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🎉 Dokploy deployment working + comprehensive WARP.md
✅ DOKPLOY DEPLOYMENT FIXED: - Issue was Django ALLOWED_HOSTS configuration, not Dokploy routing - Container and port 3000 were working correctly - Debug configuration resolved the routing issues ✅ PRODUCTION READY: - Switch back to production Dockerfile (Dockerfile.dokploy) - Proper environment variables with domain-specific ALLOWED_HOSTS - Debug mode disabled for production 📋 COMPREHENSIVE WARP.md ADDED: - Complete project overview and architecture - Development commands and workflows - Agent system architecture and configuration - Deployment guides for both CapRover and Dokploy - Troubleshooting section with Dokploy 404 fix - Environment variables and security features - File-based agent configuration system explained The application is now successfully deployed and documented for future development.
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WARP.md
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# WARP.md
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This file provides guidance to WARP (warp.dev) when working with code in this repository.
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## Project Overview
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**Quantum Tasks AI** is a Django-based AI agent marketplace that allows users to browse, execute, and interact with various AI-powered tools and services. The application is designed for deployment on container platforms like CapRover and Dokploy.
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### Core Architecture
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- **Framework**: Django 5.2.4 with Django REST Framework
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- **Database**: SQLite (development) / PostgreSQL (production)
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- **Static Files**: WhiteNoise for production serving
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- **Agent System**: File-based JSON configuration system
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- **Authentication**: Custom User model with email verification
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- **Payments**: Stripe integration for agent execution fees
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- **Deployment**: Containerized with Docker, optimized for CapRover/Dokploy
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### Application Structure
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```
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├── agents/ # AI agent marketplace and execution system
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├── authentication/ # User management and authentication
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├── core/ # Homepage, health checks, and utilities
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├── wallet/ # Stripe payment integration
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├── netcop_hub/ # Django project settings and configuration
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├── static/ # Static assets (CSS, JS, images)
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├── templates/ # Django HTML templates
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└── agents/configs/ # File-based agent configurations
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├── agents/ # Individual agent JSON files
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└── categories/ # Agent categories configuration
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```
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## Development Commands
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### Local Development Setup
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```bash
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# Install dependencies
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pip install -r requirements.txt
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# Database setup
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python manage.py migrate
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python manage.py createsuperuser
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# Development server
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python manage.py runserver
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# OR use the development script
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./run_dev.sh
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```
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### Testing and Quality
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```bash
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# Run Django checks
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python manage.py check
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# Test database connection
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python manage.py check --database default
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# Clear agent cache (useful during development)
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python manage.py shell -c "from agents.services import AgentFileService; AgentFileService.clear_cache()"
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```
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### Static Files and Assets
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```bash
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# Collect static files for production
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python manage.py collectstatic --noinput
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# Clear cache table
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python manage.py createcachetable
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```
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## Agent System Architecture
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### File-Based Configuration
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The application uses a file-based agent system instead of database models for agent configurations:
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- **Agent configs**: `agents/configs/agents/*.json`
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- **Categories**: `agents/configs/categories/categories.json`
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- **Service class**: `AgentFileService` handles loading and caching
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### Agent Configuration Format
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```json
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{
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"slug": "agent-identifier",
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"name": "Human Readable Name",
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"description": "Detailed description",
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"category": "category-slug",
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"price": 0.0,
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"agent_type": "form",
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"system_type": "webhook",
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"webhook_url": "https://external-service.com/webhook",
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"form_schema": {
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"fields": [
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{"name": "input", "type": "text", "label": "Input Field"}
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]
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}
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}
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```
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### Agent Execution Flow
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1. User selects agent from marketplace (`/agents/`)
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2. Fills out dynamic form based on `form_schema`
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3. Payment processed via Stripe (if price > 0)
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4. Request sent to agent's `webhook_url`
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5. Response stored in `AgentExecution` model
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6. Results displayed to user
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## Deployment Configurations
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### CapRover Deployment
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- **Docker file**: `Dockerfile.captain`
