feat: Migrate to ultrathin monolith architecture

Consolidate 3 separate applications (reports-app, data-entry-app, telegram-bot) into a unified
architecture with single backend and frontend:

Backend Changes:
- Unified FastAPI backend at backend/ with modular structure
- Modules: reports, data_entry, telegram in backend/modules/
- Centralized config.py and main.py with all routers registered
- Single worker mode (--workers 1) for Telegram bot compatibility
- Shared Oracle connection pool and JWT authentication
- Unified requirements.txt and environment configuration

Frontend Changes:
- Single Vue.js SPA with module-based routing
- Unified frontend at src/ with modules in src/modules/{reports,data-entry}/
- Shared components and stores in src/shared/
- Error boundaries for module isolation
- Dual API proxy in Vite for module communication

Infrastructure:
- New unified startup scripts: start-prod.sh, start-test.sh, start-backend.sh
- Environment templates: .env.dev.example, .env.test.example, .env.prod.example
- Updated deployment scripts for Windows IIS
- Simplified SSH tunnel management

Documentation:
- Comprehensive CLAUDE.md with architecture overview
- Module-specific docs in docs/{data-entry,telegram}/
- Architecture decision records in docs/ARCHITECTURE-DECISIONS.md
- Deployment guides consolidated in deployment/windows/docs/

This migration reduces complexity, improves maintainability, and enables easier
deployment while maintaining all existing functionality.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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# Architecture Decision Records (ADR)
This document records important architectural decisions made during ROA2WEB development.
---
## ADR-001: Ultrathin Monolith Architecture (2025-12-24)
**Status:** Accepted
**Context:**
Originally designed as separate microservices (Reports, Data Entry, Telegram Bot as independent services).
**Decision:**
Consolidated into **ultrathin monolith** - single FastAPI application with modular structure.
**Consequences:**
- ✅ Single Windows service to manage
- ✅ Shared database connection pool
- ✅ Simpler deployment
- ✅ Lower memory usage
- ✅ Easier debugging
- ⚠️ Requires careful module isolation
**Implementation:**
- All modules under `backend/modules/`
- Single `ROA2WEB-Backend` service
- Module enable/disable via `.env` flags
---
## ADR-002: Single Worker Configuration (2025-12-29)
**Status:** Accepted
**Context:**
Telegram bot integration causes conflicts when multiple uvicorn workers run simultaneously. Each worker spawns its own bot instance, but Telegram API allows only ONE bot to poll for updates.
**Problem:**
```
telegram.error.Conflict: terminated by other getUpdates request
```
**Decision:**
**Always use `--workers 1` for the unified backend service.**
**Rationale:**
1. **Telegram Bot Requirement:** Single bot instance only
2. **SQLite Cache:** Multiple workers cause locking conflicts
3. **Performance:** Async I/O means single worker handles 100+ concurrent requests
4. **Resources:** Lower memory (~400 MB vs ~1.6 GB with 4 workers)
**Consequences:**
- ✅ Telegram bot works perfectly
- ✅ No SQLite cache conflicts
- ✅ Cache stats endpoint works (no 502 errors)
- ✅ Lower memory usage
- ✅ Same performance (I/O bound, not CPU bound)
- ⚠️ Cannot scale horizontally with multiple processes
**Implementation:**
- Configured in NSSM: `--workers 1`
- NOT configurable in `.env`
- Documented in `TELEGRAM-BOT-DEPLOYMENT.md`
**Alternatives Considered:**
- Separate bot service: More complexity, no significant benefit
- Redis pub/sub for bot: Over-engineering for current scale
**Performance Characteristics:**
- Concurrent users: 100+
- Requests per minute: 1000+
- Response time: 50-200ms (DB query time)
- Adequate for: 50-100 concurrent users
---
## ADR-003: IIS Sub-Application Deployment (2025-12-29)
**Status:** Accepted
**Context:**
Application deployed at `/roa2web` path on IIS, not at root.
**Decision:**
Use Vite `base: '/roa2web/'` and axios `baseURL: import.meta.env.BASE_URL + 'api'` for all frontend API calls.
**Consequences:**
- ✅ Works correctly on production sub-path
- ✅ Works correctly on development root path
- ⚠️ All axios instances must use BASE_URL
- ⚠️ Router must use base path
**Implementation:**
- `vite.config.js`: `base: process.env.NODE_ENV === 'production' ? '/roa2web/' : '/'`
- All `axios.create()`: `baseURL: import.meta.env.BASE_URL + 'api/...'`
- IIS `web.config`: Reverse proxy rules for `/api/*``localhost:8000`
---
## ADR-004: Pydantic v2 Migration (2025-12-29)
**Status:** In Progress
**Context:**
Pydantic v2 changed `schema_extra``json_schema_extra`.
**Decision:**
Update all models incrementally to use `json_schema_extra`.
**Implementation:**
-`backend/modules/reports/models/trial_balance.py` updated
-`backend/modules/data_entry/schemas/ocr.py` already correct
- ⚠️ Warning eliminated in logs
---
## ADR-005: Web.config as Static File (2025-12-29)
**Status:** Accepted
**Context:**
IIS requires `web.config` for URL rewrite rules, but it wasn't consistently deployed.
**Decision:**
1. Store canonical `web.config` in `deployment/windows/config/`
2. Create `Create-WebConfig.ps1` script for manual creation
3. Include in deployment package
**Consequences:**
- ✅ Consistent configuration across deployments
- ✅ Easy to recreate if deleted
- ✅ Version controlled
**Implementation:**
- Canonical: `deployment/windows/config/web.config`
- Deployed to: `C:\inetpub\wwwroot\roa2web\frontend\web.config`
- Creation script: `Create-WebConfig.ps1`
---
## Future Decisions to Document
### Pending Considerations
1. **Horizontal Scaling:**
- If needed: Load balancer + multiple app instances
- Alternative: Separate bot service to allow multiple workers
- Current decision: Single worker sufficient
2. **Cache Strategy:**
- Current: SQLite L2 cache + memory L1
- Alternative: Redis for distributed cache
- Decision: Keep SQLite for simplicity
3. **Database Connection Pool:**
- Current: Shared pool across all modules
- Sizing: 5-10 connections
- Per-module pools: Not needed yet
---
## Decision Process
When making architectural decisions:
1. **Document the context** - Why is this decision needed?
2. **List alternatives** - What other options exist?
3. **Explain rationale** - Why this option over others?
4. **Note consequences** - What are the trade-offs?
5. **Implementation details** - How is this implemented?
6. **Reference documentation** - Where to find more details?
---
**Last Updated:** 2025-12-29

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# 📊 ROA2WEB - SCHEMĂ GRAFICĂ ARHITECTURĂ
Această schemă prezintă arhitectura completă a aplicației ROA2WEB, incluzând frontend-ul Vue.js, backend-ul FastAPI, middleware-ul de autentificare și conexiunea la baza de date Oracle.
## 🏗️ **ARHITECTURA GENERALĂ**
```
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🌐 CLIENT │
└─────────────────┬───────────────────────────────────────────────────────────────┘
│ HTTP Requests
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🖥️ FRONTEND │
│ Vue.js 3 + PrimeVue + Vite │
│ Port: 5173 (dev) / 3000 (prod) │
│ │
│ 📁 Components: 📦 Stores (Pinia): │
│ • LoginView.vue • auth.js (JWT tokens) │
│ • DashboardView.vue • companies.js │
│ • InvoicesView.vue • dashboard.js │
│ • BankCashRegisterView.vue • invoices.js │
│ • treasury.js │
│ 🔧 Services: │
│ • api.js (Axios HTTP client) │
│ • JWT token management │
└─────────────────┬───────────────────────────────────────────────────────────────┘
│ API Calls (axios)
│ Authorization: Bearer <JWT>
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🚀 BACKEND API │
│ FastAPI + Uvicorn │
│ Port: 8000 │
│ │
│ 🛡️ MIDDLEWARE LAYER: │
│ ┌─────────────────────────────────────────────────────────────────────────┐ │
│ │ 1. CORSMiddleware (Frontend communication) │ │
│ │ 2. AuthenticationMiddleware (JWT validation) │ │
│ │ • Token extraction from Authorization header │ │
│ │ • JWT verification & user data injection │ │
│ │ • Rate limiting (5 req/5min per IP) │ │
│ │ • Security headers injection │ │
│ │ • Excluded paths: ["/", "/docs", "/health", "/api/auth/login"] │ │
│ └─────────────────────────────────────────────────────────────────────────┘ │
│ │
│ 🛤️ API ROUTES: │
│ • /api/auth/login (POST) - User authentication │
│ • /api/companies (GET) - Company list │
│ • /api/dashboard (GET) - Dashboard data │
│ • /api/invoices (GET) - Invoice reports │
│ • /api/treasury (GET) - Treasury/Bank data │
│ • /api/trial-balance (GET) - Trial Balance (Balanță de Verificare) │
│ • /health (GET) - Health check │
│ │
│ 📊 SERVICES (with caching): │
│ • invoice_service.py (@cached: invoices, schema) │
│ • dashboard_service.py (@cached: dashboard_summary, trends, etc.) │
│ • treasury_service.py (@cached: treasury, schema) │
│ │
│ ⚡ CACHE LAYER (Two-Tier): │
│ ┌─────────────────────────────────────────────────────────────────────────┐ │
│ │ L1 (Memory): Fast in-memory cache (LRU, max 1000 entries) │ │
│ │ L2 (SQLite): Persistent cache database (./cache_data/) │ │
│ │ │ │
│ │ Features: │ │
│ │ • Automatic TTL per cache type (schema: 24h, invoices: 10min, etc.) │ │
│ │ • Performance tracking & benchmarking │ │
│ │ • Per-user cache enable/disable │ │
│ │ • Event-based invalidation (optional) │ │
│ │ • Cache hit/miss metrics in response headers │ │
│ │ │ │
│ │ Usage: @cached(cache_type='...', key_params=['company', 'username']) │ │
│ └─────────────────────────────────────────────────────────────────────────┘ │
└─────────────────┬───────────────────────────────────────────────────────────────┘
│ Database Queries (on cache miss)
│ SSH Tunnel Required
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🔐 SSH TUNNEL LAYER │
│ ./ssh_tunnel.sh (Local port forwarding) │
│ Local: localhost:1526 ➜ Remote: oracle_server:1521 │
└─────────────────┬───────────────────────────────────────────────────────────────┘
│ Encrypted connection
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🏛️ ORACLE DATABASE │
│ Schema: CONTAFIN_ORACLE │
│ Port: 1521 (remote) / 1526 (local via tunnel) │
│ │
│ 📋 Main Tables/Views: │
│ • UTILIZATORI (Users) │
│ • V_NOM_FIRME (Companies) │
│ • VDEF_UTIL_FIRME (User-Company relations) │
│ • Financial data tables (invoices, payments, etc.) │
│ │
│ 🔧 Stored Procedures: │
│ • pack_drepturi.verificautilizator (Authentication) │
└─────────────────────────────────────────────────────────────────────────────────┘
```
## ⚡ **ARHITECTURA CACHE (TWO-TIER L1 + L2)**
```
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🔥 CACHE LAYER ARCHITECTURE │
└─────────────────────────────────────────────────────────────────────────────────┘
API Request (service method decorated with @cached)
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 1. Check if Cache Enabled (Global + Per-User) │
│ • Global setting: CACHE_ENABLED=True/False │
│ • Per-user setting: SQLite user_settings table │
└───┬─────────────────────────────────────────────────────────────────────────────┘
↓ (if disabled: query Oracle directly)
┌───▼─────────────────────────────────────────────────────────────────────────────┐
│ 2. Generate Cache Key │
│ • Pattern: {cache_type}:{param1}:{param2}:... │
│ • Example: "invoices:123:user1:2024-01" │
└───┬─────────────────────────────────────────────────────────────────────────────┘
┌───▼─────────────────────────────────────────────────────────────────────────────┐
│ 3. Try L1 (Memory Cache) │
│ • Python dict with TTL │
│ • LRU eviction (max 1000 entries) │
│ • ⚡ Ultra-fast (microseconds) │
│ └─→ HIT? Return value + track performance (L1) │
└───┬─────────────────────────────────────────────────────────────────────────────┘
↓ (if MISS)
┌───▼─────────────────────────────────────────────────────────────────────────────┐
│ 4. Try L2 (SQLite Cache) │
│ • Persistent database (./cache_data/roa2web_cache.db) │
│ • Indexed by key, company_id, cache_type │
│ • 🗄️ Slower than L1 but faster than Oracle │
│ └─→ HIT? Populate L1 + return value + track performance (L2) │
└───┬─────────────────────────────────────────────────────────────────────────────┘
↓ (if MISS)
┌───▼─────────────────────────────────────────────────────────────────────────────┐
│ 5. CACHE MISS - Query Oracle │
│ • Execute actual database query │
│ • Measure execution time (benchmark) │
│ • Store result in L1 + L2 │
│ • Track performance (cache miss) │
└─────────────────────────────────────────────────────────────────────────────────┘
📊 CACHE TYPES & TTL (Time To Live):
• schema: 24 hours (CACHE_TTL_SCHEMA=86400)
• companies: 30 min (CACHE_TTL_COMPANIES=1800)
• dashboard_summary: 30 min (CACHE_TTL_DASHBOARD_SUMMARY=1800)
• dashboard_trends: 30 min (CACHE_TTL_DASHBOARD_TRENDS=1800)
• invoices: 10 min (CACHE_TTL_INVOICES=600)
• invoices_summary: 15 min (CACHE_TTL_INVOICES_SUMMARY=900)
• treasury: 10 min (CACHE_TTL_TREASURY=600)
• trial_balance: 10 min (CACHE_TTL_TRIAL_BALANCE=600)
🔧 CACHE MANAGEMENT ENDPOINTS:
• GET /api/cache/stats - Cache statistics (hits, misses, performance)
• POST /api/cache/invalidate - Invalidate cache (all/company/type)
• GET /api/cache/user-settings - Get user cache settings
• POST /api/cache/user-settings - Enable/disable cache for user
📈 PERFORMANCE TRACKING:
Each cached request includes metadata:
• cache_hit: true/false (was result from cache?)
• cache_source: "L1" | "L2" | null (which cache tier?)
• response_time_ms: float (total response time)
• time_saved_ms: float (estimated time saved vs Oracle query)
```
## 🔄 **FLUX DE AUTENTIFICARE**
```
1. User Login (Frontend)
2. POST /api/auth/login (Backend)
3. Oracle Authentication via SSH Tunnel
• pack_drepturi.verificautilizator(username, password)
4. JWT Token Generation (Backend)
• Access Token (30 min)
• Refresh Token (7 days)
• User data + companies + permissions
5. Token Storage (Frontend - Pinia Store)
6. Subsequent API Requests
• Authorization: Bearer <token>
• AuthenticationMiddleware validation
• User data injection in request.state
```
## 🚦 **MIDDLEWARE AUTHENTICATION FLOW**
```
Incoming Request
┌─────────────────┐
│ Rate Limiting │ → 429 if exceeded (5 req/5min per IP)
└─────┬───────────┘
┌─────────────────┐
│ Path Exclusion │ → Skip auth for /docs, /health, /api/auth/login
└─────┬───────────┘
┌─────────────────┐
│ Token Extract │ → 401 if missing Authorization header
└─────┬───────────┘
┌─────────────────┐
│ JWT Validation │ → 401 if invalid/expired/malformed
└─────┬───────────┘
┌─────────────────┐
│ User Injection │ → request.state.user = CurrentUser
└─────┬───────────┘ → request.state.is_authenticated = True
↓ → request.state.token_data = TokenData
┌─────────────────┐
│ Security Headers│ → X-Content-Type-Options, X-Frame-Options
└─────┬───────────┘ → X-XSS-Protection, X-Process-Time
┌─────────────────┐
│ Route Handler │
└─────────────────┘
```
## 🗂️ **STRUCTURA DE FIȘIERE**
### Frontend (Vue.js)
```
frontend/
├── src/
│ ├── components/
│ │ ├── dashboard/
│ │ ├── layout/
│ │ ├── reports/
│ │ └── ui/
│ ├── stores/ (Pinia)
│ │ ├── auth.js
│ │ ├── companies.js
│ │ ├── dashboard.js
│ │ ├── invoices.js
│ │ └── treasury.js
│ ├── services/
│ │ └── api.js
│ ├── views/
│ │ ├── LoginView.vue
│ │ ├── DashboardView.vue
│ │ ├── InvoicesView.vue
│ │ └── BankCashRegisterView.vue
│ └── router/
└── tests/ (Playwright E2E)
```
### Backend (FastAPI)
```
backend/
├── app/
│ ├── main.py
│ ├── routers/
│ │ ├── auth.py
│ │ ├── companies.py
│ │ ├── dashboard.py
│ │ ├── invoices.py
│ │ └── treasury.py
│ ├── services/
│ │ ├── invoice_service.py
│ │ ├── dashboard_service.py
│ │ └── treasury_service.py
│ └── models/
└── shared/
├── auth/
│ ├── middleware.py
│ ├── jwt_handler.py
│ ├── auth_service.py
│ └── models.py
└── database/
└── oracle_pool.py
```
## 🔧 **TEHNOLOGII UTILIZATE**
### Frontend Stack
- **Vue.js 3** - Framework JavaScript reactiv
- **PrimeVue** - UI Component Library
- **Pinia** - State Management
- **Vite** - Build Tool & Dev Server
- **Axios** - HTTP Client
- **Vue Router** - Client-side routing
- **Chart.js** - Data visualization
- **Playwright** - E2E Testing
### Backend Stack
- **FastAPI** - Python Web Framework
- **Uvicorn** - ASGI Server
- **PyJWT** - JWT Token handling
- **cx_Oracle** - Oracle Database driver
- **Pydantic** - Data validation
- **Python-dotenv** - Environment variables
### Database & Infrastructure
- **Oracle Database** - Persistent data storage
- **SSH Tunnel** - Secure database connection (Linux/development)
- **Docker** - Containerization (Linux production)
- **Nginx** - Reverse proxy & static files (Linux production)
- **Windows Server + IIS** - Windows production deployment
- **NSSM** - Windows service manager
## 🪟 **ARHITECTURA WINDOWS SERVER/IIS**
### Deployment pe Windows Server
ROA2WEB poate fi deployment pe Windows Server folosind IIS și Windows Services, fără Docker:
```
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🌐 CLIENT │
└─────────────────┬───────────────────────────────────────────────────────────────┘
│ HTTP/HTTPS Requests
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🪟 IIS WEB SERVER │
│ Port: 80/443 (HTTPS with SSL certificate) │
│ │
│ 📁 Static Files Serving: 🔀 URL Rewrite Module: │
│ • Frontend (Vue.js build) • /api/* → Backend Service │
│ • web.config configuration • /* → index.html (SPA routing) │
│ • Compression & Caching • Application Request Routing (ARR) │
│ │
│ ⚙️ Application Pool: │
│ • ROA2WEB-AppPool (.NET not required) │
│ • Integrated pipeline mode │
└─────────────────┬───────────────────────────────────────────────────────────────┘
│ Reverse Proxy to Backend
│ http://localhost:8000/api/*
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🔧 WINDOWS SERVICE │
│ Service Name: ROA2WEB-Backend │
│ Manager: NSSM (Non-Sucking Service Manager) │
│ Port: 8000 (localhost only) │
│ │
│ 📊 Backend Components: │
│ • FastAPI + Uvicorn (Python 3.11+) │
│ • Auto-start on Windows boot │
│ • Auto-restart on failure (5 sec delay) │
│ • Logging to file (stdout/stderr) │
│ │
│ 📁 Installation Location: │
│ • C:\inetpub\wwwroot\roa2web\backend\ │
└─────────────────┬───────────────────────────────────────────────────────────────┘
│ Direct Database Connection
│ No SSH Tunnel Required
┌─────────────────────────────────────────────────────────────────────────────────┐
│ 🏛️ ORACLE DATABASE (Local/Network) │
│ Connection: Direct TCP/IP (localhost:1521 or network) │
│ Schema: CONTAFIN_ORACLE │
│ │
│ 📋 Same Tables/Views as Linux deployment │
│ 🔧 Same Stored Procedures │
└─────────────────────────────────────────────────────────────────────────────────┘
```
### Diferențe între Linux și Windows Deployment
| Aspect | Linux (Docker) | Windows (IIS) |
|--------|----------------|---------------|
| **Web Server** | Nginx (container) | IIS (native) |
| **Backend Runtime** | Docker container | Windows Service (NSSM) |
| **Database Access** | SSH Tunnel required | Direct connection |
| **SSL/TLS** | Let's Encrypt (certbot) | IIS SSL certificates |
| **Service Management** | Docker Compose | PowerShell + Services.msc |
| **Deployment** | `./scripts/deploy.sh` | `Deploy-ROA2WEB.ps1` |
| **Logs** | Docker logs | Windows Event Log + Files |
| **Auto-start** | Docker restart policies | Windows Service auto-start |
### Structura Fișiere Windows Deployment
```
C:\inetpub\wwwroot\roa2web\
├── backend\ # FastAPI application
│ ├── app\
│ │ ├── main.py
│ │ ├── routers\
│ │ ├── services\
│ │ └── models\
│ ├── shared\ # Shared components
│ │ ├── auth\
│ │ ├── database\
│ │ └── utils\
│ ├── requirements.txt
│ ├── .env # Production config
│ └── logs\
├── frontend\ # Vue.js build output
│ ├── index.html
│ ├── assets\
│ ├── web.config # IIS configuration
│ └── ...
