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Integrate DocSum set_env to ut scripts. (#1860)

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Integrate DocSum set_env to ut scripts.
Add README.md for DocSum and InstructionTuning UT scripts.

Signed-off-by: ZePan110 <ze.pan@intel.com>
This commit is contained in:
ZePan110
2025-04-28 13:35:05 +08:00
committed by GitHub
parent c546d96e98
commit 99b62ae49e
11 changed files with 121 additions and 134 deletions
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2
DocSum/docker_compose/amd/gpu/rocm/set_env.sh
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@@ -3,7 +3,7 @@
# Copyright (C) 2024 Advanced Micro Devices, Inc. # Copyright (C) 2024 Advanced Micro Devices, Inc.
# SPDX-License-Identifier: Apache-2.0 # SPDX-License-Identifier: Apache-2.0
export HOST_IP='' export HOST_IP=${ip_address}
export DOCSUM_MAX_INPUT_TOKENS="2048" export DOCSUM_MAX_INPUT_TOKENS="2048"
export DOCSUM_MAX_TOTAL_TOKENS="4096" export DOCSUM_MAX_TOTAL_TOKENS="4096"
export DOCSUM_LLM_MODEL_ID="Intel/neural-chat-7b-v3-3" export DOCSUM_LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"

2
DocSum/docker_compose/amd/gpu/rocm/set_env_vllm.sh
View File

@@ -3,7 +3,7 @@
# Copyright (C) 2024 Advanced Micro Devices, Inc. # Copyright (C) 2024 Advanced Micro Devices, Inc.
# SPDX-License-Identifier: Apache-2.0 # SPDX-License-Identifier: Apache-2.0
export HOST_IP='' export HOST_IP=${ip_address}
export DOCSUM_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} export DOCSUM_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export DOCSUM_MAX_INPUT_TOKENS=2048 export DOCSUM_MAX_INPUT_TOKENS=2048
export DOCSUM_MAX_TOTAL_TOKENS=4096 export DOCSUM_MAX_TOTAL_TOKENS=4096

6
DocSum/docker_compose/set_env.sh
View File

@@ -10,7 +10,7 @@ export no_proxy="${no_proxy},${host_ip}" # Example: no_proxy="localhost, 127.0.0
export http_proxy=$http_proxy export http_proxy=$http_proxy
export https_proxy=$https_proxy export https_proxy=$https_proxy
export host_ip=$(hostname -I | awk '{print $1}') # Example: host_ip="192.168.1.1" export host_ip=$(hostname -I | awk '{print $1}') # Example: host_ip="192.168.1.1"
export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token" export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export LLM_ENDPOINT_PORT=8008 export LLM_ENDPOINT_PORT=8008
export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3" export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
@@ -20,10 +20,12 @@ export MAX_TOTAL_TOKENS=2048
export LLM_PORT=9000 export LLM_PORT=9000
export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}" export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
export DocSum_COMPONENT_NAME="OpeaDocSumvLLM" # OpeaDocSumTgi export DocSum_COMPONENT_NAME="OpeaDocSumvLLM" # OpeaDocSumTgi
export FRONTEND_SERVICE_PORT=5173
export MEGA_SERVICE_HOST_IP=${host_ip} export MEGA_SERVICE_HOST_IP=${host_ip}
export LLM_SERVICE_HOST_IP=${host_ip} export LLM_SERVICE_HOST_IP=${host_ip}
export ASR_SERVICE_HOST_IP=${host_ip} export ASR_SERVICE_HOST_IP=${host_ip}
export BACKEND_SERVICE_PORT=8888 export BACKEND_SERVICE_PORT=8888
export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum" export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
export LOGFLAG=True

