# Google Gemini Setup Learn how to use Google Gemini effectively with Tomba API documentation for code generation and development assistance. ## Quick Use ### Direct Documentation Reference Reference our documentation in your Gemini prompts: ``` Please analyze the Tomba API documentation at https://docs.tomba.io/llms.txt and help me create a Java Spring Boot application that integrates email verification into user registration with proper error handling and rate limiting. ``` ### Code Generation with Context ``` Using the Tomba API documentation available at https://docs.tomba.io/llms.txt, generate a complete Flutter/Dart package for email verification that includes: - HTTP client configuration - Model classes for API responses - Error handling - Rate limiting - Unit tests - Usage examples ``` ## Gemini-Specific Features ### 1. Multi-Modal Capabilities Upload screenshots or diagrams along with your code requests: ``` I've uploaded a diagram of my application architecture. Based on this architecture and the Tomba API documentation (https://docs.tomba.io/llms.txt), help me integrate email verification into the user registration flow. Show me how to implement this in the service layer. ``` ### 2. Code Analysis and Optimization ``` Here's my current email validation implementation: [Paste code] Based on the Tomba API documentation at https://docs.tomba.io/llms.txt, analyze this code and provide optimizations for: - Performance improvements - Better error handling - Rate limiting integration - Security enhancements - Code maintainability ``` ### 3. Long-Form Technical Documentation ``` Based on the Tomba API documentation (https://docs.tomba.io/llms.txt), create comprehensive technical documentation for integrating email verification into a Node.js application, including: 1. Architecture overview 2. Implementation guide 3. Configuration options 4. Error handling strategies 5. Performance considerations 6. Security best practices 7. Testing approaches 8. Deployment guidelines 9. Monitoring and logging 10. Troubleshooting guide Make it detailed enough for a development team to follow. ``` ## Development Workflows ### 1. API Client Development **Planning Phase**: ``` I need to create a robust API client for Tomba email verification. The API documentation is available at https://docs.tomba.io/llms.txt. Please analyze the API and provide: 1. Recommended architecture for the client 2. Key design patterns to implement 3. Error handling strategy 4. Rate limiting approach 5. Caching considerations 6. Testing strategy 7. Documentation requirements Focus on scalability and maintainability for an enterprise application. ``` **Implementation Phase**: ``` Based on our previous discussion and the Tomba API documentation, implement a production-ready TypeScript client with: Core Features: - Authentication management - Request/response interceptors - Automatic retry with exponential backoff - Rate limiting with queue management - Response caching with TTL - Comprehensive error handling - Event-driven architecture for monitoring - TypeScript interfaces for all endpoints - Configurable timeouts and retries - Health check capabilities Please provide the complete implementation with detailed comments. ``` ### 2. Framework-Specific Integration **Django Integration**: ``` Using the Tomba API (documentation: https://docs.tomba.io/llms.txt), create a Django integration package that includes: 1. Django settings configuration 2. Custom user model with email verification 3. Middleware for request validation 4. Management commands for bulk operations 5. Admin interface integration 6. Celery tasks for background processing 7. Custom form fields with validation 8. REST API views using Django REST Framework 9. Unit and integration tests 10. Documentation with examples Structure this as a reusable Django package. ``` **Angular Integration**: ``` Based on the Tomba API docs (https://docs.tomba.io/llms.txt), create an Angular service and components for email verification: 1. Injectable service with HTTP client 2. Reactive forms integration 3. Custom validators for real-time verification 4. Error handling with user-friendly messages 5. Loading states and progress indicators 6. Caching with Angular HTTP interceptors 7. TypeScript models and interfaces 8. Unit tests with Jasmine/Karma 9. E2E tests with Protractor/Cypress 10. Component library with Storybook Include proper dependency injection and RxJS patterns. ``` ### 3. Performance and Scalability **High-Performance Implementation**: ``` Design a high-performance email verification system using Tomba API (docs: