jandres/GenAIExamples
1
0
Fork 0
Code Issues Pull Requests Actions 5 Packages Projects Releases Wiki Activity

Refine DocSum Test Script (#247)

Browse Source 
Signed-off-by: zehao-intel <zehao.huang@intel.com>
This commit is contained in:
zehao-intel
2024-05-31 20:07:38 +08:00
committed by GitHub
parent 6ebfea1f10
commit ecb273216b
2 changed files with 98 additions and 89 deletions
Download Patch File Download Diff File Expand all files Collapse all files

93
DocSum/tests/test_docsum_on_gaudi.sh
View File

@@ -43,57 +43,62 @@ function start_services() {
sleep 2m # Waits 2 minutes
}
function validate_services() {
local URL="$1"
local EXPECTED_RESULT="$2"
local SERVICE_NAME="$3"
local DOCKER_NAME="$4"
local INPUT_DATA="$5"
local HTTP_STATUS=$(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
sleep 1s
}
function validate_microservices() {
# Check if the microservices are running correctly.
# TODO: Any results check required??
curl http://${ip_address}:8008/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
-H 'Content-Type: application/json' > ${LOG_PATH}/generate.log
exit_code=$?
if [ $exit_code -ne 0 ]; then
echo "Microservice failed, please check the logs in artifacts!"
docker logs tgi-gaudi-server >> ${LOG_PATH}/generate.log
exit 1
fi
sleep 5s
curl http://${ip_address}:9000/v1/chat/docsum \
-X POST \
-d '{"query":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}' \
-H 'Content-Type: application/json' > ${LOG_PATH}/completions.log
exit_code=$?
if [ $exit_code -ne 0 ]; then
echo "Microservice failed, please check the logs in artifacts!"
docker logs docsum-gaudi-backend-server >> ${LOG_PATH}/completions.log
exit 1
fi
sleep 5s
# tgi for llm service
validate_services \
"${ip_address}:8008/generate" \
"generated_text" \
"tgi-gaudi" \
"tgi-gaudi-server" \
'{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}'
# llm microservice
validate_services \
"${ip_address}:9000/v1/chat/docsum" \
"data: " \
"llm" \
"llm-docsum-gaudi-server" \
'{"query":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
}
function validate_megaservice() {
# Curl the Mega Service
curl http://${ip_address}:8888/v1/docsum -H "Content-Type: application/json" -d '{
"messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}' > ${LOG_PATH}/curl_megaservice.log
echo "Checking response results, make sure the output is reasonable. "
local status=false
if [[ -f $LOG_PATH/curl_megaservice.log ]] && \
[[ $(grep -c "versatile toolkit" $LOG_PATH/curl_megaservice.log) != 0 ]] && \
[[ $(grep -c "offering" $LOG_PATH/curl_megaservice.log) != 0 ]] && \
[[ $(grep -c "extraction" $LOG_PATH/curl_megaservice.log) != 0 ]]; then
status=true
fi
if [ $status == false ]; then
echo "Response check failed, please check the logs in artifacts!"
exit 1
else
echo "Response check succeed!"
fi
echo "Checking response format, make sure the output format is acceptable for UI."
# TODO
validate_services \
"${ip_address}:8888/v1/docsum" \
"versatile toolkit" \
"mega-docsum" \
"docsum-gaudi-backend-server" \
'{"messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
}
function stop_docker() {

94
DocSum/tests/test_docsum_on_xeon.sh
View File

@@ -41,58 +41,62 @@ function start_services() {
sleep 2m # Waits 2 minutes
}
function validate_services() {
local URL="$1"
local EXPECTED_RESULT="$2"
local SERVICE_NAME="$3"
local DOCKER_NAME="$4"
local INPUT_DATA="$5"
local HTTP_STATUS=$(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
sleep 1s
}
function validate_microservices() {
# Check if the microservices are running correctly.
# TODO: Any results check required??
curl http://${ip_address}:8008/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
-H 'Content-Type: application/json' > ${LOG_PATH}/generate.log
exit_code=$?
if [ $exit_code -ne 0 ]; then
echo "Microservice failed, please check the logs in artifacts!"
docker logs tgi_service >> ${LOG_PATH}/generate.log
exit 1
fi
sleep 5s
curl http://${ip_address}:9000/v1/chat/docsum \
-X POST \
-d '{"query":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}' \
-H 'Content-Type: application/json' > ${LOG_PATH}/completions.log
exit_code=$?
if [ $exit_code -ne 0 ]; then
echo "Microservice failed, please check the logs in artifacts!"
docker logs llm-docsum-server >> ${LOG_PATH}/completions.log
exit 1
fi
sleep 5s
# tgi for llm service
validate_services \
"${ip_address}:8008/generate" \
"generated_text" \
"tgi-llm" \
"tgi_service" \
'{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}'
# llm microservice
validate_services \
"${ip_address}:9000/v1/chat/docsum" \
"data: " \
"llm" \
"llm-docsum-server" \
'{"query":"Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
}
function validate_megaservice() {
# Curl the Mega Service
curl http://${ip_address}:8888/v1/docsum -H "Content-Type: application/json" -d '{
"messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}' > ${LOG_PATH}/curl_megaservice.log
echo "Checking response results, make sure the output is reasonable. "
local status=false
if [[ -f $LOG_PATH/curl_megaservice.log ]] && \
[[ $(grep -c " flexible" $LOG_PATH/curl_megaservice.log) != 0 ]] && \
[[ $(grep -c " tool" $LOG_PATH/curl_megaservice.log) != 0 ]] && \
[[ $(grep -c "kit" $LOG_PATH/curl_megaservice.log) != 0 ]]; then
status=true
fi
if [ $status == false ]; then
echo "Response check failed, please check the logs in artifacts!"
exit 1
else
echo "Response check succeed!"
fi
echo "Checking response format, make sure the output format is acceptable for UI."
# TODO
validate_services \
"${ip_address}:8888/v1/docsum" \
"versatile toolkit" \
"mega-docsum" \
"docsum-xeon-backend-server" \
'{"messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
}
function stop_docker() {