45
DocSum/tests/README.md Normal file
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@@ -0,0 +1,45 @@
# DocSum E2E test scripts
## Set the required environment variable
```bash
export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token"
```
## Run test
On Intel Xeon with vLLM:
```bash
bash test_compose_on_xeon.sh
```
On Intel Xeon with TGI:
```bash
bash test_compose_tgi_on_xeon.sh
```
On Intel Gaudi with vLLM:
```bash
bash test_compose_on_gaudi.sh
```
On Intel Gaudi with TGI:
```bash
bash test_compose_tgi_on_gaudi.sh
```
On AMD ROCm with TGI:
```bash
bash test_compose_on_rocm.sh
```
On AMD ROCm with vLLM:
```bash
bash test_compose_vllm_on_rocm.sh
```

25
DocSum/tests/test_compose_on_gaudi.sh
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@@ -10,35 +10,22 @@ export http_proxy=$http_proxy
export https_proxy=$https_proxy export https_proxy=$https_proxy
export host_ip=$(hostname -I | awk '{print $1}') export host_ip=$(hostname -I | awk '{print $1}')
WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests"
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}" echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}" echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export no_proxy="${no_proxy},${host_ip}"
export MODEL_CACHE=${model_cache:-"./data"}
export REGISTRY=${IMAGE_REPO} export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG} export TAG=${IMAGE_TAG}
export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} source $WORKPATH/docker_compose/set_env.sh
export LLM_ENDPOINT_PORT=8008
export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3" export MODEL_CACHE=${model_cache:-"./data"}
export NUM_CARDS=1 export NUM_CARDS=1
export BLOCK_SIZE=128 export BLOCK_SIZE=128
export MAX_NUM_SEQS=256 export MAX_NUM_SEQS=256
export MAX_SEQ_LEN_TO_CAPTURE=2048 export MAX_SEQ_LEN_TO_CAPTURE=2048
export MAX_INPUT_TOKENS=2048 export MAX_INPUT_TOKENS=2048
export MAX_TOTAL_TOKENS=4096 export MAX_TOTAL_TOKENS=4096
export LLM_PORT=9000
export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
export DocSum_COMPONENT_NAME="OpeaDocSumvLLM"
export MEGA_SERVICE_HOST_IP=${host_ip}
export LLM_SERVICE_HOST_IP=${host_ip}
export ASR_SERVICE_HOST_IP=${host_ip}
export FRONTEND_SERVICE_PORT=5173
export BACKEND_SERVICE_PORT=8888
export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
export LOGFLAG=True
WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests"
# Get the root folder of the current script # Get the root folder of the current script
ROOT_FOLDER=$(dirname "$(readlink -f "$0")") ROOT_FOLDER=$(dirname "$(readlink -f "$0")")