├── logs\ # Service logs
│ ├── backend-stdout.log
│ └── backend-stderr.log
└── backups\ # Deployment backups
└── backup-YYYYMMDD-HHMMSS\
```
### Comenzi Windows Deployment
```powershell
# Instalare inițială
.\Install-ROA2WEB.ps1
# Deployment actualizări
.\Deploy-ROA2WEB.ps1 -SourcePath "C:\path\to\deploy-package"
# Management serviciu
.\Start-ROA2WEB.ps1
.\Stop-ROA2WEB.ps1
.\Restart-ROA2WEB.ps1
# Verificare status
Get-Service ROA2WEB-Backend
Get-Website ROA2WEB
# Logs
Get-Content C:\inetpub\wwwroot\roa2web\logs\backend-stdout.log -Tail 50 -Wait
```
Pentru detalii complete despre deployment pe Windows, consultați:
- `/deployment/windows/docs/WINDOWS_DEPLOYMENT.md`
- `/deployment/windows/README.md`
## ⚙️ **COMENZI DE DEZVOLTARE**
### Start SSH Tunnel
```bash
cd /mnt/d/PROIECTE/roa-flask/roa2web
./ssh_tunnel.sh start
```
### Backend Development
```bash
cd reports-app/backend/
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
```
### Frontend Development
```bash
cd reports-app/frontend/
npm install
npm run dev
```
### Testing
```bash
cd shared/
python -m pytest -v
```
## 🛡️ **SECURITATE**
### Middleware de Autentificare
- **JWT Token Validation** - Verificare automată pentru toate endpoint-urile protejate
- **Rate Limiting** - Protecție împotriva atacurilor brute force
- **Security Headers** - X-Content-Type-Options, X-Frame-Options, X-XSS-Protection
- **CORS Protection** - Configurare restrictivă pentru frontend-uri autorizate
### Baza de Date
- **SSH Tunnel** - Conexiune criptată la Oracle
- **Schema Dedicată** - CONTAFIN_ORACLE pentru izolare
- **Stored Procedures** - Validare securizată de utilizatori
---
*Această schemă oferă o vedere de ansamblu asupra arhitecturii ROA2WEB și poate fi utilizată pentru documentare, onboarding și planificarea dezvoltării viitoare.*

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# ROA2WEB Docker Setup Guide
This guide covers how to set up and run ROA2WEB using Docker and Docker Compose for both development and production environments.
## 📋 Prerequisites
- Docker (20.10+)
- Docker Compose (2.0+)
- Git
- 4GB+ available RAM
- 10GB+ available disk space
### Windows/WSL2 Users
- WSL2 with Ubuntu/Debian
- Docker Desktop for Windows with WSL2 backend
## 🚀 Quick Start (Development)
### 1. Clone and Setup Environment
```bash
cd
cp .env.development .env
```
### 2. Configure Database Connection
Edit `.env` file with your Oracle database credentials:
```env
ORACLE_USER=CONTAFIN_ORACLE
ORACLE_PASSWORD=your_password_here
ORACLE_HOST=localhost # via SSH tunnel
ORACLE_PORT=1521
ORACLE_SID=ROA
```
### 3. Start SSH Tunnel (if needed)
```bash
./ssh_tunnel.sh start
```
### 4. Build and Start Services
```bash
# Build images and start services
docker-compose up --build
# Or run in background
docker-compose up -d --build
```
### 5. Access the Application
- **Frontend**: http://localhost:8080 (via Nginx Gateway)
- **Backend API**: http://localhost:8000 (direct access)
- **Frontend Direct**: http://localhost:3000 (direct access)
- **Redis**: http://localhost:6379 (direct access)
### 6. View Logs
```bash
# All services
docker-compose logs -f
# Specific service
docker-compose logs -f roa-backend
docker-compose logs -f roa-frontend
docker-compose logs -f roa-gateway
```
## 🏭 Production Deployment
### 1. Prepare Production Environment
```bash
# Copy production template
cp .env.production .env.production.local
# Edit with your production values
nano .env.production.local
```
### 2. Create Production Secrets
```bash
# Create secrets directory
mkdir -p secrets/
# Add your production secrets
echo "your_oracle_password" > secrets/oracle_password.txt
echo "your_jwt_secret_key" > secrets/jwt_secret_key.txt
echo "your_redis_password" > secrets/redis_password.txt
# Secure the secrets
chmod 600 secrets/*.txt
```
### 3. Configure SSL Domain
Update `.env.production.local`:
```env
DOMAIN=your-domain.com
SSL_EMAIL=admin@your-domain.com
```
### 4. Deploy to Production
```bash
# Using deployment script (recommended)
./scripts/deploy.sh
# Or manually
docker-compose -f docker-compose.yml -f docker-compose.production.yml up -d --build
```
### 5. Verify Deployment
```bash
# Check services health
./scripts/health-check.sh
# Check individual services
curl http://localhost/health
curl http://localhost/api/health
```
## 🛠️ Development Workflow
### Hot Reload Development
The development setup includes hot reload for both frontend and backend:
```bash
# Start with override (development config)
docker-compose up
# Backend code changes in reports-app/backend/app/ are reflected immediately
# Frontend code changes in reports-app/frontend/src/ trigger rebuild
```
### Database Changes
```bash
# Restart backend after database schema changes
docker-compose restart roa-backend
# View backend logs
docker-compose logs -f roa-backend
```
### Frontend Development
```bash
# Rebuild frontend after package changes
docker-compose build roa-frontend
docker-compose up -d roa-frontend
# Access frontend directly for debugging
# http://localhost:3000
```
## 📊 Monitoring and Maintenance
### Health Checks
```bash
# Comprehensive health check
./scripts/health-check.sh full
# Quick service check
./scripts/health-check.sh quick
# Continuous monitoring
./scripts/health-check.sh watch
```
### Backup and Restore
```bash
# Full backup
./scripts/backup.sh full
# Database only
./scripts/backup.sh database
# List backups
./scripts/backup.sh list
# Restore from backup
./scripts/backup.sh restore backup_20240131_143022
```
### Log Management
```bash
# View real-time logs
docker-compose logs -f
# View logs with timestamps
docker-compose logs -t
# Export logs
docker-compose logs > roa2web_logs_$(date +%Y%m%d).log
```
## 🔧 Troubleshooting
### Common Issues
#### 1. Port Already in Use
```bash
# Check what's using the port
sudo netstat -tlnp | grep :8080
# Stop the conflicting service or change ports in docker-compose.override.yml
```
#### 2. Database Connection Failed
```bash
# Check SSH tunnel status
./ssh_tunnel.sh status
# Restart SSH tunnel
./ssh_tunnel.sh restart
# Test database connection
docker-compose exec roa-backend python -c "from shared.database.oracle_pool import test_connection; test_connection()"
```
#### 3. Frontend Build Errors
```bash
# Clear node_modules and rebuild
docker-compose build --no-cache roa-frontend
# Check frontend logs
docker-compose logs roa-frontend
```
#### 4. SSL Certificate Issues (Production)
```bash
# Generate test certificates
docker-compose exec roa-gateway /usr/local/bin/ssl-renew.sh
# Check certificate status
docker-compose exec roa-gateway openssl x509 -in /etc/letsencrypt/live/your-domain.com/cert.pem -text -noout
```
### Service Recovery
#### Quick Recovery
```bash
# Restart all services
docker-compose restart
# Rollback to previous version
./scripts/rollback.sh quick
```
#### Full Recovery
```bash
# Stop everything
docker-compose down
# Clean up
docker system prune -f
# Restart fresh
docker-compose up -d --build
```
### Performance Tuning
#### Development
```bash
# Allocate more memory to Docker
# Docker Desktop: Settings > Resources > Memory (recommend 4GB+)
# Disable unnecessary services in development
# Comment out services in docker-compose.override.yml
```
#### Production
```bash
# Monitor resource usage
docker stats
# Scale services
docker-compose -f docker-compose.yml -f docker-compose.production.yml up -d --scale roa-backend=2
# Optimize images
docker image prune -f
docker volume prune -f
```
## 🔒 Security
### Development Security
- Never commit actual credentials to version control
- Use `.env` files that are gitignored
- SSH tunnel provides secure database access
### Production Security
- Use Docker secrets for sensitive data
- Enable SSL/TLS with valid certificates
- Regular security updates
- Monitor logs for suspicious activity
```bash
# Update base images
docker-compose pull
docker-compose up -d --build
# Security scan
docker scout cves backend:latest
```
## 📚 Advanced Configuration
### Custom Nginx Configuration
Edit `nginx/conf/sites-enabled/roa2web.conf` for custom routing:
```nginx
# Add custom location
location /custom-api/ {
proxy_pass http://custom-service:3000/;
proxy_set_header Host $host;
}
```
### Environment-Specific Overrides
Create custom compose files:
```yaml
# docker-compose.staging.yml
version: '3.8'
services:
roa-backend:
environment:
- DEBUG=false
- LOG_LEVEL=INFO
```
### Adding New Services
```yaml
# Add to docker-compose.yml
services:
new-service:
build: ./new-service
networks:
- roa-network
depends_on:
- roa-backend
```
## 📞 Support
### Getting Help
1. Check logs: `docker-compose logs`
2. Run health check: `./scripts/health-check.sh`
3. Review this documentation
4. Check GitHub issues
5. Contact the development team
### Useful Commands Reference
```bash
# Quick commands
docker-compose up -d # Start services in background
docker-compose down # Stop and remove containers
docker-compose ps # Show running services
docker-compose exec roa-backend sh # Access backend container
# Maintenance
docker system df # Show Docker disk usage
docker system prune -f # Clean up unused resources
docker-compose pull # Update base images
docker-compose build --no-cache # Rebuild without cache
```
---
*Last updated: $(date +%Y-%m-%d)*
*ROA2WEB Docker Setup Guide v1.0*

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@@ -1,234 +0,0 @@
# ROA2WEB Microservices Guide
🚀 **Ghid pentru Adăugarea de Module Noi în Ecosistemul ROA2WEB**
## 📋 Conceptul Microserviciilor
ROA2WEB folosește o arhitectură microservicii care permite adăugarea ușoară de module noi fără a afecta funcționalitatea existentă.
### 🏗️ Structura unui Microserviciu
```
new-app/
├── backend/ # FastAPI Backend
│ ├── app/
│ │ ├── main.py # Entry point
│ │ ├── models/ # Pydantic models
│ │ ├── routers/ # API endpoints
│ │ ├── services/ # Business logic
│ │ └── schemas/ # Response schemas
│ ├── requirements.txt
│ ├── Dockerfile
│ └── .env.example
├── frontend/ # Vue.js Frontend (opțional)
│ ├── src/
│ │ ├── main.js
│ │ ├── App.vue
│ │ ├── router/
│ │ ├── stores/
│ │ ├── views/
│ │ └── components/
│ ├── package.json
│ ├── vite.config.js
│ └── Dockerfile
└── README.md
```
## 🔧 Shared Components
Toate microserviciile folosesc componentele comune din directorul `shared/`:
### Database Pool
```python
from shared.database.oracle_pool import oracle_pool
async with oracle_pool.get_connection() as conn:
# Database operations
```
### Authentication
```python
from shared.auth.jwt_handler import jwt_handler
from shared.auth.middleware import require_auth
@require_auth
async def protected_endpoint():
# Protected logic
```
## 🚀 Pași pentru Adăugare Microserviciu Nou
### 1. Creare Structură
```bash
mkdir -p new-app/{backend/app/{models,routers,services,schemas},frontend/src/{router,stores,views,components}}
```
### 2. Backend Setup
**`new-app/backend/app/main.py`**:
```python
from fastapi import FastAPI
import sys
import os
# Add shared path
sys.path.append(os.path.join(os.path.dirname(__file__), '../../../shared'))
from database.oracle_pool import oracle_pool
from auth.jwt_handler import jwt_handler
app = FastAPI(title="New App API")
@app.on_event("startup")
async def startup():
await oracle_pool.initialize()
@app.on_event("shutdown")
async def shutdown():
await oracle_pool.close_pool()
```
### 3. Frontend Setup (Opțional)
Dacă microserviciul necesită UI:
**`new-app/frontend/package.json`**:
```json
{
"name": "new-app-frontend",
"version": "1.0.0",
"scripts": {
"dev": "vite",
"build": "vite build"
},
"dependencies": {
"vue": "^3.3.0",
"primevue": "^3.0.0",
"pinia": "^2.0.0"
}
}
```
### 4. Docker Configuration
**`new-app/backend/Dockerfile`**:
```dockerfile
FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]
```
### 5. Nginx Routing
Adaugă în `nginx/nginx.conf`:
```nginx
location /new-app/ {
proxy_pass http://new-app-backend:8000/;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
}
```
### 6. Docker Compose Integration
Adaugă în `docker-compose.yml`:
```yaml
services:
new-app-backend:
build: ./new-app/backend
networks:
- roa-network
environment:
- ORACLE_USER=${ORACLE_USER}
- ORACLE_PASSWORD=${ORACLE_PASSWORD}
- ORACLE_DSN=${ORACLE_DSN}
```
## 📊 Exemple de Microservicii
### 1. Invoicing App
- Gestionare facturi
- Generare PDF
- Email notifications
### 2. Inventory App
- Gestiune stocuri
- Mișcări de marfă
- Rapoarte inventar
### 3. CRM App
- Gestionare clienți
- Istoric interacțiuni
- Pipeline vânzări
## 🔐 Securitate
### Autentificare
Toate microserviciile folosesc JWT tokens din `shared/auth/`.
### Autorizare
Implementează middleware pentru verificarea permisiunilor per modul.
### Database Access
Folosește doar `shared/database/oracle_pool.py` pentru acces la baza de date.
## 📋 Best Practices
### 1. Naming Convention
- **Directoare**: `kebab-case` (ex: `invoicing-app`)
- **API Endpoints**: `/api/v1/resource`
- **Database**: Schema separată per modul
### 2. Error Handling
```python
from shared.utils.exceptions import ROAException
@app.exception_handler(ROAException)
async def roa_exception_handler(request, exc):
return {"error": str(exc)}
```
### 3. Logging
```python
import logging
logger = logging.getLogger(f"roa.{__name__}")
```
### 4. Testing
```bash
# Unit tests
pytest new-app/backend/tests/
# Integration tests
pytest tests/integration/test_new_app.py
```
## 🔄 Deployment
### Development
```bash
docker-compose up new-app-backend new-app-frontend
```
### Production
Folosește orchestratoare precum Kubernetes pentru scalare automată.
## 📞 Support
Pentru întrebări despre dezvoltarea de microservicii:
1. Consultă documentația shared components
2. Urmărește pattern-urile din `reports-app/`
3. Testează integrarea cu componentele comune
---
*Arhitectura microservicii permite creșterea organică a platformei ROA2WEB* 🚀

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@@ -0,0 +1,564 @@
# ROA2WEB Ultrathin Monolith Architecture
**Version:** 1.0.0
**Last Updated:** 2025-12-29
**Status:** ✅ Active
---
## 🎯 Overview
ROA2WEB uses an **ultrathin monolith** architecture - a single unified backend and frontend application with modular organization. This architecture provides the simplicity of a monolith with the organizational benefits of microservices.
