A.G. Sayyed

This document explores the multi-model approach for AI implementation covering model selection criteria, prompt engineering, continuous evaluation and collaborative team strategies for optimal AI deployment.

This document describes how to build flexible, composable chains using LangChain Expression Language (LCEL), including prompt templates, pipe operators, runnable primitives, and type coercion mechanisms.

This document describes chains in LangChain for generating responses, memory storage mechanisms, and agents for dynamic action sequencing to build sophisticated LLM applications.

This document defines LangChain and explores its core components including language models, chat models, chat messages, prompt templates, example selectors, and output parsers for building LLM applications.