29
DocSum/tests/test_compose_on_rocm.sh
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@@ -14,21 +14,8 @@ export MODEL_CACHE=${model_cache:-"./data"}
WORKPATH=$(dirname "$PWD") WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests" LOG_PATH="$WORKPATH/tests"
ip_address=$(hostname -I | awk '{print $1}') ip_address=$(hostname -I | awk '{print $1}')
export HOST_IP=${ip_address}
export host_ip=${ip_address} export host_ip=${ip_address}
export DOCSUM_MAX_INPUT_TOKENS="2048" source $WORKPATH/docker_compose/amd/gpu/rocm/set_env.sh
export DOCSUM_MAX_TOTAL_TOKENS="4096"
export DOCSUM_LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
export DOCSUM_TGI_SERVICE_PORT="8008"
export DOCSUM_TGI_LLM_ENDPOINT="http://${HOST_IP}:${DOCSUM_TGI_SERVICE_PORT}"
export DOCSUM_HUGGINGFACEHUB_API_TOKEN=''
export DOCSUM_WHISPER_PORT="7066"
export ASR_SERVICE_HOST_IP="${HOST_IP}"
export DOCSUM_LLM_SERVER_PORT="9000"
export DOCSUM_BACKEND_SERVER_PORT="18072"
export DOCSUM_FRONTEND_PORT="18073"
export BACKEND_SERVICE_ENDPOINT="http://${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum"
function build_docker_images() { function build_docker_images() {
opea_branch=${opea_branch:-"main"} opea_branch=${opea_branch:-"main"}
@@ -129,7 +116,7 @@ function validate_microservices() {
# whisper microservice # whisper microservice
ulimit -s 65536 ulimit -s 65536
validate_services \ validate_services \
"${host_ip}:${DOCSUM_WHISPER_PORT}/v1/asr" \ "${HOST_IP}:${DOCSUM_WHISPER_PORT}/v1/asr" \
'{"asr_result":"well"}' \ '{"asr_result":"well"}' \
"whisper-service" \ "whisper-service" \
"whisper-service" \ "whisper-service" \
@@ -137,7 +124,7 @@ function validate_microservices() {
# tgi for llm service # tgi for llm service
validate_services \ validate_services \
"${host_ip}:${DOCSUM_TGI_SERVICE_PORT}/generate" \ "${HOST_IP}:${DOCSUM_TGI_SERVICE_PORT}/generate" \
"generated_text" \ "generated_text" \
"docsum-tgi-service" \ "docsum-tgi-service" \
"docsum-tgi-service" \ "docsum-tgi-service" \
@@ -145,7 +132,7 @@ function validate_microservices() {
# llm microservice # llm microservice
validate_services \ validate_services \
"${host_ip}:${DOCSUM_LLM_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_LLM_SERVER_PORT}/v1/docsum" \
"text" \ "text" \
"docsum-llm-server" \ "docsum-llm-server" \
"docsum-llm-server" \ "docsum-llm-server" \
@@ -158,7 +145,7 @@ function validate_megaservice() {
local DOCKER_NAME="docsum-backend-server" local DOCKER_NAME="docsum-backend-server"
local EXPECTED_RESULT="[DONE]" local EXPECTED_RESULT="[DONE]"
local INPUT_DATA="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." local INPUT_DATA="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."
local URL="${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" local URL="${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum"
local DATA_TYPE="type=text" local DATA_TYPE="type=text"
local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -F "$DATA_TYPE" -F "$INPUT_DATA" -H 'Content-Type: multipart/form-data' "$URL") local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -F "$DATA_TYPE" -F "$INPUT_DATA" -H 'Content-Type: multipart/form-data' "$URL")
@@ -188,7 +175,7 @@ function validate_megaservice_json() {
echo "" echo ""
echo ">>> Checking text data with Content-Type: application/json" echo ">>> Checking text data with Content-Type: application/json"
validate_services \ validate_services \
"${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \
"[DONE]" \ "[DONE]" \
"docsum-backend-server" \ "docsum-backend-server" \
"docsum-backend-server" \ "docsum-backend-server" \
@@ -196,7 +183,7 @@ function validate_megaservice_json() {
echo ">>> Checking audio data" echo ">>> Checking audio data"
validate_services \ validate_services \
"${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \
"[DONE]" \ "[DONE]" \
"docsum-backend-server" \ "docsum-backend-server" \
"docsum-backend-server" \ "docsum-backend-server" \
@@ -204,7 +191,7 @@ function validate_megaservice_json() {
echo ">>> Checking video data" echo ">>> Checking video data"
validate_services \ validate_services \
"${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \
"[DONE]" \ "[DONE]" \
"docsum-backend-server" \ "docsum-backend-server" \
"docsum-backend-server" \ "docsum-backend-server" \

32
DocSum/tests/test_compose_on_xeon.sh
View File

@@ -10,30 +10,18 @@ export http_proxy=$http_proxy
export https_proxy=$https_proxy export https_proxy=$https_proxy
export host_ip=$(hostname -I | awk '{print $1}') export host_ip=$(hostname -I | awk '{print $1}')
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export no_proxy="${no_proxy},${host_ip}"
export MODEL_CACHE=${model_cache:-"./data"}
export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG}
export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export LLM_ENDPOINT_PORT=8008
export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
export MAX_INPUT_TOKENS=2048
export MAX_TOTAL_TOKENS=4096
export LLM_PORT=9000
export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
export DocSum_COMPONENT_NAME="OpeaDocSumvLLM"
export MEGA_SERVICE_HOST_IP=${host_ip}
export LLM_SERVICE_HOST_IP=${host_ip}
export ASR_SERVICE_HOST_IP=${host_ip}
export FRONTEND_SERVICE_PORT=5173
export BACKEND_SERVICE_PORT=8888
export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
export LOGFLAG=True
WORKPATH=$(dirname "$PWD") WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests" LOG_PATH="$WORKPATH/tests"
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG}
source $WORKPATH/docker_compose/set_env.sh
export MODEL_CACHE=${model_cache:-"./data"}
export MAX_INPUT_TOKENS=2048
export MAX_TOTAL_TOKENS=4096
# Get the root folder of the current script # Get the root folder of the current script
ROOT_FOLDER=$(dirname "$(readlink -f "$0")") ROOT_FOLDER=$(dirname "$(readlink -f "$0")")

