crmne / ruby_llm
git clone https://github.com/crmne/ruby_llm.git
v2.1.1 · 9d ago
🔥 on GitHub Trending today
The Ruby AI framework.
—
stars, 24h
—
stars, 7 days
+92
stars, 30 days · #2,514
4.5k
★ total
517
forks · 8 open issues
Star history starts 2026-10-20; the chart appears after the second daily snapshot.
LanguageRuby
LicenseMIT
Created2025-01-30 (1y ago)
Last pushtoday
Watchers32
OwnerUser
Seen on GitHub Trending
- 2026-10-20 — #10 monthly in ruby · +92 ★
GitHub topics
agent-frameworkagentic-aiagentsaiai-agentsai-frameworkanthropicembeddingsgeminigenerative-ailarge-language-modelsllmmultimodalollamaopenairagrailsrubystructured-outputtool-calling
Links
- GitHub: github.com/crmne/ruby_llm
- Homepage: https://rubyllm.com/
- Releases · Issues · Hacker News mentions
README excerpt
The Ruby AI framework Build AI features the Ruby way: models, tools, agents, sandboxed code, evaluations, and Rails conventions, designed together, with one consistent API. Website · Getting Started · What's New in 2.1 Battle tested at - *Fully private work AI* https://github.com/user-attachments/assets/519fcb20-ab8c-4af3-9185-0953b3ba7b81 > [!NOTE] > Using RubyLLM? Share your story! Takes 5 minutes. --- ## 23 providers. One API. Build with the models you want. Move between hosted and local providers without rewriting your application, or connect an OpenAI-compatible endpoint. Browse models and pricing · Connect a provider ## A complete AI framework for Ruby More than a client for model APIs. RubyLLM gives your application the conventions, the runtime, and every piece in between: agents that run code safely, workflows, evaluations, observability, and the data they need, designed to work together. * **Code execution (main):** Let the model run Ruby, Python, JavaScript, and shell in a sandbox on your servers with `with_code_execution` * **Skills (main):** Teach the model your workflows with folders of instructions and scripts in the Agent Skills format with `with_skills` * **MCP:** Connect agents to your systems with server classes in `app/mcp`, per-user inputs, tool filtering, and OAuth with `RubyLLM::MCP` * **Agents:** Reusable assistants with `RubyLLM::Agent` * **The agentic loop:** Drive it yourself with `ask_later`, `step`, and `complete?` * **Evaluations (main):** Reusable datasets, model criteria, and Ruby assertions with `RubyLLM::Evaluation` * **Chat:** Conversational AI with `RubyLLM.chat` * **Vision:** Analyze images and videos * **Audio:** Transcribe speech with `RubyLLM.transcribe` and generate it with `RubyLLM.speak` * **Documents:** Ask questions about PDFs, text files, and other supported formats * **OCR:** Turn documents into markdown with `RubyLLM.ocr` * **Image generation:** Create images with `RubyLLM.paint` * **Video generation:** Create videos with `RubyLLM.animate` * **Embeddings:** Generate embeddings with `RubyLLM.embed` * **Reranking:** Order retrieval candidates by relevance with `RubyLLM.rerank` * **Moderation:** Content flags, categories, and scores with `RubyLLM.moderate` * **Judgments:** Probabilities, choices, and scores with `RubyLLM::Judge` and `RubyLLM.judge` * **Tools:** Let AI call your Ruby methods * **Tool approval:** Park a run until a human approves with `requires_approval` * **Provider tools:** Web search, code execution, and MCP connectors with `with_provider_tools` * **Prompt templates:** ERB prompts in `app/prompts`, rendered with `RubyLLM.render_prompt` * **Workflows:** Correlate multi-agent runs in your telemetry with `RubyLLM.workflow` * **Structured output:** Define a Ruby schema and read the result with `response.parsed` * **Streaming:** Real-time responses with blocks * **Rails:** Active Record persistence, Active Storage attachments, Hotwire streaming, and generators * **Files:** Upload once an