SearchQnA App - Adding files to deploy SearchQnA application on AMD GPU (#1193)

Signed-off-by: Chingis Yundunov <YundunovCN@sibedge.com>
This commit is contained in:
chyundunovDatamonsters
2025-01-27 09:58:55 +07:00
committed by GitHub
parent ed163087ba
commit 39abef8be8
4 changed files with 525 additions and 0 deletions

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# Build and deploy SearchQnA Application on AMD GPU (ROCm)
## Build images
### Build Embedding Image
```bash
git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/src/Dockerfile .
```
### Build Retriever Image
```bash
docker build --no-cache -t opea/web-retriever-chroma:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/web_retrievers/src/Dockerfile .
```
### Build Rerank Image
```bash
docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/rerankings/src/Dockerfile .
```
### Build the LLM Docker Image
```bash
docker build -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/src/text-generation/Dockerfile .
```
### Build the MegaService Docker Image
```bash
git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/SearchQnA
docker build --no-cache -t opea/searchqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
```
### Build the UI Docker Image
```bash
cd GenAIExamples/SearchQnA/ui
docker build --no-cache -t opea/opea/searchqna-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
```
## Deploy SearchQnA Application
### Features of Docker compose for AMD GPUs
1. Added forwarding of GPU devices to the container TGI service with instructions:
```yaml
shm_size: 1g
devices:
- /dev/kfd:/dev/kfd
- /dev/dri/:/dev/dri/
cap_add:
- SYS_PTRACE
group_add:
- video
security_opt:
- seccomp:unconfined
```
In this case, all GPUs are thrown. To reset a specific GPU, you need to use specific device names cardN and renderN.
For example:
```yaml
shm_size: 1g
devices:
- /dev/kfd:/dev/kfd
- /dev/dri/card0:/dev/dri/card0
- /dev/dri/render128:/dev/dri/render128
cap_add:
- SYS_PTRACE
group_add:
- video
security_opt:
- seccomp:unconfined
```
To find out which GPU device IDs cardN and renderN correspond to the same GPU, use the GPU driver utility
### Go to the directory with the Docker compose file
```bash
cd GenAIExamples/SearchQnA/docker_compose/amd/gpu/rocm
```
### Set environments
In the file "GenAIExamples/SearchQnA/docker_compose/amd/gpu/rocm/set_env.sh " it is necessary to set the required values. Parameter assignments are specified in the comments for each variable setting command
```bash
chmod +x set_env.sh
. set_env.sh
```
### Run services
```
docker compose up -d
```
# Validate the MicroServices and MegaService
## Validate TEI service
```bash
curl http://${SEARCH_HOST_IP}:3001/embed \
-X POST \
-d '{"inputs":"What is Deep Learning?"}' \
-H 'Content-Type: application/json'
```
## Validate Embedding service
```bash
curl http://${SEARCH_HOST_IP}:3002/v1/embeddings\
-X POST \
-d '{"text":"hello"}' \
-H 'Content-Type: application/json'
```
## Validate Web Retriever service
```bash
export your_embedding=$(python3 -c "import random; embedding = [random.uniform(-1, 1) for _ in range(768)]; print(embedding)")
curl http://${SEARCH_HOST_IP}:3003/v1/web_retrieval \
-X POST \
-d "{\"text\":\"What is the 2024 holiday schedule?\",\"embedding\":${your_embedding}}" \
-H 'Content-Type: application/json'
```
## Validate TEI Reranking service
```bash
curl http://${SEARCH_HOST_IP}:3004/rerank \
-X POST \
-d '{"query":"What is Deep Learning?", "texts": ["Deep Learning is not...", "Deep learning is..."]}' \
-H 'Content-Type: application/json'
```
## Validate Reranking service
```bash
curl http://${SEARCH_HOST_IP}:3005/v1/reranking\
-X POST \
-d '{"initial_query":"What is Deep Learning?", "retrieved_docs": [{"text":"Deep Learning is not..."}, {"text":"Deep learning is..."}]}' \
