SAP is rapidly advancing its use of AI agents on Joule, showcasing their ability to handle complex requests using a variety of tools. This tutorial serves as a foundation for building a custom AI agent on the Business Technology Platform (BTP). While not production-ready, it provides valuable insights into creating and extending AI agents using the LangGraph framework. Users will learn how to develop an AI agent within a Jupyter Notebook, deploy it as a REST API, and create a simple user interface. The tutorial covers essential functions, such as checking invoice statuses and sending emails, allowing users to design versatile and interactive AI assistants for business needs.
SAP Accelerates AI Agent Development on Business Technology Platform
SAP is making significant strides with AI agents through its Joule platform. These AI agents are remarkably efficient at managing complex requests by using an array of tools tailored to specific tasks. If you’re interested in building your own custom AI agent on SAP’s Business Technology Platform (BTP), there’s an informative tutorial that can serve as a valuable starting point.
The tutorial guides you through the process of creating an AI agent using the open-source framework LangGraph on BTP. Here are some highlights:
– Tutorial Intent: While this guide isn’t production-ready, it provides inspiration and a foundational understanding of how to create and expand your own AI agents.
– Technologies Used: You’ll explore how to develop an AI agent that functions as a REST-API, enhancing its ability to interact with various applications seamlessly.
Key Components of the Tutorial
The tutorial consists of several key sections, making it user-friendly for developers at various levels:
1. Background: Introduction to AI agents.
2. Architecture: Overview of the system design.
3. Prerequisites: Required tools and setups.
4. Development: Step-by-step instructions to build your AI agent in a Jupyter Notebook.
5. Deployment: Guidance on deploying your AI agent as a REST-API.
6. Sandbox Interface: Creating a basic user interface on top of the application.
Hands-On Example
To illustrate the agent’s capabilities, the tutorial presents a practical business scenario: “Send an email to Peter and let him know whether invoice XYZ has been paid.” While the agent may not connect to an actual ERP system, it simulates responses to showcase its functionality.
The tutorial emphasizes using Python functions as tools that the AI agent can utilize autonomously. This flexibility allows the agent to handle various tasks, such as checking invoice status, retrieving email addresses, and sending emails without hardcoded workflows.
Getting Started
To dive into the development process:
– Familiarize yourself with Python and Jupyter Notebooks.
– Install essential packages in your Python environment, including Langchain and Langgraph.
– Access the comprehensive code samples available in the designated GitHub repository for practical guidance.
Optionally, should you wish to implement an FAQ assistant for your AI agent, additional steps are included in the tutorial to facilitate this feature, expanding the agent’s functionality.
Conclusion
This tutorial offers a practical avenue for developers looking to harness the power of AI agents on the SAP BTP. Whether you’re an experienced programmer or just starting, the step-by-step guidance and sample codes will help you create a proficient AI agent tailored to your business needs.
Tags: SAP BTP, AI agents, LangGraph, Jupyter Notebook, REST API, Business Technology Platform, Custom AI Agent, Development Tutorial
What is a custom AI agent?
A custom AI agent is a software program that uses artificial intelligence to perform specific tasks for you. You can design it to answer questions, help with tasks, or provide information based on your needs.
Why should I create a custom AI agent?
Creating a custom AI agent can help save time and improve productivity. It can handle repetitive tasks, provide quick answers, and help you manage your projects more efficiently.
What skills do I need to create an AI agent?
You don’t need to be an expert, but basic programming knowledge is helpful. Familiarity with tools and platforms for AI development will make the process easier. There are many resources available to learn these skills.
How long does it take to create a custom AI agent?
The time it takes can vary. Simple agents can be created in a few hours, while more complex ones may take days or even weeks. It depends on what you want your agent to do and how much customization is involved.
Where can I learn to create a custom AI agent?
There are many online tutorials, courses, and communities where you can learn. Websites like Coursera, Udemy, and YouTube have helpful resources to guide you through the process step by step.