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Fun with Large Models
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Fun with Large Models

Master's graduate from Beijing Institute of Technology, published four top‑journal papers, previously worked as a developer at ByteDance and Alibaba. Currently researching large models at a major state‑owned enterprise. Committed to sharing concise, practical AI large‑model development experience, believing that AI large models will become as essential as PCs in the future. Let's start experimenting now!

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Recent Articles

Latest from Fun with Large Models

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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
Fun with Large Models
Fun with Large Models
Oct 31, 2025 · Artificial Intelligence

How to Use Coze Variables and Long‑Term Memory in Low‑Code Agent Development (Part 6)

This guide walks through Coze’s variable and long‑term memory features, showing how to define and use variables for user data, configure persistent memory, and combine both to build personalized, context‑aware AI agents, with step‑by‑step screenshots, code snippets, and real‑world scenarios.

AI AgentsCozeLong-term Memory
0 likes · 14 min read
How to Use Coze Variables and Long‑Term Memory in Low‑Code Agent Development (Part 6)
Fun with Large Models
Fun with Large Models
Oct 22, 2025 · Artificial Intelligence

Building and Deploying a Multi‑Agent DeepResearch App with LangGraph

This article walks through constructing a LangGraph graph that encapsulates three agents—task planning, web search, and report generation—into a DeepResearch application, then shows how to package and deploy the backend and frontend so users can interact with the system via a web UI.

AI agentDeepResearchDeployment
0 likes · 12 min read
Building and Deploying a Multi‑Agent DeepResearch App with LangGraph
Fun with Large Models
Fun with Large Models
Oct 18, 2025 · Artificial Intelligence

Building DeepResearch from Scratch (Part 2): Architecture Design and Implementation with LangGraph

This article walks through the design and implementation of a multi‑agent DeepResearch application using the Pipeline‑Agent pattern with LangGraph and LangChain, detailing three agents for task planning, web search via Tavily, and report generation, and provides complete Python code and test results.

AI AgentsLangChainLangGraph
0 likes · 16 min read
Building DeepResearch from Scratch (Part 2): Architecture Design and Implementation with LangGraph
Fun with Large Models
Fun with Large Models
Oct 15, 2025 · Artificial Intelligence

Low-Code Agent Framework Guide Part 4: Best Practices for Coze Model and Plugin Settings

This guide walks through Coze's large‑model configuration—including model selection, generation diversity, input/output parameters, and persona templates—demonstrates a complete e‑commerce chatbot setup, and details two plugin integration methods with three concise best‑practice rules for effective agent development.

CozePlugin Integratione‑commerce chatbot
0 likes · 14 min read
Low-Code Agent Framework Guide Part 4: Best Practices for Coze Model and Plugin Settings