https://docs.tomba.io/llms.txt) for an application processing 1M+ emails daily: Requirements: - Sub-100ms response times - 99.99% uptime - Horizontal scaling - Fault tolerance - Cost optimization Design considerations: 1. Connection pooling strategies 2. Request batching and queuing 3. Multi-level caching (Redis, CDN, application) 4. Circuit breaker pattern 5. Health checks and monitoring 6. Graceful degradation 7. Rate limiting strategies 8. Database optimization 9. Microservices architecture 10. Auto-scaling policies Provide implementation details for each component. ``` ## Code Generation Examples ### 1. Go Microservice **Prompt**: ``` Using the Tomba API documentation (https://docs.tomba.io/llms.txt), create a complete Go microservice for email verification with: Architecture: - Clean architecture pattern - Dependency injection - Interface-based design - Repository pattern Features: - HTTP API with Gin framework - gRPC service definitions - Rate limiting with Redis - Caching with multiple backends - Structured logging with logrus - Metrics with Prometheus - Health checks - Graceful shutdown - Configuration management - Database integration (PostgreSQL) Testing: - Unit tests with testify - Integration tests - Mock implementations - Performance benchmarks DevOps: - Dockerfile - Docker Compose - Kubernetes manifests - CI/CD pipeline (GitHub Actions) Provide the complete implementation with proper project structure. ``` ### 2. Python FastAPI Service **Prompt**: ``` Based on the Tomba API documentation at https://docs.tomba.io/llms.txt, create a production-ready FastAPI service with: Core Features: - Async/await throughout - Pydantic models for validation - SQLAlchemy for database operations - Redis for caching and rate limiting - Celery for background tasks - Authentication with JWT - API documentation with OpenAPI - Error handling and logging - Health checks and metrics Advanced Features: - Dependency injection - Middleware for rate limiting - Background task processing - WebSocket support for real-time updates - File upload for bulk operations - Export functionality (CSV, JSON) - Admin interface - Monitoring dashboard Production Ready: - Docker containerization - Configuration management - Testing suite (pytest) - CI/CD pipeline - Monitoring and alerting - Security best practices Include complete project structure and deployment guides. ``` ### 3. React TypeScript Application **Prompt**: ``` Using the Tomba API (docs: https://docs.tomba.io/llms.txt), create a complete React TypeScript application for email management with: Application Features: - Email verification dashboard - Bulk email processing - Real-time validation - Export/import functionality - User management - Analytics and reporting Technical Implementation: - React 18 with hooks - TypeScript throughout - Tailwind CSS for styling - React Query for data fetching - React Hook Form for forms - React Router for navigation - Context API for state management - WebSocket for real-time updates Development Tools: - Vite for build tooling - ESLint and Prettier - Husky for git hooks - Jest and React Testing Library - Storybook for component development - Chromatic for visual testing Production Features: - Error boundaries - Performance optimization - Accessibility compliance - SEO optimization - PWA capabilities - Monitoring integration Include complete project setup and development workflow. ``` ## Advanced Gemini Features ### 1. Code Explanation and Documentation ``` Analyze this Tomba API integration code and provide: 1. Line-by-line explanation of complex parts 2. Architectural decisions and their rationale 3. Performance implications 4. Security considerations 5. Potential improvements 6. Alternative implementation approaches 7. Testing strategies 8. Deployment considerations [Paste your code here] Make the explanation detailed enough for a junior developer to understand and maintain. ``` ### 2. Comparative Analysis ``` Based on the Tomba API documentation (https://docs.tomba.io/llms.txt), compare different implementation approaches for email verification: 1. Client-side vs Server-side validation 2. Synchronous vs Asynchronous processing 3. Different programming languages (Node.js, Python, Go, Java) 4. Framework choices (Express, FastAPI, Gin, Spring Boot) 5. Database options (PostgreSQL, MongoDB, Redis) 6. Caching strategies (In-memory, Redis, CDN) 7. Deployment options (Docker, Kubernetes, Serverless) Provide pros/cons, use cases, and implementation examples for each approach. ``` ### 3. Troubleshooting and Debugging ``` I'm experiencing issues with my Tomba API