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TTI Middleware

Provider-agnostic Text-to-Image middleware with GDPR compliance and character consistency support. Currently supports Google Cloud (Imagen 3, Imagen 4, Gemini Flash Image, Gemini 3 Pro Image), Eden AI, and IONOS. Features EU data residency via Vertex AI, automatic region fallback, retry logic, and comprehensive error handling.

npm version npm downloads TypeScript Node.js MIT License GitHub

Table of Contents

Features

  • Multi-Provider Architecture: Unified API for all TTI providers
    • Google Cloud (Recommended): Imagen 3, Imagen 4, Gemini Flash Image & Gemini 3 Pro Image with EU data residency
    • Eden AI: Aggregator with access to OpenAI, Stability AI, Replicate (experimental)
    • IONOS: German cloud provider with OpenAI-compatible API (experimental)
  • Character Consistency: Generate consistent characters across multiple images (perfect for children's book illustrations)
  • GDPR/DSGVO Compliance: Built-in EU region support with automatic fallback
  • Region Rotation: Opt-in region rotation on quota errors (429) for Google Cloud — rotate through regions instead of retrying the same exhausted region
  • Retry Logic: Exponential backoff with jitter for transient errors (429, 408, 5xx, timeouts)
  • TypeScript First: Full type safety with comprehensive interfaces
  • Logging Control: Configurable log levels via environment or API
  • Debug Logging: Markdown file logging for debugging prompts and responses
  • Error Handling: Typed error classes for precise error handling

Quick Start

Installation

Install from npm:

npm install @loonylabs/tti-middleware

# For Google Cloud provider (recommended):
npm install @google-cloud/aiplatform @google/genai

Or install directly from GitHub:

npm install github:loonylabs-dev/tti-middleware

Basic Usage

import { TTIService, GoogleCloudTTIProvider, TTIProvider } from '@loonylabs/tti-middleware';

// Create service and register provider
const service = new TTIService();
service.registerProvider(new GoogleCloudTTIProvider({
  projectId: process.env.GOOGLE_CLOUD_PROJECT,
  region: 'europe-west4', // EU region for GDPR
}));

// Generate an image
const result = await service.generate({
  prompt: 'A futuristic city with flying cars, cyberpunk style',
  model: 'imagen-3',
});

console.log('Image generated:', result.images[0].base64?.substring(0, 50) + '...');
console.log('Duration:', result.metadata.duration, 'ms');
Using Character Consistency

Generate consistent characters across multiple images:

// 1. Create the initial character
const character = await service.generate({
  prompt: 'A cute cartoon bear with a red hat and blue scarf, watercolor style',
  model: 'gemini-flash-image', // Only this model supports character consistency!
});

// 2. Generate new scenes with the same character (Structured Mode)
const scene = await service.generate({
  prompt: 'dancing happily in the rain, jumping in puddles',
  model: 'gemini-flash-image',
  referenceImages: [{
    base64: character.images[0].base64!,
    mimeType: 'image/png',
  }],
  subjectDescription: 'cute cartoon bear with red hat and blue scarf',
});

// 3. Or use Index-Based Mode for multiple characters
const multiCharScene = await service.generate({
  prompt: 'The FIRST reference image character meets the SECOND reference image character',
  model: 'gemini-flash-image',
  referenceImages: [
    { base64: character1.images[0].base64!, mimeType: 'image/png' },
    { base64: character2.images[0].base64!, mimeType: 'image/png' },
  ],
  // subjectDescription omitted = Index-Based Mode
});

Important: Character consistency is only supported by gemini-flash-image model!