### Key Characteristics
- **Single Backend Process**: One FastAPI application serving all modules
- **Single Frontend Build**: One Vue.js SPA with lazy-loaded modules
- **Modular Organization**: Business logic separated into distinct modules
- **Shared Resources**: Database pools, auth, cache shared across modules
- **Independent Modules**: Each module can be developed and tested independently
---
## 🏗️ Architecture Diagram
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ 🌐 CLIENT BROWSER │
└────────────────────────────────┬────────────────────────────────────────────┘
│ HTTP/HTTPS Requests
┌─────────────────────────────────────────────────────────────────────────────┐
│ 📦 UNIFIED VUE.JS FRONTEND │
│ Single-page application (SPA) served from /dist │
│ Port: 3000 (dev) / 80,443 (production) │
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ Frontend Modules (Lazy Loaded) │ │
│ │ │ │
│ │ • src/modules/reports/ - Reports module UI │ │
│ │ • src/modules/data-entry/ - Data entry module UI │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ Shared Frontend Components │ │
│ │ │ │
│ │ • src/shared/components/ - Reusable Vue components │ │
│ │ • src/shared/stores/ - Pinia stores │ │
│ │ • src/assets/css/ - Global CSS system │ │
│ │ • shared/frontend/ - Login, auth components │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
└────────────────────────────────┬────────────────────────────────────────────┘
│ API Calls (Axios)
│ Authorization: Bearer <JWT>
┌─────────────────────────────────────────────────────────────────────────────┐
│ 🚀 UNIFIED FASTAPI BACKEND │
│ Single Python process running all modules │
│ Port: 8000 (dev) / 8001 (production) │
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ 🛡️ Global Middleware Layer │ │
│ │ │ │
│ │ • CORSMiddleware - CORS handling │ │
│ │ • AuthenticationMiddleware - JWT validation & user injection │ │
│ │ • Rate Limiting - 5 req/5 min per IP │ │
│ │ • Security Headers - XSS, CSP, Frame protection │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ 📊 Backend Modules (backend/modules/) │ │
│ │ │ │
│ │ reports/ │ │
│ │ ├── routers/ - API endpoints │ │
│ │ ├── services/ - Business logic with caching │ │
│ │ ├── models/ - Pydantic models │ │
│ │ └── cache/ - L1+L2 cache implementation │ │
│ │ │ │
│ │ data_entry/ │ │
│ │ ├── routers/ - API endpoints │ │
│ │ ├── services/ - Business logic │ │
│ │ ├── models/ - SQLModel ORM models │ │
│ │ └── db/ - SQLite database │ │
│ │ │ │
│ │ telegram/ │ │
│ │ ├── bot/ - Telegram bot handlers │ │
│ │ ├── api/ - Internal API for bot │ │
│ │ └── db/ - Bot session management │ │
│ │ │ │
│ │ data/ │ │
│ │ └── telegram_bot.db - Telegram bot SQLite database │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
│ │
│ ┌─────────────────────────────────────────────────────────────────────┐ │
│ │ 🔧 Shared Backend Components (shared/) │ │
│ │ │ │
│ │ database/ │ │
│ │ └── oracle_pool.py - Singleton Oracle connection pool │ │
│ │ │ │
│ │ auth/ │ │
│ │ ├── middleware.py - JWT authentication middleware │ │
│ │ ├── jwt_handler.py - Token creation/validation │ │
│ │ └── models.py - Auth data models │ │
│ │ │ │
│ └─────────────────────────────────────────────────────────────────────┘ │
└────────────────────────────────┬────────────────────────────────────────────┘
│ Database Queries
│ (Oracle + SQLite)
┌─────────────────────────────────────────────────────────────────────────────┐
│ 🗄️ DATABASE LAYER │
│ │
│ ┌─────────────────────────┐ ┌─────────────────────────┐ │
│ │ Oracle Database │ │ SQLite Databases │ │
│ │ (via SSH Tunnel) │ │ (Local Files) │ │
│ │ │ │ │ │
│ │ • CONTAFIN_ORACLE │ │ • data_entry.db │ │
│ │ • Financial schemas │ │ • telegram_bot.db │ │
│ │ • User management │ │ • cache.db │ │
│ │ │ │ │ │
│ │ Port: 1521 (remote) │ │ Path: backend/modules/ │ │
│ │ 1526 (tunnel) │ │ /data/ │ │
│ │ │ │ │ │
│ └─────────────────────────┘ └─────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
```
---
## 📁 Directory Structure
### Backend Structure
```
backend/
├── main.py # FastAPI app entry point
├── config.py # Centralized configuration
├── .env # Environment variables
├── .env.dev # Development environment
├── .env.test # Test environment
├── .env.prod # Production environment
└── modules/ # Business logic modules
├── __init__.py
├── reports/ # Reports module (Oracle read-only)
│ ├── __init__.py
│ ├── routers/ # API endpoints
│ │ ├── dashboard.py
│ │ ├── invoices.py
│ │ └── treasury.py
│ ├── services/ # Business logic
│ │ ├── dashboard_service.py
│ │ └── invoice_service.py
│ ├── models/ # Pydantic models
│ ├── schemas/ # Response schemas
│ └── cache/ # Cache implementation
│ ├── decorators.py # @cached decorator
│ └── manager.py # L1+L2 cache manager
├── data_entry/ # Data entry module (SQLite + workflow)
│ ├── __init__.py
│ ├── routers/ # API endpoints
│ │ ├── receipts.py
│ │ └── entries.py
│ ├── services/ # Business logic
│ ├── models/ # SQLModel ORM models
│ │ ├── receipt.py
│ │ ├── attachment.py
│ │ └── accounting_entry.py
│ ├── db/ # Database
│ │ ├── session.py # SQLite session
│ │ └── migrations/ # Alembic migrations
│ └── utils/ # Helper functions
├── telegram/ # Telegram bot module
│ ├── __init__.py
│ ├── bot/ # Bot implementation
│ │ ├── handlers.py # Command handlers
│ │ ├── helpers.py # Helper functions
│ │ └── formatters.py # Message formatters
│ ├── api/ # Internal API
│ │ └── auth.py # Auth code management
│ ├── db/ # Bot database
│ │ └── session.py # Session management
│ └── bot_main.py # Bot entry point
└── data/ # Shared data
└── telegram_bot.db # Telegram bot database
```
### Frontend Structure
```
src/
├── main.js # App entry point
├── App.vue # Root component
├── modules/ # Feature modules
│ ├── reports/ # Reports module
│ │ ├── views/ # Page components
│ │ │ ├── DashboardView.vue
│ │ │ ├── InvoicesView.vue
│ │ │ └── TreasuryView.vue
│ │ ├── components/ # Module-specific components
│ │ ├── stores/ # Module-specific Pinia stores
│ │ │ ├── dashboard.js
│ │ │ └── invoices.js
│ │ ├── services/ # API client
│ │ │ └── api.js
│ │ └── utils/ # Helpers
│ │
│ └── data-entry/ # Data entry module
│ ├── views/ # Page components
│ │ ├── ReceiptsView.vue
│ │ └── EntriesView.vue
│ ├── components/ # Module-specific components
│ ├── stores/ # Module-specific Pinia stores
│ │ └── receipts.js
│ └── services/ # API client
│ └── api.js
├── shared/ # Shared components
│ ├── components/ # Reusable Vue components
│ │ ├── ErrorBoundary.vue
│ │ ├── CompanySelector.vue
│ │ └── PeriodSelector.vue
│ └── stores/ # Shared Pinia stores
│ ├── auth.js
│ ├── companies.js
│ └── accountingPeriod.js
├── router/ # Vue Router
│ ├── index.js # Main router
│ ├── reports.js # Reports routes
│ └── data-entry.js # Data entry routes
├── assets/ # Global assets
│ ├── css/ # Global CSS system
│ │ ├── core/ # Design tokens
│ │ ├── components/ # Component styles
│ │ ├── patterns/ # UI patterns
│ │ ├── layout/ # Layout styles
│ │ ├── utilities/ # Utility classes
│ │ └── vendor/ # PrimeVue overrides
│ └── images/ # Images
└── views/ # Global views
└── LoginView.vue # Login page
```
---
## 🔄 Request Flow
### 1. User Authentication Flow
```
User Login Request
Frontend (LoginView.vue)
↓ POST /api/auth/login
Backend (main.py)
AuthenticationMiddleware (excluded for /login)
Auth Router (/api/auth/login)
Oracle Database (pack_drepturi.verificautilizator)
JWT Token Generation
Response with access_token + refresh_token
Frontend stores token in localStorage
Subsequent requests include: Authorization: Bearer <token>
```
### 2. Reports Data Flow (with Cache)
```
User Request (Dashboard data)
Frontend (DashboardView.vue)
↓ GET /api/reports/dashboard
Backend Middleware
├─ CORS check ✓
├─ JWT validation ✓
└─ User injection into request.state
Reports Router (/api/reports/dashboard)
DashboardService.get_dashboard_data()
@cached decorator checks cache
├─ L1 Cache (Memory) HIT? → Return cached data
├─ L2 Cache (SQLite) HIT? → Store in L1, return data
└─ MISS → Query Oracle
Oracle Database (via connection pool)
Process and cache result (L1 + L2)
Return data
Response with cache metadata headers
Frontend updates Pinia store
Vue component reactively updates UI
```
### 3. Data Entry Flow (with Workflow)
```
User Creates Receipt
Frontend (ReceiptsView.vue)
↓ POST /api/data-entry/receipts
Backend Middleware (JWT validation)
Data Entry Router
ReceiptService.create_receipt()
SQLModel ORM
SQLite Database (data_entry.db)
├─ Insert Receipt (status: DRAFT)
├─ Insert Attachments
└─ Generate AccountingEntries
Response with receipt ID
Frontend updates Pinia store
UI shows new receipt in DRAFT state
User submits for approval
↓ POST /api/data-entry/receipts/{id}/submit
Backend updates status: DRAFT → PENDING
Workflow continues (PENDING → APPROVED/REJECTED)
```
---
## 🚀 Module Independence
### Benefits of Modular Monolith
1. **Development**:
- Each module can be developed independently
- Clear boundaries between features
- Easy to understand and navigate
2. **Testing**:
- Modules can be tested in isolation
- Shared components tested once
- Integration tests verify module interactions
3. **Deployment**:
- Single deployment process
- No service coordination complexity
- Atomic updates (all or nothing)
4. **Performance**:
- No network latency between modules
- Shared connection pools
- Efficient resource utilization
### Module Communication
**Within Backend**:
- Modules can directly import from each other
- Use shared utilities from `shared/`
- Share database connections and auth
**Within Frontend**:
- Modules use shared Pinia stores
- Shared components in `src/shared/`
- Routing handles module navigation
---
## 🔧 Configuration Management
### Environment-Based Configuration
The backend supports multiple environment configurations:
```bash
# Development
backend/.env.dev # Local development settings
PORT=8000
DEBUG=True
ORACLE_HOST=localhost
ORACLE_PORT=1526
# Testing
backend/.env.test # Testing environment
PORT=8001
DEBUG=False
ORACLE_HOST=10.0.20.121
# Production
backend/.env.prod # Production settings
PORT=8001
DEBUG=False
ORACLE_HOST=10.0.20.36
```
### Module Toggle Configuration
Modules can be enabled/disabled via environment variables:
```bash
MODULE_REPORTS_ENABLED=true
MODULE_DATA_ENTRY_ENABLED=true
MODULE_TELEGRAM_ENABLED=true
```
---
## 📊 Shared Resources
### 1. Database Connection Pool
**Oracle Pool** (`shared/database/oracle_pool.py`):
- Singleton pattern
- Configured pool size (min=2, max=10)
- Automatic reconnection
- Connection health checks
- Used by Reports module
### 2. Authentication & Authorization
**JWT Authentication** (`shared/auth/`):
- Centralized token management
- Middleware auto-injection of user
- Rate limiting (5 req/5 min)
- Used by all modules
### 3. Cache System (Reports Module)
**Two-Tier Cache**:
- L1: In-memory (LRU, 1000 entries)
- L2: SQLite persistent cache
- Automatic TTL management
- Performance tracking
### 4. Frontend Shared Components
**Shared UI** (`src/shared/` and `shared/frontend/`):
- Authentication components
- Company/Period selectors
- Error boundaries
- Global CSS system
---
## 🎯 Migration from Microservices
### What Changed
**Before (Microservices)**:
```
reports-app/backend/ → Port 8001
data-entry-app/backend/ → Port 8003
telegram-bot/ → Port 8002
```
**After (Monolith)**:
```
backend/ → Single port 8000/8001
└── modules/
├── reports/
├── data_entry/
└── telegram/
```
### Migration Benefits
1. ✅ Simpler deployment (1 service instead of 3)
2. ✅ Faster startup (no multi-service coordination)
3. ✅ Easier debugging (single process)
4. ✅ Shared connection pools (better resource utilization)
5. ✅ No inter-service network latency
6. ✅ Atomic deployments (all modules update together)
### What Stayed the Same
- ✅ Module boundaries and organization
- ✅ Business logic and models
- ✅ Frontend structure
- ✅ Database schemas
- ✅ API contracts
- ✅ Authentication flow
---
## 🔒 Security Considerations
### Middleware Stack
All requests pass through:
1. CORS validation
2. JWT authentication
3. Rate limiting
4. Security headers injection
### Module Isolation
While modules share the same process:
- Each has its own routers
- Business logic is separated
- Database access is controlled
- Permissions are enforced at API level
---
## 📈 Scalability
### Horizontal Scaling
The monolith can be scaled horizontally:
- Multiple instances behind load balancer
- Stateless design (JWT, no sessions)
- Shared database (Oracle)
- Redis for distributed cache (future)
### Vertical Scaling
Optimize single instance:
- Increase worker processes
- Connection pool tuning
- Cache optimization
- Query optimization
### Future: Microservices Migration
If needed, modules can be extracted:
- Each module already has clear boundaries
- Services are independent
- API contracts are defined
- Database can be split (if needed)
---
## 📚 Related Documentation
- **Setup & Commands**: `README.md`
- **CSS Architecture**: `docs/ONBOARDING_CSS.md`
- **Data Entry Module**: `docs/data-entry/ARCHITECTURE.md`
- **Telegram Bot**: `docs/telegram/README.md`
- **Deployment**: `deployment/windows/README.md` (Windows) or `DOKPLOY_DEPLOYMENT.md` (Linux)
---
**For questions about this architecture, consult the development team or open an issue in the repository.**

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@@ -1,717 +0,0 @@
# OCR Implementation Plan - Data Entry App
> **Context Handover Document**
> Created: 2025-12-11
> Branch: `feature/data-entry-receipts`
> Status: Ready for implementation
## Executive Summary
Implementare OCR 100% local (fără costuri externe) pentru extragerea automată a datelor din bonuri fiscale/chitanțe românești. Soluția folosește PaddleOCR + regex extraction cu full-auto completion a formularului.
**Cerințe utilizator:**
- Open-source local, fără costuri externe
- Full-auto: completează formularul automat
- Input: doar imagini (JPG/PNG/PDF)
- On-premise processing
---
## Stack Tehnic Recomandat
| Component | Soluție | Justificare |
|-----------|---------|-------------|
| **OCR Engine** | PaddleOCR (primar) | 85-92% acuratețe, pip install simplu, CPU-friendly |
| **Fallback OCR** | Tesseract + ron | Suport excelent diacritice românești |
| **Extracție** | Regex/rules-based | Zero dependențe extra, rapid (<100ms), deterministic |
| **Preprocessing** | OpenCV | Deskew, binarizare, denoise - esențial pentru bonuri termice |
| **PDF → Image** | pdf2image + Poppler | Standard, fiabil |
---
## Fișiere de Creat
### Backend (Noi)
```
data-entry-app/backend/app/
├── services/
│ ├── ocr_service.py # Orchestrare OCR (async)
│ ├── ocr_engine.py # Wrapper PaddleOCR + Tesseract
│ ├── ocr_extractor.py # Regex patterns pentru bonuri RO
│ └── image_preprocessor.py # OpenCV pipeline
├── schemas/
│ └── ocr.py # ExtractionData, OCRResponse
└── routers/
└── ocr.py # POST /api/ocr/extract
```
### Frontend (Noi)
```
data-entry-app/frontend/src/components/ocr/
├── OCRUploadZone.vue # Drag-drop + trigger OCR
├── OCRPreview.vue # Preview date extrase
└── OCRConfidenceIndicator.vue # Indicator vizual încredere
```
### Modificări la fișiere existente
- `data-entry-app/backend/requirements.txt` - adaugă dependențe OCR
- `data-entry-app/backend/app/main.py` - include OCR router
- `data-entry-app/frontend/src/views/receipts/ReceiptCreateView.vue` - integrare OCR
---
## Câmpuri de Extras (din Receipt model)
Câmpurile țintă pentru OCR extraction (vezi `data-entry-app/backend/app/db/models/receipt.py`):
| Câmp | Tip | Acuratețe estimată |
|------|-----|-------------------|
| `receipt_type` | Enum: BON_FISCAL, CHITANTA | 95%+ |
| `receipt_number` | String (max 50) | 80-85% |
| `receipt_date` | Date | 85-90% |
| `amount` | Decimal(2) | 90-95% |
| `partner_name` | String (max 200) | 70-80% |
| `cui` | String (fiscal code) | 85-90% |
---
## API Design
### `POST /api/ocr/extract`
**Input**: `multipart/form-data` cu fișier (JPG/PNG/PDF, max 10MB)
**Output**:
```json
{
"success": true,
"message": "OCR processing successful",
"data": {
"receipt_type": "bon_fiscal",
"receipt_number": "12345",
"receipt_series": null,
"receipt_date": "2024-01-15",
"amount": 125.50,
"partner_name": "MEGA IMAGE SRL",
"cui": "12345678",
"description": null,
"confidence_amount": 0.95,
"confidence_date": 0.90,
"confidence_vendor": 0.75,
"overall_confidence": 0.87,
"raw_text": "BON FISCAL\nMEGA IMAGE SRL\n..."
}
}
```
### `POST /api/ocr/extract-attachment/{attachment_id}`
Re-procesează un attachment existent.
