LangChain·1yHow do I speed up my agent?
Speeding up AI agents involves identifying latency sources, optimizing the user experience to reduce perceived latency, minimizing and speeding up LLM calls, and executing tasks in parallel. Tools like LangSmith and LangGraph are beneficial for diagnosing latency issues and improving performance through strategic tradeoffs between cost, speed, and capability.
Real Python·1yLangGraph: Build Stateful AI Agents in Python – Real Python
LangGraph is a powerful Python library designed for building stateful, cyclic, and multi-actor large language model (LLM) applications. It is built on top of LangChain and enables the creation of sophisticated workflows, incorporating state graphs with nodes, conditional edges, and cycles. This tutorial guides through setting up LangGraph, defining state graphs, and building AI agents for tasks like email parsing, decision-making, and interacting with APIs.