SAP is rapidly advancing with AI agents on its Joule platform, showcasing their ability to handle complex tasks by using various tools. If you’re interested in creating a custom AI agent on SAP’s Business Technology Platform (BTP), a helpful tutorial is available. While it’s not ready for production use, it serves as a fantastic starting point for learning how to build and customize your AI agent using the LangGraph framework. The tutorial covers essential steps, including developing the agent in a Jupyter Notebook, deploying it as a REST-API, and enhancing it with a user interface. You can find all the necessary code and resources on the provided GitHub repository.
SAP Accelerates AI Development with Joule
SAP is pushing ahead rapidly with its AI agents on Joule, marking an exciting time for businesses looking to streamline operations. These AI agents have the capability to handle complex requests by utilizing a suite of generic tools, making them a valuable resource for companies.
For those interested in creating custom AI agents on Business Technology Platform (BTP), there is a new tutorial available that serves as an excellent starting point. While the tutorial is not yet production-ready, it offers inspiration and practical guidance for building your own AI projects. Learn about how AI agents function and how to create and enhance them using the open-source framework LangGraph on BTP.
Key Highlights of the Tutorial:
– Background: Understand the context behind AI agents
– Architecture: Explore how the components work together
– Prerequisites: What you need to get started
– Hands-On Development: Create an AI agent in a Jupyter Notebook and deploy it as a REST API
– User Interface: Integrate a sandbox UI for user interaction
The full code for this tutorial can be accessed in a dedicated GitHub repository. A heartfelt shout-out goes to Can Abdulla for providing feedback prior to the blog’s launch.
Creating a Custom BTP AI Agent
The tutorial walks you through building an AI agent that can perform simple tasks, like sending an email to someone regarding the status of an invoice. To start, you don’t need a live connection to an ERP system; the tutorial uses mock responses for simplicity.
For example, users will define certain Python functions like get_invoice_status and send_email, which the AI agent can call to retrieve and send information. Additional tools can also be added for enhanced functionality, such as retrieving text from web links or checking lunch menus for a day.
With a minimal architecture, the key components needed include:
– SAP Generative AI Hub: To access the AI models
– Cloud Foundry: For deploying the code as a REST API
If you want your AI agent to answer SAP-specific questions, you will need to implement additional components such as SAP HANA Cloud and Mistral-Large-Instruct.
Beginner-Friendly Environment Setup
To follow along, you’ll need to set up a Python environment, ideally using Miniconda for simplicity. The tutorial provides the required package installations to equip your environment.
Once set up, you can execute functions that will interact with the AI agent. This setup allows for innovative features such as automating responses based on incoming questions, thereby enhancing user experience and engagement.
Conclusion
Whether you are a developer or a business leader, this opportunity to get hands-on with SAP’s AI agent technology is invaluable. By following the tutorial, you can gain insights into not just how to build your AI agent but also understand its functionalities and potential business applications.
For more on creating custom AI agents on BTP and getting started with SAP technology, visit the provided GitHub repository and delve into the resources available.
Primary Keyword: SAP AI Agents
Secondary Keywords: Custom AI Development, Business Technology Platform, Jupyter Notebook
Explore the future of AI with SAP and step into a world of limitless possibilities! Happy coding!
What is the tutorial about?
This tutorial teaches you how to create your very own custom AI agent. You’ll learn step-by-step how to design, build, and train it for specific tasks.
What do I need to start the tutorial?
To start, you need a computer with internet access, basic coding knowledge, and a willingness to learn. Some programming experience is helpful but not required.
Can I use this AI agent for any tasks?
Yes, you can customize the AI agent to perform many tasks, like answering questions, scheduling, or even providing customer support. It depends on how you build and train it.
How long will it take to create an AI agent?
The time varies, but you can expect to spend several hours to a few days to complete the tutorial and build your AI agent. It depends on your pace and how complex you want your agent to be.
Will I need any special software?
Yes, you will need some specific software tools for coding and training your AI agent, such as coding IDEs or machine learning libraries. The tutorial will guide you on what to download and how to set it up.