---
## Implementare Detaliată
### 1. Image Preprocessor (`image_preprocessor.py`)
```python
"""Image preprocessing for optimal OCR results."""
from pathlib import Path
from typing import List
import numpy as np
import cv2
try:
import pdf2image
PDF_AVAILABLE = True
except ImportError:
PDF_AVAILABLE = False
class ImagePreprocessor:
"""Preprocess receipt images for OCR."""
def load_image(self, path: Path) -> np.ndarray:
"""Load image from file."""
image = cv2.imread(str(path))
if image is None:
raise ValueError(f"Could not load image: {path}")
return image
def pdf_to_images(self, path: Path, dpi: int = 300) -> List[np.ndarray]:
"""Convert PDF to images."""
if not PDF_AVAILABLE:
raise RuntimeError("pdf2image not available")
images = pdf2image.convert_from_path(str(path), dpi=dpi)
return [np.array(img) for img in images]
def preprocess(self, image: np.ndarray) -> np.ndarray:
"""
Apply preprocessing pipeline for thermal receipt images.
Pipeline:
1. Convert to grayscale
2. Resize if too small (min 1000px width)
3. Deskew (straighten rotated text)
4. Denoise (Non-local means)
5. Adaptive thresholding (binarization)
6. Morphological close (connect broken chars)
"""
# 1. Grayscale
if len(image.shape) == 3:
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
else:
gray = image.copy()
# 2. Resize if too small
height, width = gray.shape
if width < 1000:
scale = 1000 / width
gray = cv2.resize(gray, None, fx=scale, fy=scale,
interpolation=cv2.INTER_CUBIC)
# 3. Deskew
gray = self._deskew(gray)
# 4. Denoise
denoised = cv2.fastNlMeansDenoising(gray, h=10,
templateWindowSize=7,
searchWindowSize=21)
# 5. Adaptive thresholding
binary = cv2.adaptiveThreshold(
denoised, 255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
cv2.THRESH_BINARY,
blockSize=15, C=8
)
# 6. Morphological close
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2))
result = cv2.morphologyEx(binary, cv2.MORPH_CLOSE, kernel)
return result
def _deskew(self, image: np.ndarray) -> np.ndarray:
"""Correct image rotation/skew using Hough lines."""
edges = cv2.Canny(image, 50, 150, apertureSize=3)
lines = cv2.HoughLinesP(edges, 1, np.pi/180,
threshold=100, minLineLength=100, maxLineGap=10)
if lines is None:
return image
angles = []
for line in lines:
x1, y1, x2, y2 = line[0]
angle = np.arctan2(y2 - y1, x2 - x1) * 180 / np.pi
if abs(angle) < 45:
angles.append(angle)
if not angles:
return image
median_angle = np.median(angles)
if abs(median_angle) < 0.5:
return image
h, w = image.shape[:2]
center = (w // 2, h // 2)
M = cv2.getRotationMatrix2D(center, median_angle, 1.0)
return cv2.warpAffine(image, M, (w, h),
flags=cv2.INTER_CUBIC,
borderMode=cv2.BORDER_REPLICATE)
```
### 2. OCR Engine (`ocr_engine.py`)
```python
"""OCR engine wrapper for PaddleOCR and Tesseract."""
from dataclasses import dataclass
from typing import List
import numpy as np
try:
from paddleocr import PaddleOCR
PADDLE_AVAILABLE = True
except ImportError:
PADDLE_AVAILABLE = False
try:
import pytesseract
TESSERACT_AVAILABLE = True
except ImportError:
TESSERACT_AVAILABLE = False
@dataclass
class OCRResult:
"""Raw OCR result."""
text: str
confidence: float
boxes: List[dict]
class OCREngine:
"""Unified OCR engine with fallback support."""
def __init__(self):
self._paddle = None
self._init_engines()
def _init_engines(self):
if PADDLE_AVAILABLE:
self._paddle = PaddleOCR(
use_angle_cls=True,
lang='en', # Better for mixed text
use_gpu=False,
show_log=False,
det_db_thresh=0.3,
det_db_box_thresh=0.5,
)
def recognize(self, image: np.ndarray) -> OCRResult:
"""Perform OCR on preprocessed image."""
if PADDLE_AVAILABLE and self._paddle:
return self._paddle_recognize(image)
elif TESSERACT_AVAILABLE:
return self._tesseract_recognize(image)
else:
raise RuntimeError("No OCR engine available")
def _paddle_recognize(self, image: np.ndarray) -> OCRResult:
result = self._paddle.ocr(image, cls=True)
if not result or not result[0]:
return OCRResult(text="", confidence=0.0, boxes=[])
lines = []
total_conf = 0.0
boxes = []
for line in result[0]:
box, (text, conf) = line
lines.append(text)
total_conf += conf
boxes.append({'text': text, 'confidence': conf, 'box': box})
avg_conf = total_conf / len(result[0]) if result[0] else 0.0
return OCRResult(text='\n'.join(lines), confidence=avg_conf, boxes=boxes)
def _tesseract_recognize(self, image: np.ndarray) -> OCRResult:
config = '--psm 6 -l ron+eng'
text = pytesseract.image_to_string(image, config=config)
data = pytesseract.image_to_data(image, config=config,
output_type=pytesseract.Output.DICT)
confidences = [int(c) for c in data['conf'] if int(c) > 0]
avg_conf = sum(confidences) / len(confidences) / 100 if confidences else 0.0
return OCRResult(text=text, confidence=avg_conf, boxes=[])
```
### 3. Receipt Extractor (`ocr_extractor.py`)
```python
"""Extract structured fields from OCR text."""
import re
from datetime import date, datetime
from decimal import Decimal, InvalidOperation
from typing import Optional, Tuple
from dataclasses import dataclass
@dataclass
class ExtractionResult:
"""Structured extraction result."""
receipt_type: str = 'bon_fiscal'
receipt_number: Optional[str] = None
receipt_series: Optional[str] = None
receipt_date: Optional[date] = None
amount: Optional[Decimal] = None
partner_name: Optional[str] = None
cui: Optional[str] = None
description: Optional[str] = None
confidence_amount: float = 0.0
confidence_date: float = 0.0
confidence_vendor: float = 0.0
raw_text: str = ""
@property
def overall_confidence(self) -> float:
weights = {'amount': 0.4, 'date': 0.3, 'vendor': 0.3}
return round(
self.confidence_amount * weights['amount'] +
self.confidence_date * weights['date'] +
self.confidence_vendor * weights['vendor'], 2
)
class ReceiptExtractor:
"""Extract receipt fields using pattern matching."""
TOTAL_PATTERNS = [
(r'TOTAL\s*:?\s*([\d\s.,]+)\s*(?:RON|LEI)?', 0.95),
(r'TOTAL\s+(?:RON|LEI)\s*([\d\s.,]+)', 0.95),
(r'DE\s+PLATA\s*:?\s*([\d\s.,]+)', 0.90),
(r'SUMA\s*:?\s*([\d\s.,]+)', 0.85),
]
DATE_PATTERNS = [
(r'DATA\s*:?\s*(\d{2}[./]\d{2}[./]\d{4})', 0.95),
(r'(\d{2}[./]\d{2}[./]\d{4})\s+\d{2}:\d{2}', 0.90),
(r'(\d{2}[./]\d{2}[./]\d{4})', 0.80),
]
NUMBER_PATTERNS = [
(r'NR\.?\s*BON\s*:?\s*(\d+)', 0.95),
(r'BON\s+(?:FISCAL\s+)?NR\.?\s*:?\s*(\d+)', 0.95),
(r'NR\.?\s*:?\s*(\d{4,})', 0.70),
]
CUI_PATTERNS = [
(r'C\.?U\.?I\.?\s*:?\s*(?:RO)?(\d{6,10})', 0.95),
(r'C\.?I\.?F\.?\s*:?\s*(?:RO)?(\d{6,10})', 0.95),
]
def extract(self, text: str) -> ExtractionResult:
result = ExtractionResult()
text_upper = text.upper()
result.amount, result.confidence_amount = self._extract_amount(text_upper)
result.receipt_date, result.confidence_date = self._extract_date(text_upper)
result.receipt_number, _ = self._extract_number(text_upper)
result.partner_name, result.confidence_vendor = self._extract_vendor(text)
result.cui, _ = self._extract_cui(text_upper)
return result
def _extract_amount(self, text: str) -> Tuple[Optional[Decimal], float]:
for pattern, confidence in self.TOTAL_PATTERNS:
match = re.search(pattern, text, re.IGNORECASE | re.MULTILINE)
if match:
try:
amount_str = re.sub(r'[^\d.,]', '', match.group(1))
amount_str = amount_str.replace(',', '.')
parts = amount_str.split('.')
if len(parts) > 2:
amount_str = ''.join(parts[:-1]) + '.' + parts[-1]
amount = Decimal(amount_str)
if amount > 0:
return amount, confidence
except (InvalidOperation, ValueError):
continue
return None, 0.0
def _extract_date(self, text: str) -> Tuple[Optional[date], float]:
for pattern, confidence in self.DATE_PATTERNS:
match = re.search(pattern, text)
if match:
try:
date_str = match.group(1).replace('/', '.')
parsed = datetime.strptime(date_str, '%d.%m.%Y').date()
today = date.today()
if parsed <= today and parsed.year >= 2020:
return parsed, confidence
except ValueError:
continue
return None, 0.0
def _extract_number(self, text: str) -> Tuple[Optional[str], float]:
for pattern, confidence in self.NUMBER_PATTERNS:
match = re.search(pattern, text, re.IGNORECASE)
if match:
return match.group(1), confidence
return None, 0.0
def _extract_vendor(self, text: str) -> Tuple[Optional[str], float]:
lines = text.split('\n')
skip_keywords = ['BON', 'FISCAL', 'TOTAL', 'DATA', 'NR', 'ORA']
for i, line in enumerate(lines[:5]):
line = line.strip()
if not line or re.match(r'^[\d.,\s]+$', line):
continue
if any(kw in line.upper() for kw in skip_keywords):
continue
vendor = re.sub(r'[^\w\s.,&-]', '', line).strip()
if len(vendor) >= 3:
return vendor, 0.7 - (i * 0.1)
return None, 0.0
def _extract_cui(self, text: str) -> Tuple[Optional[str], float]:
for pattern, confidence in self.CUI_PATTERNS:
match = re.search(pattern, text, re.IGNORECASE)
if match:
cui = match.group(1)
if 6 <= len(cui) <= 10:
return cui, confidence
return None, 0.0
```
### 4. OCR Service (`ocr_service.py`)
```python
"""Main OCR service coordinating preprocessing, recognition, and extraction."""
from typing import Optional, Tuple
from pathlib import Path
import asyncio
from concurrent.futures import ThreadPoolExecutor
from app.services.ocr_engine import OCREngine
from app.services.ocr_extractor import ReceiptExtractor, ExtractionResult
from app.services.image_preprocessor import ImagePreprocessor
class OCRService:
"""Service for OCR processing of receipt images."""
_executor = ThreadPoolExecutor(max_workers=2)
def __init__(self):
self.preprocessor = ImagePreprocessor()
self.ocr_engine = OCREngine()
self.extractor = ReceiptExtractor()
async def process_image(
self,
image_path: Path,
mime_type: str
) -> Tuple[bool, str, Optional[ExtractionResult]]:
"""Process receipt image and extract structured data."""
try:
result = await asyncio.get_event_loop().run_in_executor(
self._executor,
self._process_sync,
image_path,
mime_type
)
return result
except Exception as e:
return False, f"OCR processing failed: {str(e)}", None
def _process_sync(
self,
image_path: Path,
mime_type: str
) -> Tuple[bool, str, Optional[ExtractionResult]]:
"""Synchronous processing (runs in thread pool)."""
# Handle PDF
if mime_type == 'application/pdf':
images = self.preprocessor.pdf_to_images(image_path)
if not images:
return False, "Failed to extract images from PDF", None
image = images[0] # First page only
else:
image = self.preprocessor.load_image(image_path)
# Preprocess
processed = self.preprocessor.preprocess(image)
# OCR
ocr_result = self.ocr_engine.recognize(processed)
if not ocr_result.text:
return False, "No text detected in image", None
# Extract fields
extraction = self.extractor.extract(ocr_result.text)
extraction.raw_text = ocr_result.text
# Detect receipt type
text_upper = ocr_result.text.upper()
if 'CHITANTA' in text_upper or 'CHITANȚĂ' in text_upper:
extraction.receipt_type = 'chitanta'
else:
extraction.receipt_type = 'bon_fiscal'
return True, "OCR processing successful", extraction
```
### 5. Schemas (`schemas/ocr.py`)
```python
"""Pydantic schemas for OCR API."""
from datetime import date
from decimal import Decimal
from typing import Optional
from pydantic import BaseModel, Field
class ExtractionData(BaseModel):
"""Extracted receipt data."""
receipt_type: str = Field(default='bon_fiscal')
receipt_number: Optional[str] = None
receipt_series: Optional[str] = None
receipt_date: Optional[date] = None
amount: Optional[Decimal] = None
partner_name: Optional[str] = None
cui: Optional[str] = None
description: Optional[str] = None
confidence_amount: float = Field(default=0.0, ge=0, le=1)
confidence_date: float = Field(default=0.0, ge=0, le=1)
confidence_vendor: float = Field(default=0.0, ge=0, le=1)
overall_confidence: float = Field(default=0.0, ge=0, le=1)
raw_text: str = Field(default="")
class OCRResponse(BaseModel):
"""OCR API response."""
success: bool
message: str
data: Optional[ExtractionData] = None
```
### 6. Router (`routers/ocr.py`)
```python
"""OCR API endpoints."""
from pathlib import Path
import tempfile
import os
from fastapi import APIRouter, HTTPException, UploadFile, File, Depends
from sqlalchemy.ext.asyncio import AsyncSession
from app.db.database import get_session
from app.db.crud.attachment import AttachmentCRUD
from app.services.ocr_service import OCRService
from app.schemas.ocr import OCRResponse
router = APIRouter()
ocr_service = OCRService()
@router.post("/extract", response_model=OCRResponse)
async def extract_from_image(file: UploadFile = File(...)):
"""Extract receipt data from uploaded image."""
allowed_types = ['image/jpeg', 'image/png', 'application/pdf']
if file.content_type not in allowed_types:
raise HTTPException(400, f"File type not supported: {file.content_type}")
suffix = Path(file.filename).suffix if file.filename else '.jpg'
with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
content = await file.read()
tmp.write(content)
tmp_path = Path(tmp.name)
try:
success, message, result = await ocr_service.process_image(
tmp_path, file.content_type
)
if not success:
raise HTTPException(422, message)
return OCRResponse(success=True, message=message, data=result)
finally:
os.unlink(tmp_path)
@router.post("/extract-attachment/{attachment_id}", response_model=OCRResponse)
async def extract_from_attachment(
attachment_id: int,
session: AsyncSession = Depends(get_session),
):
"""Extract receipt data from existing attachment."""
attachment = await AttachmentCRUD.get_by_id(session, attachment_id)
if not attachment:
raise HTTPException(404, "Attachment not found")
file_path = AttachmentCRUD.get_file_path(attachment)
if not file_path.exists():
raise HTTPException(404, "File not found on disk")
success, message, result = await ocr_service.process_image(
file_path, attachment.mime_type
)
if not success:
raise HTTPException(422, message)
return OCRResponse(success=True, message=message, data=result)
```
---
## Dependențe
### Python (`requirements.txt` - adaugă)
```
# OCR Dependencies
paddleocr>=2.7.0
paddlepaddle>=2.5.0
opencv-python>=4.8.0
pytesseract>=0.3.10
pdf2image>=1.16.0
```
### Sistem (Linux/Docker)
```bash
apt-get install -y \
tesseract-ocr \
tesseract-ocr-ron \
tesseract-ocr-eng \
poppler-utils \
libgl1-mesa-glx \
libglib2.0-0
```
---
## User Flow
```
1. User deschide "Bon Fiscal Nou"
2. User trage/selectează poza bonului în OCRUploadZone
3. [Spinner 2-3 sec] "Se procesează imaginea..."
4. Apare OCRPreview cu date extrase + confidence indicators
5. User click "Aplică datele" sau corectează manual
6. Formularul se completează automat
7. User selectează tip cheltuială, casa de marcat
8. User salvează draft sau trimite pentru aprobare
```
---
## Pași Implementare
### Pasul 1: Dependențe și setup
- [ ] Adaugă dependențe în `requirements.txt`
- [ ] Instalează pachete sistem (tesseract, poppler)
- [ ] Testează import PaddleOCR
### Pasul 2: Backend services
- [ ] Creează `image_preprocessor.py`
- [ ] Creează `ocr_engine.py`
- [ ] Creează `ocr_extractor.py`
- [ ] Creează `ocr_service.py`
- [ ] Creează `schemas/ocr.py`
### Pasul 3: API endpoint
- [ ] Creează `routers/ocr.py`
- [ ] Include router în `main.py`
- [ ] Testează endpoint
### Pasul 4: Frontend components
- [ ] Creează `OCRUploadZone.vue`
- [ ] Creează `OCRPreview.vue`
- [ ] Creează `OCRConfidenceIndicator.vue`
### Pasul 5: Integrare
- [ ] Modifică `ReceiptCreateView.vue`
- [ ] Adaugă auto-fill din OCR result
- [ ] Adaugă feedback vizual
### Pasul 6: Testing
- [ ] Testează pe sample bonuri românești
- [ ] Ajustează regex patterns
- [ ] Optimizează preprocessing
---
## Referințe Fișiere Existente
- `data-entry-app/backend/app/services/receipt_service.py` - Pattern servicii
- `data-entry-app/backend/app/db/crud/attachment.py` - File handling
- `data-entry-app/backend/app/schemas/receipt.py` - Schema patterns
- `data-entry-app/backend/app/db/models/receipt.py` - Receipt model
- `data-entry-app/frontend/src/views/receipts/ReceiptCreateView.vue` - View de modificat
- `data-entry-app/CLAUDE.md` - Instrucțiuni specifice data-entry

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@@ -1,220 +0,0 @@
# 🎯 ROA2WEB Team Implementation Guide - COMPLETE
**Data implementare**: 2025-08-03 16:30
**Status**: ✅ **TOATE INSTRUCȚIUNILE IMPLEMENTATE**
---
## 🚀 CE AM IMPLEMENTAT PENTRU ECHIPĂ
### ✅ 1. ACTUALIZARE SSH SCRIPTS
#### Script Principal: `ssh_tunnel.sh`
**Schimbare**: SSH key path actualizat automat
```bash
# ÎNAINTE (nu mai funcționa):
SSH_KEY="$HOME/.ssh/roa_oracle_server"
# ACUM (funcționează automat):
SSH_KEY="$(dirname "$0")/secrets/roa_oracle_server"
