Added compose example for VisualQnA deployment on AMD ROCm systems

VisualQnA/docker_compose/amd/gpu/rocm/README.md

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+# Build Mega Service of VisualQnA on AMD ROCm
+
+This document outlines the deployment process for a VisualQnA application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline on Intel Xeon 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 soon, it will simplify the deployment process for this service.
+
+## 🚀 Build Docker Images
+
+First of all, you need to build Docker Images locally and install the python package of it.
+
+### 1. Build LVM and NGINX Docker Images
+
+```bash
+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. Build MegaService Docker Image
+
+To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `visualqna.py` Python script. Build MegaService Docker image via below command:
+
+```bash
+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 .
+```
+
+### 3. Build UI Docker Image
+
+Build frontend Docker image via below command:
+
+```bash
+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 .
+```
+
+### 4. Pull TGI AMD ROCm Image
+
+```bash
+docker pull ghcr.io/huggingface/text-generation-inference:2.4.1-rocm
+```
+
+Then run the command `docker images`, you will have the following 5 Docker Images:
+
+1. `ghcr.io/huggingface/text-generation-inference:2.4.1-rocm`
+2. `opea/lvm-tgi:latest`
+3. `opea/visualqna:latest`
+4. `opea/visualqna-ui:latest`
+5. `opea/nginx`
+
+## 🚀 Start Microservices
+
+### Setup Environment Variables
+
+Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.
+
+**Export the value of the public IP address of your ROCM server to the `host_ip` environment variable**
+
+> Change the External_Public_IP below with the actual IPV4 value
+
+```
+export host_ip="External_Public_IP"
+```
+
+**Append the value of the public IP address to the no_proxy list**
+
+```
+export your_no_proxy="${your_no_proxy},${host_ip}"
+```
+
+```bash
+export HOST_IP=${your_host_ip}
+export VISUALQNA_TGI_SERVICE_PORT="8399"
+export VISUALQNA_HUGGINGFACEHUB_API_TOKEN={your_hugginface_api_token}
+export VISUALQNA_CARD_ID="card1"
+export VISUALQNA_RENDER_ID="renderD136"
+export LVM_MODEL_ID="Xkev/Llama-3.2V-11B-cot"
+export MODEL="llava-hf/llava-v1.6-mistral-7b-hf"
+export LVM_ENDPOINT="http://${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://${HOST_IP}:18003/v1/visualqna"
+export FRONTEND_SERVICE_IP=${HOST_IP}
+export FRONTEND_SERVICE_PORT=18001
+export BACKEND_SERVICE_NAME=visualqna
+export BACKEND_SERVICE_IP=${HOST_IP}
+export BACKEND_SERVICE_PORT=18002
+export NGINX_PORT=18003
+
+```
+
+Note: Please replace with `host_ip` with you external IP address, do not use localhost.
+
+Note: You can use set_env.sh file with bash command (. setset_env.sh) to set up needed variables.
+
+### Start all the services Docker Containers
+
+> Before running the docker compose command, you need to be in the folder that has the docker compose yaml file
+
+```bash
+cd GenAIExamples/VisualQnA/docker_compose/amd/gpu/rocm
+```
+
+```bash
+docker compose -f compose.yaml up -d
+```
+
+### Validate Microservices
+
+Follow the instructions to validate MicroServices.
+
+> Note: If you see an "Internal Server Error" from the `curl` command, wait a few minutes for the microserver to be ready and then try again.
+
+1. LLM Microservice
+
+   ```bash
+   http_proxy="" curl http://${host_ip}:9399/v1/lvm -XPOST -d '{"image": "iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAFUlEQVR42mP8/5+hnoEIwDiqkL4KAcT9GO0U4BxoAAAAAElFTkSuQmCC", "prompt":"What is this?"}' -H 'Content-Type: application/json'
+   ```
+
+2. MegaService
+
+```bash
+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:
+
+```yaml
+  visualqna-gaudi-ui-server:
+    image: opea/visualqna-ui:latest
+    ...
+    ports:
+      - "80:5173"
+```

