David Oluyale·2d agoGoing Deep: Building a Deep Agent Twice — From Scratch, Then With LangChainA “shallow” agent is a model in a tool loop: ask, call tools, answer. It works for tasks that fit in one sitting, and falls apart on…
Jahnavi·3d agoFrom API Call to LLM Application: Getting Started with LangChainFrom a single model call to a reusable chain using prompt templates, output parsers, and LCELA response icon1A response icon1
Jayanti prasad Ph.D·Oct 28Creating a simple AI agent with LangChain create_agentAI agents can involve many components, at least the following four are essential :
InTowards AIbySayanteka Chakraborty·Oct 27Build AI Agents in 5 Minutes Using LangChainRead this story for free…
Vishal Purohit·Oct 27One Agent Isn’t Enough: Building Autonomous Multi-Agent Swarms with LangGraph!When building production AI agents, developers often fall into the “God Agent” trap.A response icon1A response icon1
Sara Hamouda·Oct 27LangChain detailed..De Sentence Transformers à FAISS, du chargement de documents à la recherche sémantique : comprendre LangChain, son architecture, ses…
Neha singh·Oct 21How AI Agents Actually Work Behind the ScenesWe often think that we just need to provide some tools to an LLM, and magically, it starts calling tools, performing tasks, and giving us…
Nachiket Mehendale·Oct 19Protecting User Data in LangChainPassing the Logged-In User’s ID to a Tool Through Agent State, Without Exposing It to the LLM
Dineshthumma·Oct 18My Attempt at Code Intelligence Using Graph RAG + Vector RAG, and What I Found OutFrom when i tried Claude’s Add from GitHub i wanted to do a try at graph RAG for myself and host it locally and this was my attempt and…
ALI ZAIN·Oct 15LangChain vs LlamaIndex vs Custom RAG: What Actually Differs When You Build the Same Bot 3 Times —…We did LangChain vs LlamaIndex vs Custom RAG. Our first scorecard said the frameworks hallucinated 83 to 92% of the time. It was wrong, and…