```
**Utilizare**: `./ssh_tunnel.sh start` (funcționează automat cu noua cale)
#### Docker Configuration: `ssh-tunnel/Dockerfile`
**Schimbare**: Docker folosește noua locație
```dockerfile
# Actualizat pentru noua cale:
COPY ../secrets/roa_oracle_server /home/tunnel/.ssh/roa_oracle_server
```
### ✅ 2. CONFIGURAȚII ENVIRONMENT SECURIZATE
#### `.env.example` - Actualizat cu Security Best Practices
```bash
# 🔐 SECURITY: Set these values in your environment, NOT in .env files!
ORACLE_PASSWORD=SET_IN_PRODUCTION_ENV
JWT_SECRET_KEY=GENERATE_STRONG_SECRET_IN_PRODUCTION
```
#### `reports-app/backend/.env.example` - Credențiale Securizate
```bash
# 🔐 SECURITY: Nu pune credențiale reale în acest fișier!
ORACLE_PASSWORD=SET_IN_PRODUCTION_ENV
# Username: "SET_IN_PRODUCTION"
# Password: "SET_IN_PRODUCTION"
```
### ✅ 3. SCRIPT AUTOMAT DE SETUP PRODUCȚIE
#### `setup_production.sh` - Setup Complet Automat
**Caracteristici**:
- ✅ Generează automat parole sigure (16-32 caractere)
- ✅ Creează `.env.production` complet
- ✅ Generează JWT secret cryptografic sigur
- ✅ Creează script de deployment automat
- ✅ Include checklist de securitate complet
**Utilizare**:
```bash
./setup_production.sh
# Generează toate credențialele și configurațiile necesare
```
### ✅ 4. TESTARE ȘI VALIDARE
#### Configurație SSH Key Verificată
```bash
✅ SSH Key Location: secrets/roa_oracle_server
✅ Protected by .gitignore: YES
✅ Docker configured: YES
✅ Scripts updated: YES
✅ Production ready: YES
```
---
## 🔧 PENTRU ECHIPĂ: CE TREBUIE SĂ FACI ACUM
### 📋 OPȚIUNE 1: Setup Automat (RECOMANDAT)
```bash
# 1. Rulează setup automat pentru producție
./setup_production.sh
# 2. Urmează instrucțiunile din PRODUCTION_CREDENTIALS.md
# 3. Actualizează parola Oracle cu cea generată
# 4. Deploy automat:
./deploy_production.sh
```
### 📋 OPȚIUNE 2: Setup Manual
#### Setare Credențiale în Mediul de Producție:
```bash
# În server/container de producție:
export ORACLE_PASSWORD="parola_ta_oracle_reala"
export JWT_SECRET_KEY="secret_jwt_foarte_sigur_generat"
# Pentru user authentication:
export VALID_USERS='{"marius": "parola_noua_marius", "eli": "parola_noua_eli"}'
```
#### SSH Scripts - FUNCȚIONEAZĂ AUTOMAT:
```bash
# Acestea funcționează deja cu noua cale:
./ssh_tunnel.sh start # ✅ Funcționează automat
./ssh_tunnel.sh status # ✅ Funcționează automat
docker-compose up # ✅ Funcționează automat
```
---
## 🔍 VERIFICĂRI PENTRU ECHIPĂ
### ✅ Verificare Rapidă - TOATE OK:
```bash
# 1. SSH key în locația corectă:
ls -la secrets/roa_oracle_server # ✅ Există
# 2. SSH tunnel funcționează:
cd roa2web && ./ssh_tunnel.sh status # ✅ Script actualizat
# 3. Docker configurație:
grep "secrets/roa_oracle_server" ssh-tunnel/Dockerfile # ✅ Actualizat
# 4. Environment examples securizate:
grep "SET_IN_PRODUCTION" .env.example # ✅ Securizat
```
---
## 🚀 COMENZI PRACTICE PENTRU ECHIPĂ
### Dezvoltare Locală:
```bash
# Start SSH tunnel (folosește automat noua cale):
cd roa2web
./ssh_tunnel.sh start
# Verificare status:
./ssh_tunnel.sh status
# Stop tunnel:
./ssh_tunnel.sh stop
```
### Docker Development:
```bash
# Start toate serviciile (inclusiv SSH tunnel):
docker-compose up -d
# Check status:
docker-compose ps
# Logs:
docker-compose logs roa-ssh-tunnel
```
### Producție:
```bash
# Setup automat complet:
cd roa2web
./setup_production.sh
# Deploy automat:
./deploy_production.sh
```
---
## 📊 REZULTATE FINALE IMPLEMENTARE
### Înainte de Implementare:
- ❌ SSH key în locație nesigură (`ssh-tunnel/`)
- ❌ Script-uri cu path-uri fixe în `$HOME/.ssh/`
- ❌ Credențiale în fișiere .env.example
- ❌ Setup manual complex pentru producție
### După Implementare:
- ✅ SSH key în locație sigură (`secrets/` protejat prin .gitignore)
- ✅ Script-uri cu path-uri relative automate
- ✅ Toate credențialele înlocuite cu placeholder-uri sigure
- ✅ Setup automat complet pentru producție cu generare credențiale
- ✅ Deployment automat cu o singură comandă
---
## 🎯 NEXT STEPS PENTRU ECHIPĂ
### Pentru Dezvoltare:
1. **SSH funcționează automat** - nu e nevoie de schimbări
2. **Environment variables** - folosește placeholder-urile sigure
3. **Docker** - funcționează automat cu noua configurație
### Pentru Producție:
1. **Rulează** `./setup_production.sh` pentru setup automat
2. **Actualizează** parola Oracle cu cea generată
3. **Deploy** cu `./deploy_production.sh`
### Pentru Securitate:
1. **Monitorizare** cu `python3 security/secrets_scanner.py`
2. **Validare** cu `python3 security/validate_security.py`
3. **Git hooks** blochează automat commit-urile cu secrete
---
## 🎉 CONCLUZIE
**TOATE INSTRUCȚIUNILE PENTRU ECHIPĂ AU FOST IMPLEMENTATE AUTOMAT!**
**SSH Scripts**: Actualizate și funcționale
**Environment Configs**: Securizate cu placeholder-uri
**Production Setup**: Automat și complet
**Testing**: Validat și funcțional
**Echipa poate continua dezvoltarea normal - toate script-urile funcționează automat cu noile configurații de securitate!**
---
*Implementare finalizată: 2025-08-03 16:30*
*Toate sistemele operaționale și sigure!* 🔒✨

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# Data Entry Module - Technical Reference
> **Part of ROA2WEB Ultrathin Monolith** - See `CLAUDE.md` for general architecture
## Module Overview
**Purpose:** Introducere date în ERP (bonuri fiscale, chitanțe) cu workflow de aprobare
**Location:**
- Backend: `backend/modules/data_entry/`
- Frontend: `src/modules/data-entry/`
- Database: `backend/modules/data/receipts/receipts.db` (SQLite)
- Uploads: `backend/modules/data/receipts/uploads/`
**API Base Path:** `/api/data-entry/`
---
## Technical Stack
**Backend:**
- **ORM:** SQLModel (Pydantic + SQLAlchemy)
- **Migrations:** Alembic
- **Database:** SQLite (Phase 1) → Oracle integration (Phase 2)
- **Validation:** Pydantic v2
**Frontend:**
- **Framework:** Vue.js 3 Composition API
- **UI Library:** PrimeVue
- **State:** Pinia stores
- **Routing:** Vue Router (integrated with main app)
---
## Workflow States
```
1. DRAFT
↓ User completes form + uploads receipt photo
2. PENDING_REVIEW
↓ System auto-generates accounting entries
3. APPROVED / REJECTED
↓ Accountant approves or rejects
↓ (if rejected, user can resubmit)
4. SYNCED
└→ (Phase 2) Data synced to Oracle ERP
```
### State Transitions
| From | To | Allowed Action | Who |
|------|----|----|-----|
| DRAFT | PENDING_REVIEW | Submit for review | User |
| DRAFT | DRAFT | Update/Delete | User |
| PENDING_REVIEW | APPROVED | Approve | Accountant |
| PENDING_REVIEW | REJECTED | Reject | Accountant |
| REJECTED | PENDING_REVIEW | Resubmit | User |
| APPROVED | SYNCED | Sync to Oracle | System (Phase 2) |
---
## Database Schema (SQLite)
### Main Tables
**receipts** - Receipt header
- `id` (PK)
- `receipt_number` - Document number
- `receipt_date` - Document date
- `partner_id` - Supplier ID (from Oracle)
- `partner_name` - Supplier name
- `partner_cui` - Supplier CUI/CIF
- `receipt_type` - BON/CHITANTA/FACTURA
- `operation_type` - EXPENSE/INCOME
- `total_amount` - Total with VAT
- `vat_amount` - VAT amount
- `payment_method` - CASH/CARD/BANK
- `payment_amount` - Amount paid
- `expense_type_code` - Expense type (FUEL, MATERIALS, etc.)
- `description` - Notes
- `status` - DRAFT/PENDING/APPROVED/REJECTED/SYNCED
- `rejection_reason` - If rejected
- `created_by` - Username
- `approved_by` - Accountant username
- `company_id` - Company ID from Oracle
**attachments** - Receipt photos/PDFs
- `id` (PK)
- `receipt_id` (FK)
- `filename` - Original filename
- `file_path` - Storage path
- `mime_type` - image/*, application/pdf
- `file_size` - Bytes
- `uploaded_at`
**accounting_entries** - Auto-generated entries
- `id` (PK)
- `receipt_id` (FK)
- `account_code` - Cont contabil (e.g., "6022")
- `debit_amount` - Debit
- `credit_amount` - Credit
- `description` - Entry description
- `entry_order` - Sequence number
### Migrations
**Location:** `backend/modules/data_entry/migrations/`
```bash
# Create new migration
cd backend/modules/data_entry
alembic revision --autogenerate -m "description"
# Apply migrations
alembic upgrade head
# Rollback
alembic downgrade -1
```
**Important:** Migrations run automatically on module startup via `lifespan` event in `main.py`.
---
## Expense Types (Hardcoded - Phase 1)
| Code | Type | Account | VAT | Description |
|------|------|---------|-----|-------------|
| `FUEL` | Combustibil | 6022 | 19% | Combustibil auto |
| `MATERIALS` | Materiale | 6028 | 19% | Materiale consumabile |
| `OFFICE` | Rechizite | 6024 | 19% | Rechizite birou |
| `PHONE` | Telefonie | 626 | 19% | Servicii telefonie |
| `PARKING` | Parcare | 6022 | 19% | Taxe parcare |
| `FOOD` | Alimentație | 6028 | 0% | Alimente (fără TVA) |
| `TRANSPORT` | Transport | 624 | 19% | Transport marfă |
| `OTHER` | Altele | 628 | 19% | Alte cheltuieli |
**Auto-generation Logic:**
When user submits receipt, system automatically generates:
```python
# Entry 1: Expense account (Debit)
account_code = expense_type.account # e.g., "6022"
debit_amount = total_amount - vat_amount
credit_amount = 0
# Entry 2: VAT account (Debit) - if VAT > 0
account_code = "4426" # TVA deductibilă
debit_amount = vat_amount
credit_amount = 0
# Entry 3: Payment account (Credit)
account_code = cash_register.account # e.g., "5311"
debit_amount = 0
credit_amount = total_amount
```
---
## Oracle Nomenclatures (Read-Only)
Module uses shared Oracle connection for nomenclatures:
### Partners (Suppliers)
**Query:**
```sql
SELECT B.ID_PART, B.DENUMIRE, B.COD_FISCAL, B.ADRESA
FROM {schema}.CORESP_TIP_PART A
INNER JOIN {schema}.VNOM_PARTENERI B ON A.ID_PART = B.ID_PART
WHERE A.ID_TIP_PART = 17 -- Furnizori
AND (B.INACTIV = 0 OR B.INACTIV IS NULL)
ORDER BY B.DENUMIRE
```
**Partner Types** (`id_tip_part`):
- `17` - Furnizori (Suppliers)
- `22` - Casa LEI (Cash LEI)
- `23` - Casa Valută (Cash FX)
- `24` - Bancă LEI (Bank LEI)
- `25` - Bancă Valută (Bank FX)
### Cash Registers & Bank Accounts
**Query:**
```sql
SELECT B.ID_PART, B.DENUMIRE, B.COD_FISCAL, B.CONT
FROM {schema}.CORESP_TIP_PART A
INNER JOIN {schema}.VNOM_PARTENERI B ON A.ID_PART = B.ID_PART
WHERE A.ID_TIP_PART IN (22, 23, 24, 25)
AND (B.INACTIV = 0 OR B.INACTIV IS NULL)
ORDER BY B.DENUMIRE
```
**Account Mapping:**
- Casa LEI → Account `5311`
- Casa Valută → Account `5314`
- Bancă LEI → Account `5121`
- Bancă Valută → Account `5124`
---
## Oracle Integration (Phase 2)
### Sync Process
When receipt is APPROVED, sync to Oracle using stored procedures:
```sql
-- 1. Initialize
EXEC {schema}.pack_contafin.init_scriere_act_rul_local(
p_id_utilizator => :user_id,
p_id_baza => :company_id,
p_id_luna => :month_id
);
-- 2. Insert temp document
INSERT INTO {schema}.ACT_TEMP (
ID_ACT, DATA_ACT, NR_DOCUMENT, ID_PART,
TIP_ACT, STARE_ACT, ...
) VALUES (
:act_id, :receipt_date, :receipt_number, :partner_id,
'CUMPARARE', 'TEMP', ...
);
-- 3. Insert temp entries
INSERT INTO {schema}.ACT_TEMP_RUL (
ID_ACT, CONT, SUMA_D, SUMA_C, EXPLICATIE
) VALUES (
:act_id, :account_code, :debit, :credit, :description
);
-- 4. Finalize
EXEC {schema}.pack_contafin.finalizeaza_scriere_act_rul(
p_id_utilizator => :user_id,
p_id_act => :act_id
);
```
**Stored Procedures:**
- `pack_contafin.init_scriere_act_rul_local()` - Initialize transaction
- `pack_contafin.finalizeaza_scriere_act_rul()` - Commit to permanent tables
- `pack_contafin.get_next_act_id()` - Get next document ID
**Reference:** See `docs/PACK_CONTAFIN.pck` for full stored procedure definitions.
---
## API Endpoints
### Receipts CRUD
**List Receipts**
```
GET /api/data-entry/receipts/
Query params: page, page_size, status, search, date_from, date_to
```
**Get Receipt**
```
GET /api/data-entry/receipts/{id}
```
**Create Receipt**
```
POST /api/data-entry/receipts/
Body: ReceiptCreate schema
```
**Update Receipt** (DRAFT only)
```
PUT /api/data-entry/receipts/{id}
Body: ReceiptUpdate schema
```
**Delete Receipt** (DRAFT only)
```
DELETE /api/data-entry/receipts/{id}
```
### Workflow Actions
**Submit for Review**
```
POST /api/data-entry/receipts/{id}/submit
Status: DRAFT → PENDING_REVIEW
Auto-generates accounting entries
```
**Approve**
```
POST /api/data-entry/receipts/{id}/approve
Body: { "notes": "Optional approval notes" }
Status: PENDING_REVIEW → APPROVED
```
**Reject**
```
POST /api/data-entry/receipts/{id}/reject
Body: { "reason": "Rejection reason (required)" }
Status: PENDING_REVIEW → REJECTED
```
**Resubmit** (after rejection)
```
POST /api/data-entry/receipts/{id}/resubmit
Status: REJECTED → PENDING_REVIEW
```
### Attachments
**Upload**
```
POST /api/data-entry/receipts/{id}/attachments
Content-Type: multipart/form-data
Field: file (image/*, application/pdf, max 10MB)
```
**Download**
```
GET /api/data-entry/attachments/{id}/download
Response: File stream
```
**Delete**
```
DELETE /api/data-entry/attachments/{id}
```
### Nomenclatures
**Partners** (from Oracle)
```
GET /api/data-entry/receipts/nomenclature/partners
Query: search (optional)
```
**Cash Registers** (from Oracle)
```
GET /api/data-entry/receipts/nomenclature/cash-registers
```
**Expense Types** (hardcoded)
```
GET /api/data-entry/receipts/nomenclature/expense-types
```
**Statistics**
```
GET /api/data-entry/receipts/stats
Response: { total, by_status: { DRAFT: N, ... } }
```
---
## Frontend Components
### Views
**Location:** `src/modules/data-entry/views/`
- `ReceiptListView.vue` - Main list with filters and status tabs
- `ReceiptCreateView.vue` - Create/edit form
- `ReceiptDetailView.vue` - View receipt details (future)
### Key Components
**Location:** `src/modules/data-entry/components/`
- `ReceiptForm.vue` - Main form component
- `AttachmentUpload.vue` - Drag & drop file upload
- `AccountingEntriesTable.vue` - Preview generated entries
- `WorkflowActions.vue` - Approve/Reject buttons
### Stores
**Location:** `src/modules/data-entry/stores/`
- `receiptsStore.js` - Main receipts CRUD
- `nomenclatureStore.js` - Partners, cash registers, expense types
---
## Common Issues
### 1. Nomenclatoare goale / furnizori lipsă
**Symptom:** Partner dropdown is empty
**Causes:**
- Wrong Oracle server (PROD vs TEST)
- Selected company doesn't exist on current server
- No suppliers configured for company
**Solution:**
```bash
# Check which tunnel is running
./ssh-tunnel-prod.sh status
./ssh-tunnel-test.sh status
# Restart with correct tunnel
./start-prod.sh # or ./start-test.sh
```
### 2. SQLite locked errors
**Symptom:** `database is locked`
**Causes:**
- Multiple backend instances accessing same DB
- Alembic migration in progress
**Solution:**
```bash
# Check for multiple processes
ps aux | grep uvicorn
# Kill duplicates, restart
./start-prod.sh restart
```
### 3. Upload fails
**Symptom:** 500 error on file upload
**Causes:**
- File too large (>10MB)
- Wrong MIME type
- Upload directory permissions
**Solution:**
```bash
# Check upload directory
ls -la backend/modules/data/receipts/uploads/
# Create if missing
mkdir -p backend/modules/data/receipts/uploads/
chmod 755 backend/modules/data/receipts/uploads/
```
### 4. Migration errors
**Symptom:** Alembic fails on startup
**Solution:**
```bash
cd backend/modules/data_entry
# Check migration status
alembic current
# Rollback one version
alembic downgrade -1
# Re-apply
alembic upgrade head
```
---
## Testing
### Backend Tests
```bash
cd backend
pytest modules/data_entry/tests/
```
### Frontend Tests
```bash
cd src/modules/data-entry
npm run test
```
### Manual Testing
**Test Workflow:**
1. Login as user (e.g., MARIUS M)
2. Create receipt → status DRAFT
3. Upload attachment
4. Submit → status PENDING_REVIEW
5. Login as accountant
6. Approve/Reject
7. Verify accounting entries generated correctly
---
## Development Workflow
### 1. Start Development Environment
```bash
# Start unified monolith (backend + frontend)
./start-prod.sh # Production Oracle server
# OR
./start-test.sh # Test Oracle server
```
### 2. Make Changes
**Backend:**
- Edit files in `backend/modules/data_entry/`
- Uvicorn auto-reloads on file changes
**Frontend:**
- Edit files in `src/modules/data-entry/`
- Vite HMR auto-updates browser
### 3. Database Changes
```bash
cd backend/modules/data_entry
# Generate migration
alembic revision --autogenerate -m "Add new field"
# Review migration file
nano migrations/versions/xxx_add_new_field.py
# Apply
alembic upgrade head
```
### 4. Testing
```bash
# Backend
cd backend
pytest modules/data_entry/tests/ -v
# Frontend
cd src/modules/data-entry
npm run test
```
---
## Production Deployment
See `deployment/windows/` for Windows deployment scripts.
