The Critical Importance of Logging LLM Prompts and Responses

Why Logging LLM Interactions Matters

As Large Language Models (LLMs) become integral to business applications, systematic logging of prompts and responses emerges as a critical requirement. Here's why:

1. Transparency & Auditability

   • Trace decision-making processes
   • Meet GDPR/CPRA compliance requirement…

The Model Context Protocol

Introduction

The Model Context Protocol (MCP) is an innovative framework designed to standardize interactions between Large Language Models (LLMs) and external systems such as databases, APIs, and enterprise tools. Developed by Anthropic (creators of Claude AI), MCP addresses critical chal…

Ontology and Its Usefulness for Large Language Models

Introduction

In the rapidly evolving field of artificial intelligence (AI), structured knowledge representation plays a pivotal role in enhancing machine understanding and reasoning capabilities. Ontology, a formal framework for organizing domain-specific knowledge, has emerged as a critical tool fo…

Understanding Ontology, Knowledge Graphs, RAG, and GraphRAG in LLM Applications

Introduction

In the realm of artificial intelligence (AI), structured knowledge representation and retrieval techniques are pivotal for enhancing Large Language Models (LLMs). This article clarifies four key concepts—Ontology, Knowledge Graphs, Retrieval-Augmented Generation (RAG), and&nbs…