-H 'Content-Type: application/json'
```
## Validate TGI service
```bash
curl http://${SEARCH_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'
```
## Validate LLM service
```bash
curl http://${SEARCH_HOST_IP}:3007/v1/chat/completions\
-X POST \
-d '{"query":"What is Deep Learning?","max_tokens":17,"top_k":10,"top_p":0.95,"typical_p":0.95,"temperature":0.01,"repetition_penalty":1.03,"streaming":true}' \
-H 'Content-Type: application/json'
```
## Validate MegaService
```bash
curl http://${SEARCH_HOST_IP}:3008/v1/searchqna -H "Content-Type: application/json" -d '{
"messages": "What is the latest news? Give me also the source link.",
"stream": "True"
}'
```

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# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
# SPDX-License-Identifier: Apache-2.0
services:
search-tei-embedding-service:
image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
container_name: search-tei-embedding-server
ports:
- "3001:80"
volumes:
- "./data:/data"
shm_size: 1g
environment:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
HF_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
HUGGING_FACE_HUB_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
HUGGINGFACEHUB_API_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
command: --model-id ${SEARCH_EMBEDDING_MODEL_ID} --auto-truncate
search-embedding:
image: ${REGISTRY:-opea}/embedding:${TAG:-latest}
container_name: search-embedding-server
depends_on:
- search-tei-embedding-service
ports:
- "3002:6000"
ipc: host
environment:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
TEI_EMBEDDING_HOST_IP: ${SEARCH_HOST_IP}
TEI_EMBEDDING_ENDPOINT: ${SEARCH_TEI_EMBEDDING_ENDPOINT}
HF_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
restart: unless-stopped
search-web-retriever:
image: ${REGISTRY:-opea}/web-retriever:${TAG:-latest}
container_name: search-web-retriever-server
ports:
- "3003:7077"
ipc: host
environment:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
TEI_EMBEDDING_ENDPOINT: ${SEARCH_TEI_EMBEDDING_ENDPOINT}
GOOGLE_API_KEY: ${SEARCH_GOOGLE_API_KEY}
GOOGLE_CSE_ID: ${SEARCH_GOOGLE_CSE_ID}
restart: unless-stopped
search-tei-reranking-service:
image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
container_name: search-tei-reranking-server
ports:
- "3004:80"
volumes:
- "./data:/data"
shm_size: 1g
environment:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
command: --model-id ${SEARCH_RERANK_MODEL_ID} --auto-truncate
search-reranking:
image: ${REGISTRY:-opea}/reranking:${TAG:-latest}
container_name: search-reranking-server
depends_on:
- search-tei-reranking-service
ports:
- "3005:8000"
ipc: host
environment:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
TEI_RERANKING_ENDPOINT: ${SEARCH_TEI_RERANKING_ENDPOINT}
HF_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
HUGGING_FACE_HUB_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
HUGGINGFACEHUB_API_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
restart: unless-stopped
search-tgi-service:
image: ghcr.io/huggingface/text-generation-inference:2.3.1-rocm
container_name: search-tgi-service
ports:
- "3006:80"
volumes:
- "./data:/data"
environment:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
HUGGING_FACE_HUB_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
HUGGINGFACEHUB_API_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
shm_size: 1g
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 ${SEARCH_LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048
search-llm:
image: ${REGISTRY:-opea}/llm-textgen:${TAG:-latest}
container_name: search-llm-server
depends_on:
- search-tgi-service
ports:
- "3007:9000"
ipc: host
environment:
no_proxy: ${no_proxy}
http_proxy: ${http_proxy}
https_proxy: ${https_proxy}
