This repository contains the code snippets used in "LLM Prompt Engineering For Developers"

Kotlin + SpringBoot + Koog + Promptfoo example

Community Plugin for Genkit to use Promptfoo

Examples of how to use Docker Model Runner, Docker MCP Toolkit, and Promptfoo together to evaluate models, agents, and MCP servers

Prompting Blueprints: copy-ready prompt patterns, model tips (GPT-5, Gemini), tool tactics (NotebookLM, Perplexity Comet, Copilot Agents), and promptfoo evaluations for structured outputs.

Sample project demonstrates how to use Promptfoo, a test framework for evaluating the output of generative AI models

A fun experiment using promptfoo for evaluating LLM responses on pizza order transcripts

Quickstart guide for using PromptFoo to evaluate LLM prompts via CLI or Colab.

Virtual Teaching Assistant (Virtual TA) is an innovative, intelligent and automated assistant designed specifically for the Tools in Data Science (TDS) course offered by the IIT Madras Online Degree Program. This cutting-edge system revolutionizes the learning experience by providing students with accurate, context-aware answers to their questions.

Integrating promptfoo into CI/CD pipelines to automatically evaluate prompts, test for security vulnerabilities, and ensure quality before deployment.

FastAPI-based virtual teaching assistant

Prompt-based tone classification with LLMs using Promptfoo evaluation.

Sample implementation demonstrating how to use Firebase Genkit with Promptfoo

This repository demonstrates how to perform LLM prompt evaluation, deterministic testing, and regression detection using PromptFoo. It is designed to help developers, researchers, and QA teams ensure that prompt or model updates produce consistent and reliable results.