InfoWorld

Surveying the LLM application framework landscape

Large language models by themselves are less than meets the eye; the moniker “stochastic parrots” isn’t wrong. Connect LLMs to specific data for retrieval-augmented generation (RAG) and you get a more ...
JD Supra

Engineering Confidence: 14 Critical Questions for Secure LLM and RAG Deployment

The rapid evolution of large language models (LLMs), retrieval-augmented generation (RAG), and Model Protocol Context (MCP) implementation has led many developers and teams to quickly adopt and ...
Geeky Gadgets

LLMWare unified framework for developing LLM apps with RAG

– High-performance document parsers to rapidly ingest, text chunk and ingest common document types. – Comprehensive intuitive querying methods: semantic, text, and hybrid retrieval with integrated ...
InfoWorld

DSPy: An open-source framework for LLM-powered applications

DSPy (short for Declarative Self-improving Python) is an open-source Python framework created by researchers at Stanford University. Described as a toolkit for “programming, rather than prompting, ...
Diginomica

Want better LLM results? Then it's time for AI evaluation tools - learning from Galileo's RAG and agent metrics

A consistent media flood of sensational hallucinations from the big AI chatbots. Widespread fear of job loss, especially due to lack of proper communication from leadership - and relentless overhyping ...