uncloseai.

PHP Examples - Free LLM & TTS AI Service

PHP Examples

This page demonstrates how to use the uncloseai. API endpoints with PHP using the openai-php/client community library. All examples use the same OpenAI-compatible API interface, making it easy to switch between different models and endpoints.

Available Endpoints:

hermes.ai.unturf.com: https://hermes.ai.unturf.com/v1 - chat completions on an RTX 4090
qwen.ai.unturf.com: https://qwen.ai.unturf.com/v1 - chat completions on an RTX 3090
TTS: https://speech.ai.unturf.com/v1 - Text-to-speech generation

Both chat hostnames currently serve the same model, turboderp/Qwen3.8-27B-exl3 (read live from /v1/models). Hostnames are routing labels, not model names: every example below asks the endpoint which model it serves instead of hard-coding an id, so a model swap on the cards never breaks your code. The served model reasons before it answers (the reasoning arrives in a separate reasoning field), so give it room: the samples ask for 600 tokens because at 150 the budget ran out before the answer began.

Many endpoints from environment variables

Our clients (uncloseai-cli, uncloseai.js, opencompletion and the downloadable implementation for every language on this site) share one convention, so an endpoint is configuration, never code:

Variable	Meaning
`MODEL_ENDPOINT_N`	Base URL of the N-th OpenAI-compatible endpoint, ending in `/v1`. The only required variable. Scan N from 0 upward and skip gaps: uncloseai-cli counts from 0, the per-language implementations from 1.
`MODEL_API_KEY_N`	Bearer key for endpoint N. Unset means no key, which is all our free relay needs; a cloud endpoint sets one.
`MODEL_ID_N`	Model id to send. Unset means ask `/v1/models` and take the first id, the rule used by every sample on this page.
`MODEL_LABEL_N`	A display name for endpoint N; defaults to its hostname.
`TTS_ENDPOINT_N`	The same shape for text-to-speech endpoints.

export MODEL_ENDPOINT_0="https://hermes.ai.unturf.com/v1"
export MODEL_ENDPOINT_1="https://qwen.ai.unturf.com/v1"
# export MODEL_API_KEY_1="sk-..."      # only for an endpoint that needs one
export TTS_ENDPOINT_0="https://speech.ai.unturf.com/v1"

The first endpoint is the default; the rest fail over, in order. The PHP implementation under /languages/ reads these variables and discovers each endpoint's models at startup.

PHP Client Installation

Install the OpenAI PHP client via Composer:

composer require openai-php/client

Non-Streaming Examples

Non-streaming mode waits for the complete response before returning. This is simpler to use but provides no intermediate feedback during generation.

Using hermes.ai.unturf.com (RTX 4090)

<?php

require 'vendor/autoload.php';

use OpenAI;

$client = OpenAI::factory()
    ->withApiKey('choose-any-value')
    ->withBaseUri('https://hermes.ai.unturf.com/v1')
    ->make();

// Ask the endpoint which model it serves; never hard-code an id.
$model = $client->models()->list()->data[0]->id;

$response = $client->chat()->create([
    'model' => $model,
    'messages' => [
        ['role' => 'user', 'content' => 'Give a Python Fizzbuzz solution in one line of code?'],
    ],
    'temperature' => 0.5,
    'max_tokens' => 600,
]);

echo $response->choices[0]->message->content;

Using qwen.ai.unturf.com (RTX 3090)

<?php

require 'vendor/autoload.php';

use OpenAI;

$client = OpenAI::factory()
    ->withApiKey('choose-any-value')
    ->withBaseUri('https://qwen.ai.unturf.com/v1')
    ->make();

// Ask the endpoint which model it serves; never hard-code an id.
$model = $client->models()->list()->data[0]->id;

$response = $client->chat()->create([
    'model' => $model,
    'messages' => [
        ['role' => 'user', 'content' => 'Give a Python Fizzbuzz solution in one line of code?'],
    ],
    'temperature' => 0.5,
    'max_tokens' => 600,
]);

echo $response->choices[0]->message->content;

Streaming Examples

Streaming mode returns chunks of the response as they are generated, providing real-time feedback. This is ideal for interactive applications and long responses.

Using hermes.ai.unturf.com (RTX 4090)

<?php

require 'vendor/autoload.php';

use OpenAI;

$client = OpenAI::factory()
    ->withApiKey('choose-any-value')
    ->withBaseUri('https://hermes.ai.unturf.com/v1')
    ->make();

// Ask the endpoint which model it serves; never hard-code an id.
$model = $client->models()->list()->data[0]->id;

$stream = $client->chat()->createStreamed([
    'model' => $model,
    'messages' => [
        ['role' => 'user', 'content' => 'Give a Python Fizzbuzz solution in one line of code?'],
    ],
    'temperature' => 0.5,
    'max_tokens' => 600,
]);

foreach ($stream as $response) {
    echo $response->choices[0]->delta->content ?? '';
}

Using qwen.ai.unturf.com (RTX 3090)

<?php

require 'vendor/autoload.php';

use OpenAI;

$client = OpenAI::factory()
    ->withApiKey('choose-any-value')
    ->withBaseUri('https://qwen.ai.unturf.com/v1')
    ->make();

// Ask the endpoint which model it serves; never hard-code an id.
$model = $client->models()->list()->data[0]->id;

$stream = $client->chat()->createStreamed([
    'model' => $model,
    'messages' => [
        ['role' => 'user', 'content' => 'Give a Python Fizzbuzz solution in one line of code?'],
    ],
    'temperature' => 0.5,
    'max_tokens' => 600,
]);

foreach ($stream as $response) {
    echo $response->choices[0]->delta->content ?? '';
}

Text-to-Speech Example

Generate audio speech from text using the TTS endpoint. The audio is saved as an MP3 file.

<?php

require 'vendor/autoload.php';

use OpenAI;

$client = OpenAI::factory()
    ->withApiKey('YOLO')
    ->withBaseUri('https://speech.ai.unturf.com/v1')
    ->make();

$response = $client->audio()->speech([
    'model' => 'tts-1-f5',
    'voice' => 'foxhop',
    'input' => 'I think so therefore, Today is a wonderful day to grow something people love!',
    'speed' => 0.9,
]);

file_put_contents('speech.mp3', $response);