Pocket-sized Ruby AI agent framework / LLM assistant with multi-LLM support
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Updated
Apr 23, 2026 - Ruby
Pocket-sized Ruby AI agent framework / LLM assistant with multi-LLM support
DeTAILS: Deep Thematic Analysis with Iterative LLM Support. DeTAILS is a toolkit for Thematic Analysis (and qualitative coding). By grounding LLMs in your research, DeTAILS automates the heavy lifting—scanning transcripts for quotes, generating codes and themes—while you (the researcher) guide the analysis to ensure rigor and depth.
Frontend module for Averion Labs’ medical-AI SaaS: a React 18 + TypeScript web app built with Vite and Tailwind, supporting image-based diagnostics, billing, user roles and LLM-powered insights.
A simple way for open source maintainers to request recognition from AI coding agents
A production-ready RAG assistant for industrial engineering manuals. Extracts structured troubleshooting data from complex PDFs with exact source page traceability using LlamaIndex, OpenAI, and OOP principles.
Convert webpages and PDFs into clean, structured data optimized for retrieval-augmented generation in a single API call.
A local-first autonomous LLM agent that perceives and navigates a Blazor WebAssembly UI using a ReAct loop, powered by Ollama, zero data leaves the machine.
Define a standard file to let open source maintainers specify preferred recognition signals for AI-driven code reuse.
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