Results for ragged

Ragged array library, complying with Python API specification.

Reusable AI assistant library for local LLM integration (Ollama, LM Studio, etc.)

Retrieval-Augmented Generation for Rust Agent Development Kit (ADK-Rust) agents

Tiny LLM inference for ESP32 microcontrollers with INT8/INT4 quantization, multi-chip federation, RuVector semantic memory, and SNN-gated energy optimization

A Rust library and CLI for Retrieval-Augmented Generation

A complete library to interact with Aiplatform (protocol v1beta1)

Local-first RAG CLI powered by candle for semantic search over your files

Enterprise RAG module with chat context storage, vector search, session management, and model downloading. Rust implementation with Node.js compatibility.

A Rust crate designed to extract, clean, and convert web content from URLs found in text messages into clean Markdown format. Originally created as an auxiliary component for Retrieval-Augmented Generation (RAG) solutions to process URLs submitted by users.

Core Rust RAG engine with optional Flutter Rust Bridge integration

Codebase indexing + hybrid retrieval (vector + BM25) for the Brainwires Agent Framework. Includes AST-aware chunking via tree-sitter (12 languages), Git history search, and reranking via spectral diversity / cross-encoder.

A semantic markdown document loader and splitter for RAG pipelines

Pure-Rust Retrieval-Augmented Generation pipeline built on Trueno

Gem to rag-adjust text content based on Mark Boulton's 24ways article: http://24ways.org/2013/run-ragged/ and Nathan Ford's JS implementation: https://github.com/nathanford/ragadjust

Manage AI vector embeddings in C with Ruby integration

Simple retrieval-augmented generation on markdown files

Simple Rag is a lightweight library that transforms any Ruby project into a simple RAG application.

CRUDRAG generates RubyLLM CRUD tools and a semantic RAG index that agents can use to interact with your data layer.

fornix-rag — reserved

A RAG (Retrieval Augmented Generation) engine that integrates seamlessly with Rails applications

A batteries-included RAG framework that orchestrates document loading, chunking, embedding, vector storage, retrieval, and generation. Think LangChain for Ruby — simpler, more opinionated, and Rails-native.

Command-line interface for Ragdoll's unified text-based RAG system. Converts all media types (images, audio, documents) to searchable text for powerful cross-modal search capabilities. Under development. Contributors welcome.

Rails engine providing ActiveRecord integration, background jobs, and UI components for Ragdoll's unified text-based RAG system. Converts all media types to searchable text for powerful cross-modal search capabilities.

Measures quality metrics like faithfulness, relevance, context precision, and answer correctness for LLM and RAG applications. Think Ragas or DeepEval for Ruby.

A cross-encoder reranking library for Ruby. Supports Cohere, Jina, and local ONNX models. The single biggest quality improvement you can add to a RAG pipeline.