API Integration Tutorial

Integrate GemPix 2 into your applications. Complete API docs, code examples in Python/Node.js, webhook setup, and error handling.

API Integration Tutorial

The GemPix 2 web interface is powerful for manual creation. The API is essential for automation, integration, and scaling to thousands of generations. Whether you're building a SaaS product, automating marketing workflows, or creating custom tools, the GemPix 2 API provides programmatic access to all platform features.

This comprehensive developer guide covers authentication, all available endpoints, request/response formats, error handling, rate limits, code examples in Python and JavaScript, webhook integration, and production best practices. By the end, you'll have working code to integrate GemPix 2 into your applications and workflows.

The API follows RESTful principles, uses JSON for all requests and responses, and supports all features available in the web interface including [[features/character-consistency]], [[features/conversational-editing]], [[features/multi-image-fusion]], and [[features/precise-local-edits]].

Getting Started with the API

Authentication and API Keys

Obtaining your API key:

  1. Log in to your GemPix 2 account
  2. Navigate to Settings → Developer → API Keys
  3. Click "Generate New API Key"
  4. Copy and securely store your key (shown only once)
  5. Name your key for organization (e.g., "Production App", "Testing")

API key format:

gp2_live_1234567890abcdef1234567890abcdef1234567890abcdef

Security best practices:

  • Never commit API keys to version control
  • Use environment variables: GEMPIX2_API_KEY
  • Rotate keys every 90 days
  • Use separate keys for development, staging, production
  • Revoke keys immediately if compromised

Authentication method:

All API requests require authentication via Bearer token in the Authorization header:

Authorization: Bearer gp2_live_1234567890abcdef1234567890abcdef1234567890abcdef

Base URL and Endpoints

Base URL:

https://api.gempix2go.com/v1

Available endpoints:

  • POST /generate - Generate new image from prompt
  • POST /edit - Conversational editing of existing image
  • POST /fusion - Multi-image fusion
  • POST /local-edit - Precise local editing
  • GET /generation/\{id\} - Retrieve generation status and result
  • GET /history - List generation history
  • DELETE /generation/\{id\} - Delete generation
  • GET /account - Account information and credit balance
  • POST /upscale - Upscale existing image

Quick Start Examples

Python example:

import requests
import os

API_KEY = os.environ['GEMPIX2_API_KEY']
BASE_URL = 'https://api.gempix2go.com/v1'

headers = {
    'Authorization': f'Bearer {API_KEY}',
    'Content-Type': 'application/json'
}

# Generate image
payload = {
    'prompt': 'Professional office interior, modern minimalist design, natural lighting',
    'resolution': '1024x1024',
    'quality': 'high'
}

response = requests.post(
    f'{BASE_URL}/generate',
    headers=headers,
    json=payload
)

if response.status_code == 200:
    result = response.json()
    print(f"Generation ID: {result['id']}")
    print(f"Image URL: {result['image_url']}")
    print(f"Credits used: {result['credits_used']}")
else:
    print(f"Error: {response.status_code} - {response.json()}")

JavaScript/Node.js example:

const axios = require('axios');

const API_KEY = process.env.GEMPIX2_API_KEY;
const BASE_URL = 'https://api.gempix2go.com/v1';

const headers = {
  'Authorization': `Bearer ${API_KEY}`,
  'Content-Type': 'application/json'
};

// Generate image
async function generateImage() {
  try {
    const response = await axios.post(
      `${BASE_URL}/generate`,
      {
        prompt: 'Professional office interior, modern minimalist design, natural lighting',
        resolution: '1024x1024',
        quality: 'high'
      },
      { headers }
    );

    console.log(`Generation ID: ${response.data.id}`);
    console.log(`Image URL: ${response.data.image_url}`);
    console.log(`Credits used: ${response.data.credits_used}`);
  } catch (error) {
    console.error(`Error: ${error.response.status} - ${error.response.data}`);
  }
}

generateImage();

Core API Endpoints

POST /generate - Generate New Image

Description: Creates a new image from a text prompt with optional features.

