Provides tools for implementing Retrieval-Augmented Generation (RAG) workflows with Large Language Models (LLMs). Includes functions for document processing, text chunking, embedding generation, storage management, and content retrieval. Supports various document types and embedding providers (Ollama, OpenAI), with DuckDB as the default storage backend. Integrates with the ellmer package to equip chat objects with retrieval capabilities. Designed to offer both sensible defaults and customization options with transparent access to intermediate outputs.

A conversational AI system that listens, learns, and challenges

Templates for creating vagrant boxes. Contribute to mwrock/packer-templates development by creating an account on GitHub.

Blog of the MZES Social Science Data Lab

A workflow for refactoring one-time analyses to sustainable data products