#Agent tool calling
7 related articles
Tutorials·3 min
ReAct vs. CodeAct: Two Core Approaches to Agent Tool Calling
In-depth comparison of ReAct and CodeAct — two core Agent tool-calling architectures. From paper principles to code implementation, learn the trade-offs between reasoning+action and code execution.
Read more →
Tutorials·3 min
Getting Started with AI Agent Development: A Complete Learning Path from Concepts to Practice
A comprehensive guide to AI Agent development for beginners, covering core concepts, market outlook, LangChain framework, RAG knowledge bases, and hands-on projects to systematically master intelligent agent development skills.
Read more →
Tutorials·3 min
MCP Protocol Explained: Differences from Function Calling and Agent Tool Development in Practice
Deep dive into MCP (Model Context Protocol): its principles, communication architecture, and practical applications. Compare MCP vs Function Calling, explore client-server communication and security.
Read more →
Tutorials·3 min
Dify Local Deployment Tutorial: Setting Up an AI Development Platform from Scratch with BT Panel + Docker
Step-by-step tutorial on deploying Dify locally using VMware, Ubuntu, BT Panel, and Docker. Covers environment setup, common error fixes, and next steps for building AI apps.
Read more →
Tutorials·1 min
AI Large Language Model Learning Roadmap: Six Stages from Zero to Engineer
A systematic LLM engineer learning roadmap covering Transformer basics, prompt engineering, RAG, Agent development, API integration, fine-tuning, deployment, and project practice across six stages.
Read more →
Tech Frontiers·2 min
Step 3.7 Flash: Deep Dive into the 198B Sparse MoE Multimodal Model
Deep dive into StepFun AI's Step 3.7 Flash, a 198B sparse MoE vision-language model with 256K context and 3-level reasoning, excelling in multimodal understanding, AI coding, and Agent tool orchestration.
Read more →