VisualQnA/docker_compose/amd/gpu/rocm/compose.yaml

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+# Copyright (C) 2024 Advanced Micro Devices, Inc.
+# SPDX-License-Identifier: Apache-2.0
+
+services:
+  visualqna-llava-tgi-service:
+    image: ghcr.io/huggingface/text-generation-inference:2.4.1-rocm
+    container_name: visualqna-tgi-service
+    ports:
+      - "${VISUALQNA_TGI_SERVICE_PORT:-8399}:80"
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      TGI_LLM_ENDPOINT: "http://${HOST_IP}:${VISUALQNA_TGI_SERVICE_PORT}"
+      HUGGINGFACEHUB_API_TOKEN: ${VISUALQNA_HUGGINGFACEHUB_API_TOKEN}
+      HUGGING_FACE_HUB_TOKEN: ${VISUALQNA_HUGGINGFACEHUB_API_TOKEN}
+    volumes:
+      - "/var/opea/visualqna-service/data:/data"
+    shm_size: 64g
+    devices:
+      - /dev/kfd:/dev/kfd
+      - /dev/dri/:/dev/dri/
+    cap_add:
+      - SYS_PTRACE
+    group_add:
+      - video
+    security_opt:
+      - seccomp:unconfined
+    ipc: host
+    command: --model-id ${LVM_MODEL_ID} --max-input-length 4096 --max-total-tokens 8192
+  lvm-tgi:
+    image: ${REGISTRY:-opea}/lvm-tgi:${TAG:-latest}
+    container_name: lvm-tgi-server
+    depends_on:
+      - visualqna-llava-tgi-service
+    ports:
+      - "9399:9399"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      LVM_ENDPOINT: ${LVM_ENDPOINT}
+      HF_HUB_DISABLE_PROGRESS_BARS: 1
+      HF_HUB_ENABLE_HF_TRANSFER: 0
+    restart: unless-stopped
+  visualqna-rocm-backend-server:
+    image: ${REGISTRY:-opea}/visualqna:${TAG:-latest}
+    container_name: visualqna-rocm-backend-server
+    depends_on:
+      - visualqna-llava-tgi-service
+      - lvm-tgi
+    ports:
+      - "${BACKEND_SERVICE_PORT:-8888}:8888"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - MEGA_SERVICE_HOST_IP=${MEGA_SERVICE_HOST_IP}
+      - LVM_SERVICE_HOST_IP=${LVM_SERVICE_HOST_IP}
+    ipc: host
+    restart: always
+  visualqna-rocm-ui-server:
+    image: ${REGISTRY:-opea}/visualqna-ui:${TAG:-latest}
+    container_name: visualqna-rocm-ui-server
+    depends_on:
+      - visualqna-rocm-backend-server
+    ports:
+      - "${FRONTEND_SERVICE_PORT:-5173}:5173"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - BACKEND_BASE_URL=${BACKEND_SERVICE_ENDPOINT}
+    ipc: host
+    restart: always
+  visualqna-nginx-server:
+    image: ${REGISTRY:-opea}/nginx:${TAG:-latest}
+    container_name: visualqna-rocm-nginx-server
+    depends_on:
+      - visualqna-rocm-backend-server
+      - visualqna-rocm-ui-server
+    ports:
+      - "${NGINX_PORT:-80}:80"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - FRONTEND_SERVICE_IP=${HOST_IP}
+      - FRONTEND_SERVICE_PORT=${FRONTEND_SERVICE_PORT}
+      - BACKEND_SERVICE_NAME=${BACKEND_SERVICE_NAME}
+      - BACKEND_SERVICE_IP=${HOST_IP}
+      - BACKEND_SERVICE_PORT=${BACKEND_SERVICE_PORT}
+    ipc: host
+    restart: always
+
+networks:
+  default:
+    driver: bridge

VisualQnA/docker_compose/amd/gpu/rocm/set_env.sh

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+#!/usr/bin/env bash
+
+# Copyright (C) 2024 Advanced Micro Devices, Inc
+# SPDX-License-Identifier: Apache-2.0
+
+export HOST_IP=${Your_host_ip_address}
+export VISUALQNA_TGI_SERVICE_PORT="8399"
+export VISUALQNA_HUGGINGFACEHUB_API_TOKEN=${Your_HUGGINGFACEHUB_API_TOKEN}
+export VISUALQNA_CARD_ID="card1"
+export VISUALQNA_RENDER_ID="renderD136"
+export LVM_MODEL_ID="Xkev/Llama-3.2V-11B-cot"
+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}:${BACKEND_SERVICE_PORT}/v1/visualqna"
+export FRONTEND_SERVICE_IP=${HOST_IP}
+export FRONTEND_SERVICE_PORT=18001
+export BACKEND_SERVICE_NAME=visualqna
+export BACKEND_SERVICE_IP=${HOST_IP}
+export BACKEND_SERVICE_PORT=18002
+export NGINX_PORT=18003