Add the Language Translation Example (#94)
Signed-off-by: zehao-intel <zehao.huang@intel.com> Signed-off-by: chensuyue <suyue.chen@intel.com>
This commit is contained in:
zehao-intel
161
Translation/tests/test_langchain_inference.sh
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161
Translation/tests/test_langchain_inference.sh
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#!/bin/bash
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# Copyright (c) 2024 Intel Corporation
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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set -xe
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function test_env_setup() {
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WORKPATH=$(dirname "$PWD")
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LOG_PATH="$WORKPATH/tests/langchain.log"
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TGI_CONTAINER_NAME="test-tgi-gaudi-server"
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LANGCHAIN_CONTAINER_NAME="test-translation-gaudi"
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}
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function rename() {
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# Rename the docker container/image names to avoid conflict with local test
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cd ${WORKPATH}
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sed -i "s/tgi-gaudi-server-translation/${TGI_CONTAINER_NAME}/g" serving/tgi_gaudi/launch_tgi_service.sh
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}
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function launch_tgi_gaudi_service() {
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local card_num=1
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local port=8870
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local model_name="haoranxu/ALMA-13B"
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cd ${WORKPATH}/serving/tgi_gaudi
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bash build_docker.sh
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bash launch_tgi_service.sh $card_num $port $model_name
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sleep 2m
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}
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function launch_langchain_service() {
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cd $WORKPATH
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local port=8875
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cd langchain/docker
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docker build . --build-arg http_proxy=${http_proxy} --build-arg https_proxy=${http_proxy} -t intel/gen-ai-examples:${LANGCHAIN_CONTAINER_NAME}
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docker run -d --name=${LANGCHAIN_CONTAINER_NAME} --net=host -e TGI_ENDPOINT=http://localhost:8870 -e HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} \
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-e SERVER_PORT=${port} -e http_proxy=${http_proxy} -e https_proxy=${https_proxy} --ipc=host intel/gen-ai-examples:${LANGCHAIN_CONTAINER_NAME}
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sleep 2m
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}
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function run_tests() {
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cd $WORKPATH
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local port=8875
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# response: {"target_language":"I love machine translation"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "zh","language_to": "en","source_language": "我爱机器翻译。"}' \
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-H 'Content-Type: application/json' > $LOG_PATH
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#response: {"target_language":"我是一名翻译"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "English","language_to": "Chinese","source_language": "I am a translator"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"Hallo Welt"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "en","language_to": "de","source_language": "hello world"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"Machine learning"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "German","language_to": "English","source_language": "Maschinelles Lernen"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"Ég er glöð"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "en","language_to": "is","source_language": "I am happy"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"Hello world"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "Icelandic","language_to": "English","source_language": "Halló heimur"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"Velká jazyková model"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "en","language_to": "cs","source_language": "Large Language Model"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"I'm glad to see you"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "Czech","language_to": "English","source_language": "rád tě vidím"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"Хотите танцевать"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "English","language_to": "ru","source_language": "Shall we dance?"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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# response: {"target_language":"operating system"}
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curl http://localhost:${port}/v1/translation \
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-X POST \
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-d '{"language_from": "Russian","language_to": "English","source_language": "операционная система"}' \
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-H 'Content-Type: application/json' >> $LOG_PATH
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}
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function check_response() {
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cd $WORKPATH
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echo "Checking response"
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local status=false
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if [[ -f $LOG_PATH ]] && [[ $(grep -c "I love machine translation" $LOG_PATH) != 0 ]] && \
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[[ $(grep -c "我是一名翻译" $LOG_PATH) != 0 ]] && [[ $(grep -c "Hallo Welt" $LOG_PATH) != 0 ]] && \
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[[ $(grep -c "Machine learning" $LOG_PATH) != 0 ]] && [[ $(grep -c "Ég er glöð" $LOG_PATH) != 0 ]] && \
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[[ $(grep -c "Velká jazyková model" $LOG_PATH) != 0 ]] && [[ $(grep -c "I'm glad to see you" $LOG_PATH) != 0 ]] && \
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[[ $(grep -c "operating system" $LOG_PATH) != 0 ]]; then
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status=true
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fi
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if [ $status == false ]; then
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echo "Response check failed, please check the logs in artifacts!"
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exit 1
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else
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echo "Response check succeed!"
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fi
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}
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function docker_stop() {
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local container_name=$1
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cid=$(docker ps -aq --filter "name=$container_name")
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if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid; fi
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}
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function main() {
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test_env_setup
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rename
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docker_stop $TGI_CONTAINER_NAME && docker_stop $LANGCHAIN_CONTAINER_NAME && sleep 5s
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launch_tgi_gaudi_service
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launch_langchain_service
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run_tests
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check_response
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docker_stop $TGI_CONTAINER_NAME && docker_stop $LANGCHAIN_CONTAINER_NAME && sleep 5s
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echo y | docker system prune
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}
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main
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