Switching Providers
// Use Google Cloud (recommended for EU)
const googleResult = await service.generate({
  prompt: 'A mountain landscape',
  model: 'imagen-3',
}, TTIProvider.GOOGLE_CLOUD);

// Use Eden AI (experimental)
const edenResult = await service.generate({
  prompt: 'A mountain landscape',
  model: 'openai', // Uses DALL-E via Eden AI
}, TTIProvider.EDENAI);

// Use IONOS (experimental)
const ionosResult = await service.generate({
  prompt: 'A mountain landscape',
}, TTIProvider.IONOS);

Prerequisites

Required Dependencies
  • Node.js 18+
  • TypeScript 5.3+
  • Google Cloud SDK (optional, for Google Cloud provider)

For Google Cloud provider:

npm install @google-cloud/aiplatform @google/genai

Configuration

Environment Setup

Create a .env file in your project root:

# Default provider
TTI_DEFAULT_PROVIDER=google-cloud

# Logging level (debug, info, warn, error, silent)
TTI_LOG_LEVEL=info

# Google Cloud (recommended for EU/GDPR)
GOOGLE_CLOUD_PROJECT=your-project-id
GOOGLE_APPLICATION_CREDENTIALS=./service-account.json
GOOGLE_CLOUD_REGION=europe-west4  # Recommended for Gemini

# Eden AI (experimental)
EDENAI_API_KEY=your-api-key

# IONOS (experimental)
IONOS_API_KEY=your-api-key
IONOS_API_URL=https://api.ionos.cloud/ai/v1

Providers & Models

Google Cloud (Recommended)

Model ID Character Consistency EU Regions Max Images
Imagen 3 imagen-3 No All EU regions 4
Imagen 4 imagen-4 No All EU regions 4
Imagen 4 Fast imagen-4-fast No All EU regions 4
Imagen 4 Ultra imagen-4-ultra No All EU regions 4
Gemini Flash Image gemini-flash-image Yes europe-west1, europe-west4, europe-north1 1
Gemini 3 Pro Image gemini-pro-image No global endpoint (auto-routed) 1

Important:

  • gemini-flash-image is NOT available in europe-west3 (Frankfurt) - auto-fallback to EU alternative
  • gemini-pro-image requires the global Vertex AI endpoint - the middleware handles this automatically

Eden AI (Experimental)

Model ID Notes
OpenAI DALL-E openai Via Eden AI aggregator
Stability AI stabilityai Via Eden AI aggregator
Replicate replicate Via Eden AI aggregator

IONOS (Experimental)

Model ID Notes
Default default OpenAI-compatible API

Google Cloud Region Availability

Region Location Imagen 3 Imagen 4 Gemini Flash Image Gemini Pro Image
europe-west1 Belgium Yes Yes Yes global endpoint
europe-west3 Frankfurt Yes Yes No global endpoint
europe-west4 Netherlands Yes Yes Yes (Recommended) global endpoint
europe-north1 Finland Yes Yes Yes global endpoint
europe-west9 Paris Yes Yes No global endpoint

Character Consistency

Generate consistent characters across multiple images - perfect for children's book illustrations.

Mode 1: Structured Mode (Single Character)

Best for scenes with a single consistent character:

// Step 1: Create a character
const bear = await service.generate({
  prompt: 'A cute cartoon bear with a red hat, watercolor style',
  model: 'gemini-flash-image',
});

// Step 2: Use in different scenes
const scenes = ['playing in the park', 'reading a book', 'eating honey'];

for (const scene of scenes) {
  const result = await service.generate({
    prompt: scene,
    model: 'gemini-flash-image',
    referenceImages: [{ base64: bear.images[0].base64!, mimeType: 'image/png' }],
    subjectDescription: 'cute cartoon bear with red hat',  // Required in structured mode
  });
  // Save result...
}

Mode 2: Index-Based Mode (Multiple Characters)

Best for scenes with multiple distinct characters. Reference images directly in your prompt by their position:

// Load two different character references
const cowboy1 = await loadImage('cowboy1.png');
const cowboy2 = await loadImage('cowboy2.png');

// Reference each image by index in the prompt
const duelScene = await service.generate({
  prompt: `Generate a cinematic wide shot of a western duel.
    - The character on the LEFT should look exactly like the person in the FIRST reference image.
    - The character on the RIGHT should look exactly like the person in the SECOND reference image.
    They are standing in a dusty street at high noon.`,
  model: 'gemini-flash-image',
  referenceImages: [
    { base64: cowboy1, mimeType: 'image/png' },
    { base64: cowboy2, mimeType: 'image/png' },
  ],
  // subjectDescription intentionally omitted for index-based mode
  aspectRatio: '16:9',
});

Reference keywords: Use "FIRST reference image", "SECOND reference image" or "Image 1", "Image 2" etc.