Request parameters:

{
  "prompt": "string (required, max 2000 characters)",
  "resolution": "string (optional, default: '1024x1024')",
  "quality": "string (optional, default: 'standard')",
  "character_reference_id": "string (optional)",
  "negative_prompt": "string (optional, max 500 characters)",
  "style_preset": "string (optional)",
  "aspect_ratio": "string (optional)"
}

Parameter details:

  • prompt: Text description of desired image
  • resolution: Options: 512x512, 1024x1024, 2048x2048, 4096x4096
  • quality: Options: standard (fast), high (better), ultra (best)
  • character_reference_id: ID of previous generation to use for [[features/character-consistency]]
  • negative_prompt: Elements to avoid in generation
  • style_preset: Predefined styles: photographic, digital_art, cinematic, anime, 3d_render
  • aspect_ratio: Options: 1:1, 16:9, 9:16, 4:3, 3:4, 21:9

Response:

{
  "id": "gen_1234567890abcdef",
  "status": "completed",
  "image_url": "https://cdn.gempix2go.com/generations/gen_1234567890abcdef.png",
  "thumbnail_url": "https://cdn.gempix2go.com/thumbnails/gen_1234567890abcdef.jpg",
  "prompt": "Professional office interior...",
  "resolution": "1024x1024",
  "quality": "high",
  "credits_used": 5,
  "created_at": "2025-11-07T14:32:10Z",
  "metadata": {
    "generation_time_ms": 2340,
    "model_version": "gemini-3-pro-v2.1"
  }
}

Status codes:

  • 200 OK: Generation completed successfully
  • 202 Accepted: Generation queued (check status with GET /generation/{id})
  • 400 Bad Request: Invalid parameters
  • 401 Unauthorized: Invalid API key
  • 402 Payment Required: Insufficient credits
  • 429 Too Many Requests: Rate limit exceeded
  • 500 Internal Server Error: Server error

Python example with all features:

import requests
import os

API_KEY = os.environ['GEMPIX2_API_KEY']
BASE_URL = 'https://api.gempix2go.com/v1'

headers = {
    'Authorization': f'Bearer {API_KEY}',
    'Content-Type': 'application/json'
}

# Advanced generation with character consistency
payload = {
    'prompt': 'Same character sitting at outdoor cafe, holding coffee cup, relaxed expression',
    'resolution': '2048x2048',
    'quality': 'high',
    'character_reference_id': 'gen_abc123previousgen',  # From previous generation
    'negative_prompt': 'blurry, low quality, distorted',
    'style_preset': 'photographic'
}

response = requests.post(
    f'{BASE_URL}/generate',
    headers=headers,
    json=payload,
    timeout=60
)

result = response.json()

if response.status_code == 200:
    print(f"✓ Generation successful")
    print(f"  ID: {result['id']}")
    print(f"  URL: {result['image_url']}")
    print(f"  Credits: {result['credits_used']}")
    print(f"  Time: {result['metadata']['generation_time_ms']}ms")
elif response.status_code == 202:
    print(f"⏳ Generation queued: {result['id']}")
    print(f"   Check status at: /generation/{result['id']}")
else:
    print(f"✗ Error {response.status_code}: {result.get('error', 'Unknown error')}")

POST /edit - Conversational Editing

Description: Applies iterative edits to existing generation using natural language.

Request parameters:

{
  "generation_id": "string (required)",
  "edit_prompt": "string (required, max 500 characters)",
  "preserve_consistency": "boolean (optional, default: true)"
}

Parameter details:

  • generation_id: ID of existing generation to edit
  • edit_prompt: Natural language editing instruction
  • preserve_consistency: Maintain original style and composition

Response: Same format as /generate endpoint

Python example:

# Edit existing generation
edit_payload = {
    'generation_id': 'gen_1234567890abcdef',
    'edit_prompt': 'Change background to sunset lighting',
    'preserve_consistency': True
}

response = requests.post(
    f'{BASE_URL}/edit',
    headers=headers,
    json=edit_payload
)

result = response.json()
print(f"Edited image URL: {result['image_url']}")
print(f"Credits used: {result['credits_used']}")

JavaScript example with chained edits:

async function chainedEditing(generationId) {
  const edits = [
    'Make the lighting warmer',
    'Add a laptop on the desk',
    'Change shirt color to blue'
  ];

  let currentId = generationId;

  for (const editPrompt of edits) {
    const response = await axios.post(
      `${BASE_URL}/edit`,
      {
        generation_id: currentId,
        edit_prompt: editPrompt,
        preserve_consistency: true
      },
      { headers }
    );

    currentId = response.data.id;
    console.log(`Applied edit: "${editPrompt}" → ${currentId}`);
  }

  console.log(`Final edited image: ${currentId}`);
  return currentId;
}

POST /fusion - Multi-Image Fusion

Description: Combines multiple images into single composition.

