A complete Nano Banana Pro developer tutorial, from getting started to advanced usage.

Nano Banana Pro Full Developer Tutorial

Welcome to the Nano Banana Pro full developer tutorial! This guide will help you get the most out of the core AI image generation technology behind the Nonabanana Images platform.

🚀 Getting Started

Prerequisites

Basic understanding of image generation concepts.
A Nonabanana Images account.
Familiarity with writing text prompts.

Account Setup

Create an account: Visit Nonabanana Images and sign up.
Choose a plan: Select a subscription plan that fits your needs.
API key: Obtain your API key for integration and development.

📚 Core Concepts

What is Nano Banana Pro?

Nano Banana Pro is the core AI image generation model of the Nonabanana Images platform, built with state-of-the-art deep learning techniques:

High-resolution output: Supports up to 4K resolution.
Multiple styles: Photorealistic, anime, oil painting, abstract, and more.
Fast generation: Second-level response times.
Business-friendly: Licensing suitable for commercial projects.

Model providers and infrastructure

Nonabanana Images and Nano Banana Pro are independent products created and operated by our team and are not affiliated with, sponsored by, or officially endorsed by Google, the Gemini team, Fal, or any other model providers.
Our service provides a custom interface and workflow on top of AI models (including models powered by Gemini and models hosted by Fal via third-party providers) to make image generation easier to use and to offer additional features.
There is currently no "official Nano Banana" product sold by Google; any purchase on nanobananaimages.com is a purchase of our independent service, not an official Google or Gemini product.
The underlying model infrastructure and compute are operated by the respective model providers.

How It Works (High Level)

graph TD
    A[Text prompt] --> B[NLP parsing]
    B --> C[Semantic understanding]
    C --> D[Image generation]
    D --> E[Post-processing]
    E --> F[High-quality output]

🛠️ API Usage Guide

Basic API Call

// Basic image generation
const response = await fetch('https://api.nanobananaimages.com/v1/generate', {
  method: 'POST',
  headers: {
    Authorization: 'Bearer YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    prompt: 'A cute kitten playing in the sunshine',
    width: 1024,
    height: 1024,
    style: 'realistic',
  }),
});

const result = await response.json();

Advanced Parameters

const advancedConfig = {
  prompt:
    'A futuristic city skyline at night with strong sci-fi vibes, neon lights glowing',
  negative_prompt: 'blurry, low quality, distorted',
  width: 1920,
  height: 1080,
  steps: 30,
  guidance_scale: 7.5,
  style_preset: 'cinematic',
  seed: 12345,
  num_images: 4,
};

💡 Prompt Engineering Tips

Effective Prompt Structure

Basic structure:

[Subject] + [Scene] + [Style] + [Details]

Example:

'A golden retriever running on the beach at sunset, oil painting style, highly detailed fur'

Prompt Optimization Strategies

1. Be specific

❌ Vague: a dog
✅ Specific: a golden retriever with golden fur, friendly expression, standing on green grass

2. Add style keywords

- Photorealistic: photorealistic, detailed, high resolution
- Anime: anime style, manga, cel shading
- Artistic: oil painting, watercolor, impressionist

3. Control composition

- Close-up: close-up, portrait
- Wide: wide angle, landscape
- Top-down: bird's eye view
- Low angle: low angle shot

🎨 Styles and Parameter Control

Style Presets

Style name	Description	Typical use cases
Realistic	Photo-realistic	Product shots, portraits
Anime	Japanese anime style	Character design, illustration
Cinematic	Film-like cinematic look	Scene design, concept art
Oil Painting	Oil painting style	Art creation, wall art
Abstract	Abstract art	Modern design, background textures

Key Parameters

Guidance Scale

Range: 1–20
Recommended: 7–12
What it does: Controls how strictly the model follows your prompt.

Low (1–5): more creative freedom
Medium (6–10): balance between creativity and accuracy
High (11–20): strictly follow the prompt description

Steps (Number of Iterations)

Range: 10–50
Recommended: 20–30
What it does: Affects image quality and generation time.

Quick preview: 10–15 steps
Standard quality: 20–25 steps
High quality: 30–50 steps

🔧 Advanced Features

Batch Generation

const batchGeneration = {
  prompt: 'Four seasons landscape series',
  variations: [
    'Spring cherry blossoms in full bloom',
    'Summer beach sunset',
    'Autumn maple leaves falling',
    'Peaceful winter snow scenery',
  ],
  style: 'landscape photography',
};

Image Editing and Expansion

Outpainting (Extend the Image)

const outpaintConfig = {
  image: 'base64_encoded_image',
  direction: 'right',
  expansion_factor: 1.5,
  prompt: 'Natural extension that continues the existing scene style',
};

Inpainting (Local Editing)

const inpaintConfig = {
  image: 'base64_encoded_image',
  mask: 'base64_mask',
  prompt: 'Description of the new content to replace the masked area',
};

🚀 Performance Optimization

Caching Strategy

// Simple smart cache implementation
class ImageGenerator {
  constructor() {
    this.cache = new Map();
  }

  async generate(prompt, config = {}) {
    const cacheKey = this.generateCacheKey(prompt, config);

    if (this.cache.has(cacheKey)) {
      return this.cache.get(cacheKey);
    }

    const result = await this.callAPI(prompt, config);
    this.cache.set(cacheKey, result);

    return result;
  }
}

Concurrency

// Generate multiple images in parallel
async function generateBatch(prompts) {
  const promises = prompts.map((prompt) => generateImage(prompt));

  const results = await Promise.all(promises);
  return results;
}

📊 Quality Evaluation and Improvement

Quality Metrics

Sharpness: Are image details rich and clear?
Accuracy: Does the image match the prompt?
Consistency: Is the style consistent across images?
Creativity: Does the result have unique value?

