Deploying VisualQnA on Intel® Gaudi® Processors¶

This document outlines the deployment process for a VisualQnA application utilizing the GenAIComps microservice pipeline on Intel Gaudi server. The steps include Docker image creation, container deployment via Docker Compose, and service execution to integrate microservices such as llm. We will publish the Docker images to Docker Hub, it will simplify the deployment process for this service.

VisualQnA Quick Start Deployment¶

This section describes how to quickly deploy and test the VisualQnA service manually on an Intel® Xeon® processor. The basic steps are:

Build Docker Images
Setup Environment Variables
Deploy the Services Using Docker Compose

Build Docker Images¶

First of all, you need to build Docker Images locally. This step can be ignored after the Docker images published to Docker hub.

Please refer the table below to build different microservices from source:

Microservice	Deployment Guide
MegaService	Build MegaService Docker Image
LVM and NGINX	Build LVM and NGINX Docker Images
vLLM or TGI	Build vLLM or Pull TGI Gaudi Image
UI	Basic UI build guide

Then run the command docker images, you will have the following 5 Docker Images:

opea/vllm-gaudi:latest
ghcr.io/huggingface/tgi-gaudi:2.3.1 (Optional)
opea/lvm:latest
opea/visualqna:latest
opea/visualqna-ui:latest
opea/nginx

Setup Environment Variables¶

Since the compose.yaml will consume some environment variables, you need to setup them in advance as below.

source set_env.sh

Note: Please replace with host_ip with you external IP address, do not use localhost.

Deploy the Services Using Docker Compose¶

cd GenAIExamples/VisualQnA/docker_compose/intel/hpu/gaudi/

docker compose -f compose.yaml up -d
# if use TGI as the LLM serving backend
docker compose -f compose_tgi.yaml up -d

NOTE: Users need at least one Gaudi cards to run the VisualQnA successfully.

After running docker compose, check if all the containers launched via docker compose have started.

Validate MicroServices¶

Follow the instructions to validate MicroServices.

Note: If you see an “Internal Server Error” from the curl command, wait a few minutes for the microserver to be ready and then try again.

LLM Microservice

http_proxy="" curl http://${host_ip}:9399/v1/lvm -XPOST -d '{"image": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC", "prompt":"What is this?"}' -H 'Content-Type: application/json'

MegaService

curl http://${host_ip}:8888/v1/visualqna -H "Content-Type: application/json" -d '{
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What'\''s in this image?"
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://www.ilankelman.org/stopsigns/australia.jpg"
            }
          }
        ]
      }
    ],
    "max_tokens": 300
    }'

Launch the UI¶

To access the frontend, open the following URL in your browser: http://{host_ip}:5173. By default, the UI runs on port 5173 internally. If you prefer to use a different host port to access the frontend, you can modify the port mapping in the compose.yaml file as shown below:

  visualqna-gaudi-ui-server:
    image: opea/visualqna-ui:latest
    ...
    ports:
      - "80:5173"