LangChain Archives

How to Deploy Arize Phoenix on Docker: Monitor and Debug LLM, RAG, and AI Agents in Real Time

June 24, 2026

Arize Phoenix is an open-source observability platform that gives you full trace visibility into every LLM call, RAG retrieval step, and AI agent action in real time. This guide walks you through deploying it with Docker and connecting your Python app to start monitoring prompts, completions, latency, and evaluation scores from day one.

Advanced RAG: Solving the ‘Broken Table’ Problem with Multi-vector Retrieval

June 7, 2026

Standard RAG fails when tables are split across chunks. This guide shows how to use Multi-vector Retrieval to link searchable summaries to full-context tables and images, boosting accuracy for complex documents.

Build a Real-Time AI Research Agent: LangChain and Tavily API Guide

May 9, 2026

Build a production-ready AI Research Agent using LangChain and Tavily. Learn how to connect LLMs to the live internet for accurate, real-time data synthesis in Python.

Build a Smarter Inbox: Automating Email Triage with LangChain and the Gmail API

May 7, 2026

Ditch the manual triage. Learn how to build a production-grade system using LangChain for email classification and the Gmail API to automate drafting, cutting response times from hours to minutes.

Beyond Linear Chains: Building Production-Ready AI Agents with LangGraph

April 30, 2026

Ditch the spaghetti code. Learn how to use LangGraph to build resilient, stateful AI agents with built-in error handling and human-in-the-loop checkpoints.

Extract and Process PDF Tables with Docling for RAG Systems

April 8, 2026

After 6 months of using Docling in production for PDF-heavy RAG systems, I share how to extract tables properly, chunk them intelligently, and index them for accurate retrieval. Covers quick start, pipeline setup, and hard-won practical tips.

AI Agents: What They Are & How to Build Your First Automated Workflow

March 24, 2026

AI agents are changing how we automate complex IT tasks, using large language models (LLMs) with specialized tools and advanced reasoning. This tutorial shows you how to build your first agent with Python and LangChain, covering environment setup, configuration, and key monitoring techniques.