RubyLLM 2.0 expands support across multiple AI providers and introduces new features including video, speech, OCR, batches, and Rails integration. The framework adds human approval controls for tools, citations for document and web references, and separates providers from protocols for consistent APIs across different services.
RubyLLM 2.0 expands the framework with support for new providers (Cohere, Deepgram, ElevenLabs, Ollama Cloud), AI operations (video, speech, OCR, reranking, batches), and conversation controls including tool approvals, citations, and agentic workflows. The update adds consistent Ruby APIs across seventeen providers while maintaining streaming and usage tracking throughout.
Wispr Advanced Interfaces Lab introduced Canto, a speech recognition model designed for real-world dictation conditions. Tested on real Wispr Flow usage data, Canto achieved the lowest word error rate among comparable models from Google, OpenAI, AssemblyAI, and Deepgram, performing particularly well on low-volume and short utterances despite ranking second to Gemini 3.1 Pro on overall challenge audio.