Code & Development · GitHub ·3,834 ★

ruby_llm

One beautiful Ruby API for OpenAI, Anthropic, Gemini, Bedrock, Azure, OpenRouter, DeepSeek, Ollama, VertexAI, Perplexity, Mistral, xAI, GPUStack & OpenAI compatible APIs. Agents, Chat, Vision, Audio, PDF, Images, Embeddings, Tools, Streaming & Rails integration.

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Details

Author
crmne
Category
Code & Development
Platform
GitHub
Framework
openai
Language
ruby
Stars
3,834
First indexed
2026-05-15
Last active
2026-04-10
Directory sync
2026-05-15
@crmne@paolinopaolino.me

Overview

One beautiful Ruby API for OpenAI, Anthropic, Gemini, Bedrock, Azure, OpenRouter, DeepSeek, Ollama, VertexAI, Perplexity, Mistral, xAI, GPUStack & OpenAI compatible APIs. Agents, Chat, Vision, Audio, PDF, Images, Embeddings, Tools, Streaming & Rails integration.

Quick start

git

git clone https://github.com/crmne/ruby_llm

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What ruby_llm can do

hraudiorouterapiimage
  • Hr — Handles people operations such as hiring and policy Q&A.
  • Audio — Transcribes, generates, or transforms audio.
  • Router — router task automation.
  • Api — api task automation.
  • Image — Generates or edits images from natural-language prompts.

Frequently asked questions

What is ruby_llm?
One beautiful Ruby API for OpenAI, Anthropic, Gemini, Bedrock, Azure, OpenRouter, DeepSeek, Ollama, VertexAI, Perplexity, Mistral, xAI, GPUStack & OpenAI compatible APIs. Agents, Chat, Vision, Audio, PDF, Images, Embeddings, Tools, Streaming & Rails integration.
How do I install ruby_llm?
Use git: `git clone https://github.com/crmne/ruby_llm`. Full setup details on the source page linked above.
Is ruby_llm open source?
ruby_llm is published on GitHub.
What are alternatives to ruby_llm?
Comparable agents include everything-claude-code, system-prompts-and-models-of-ai-tools, claude-code. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for ruby_llm is sourced from GitHub, published by crmne.

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