Skip to content

Home

Jump to bottom
Jose Moreira Batista Neto edited this page Jan 3, 2024 · 5 revisions

Welcome to the dstoolkit-AI-Jumpstart-Kit wiki!

The "AI Orchestration Jumpstart Kit" is a toolkit designed to streamline and accelerate the adoption of AI technologies. It provides pre-built components, best practices, and documentation for easier integration of AI solutions into various environments.

Introduction

The package provides repeatable IP and a sample Semantic Kernel SDK-based prototype implementation with configurable parameters and settings.

  • Allows for quick start use of SK without the need to develop code
  • Enables team members to work the solution independently
  • Includes:
    • Endpoints for basic SK requests
    • Endpoints for creating more SK semantic functions prompts and configuration files
    • Implementation of an in-Memory Vector Database
    • Reference source code

The AI Orchestration Jumpstart Kit is a tool designed to enhance the efficiency and productivity of AI development teams, particularly those with minimal experience with the Semantic Kernel. The kit provides a repeatable IP and a prototype implementation with configurable parameters and settings, eliminating the need for extensive code development. It enables effective division of labor within teams, facilitating independent work on different aspects of a project, such as creating Semantic Functions or developing the Web UI. The kit has proven its value in various scenarios, including the development of a Health Clinic Copilot system, demonstrating its potential to accelerate project completion times and reduce development costs.

History

Following involvement in a hackathon project, we were tasked with developing a solution for a Health Clinic Copilot. This system was designed to respond to customer inquiries using a database of medical facts. Facilitated by the WebAPI in this IP, it allowed our team to divide and conquer different tasks without overlap or conflict. Some team members focused on refining the semantic functions for the AI prompts, while others concentrated on gathering and organizing the medical facts. Importantly, all of this was achieved without the need for Semantic kernel code development.

Clone this wiki locally