Requirements

Mode subjectDescription Use Case
Structured Required Single character across scenes
Index-Based Omitted Multiple characters in one scene
  • Model must be gemini-flash-image (only model supporting character consistency)

GDPR / Compliance

Provider Compliance Overview

Provider DPA GDPR EU Data Residency Document
Google Cloud Yes Yes Yes CDPA
Eden AI Yes Depends* Depends* Privacy Policy
IONOS Yes Yes Yes AGB

*Eden AI is an aggregator - compliance depends on the underlying provider.

Google Cloud Data Usage

  • Customer data is NOT used for training AI models
  • Data stays in configured region (e.g., europe-west4)
  • Zero data retention option available
  • Vertex AI Privacy Whitepaper
Checking EU Region Status
import { GoogleCloudTTIProvider } from '@loonylabs/tti-middleware';

const provider = new GoogleCloudTTIProvider({
  projectId: 'my-project',
  region: 'europe-west4',
});

console.log('Is EU region:', provider.isEURegion()); // true
console.log('Current region:', provider.getRegion()); // 'europe-west4'

API Reference

TTIService

class TTIService {
  registerProvider(provider: BaseTTIProvider): void;
  generate(request: TTIRequest, provider?: TTIProvider): Promise<TTIResponse>;
  getProvider(name: TTIProvider): BaseTTIProvider | undefined;
  listAllModels(): Array<{ provider: TTIProvider; models: ModelInfo[] }>;
}

TTIRequest

interface TTIRequest {
  prompt: string;
  model?: string;           // 'imagen-3', 'imagen-4', 'gemini-flash-image', 'gemini-pro-image', etc.
  n?: number;               // Number of images (default: 1)
  aspectRatio?: string;     // '1:1', '16:9', '4:3', etc.

  // Character consistency
  referenceImages?: TTIReferenceImage[];
  subjectDescription?: string;

  // Retry configuration
  retry?: boolean | RetryOptions;  // true (default), false, or custom config

  providerOptions?: Record<string, unknown>;
}

TTIResponse

interface TTIResponse {
  images: TTIImage[];
  metadata: {
    provider: string;
    model: string;
    region?: string;
    duration: number;
  };
  usage: {
    imagesGenerated: number;
    modelId: string;
  };
  billing?: {          // Only if provider returns costs
    cost: number;
    currency: string;
    source: 'provider' | 'estimated';
  };
}

Advanced Features

Region Rotation (Google Cloud)

When Vertex AI returns 429 (Resource Exhausted) due to Dynamic Shared Quota, the middleware can rotate through a list of regions instead of retrying the same exhausted region:

const provider = new GoogleCloudTTIProvider({
  projectId: 'my-project',
  region: 'europe-west4',
  regionRotation: {
    regions: ['europe-west4', 'europe-west1', 'europe-north1', 'europe-central2'],
    fallback: 'global',
    alwaysTryFallback: true, // Default: one bonus attempt on fallback after budget exhausted
  },
});

Key behavior:

  • maxRetries is the total budget across all regions (no multiplier)
  • Only quota errors (429, Resource Exhausted) trigger rotation — server errors (500, 503) retry the same region
  • alwaysTryFallback: true (default): one bonus attempt on fallback even if retry budget is exhausted
  • Without regionRotation: existing behavior unchanged
Retry Configuration

Automatic retry with exponential backoff and jitter for transient errors (429, 408, 5xx, network timeouts). Follows Google Cloud best practices.

