274 lines
9.2 KiB
Bash
274 lines
9.2 KiB
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}
|
|
export MODEL_CACHE=${model_cache:-"./data"}
|
|
export REDIS_DB_PORT=6379
|
|
export REDIS_INSIGHTS_PORT=8001
|
|
export REDIS_RETRIEVER_PORT=7000
|
|
export EMBEDDER_PORT=6000
|
|
export TEI_EMBEDDER_PORT=8090
|
|
export DATAPREP_REDIS_PORT=6007
|
|
|
|
WORKPATH=$(dirname "$PWD")
|
|
LOG_PATH="$WORKPATH/tests"
|
|
ip_address=$(hostname -I | awk '{print $1}')
|
|
|
|
export http_proxy=${http_proxy}
|
|
export https_proxy=${https_proxy}
|
|
export no_proxy=${no_proxy},${ip_address}
|
|
|
|
function build_docker_images() {
|
|
opea_branch=${opea_branch:-"main"}
|
|
# If the opea_branch isn't main, replace the git clone branch in Dockerfile.
|
|
if [[ "${opea_branch}" != "main" ]]; then
|
|
cd $WORKPATH
|
|
OLD_STRING="RUN git clone --depth 1 https://github.com/opea-project/GenAIComps.git"
|
|
NEW_STRING="RUN git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git"
|
|
find . -type f -name "Dockerfile*" | while read -r file; do
|
|
echo "Processing file: $file"
|
|
sed -i "s|$OLD_STRING|$NEW_STRING|g" "$file"
|
|
done
|
|
fi
|
|
|
|
cd $WORKPATH/docker_image_build
|
|
git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
|
|
|
|
# Download Gaudi vllm of latest tag
|
|
git clone https://github.com/HabanaAI/vllm-fork.git && cd vllm-fork
|
|
VLLM_FORK_VER=v0.6.6.post1+Gaudi-1.20.0
|
|
echo "Check out vLLM tag ${VLLM_FORK_VER}"
|
|
git checkout ${VLLM_FORK_VER} &> /dev/null && cd ../
|
|
|
|
echo "Build all the images with --no-cache, check docker_image_build.log for details..."
|
|
service_list="codegen codegen-gradio-ui llm-textgen vllm-gaudi dataprep retriever embedding"
|
|
docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
|
|
|
|
docker images && sleep 1s
|
|
}
|
|
|
|
function start_services() {
|
|
local compose_profile="$1"
|
|
local llm_container_name="$2"
|
|
|
|
cd $WORKPATH/docker_compose/intel/hpu/gaudi
|
|
|
|
export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
|
|
export LLM_ENDPOINT="http://${ip_address}:8028"
|
|
export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
|
|
export MEGA_SERVICE_PORT=7778
|
|
export MEGA_SERVICE_HOST_IP=${ip_address}
|
|
export LLM_SERVICE_HOST_IP=${ip_address}
|
|
export BACKEND_SERVICE_ENDPOINT="http://${ip_address}:${MEGA_SERVICE_PORT}/v1/codegen"
|
|
export NUM_CARDS=1
|
|
export host_ip=${ip_address}
|
|
|
|
export REDIS_URL="redis://${host_ip}:${REDIS_DB_PORT}"
|
|
export RETRIEVAL_SERVICE_HOST_IP=${host_ip}
|
|
export RETRIEVER_COMPONENT_NAME="OPEA_RETRIEVER_REDIS"
|
|
export INDEX_NAME="CodeGen"
|
|
|
|
export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
|
|
export TEI_EMBEDDING_HOST_IP=${host_ip}
|
|
export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:${TEI_EMBEDDER_PORT}"
|
|
export DATAPREP_ENDPOINT="http://${host_ip}:${DATAPREP_REDIS_PORT}/v1/dataprep"
|
|
|
|
export INDEX_NAME="CodeGen"
|
|
|
|
# Start Docker Containers
|
|
docker compose --profile ${compose_profile} up -d | tee ${LOG_PATH}/start_services_with_compose.log
|
|
|
|
n=0
|
|
until [[ "$n" -ge 100 ]]; do
|
|
docker logs ${llm_container_name} > ${LOG_PATH}/llm_service_start.log 2>&1
|
|
if grep -E "Connected|complete" ${LOG_PATH}/llm_service_start.log; then
|
|
break
|
|
fi
|
|
sleep 5s
|
|
n=$((n+1))
|
|
done
|
|
}
|
|
|
|
function validate_services() {
|
|
local URL="$1"
|
|
local EXPECTED_RESULT="$2"
|
|
local SERVICE_NAME="$3"
|
|
local DOCKER_NAME="$4"
|
|
local INPUT_DATA="$5"
|
|
|
|
if [[ "$SERVICE_NAME" == "ingest" ]]; then
|
|
local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -F "$INPUT_DATA" -F index_name=test_redis -H 'Content-Type: multipart/form-data' "$URL")
|
|
|
|
if [ "$HTTP_STATUS" -eq 200 ]; then
|
|
echo "[ $SERVICE_NAME ] HTTP status is 200. Data preparation succeeded..."
|
|
else
|
|
echo "[ $SERVICE_NAME ] Data preparation failed..."
|
|
fi
|
|
|
|
else
|
|
local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL")
|
|
if [ "$HTTP_STATUS" -eq 200 ]; then
|
|
echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..."
