m, ...s.meetings] })), + updateMeeting: (id, updates) => + set((s) => ({ meetings: s.meetings.map((m) => (m.id === id ? { ...m, ...updates } : m)) })), + removeMeeting: (id) => set((s) => ({ meetings: s.meetings.filter((m) => m.id !== id) })), +})) diff --git a/frontend/src/store/recordingStore.ts b/frontend/src/store/recordingStore.ts new file mode 100644 index 0000000..cf3798f --- /dev/null +++ b/frontend/src/store/recordingStore.ts @@ -0,0 +1,35 @@ +import { create } from 'zustand' + +type RecordingStatus = 'idle' | 'recording' | 'paused' | 'uploading' | 'done' | 'error' + +interface RecordingState { + status: RecordingStatus + meetingId: string | null + title: string + duration: number + chunksUploaded: number + isOffline: boolean + setStatus: (s: RecordingStatus) => void + setMeetingId: (id: string) => void + setTitle: (t: string) => void + incrementDuration: () => void + incrementChunks: () => void + setOffline: (v: boolean) => void + reset: () => void +} + +export const useRecordingStore = create((set) => ({ + status: 'idle', + meetingId: null, + title: '', + duration: 0, + chunksUploaded: 0, + isOffline: false, + setStatus: (status) => set({ status }), + setMeetingId: (meetingId) => set({ meetingId }), + setTitle: (title) => set({ title }), + incrementDuration: () => set((s) => ({ duration: s.duration + 1 })), + incrementChunks: () => set((s) => ({ chunksUploaded: s.chunksUploaded + 1 })), + setOffline: (isOffline) => set({ isOffline }), + reset: () => set({ status: 'idle', meetingId: null, title: '', duration: 0, chunksUploaded: 0, isOffline: false }), +})) diff --git a/frontend/src/types/index.ts b/frontend/src/types/index.ts new file mode 100644 index 0000000..f7e9365 --- /dev/null +++ b/frontend/src/types/index.ts @@ -0,0 +1,131 @@ +export interface User { + id: string + name: string + email: string + roles?: string[] +} + +export interface Meeting { + id: string + title: string + status: 'receiving_chunks' | 'uploading' | 'processing' | 'transcribing' | 'analyzing' | 'completed' | 'error' + progress?: number + duration?: number + created_at: string + updated_at?: string + date?: string + transcription?: Transcription + participants?: Speaker[] + error_message?: string + owner_email?: string + owner_name?: string +} + +export interface Speaker { + label: string + name?: string +} + +// Transcription from meeting.transcription field +export interface Transcription { + segments: TranscriptSegment[] + speakers_count?: number + audio_duration?: number + language?: string + full_text?: string + diarization_method?: string +} + +export interface TranscriptSegment { + start: number + end: number + speaker: string + text: string +} + +// Keep for backward compat +export type Transcript = Transcription + +export interface MeetingAnalysis { + type: string + content: unknown + created_at: string +} + +// Minutes — matches backend AnalysisType.minutes +export interface Minutes { + title?: string + participants?: { name: string; role?: string }[] + agenda?: string[] + decisions?: string[] + action_items?: { description: string; responsible?: string; deadline?: string }[] + next_steps?: string[] + open_points?: string[] +} + +// Summary — matches backend AnalysisType.summary +export interface SummaryData { + summary?: string + key_points?: string[] + duration_minutes?: number + total_participants?: number +} + +// Sentiment — matches backend AnalysisType.sentiment +export interface SentimentData { + overall_sentiment?: string + timeline?: { time_range: string; sentiment: string; notes: string }[] + participants_sentiment?: { speaker: string; sentiment: string; details: string }[] + tension_moments?: string[] + consensus_moments?: string[] + participation_metrics?: { speaker: string; talk_percentage: number; interventions_count: number }[] +} + +// Psychological — matches backend AnalysisType.psychological +export interface PsychologicalData { + participants_profiles?: { + speaker: string + name?: string + communication_style?: string + leadership_tendencies?: string + disengagement_signs?: string + power_dynamics_role?: string + }[] + group_dynamics?: string + key_observations?: string[] +} + +// Communication — matches backend AnalysisType.communication +export interface CommunicationData { + overall_score?: number + dimensions?: Record + strengths?: { description: string; example?: string }[] + improvement_areas?: { description: string; suggestion?: string }[] + general_feedback?: string +} + +// Backward compat alias used by Evolution page +export interface FeedbackData { + score?: number + summary?: string + strengths?: string[] + improvements?: string[] +} + +export interface Participant { + id: string + name: string + email?: string + voice_enrolled: boolean + created_at: string +} + +export interface OfflineChunk { + id?: number + meetingId: string + chunkIndex: number + blob: Blob + mimeType: string + status: 'pending' | 'uploading' | 'done' | 'error' + createdAt: number +} diff --git a/frontend/src/utils/cn.ts b/frontend/src/utils/cn.ts new file mode 100644 index 