Request parameters:

{
  "source_images": [
    {
      "generation_id": "string (optional)",
      "url": "string (optional)",
      "role": "string (required)"
    }
  ],
  "composition_prompt": "string (required, max 1000 characters)",
  "resolution": "string (optional, default: '1024x1024')",
  "quality": "string (optional, default: 'standard')"
}

Parameter details:

  • source_images: Array of 2-5 images to fuse
    • generation_id: Reference existing GemPix 2 generation
    • url: External image URL (must be publicly accessible)
    • role: Image purpose: foreground, background, element, reference
  • composition_prompt: Detailed description of how to combine images
  • resolution: Output resolution
  • quality: Generation quality level

Python example:

fusion_payload = {
    'source_images': [
        {
            'generation_id': 'gen_product123',
            'role': 'foreground'
        },
        {
            'url': 'https://example.com/background.jpg',
            'role': 'background'
        }
    ],
    'composition_prompt': 'Place product in center of lifestyle scene, natural lighting integration, professional product photography',
    'resolution': '2048x2048',
    'quality': 'high'
}

response = requests.post(
    f'{BASE_URL}/fusion',
    headers=headers,
    json=fusion_payload
)

result = response.json()
print(f"Fused image: {result['image_url']}")

JavaScript example - batch product placement:

async function batchProductFusion(productId, backgrounds) {
  const results = [];

  for (const bg of backgrounds) {
    const response = await axios.post(
      `${BASE_URL}/fusion`,
      {
        source_images: [
          { generation_id: productId, role: 'foreground' },
          { generation_id: bg.id, role: 'background' }
        ],
        composition_prompt: `Place product naturally in ${bg.description}, match lighting, professional photography`,
        resolution: '2048x2048',
        quality: 'high'
      },
      { headers }
    );

    results.push({
      background: bg.description,
      image_url: response.data.image_url,
      id: response.data.id
    });

    // Rate limiting: wait 1 second between requests
    await new Promise(resolve => setTimeout(resolve, 1000));
  }

  return results;
}

// Usage
const backgrounds = [
  { id: 'gen_kitchen', description: 'modern kitchen scene' },
  { id: 'gen_office', description: 'professional office desk' },
  { id: 'gen_outdoor', description: 'outdoor patio setting' }
];

const fusions = await batchProductFusion('gen_product123', backgrounds);

POST /local-edit - Precise Local Editing

Description: Applies surgical edits to specific regions of image.

Request parameters:

{
  "generation_id": "string (required)",
  "region": {
    "x": "number (required, 0-1 normalized)",
    "y": "number (required, 0-1 normalized)",
    "width": "number (required, 0-1 normalized)",
    "height": "number (required, 0-1 normalized)"
  },
  "edit_prompt": "string (required, max 500 characters)"
}

Parameter details:

  • generation_id: ID of existing generation
  • region: Bounding box coordinates (normalized 0-1 scale)
    • (0, 0) = top-left corner
    • (1, 1) = bottom-right corner
  • edit_prompt: What to change in selected region

Python example:

# Edit specific region (center-right area)
local_edit_payload = {
    'generation_id': 'gen_1234567890abcdef',
    'region': {
        'x': 0.5,      # Start at 50% from left
        'y': 0.25,     # Start at 25% from top
        'width': 0.4,  # 40% of image width
        'height': 0.5  # 50% of image height
    },
    'edit_prompt': 'Change shirt color to navy blue'
}

response = requests.post(
    f'{BASE_URL}/local-edit',
    headers=headers,
    json=local_edit_payload
)

result = response.json()
print(f"Locally edited image: {result['image_url']}")

GET /generation/{id} - Retrieve Generation

Description: Get status and details of specific generation.

Request: No body, just path parameter

Response:

{
  "id": "gen_1234567890abcdef",
  "status": "completed",
  "image_url": "https://cdn.gempix2go.com/generations/gen_1234567890abcdef.png",
  "thumbnail_url": "https://cdn.gempix2go.com/thumbnails/gen_1234567890abcdef.jpg",
  "prompt": "Professional office interior...",
  "resolution": "1024x1024",
  "quality": "high",
  "credits_used": 5,
  "created_at": "2025-11-07T14:32:10Z",
  "completed_at": "2025-11-07T14:32:12Z",
  "metadata": {
    "generation_time_ms": 2340,
    "model_version": "gemini-3-pro-v2.1"
  }
}

Status values:

