bea9bb0242
Signed-off-by: letonghan <letong.han@intel.com> Signed-off-by: chensuyue <suyue.chen@intel.com>
86 lines
3.0 KiB
Bash
86 lines
3.0 KiB
Bash
#!/bin/bash
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# Copyright (C) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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set -x
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WORKPATH=$(dirname "$PWD")
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LOG_PATH="$WORKPATH/tests"
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ip_address=$(hostname -I | awk '{print $1}')
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function build_docker_images() {
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cd $WORKPATH
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docker build --no-cache -t opea/retriever-pgvector:comps --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/pgvector/langchain/Dockerfile .
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if [ $? -ne 0 ]; then
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echo "opea/retriever-pgvector built fail"
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exit 1
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else
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echo "opea/retriever-pgvector built successful"
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fi
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}
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function start_service() {
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# pgvector
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export POSTGRES_USER=testuser
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export POSTGRES_PASSWORD=testpwd
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export POSTGRES_DB=vectordb
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pgvector_port=5079
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docker run --name test-comps-retriever-pgvector-vectorstore -e POSTGRES_USER=${POSTGRES_USER} -e POSTGRES_HOST_AUTH_METHOD=trust -e POSTGRES_DB=${POSTGRES_DB} -e POSTGRES_PASSWORD=${POSTGRES_PASSWORD} -d -v $WORKPATH/comps/vectorstores/pgvector/init.sql:/docker-entrypoint-initdb.d/init.sql -p $pgvector_port:5432 pgvector/pgvector:0.7.0-pg16
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sleep 10s
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# tei endpoint
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tei_endpoint=5431
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model="BAAI/bge-base-en-v1.5"
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docker run -d --name="test-comps-retriever-pgvector-tei-endpoint" -p $tei_endpoint:80 -v ./data:/data --pull always ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 --model-id $model
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sleep 30s
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export TEI_EMBEDDING_ENDPOINT="http://${ip_address}:${tei_endpoint}"
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# pgvector retriever
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docker run -d --name="test-comps-retriever-pgvector-ms" -p 5003:7000 --ipc=host -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e PG_CONNECTION_STRING=postgresql+psycopg2://${POSTGRES_USER}:${POSTGRES_PASSWORD}@$ip_address:$pgvector_port/${POSTGRES_DB} -e INDEX_NAME=$INDEX_NAME -e TEI_ENDPOINT=$TEI_ENDPOINT opea/retriever-pgvector:comps
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sleep 3m
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}
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function validate_microservice() {
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retriever_port=5003
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test_embedding=$(python -c "import random; embedding = [random.uniform(-1, 1) for _ in range(768)]; print(embedding)")
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result=$(http_proxy=''
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curl http://${ip_address}:$retriever_port/v1/retrieval \
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-X POST \
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-d "{\"text\":\"test\",\"embedding\":${test_embedding}}" \
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-H 'Content-Type: application/json')
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if [[ $result == *"retrieved_docs"* ]]; then
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echo "Result correct."
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else
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echo "Result wrong. Received was $result"
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docker logs test-comps-retriever-pgvector-vectorstore >> ${LOG_PATH}/vectorstore.log
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docker logs test-comps-retriever-pgvector-tei-endpoint >> ${LOG_PATH}/tei-endpoint.log
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docker logs test-comps-retriever-pgvector-ms >> ${LOG_PATH}/retriever-pgvector.log
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exit 1
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fi
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}
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function stop_docker() {
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cid_retrievers=$(docker ps -aq --filter "name=test-comps-retriever-pgvector*")
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if [[ ! -z "$cid_retrievers" ]]; then
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docker stop $cid_retrievers && docker rm $cid_retrievers && sleep 1s
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fi
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}
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function main() {
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stop_docker
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build_docker_images
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start_service
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validate_microservice
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stop_docker
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echo y | docker system prune
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}
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main
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