integration: Symptoms: - Intermittent timeouts (15% of requests) - High memory usage - Occasional 429 rate limit errors - Slow response times during peak hours Current setup: - Node.js with Express - Single instance deployment - No caching - Basic error handling Based on the Tomba API documentation and best practices, diagnose the issues and provide: 1. Root cause analysis 2. Step-by-step debugging approach 3. Monitoring and logging improvements 4. Performance optimizations 5. Infrastructure recommendations 6. Code improvements 7. Testing strategies for validation Include specific code examples and configuration changes. ``` ## Best Practices for Gemini ### 1. Detailed Context Provision ``` Project Context: - Technology Stack: React, Node.js, PostgreSQL, Redis - Scale: 100k users, 500k emails/day - Team: 5 developers, 2 DevOps engineers - Timeline: 8 weeks for MVP - Budget: $50k for infrastructure - Compliance: GDPR, SOX Technical Requirements: - 99.9% uptime SLA - <200ms API response time - Real-time email validation - Bulk processing capabilities - Audit logging - Multi-tenant architecture Based on the Tomba API documentation (https://docs.tomba.io/llms.txt), design and implement an email verification system that meets these requirements. ``` ### 2. Iterative Development ``` Let's build this email verification system iteratively: Phase 1: Core API integration and basic validation Phase 2: Error handling and rate limiting Phase 3: Caching and performance optimization Phase 4: Monitoring and alerting Phase 5: Security hardening and compliance Start with Phase 1. Based on the Tomba API docs, implement the core email verification functionality with proper TypeScript types and basic error handling. ``` ### 3. Comprehensive Testing Strategy ``` For the Tomba API integration we're building, create a comprehensive testing strategy that includes: Unit Testing: - Individual function testing - Mock API responses - Error scenario validation - Edge case handling Integration Testing: - End-to-end API flows - Database integration - Cache integration - Third-party service mocking Performance Testing: - Load testing with varying request volumes - Stress testing for rate limits - Memory usage profiling - Response time benchmarking Security Testing: - Authentication validation - Input sanitization - API key protection - Rate limiting effectiveness Provide test implementation examples for each category using appropriate testing frameworks. ``` ## Integration Patterns ### 1. Event-Driven Architecture ``` Design an event-driven architecture for email verification using Tomba API (docs: https://docs.tomba.io/llms.txt) with: Events: - EmailVerificationRequested - EmailVerificationCompleted - EmailVerificationFailed - BulkVerificationStarted - BulkVerificationCompleted Components: - Event producers (API endpoints) - Event consumers (verification services) - Event store (database) - Message broker (Redis/RabbitMQ) - Notification service Implementation: - Event schemas - Publisher/subscriber patterns - Error handling and retry logic - Dead letter queues - Event sourcing patterns - CQRS implementation Provide complete implementation with Node.js and TypeScript. ``` ### 2. CQRS and Event Sourcing ``` Implement CQRS and Event Sourcing patterns for email verification using Tomba API: Commands: - VerifyEmailCommand - BulkVerifyEmailsCommand - UpdateVerificationStatusCommand Queries: - GetEmailVerificationQuery - GetBulkVerificationStatusQuery - GetVerificationHistoryQuery Events: - EmailVerificationStartedEvent - EmailVerificationCompletedEvent - VerificationStatusUpdatedEvent Include aggregate roots, event handlers, and projection builders. ``` ## Troubleshooting ### Common Issues with Gemini 1. **Context Length**: Break long requests into smaller, focused queries 2. **Code Formatting**: Request specific output formats (markdown, code blocks) 3. **Technical Depth**: Be explicit about the level of detail needed 4. **Implementation Scope**: Clearly define what you want implemented vs planned ### Optimization Tips 1. **Use Specific Examples**: Provide concrete scenarios and requirements 2. **Request Alternatives**: Ask for multiple implementation approaches 3. **Include Constraints**: Mention performance, security, and scalability requirements 4. **Ask for Explanations**: Request rationale behind implementation decisions ## Additional Resources - [Google Gemini Documentation](https://ai.google.dev/docs) - [Tomba API Reference](/api) - [Authentication Guide](/authentication) - [Rate Limits Documentation](/rate-limits) - [Best Practices Guide](/features)