This post outlines the process of creating a deployable function in Jupyter Notebook using watsonx.ai, which is then exposed via a REST API. It emphasizes the separation of development in projects and runtime in deployment spaces, detailing steps from environment setup to function deployment and usage of the API endpoint.
RAG is Dead … Long Live RAG
The post explains why traditional Retrieval-Augmented Generation (RAG) approaches no longer scale and how modern architectures, including GraphRAG, address these limitations. It highlights why data quality, metadata, and disciplined system design matter more than models or frameworks, and provides a practical foundation for building robust RAG systems, illustrated with IBM technologies but applicable far beyond them.
(outdated) Develop and Deploy Custom AI Agents to watsonx.ai on IBM Cloud
This blog post details the development and deployment of a customizable AI Agent using watsonx.ai. It covers motivations, architecture, and code for a weather query tool, explaining local execution, testing with pytest, and deployment via scripts. The integration with Streamlit UI is emphasized, showcasing seamless deployment processes and enhanced functionality for developers.
