Kalyan KS

llm-engineer-toolkit. A curated list of 120+ LLM libraries category wise.

rag-zero-to-hero-guide. Comprehensive guide to learn RAG from basics to advanced.

LLM-Interview-Questions-and-Answers-Hub. 100+ LLM interview questions with answers.

RAG-Interview-Questions-and-Answers-Hub. 100+ RAG interview questions with answers.

Prompt-Engineering-Techniques-Hub. This repo contains implementation of 25+ prompt engineering techniques.

LLM-Survey-Papers-Collection. A category wise collection of 200+ LLM survey papers.

KalyanKS-NLP.

all-rag-techniques. Explore various RAG techniques in a straightforward way. This repository provides practical examples and resources for developers looking to enhance their skills. 🐙🌍

RAG_Techniques. This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.

ragas. Supercharge Your LLM Application Evaluations 🚀

learn-agentic-ai. Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.

deepeval. The LLM Evaluation Framework

RocketEval-ICLR. 🚀 [ICLR '25] RocketEval: Efficient Automated LLM Evaluation via Grading Checklist

ai-hands-on. A group of notebooks and other files which can help you learn AI from scratch.

building-effective-agentic-ai-systems-dhs2025. This repository will contain the presentation and python jupyter notebooks for my DataHack Summit 2025 conference talk, Building Effective Agentic AI Systems: Lessons from the Field. Drawing from my experience building deploying Agentic AI systems, we’ll focus on three pillars: Architecting, Optimizing, and Observability for Agentic AI Systems.

mastering-intelligent-agents-langgraph-workshop-dhs2025. This repository will contain all the presentations, content, hands-on python notebooks for a full day Agentic AI workshop on Building Simple and Complex Agents, Deploying and Monitoring AI Agents with LangGraph for the DataHack Summit 2025 conference.

speed_up_your_RAG_app. Speed up your RAG by performing cosine similarity parallel on your CPU Cores

Agent_Mont. Comprehensive metrics, insights, and visualization for Phidata and Crew AI applications

quarkdown. 🪐 Markdown with superpowers — from ideas to presentations, articles and books.