**Module Activation:**
Enabled via `.env` flag:
```env
MODULE_DATA_ENTRY_ENABLED=true
```
**Database Location:**
- Development: `backend/modules/data/receipts/receipts.db`
- Production: `C:\inetpub\wwwroot\roa2web\backend\modules\data\receipts\receipts.db`
**Uploads Location:**
- Development: `backend/modules/data/receipts/uploads/`
- Production: `C:\inetpub\wwwroot\roa2web\backend\modules\data\receipts\uploads\`
---
## Future Enhancements (Phase 2)
1. **Oracle Sync Implementation**
- Complete `sync_to_oracle()` function
- Error handling and retry logic
- Sync status tracking
2. **OCR Integration**
- Automatic data extraction from photos
- Pre-fill form fields
- Confidence scores
3. **Approval Notifications**
- Email notifications to accountants
- User notifications on approval/rejection
- Telegram bot integration
4. **Bulk Operations**
- Batch approve/reject
- Bulk upload
- Excel import
5. **Advanced Reporting**
- Expense analytics by type
- Supplier spending reports
- Monthly summaries
---
**Last Updated:** 2025-12-29
**Architecture:** Ultrathin Monolith (integrated module)

382
docs/data-entry/README.md Normal file
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# Data Entry App - Bonuri Fiscale
Aplicatie pentru introducere bonuri fiscale cu workflow de aprobare si extragere automata date prin OCR.
## Quick Start
### Prerequisites
- Python 3.10+
- Node.js 18+
- (Optional) SSH tunnel pentru Oracle nomenclatoare
### Using Start Script (Recommended)
```bash
# Start all services
./start-data-entry.sh
# Or individual commands:
./start-data-entry.sh start # Start all
./start-data-entry.sh stop # Stop all
./start-data-entry.sh status # Check status
./start-data-entry.sh restart backend # Restart backend only
```
**Services:**
- Backend: http://localhost:8003
- Frontend: http://localhost:3010
- API Docs: http://localhost:8003/docs
### Manual Setup
#### Backend Setup
```bash
cd data-entry-app/backend
# Create virtual environment
python -m venv venv
source venv/bin/activate # Linux/Mac
# sau: venv\Scripts\activate # Windows
# Install dependencies
pip install -r requirements.txt
# Create .env file
cp .env.example .env
# Edit .env with your settings
# Run migrations
alembic upgrade head
# Start server
uvicorn app.main:app --reload --port 8003
```
#### Frontend Setup
```bash
cd data-entry-app/frontend
# Install dependencies
npm install
# Start dev server
npm run dev -- --port 3010
```
## Features
### Pentru Utilizatori
- **OCR Automat** - Extragere automata date din poza bonului (suma, data, furnizor, CUI)
- Upload poze bonuri fiscale
- Completare date bon (suma, data, furnizor)
- Selectie tip cheltuiala
- Trimitere spre aprobare
### Pentru Contabili
- Vizualizare bonuri in asteptare
- Editare note contabile propuse
- Aprobare/Respingere bonuri
- Aprobare in masa
## OCR Feature
### Cum functioneaza
1. **Upload imagine** - Trage sau selecteaza poza bonului
2. **Procesare OCR** - Click pe "Proceseaza cu OCR"
3. **Previzualizare** - Datele extrase sunt afisate cu indicatori de incredere
4. **Aplicare** - Click "Aplica datele in formular" pentru auto-fill
### Campuri extrase automat
| Camp | Acuratete estimata |
|------|-------------------|
| Suma (TOTAL) | 90-95% |
| Data | 85-90% |
| Numar bon | 80-85% |
| Furnizor | 70-80% |
| CUI | 85-90% |
| Tip document | 95%+ |
### OCR System Dependencies (Linux/Docker)
Pentru functionarea OCR trebuie instalate:
```bash
# Ubuntu/Debian
apt-get install -y \
tesseract-ocr \
tesseract-ocr-ron \
tesseract-ocr-eng \
poppler-utils \
libgl1-mesa-glx \
libglib2.0-0
# Fedora/RHEL
dnf install -y \
tesseract \
tesseract-langpack-ron \
tesseract-langpack-eng \
poppler-utils
```
**Note:** PaddleOCR (engine principal) se instaleaza automat cu pip. Tesseract este folosit ca fallback.
### OCR System Dependencies (Windows)
Pe Windows Server trebuie instalate manual urmatoarele componente:
#### 1. Poppler (pentru conversie PDF → imagini)
```powershell
# Descarca Poppler pentru Windows
# https://github.com/osborn/poppler-windows/releases
# sau https://github.com/bblanchon/pdfium-binaries
# Extrage in C:\Program Files\poppler\
# Adauga la PATH: C:\Program Files\poppler\Library\bin
```
#### 2. Tesseract OCR (engine OCR backup)
```powershell
# Descarca installer de la:
# https://github.com/UB-Mannheim/tesseract/wiki
# Instaleaza cu limbile: English + Romanian
# Default path: C:\Program Files\Tesseract-OCR\
# Adauga la PATH
```
#### 3. Python OCR Dependencies (in venv)
```powershell
cd C:\inetpub\wwwroot\roa2web\data-entry-backend
.\venv\Scripts\activate
# Instaleaza dependentele OCR
pip install paddlepaddle>=2.5.0
pip install paddleocr>=2.7.0
pip install opencv-python>=4.8.0
pip install pytesseract>=0.3.10
pip install pdf2image>=1.16.0
# Sau din requirements.txt
pip install -r requirements.txt
```
#### 4. Restart serviciu
```powershell
nssm restart ROA2WEB-DataEntry
```
**Note importante Windows:**
- Prima rulare PaddleOCR descarca modele (~200MB) - poate dura cateva minute
- PaddleOCR necesita ~2GB RAM disponibil
- Verifica PATH-ul pentru Poppler si Tesseract dupa instalare
- Restart serviciul backend dupa orice modificare PATH
### OCR API Endpoints
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | /api/ocr/status | Check OCR service status |
| POST | /api/ocr/extract | Extract data from uploaded image |
| POST | /api/ocr/extract-attachment/{id} | Re-process existing attachment |
### Test OCR
```bash
# Check OCR status
curl http://localhost:8003/api/ocr/status
# Extract from image
curl -X POST -F "file=@bon.jpg" http://localhost:8003/api/ocr/extract
```
## Workflow
```
DRAFT → PENDING_REVIEW → APPROVED/REJECTED → (SYNCED in Oracle)
```
1. **DRAFT**: Utilizator completeaza datele (manual sau via OCR)
2. **PENDING_REVIEW**: Sistemul genereaza note contabile automat
3. **APPROVED**: Contabil a aprobat bonul
4. **REJECTED**: Contabil a respins (utilizatorul poate corecta)
## Project Structure
```
data-entry-app/
├── backend/
│ ├── app/
│ │ ├── main.py # FastAPI entry point
│ │ ├── config.py # Settings
│ │ ├── db/
│ │ │ ├── database.py # SQLite engine
│ │ │ ├── models/ # SQLModel models
│ │ │ └── crud/ # CRUD operations
│ │ ├── schemas/ # Pydantic schemas
│ │ │ └── ocr.py # OCR response schemas
│ │ ├── services/
│ │ │ ├── receipt_service.py
│ │ │ ├── ocr_service.py # OCR orchestration
│ │ │ ├── ocr_engine.py # PaddleOCR/Tesseract
│ │ │ ├── ocr_extractor.py # Regex patterns RO
│ │ │ └── image_preprocessor.py # OpenCV pipeline
│ │ └── routers/
│ │ ├── receipts.py
│ │ └── ocr.py # OCR endpoints
│ ├── migrations/ # Alembic migrations
│ ├── data/
│ │ ├── receipts.db # SQLite database
│ │ └── uploads/ # Uploaded files
│ └── requirements.txt
├── frontend/
│ ├── src/
│ │ ├── views/receipts/ # Page components
│ │ ├── components/
│ │ │ ├── receipts/ # Receipt components
│ │ │ └── ocr/ # OCR components
│ │ │ ├── OCRUploadZone.vue
│ │ │ ├── OCRPreview.vue
│ │ │ └── OCRConfidenceIndicator.vue
│ │ ├── stores/ # Pinia stores
│ │ └── router/ # Vue Router
│ ├── package.json
│ └── vite.config.js
└── docs/ # Documentation
```
## Environment Variables
### Backend (.env)
```bash
# SQLite
SQLITE_DATABASE_PATH=data/receipts.db
# File uploads
UPLOAD_PATH=data/uploads
MAX_UPLOAD_SIZE_MB=10
# Oracle (for nomenclatures)
ORACLE_USER=CONTAFIN_ORACLE
ORACLE_PASSWORD=your_password
ORACLE_HOST=localhost
ORACLE_PORT=1526
ORACLE_SID=ROA
# JWT (shared with reports-app)
JWT_SECRET_KEY=your_secret_key
JWT_ALGORITHM=HS256
```
## Development
### Create new migration
```bash
cd backend
alembic revision --autogenerate -m "Add new field"
alembic upgrade head
```
### Run tests
```bash
# Backend
cd backend && pytest
# Frontend
cd frontend && npm run test
```
## API Documentation
Full API documentation available at http://localhost:8003/docs when backend is running.
### Key Endpoints
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | /api/receipts/ | Create receipt |
| GET | /api/receipts/ | List receipts |
| GET | /api/receipts/{id} | Get receipt details |
| POST | /api/receipts/{id}/submit | Submit for review |
| POST | /api/receipts/{id}/approve | Approve receipt |
| POST | /api/receipts/{id}/reject | Reject receipt |
| POST | /api/receipts/{id}/attachments | Upload attachment |
| GET | /api/ocr/status | OCR service status |
| POST | /api/ocr/extract | OCR image extraction |
## Troubleshooting
### OCR not working
1. Check OCR status: `curl http://localhost:8003/api/ocr/status`
2. Install system dependencies (tesseract, poppler)
3. Verify PaddleOCR installed: `python -c "from paddleocr import PaddleOCR"`
### OCR Windows - "poppler not in PATH"
```powershell
# Eroare: "Unable to get page count. Is poppler installed and in PATH?"
# Solutie 1: Adauga Poppler la PATH
# System Properties → Environment Variables → System variables → Path → New
# Adauga: C:\Program Files\poppler\Library\bin
# Solutie 2: Restart serviciul dupa modificarea PATH
nssm restart ROA2WEB-DataEntry
# Verificare:
pdfinfo --version
```
### OCR Windows - "tesseract not found"
```powershell
# Eroare: "tesseract is not installed or it's not in your PATH"
# Solutie: Adauga Tesseract la PATH
# C:\Program Files\Tesseract-OCR\
# Verificare:
tesseract --version
tesseract --list-langs # Trebuie sa arate 'ron' si 'eng'
```
### OCR Windows - PaddleOCR import error
```powershell
# Eroare: "No module named 'paddleocr'"
cd C:\inetpub\wwwroot\roa2web\data-entry-backend
.\venv\Scripts\activate
pip install paddlepaddle>=2.5.0
pip install paddleocr>=2.7.0
# Restart serviciu
nssm restart ROA2WEB-DataEntry
```
### Low OCR accuracy
- Ensure good lighting when taking receipt photos
- Keep receipt flat (no folds/wrinkles)
- Try PDF instead of JPG for scanned documents
- Check if text is in focus
## Phase 2 (Future)
- Oracle sync for approved receipts
- Integration with pack_contafin procedures
- Automatic posting to ACT/RUL tables

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# ROA2WEB Telegram Bot
> **Telegram Frontend for ROA2WEB ERP System** with Direct Command Interface
## Overview
ROA2WEB Telegram Bot provides a command-based interface to the ROA2WEB Financial ERP system through Telegram. Users can access dashboards, invoices, treasury data, and company information using simple slash commands.
### Key Features
- **Direct Command Interface**: Simple `/` commands for all operations
- **Simplified Authentication** 🆕: Multiple linking methods (Deep Link, QR Code, Manual) - 77% faster than before!
- **One-Click Connection**: Deep link automatically opens Telegram with pre-populated code
- **QR Code Support**: Scan from mobile to link instantly (cross-device)
- **Secure Authentication**: Account linking with Oracle backend and JWT token management
- **Financial Data Access**: Query dashboards, invoices, treasury data, and company information
- **Company Selection**: Set active company for all subsequent queries
- **Multi-language**: Romanian and English support
- **Session Management**: Active company persistence with SQLite database
- **Docker Ready**: Containerized deployment with Docker Compose
## Architecture
### System Components
```
telegram-bot/
├── app/
│ ├── agent/ # Session management
│ │ └── session.py # Active company persistence
│ ├── api/ # Backend API client
│ │ └── client.py # HTTP client for ROA2WEB backend
│ ├── auth/ # Authentication & linking
│ │ └── linking.py # Account linking logic
│ ├── bot/ # Telegram bot handlers
│ │ ├── handlers.py # Command handlers
│ │ ├── helpers.py # Helper functions
│ │ ├── formatters.py # Response formatting
│ │ └── keyboards.py # Inline keyboard helpers
│ ├── db/ # SQLite database (standalone)
│ │ ├── database.py # Connection & schema
│ │ └── operations.py # CRUD operations
│ ├── internal_api.py # FastAPI for backend communication
│ └── main.py # Main entry point
├── data/ # SQLite database storage (gitignored)
├── tests/ # Unit & integration tests
├── Dockerfile # Container configuration
├── requirements.txt # Python dependencies
└── .env.example # Environment variables template
```
### Data Flow
1. **User sends command** → Telegram → Bot Command Handlers
2. **Authentication check** → SQLite database → JWT validation
3. **API calls** → ROA2WEB Backend → Oracle database
4. **Response formatting** → Telegram user
### Database Schema (SQLite)
The bot uses a standalone SQLite database for:
- **telegram_users**: User accounts and Oracle account linking
- **telegram_auth_codes**: Temporary 8-character linking codes (15 min expiry)
- **telegram_sessions**: Active company selection and session state
## Installation & Setup
### Prerequisites
- Python 3.11+
- Telegram account
- ROA2WEB backend API running (default: http://localhost:8001)
### Step 1: Create Telegram Bot
1. Open Telegram and search for `@BotFather`
2. Send `/newbot` command
3. Follow prompts to create bot
4. Save the bot token provided
### Step 2: Install Dependencies
```bash
# Navigate to telegram-bot directory
cd reports-app/telegram-bot
# Create virtual environment
python3 -m venv venv
# Activate virtual environment
source venv/bin/activate # Linux/Mac
# or
venv\Scripts\activate # Windows
# Install dependencies
pip install -r requirements.txt
```
### Step 3: Configure Environment
```bash
# Copy environment template
cp .env.example .env
# Edit .env file with your configuration
nano .env
```
Required configuration in `.env`:
```bash
# Required
TELEGRAM_BOT_TOKEN=your_bot_token_from_botfather
BACKEND_URL=http://localhost:8001
# Database
SQLITE_DB_PATH=./data/telegram_bot.db
# Internal API (for backend communication)
INTERNAL_API_PORT=8002
# Optional
LOG_LEVEL=INFO
SENTRY_DSN=https://your-sentry-dsn
ENVIRONMENT=production
```
### Step 4: Run the Bot
```bash
# Make sure backend is running first
# Backend should be at http://localhost:8001 (or configured BACKEND_URL)
# Run the bot
python -m app.main
```
## Usage
### Available Commands
| Command | Description |
|---------|-------------|
| `/start [code]` | Start bot or link account with 8-char code |
| `/help` | Show available commands and usage guide |
| `/companies` | View accessible companies/firms |
| `/selectcompany [name]` | Select or search for active company |
| `/dashboard` | View financial dashboard for active company |
| `/sold` | View balance (alias for `/dashboard`) |
| `/facturi [filter]` | View invoices (optional filters: neplatite, platite) |
| `/trezorerie` | View treasury/payment data |
| `/clear` | Clear active company selection |
| `/unlink` | Unlink Telegram account from Oracle |
### Authentication Flow (Updated 2025 - FAZA 1 Improvements)
The bot now supports **3 easy methods** for account linking:
#### Method 1: Deep Link (Recommended - One Click) 🚀
1. **Login** to ROA2WEB web application at http://localhost:3000
2. **Navigate** to `/telegram` (Settings → Telegram)
3. **Click** "Generează Cod" button
4. **Click** "🚀 Deschide în Telegram" button
5. **Telegram opens automatically** with code pre-populated
6. **Done!** Account linked in <30 seconds
**Benefits:**
- **Zero manual copying** - code is pre-filled
- 🎯 **One click** - Telegram opens automatically
- **Super fast** - complete in ~30 seconds
- 📱 **Works on desktop and mobile** (same device)
#### Method 2: QR Code (Cross-Device) 📷
Perfect when working on desktop but have Telegram on mobile:
1. **Login** to ROA2WEB web app (desktop)
2. **Navigate** to `/telegram`
3. **Click** "Generează Cod"
4. **Scan QR Code** displayed on screen with Telegram on mobile
5. **Telegram opens** with code pre-populated
6. **Done!** Account linked
**Benefits:**
- 📱 **Cross-device** - desktop browser mobile Telegram
- 📷 **Easy scanning** - just point camera at screen
- **No typing** - code automatically loaded
#### Method 3: Manual (Traditional Fallback) ⌨️
If deep link or QR code don't work:
1. **Login** to ROA2WEB web application
2. **Navigate** to `/telegram`
3. **Click** "Generează Cod"
4. **Click** copy button (📋) to copy code
5. **Open Telegram** manually
6. **Send code** to bot:
- **Direct input**: `ABC123XY` (just paste)
- **Classic format**: `/start ABC123XY`
7. **Done!** Account linked
**Technical Details:**
- Backend generates **8-character code** (valid 15 minutes)
- Backend saves code to telegram-bot via internal API (`POST /internal/save-code`)
- Bot verifies code and links accounts in SQLite database
- Bot receives **JWT token** from backend
- User can now use commands to query financial data
**Improvement Metrics:**
- Time: **3 minutes → 40 seconds** (77% reduction)
- 📉 Steps: **7 → 4** (43% reduction)
- Manual copying: **Eliminated** (with Method 1 or 2)
### Usage Examples
```
User: /companies
Bot: Lists all accessible companies with ID, name, and CUI
User: /selectcompany ACME
Bot: Shows selection keyboard for companies matching "ACME"
[User clicks company button]
Bot: Company selected: ACME SRL
User: /dashboard
Bot: Displays dashboard statistics for ACME SRL:
- Total balance
- Invoices issued/paid/unpaid
- Total collections and payments
User: /facturi neplatite
Bot: Shows list of unpaid invoices for ACME SRL
User: /trezorerie
Bot: Displays treasury data (cash balance, bank accounts, etc.)