|
|
|
|
local CONTENT=$(curl -s -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL" | tee ${LOG_PATH}/${SERVICE_NAME}.log)
|
|
|
|
if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
|
|
echo "[ $SERVICE_NAME ] Content is as expected."
|
|
else
|
|
echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
|
|
docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
|
|
exit 1
|
|
fi
|
|
else
|
|
echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS"
|
|
docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log
|
|
exit 1
|
|
fi
|
|
fi
|
|
sleep 5s
|
|
}
|
|
|
|
function validate_microservices() {
|
|
local llm_container_name="$1"
|
|
|
|
# tgi for llm service
|
|
validate_services \
|
|
"${ip_address}:8028/v1/chat/completions" \
|
|
"completion_tokens" \
|
|
"llm-service" \
|
|
"${llm_container_name}" \
|
|
'{"model": "Qwen/Qwen2.5-Coder-7B-Instruct", "messages": [{"role": "user", "content": "def print_hello_world():"}], "max_tokens": 256}'
|
|
|
|
# llm microservice
|
|
validate_services \
|
|
"${ip_address}:9000/v1/chat/completions" \
|
|
"data: " \
|
|
"llm" \
|
|
"llm-textgen-gaudi-server" \
|
|
'{"query":"def print_hello_world():"}'
|
|
|
|
# Data ingest microservice
|
|
validate_services \
|
|
"${ip_address}:6007/v1/dataprep/ingest" \
|
|
"Data preparation succeeded" \
|
|
"ingest" \
|
|
"dataprep-redis-server" \
|
|
'link_list=["https://modin.readthedocs.io/en/latest/index.html"]'
|
|
|
|
}
|
|
|
|
function validate_megaservice() {
|
|
# Curl the Mega Service
|
|
validate_services \
|
|
"${ip_address}:7778/v1/codegen" \
|
|
"print" \
|
|
"mega-codegen" \
|
|
"codegen-gaudi-backend-server" \
|
|
'{"messages": "def print_hello_world():"}'
|
|
|
|
# Curl the Mega Service with index_name and agents_flag
|
|
validate_services \
|
|
"${ip_address}:7778/v1/codegen" \
|
|
"" \
|
|
"mega-codegen" \
|
|
"codegen-gaudi-backend-server" \
|
|
'{ "index_name": "test_redis", "agents_flag": "True", "messages": "def print_hello_world():", "max_tokens": 256}'
|
|
|
|
}
|
|
|
|
function validate_frontend() {
|
|
cd $WORKPATH/ui/svelte
|
|
local conda_env_name="OPEA_e2e"
|
|
export PATH=${HOME}/miniforge3/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 $exit_status
|
|
else
|
|
echo "[TEST INFO]: ---------frontend test passed---------"
|
|
fi
|
|
}
|
|
|
|
function validate_gradio() {
|
|
local URL="http://${ip_address}:5173/health"
|
|
local HTTP_STATUS=$(curl "$URL")
|
|
local SERVICE_NAME="Gradio"
|
|
|
|
if [ "$HTTP_STATUS" = '{"status":"ok"}' ]; then
|
|
echo "[ $SERVICE_NAME ] HTTP status is 200. UI server is running successfully..."
|
|
else
|
|
echo "[ $SERVICE_NAME ] UI server has failed..."
|
|
fi
|
|
}
|
|
|
|
function stop_docker() {
|
|
local docker_profile="$1"
|
|
|
|
cd $WORKPATH/docker_compose/intel/hpu/gaudi
|
|
docker compose --profile ${docker_profile} down
|
|
}
|
|
|
|
function main() {
|
|
# all docker docker compose profiles for XEON Platform
|
|
docker_compose_profiles=("codegen-gaudi-vllm" "codegen-gaudi-tgi")
|
|
docker_llm_container_names=("vllm-gaudi-server" "tgi-gaudi-server")
|
|
|
|
# get number of profiels and container
|
|
len_profiles=${#docker_compose_profiles[@]}
|
|
len_containers=${#docker_llm_container_names[@]}
|
|
|
|
# number of profiels and docker container names must be matched
|
|
if [ ${len_profiles} -ne ${len_containers} ]; then
|
|
echo "Error: number of profiles ${len_profiles} and container names ${len_containers} mismatched"
|
|
exit 1
|
|
fi
|
|
|
|
# stop_docker, stop all profiles
|
|
for ((i = 0; i < len_profiles; i++)); do
|
|
stop_docker "${docker_compose_profiles[${i}]}"
|
|
done
|
|
|
|
# build docker images
|
|
if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
|
|
|
|
# loop all profiles
|
|
for ((i = 0; i < len_profiles; i++)); do
|
|
echo "Process [${i}]: ${docker_compose_profiles[$i]}, ${docker_llm_container_names[${i}]}"
|
|
start_services "${docker_compose_profiles[${i}]}" "${docker_llm_container_names[${i}]}"
|
|
docker ps -a
|
|
|
|
validate_microservices "${docker_llm_container_names[${i}]}"
|
|
validate_megaservice
|
|
validate_gradio
|
|
|
|
stop_docker "${docker_compose_profiles[${i}]}"
|
|
sleep 5s
|
|
done
|
|
|
|
echo y | docker system prune
|
|
}
|
|
|
|
main
|