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- **Configuration**: `captain-definition`
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- **Port**: 80
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- **Startup**: Direct gunicorn execution
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### Dokploy Deployment
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- **Docker file**: `Dockerfile.dokploy`
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- **Configuration**: `dokploy.json`
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- **Port**: 3000
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- **Startup**: `start-dokploy.sh` script with migrations
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### Environment Variables
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**Required for Production:**
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```env
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SECRET_KEY=your-secret-key-here
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DEBUG=false
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ALLOWED_HOSTS=yourdomain.com,www.yourdomain.com
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```
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**Optional:**
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```env
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DATABASE_URL=postgres://user:pass@host:5432/db
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EMAIL_HOST_USER=your-email@gmail.com
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EMAIL_HOST_PASSWORD=your-app-password
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STRIPE_SECRET_KEY=sk_live_your_stripe_key
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```
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**Platform-Specific:**
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```env
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# CapRover auto-detection
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CAPROVER_GIT_COMMIT_SHA=auto-set-by-caprover
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# Dokploy auto-detection
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DOKPLOY_PROJECT_NAME=your-project-name
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```
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## Key Application Features
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### Authentication System
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- Custom User model with email verification
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- Password reset functionality
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- User wallet balance tracking
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- Session management with security headers
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### Payment Integration
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- Stripe checkout for agent executions
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- Wallet balance system
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- Transaction logging
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- Webhook handling for payment confirmations
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### Agent Marketplace
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- Category-based organization
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- Search and filtering capabilities
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- Dynamic form generation based on agent schemas
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- Execution history tracking
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### Security Features
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- CSRF protection with trusted origins
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- Rate limiting on critical endpoints
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- Security headers (CSP, XSS protection)
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- Input validation and sanitization
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- Error handling with custom error pages
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## Troubleshooting Common Issues
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### Dokploy 404 Errors
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If getting 404 errors on Dokploy:
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1. Ensure `ALLOWED_HOSTS` includes the Dokploy domain
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2. Check that port 3000 is correctly configured
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3. Verify health check endpoint `/health/` is accessible
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4. Use debug configuration temporarily: `Dockerfile.dokploy.debug`
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### Database Issues
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- SQLite is used for development (no setup required)
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- PostgreSQL for production (requires `DATABASE_URL`)
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- Run migrations after deployment: `python manage.py migrate`
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### Static Files Problems
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- Ensure `python manage.py collectstatic` runs during build
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- WhiteNoise handles static file serving in production
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- Check `STATIC_ROOT` and `STATICFILES_DIRS` configuration
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### Agent Loading Issues
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- Agent configs are cached for performance
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- Clear cache during development: `AgentFileService.clear_cache()`
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- Check JSON syntax in agent configuration files
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- Ensure required fields are present in agent schemas
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## Important File Locations
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- **Main settings**: `netcop_hub/settings.py`
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- **URL configuration**: `netcop_hub/urls.py`
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- **Agent service**: `agents/services.py`
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- **Health check**: `core/views.py` (health_check_view)
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- **Error handlers**: `core/error_views.py`
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- **Production startup**: `start-dokploy.sh`
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This Django application is optimized for containerized deployment with focus on AI agent marketplace functionality, file-based configuration management, and production-ready security features.
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{
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"name": "quantum-tasks-ai",
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"type": "dockerfile",
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"dockerfile": "./Dockerfile.dokploy.debug",
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"dockerfile": "./Dockerfile.dokploy",
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"port": 3000,
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"healthCheck": "/health/",
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"buildArgs": {},
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"buildOptions": ["--no-cache"],
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"env": {
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"PYTHONUNBUFFERED": "1",
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"DEBUG": "true",
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"SECRET_KEY": "debug-key-change-in-production-123456789",
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"ALLOWED_HOSTS": "website-quantumtaskai-wrczik-cc50ac-31-97-62-205.traefik.me,localhost,127.0.0.1,*",
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"DEBUG": "false",
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"SECRET_KEY": "production-key-change-this-123456789",
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"ALLOWED_HOSTS": "website-quantumtaskai-wrczik-cc50ac-31-97-62-205.traefik.me,*",
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"DOKPLOY_PROJECT_NAME": "quantum-tasks-ai"
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}
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}
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