Add example for AudioQnA deploy in AMD ROCm

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

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+# Build Mega Service of AudioQnA on AMD ROCm GPU
+
+This document outlines the deployment process for a AudioQnA application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice
+pipeline on server on AMD ROCm GPU platform.
+
+## 🚀 Build Docker images
+
+### 1. Source Code install GenAIComps
+
+```bash
+git clone https://github.com/opea-project/GenAIComps.git
+cd GenAIComps
+```
+
+### 2. Build ASR Image
+
+```bash
+docker build -t opea/whisper:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/asr/whisper/dependency/Dockerfile .
+
+
+docker build -t opea/asr:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/asr/whisper/Dockerfile .
+```
+
+### 3. Build LLM Image
+
+```bash
+docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile .
+```
+
+Note:
+For compose for ROCm example AMD optimized image hosted in huggingface repo will be used for TGI service: ghcr.io/huggingface/text-generation-inference:2.3.1-rocm (https://github.com/huggingface/text-generation-inference)
+
+### 4. Build TTS Image
+
+```bash
+docker build -t opea/speecht5:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/tts/speecht5/dependency/Dockerfile .
+
+docker build -t opea/tts:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/tts/speecht5/Dockerfile .
+```
+
+### 6. Build MegaService Docker Image
+
+To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `audioqna.py` Python script. Build the MegaService Docker image using the command below:
+
+```bash
+git clone https://github.com/opea-project/GenAIExamples.git
+cd GenAIExamples/AudioQnA/
+docker build --no-cache -t opea/audioqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+```
+
+Then run the command `docker images`, you will have following images ready:
+
+1. `opea/whisper:latest`
+2. `opea/asr:latest`
+3. `opea/llm-tgi:latest`
+4. `opea/speecht5:latest`
+5. `opea/tts:latest`
+6. `opea/audioqna:latest`
+
+## 🚀 Set the environment variables
+
+Before starting the services with `docker compose`, you have to recheck the following environment variables.
+
+```bash
+export host_ip=<your External Public IP>    # export host_ip=$(hostname -I | awk '{print $1}')
+export HUGGINGFACEHUB_API_TOKEN=<your HF token>
+
+export TGI_LLM_ENDPOINT=http://$host_ip:3006
+export LLM_MODEL_ID=Intel/neural-chat-7b-v3-3
+
+export ASR_ENDPOINT=http://$host_ip:7066
+export TTS_ENDPOINT=http://$host_ip:7055
+
+export MEGA_SERVICE_HOST_IP=${host_ip}
+export ASR_SERVICE_HOST_IP=${host_ip}
+export TTS_SERVICE_HOST_IP=${host_ip}
+export LLM_SERVICE_HOST_IP=${host_ip}
+
+export ASR_SERVICE_PORT=3001
+export TTS_SERVICE_PORT=3002
+export LLM_SERVICE_PORT=3007
+```
+
+or use set_env.sh file to setup environment variables.
+
+Note: Please replace with host_ip with your external IP address, do not use localhost.
+
+Note: In order to limit access to a subset of GPUs, please pass each device individually using one or more -device /dev/dri/rendered, where is the card index, starting from 128. (https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html#docker-restrict-gpus)
+
+Example for set isolation for 1 GPU
+
+      - /dev/dri/card0:/dev/dri/card0
+      - /dev/dri/renderD128:/dev/dri/renderD128
+
+Example for set isolation for 2 GPUs
+
+      - /dev/dri/card0:/dev/dri/card0
+      - /dev/dri/renderD128:/dev/dri/renderD128
+      - /dev/dri/card0:/dev/dri/card0
+      - /dev/dri/renderD129:/dev/dri/renderD129
+
+Please find more information about accessing and restricting AMD GPUs in the link (https://rocm.docs.amd.com/projects/install-on-linux/en/latest/how-to/docker.html#docker-restrict-gpus)
+
+## 🚀 Start the MegaService
+
+```bash
+cd GenAIExamples/AudioQnA/docker_compose/amd/gpu/rocm/
+docker compose up -d
+```
+
+In following cases, you could build docker image from source by yourself.
+
+- Failed to download the docker image.
+- If you want to use a specific version of Docker image.
+
+Please refer to 'Build Docker Images' in below.
+
+## 🚀 Consume the AudioQnA Service
+
+Test the AudioQnA megaservice by recording a .wav file, encoding the file into the base64 format, and then sending the
+base64 string to the megaservice endpoint. The megaservice will return a spoken response as a base64 string. To listen
+to the response, decode the base64 string and save it as a .wav file.
+
+```bash
+curl http://${host_ip}:3008/v1/audioqna \
+  -X POST \
+  -d '{"audio": "UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA", "max_tokens":64}' \
+  -H 'Content-Type: application/json' | sed 's/^"//;s/"$//' | base64 -d > output.wav
+```
+
+## 🚀 Test MicroServices
+
+```bash
+# whisper service
+curl http://${host_ip}:7066/v1/asr \
+  -X POST \
+  -d '{"audio": "UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA"}' \
+  -H 'Content-Type: application/json'
+
+# asr microservice
+curl http://${host_ip}:3001/v1/audio/transcriptions \
+  -X POST \
+  -d '{"byte_str": "UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA"}' \
+  -H 'Content-Type: application/json'
+
+# tgi service
+curl http://${host_ip}:3006/generate \
+  -X POST \
+  -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
+  -H 'Content-Type: application/json'
+
+# llm microservice
+curl http://${host_ip}:3007/v1/chat/completions\
+  -X POST \
+  -d '{"query":"What is Deep Learning?","max_tokens":17,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":false}' \
+  -H 'Content-Type: application/json'
+
+# speecht5 service
+curl http://${host_ip}:7055/v1/tts \
+  -X POST \
+  -d '{"text": "Who are you?"}' \
+  -H 'Content-Type: application/json'
+
+# tts microservice
+curl http://${host_ip}:3002/v1/audio/speech \
+  -X POST \
+  -d '{"text": "Who are you?"}' \
+  -H 'Content-Type: application/json'
+
+```

