305 related articles

In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.

An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.
GitHub Daily · July 24: Agentic Tools …
GitHub Trending July 24: Agentic capabilities go from concept to standard feature. Instatic and Chat2DB deeply integrate AI into CMS and database clients, while dive-into-llms remains the go-to Chinese LLM tutorial.
GitHub Daily · July 24: Agentic Tools …
GitHub Trending July 24: Agentic capabilities go from concept to standard, with Instatic and Chat2DB embedding AI deeply into CMS and database clients.

Step-by-step guide to deploying Dify AI platform locally with Docker. Covers Linux, Windows, macOS setup, docker compose launch, and first-time initialization in under 30 minutes.

A systematic roadmap from LangChain and LangGraph to multi-agent development, covering RAG, Tool Calling, MCP, and more, helping developers break into AI app development.

A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.

A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.

A step-by-step guide to locally deploying the Dify open-source AI platform using BT Panel on a VMware virtual machine, covering Ubuntu setup, Docker config, and image pull troubleshooting—beginner-friendly.

A step-by-step guide to locally deploying the open-source Dify AI platform using the BT Panel on a VMware virtual machine—covering Ubuntu setup, Docker config, and image pull troubleshooting.

Dify is a low-code AI app platform supporting chatbots, Agents, and workflows. Compatible with DeepSeek, ChatGPT, and more. Learn cloud and local deployment options.

A systematic overview of the AI Agent tech stack: RAG retrieval, Agent planning, MCP protocol, AI Gateway, and observability — helping developers build production-grade AI systems.
WrenAI: An Open-Source GenBI Tool for …
WrenAI is an open-source GenBI tool by the Canner team that converts natural language into trusted SQL, charts, and dashboards via a semantic layer. Supports 20+ data sources including BigQuery and Snowflake. 16,000+ GitHub stars.

A complete Dify 1.8 guide covering 3 deployment methods (Docker/cloud/source), MySQL integration, 5 app types (Chatbot/Agent/Workflow), model selection, and publishing strategies.

A beginner's guide to Dify: build RAG knowledge bases visually with zero coding. Covers agents, workflows, and why private deployment makes Dify ideal for enterprise AI.

A deep dive into ByteDance's Coze platform: tool categories, positioning vs. Dify, skill store, multi-agent collaboration, and workflow building — your AI Agent selection guide.

What is an AI agent? How does it differ from a large language model? Learn the core concepts, the Agent formula (LLM + Workflow + Knowledge Base), and how to choose between Dify, LangChain, and LlamaIndex.

ATLAS is a solo-built AI geolocation tool that identifies global locations from street-view images alone — no metadata. 81% country accuracy, 111 countries, 3-second response, ~4000 avg score.

A systematic guide to enterprise Ontology: its core value, tools like OntoFlow and FIBO, when to build one, and how to deploy business-domain-level AI Agents.

n8n is a powerful low-code workflow automation platform supporting AI Agents, Chain nodes, and RAG systems. Learn the three core AI modules and get started fast.