Tag
agents
Agents are LLM-driven workflows that can break down tasks, call tools, keep state, and iterate on results. Here you’ll see editor automation, data-viz and file-retrieval benchmarks, plus structured-output patterns that determine whether models can operate as systems, not just chatbots.
4 articles
RAGFlow adds agents to open-source RAG
RAGFlow pairs retrieval-augmented generation with agent features, Docker self-hosting, and support for newer models like GPT-5 and Gemini 3 Pro.
DV-World tests chart agents in real workflows
DV-World benchmarks data-viz agents on spreadsheet, evolution, and intent-alignment tasks that mirror real enterprise workflows.
HippoCamp tests agents on your personal files
HippoCamp benchmarks multimodal agents on dense personal file systems, exposing weak retrieval, grounding, and cross-modal reasoning.
AI Cookbook Packs Practical LLM Code for Developers
Dave Ebbelaar’s AI Cookbook offers 3,887-star Python examples for agents, Anthropic, and OpenAI workflows developers can copy today.