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Fun with Large Models
Fun with Large Models
Nov 8, 2025 · Artificial Intelligence

Unlocking LangChain 1.0 create_agent: Advanced MCP, Structured Output, Memory & Middleware

This guide dives into the four advanced capabilities of LangChain 1.0's create_agent API—MCP tool integration, structured output, memory management, and middleware—showcasing practical examples such as an Amap MCP planner, Pydantic‑based response formatting, InMemorySaver chat history, and custom middleware for dynamic model selection.

AI agentsLangChainMCP
0 likes · 22 min read
Unlocking LangChain 1.0 create_agent: Advanced MCP, Structured Output, Memory & Middleware
Fun with Large Models
Fun with Large Models
Nov 4, 2025 · Artificial Intelligence

Mastering LangChain 1.0’s create_agent API: Basics, Message Types, and Stream Modes

This tutorial walks through setting up a Python environment, explains the three essential components of LangChain 1.0’s create_agent API, details the built‑in message types, and demonstrates four streaming output modes using a weather‑assistant example to help developers quickly adopt the new agent framework.

AI agentsLangChainPython
0 likes · 11 min read
Mastering LangChain 1.0’s create_agent API: Basics, Message Types, and Stream Modes
Fun with Large Models
Fun with Large Models
Nov 2, 2025 · Artificial Intelligence

Fast-Track LangChain 1.0: Core Upgrades and the New create_agent API

This guide walks through LangChain 1.0’s three major upgrades— the new create_agent API that replaces legacy agent builders, standardized content_blocks for unified model output, and a streamlined package structure—while showing how middleware hooks, built‑in and custom middleware, and improved structured output simplify production‑grade AI agent development.

AI agentsLangChainPython
0 likes · 15 min read
Fast-Track LangChain 1.0: Core Upgrades and the New create_agent API