Building Smarter Agents in KNIME: New Tools, Live Demo, and Workflow Deep Dive скачать в хорошем качестве

Building Smarter Agents in KNIME: New Tools, Live Demo, and Workflow Deep Dive

New Tools: RAG, DB Query and an improved web search for my AI Personal Assistant! Sub:    / @lowcodeaiforthewin-fx2bo   In this video, we continue the series on exploring agentic systems in KNIME. I share updates on the progress made since the first video, highlighting improvements, new tools, and a live demonstration of a personal assistant agent in action. Key advancements include enhancing the web search tool with Python libraries like DuckDuckGo Search and Goose3, as well as developing two new tools: a retrieval-augmented generation (RAG) tool for interacting with documents and a database query tool for answering natural language questions using structured data. The centerpiece of this video is a fully integrated personal assistant agent that dynamically delegates tasks to specialized agents. You'll see how the agent orchestrator decides which agent to activate—be it for web search, database queries, or document interaction—and handles user questions seamlessly. I walk you through a live demonstration of querying financial data, searching for information on recent events, and generating Python extension development tips using the new tools. I also dive into the technical side, showing how agent workflows are defined, emphasizing the use of structured prompts in XML-like formats, and explaining the logic behind recursive loops, state variables, and message histories. Finally, I provide a high-level breakdown of the generic agent workflow, which forms the backbone of this system. If you're interested in AI-driven tools, prompt engineering, or building agent-based systems, this video offers practical insights and inspiration for your own projects.