Generate Image: GET https://image.pollinations.ai/prompt/{prompt}
- Params: prompt*, model, seed, width, height, nologo, private, enhance, safe
- Return: Image file
List Models: GET https://image.pollinations.ai/models
Generate (GET): GET https://text.pollinations.ai/{prompt}
- Params: prompt*, model, seed, json, system
- Return: Generated text
Generate (POST): POST https://text.pollinations.ai/
- Body: messages*, model, seed, jsonMode
- Return: Generated text
OpenAI Compatible: POST https://text.pollinations.ai/openai
- Body: Follows OpenAI ChatGPT API format
- Return: OpenAI-style response
List Models: GET https://text.pollinations.ai/models
// React code example using usePollinationsImage hook
// For more details, visit: https://react-hooks.pollinations.ai/
import React from 'react';
import { usePollinationsImage } from '@pollinations/react';
const GeneratedImageComponent = () => {
const imageUrl = usePollinationsImage('your prompt here', {
width: 1024,
height: 1024,
seed: 123,
model: 'flux'
});
return (
<div>
{imageUrl ? <img src={imageUrl} alt="Generated Image" /> : <p>Loading...</p>}
</div>
);
};
export default GeneratedImageComponent;
<html>
<body>
<h2>Image Parameters</h2>
<p>Prompt: your prompt here</p>
<p>Width: 1024</p>
<p>Height: 1024</p>
<p>Seed: 123 <i>Each seed generates a new image variation</i></p>
<p>Model: flux</p>
<img
src="https://image.pollinations.ai/prompt/your%20prompt%20here"
alt="Generated Image"
/>
</body>
</html>
GET https://image.pollinations.ai/feed
- Description: Provides a real-time stream of images generated by users.
- Usage: Connect using an SSE-compatible client to receive continuous image data.
- Example:
const eventSource = new EventSource('https://image.pollinations.ai/feed');
eventSource.onmessage = function(event) {
const imageData = JSON.parse(event.data);
console.log('New image generated:', imageData);
};
GET https://text.pollinations.ai/feed
- Description: Provides a real-time stream of text generated by users.
- Usage: Connect using an SSE-compatible client to receive continuous text data.
- Example:
const eventSource = new EventSource('https://text.pollinations.ai/feed');
eventSource.onmessage = function(event) {
const textData = JSON.parse(event.data);
console.log('New text generated:', textData);
};
import requests
def generate_video(prompt, duration=10, resolution='1080p', model='video-gen', seed=None):
url = "https://video.pollinations.ai/generate"
payload = {
"prompt": prompt,
"model": model,
"duration": duration,
"resolution": resolution,
"seed": seed
}
response = requests.post(url, json=payload)
with open('generated_video.mp4', 'wb') as file:
file.write(response.content)
print('Video downloaded!')
generate_video("A futuristic cityscape", duration=10, resolution='1080p', model='video-gen', seed=42)
const fetch = require('node-fetch');
async function generateVideo() {
const response = await fetch('https://video.pollinations.ai/generate', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
},
body: JSON.stringify({
prompt: "A futuristic cityscape",
model: "video-gen",
duration: 10,
resolution: "1080p",
seed: 42
}),
});
const data = await response.buffer();
const fs = require('fs');
fs.writeFileSync('generated_video.mp4', data);
console.log('Video downloaded!');
}
generateVideo();