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.
A Bee API and Bee UI development example for adding a TypeScript tool made for the Bee Agent Framework
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.
CheatSheet “Ready to Go” for Bee API and UI development
The content outlines the setup process for a development environment aimed at contributing to the Bee API and Bee UI repositories within the broader Bee Stack. It details the steps of cloning repositories, starting infrastructure, configuring .env files, and launching both the Bee API and UI servers, ensuring readiness for development.
Create a Full-Screen Web-Chat with watsonx Assistant, IBM Cloud Code Engine and watsonx.ai
The blog post shows integrating watsonx Assistant and watsonx.ai to create a full-screen user interface for interacting with a large language model (LLM) using minimal coding. It outlines the motivation, architecture, setup process, and specific actions necessary to deploy the integration on IBM Cloud Code Engine.
Bee Agent example for a simple travel assistant using a custom tool and observe the agent behavior in detail (Bee Framework 0.0.34 and watsonx.ai)
This blog post explains the implementation of a custom travel assistant agent using the Bee Agent Framework. It covers creating a tool to suggest vacation locations and utilizing weather data, integrating with MLFlow for observability. The article emphasizes practical execution steps, system requirements, and the motivation behind combining location and weather insights for user queries.
Unlock watsonx Capabilities: Where do you start finding implementation examples when you are an AI engineer or developer?
IBM has launched the watsonx Developer Hub, consisting of four sections: Get Started, Capabilities, Guides, and Support. This Hub is a valuable resource for developers looking to learn about watsonx, emphasizing its significance in the development process.
An Example of how use the “Bee Agent Framework” (v0.0.33) with watsonx.ai
This blog post explores the Bee Agent Framework integration with watsonx.ai, detailing the setup process for a weather agent example on MacOS. It discusses necessary installations, environment variable configurations, and code updates needed due to framework changes. The execution output illustrates how the agent retrieves current weather data for Las Vegas.
Implementing LangChain AI Agent with WatsonxLLM for a Weather Queries application
This blog post describes the customization of the LangChain AI Agent example from IBM Developer using Watsonx in Python. It demonstrates the implementation of a weather query application with detailed steps. The post offers insight into model parameters, creating prompts, agent chains, tool definitions, and execution. Additionally, it provides links to additional resources for further exploration.
Does it work to use ChatWatsonx from langchain_ibm to implement an agent that invokes functions?
The blog post explores integrating ChatWatsonx with LangChain for function calls, using a weather example. It aims to understand AI agent tools and actions. The process includes defining tools functions, creating WatsonxChat instance, and implementing a structured ChatPromptTemplate. While not fully successful, it highlights the importance of the prompt.
Integrating langchain_ibm with watsonx and LangChain for function calls: Example and Tutorial
The blog post demonstrates using the ChatWatsonx class of langchain_ibm for "function calls" with LangChain and IBM watsonx™ AI. It provides an example of a chat function call for weather information for various cities. The post also includes instructions to set up and run the example. Additional resources and examples are also provided.
