🌸 Pollinations MVP - Image Generation API

A simplified MVP version of Pollinations.AI focusing on core image generation functionality.

🚀 Features

• ✨ Simple Image Generation - Generate images from text prompts via URL
• 🎨 FLUX Model Support - Uses advanced AI models for high-quality images
• 🔧 Customizable Parameters - Control width, height, seed, and more
• ⚡ Fast & Lightweight - Minimal dependencies, easy to deploy
• 🆓 Free to Use - No API keys required for basic usage

📦 Installation

# Clone the repository
git clone https://github.com/gitmvp-com/pollinations-mvp.git
cd pollinations-mvp

# Install dependencies
npm install

# Copy environment configuration
cp .env.example .env

# Start the server
npm start

🎯 Quick Start

Start the Server

npm start

The server will start on http://localhost:16384

Generate Your First Image

Open your browser or use curl:

# Simple generation
curl -o image.jpg "http://localhost:16384/prompt/a%20beautiful%20sunset%20over%20mountains"

# With custom parameters
curl -o image.jpg "http://localhost:16384/prompt/cyberpunk%20city?width=1920&height=1080&seed=42"

🔧 API Usage

Generate Image

Endpoint: GET /prompt/{prompt}

Parameters:

Parameter	Type	Default	Description
width	integer	1024	Image width in pixels
height	integer	1024	Image height in pixels
seed	integer	random	Seed for reproducible results
model	string	flux	Model to use (flux, turbo)
enhance	boolean	false	Auto-enhance prompt

Example:

# Generate a landscape image
curl "http://localhost:16384/prompt/mountain%20landscape?width=1920&height=1080&seed=123" > landscape.jpg

# Generate with enhanced prompt
curl "http://localhost:16384/prompt/cute%20cat?enhance=true" > cat.jpg

List Available Models

Endpoint: GET /models

curl http://localhost:16384/models

Response:

["flux", "turbo"]

🌐 Integration Examples

Python

import requests
from urllib.parse import quote

prompt = "A serene mountain landscape at sunrise"
url = f"http://localhost:16384/prompt/{quote(prompt)}"
params = {"width": 1280, "height": 720, "seed": 42}

response = requests.get(url, params=params)
with open("image.jpg", "wb") as f:
    f.write(response.content)

print("Image generated successfully!")

JavaScript (Node.js)

import fetch from 'node-fetch';
import fs from 'fs';

const prompt = "A futuristic city with flying cars";
const url = `http://localhost:16384/prompt/${encodeURIComponent(prompt)}?width=1280&height=720`;

const response = await fetch(url);
const buffer = await response.buffer();
fs.writeFileSync('city.jpg', buffer);

console.log('Image generated successfully!');

HTML (Direct Image)

<img src="http://localhost:16384/prompt/beautiful%20sunset?width=800&height=600" 
     alt="AI Generated Sunset" />

🏗️ Architecture

This MVP is intentionally simple:

┌─────────────────┐
│  Client Request │
│  /prompt/...    │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│   HTTP Server   │
│  (Node.js)      │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  Rate Limiter   │
│  (IP-based)     │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│ Image Generator │
│ (FLUX API)      │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  Return Image   │
│   (JPEG/PNG)    │
└─────────────────┘

📁 Project Structure

pollinations-mvp/
├── src/
│   ├── index.js          # Main server
│   ├── generator.js      # Image generation logic
│   ├── rateLimiter.js    # Simple rate limiting
│   └── utils.js          # Helper functions
├── .env.example          # Environment template
├── package.json          # Dependencies
└── README.md            # Documentation

🔐 Configuration

Edit .env to customize:

# Server port
PORT=16384

# Image generation API (default: Pollinations public API)
IMAGE_API_URL=https://image.pollinations.ai/prompt

# Rate limiting (milliseconds between requests)
RATE_LIMIT_INTERVAL=30000

🚀 Deployment

Docker

# Build
docker build -t pollinations-mvp .

# Run
docker run -p 16384:16384 pollinations-mvp

Node.js

# Production mode
NODE_ENV=production npm start

🤝 Differences from Full Pollinations.AI

This MVP focuses on simplicity and includes only:

✅ Included:

• Basic image generation
• Simple rate limiting
• Model selection (flux, turbo)
• Parameter customization

❌ Not Included (in full version):

• Advanced authentication system
• Multiple backend services
• Real-time feeds
• Audio generation
• Text generation
• Vision/multimodal features
• React hooks library
• Advanced caching strategies
• Content safety filters
• Analytics & telemetry

📚 Learn More

• Full Pollinations.AI: github.com/pollinations/pollinations
• API Documentation: Pollinations API Docs
• Website: pollinations.ai

📄 License

MIT License - see LICENSE file for details.

🙏 Credits

This MVP is inspired by the amazing work of the Pollinations.AI team. This is a simplified educational version focusing on core image generation features.

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Made with ❤️ for learning and experimentation