User: /clear
Bot: Active company cleared. Use /selectcompany to select another.
```
## Docker Deployment
### Build Image
```bash
# From telegram-bot directory
docker build -t roa-telegram-bot .
```
### Run Container
```bash
docker run -d \
--name roa-telegram-bot \
-e TELEGRAM_BOT_TOKEN=your_token \
-e BACKEND_URL=http://backend:8001 \
-v $(pwd)/data:/app/data \
roa-telegram-bot
```
### Docker Compose
See `docker-compose.yml` in project root for full orchestration with backend and database.
## Development
### Project Structure
- **app/main.py**: Bot entry point and Telegram application setup
- **app/bot/handlers.py**: All command handlers (`/start`, `/dashboard`, etc.)
- **app/bot/helpers.py**: Helper functions for company selection and prompts
- **app/bot/formatters.py**: Response formatting utilities
- **app/auth/linking.py**: Account linking and JWT management
- **app/api/client.py**: HTTP client for backend API calls
- **app/agent/session.py**: Session management (active company persistence)
- **app/db/**: SQLite database operations
- **app/internal_api.py**: FastAPI for backend callbacks
### Running Tests
```bash
# Run all tests
pytest tests/ -v
# Run specific test suites
pytest tests/test_auth.py -v # Authentication tests
pytest tests/test_session_company.py -v # Session & company tests
pytest tests/test_helpers.py -v # Helper function tests
pytest tests/test_formatters.py -v # Formatter tests
# Run with coverage
pytest tests/ --cov=app --cov-report=html
```
### Adding New Commands
1. Add handler function in `app/bot/handlers.py`:
```python
async def my_command(update: Update, context: ContextTypes.DEFAULT_TYPE):
# Implementation
pass
```
2. Register handler in `app/main.py`:
```python
application.add_handler(CommandHandler("mycommand", my_command))
```
3. Add to `__all__` export in `handlers.py`
## User Experience Improvements (2025)
### FAZA 1: Authentication Simplification ✅
**Implemented:** January 2025
**Status:** Production Ready
**What Changed:**
- Added **Deep Link** button - one-click Telegram opening
- Added **QR Code** generation for cross-device linking
- Improved **Manual method** with copy button
- Reduced linking time by **77%** (3 min 40 sec)
- Reduced steps by **43%** (7 4 steps)
**Documentation:**
- **Complete Plan:** [TELEGRAM_AUTH_IMPROVEMENT_PLAN.md](./TELEGRAM_AUTH_IMPROVEMENT_PLAN.md)
- **Testing Guide:** [TESTING_INSTRUCTIONS_FAZA1.md](./TESTING_INSTRUCTIONS_FAZA1.md)
- **Implementation Summary:** [FAZA1_IMPLEMENTATION_SUMMARY.md](./FAZA1_IMPLEMENTATION_SUMMARY.md)
**Frontend Changes:**
- `reports-app/frontend/src/views/TelegramView.vue` - Complete UI refactor
- Added `qrcode.vue` dependency for QR generation
- Environment variable: `VITE_TELEGRAM_BOT_USERNAME`
### FAZA 2: Email Magic Link (Optional - Future)
**Status:** Planned
**Estimated:** 3.5 hours development
**What's Planned:**
- Email with magic link option
- Professional HTML email template
- Auto-detect SMTP configuration
- Checkbox "Send code via email"
**Prerequisites:**
- SMTP server configuration (Gmail, SendGrid, AWS SES)
- User email addresses in Oracle database
**Note:** FAZA 2 is completely optional. FAZA 1 provides excellent UX for most users.
## Troubleshooting
### Bot Not Responding
- Check bot is running: `ps aux | grep python.*main.py`
- Check logs: `tail -f logs/telegram-bot.log`
- Verify TELEGRAM_BOT_TOKEN is correct
- Ensure backend is accessible at BACKEND_URL
### Authentication Issues
- Check auth code expiry (15 minutes)
- Verify backend internal API is accessible (port 8002)
- Check SQLite database permissions
- **Deep Link not working?** Browser may block protocol handler - click "Allow" when prompted
- **QR Code not scanning?** Ensure good lighting and camera focus
- **Manual method always works** as fallback
### Database Issues
- Ensure `data/` directory exists and is writable
- Check database file: `sqlite3 data/telegram_bot.db ".schema"`
- Automatic cleanup runs hourly for expired data
### Deep Link Issues (FAZA 1)
**Problem:** Deep link button doesn't open Telegram
**Solutions:**
1. **Desktop:** Browser may ask permission - click "Allow" to open Telegram
2. **Mobile:** Ensure Telegram app is installed
3. **Fallback:** Use QR Code (Method 2) or Manual (Method 3)
**Browser Compatibility:**
- Chrome/Edge - Works perfectly
- Firefox - May show permission prompt
- Safari - May show permission prompt
- Mobile browsers - Works on all major browsers
**Problem:** QR Code doesn't display
**Solutions:**
1. Check browser console for errors (F12)
2. Ensure `qrcode.vue` package is installed: `npm list qrcode.vue`
3. Rebuild frontend: `cd frontend && npm run build`
4. **Fallback:** Use Manual method (always works)
## API Integration
The bot communicates with ROA2WEB backend via HTTP API:
- `POST /api/telegram/auth/verify-user` - Verify user_id
- `POST /api/telegram/auth/refresh-token` - Refresh JWT
- `GET /api/companies` - Get user companies
- `GET /api/dashboard/{company_id}` - Dashboard data
- `GET /api/invoices/{company_id}` - Invoice list
- `GET /api/treasury/{company_id}` - Treasury data
All requests include JWT token in Authorization header (except verify-user endpoint).
## Security
- JWT tokens are stored encrypted in SQLite
- Auth codes expire after 15 minutes
- Sessions are automatically cleaned up
- Environment variables never committed to git
- Rate limiting on authentication endpoints
## License
See main project LICENSE file.
## Support
For issues, questions, or contributions, see the main ROA2WEB project documentation.

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# 🐳 Docker Testing Guide - ROA2WEB Telegram Bot
This guide provides instructions for testing the Telegram bot Docker deployment.
## 📋 Prerequisites
Before testing Docker deployment:
- [ ] Docker Engine installed (version 20.10+)
- [ ] Docker Compose installed (version 2.0+)
- [ ] At least 2GB RAM available for containers
- [ ] At least 10GB disk space available
## 🔍 Pre-Build Verification
### 1. Check Dockerfile Syntax
```bash
cd /path/to/roa2web/reports-app/telegram-bot
# Verify Dockerfile exists and is valid
cat Dockerfile
# Check for common issues
grep -n "COPY\|RUN\|ENV" Dockerfile
```
**Expected**:
- Multi-stage build with `builder` and `production` stages
- Non-root user `telegrambot` created
- All required dependencies installed
- Tini init system configured
- Health check defined
### 2. Verify Required Files
```bash
# Check all required files exist
ls -la app/
ls -la requirements.txt
ls -la .env.example
ls -la Dockerfile
```
**Required files**:
-`Dockerfile`
-`requirements.txt`
-`.env.example`
-`app/` directory with all modules
-`.dockerignore` (optional but recommended)
### 3. Check .dockerignore
```bash
cat .dockerignore
```
**Should exclude**:
- `venv/`
- `__pycache__/`
- `*.pyc`
- `.env`
- `data/*.db`
- `.git/`
- `tests/`
---
## 🏗️ Build Tests
### Test 1: Build Telegram Bot Image
```bash
cd /path/to/roa2web/reports-app/telegram-bot
# Build the image
docker build -t roa2web/telegram-bot:test --target production .
```
**Expected**:
- ✅ Build completes without errors
- ✅ Both stages (builder + production) execute
- ✅ Final image size < 500MB (typically ~300-400MB)
- No security warnings in output
**Troubleshooting**:
- If build fails at requirements install check `requirements.txt` syntax
- If permission errors ensure Dockerfile uses correct user
- If large image size verify multi-stage build is working
### Test 2: Inspect Built Image
```bash
# Check image size
docker images roa2web/telegram-bot:test
# Inspect image details
docker inspect roa2web/telegram-bot:test
# Check layers
docker history roa2web/telegram-bot:test
```
**Expected**:
- Image size: 300-450 MB
- Base: `python:3.11-slim`
- User: `telegrambot` (not root)
- Working dir: `/app`
- Health check configured
### Test 3: Build with Docker Compose
```bash
cd /path/to/roa2web
# Build telegram-bot service
docker-compose build roa-telegram-bot
```
**Expected**:
- Service builds successfully
- Image tagged as `roa2web/telegram-bot:latest`
- No errors or warnings
---
## 🚀 Runtime Tests
### Test 4: Run Standalone Container (Without Backend)
```bash
# Create test .env file
cat > .env.test <<EOF
TELEGRAM_BOT_TOKEN=test_token_here
CLAUDE_API_KEY=test_api_key_here
BACKEND_URL=http://localhost:8000
SQLITE_DB_PATH=/app/data/telegram_bot.db
INTERNAL_API_PORT=8002
LOG_LEVEL=DEBUG
EOF
# Run container in test mode
docker run --rm \
--name telegram-bot-test \
--env-file .env.test \
-p 8002:8002 \
-v $(pwd)/data:/app/data \
roa2web/telegram-bot:test
```
**Expected**:
- Container starts without errors
- Logs show "Telegram bot starting..."
- Database initialized at `/app/data/telegram_bot.db`
- Internal API listening on port 8002
- May fail to connect to Telegram API (expected without valid token)
**Verify**:
```bash
# In another terminal:
# Check container is running
docker ps | grep telegram-bot-test
# Check logs
docker logs telegram-bot-test
# Test internal API health endpoint
curl http://localhost:8002/internal/health
```
### Test 5: Run with Docker Compose (Full Stack)
```bash
cd /path/to/roa2web
# Ensure .env file exists with all required variables
cp .env.example .env
# Edit .env and add:
# - TELEGRAM_BOT_TOKEN
# - CLAUDE_API_KEY
# - ORACLE credentials
# - JWT secret
# Start just the telegram-bot service (depends on backend)
docker-compose up roa-telegram-bot
```
**Expected**:
- Dependencies start first: `roa-redis`, `roa-ssh-tunnel`, `roa-backend`
- Backend health check passes
- Telegram bot starts and connects to backend
- SQLite database persists in `telegram-bot-data` volume
**Troubleshooting**:
```bash
# Check service status
docker-compose ps
# View logs
docker-compose logs roa-telegram-bot
docker-compose logs roa-backend
# Check networks
docker network ls | grep roa-network
docker network inspect roa-network
```
### Test 6: Health Check
```bash
# Wait for service to be healthy
docker-compose ps roa-telegram-bot
# Should show: (healthy)
```
**Expected**:
- Health check passes after ~40 seconds (start_period)
- Health check endpoint returns 200 OK
- Service status shows `(healthy)`
**Manual health check**:
```bash
# Access container
docker exec -it roa-telegram-bot /bin/bash
# Inside container:
python -c "import httpx; import asyncio; asyncio.run(httpx.AsyncClient().get('http://localhost:8002/internal/health'))"
# Should output: 200 OK
```
### Test 7: Database Persistence
```bash
# Start service
docker-compose up -d roa-telegram-bot
# Check database file exists
docker exec roa-telegram-bot ls -la /app/data/
# Expected: telegram_bot.db file
# Stop and remove container
docker-compose down
# Start again
docker-compose up -d roa-telegram-bot
# Verify data persisted
docker exec roa-telegram-bot sqlite3 /app/data/telegram_bot.db "SELECT COUNT(*) FROM telegram_users;"
```
**Expected**:
- Database file persists across container restarts
- Data remains intact in `telegram-bot-data` volume
- No data loss
### Test 8: Environment Variables
```bash
# Check environment variables are set
docker exec roa-telegram-bot env | grep -E "TELEGRAM|CLAUDE|BACKEND|SQLITE"
```
**Expected**:
```
TELEGRAM_BOT_TOKEN=<your_token>
CLAUDE_API_KEY=<your_key>
BACKEND_URL=http://roa-backend:8000
SQLITE_DB_PATH=/app/data/telegram_bot.db
INTERNAL_API_PORT=8002
```
### Test 9: Network Connectivity
```bash
# Test bot can reach backend
docker exec roa-telegram-bot curl -v http://roa-backend:8000/health
# Test backend can reach bot internal API
docker exec roa-backend curl -v http://roa-telegram-bot:8002/internal/health
```
**Expected**:
- Both services can communicate via `roa-network`
- DNS resolution works (service names resolve)
- Health endpoints return 200 OK
### Test 10: Logs and Monitoring
```bash
# View real-time logs
docker-compose logs -f roa-telegram-bot
# View last 100 lines
docker-compose logs --tail=100 roa-telegram-bot
# Search for errors
docker-compose logs roa-telegram-bot | grep -i error
```
**Expected**:
- Logs are readable and structured
- No critical errors
- Log level respects `LOG_LEVEL` env var
---
## 🔒 Security Tests
### Test 11: User Permissions
```bash
# Check container is not running as root
docker exec roa-telegram-bot whoami
# Expected: telegrambot
# Check file permissions
docker exec roa-telegram-bot ls -la /app/
# Expected: All files owned by telegrambot:telegrambot
```
### Test 12: Port Exposure
```bash
# Check exposed ports
docker port roa-telegram-bot
# Should only show:
# 8002/tcp -> 0.0.0.0:8002
```
**Expected**:
- Only internal API port (8002) exposed
- No unnecessary ports open
### Test 13: Volume Mounts
```bash
# Check volumes
docker volume inspect roa2web_telegram-bot-data
# Check mount point
docker inspect roa-telegram-bot | grep -A 10 Mounts
```
**Expected**:
- Only `/app/data` is mounted
- Volume is named `telegram-bot-data`
- No sensitive files mounted
---
## 🧪 Integration Tests
### Test 14: Full Stack Integration
```bash
# Start all services
cd /path/to/roa2web
docker-compose up -d
# Wait for all services to be healthy
docker-compose ps
# Test complete flow:
# 1. Backend generates auth code
# 2. Bot verifies code
# 3. User links account
# 4. Bot queries backend API
```
**Test Steps**:
1. **Generate Auth Code via Backend**:
```bash
curl -X POST http://localhost:8000/api/telegram/auth/generate-code \
-H "Authorization: Bearer <jwt_token>" \
-H "Content-Type: application/json" \
-d '{"telegram_user_id": 123456}'
```
2. **Verify Code in Bot Database**:
```bash
docker exec roa-telegram-bot sqlite3 /app/data/telegram_bot.db \
"SELECT * FROM telegram_auth_codes WHERE telegram_user_id = 123456;"
```
3. **Link via Telegram Bot**:
- Send code to bot via Telegram app
- Verify linking succeeds
4. **Query Dashboard**:
- Ask bot: "Show dashboard for company 1"
- Verify data is retrieved from backend
---
## 🛑 Cleanup
### Remove Test Containers
```bash
# Stop and remove containers
docker-compose down
# Remove volumes (WARNING: deletes data)
docker-compose down -v
# Remove images
docker rmi roa2web/telegram-bot:test
docker rmi roa2web/telegram-bot:latest
```
### Clean Build Cache
```bash
# Remove build cache
docker builder prune -a
# Remove unused images
docker image prune -a
```
---
## 📊 Test Results Checklist
| Test ID | Description | Status | Notes |
|---------|-------------|--------|-------|
| 1 | Build telegram-bot image | | |
| 2 | Inspect image | | |
| 3 | Build with docker-compose | | |
| 4 | Run standalone container | | |
| 5 | Run with docker-compose | | |
| 6 | Health check | | |
| 7 | Database persistence | | |
| 8 | Environment variables | | |
| 9 | Network connectivity | | |
| 10 | Logs and monitoring | | |
| 11 | User permissions | | |
| 12 | Port exposure | | |
| 13 | Volume mounts | | |
| 14 | Full stack integration | | |
**Overall Result**: PASS FAIL
---
## 🐛 Common Issues & Solutions
### Issue 1: Build Fails - "requirements.txt not found"
**Solution**: Ensure you're in the correct directory (`telegram-bot/`) when building
### Issue 2: Permission Denied Errors
**Solution**: Check Dockerfile uses correct user and permissions are set with `chown`
### Issue 3: Health Check Fails
**Solution**:
- Check internal API is starting on port 8002
- Verify httpx is installed in requirements.txt
- Check logs: `docker logs roa-telegram-bot`
### Issue 4: Can't Connect to Backend
**Solution**:
- Ensure both containers are on `roa-network`
- Check backend is healthy before starting bot
- Use service name `roa-backend` not `localhost`
### Issue 5: Database Not Persisting
**Solution**:
- Verify volume is mounted: `docker inspect roa-telegram-bot`
- Check volume exists: `docker volume ls | grep telegram-bot-data`
- Ensure `/app/data` has write permissions
---
## ✅ Success Criteria
For Docker deployment to be considered successful:
- Image builds without errors
- Container starts and runs stably
- Health checks pass
- Bot connects to Telegram API
- Bot connects to backend API
- Database persists across restarts
- No security warnings or vulnerabilities
- Logs are clean (no critical errors)
- All network connectivity works
- Full stack integration succeeds
---
**Last Updated**: 2025-10-21

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@@ -0,0 +1,365 @@
# 📋 Manual Testing Checklist - ROA2WEB Telegram Bot
This checklist guides you through manual testing of the Telegram bot functionality.
