Automate AI Workflows with Qualcomm AI Runtime

What We’re Building

In this tutorial, we will build a sophisticated AI workflow automation system using the Qualcomm AI Runtime (QAIRT). This system will allow you to efficiently deploy AI models, manage inference tasks, and handle model updates with minimal downtime. The finished project will streamline the deployment process, reduce errors, and optimize resource usage.

The system leverages advanced features of QAIRT, such as model optimization, efficient resource allocation, and seamless integration with various AI frameworks. By the end of this tutorial, you will have a deep understanding of how to automate complex AI workflows, enabling scalable and efficient AI deployments in production environments.

Setup and Installation

To begin, we need to set up our development environment and install the necessary tools. This includes the Qualcomm AI Runtime SDK, which provides the tools and libraries required to build and optimize AI workflows.

pip install qairt-sdk

Next, configure your environment variables to include the necessary paths for the QAIRT SDK. This ensures that the SDK tools can be accessed from any directory in your terminal.

# .env file example
QAIRT_HOME=/path/to/qairt-sdk
PATH=$QAIRT_HOME/bin:$PATH
  

Make sure to replace /path/to/qairt-sdk...