  • queued: Generation queued, not started yet
  • processing: Currently generating
  • completed: Successfully completed
  • failed: Generation failed (see error field)

Python polling example:

import time

def wait_for_generation(generation_id, max_wait=120, poll_interval=2):
    """Poll generation status until completed or timeout."""
    start_time = time.time()

    while time.time() - start_time < max_wait:
        response = requests.get(
            f'{BASE_URL}/generation/{generation_id}',
            headers=headers
        )

        result = response.json()
        status = result['status']

        if status == 'completed':
            print(f"✓ Generation completed in {result['metadata']['generation_time_ms']}ms")
            return result
        elif status == 'failed':
            raise Exception(f"Generation failed: {result.get('error', 'Unknown error')}")
        else:
            print(f"⏳ Status: {status}, waiting...")
            time.sleep(poll_interval)

    raise TimeoutError(f"Generation {generation_id} timed out after {max_wait}s")

# Usage
gen_result = wait_for_generation('gen_1234567890abcdef')
print(f"Image URL: {gen_result['image_url']}")

GET /history - List Generation History

Description: Retrieve paginated list of generations.

Query parameters:

  • page: Page number (default: 1)
  • per_page: Items per page (default: 20, max: 100)
  • status: Filter by status: completed, failed, all (default: all)
  • start_date: Filter from date (ISO 8601 format)
  • end_date: Filter to date (ISO 8601 format)

Request example:

params = {
    'page': 1,
    'per_page': 50,
    'status': 'completed',
    'start_date': '2025-11-01T00:00:00Z'
}

response = requests.get(
    f'{BASE_URL}/history',
    headers=headers,
    params=params
)

history = response.json()
print(f"Total: {history['total']}")
print(f"Page {history['page']} of {history['total_pages']}")

for gen in history['generations']:
    print(f"  {gen['id']}: {gen['prompt'][:50]}... ({gen['created_at']})")

GET /account - Account Information

Description: Retrieve account details and credit balance.

Response:

{
  "user_id": "user_abc123",
  "email": "[email protected]",
  "account_tier": "professional",
  "credits_balance": 1250,
  "credits_used_total": 8750,
  "generations_count": 432,
  "created_at": "2025-01-15T10:20:30Z",
  "api_rate_limit": {
    "requests_per_minute": 60,
    "requests_per_hour": 1000,
    "current_usage": {
      "minute": 15,
      "hour": 342
    }
  }
}

Python example:

response = requests.get(
    f'{BASE_URL}/account',
    headers=headers
)

account = response.json()
print(f"Credits remaining: {account['credits_balance']}")
print(f"Rate limit: {account['api_rate_limit']['requests_per_minute']}/min")
print(f"Current usage: {account['api_rate_limit']['current_usage']['minute']}/min")

Rate Limits and Quotas

Rate Limit Tiers

Free tier:

  • 10 requests per minute
  • 100 requests per hour
  • 500 requests per day

Starter tier:

  • 30 requests per minute
  • 500 requests per hour
  • 2,000 requests per day

Professional tier:

  • 60 requests per minute
  • 1,000 requests per hour
  • 10,000 requests per day

Enterprise tier:

  • 120 requests per minute
  • 5,000 requests per hour
  • Custom daily limits

Rate Limit Headers

All API responses include rate limit information:

X-RateLimit-Limit: 60
X-RateLimit-Remaining: 45
X-RateLimit-Reset: 1699387200

Python rate limit handling:

def check_rate_limits(response):
    """Extract and display rate limit info from response headers."""
    limit = response.headers.get('X-RateLimit-Limit')
    remaining = response.headers.get('X-RateLimit-Remaining')
    reset = response.headers.get('X-RateLimit-Reset')

    print(f"Rate limit: {remaining}/{limit} remaining")

    if int(remaining) < 10:
        reset_time = datetime.fromtimestamp(int(reset))
        print(f"⚠️  Low rate limit. Resets at {reset_time}")

    return int(remaining)

# Usage
response = requests.post(f'{BASE_URL}/generate', headers=headers, json=payload)
remaining = check_rate_limits(response)

if remaining < 5:
    print("Pausing to avoid rate limit...")
    time.sleep(60)

Handling Rate Limit Errors

429 Too Many Requests response:

{
  "error": "rate_limit_exceeded",
  "message": "Rate limit of 60 requests per minute exceeded",
  "retry_after": 45
}