TGI_LLM_ENDPOINT: ${SEARCH_TGI_LLM_ENDPOINT}
HUGGINGFACEHUB_API_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
LLM_ENDPOINT: ${SEARCH_TGI_LLM_ENDPOINT}
LLM_MODEL_ID: ${SEARCH_LLM_MODEL_ID}
LLM_MODEL: ${SEARCH_LLM_MODEL_ID}
HF_TOKEN: ${SEARCH_HUGGINGFACEHUB_API_TOKEN}
OPENAI_API_KEY: ${SEARCH_OPENAI_API_KEY}
restart: unless-stopped
search-backend-server:
image: ${REGISTRY:-opea}/searchqna:${TAG:-latest}
container_name: search-backend-server
depends_on:
- search-tei-embedding-service
- search-embedding
- search-web-retriever
- search-tei-reranking-service
- search-reranking
- search-tgi-service
- search-llm
ports:
- "${SEARCH_BACKEND_SERVICE_PORT:-3008}:8888"
environment:
- no_proxy=${no_proxy}
- https_proxy=${https_proxy}
- http_proxy=${http_proxy}
- MEGA_SERVICE_HOST_IP=${SEARCH_MEGA_SERVICE_HOST_IP}
- EMBEDDING_SERVICE_HOST_IP=${SEARCH_EMBEDDING_SERVICE_HOST_IP}
- WEB_RETRIEVER_SERVICE_HOST_IP=${SEARCH_WEB_RETRIEVER_SERVICE_HOST_IP}
- RERANK_SERVICE_HOST_IP=${SEARCH_RERANK_SERVICE_HOST_IP}
- LLM_SERVICE_HOST_IP=${SEARCH_LLM_SERVICE_HOST_IP}
- EMBEDDING_SERVICE_PORT=${SEARCH_EMBEDDING_SERVICE_PORT}
- WEB_RETRIEVER_SERVICE_PORT=${SEARCH_WEB_RETRIEVER_SERVICE_PORT}
- RERANK_SERVICE_PORT=${SEARCH_RERANK_SERVICE_PORT}
- LLM_SERVICE_PORT=${SEARCH_LLM_SERVICE_PORT}
ipc: host
restart: always
search-ui-server:
image: ${REGISTRY:-opea}/searchqna-ui:${TAG:-latest}
container_name: search-ui-server
depends_on:
- search-backend-server
ports:
- "${SEARCH_FRONTEND_SERVICE_PORT:-5173}:5173"
environment:
- no_proxy=${no_proxy}
- https_proxy=${https_proxy}
- http_proxy=${http_proxy}
- BACKEND_BASE_URL=${SEARCH_BACKEND_SERVICE_ENDPOINT}
ipc: host
restart: always
networks:
default:
driver: bridge

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#!/usr/bin/env bash
# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
# SPDX-License-Identifier: Apache-2.0
export SEARCH_HOST_IP=10.53.22.29
export SEARCH_EXTERNAL_HOST_IP=68.69.180.77
export SEARCH_EMBEDDING_MODEL_ID='BAAI/bge-base-en-v1.5'
export SEARCH_TEI_EMBEDDING_ENDPOINT=http://${SEARCH_HOST_IP}:3001
export SEARCH_RERANK_MODEL_ID='BAAI/bge-reranker-base'
export SEARCH_TEI_RERANKING_ENDPOINT=http://${SEARCH_HOST_IP}:3004
export SEARCH_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export SEARCH_OPENAI_API_KEY=${OPENAI_API_KEY}
export SEARCH_TGI_LLM_ENDPOINT=http://${SEARCH_HOST_IP}:3006
export SEARCH_LLM_MODEL_ID='Intel/neural-chat-7b-v3-3'
export SEARCH_MEGA_SERVICE_HOST_IP=${SEARCH_EXTERNAL_HOST_IP}
export SEARCH_EMBEDDING_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_WEB_RETRIEVER_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_RERANK_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_LLM_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_EMBEDDING_SERVICE_PORT=3002
export SEARCH_WEB_RETRIEVER_SERVICE_PORT=3003
export SEARCH_RERANK_SERVICE_PORT=3005
export SEARCH_LLM_SERVICE_PORT=3007
export SEARCH_FRONTEND_SERVICE_PORT=18143
export SEARCH_BACKEND_SERVICE_PORT=18142
export SEARCH_BACKEND_SERVICE_ENDPOINT=http://${SEARCH_EXTERNAL_HOST_IP}:${SEARCH_BACKEND_SERVICE_PORT}/v1/searchqna
export SEARCH_GOOGLE_API_KEY=${GOOGLE_API_KEY}
export SEARCH_GOOGLE_CSE_ID=${GOOGLE_CSE_ID}

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#!/bin/bash
# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
set -xe
IMAGE_REPO=${IMAGE_REPO:-"opea"}
IMAGE_TAG=${IMAGE_TAG:-"latest"}
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG}
WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests"
ip_address=$(hostname -I | awk '{print $1}')
function build_docker_images() {
cd $WORKPATH/docker_image_build
git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
echo "Build all the images with --no-cache, check docker_image_build.log for details..."