Improvement Strategies

1. Iterative Improvement

const iterativeImprovement = async (basePrompt) => {
  let bestResult = null;
  let bestScore = 0;

  for (let i = 0; i < 5; i++) {
    const variations = generatePromptVariations(basePrompt);
    const result = await generateAndEvaluate(variations);

    if (result.score > bestScore) {
      bestScore = result.score;
      bestResult = result;
    }
  }

  return bestResult;
};

2. A/B Testing

const abTest = async (prompt, variations) => {
  const results = await Promise.all(
    variations.map((variant) => generateImage(variant)),
  );

  return evaluateAndRank(results);
};

🛡️ Best Practices

1. Prompt Writing Principles

Be specific: Avoid vague descriptions.
Keep structure clear: Use a logical order.
Maintain style consistency: Use consistent style terminology.

2. Parameter Tuning Strategies

Adjust gradually: Tweak parameters step by step.
Record experiments: Save successful parameter combinations.
Test in batches: Compare results under different settings.

3. Error Handling

const robustGeneration = async (prompt, config) => {
  try {
    const result = await generateImage(prompt, config);
    return result;
  } catch (error) {
    console.error('Generation failed:', error);

    // Fallback strategy
    const fallbackConfig = {
      ...config,
      steps: Math.max(config.steps - 5, 10),
      guidance_scale: 7.0,
    };

    return await generateImage(prompt, fallbackConfig);
  }
};

🔗 Integration Examples

React Component Integration

import React, { useState } from 'react';

const ImageGeneratorComponent = () => {
  const [prompt, setPrompt] = useState('');
  const [image, setImage] = useState(null);
  const [loading, setLoading] = useState(false);

  const handleGenerate = async () => {
    setLoading(true);
    try {
      const result = await generateImage(prompt);
      setImage(result.url);
    } catch (error) {
      console.error('Generation failed:', error);
    } finally {
      setLoading(false);
    }
  };

  return (
    <div className="image-generator">
      <input
        type="text"
        value={prompt}
        onChange={(e) => setPrompt(e.target.value)}
        placeholder="Describe the image you want to generate..."
      />
      <button onClick={handleGenerate} disabled={loading || !prompt}>
        {loading ? 'Generating...' : 'Generate image'}
      </button>

      {image && <img src={image} alt="Generated" className="result-image" />}
    </div>
  );
};

Node.js Backend Service

const express = require('express');
const app = express();

app.post('/api/generate', async (req, res) => {
  try {
    const { prompt, config } = req.body;

    // Basic validation
    if (!prompt || prompt.length < 10) {
      return res.status(400).json({
        error: 'Prompt is too short, please provide a more detailed description.',
      });
    }

    const result = await generateImage(prompt, config);

    res.json({
      success: true,
      imageUrl: result.url,
      metadata: {
        prompt,
        config,
        generatedAt: new Date().toISOString(),
      },
    });
  } catch (error) {
    console.error('API Error:', error);
    res.status(500).json({
      error: 'Image generation failed, please try again later.',
    });
  }
});

app.listen(3000, () => {
  console.log('Nano Banana Pro API server started on port 3000');
});

📈 Monitoring and Analytics

Usage Analytics

const analytics = {
  trackGeneration: (prompt, config, result) => {
    const data = {
      timestamp: new Date().toISOString(),
      promptLength: prompt.length,
      config,
      success: result.success,
      generationTime: result.generationTime,
    };

    // Send to your analytics service
    sendToAnalytics(data);
  },
};

Performance Monitoring

const performanceMonitor = {
  measureGeneration: async (generateFunction) => {
    const startTime = performance.now();

    const result = await generateFunction();

    const endTime = performance.now();
    const duration = endTime - startTime;

    console.log(`Generation time: ${duration.toFixed(2)}ms`);

    return {
      ...result,
      generationTime: duration,
    };
  },
};

🔮 Looking Ahead

Nano Banana Pro is continuously evolving. Upcoming features include:

3D image generation: Support for stereoscopic/3D content.
Video generation: From still images to short video clips.
Real-time collaboration: Multi-user collaborative editing.
AI-assisted prompts: Smart prompt suggestions and improvements.

🆘 Troubleshooting

Common Issues

Q: Image generation failed
A: Check your API key, network connection, and prompt format.

Q: Image quality is poor
A: Refine your prompt, adjust parameters, and increase the number of steps.

Q: Generation is slow
A: Lower the resolution or reduce the number of steps, and check your network.

Q: Style is not what I expected
A: Specify style keywords clearly and refer to the style guide above.

Getting Help

Documentation center: https://docs.nanobananaimages.com
Community forum: https://community.nanobananaimages.com
Technical support: support@nanobananaimages.com
GitHub: https://github.com/nanobanana/pro-sdk

Congratulations! You have completed the Nano Banana Pro full developer tutorial. You are now ready to start creating stunning AI-generated images.

Remember: creativity is limitless, and technology is the bridge. Let Nano Banana Pro be the powerful tool that turns your ideas into reality.

Nano Banana Pro Guide

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