Exponential backoff implementation:

import time
from requests.exceptions import RequestException

def generate_with_retry(payload, max_retries=3):
    """Generate with exponential backoff on rate limit errors."""
    for attempt in range(max_retries):
        try:
            response = requests.post(
                f'{BASE_URL}/generate',
                headers=headers,
                json=payload,
                timeout=60
            )

            if response.status_code == 200:
                return response.json()
            elif response.status_code == 429:
                retry_after = response.json().get('retry_after', 60)
                wait_time = min(retry_after * (2 ** attempt), 300)  # Max 5 minutes
                print(f"⚠️  Rate limited. Waiting {wait_time}s before retry {attempt + 1}/{max_retries}")
                time.sleep(wait_time)
            else:
                response.raise_for_status()

        except RequestException as e:
            if attempt == max_retries - 1:
                raise
            print(f"Request failed: {e}. Retrying...")
            time.sleep(2 ** attempt)

    raise Exception(f"Failed after {max_retries} retries")

# Usage
result = generate_with_retry({
    'prompt': 'Professional office interior',
    'resolution': '1024x1024'
})

Error Handling Best Practices

Standard Error Response Format

{
  "error": "error_code",
  "message": "Human-readable error description",
  "details": {
    "field": "Additional context about the error"
  }
}

Common Error Codes

Authentication errors:

  • invalid_api_key: API key is invalid or revoked
  • missing_api_key: Authorization header missing
  • expired_api_key: API key has expired (rotate required)

Validation errors:

  • invalid_prompt: Prompt contains prohibited content or exceeds limits
  • invalid_resolution: Unsupported resolution format
  • invalid_generation_id: Referenced generation doesn't exist or not accessible

Resource errors:

  • insufficient_credits: Not enough credits for operation
  • generation_not_found: Generation ID doesn't exist
  • image_not_accessible: External image URL inaccessible

Rate limiting:

  • rate_limit_exceeded: Too many requests (see retry_after)

Server errors:

  • internal_server_error: Unexpected server error
  • service_unavailable: Temporary service disruption

Comprehensive Error Handler

class GemPix2APIError(Exception):
    """Base exception for GemPix 2 API errors."""
    def __init__(self, status_code, error_code, message, details=None):
        self.status_code = status_code
        self.error_code = error_code
        self.message = message
        self.details = details or {}
        super().__init__(self.message)

def handle_api_response(response):
    """Parse API response and raise appropriate exceptions."""
    if response.status_code == 200:
        return response.json()

    try:
        error_data = response.json()
    except ValueError:
        error_data = {'error': 'unknown', 'message': response.text}

    error_code = error_data.get('error', 'unknown')
    message = error_data.get('message', 'Unknown error')
    details = error_data.get('details', {})

    raise GemPix2APIError(
        status_code=response.status_code,
        error_code=error_code,
        message=message,
        details=details
    )

# Usage
try:
    response = requests.post(f'{BASE_URL}/generate', headers=headers, json=payload)
    result = handle_api_response(response)
    print(f"Success: {result['id']}")

except GemPix2APIError as e:
    if e.error_code == 'insufficient_credits':
        print(f"⚠️  Need to add credits. Current balance: {e.details.get('current_balance', 0)}")
    elif e.error_code == 'invalid_prompt':
        print(f"✗ Invalid prompt: {e.message}")
        print(f"  Problematic terms: {e.details.get('flagged_terms', [])}")
    elif e.error_code == 'rate_limit_exceeded':
        retry_after = e.details.get('retry_after', 60)
        print(f"⏱  Rate limited. Retry after {retry_after}s")
    else:
        print(f"✗ API Error [{e.error_code}]: {e.message}")

except RequestException as e:
    print(f"✗ Network error: {e}")

Advanced Automation Patterns

Batch Generation with Concurrency

import concurrent.futures
import requests

def generate_single(prompt_data):
    """Generate single image with error handling."""
    try:
        response = requests.post(
            f'{BASE_URL}/generate',
            headers=headers,
            json=prompt_data,
            timeout=60
        )
        result = handle_api_response(response)
        return {
            'success': True,
            'id': result['id'],
            'url': result['image_url'],
            'prompt': prompt_data['prompt']
        }
    except Exception as e:
        return {
            'success': False,
            'error': str(e),
            'prompt': prompt_data['prompt']
        }

def batch_generate(prompts, max_workers=5):
    """Generate multiple images concurrently."""
    results = []

