#Tool Calling
97 related articles
Tutorials·3 min
Godot MCP + Codex in Practice: Using AI to Auto-Generate an Endless Runner Game
Learn how to integrate Godot MCP with OpenAI Codex to control the game engine via natural language, with a full walkthrough from setup to auto-generating an endless runner scene.
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Tutorials·2 min
LangGraph vs LangChain: How to Choose Your Agent Development Framework
In-depth comparison of LangGraph vs LangChain: controllability, extensibility, and FastAPI-powered performance. Covers storage, enterprise private deployment, and migration guidance for agent developers.
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Tutorials·3 min
Getting Started with Spring AI: How Java Developers Can Integrate Large Language Models
Spring AI is the LangChain for Java, helping Java developers integrate LLMs using Spring Boot conventions. This guide covers its 6 core features, setup requirements, and enterprise positioning including RAG, Tool Calling, and Chat Memory.
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Tutorials·3 min
Claude Code Beginner's Guide: Installation, Cost-Saving Solutions & Source Code Architecture Analysis
Claude Code beginner tutorial covering installation, common issues, low-cost alternatives for budget users, and deep analysis of 8 Agent design patterns revealed by the 510K-line source code leak.
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Product Reviews
Qwen 3.6 vs Gemma 4: In-Depth Comparis…
·3 min
Qwen 3.6 vs Gemma 4: In-Depth Comparison of Local AI Coding Models Through Real-World Development
Real-world comparison of Qwen 3.6 and Gemma 4 local AI models building a Markdown editor with Tauri, testing planning ability, code generation, and development efficiency.
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Tutorials·3 min
Complete Breakdown of Andrew Ng's Agent Course: A Practical Guide to the Five Core Modules of AI Agent Development
Deep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
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Product Reviews·2 min
Kimi K2.6 Open-Source Hands-On: How Strong Is Its Orchestration of 300 Concurrent Agents?
Deep analysis of Moonshot AI's open-source Kimi K2.6 Agent orchestration: 300 sub-Agents executing 4000-step tasks, outperforming GPT-5.4 in coding benchmarks, LoRA fine-tuning on 2x RTX 4090s.
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Tutorials·3 min
From Traditional RAG to Agentic RAG: Principles Compared and Enterprise-Grade Implementation Guide
Deep dive into traditional RAG limitations and Agentic RAG upgrades, with ChatBox source code analysis covering core tool design, intelligent decision flows, and LangGraph implementation for enterprise deployment.
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Tutorials·2 min
The Three-Layer Pyramid Model for Agent Development: From Beginner to Industrial-Grade Deployment
Deep dive into the Three-Layer Pyramid Model for Agent development, covering autonomous agents, collaborative multi-agent systems, and universal orchestration agents with a complete learning path from beginner to industrial-grade deployment.
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Tutorials·3 min
Enterprise Multi-Agent Development: Low-Code Platforms vs. Hand-Written Code — An In-Depth Comparison
In-depth comparison of two enterprise multi-agent development approaches: low-code platforms like Dify vs. hand-written code with LangGraph. Covers efficiency, flexibility, security, and prompt injection defense strategies.
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Tutorials·3 min
Learning LLM Application Development from Scratch: A Complete Roadmap from RAG to Agent
How to start LLM application development from scratch? A complete roadmap covering Python basics, RAG knowledge bases, and Agent development with LangChain.
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Tutorials·3 min
Deep Agents: Enterprise-Grade Agent Engineering and Deep Research Implementation Guide
Learn how the Deep Agents framework solves enterprise AI Agent challenges like tool sprawl and context pollution, with a complete Deep Research implementation guide covering task decomposition, multi-source integration, and structured report generation.
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Product Reviews
Three AI Agents Tested Head-to-Head: W…
·3 min
Three AI Agents Tested Head-to-Head: Which One Handles E-Commerce Livestream Data Analysis Best?
Testing three AI Agents on e-commerce livestream data analysis: local deployment memory limits, costly overseas APIs, and how a cloud-based multi-model solution delivers a complete business workflow.
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Deep Dives·4 min
From Copilot to Agentic AI: A Complete Guide to Multi-Agent Collaboration Architectures
Deep dive into AI's four-stage evolution from Chat to Agentic AI, covering multi-Agent architectures, ReAct framework, and MCP protocol for developers.
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Deep Dives·4 min
The Complete Guide to Agentic RAG: Principles and Code Implementation
Deep dive into Agentic RAG vs traditional RAG, covering tool calling, multi-step iteration, query rewriting, with LangChain and LangGraph code examples for building intelligent retrieval systems.
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Tutorials·4 min
Dify AI Agent Tutorial: Tool Integration & ESA Search Configuration in Practice
Complete guide to building AI Agents on Dify with zero code, covering tool integration, ESA search configuration, time awareness solutions, and Agent design best practices.
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Tutorials·4 min
Agentic RAG in Practice: Architecture Deep Dive and LangChain Implementation Guide
Compare traditional RAG vs Agentic RAG architectures, explore planning, tool use, and multi-step iteration capabilities, with full LangChain/LangGraph ReAct Agent code and ChatBoss project examples.
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