AudioQnA/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:
+  whisper-service:
+    image: ${REGISTRY:-opea}/whisper:${TAG:-latest}
+    container_name: whisper-service
+    ports:
+      - "7066:7066"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+    restart: unless-stopped
+  asr:
+    image: ${REGISTRY:-opea}/asr:${TAG:-latest}
+    container_name: asr-service
+    ports:
+      - "3001:9099"
+    ipc: host
+    environment:
+      ASR_ENDPOINT: ${ASR_ENDPOINT}
+  speecht5-service:
+    image: ${REGISTRY:-opea}/speecht5:${TAG:-latest}
+    container_name: speecht5-service
+    ports:
+      - "7055:7055"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+    restart: unless-stopped
+  tts:
+    image: ${REGISTRY:-opea}/tts:${TAG:-latest}
+    container_name: tts-service
+    ports:
+      - "3002:9088"
+    ipc: host
+    environment:
+      TTS_ENDPOINT: ${TTS_ENDPOINT}
+  tgi-service:
+    image: ghcr.io/huggingface/text-generation-inference:2.3.1-rocm
+    container_name: tgi-service
+    ports:
+      - "3006:80"
+    volumes:
+     - "./data:/data"
+    shm_size: 1g
+    devices:
+      - /dev/kfd:/dev/kfd
+      - /dev/dri/card1:/dev/dri/card1
+      - /dev/dri/renderD136:/dev/dri/renderD136
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
+      HF_HUB_DISABLE_PROGRESS_BARS: 1
+      HF_HUB_ENABLE_HF_TRANSFER: 0
+    command: --model-id ${LLM_MODEL_ID}
+    cap_add:
+      - SYS_PTRACE
+    group_add:
+      - video
+    security_opt:
+      - seccomp:unconfined
+    ipc: host
+  llm:
+    image: ${REGISTRY:-opea}/llm-tgi:${TAG:-latest}
+    container_name: llm-tgi-server
+    depends_on:
+      - tgi-service
+    ports:
+      - "3007:9000"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      TGI_LLM_ENDPOINT: ${TGI_LLM_ENDPOINT}
+      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
+    restart: unless-stopped
+  audioqna-backend-server:
+    image: ${REGISTRY:-opea}/audioqna:${TAG:-latest}
+    container_name: audioqna-xeon-backend-server
+    depends_on:
+      - asr
+      - llm
+      - tts
+    ports:
+      - "3008:8888"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - MEGA_SERVICE_HOST_IP=${MEGA_SERVICE_HOST_IP}
+      - ASR_SERVICE_HOST_IP=${ASR_SERVICE_HOST_IP}
+      - ASR_SERVICE_PORT=${ASR_SERVICE_PORT}
+      - LLM_SERVICE_HOST_IP=${LLM_SERVICE_HOST_IP}
+      - LLM_SERVICE_PORT=${LLM_SERVICE_PORT}
+      - TTS_SERVICE_HOST_IP=${TTS_SERVICE_HOST_IP}
+      - TTS_SERVICE_PORT=${TTS_SERVICE_PORT}
+    ipc: host
+    restart: always
+
+networks:
+  default:
+    driver: bridge

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

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+#!/usr/bin/env bash                                                                                                           set_env.sh
+
+# Copyright (C) 2024 Advanced Micro Devices, Inc.
+# SPDX-License-Identifier: Apache-2.0
+
+
+# export host_ip=<your External Public IP>    # export host_ip=$(hostname -I | awk '{print $1}')
+
+export host_ip="192.165.1.21"
+export HUGGINGFACEHUB_API_TOKEN=${YOUR_HUGGINGFACEHUB_API_TOKEN}
+# <token>
+
+export TGI_LLM_ENDPOINT=http://$host_ip:3006
+export LLM_MODEL_ID=Intel/neural-chat-7b-v3-3
+
+export ASR_ENDPOINT=http://$host_ip:7066
+export TTS_ENDPOINT=http://$host_ip:7055
+
+export MEGA_SERVICE_HOST_IP=${host_ip}
+export ASR_SERVICE_HOST_IP=${host_ip}
+export TTS_SERVICE_HOST_IP=${host_ip}
+export LLM_SERVICE_HOST_IP=${host_ip}
+
+export ASR_SERVICE_PORT=3001
+export TTS_SERVICE_PORT=3002
+export LLM_SERVICE_PORT=3007