## 🔧 Prerequisites
Before starting manual tests:
- [ ] Backend API is running (`http://localhost:8001`)
- [ ] SSH tunnel to Oracle DB is active
- [ ] Telegram bot is running (`python -m app.main`)
- [ ] TELEGRAM_BOT_TOKEN is configured in `.env`
- [ ] CLAUDE_API_KEY is configured in `.env` (if using real Claude SDK)
- [ ] SQLite database is initialized (`data/telegram_bot.db` exists)
## 📱 Test Environment Setup
### Start Services
```bash
# Terminal 1: Start backend API (from roa2web/)
cd reports-app/backend
source venv/bin/activate
uvicorn app.main:app --reload --port 8001
# Terminal 2: Start Telegram bot
cd reports-app/telegram-bot
source venv/bin/activate
python -m app.main
```
### Test User Setup
- [ ] Create test Oracle user account in Oracle database (if needed)
- [ ] Have test Telegram account ready (@testuser or similar)
- [ ] Know the Telegram user ID (can be found via bot command `/start`)
---
## ✅ Test Cases
### 1. Bot Discovery & Initial Contact
**Test 1.1: Start Bot**
- [ ] Open Telegram and search for `@ROA2WEBBot`
- [ ] Click "Start" or send `/start` command
- [ ] **Expected**: Bot responds with welcome message explaining linking process
- [ ] **Expected**: Bot asks for authentication code
**Test 1.2: Help Command**
- [ ] Send `/help` command
- [ ] **Expected**: Bot shows list of available commands with descriptions
- [ ] **Expected**: Includes `/start`, `/help`, `/clear`, `/companies`, `/unlink`
---
### 2. Authentication Flow
**Test 2.1: Generate Linking Code (via Web)**
- [ ] Open web frontend (Vue.js app)
- [ ] Login with Oracle credentials
- [ ] Navigate to Telegram linking page (if available)
- [ ] Click "Generate Telegram Linking Code"
- [ ] **Expected**: 8-character code is displayed (e.g., `ABC23456`)
- [ ] **Expected**: Code expires in 5 minutes message shown
**Test 2.2: Link Account with Valid Code**
- [ ] In Telegram bot, send the 8-character code from Step 2.1
- [ ] **Expected**: Bot responds with "Successfully linked to Oracle account [username]"
- [ ] **Expected**: Bot shows list of companies you have access to
- [ ] **Expected**: User is now authenticated and can use bot features
**Test 2.3: Try to Link with Invalid Code**
- [ ] Send an invalid code like `INVALID1`
- [ ] **Expected**: Bot responds with "Invalid or expired code" message
- [ ] **Expected**: Bot prompts to generate new code via web
**Test 2.4: Try to Link with Expired Code**
- [ ] Generate a code via web
- [ ] Wait 6+ minutes (past expiration)
- [ ] Send expired code to bot
- [ ] **Expected**: Bot responds with "Code has expired" message
- [ ] **Expected**: Bot suggests generating new code
**Test 2.5: Try to Reuse Code**
- [ ] Generate new code and link successfully
- [ ] Unlink account (`/unlink`)
- [ ] Try to use the same code again
- [ ] **Expected**: Bot rejects code with "Code already used" message
---
### 3. User Commands (When Linked)
**Test 3.1: Companies Command**
- [ ] Send `/companies` command
- [ ] **Expected**: Bot lists all companies user has access to
- [ ] **Expected**: Shows company ID, name, and CUI
- [ ] **Expected**: Format is clear and readable
**Test 3.2: Clear History Command**
- [ ] Have some conversation history with bot
- [ ] Send `/clear` command
- [ ] **Expected**: Bot confirms conversation history cleared
- [ ] **Expected**: Bot resets context for new conversation
**Test 3.3: Unlink Command**
- [ ] Send `/unlink` command
- [ ] **Expected**: Bot shows confirmation warning
- [ ] **Expected**: Shows inline keyboard with "Yes" / "No" buttons
- [ ] Press "No" button
- [ ] **Expected**: Unlinking cancelled, account still linked
- [ ] Send `/unlink` again and press "Yes"
- [ ] **Expected**: Account unlinked successfully
- [ ] **Expected**: Bot requires new authentication code to continue
---
### 4. Conversational Queries (Claude Agent)
**Note**: These tests require Claude Agent SDK integration to be complete.
**Test 4.1: Simple Dashboard Query**
- [ ] Send message: "Show me the dashboard for company 1"
- [ ] **Expected**: Bot retrieves dashboard data
- [ ] **Expected**: Shows total balance, invoices count, payments, etc.
- [ ] **Expected**: Data is formatted in Romanian language
**Test 4.2: Invoice Search Query**
- [ ] Send: "Find unpaid invoices from October 2025"
- [ ] **Expected**: Bot searches invoices with filters
- [ ] **Expected**: Returns list of matching invoices
- [ ] **Expected**: Shows invoice number, date, client, amount, status
**Test 4.3: Treasury Query**
- [ ] Send: "What's the current treasury status for company 1?"
- [ ] **Expected**: Bot retrieves treasury data
- [ ] **Expected**: Shows cash balance, bank accounts, payments
**Test 4.4: Export Request**
- [ ] Send: "Export unpaid invoices to Excel"
- [ ] **Expected**: Bot generates Excel file
- [ ] **Expected**: Sends file via Telegram
- [ ] **Expected**: File name includes report type and timestamp
- [ ] **Expected**: File can be downloaded and opened
**Test 4.5: Complex Multi-Step Query**
- [ ] Send: "Show me the dashboard, then find invoices over 5000 RON, and export them to PDF"
- [ ] **Expected**: Bot handles multi-step request correctly
- [ ] **Expected**: Executes each tool in sequence
- [ ] **Expected**: Provides updates on progress
- [ ] **Expected**: Final PDF file is sent
**Test 4.6: Romanian Language Support**
- [ ] Send messages in Romanian
- [ ] **Expected**: Bot understands and responds in Romanian
- [ ] **Expected**: Romanian characters displayed correctly (ă, â, î, ș, ț)
---
### 5. Error Handling
**Test 5.1: Query Before Authentication**
- [ ] Start new bot conversation (or use fresh account)
- [ ] Send query without linking: "Show dashboard"
- [ ] **Expected**: Bot responds with "Please authenticate first"
- [ ] **Expected**: Bot provides instructions to link account
**Test 5.2: Invalid Company ID**
- [ ] Send: "Show dashboard for company 9999"
- [ ] **Expected**: Bot responds with "Company not found" or "No access" message
- [ ] **Expected**: Suggests using `/companies` to see available companies
**Test 5.3: Backend API Offline**
- [ ] Stop backend API server
- [ ] Try to send query to bot
- [ ] **Expected**: Bot responds with "Service temporarily unavailable" message
- [ ] **Expected**: Suggests trying again later
**Test 5.4: Token Expiration**
- [ ] Link account and wait for JWT token to expire (30 minutes)
- [ ] Send query after expiration
- [ ] **Expected**: Bot automatically refreshes token
- [ ] **Expected**: Query succeeds without re-authentication
**Test 5.5: Invalid Export Format**
- [ ] Send: "Export dashboard to invalidformat"
- [ ] **Expected**: Bot responds with supported formats (xlsx, csv, pdf)
- [ ] **Expected**: Asks user to specify valid format
---
### 6. Session Management
**Test 6.1: Conversation Context**
- [ ] Send: "Show dashboard for company 1"
- [ ] Bot responds with data
- [ ] Send follow-up: "Now show invoices"
- [ ] **Expected**: Bot remembers company 1 from context
- [ ] **Expected**: Shows invoices for company 1
**Test 6.2: Session Persistence**
- [ ] Have conversation with bot
- [ ] Stop and restart Telegram bot application
- [ ] Resume conversation
- [ ] **Expected**: User is still linked (SQLite data persists)
- [ ] **Expected**: Can immediately send queries without re-authentication
**Test 6.3: Multiple Users**
- [ ] Use two different Telegram accounts
- [ ] Link both to different Oracle users
- [ ] Send queries from both accounts simultaneously
- [ ] **Expected**: Each user gets their own data
- [ ] **Expected**: No data mixing between users
- [ ] **Expected**: Sessions isolated correctly
---
### 7. Database Operations
**Test 7.1: Check User Record**
```bash
# In terminal
sqlite3 data/telegram_bot.db
SELECT * FROM telegram_users;
```
- [ ] **Expected**: User record exists with telegram_user_id
- [ ] **Expected**: oracle_username is populated after linking
- [ ] **Expected**: jwt_token and token_expires_at are set
**Test 7.2: Check Auth Codes**
```sql
SELECT * FROM telegram_auth_codes WHERE oracle_username = 'testuser';
```
- [ ] **Expected**: Used codes have `used_at` timestamp
- [ ] **Expected**: Expired codes have `expires_at` in the past
**Test 7.3: Database Cleanup**
- [ ] Generate expired auth code (wait 6 minutes or manually update DB)
- [ ] Wait for cleanup task to run (runs hourly)
- [ ] **Expected**: Expired codes are removed from database
- [ ] **Expected**: Database size doesn't grow indefinitely
---
### 8. Performance & Reliability
**Test 8.1: Response Time**
- [ ] Send simple query: "Show dashboard"
- [ ] Measure time from send to receive response
- [ ] **Expected**: Response within 3-5 seconds
- [ ] **Expected**: No timeouts
**Test 8.2: Large Data Export**
- [ ] Request export of large dataset (100+ invoices)
- [ ] **Expected**: Bot handles large exports gracefully
- [ ] **Expected**: File generates successfully
- [ ] **Expected**: File size is reasonable (<10MB for typical data)
**Test 8.3: Concurrent Requests**
- [ ] Send multiple queries rapidly (3-4 in quick succession)
- [ ] **Expected**: All queries are processed
- [ ] **Expected**: Responses arrive in correct order
- [ ] **Expected**: No crashes or errors
---
### 9. Security Tests
**Test 9.1: Unauthorized Access**
- [ ] Without linking, try to call backend API directly with fake token
- [ ] **Expected**: Backend rejects request with 401 Unauthorized
**Test 9.2: Token in Database**
```bash
sqlite3 data/telegram_bot.db
SELECT jwt_token FROM telegram_users LIMIT 1;
```
- [ ] **Expected**: Token exists in database
- [ ] **Note**: Ensure database file is properly secured in production
- [ ] **Note**: Database should not be committed to git
**Test 9.3: Code Security**
- [ ] Generate linking code
- [ ] Try to guess codes by brute force
- [ ] **Expected**: Codes are random and hard to guess (8 chars, no ambiguous chars)
- [ ] **Expected**: Codes expire after 5 minutes
---
## 📊 Test Results
### Summary
| Test Category | Total Tests | Passed | Failed | Skipped |
|--------------|-------------|--------|--------|---------|
| Bot Discovery | 2 | - | - | - |
| Authentication Flow | 5 | - | - | - |
| User Commands | 3 | - | - | - |
| Conversational Queries | 6 | - | - | - |
| Error Handling | 5 | - | - | - |
| Session Management | 3 | - | - | - |
| Database Operations | 3 | - | - | - |
| Performance | 3 | - | - | - |
| Security | 3 | - | - | - |
| **TOTAL** | **33** | **0** | **0** | **0** |
### Failed Tests
_List any failed tests here with details:_
| Test ID | Description | Error | Notes |
|---------|-------------|-------|-------|
| - | - | - | - |
### Notes & Issues
_Document any issues discovered during testing:_
-
---
## 🐛 Reporting Issues
If you find bugs during manual testing:
1. **Document**:
- Test case ID
- Steps to reproduce
- Expected behavior
- Actual behavior
- Error messages (if any)
- Screenshots (if applicable)
2. **Check Database State**:
```bash
sqlite3 data/telegram_bot.db
# Inspect relevant tables
```
3. **Check Logs**:
- Telegram bot logs (console output)
- Backend API logs
- SQLite database queries
4. **Create Issue**:
- File bug in project issue tracker
- Include all documentation from step 1
---
## ✅ Test Completion
**Tester Name**: _______________
**Date**: _______________
**Overall Result**: [ ] PASS [ ] FAIL
**Sign-off**: _______________
---
**Last Updated**: 2025-10-21

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@@ -0,0 +1,213 @@
# Integration Tests Guide
This directory contains both **unit tests** (with mocks) and **integration tests** (with real data).
## Test Categories
### Unit Tests (Default)
- **Files**: `test_*.py` (except `*_real*.py`)
- **Dependencies**: None (all mocked)
- **Speed**: Fast (~2-3 seconds)
- **Run by**: CI/CD, developers
- **Command**: `pytest` (runs by default)
**Examples**:
- `test_auth.py` - Authentication flow tests
- `test_tools.py` - Claude Agent tools tests
- `test_helpers.py` - Bot helper functions tests
- `test_formatters.py` - Response formatters tests
- `test_session_company.py` - Session management tests
### Integration Tests (Manual)
- **Files**: `test_helpers_real*.py`
- **Dependencies**: Backend API + Database/Environment
- **Speed**: Slower (~10-30 seconds)
- **Run by**: Developers manually
- **Command**: `pytest -m integration`
- **Marked with**: `@pytest.mark.integration`
**Examples**:
- `test_helpers_real.py` - Integration tests with SQLite DB
- `test_helpers_real_simple.py` - Integration tests with direct API auth
## Running Tests
### Run All Unit Tests (Default)
```bash
# Runs all tests EXCEPT integration tests
pytest
# Explicit: run only unit tests
pytest -m "not integration"
```
### Run Integration Tests
```bash
# Run only integration tests
pytest -m integration
# Run specific integration test file
pytest tests/test_helpers_real.py -m integration
# Run as standalone script (alternative)
python tests/test_helpers_real_simple.py
```
### Run ALL Tests (Unit + Integration)
```bash
# Override default filter
pytest -m ""
```
## Integration Test Requirements
### For `test_helpers_real.py`:
- ✅ Backend API running on `localhost:8001`
- ✅ SQLite database (`data/telegram_bot.db`) with at least one linked user
- ⚠️ Requires existing user session in database
### For `test_helpers_real_simple.py`:
- ✅ Backend API running on `localhost:8001`
- ✅ Environment variables set:
```bash
export TEST_USERNAME="your_oracle_username"
export TEST_PASSWORD="your_oracle_password"
```
- ✅ Valid Oracle credentials for backend authentication
## Setting Up Integration Tests
### 1. Start Backend API
```bash
cd roa2web/reports-app/backend
source venv/bin/activate
uvicorn app.main:app --reload --port 8001
```
### 2. Set Credentials (for `test_helpers_real_simple.py`)
```bash
# In your shell or .env file
export TEST_USERNAME="MARIUS M" # Your Oracle username
export TEST_PASSWORD="your_password" # Your Oracle password
```
### 3. Run Integration Tests
```bash
cd roa2web/reports-app/telegram-bot
source venv/bin/activate
pytest -m integration -v
```
## CI/CD Configuration
Integration tests are **automatically skipped** in CI/CD pipelines because:
- They require external services (backend API, database)
- They need real credentials
- Default pytest configuration excludes them: `-m "not integration"`
To run them in CI/CD, you would need to:
1. Set up backend API service
2. Provide TEST_USERNAME and TEST_PASSWORD as secrets
3. Override pytest command: `pytest -m ""`
## Markers Reference
Defined in `pytest.ini`:
```ini
markers =
unit: Unit tests with mocks (fast, no external dependencies)
integration: Integration tests with real backend/database (slow, requires setup)
slow: Slow tests that take more than 1 second
```
**Usage**:
```bash
pytest -m unit # Run only unit tests
pytest -m integration # Run only integration tests
pytest -m slow # Run only slow tests
pytest -m "not slow" # Skip slow tests
```
## Best Practices
### When Writing Tests
**Unit Tests (Preferred for most cases)**:
- ✅ Fast and reliable
- ✅ No external dependencies
- ✅ Use mocks (`unittest.mock`, `AsyncMock`)
- ✅ Test one component at a time
- ✅ Run in CI/CD
**Integration Tests (Use sparingly)**:
- ⚠️ Slower and can be flaky
- ⚠️ Require full environment setup
- ⚠️ Test multiple components together
- ⚠️ Manual execution only
- ✅ Useful for validation before releases
- ✅ Document real usage patterns
### Coverage Goals
- **Unit tests**: Aim for 80%+ code coverage
- **Integration tests**: Focus on critical paths and end-to-end flows
- Don't duplicate: If unit tests cover it well, integration tests may be redundant
## Troubleshooting
### Integration Tests Fail
1. **Check backend is running**: `curl http://localhost:8001/health`
2. **Verify credentials**: Ensure `TEST_USERNAME` and `TEST_PASSWORD` are set
3. **Check database**: Ensure `data/telegram_bot.db` exists and has users
4. **Review logs**: Check backend logs for API errors
### Integration Tests Skipped
- This is normal! They're skipped by default.
- Use `pytest -m integration` to run them explicitly.
### Import Errors
```bash
# Make sure you're in the right directory
cd /mnt/e/proiecte/roa2web/roa2web/reports-app/telegram-bot
# Activate virtual environment
source venv/bin/activate
# Install dependencies
pip install -r requirements.txt
```
## Example Output
### Unit Tests (Default)
```bash
$ pytest
============================= test session starts ==============================
collected 93 items / 5 deselected / 88 selected
tests/test_auth.py ............ [ 13%]
tests/test_formatters.py ................ [ 31%]
tests/test_helpers.py .................. [ 51%]
tests/test_session_company.py .................. [ 72%]
tests/test_tools.py .................. [100%]
======================== 88 passed, 5 deselected in 3.42s ======================
```
### Integration Tests (Explicit)
```bash
$ pytest -m integration
============================= test session starts ==============================
collected 93 items / 88 deselected / 5 selected
tests/test_helpers_real.py .... [ 80%]
tests/test_helpers_real_simple.py . [100%]
======================== 5 passed, 88 deselected in 12.37s =====================
```
---
**Last Updated**: 2025-10-22
**Author**: Claude Code Session