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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 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 26, 2025 · Artificial Intelligence

From Deep Learning to Large‑Model OCR: Which Model Leads the Pack?

This article traces OCR's evolution from early CNN‑LSTM systems to modern multimodal VLMs, analyzes leading open‑source models such as DeepSeek‑OCR, PaddleOCR, and MonkeyOCR, and offers practical guidance for long‑document, academic, and edge‑computing scenarios.

DeepSeek-OCRMonkeyOCRMultimodal AI
0 likes · 15 min read
From Deep Learning to Large‑Model OCR: Which Model Leads the Pack?
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 AgentDeepResearchLangGraph
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.

Cozee‑commerce chatbotlarge model
0 likes · 14 min read
Low-Code Agent Framework Guide Part 4: Best Practices for Coze Model and Plugin Settings
Fun with Large Models
Fun with Large Models
Oct 10, 2025 · Artificial Intelligence

Coze Low-Code Agent Platform: In‑Depth Look at Its Six Core Features

This article provides a comprehensive overview of the Coze low‑code AI agent platform, detailing its free, multi‑model capabilities and six core functions—plugins, knowledge base, database, image flow, workflow, and multi‑agent collaboration—while illustrating how each feature lowers development barriers and enables sophisticated agent applications.

Agent PlatformCozeKnowledge Base
0 likes · 13 min read
Coze Low-Code Agent Platform: In‑Depth Look at Its Six Core Features