pollinations-api-client.js•7.26 kB
/**
* Pollinations API Client
*
* A simple client for the Pollinations APIs that doesn't require Cloudflare Workers
*/
/**
* Generates an image URL from a text prompt using the Pollinations Image API
*
* @param {string} prompt - The text description of the image to generate
* @param {Object} options - Additional options for image generation
* @param {string} [options.model] - Model name to use for generation
* @param {number} [options.seed] - Seed for reproducible results
* @param {number} [options.width=1024] - Width of the generated image
* @param {number} [options.height=1024] - Height of the generated image
* @returns {Object} - Object containing the image URL and metadata
*/
export async function generateImageUrl(prompt, options = {}) {
if (!prompt || typeof prompt !== 'string') {
throw new Error('Prompt is required and must be a string');
}
const {
model,
seed,
width = 1024,
height = 1024,
} = options;
// Build the query parameters
const queryParams = new URLSearchParams();
if (model) queryParams.append('model', model);
if (seed !== undefined) queryParams.append('seed', seed);
if (width) queryParams.append('width', width);
if (height) queryParams.append('height', height);
// Construct the URL
const encodedPrompt = encodeURIComponent(prompt);
const baseUrl = 'https://image.pollinations.ai';
let url = `${baseUrl}/prompt/${encodedPrompt}`;
// Add query parameters if they exist
const queryString = queryParams.toString();
if (queryString) {
url += `?${queryString}`;
}
// Return the URL directly, keeping it simple
return {
imageUrl: url,
prompt,
width,
height,
model: model || 'flux', // Default model is flux
seed
};
}
/**
* Generates an image from a text prompt and returns the image data as base64
*
* @param {string} prompt - The text description of the image to generate
* @param {Object} options - Additional options for image generation
* @param {string} [options.model] - Model name to use for generation
* @param {number} [options.seed] - Seed for reproducible results
* @param {number} [options.width=1024] - Width of the generated image
* @param {number} [options.height=1024] - Height of the generated image
* @returns {Promise<Object>} - Object containing the base64 image data, mime type, and metadata
*/
export async function generateImage(prompt, options = {}) {
// First, generate the image URL
const result = await generateImageUrl(prompt, options);
try {
// Fetch the image from the URL
const response = await fetch(result.imageUrl);
if (!response.ok) {
throw new Error(`Failed to fetch image: ${response.statusText}`);
}
// Get the image data as an ArrayBuffer
const imageBuffer = await response.arrayBuffer();
// Convert the ArrayBuffer to a base64 string
const base64Data = Buffer.from(imageBuffer).toString('base64');
// Determine the mime type from the response headers or default to image/png
const contentType = response.headers.get('content-type') || 'image/png';
return {
data: base64Data,
mimeType: contentType,
metadata: {
prompt: result.prompt,
width: result.width,
height: result.height,
model: result.model,
seed: result.seed
}
};
} catch (error) {
console.error('Error generating image:', error);
throw error;
}
}
/**
* Generates audio from a text prompt using the Pollinations Text API
*
* @param {string} prompt - The text to convert to speech
* @param {Object} options - Additional options for audio generation
* @param {string} [options.voice="alloy"] - Voice to use for audio generation
* @param {number} [options.seed] - Seed for reproducible results
* @returns {Promise<Object>} - Object containing the base64 audio data, mime type, and metadata
*/
export async function generateAudio(prompt, options = {}) {
if (!prompt || typeof prompt !== 'string') {
throw new Error('Prompt is required and must be a string');
}
const {
voice = "alloy",
seed,
} = options;
// Build the query parameters
const queryParams = new URLSearchParams();
queryParams.append('model', 'openai-audio'); // Required for audio generation
queryParams.append('voice', voice);
if (seed !== undefined) queryParams.append('seed', seed);
// Construct the URL
const encodedPrompt = encodeURIComponent(prompt);
const baseUrl = 'https://text.pollinations.ai';
let url = `${baseUrl}/${encodedPrompt}`;
// Add query parameters
const queryString = queryParams.toString();
url += `?${queryString}`;
try {
console.error(`Generating audio from URL: ${url}`);
// Fetch the audio from the URL
const response = await fetch(url);
if (!response.ok) {
throw new Error(`Failed to generate audio: ${response.statusText}`);
}
// Get the audio data as an ArrayBuffer
const audioBuffer = await response.arrayBuffer();
// Convert the ArrayBuffer to a base64 string
const base64Data = Buffer.from(audioBuffer).toString('base64');
// Determine the mime type from the response headers or default to audio/mpeg
const contentType = response.headers.get('content-type') || 'audio/mpeg';
return {
data: base64Data,
mimeType: contentType,
metadata: {
prompt,
voice,
model: 'openai-audio',
seed
}
};
} catch (error) {
console.error('Error generating audio:', error);
throw error;
}
}
/**
* List available models from Pollinations APIs
*
* @param {string} [type="image"] - The type of models to list ("image" or "text")
* @returns {Promise<Object>} - Object containing the list of available models
*/
export async function listModels(type = "image") {
try {
const baseUrl = type === "text" ?
'https://text.pollinations.ai' :
'https://image.pollinations.ai';
console.error(`Fetching ${type} models from ${baseUrl}/models`);
const response = await fetch(`${baseUrl}/models`);
if (!response.ok) {
throw new Error(`Error fetching models: ${response.statusText}`);
}
const models = await response.json();
return { models };
} catch (error) {
console.error(`Error in listModels for ${type}:`, error);
throw error;
}
}
// If this file is run directly (e.g., with Node.js)
if (typeof require !== 'undefined' && require.main === module) {
async function run() {
try {
// Example: Generate an image URL
const imageUrlResult = await generateImageUrl('A beautiful sunset over the ocean');
console.log('Image URL Result:', imageUrlResult);
// Example: List available models
const modelsResult = await listModels();
console.log('Available Models:', modelsResult);
// Example: Generate audio
console.log('Generating audio...');
const audioResult = await generateAudio('Hello world, this is a test of the Pollinations API client.');
console.log('Audio generated successfully!');
} catch (error) {
console.error('Error in example:', error);
}
}
run();
}
