I want to share my experience in the cloud, AI, and agents development areas.
This post explains how to create, test, and integrate AI support agents using IBM's watsonx.ai and watsonx Orchestrate. It describes an example to integrate a Specialist Support Agent for DB2, into multi-agent orchestration, and highlights best practices for creating efficient agent workflows and accurate responses while anticipating potential complexities.
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.
This blog post explains how to deploy a fine-tuned model to IBM watsonx on IBM Cloud. It highlights the advantages of using this platform, such as avoiding infrastructure management and ensuring enterprise security, as well as detailed steps for configuration, deployment, and accessing the model from IBM watsonx.
This blog post provides updates on the InstructLab project by IBM and Red Hat, detailing installation and configuration changes. It discusses new default locations for files and troubleshooting steps for model serving, emphasizing an overall installation process that remains largely consistent with prior guidance while noting minor user-friendly adjustments.
This blog post discusses the creation of a custom Bee Agent that operates independently from the Bee Stack and interacts in German. It explores requirements, agent examples, coding in TypeScript, and GitHub references. The author implements an agent using a specific system prompt while addressing the challenges of ensuring consistent output in German.
This blog post describes a web chat application using a large language model on watsonx, with the interface built in Streamlit.io. It focuses on motivation, architecture, code sections, and local setup, featuring basic authentication and options for user interaction. The author highlights Streamlit’s rapid prototyping capabilities and ease of use with Python.
In 2024, I published 35 blog posts focusing on innovation in AI and development, emphasizing the Bee Agent Framework and IBM's watsonx.ai. The highlights including creating cheat sheets, exploring large language models, and providing practical guides. That boost my excitement for future challenges in 2025.
This blog post explains how to integrate a custom Python tool into the Bee Agent using the Bee UI, focusing on real-time weather data retrieval. It outlines the setup process, agent customization, and testing to ensure functionality. Clear descriptions and agent interactions enhance the tool's efficacy and future applications.
The content shows my Bee Agent Framework and Bee Stack development learning journey, focusing on their integration with the watsonx.ai. It covers the setup process for different agent applications, including a weather retrieval agent and a travel assistant. It also provides guidance for contributing to the development of Bee API and UI and configuring Podman.
The blog post explains the integration of a custom TypeScript tool, TravelAgentTool, into the Bee API and UI to extend the Bee Framework's functionality. It details the steps for setup, including modifying source files, configuring environment variables, and demonstrating its use in travel inquiries. Code instructions for implementation are provided throughout.
Thomas Suedbroecker's Blog 