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Build MegaService of VisualQnA on Gaudi

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.

🚀 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.

1. Build LVM and NGINX Docker Images

git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
docker build --no-cache -t opea/lvm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/lvms/tgi-llava/Dockerfile .
docker build --no-cache -t opea/nginx:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/nginx/Dockerfile .

2. Pull TGI Gaudi Image

docker pull ghcr.io/huggingface/tgi-gaudi:2.0.5

3. Build MegaService Docker Image

To construct the Mega Service, we utilize the GenAIComps microservice pipeline within the visuralqna.py Python script. Build the MegaService Docker image using the command below:

git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/VisualQnA
docker build --no-cache -t opea/visualqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
cd ../..

4. Build UI Docker Image

Build frontend Docker image via below command:

cd GenAIExamples/VisualQnA/ui
docker build --no-cache -t opea/visualqna-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .

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

  1. ghcr.io/huggingface/tgi-gaudi:2.0.5
  2. opea/lvm-tgi:latest
  3. opea/visualqna:latest
  4. opea/visualqna-ui:latest
  5. opea/nginx

🚀 Start MicroServices and MegaService

Setup Environment Variables

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

export no_proxy=${your_no_proxy}
export http_proxy=${your_http_proxy}
export https_proxy=${your_http_proxy}
export LVM_MODEL_ID="llava-hf/llava-v1.6-mistral-7b-hf"
export LVM_ENDPOINT="http://${host_ip}:8399"
export LVM_SERVICE_PORT=9399
export MEGA_SERVICE_HOST_IP=${host_ip}
export LVM_SERVICE_HOST_IP=${host_ip}
export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8888/v1/visualqna"

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

Start all the services Docker Containers

cd GenAIExamples/VisualQnA/docker_compose/intel/hpu/gaudi/
docker compose -f compose.yaml up -d

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

Validate MicroServices and MegaService

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.

  1. 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'

  2. 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"