uncloseai.

Ruby Examples - Free LLM & TTS AI Service

Ruby Examples

This page demonstrates how to use the uncloseai. API endpoints with Ruby using the official OpenAI Ruby gem. 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 Ruby implementation under /languages/ reads these variables and discovers each endpoint's models at startup.

Ruby Client Installation

To install the official OpenAI gem for Ruby (the openai gem, not the community ruby-openai gem, whose client API differs), add to your Gemfile or use gem install:

gem install openai -v 0.31.0

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)

require "openai"

client = OpenAI::Client.new(
  api_key: "choose-any-value",
  base_url: "https://hermes.ai.unturf.com/v1"
)

# Ask the endpoint which model it serves; never hard-code an id.
model = client.models.list.data.first.id

response = client.chat.completions.create(
  model: model,
  messages: [
    { role: "user", content: "Give a Python Fizzbuzz solution in one line of code?" }
  ],
  temperature: 0.5,
  max_tokens: 600
)

puts response.choices.first.message.content

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

require "openai"

client = OpenAI::Client.new(
  api_key: "choose-any-value",
  base_url: "https://qwen.ai.unturf.com/v1"
)

# Ask the endpoint which model it serves; never hard-code an id.
model = client.models.list.data.first.id

response = client.chat.completions.create(
  model: model,
  messages: [
    { role: "user", content: "Give a Python Fizzbuzz solution in one line of code?" }
  ],
  temperature: 0.5,
  max_tokens: 600
)

puts response.choices.first.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)

require "openai"

client = OpenAI::Client.new(
  api_key: "choose-any-value",
  base_url: "https://hermes.ai.unturf.com/v1"
)

# Ask the endpoint which model it serves; never hard-code an id.
model = client.models.list.data.first.id

stream = client.chat.completions.stream_raw(
  model: model,
  messages: [
    { role: "user", content: "Give a Python Fizzbuzz solution in one line of code?" }
  ],
  temperature: 0.5,
  max_tokens: 600
)

stream.each do |chunk|
  content = chunk.choices&.first&.delta&.content
  print content if content
end

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

require "openai"

client = OpenAI::Client.new(
  api_key: "choose-any-value",
  base_url: "https://qwen.ai.unturf.com/v1"
)

# Ask the endpoint which model it serves; never hard-code an id.
model = client.models.list.data.first.id

stream = client.chat.completions.stream_raw(
  model: model,
  messages: [
    { role: "user", content: "Give a Python Fizzbuzz solution in one line of code?" }
  ],
  temperature: 0.5,
  max_tokens: 600
)

stream.each do |chunk|
  content = chunk.choices&.first&.delta&.content
  print content if content
end

Text-to-Speech Example

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

require "openai"

client = OpenAI::Client.new(
  api_key: "YOLO",
  base_url: "https://speech.ai.unturf.com/v1"
)

response = client.audio.speech.create(
  model: "tts-1-f5",
  voice: "foxhop",
  input: "I think so therefore, Today is a wonderful day to grow something people love!",
  speed: 0.9
)

# Response is a StringIO object, need to read its content
File.binwrite("speech.mp3", response.read)