34
DocSum/tests/test_compose_tgi_on_gaudi.sh
View File

@@ -9,32 +9,20 @@ IMAGE_TAG=${IMAGE_TAG:-"latest"}
export http_proxy=$http_proxy export http_proxy=$http_proxy
export https_proxy=$https_proxy export https_proxy=$https_proxy
export host_ip=$(hostname -I | awk '{print $1}') export host_ip=$(hostname -I | awk '{print $1}')
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export no_proxy="${no_proxy},${host_ip}"
export MODEL_CACHE=${model_cache:-"./data"}
export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG}
export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export LLM_ENDPOINT_PORT=8008
export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
export MAX_INPUT_TOKENS=2048
export MAX_TOTAL_TOKENS=4096
export LLM_PORT=9000
export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
export MEGA_SERVICE_HOST_IP=${host_ip}
export LLM_SERVICE_HOST_IP=${host_ip}
export ASR_SERVICE_HOST_IP=${host_ip}
export FRONTEND_SERVICE_PORT=5173
export BACKEND_SERVICE_PORT=8888
export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
export LOGFLAG=True
WORKPATH=$(dirname "$PWD") WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests" LOG_PATH="$WORKPATH/tests"
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG}
source $WORKPATH/docker_compose/set_env.sh
export MODEL_CACHE=${model_cache:-"./data"}
export MAX_INPUT_TOKENS=2048
export MAX_TOTAL_TOKENS=4096
export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
# Get the root folder of the current script # Get the root folder of the current script
ROOT_FOLDER=$(dirname "$(readlink -f "$0")") ROOT_FOLDER=$(dirname "$(readlink -f "$0")")

35
DocSum/tests/test_compose_tgi_on_xeon.sh
View File

@@ -9,31 +9,20 @@ IMAGE_TAG=${IMAGE_TAG:-"latest"}
export http_proxy=$http_proxy export http_proxy=$http_proxy
export https_proxy=$https_proxy export https_proxy=$https_proxy
export host_ip=$(hostname -I | awk '{print $1}') export host_ip=$(hostname -I | awk '{print $1}')
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export no_proxy="${no_proxy},${host_ip}"
export MODEL_CACHE=${model_cache:-"./data"}
export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG}
export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export LLM_ENDPOINT_PORT=8008
export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
export MAX_INPUT_TOKENS=2048
export MAX_TOTAL_TOKENS=4096
export LLM_PORT=9000
export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
export MEGA_SERVICE_HOST_IP=${host_ip}
export LLM_SERVICE_HOST_IP=${host_ip}
export ASR_SERVICE_HOST_IP=${host_ip}
export FRONTEND_SERVICE_PORT=5173
export BACKEND_SERVICE_PORT=8888
export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:${BACKEND_SERVICE_PORT}/v1/docsum"
export LOGFLAG=True
WORKPATH=$(dirname "$PWD") WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests" LOG_PATH="$WORKPATH/tests"
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
export REGISTRY=${IMAGE_REPO}
export TAG=${IMAGE_TAG}
source $WORKPATH/docker_compose/set_env.sh
export MODEL_CACHE=${model_cache:-"./data"}
export MAX_INPUT_TOKENS=2048
export MAX_TOTAL_TOKENS=4096
export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
# Get the root folder of the current script # Get the root folder of the current script
ROOT_FOLDER=$(dirname "$(readlink -f "$0")") ROOT_FOLDER=$(dirname "$(readlink -f "$0")")