    with concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) as executor:
        future_to_prompt = {
            executor.submit(generate_single, prompt): prompt
            for prompt in prompts
        }

        for future in concurrent.futures.as_completed(future_to_prompt):
            result = future.result()
            results.append(result)

            if result['success']:
                print(f"✓ Generated: {result['id']}")
            else:
                print(f"✗ Failed: {result['error'][:50]}")

    successful = [r for r in results if r['success']]
    failed = [r for r in results if not r['success']]

    print(f"\n{'='*60}")
    print(f"Batch complete: {len(successful)} successful, {len(failed)} failed")
    print(f"{'='*60}")

    return results

# Usage
prompts = [
    {'prompt': 'Modern office interior, natural lighting', 'resolution': '1024x1024'},
    {'prompt': 'Cozy coffee shop, warm atmosphere', 'resolution': '1024x1024'},
    {'prompt': 'Professional headshot, business attire', 'resolution': '1024x1024'},
    # ... more prompts
]

results = batch_generate(prompts, max_workers=5)

Webhook Integration for Async Operations

For long-running generations, configure webhooks to receive completion notifications.

Setting up webhooks:

# Register webhook endpoint
webhook_payload = {
    'url': 'https://your-server.com/webhooks/gempix2',
    'events': ['generation.completed', 'generation.failed'],
    'secret': 'your_webhook_secret_key'
}

response = requests.post(
    f'{BASE_URL}/webhooks',
    headers=headers,
    json=webhook_payload
)

webhook_id = response.json()['webhook_id']
print(f"Webhook registered: {webhook_id}")

Webhook payload format:

{
  "event": "generation.completed",
  "generation_id": "gen_1234567890abcdef",
  "timestamp": "2025-11-07T14:32:12Z",
  "data": {
    "id": "gen_1234567890abcdef",
    "image_url": "https://cdn.gempix2go.com/generations/gen_1234567890abcdef.png",
    "credits_used": 5
  }
}

Flask webhook receiver example:

from flask import Flask, request, jsonify
import hmac
import hashlib

app = Flask(__name__)
WEBHOOK_SECRET = 'your_webhook_secret_key'

def verify_webhook_signature(payload, signature):
    """Verify webhook authenticity."""
    expected_signature = hmac.new(
        WEBHOOK_SECRET.encode(),
        payload,
        hashlib.sha256
    ).hexdigest()

    return hmac.compare_digest(signature, expected_signature)

@app.route('/webhooks/gempix2', methods=['POST'])
def handle_webhook():
    signature = request.headers.get('X-GemPix2-Signature')
    payload = request.get_data()

    if not verify_webhook_signature(payload, signature):
        return jsonify({'error': 'Invalid signature'}), 401

    event_data = request.json
    event_type = event_data['event']

    if event_type == 'generation.completed':
        generation_id = event_data['generation_id']
        image_url = event_data['data']['image_url']

        # Process completed generation
        print(f"✓ Generation {generation_id} completed: {image_url}")
        # Save to database, trigger next workflow step, etc.

    elif event_type == 'generation.failed':
        generation_id = event_data['generation_id']
        error = event_data['data'].get('error', 'Unknown error')

        # Handle failure
        print(f"✗ Generation {generation_id} failed: {error}")
        # Log error, retry, notify user, etc.

    return jsonify({'status': 'processed'}), 200

if __name__ == '__main__':
    app.run(port=5000)

The GemPix 2 API provides programmatic access to the full platform capabilities, enabling automation, integration, and scaling to production workflows generating thousands of images. The RESTful design, comprehensive error handling, rate limiting transparency, and webhook support make it suitable for applications ranging from simple scripts to enterprise SaaS products.

Start with the quick start examples, experiment with core endpoints, implement proper error handling and rate limiting, and progressively build more sophisticated automation. The API's design mirrors the web interface features—if you understand [[features/character-consistency]], [[features/conversational-editing]], and [[features/multi-image-fusion]] from manual use, translating them to API calls is straightforward.

For production deployments, review [[guides/advanced-techniques]] for batch optimization strategies and [[guides/troubleshooting]] for common integration issues. Monitor your rate limits, implement exponential backoff, validate inputs before API calls, and use webhooks for async operations exceeding 30 seconds.

The combination of powerful generation capabilities, flexible API design, and comprehensive documentation positions GemPix 2 as the foundation for next-generation visual content automation.

Gemini API Documentation provides additional context on the underlying AI capabilities.

Last updated: November 7, 2025

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