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Generative AI Examples

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Introduction

GenAIExamples are designed to give developers an easy entry into generative AI, featuring microservice-based samples that simplify the processes of deploying, testing, and scaling GenAI applications. All examples are fully compatible with Docker and Kubernetes, supporting a wide range of hardware platforms such as Gaudi, Xeon, and NVIDIA GPU, and other hardwares, ensuring flexibility and efficiency for your GenAI adoption.

Architecture

GenAIComps is a service-based tool that includes microservice components such as llm, embedding, reranking, and so on. Using these components, various examples in GenAIExample can be constructed, including ChatQnA, DocSum, etc.

GenAIInfra, part of the OPEA containerization and cloud-native suite, enables quick and efficient deployment of GenAIExamples in the cloud.

GenAIEval measures service performance metrics such as throughput, latency, and accuracy for GenAIExamples. This feature helps users compare performance across various hardware configurations easily.

Getting Started

GenAIExamples offers flexible deployment options that cater to different user needs, enabling efficient use and deployment in various environments. Here’s a brief overview of the three primary methods: Python startup, Docker Compose, and Kubernetes.

Users can choose the most suitable approach based on ease of setup, scalability needs, and the environment in which they are operating.

Deployment Guide

Deployment are based on released docker images by default, check docker image list for detailed information. You can also build your own images following instructions.

Prerequisite

  • For Docker Compose based deployment, you should have docker compose installed. Refer to docker compose install.
  • For Kubernetes based deployment, we provide 3 ways from the easiest manifests to powerful GMC based deployment.
    • You should have a kubernetes cluster ready for use. If not, you can refer to k8s install to deploy one.
    • (Optional) You should have GMC installed to your kubernetes cluster if you want to try with GMC. Refer to GMC install for more information.
    • (Optional) You should have Helm (version >= 3.15) installed if you want to deploy with Helm Charts. Refer to the Helm Installation Guide for more information.

Deploy Examples

Use Case Docker Compose
Deployment on Xeon		 Docker Compose
Deployment on Gaudi		 Kubernetes with Manifests Kubernetes with Helm Charts Kubernetes with GMC
ChatQnA Xeon Instructions Gaudi Instructions ChatQnA with Manifests ChatQnA with Helm Charts ChatQnA with GMC
CodeGen Xeon Instructions Gaudi Instructions CodeGen with Manifests CodeGen with Helm Charts CodeGen with GMC
CodeTrans Xeon Instructions Gaudi Instructions CodeTrans with Manifests CodeTrans with Helm Charts CodeTrans with GMC
DocSum Xeon Instructions Gaudi Instructions DocSum with Manifests DocSum with Helm Charts DocSum with GMC
SearchQnA Xeon Instructions Gaudi Instructions Not Supported Not Supported SearchQnA with GMC
FaqGen Xeon Instructions Gaudi Instructions FaqGen with Manifests Not Supported FaqGen with GMC
Translation Xeon Instructions Gaudi Instructions Not Supported Not Supported Translation with GMC
AudioQnA Xeon Instructions Gaudi Instructions AudioQnA with Manifests Not Supported AudioQnA with GMC
VisualQnA Xeon Instructions Gaudi Instructions VisualQnA with Manifests Not Supported VisualQnA with GMC

Supported Examples

Check here for detailed information of supported examples, models, hardwares, etc.

Additional Content