0000000..fed2fe9 --- /dev/null +++ b/frontend/src/utils/cn.ts @@ -0,0 +1,6 @@ +import { clsx, type ClassValue } from 'clsx' +import { twMerge } from 'tailwind-merge' + +export function cn(...inputs: ClassValue[]) { + return twMerge(clsx(inputs)) +} diff --git a/frontend/src/utils/format.ts b/frontend/src/utils/format.ts new file mode 100644 index 0000000..2cc2a9d --- /dev/null +++ b/frontend/src/utils/format.ts @@ -0,0 +1,39 @@ +const SAO_PAULO_TZ = 'America/Sao_Paulo' + +export function formatDistanceToNow(dateStr: string): string { + const date = new Date(dateStr) + const diff = Date.now() - date.getTime() + const minutes = Math.floor(diff / 60000) + if (minutes < 1) return 'agora mesmo' + if (minutes < 60) return `${minutes} min atrás` + const hours = Math.floor(minutes / 60) + if (hours < 24) return `${hours}h atrás` + const days = Math.floor(hours / 24) + if (days < 7) return `${days} dias atrás` + return formatDateBR(dateStr) +} + +export function formatDateBR(dateStr: string): string { + const date = new Date(dateStr) + return new Intl.DateTimeFormat('pt-BR', { + day: '2-digit', month: '2-digit', year: 'numeric', + timeZone: SAO_PAULO_TZ, + }).format(date) +} + +export function formatDateTimeBR(dateStr: string): string { + const date = new Date(dateStr) + return new Intl.DateTimeFormat('pt-BR', { + day: '2-digit', month: '2-digit', year: 'numeric', + hour: '2-digit', minute: '2-digit', + timeZone: SAO_PAULO_TZ, + }).format(date) +} + +export function formatDuration(seconds: number): string { + const h = Math.floor(seconds / 3600) + const m = Math.floor((seconds % 3600) / 60) + const s = seconds % 60 + if (h > 0) return `${h}:${String(m).padStart(2, '0')}:${String(s).padStart(2, '0')}` + return `${String(m).padStart(2, '0')}:${String(s).padStart(2, '0')}` +} diff --git a/frontend/tsconfig.app.json b/frontend/tsconfig.app.json new file mode 100644 index 0000000..a500981 --- /dev/null +++ b/frontend/tsconfig.app.json @@ -0,0 +1,29 @@ +{ + "compilerOptions": { + "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo", + "target": "es2023", + "lib": ["ES2023", "DOM", "DOM.Iterable"], + "module": "esnext", + "types": ["vite/client"], + "skipLibCheck": true, + + /* Bundler mode */ + "moduleResolution": "bundler", + "allowImportingTsExtensions": true, + "verbatimModuleSyntax": true, + "moduleDetection": "force", + "noEmit": true, + "jsx": "react-jsx", + + /* Linting */ + "noUnusedLocals": true, + "noUnusedParameters": true, + "erasableSyntaxOnly": true, + "noFallthroughCasesInSwitch": true, + "ignoreDeprecations": "6.0", + "baseUrl": ".", + "paths": { "@/*": ["./src/*"] } + }, + "include": ["src"] +} + diff --git a/frontend/tsconfig.json b/frontend/tsconfig.json new file mode 100644 index 0000000..1ffef60 --- /dev/null +++ b/frontend/tsconfig.json @@ -0,0 +1,7 @@ +{ + "files": [], + "references": [ + { "path": "./tsconfig.app.json" }, + { "path": "./tsconfig.node.json" } + ] +} diff --git a/frontend/tsconfig.node.json b/frontend/tsconfig.node.json new file mode 100644 index 0000000..d3c52ea --- /dev/null +++ b/frontend/tsconfig.node.json @@ -0,0 +1,24 @@ +{ + "compilerOptions": { + "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo", + "target": "es2023", + "lib": ["ES2023"], + "module": "esnext", + "types": ["node"], + "skipLibCheck": true, + + /* Bundler mode */ + "moduleResolution": "bundler", + "allowImportingTsExtensions": true, + "verbatimModuleSyntax": true, + "moduleDetection": "force", + "noEmit": true, + + /* Linting */ + "noUnusedLocals": true, + "noUnusedParameters": true, + "erasableSyntaxOnly": true, + "noFallthroughCasesInSwitch": true + }, + "include": ["vite.config.ts"] +} diff --git a/frontend/vite.config.ts b/frontend/vite.config.ts new file mode 100644 index 0000000..3bcce33 --- /dev/null +++ b/frontend/vite.config.ts @@ -0,0 +1,46 @@ +import { defineConfig } from 'vite' +import react from '@vitejs/plugin-react' +import tailwindcss from '@tailwindcss/vite' +import { VitePWA } from 'vite-plugin-pwa' +import path from 'path' + +export default defineConfig({ + plugins: [ + react(), + tailwindcss(), + VitePWA({ + registerType: 'autoUpdate', + includeAssets: ['favicon.ico', 'icons/*.png', 'images/*.png'], + manifest: { + name: 'MAIA', + short_name: 'MAIA', + description: 'Meeting AI Assistant — Gravação e análise inteligente de reuniões', + theme_color: '#2D6A4F', + background_color: '#0f172a', + display: 'standalone', + orientation: 'portrait', + start_url: '/', + icons: [ + { src: '/icons/icon-192.png', sizes: '192x192', type: 'image/png' }, + { src: '/icons/icon-512.png', sizes: '512x512', type: 'image/png', purpose: 'any maskable' }, + ], + }, + workbox: { + globPatterns: ['**/*.{js,css,html,ico,png,svg,woff2}'], + // Force clients to use new SW immediately on update + skipWaiting: true, + clientsClaim: true, + runtimeCaching: [ + { + urlPattern: /^https?:\/\/.*\/api\//, + handler: 'NetworkFirst', + options: { cacheName: 'api-cache', networkTimeoutSeconds: 10 }, + }, + ], + }, + }), + ], + resolve: { + alias: { '@': path.resolve(__dirname, './src') }, + }, +})