// Default: 3 retries, exponential backoff (1s → 2s → 4s), jitter enabled
const result = await service.generate({
  prompt: 'A sunset over mountains',
  model: 'imagen-3',
  // retry: true (default)
});

// Custom retry configuration
const result = await service.generate({
  prompt: 'A sunset over mountains',
  model: 'imagen-3',
  retry: {
    maxRetries: 5,
    delayMs: 1000,
    backoffMultiplier: 2.0,  // 1s, 2s, 4s, 8s, 16s
    maxDelayMs: 30000,       // Cap at 30s
    jitter: true,            // Randomize to prevent thundering herd
  },
});

// Disable retry
const result = await service.generate({
  prompt: 'A sunset over mountains',
  model: 'imagen-3',
  retry: false,
});

Retryable errors: 429, 408, 500, 502, 503, 504, timeouts, ECONNRESET, ECONNREFUSED, socket hang up Not retried: 400, 401, 403, and other client errors

Option Default Description
maxRetries 3 Maximum retry attempts
delayMs 1000 Base delay between retries (ms)
backoffMultiplier 2.0 Exponential multiplier per attempt
maxDelayMs 30000 Maximum delay cap (ms)
jitter true Randomize delay to prevent thundering herd
Logging Configuration

Control logging via environment variable or API:

import { setLogLevel } from '@loonylabs/tti-middleware';

// Set log level programmatically
setLogLevel('warn');  // Only show warnings and errors

// Or via environment variable
// TTI_LOG_LEVEL=error

Available levels: debug, info, warn, error, silent

Debug Logging (Markdown Files)

Log all TTI requests and responses to markdown files for debugging:

import { TTIDebugger } from '@loonylabs/tti-middleware';

// Enable via environment variable
// DEBUG_TTI_REQUESTS=true

// Or programmatically
TTIDebugger.setEnabled(true);
TTIDebugger.setLogsDir('./logs/tti/requests');

// Configure all options at once
TTIDebugger.configure({
  enabled: true,
  logsDir: './logs/tti/requests',
  consoleLog: true,      // Also log to console
  includeBase64: false,  // Exclude base64 data (default)
});

Log file contents:

  • Provider, model, and region
  • Full prompt text
  • Subject description (for character consistency)
  • Reference image metadata
  • Response data (duration, image count)
  • Errors with full details

Use case: Debug why character consistency isn't working by inspecting exactly what prompt and subjectDescription are being sent to the API.

Error Handling

Typed error classes for precise error handling:

import {
  TTIError,
  InvalidConfigError,
  QuotaExceededError,
  ProviderUnavailableError,
  GenerationFailedError,
  NetworkError,
  CapabilityNotSupportedError,
} from '@loonylabs/tti-middleware';

try {
  const result = await service.generate({ prompt: 'test' });
} catch (error) {
  if (error instanceof QuotaExceededError) {
    console.log('Rate limit hit, try again later');
  } else if (error instanceof CapabilityNotSupportedError) {
    console.log('Model does not support this feature');
  } else if (error instanceof TTIError) {
    console.log(`TTI Error [${error.code}]: ${error.message}`);
  }
}

Testing

# Run all tests
npm test

# Unit tests only (123 tests, >95% coverage)
npm run test:unit

# Unit tests with watch mode
npm run test:unit:watch

# Unit tests with coverage report
npm run test:unit:coverage

# Integration tests (requires TTI_INTEGRATION_TESTS=true)
npm run test:integration

# CI/CD mode (unit tests only, in band)
npm run test:ci

# Manual test scripts
npm run test:manual:google-cloud

Integration Tests

Integration tests make real API calls. They are skipped by default.

# Enable and run integration tests
TTI_INTEGRATION_TESTS=true npm run test:integration

Prerequisites:

  • GOOGLE_CLOUD_PROJECT environment variable
  • GOOGLE_APPLICATION_CREDENTIALS pointing to service account JSON

Documentation

Contributing

We welcome contributions! Please ensure:

  1. Tests: Add tests for new features

  2. Linting: Run npm run lint before committing

  3. Conventions: Follow the existing project structure

  4. Fork the repository

  5. Create your feature branch (git checkout -b feature/amazing-feature)

  6. Commit your changes (git commit -m 'Add some amazing feature')

  7. Push to the branch (git push origin feature/amazing-feature)

  8. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Links


Made with care by the LoonyLabs Team

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