service_list="searchqna searchqna-ui embedding web-retriever reranking llm-textgen"
docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
docker pull ghcr.io/huggingface/text-generation-inference:2.3.1-rocm
docker images && sleep 1s
}
function start_services() {
cd $WORKPATH/docker_compose/amd/gpu/rocm/
export SEARCH_HOST_IP=${ip_address}
export SEARCH_EXTERNAL_HOST_IP=${ip_address}
export SEARCH_EMBEDDING_MODEL_ID='BAAI/bge-base-en-v1.5'
export SEARCH_TEI_EMBEDDING_ENDPOINT=http://${SEARCH_HOST_IP}:3001
export SEARCH_RERANK_MODEL_ID='BAAI/bge-reranker-base'
export SEARCH_TEI_RERANKING_ENDPOINT=http://${SEARCH_HOST_IP}:3004
export SEARCH_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export SEARCH_OPENAI_API_KEY=${OPENAI_API_KEY}
export SEARCH_TGI_LLM_ENDPOINT=http://${SEARCH_HOST_IP}:3006
export SEARCH_LLM_MODEL_ID='Intel/neural-chat-7b-v3-3'
export SEARCH_MEGA_SERVICE_HOST_IP=${SEARCH_EXTERNAL_HOST_IP}
export SEARCH_EMBEDDING_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_WEB_RETRIEVER_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_RERANK_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_LLM_SERVICE_HOST_IP=${SEARCH_HOST_IP}
export SEARCH_EMBEDDING_SERVICE_PORT=3002
export SEARCH_WEB_RETRIEVER_SERVICE_PORT=3003
export SEARCH_RERANK_SERVICE_PORT=3005
export SEARCH_LLM_SERVICE_PORT=3007
export SEARCH_FRONTEND_SERVICE_PORT=5173
export SEARCH_BACKEND_SERVICE_PORT=3008
export SEARCH_BACKEND_SERVICE_ENDPOINT=http://${SEARCH_HOST_IP}:${SEARCH_BACKEND_SERVICE_PORT}/v1/searchqna
export SEARCH_GOOGLE_API_KEY=${GOOGLE_API_KEY}
export SEARCH_GOOGLE_CSE_ID=${GOOGLE_CSE_ID}
sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
# Start Docker Containers
docker compose up -d > ${LOG_PATH}/start_services_with_compose.log
n=0
until [[ "$n" -ge 100 ]]; do
docker logs search-tgi-service > $LOG_PATH/search-tgi-service_start.log
if grep -q Connected $LOG_PATH/search-tgi-service_start.log; then
break
fi
sleep 5s
n=$((n+1))
done
}
function validate_megaservice() {
result=$(http_proxy="" curl http://${ip_address}:3008/v1/searchqna -XPOST -d '{"messages": "What is black myth wukong?", "stream": "False"}' -H 'Content-Type: application/json')
echo $result
if [[ $result == *"the"* ]]; then
docker logs search-web-retriever-server
docker logs search-backend-server
echo "Result correct."
else
docker logs search-web-retriever-server
docker logs search-backend-server
echo "Result wrong."
exit 1
fi
}
function validate_frontend() {
cd $WORKPATH/ui/svelte
local conda_env_name="OPEA_e2e"
export PATH=${HOME}/miniconda3/bin/:$PATH
if conda info --envs | grep -q "$conda_env_name"; then
echo "$conda_env_name exist!"
else
conda create -n ${conda_env_name} python=3.12 -y
fi
source activate ${conda_env_name}
sed -i "s/localhost/$ip_address/g" playwright.config.ts
conda install -c conda-forge nodejs=22.6.0 -y
npm install && npm ci && npx playwright install --with-deps
node -v && npm -v && pip list
exit_status=0
npx playwright test || exit_status=$?
if [ $exit_status -ne 0 ]; then
echo "[TEST INFO]: ---------frontend test failed---------"
exit $exit_status
else
echo "[TEST INFO]: ---------frontend test passed---------"
fi
}
function stop_docker() {
cd $WORKPATH/docker_compose/amd/gpu/rocm/
docker compose stop && docker compose rm -f
}
function main() {
stop_docker
if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
start_services
validate_megaservice
validate_frontend
stop_docker
echo y | docker system prune
}
main