30
DocSum/tests/test_compose_vllm_on_rocm.sh
View File

@@ -16,21 +16,7 @@ WORKPATH=$(dirname "$PWD")
LOG_PATH="$WORKPATH/tests" LOG_PATH="$WORKPATH/tests"
ip_address=$(hostname -I | awk '{print $1}') ip_address=$(hostname -I | awk '{print $1}')
export host_ip=${ip_address} source $WORKPATH/docker_compose/amd/gpu/rocm/set_env_vllm.sh
export HOST_IP=${ip_address}
export EXTERNAL_HOST_IP=${ip_address}
export DOCSUM_HUGGINGFACEHUB_API_TOKEN="${HUGGINGFACEHUB_API_TOKEN}"
export DOCSUM_MAX_INPUT_TOKENS=2048
export DOCSUM_MAX_TOTAL_TOKENS=4096
export DOCSUM_LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
export DOCSUM_VLLM_SERVICE_PORT="8008"
export DOCSUM_LLM_ENDPOINT="http://${HOST_IP}:${DOCSUM_VLLM_SERVICE_PORT}"
export DOCSUM_WHISPER_PORT="7066"
export ASR_SERVICE_HOST_IP="${HOST_IP}"
export DOCSUM_LLM_SERVER_PORT="9000"
export DOCSUM_BACKEND_SERVER_PORT="18072"
export DOCSUM_FRONTEND_PORT="18073"
export BACKEND_SERVICE_ENDPOINT="http://${EXTERNAL_HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum"
function build_docker_images() { function build_docker_images() {
opea_branch=${opea_branch:-"main"} opea_branch=${opea_branch:-"main"}
@@ -130,7 +116,7 @@ function validate_microservices() {
# whisper microservice # whisper microservice
ulimit -s 65536 ulimit -s 65536
validate_services \ validate_services \
"${host_ip}:${DOCSUM_WHISPER_PORT}/v1/asr" \ "${HOST_IP}:${DOCSUM_WHISPER_PORT}/v1/asr" \
'{"asr_result":"well"}' \ '{"asr_result":"well"}' \
"whisper-service" \ "whisper-service" \
"whisper-service" \ "whisper-service" \
@@ -138,7 +124,7 @@ function validate_microservices() {
# vLLM service # vLLM service
validate_services \ validate_services \
"${host_ip}:${DOCSUM_VLLM_SERVICE_PORT}/v1/chat/completions" \ "${HOST_IP}:${DOCSUM_VLLM_SERVICE_PORT}/v1/chat/completions" \
"content" \ "content" \
"docsum-vllm-service" \ "docsum-vllm-service" \
"docsum-vllm-service" \ "docsum-vllm-service" \
@@ -146,7 +132,7 @@ function validate_microservices() {
# llm microservice # llm microservice
validate_services \ validate_services \
"${host_ip}:${DOCSUM_LLM_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_LLM_SERVER_PORT}/v1/docsum" \
"text" \ "text" \
"docsum-llm-server" \ "docsum-llm-server" \
"docsum-llm-server" \ "docsum-llm-server" \
@@ -159,7 +145,7 @@ function validate_megaservice() {
local DOCKER_NAME="docsum-backend-server" local DOCKER_NAME="docsum-backend-server"
local EXPECTED_RESULT="[DONE]" local EXPECTED_RESULT="[DONE]"
local INPUT_DATA="messages=Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5." local INPUT_DATA="messages=Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."
local URL="${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" local URL="${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum"
local DATA_TYPE="type=text" local DATA_TYPE="type=text"
local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -F "$DATA_TYPE" -F "$INPUT_DATA" -H 'Content-Type: multipart/form-data' "$URL") local HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -X POST -F "$DATA_TYPE" -F "$INPUT_DATA" -H 'Content-Type: multipart/form-data' "$URL")
@@ -189,7 +175,7 @@ function validate_megaservice_json() {
echo "" echo ""
echo ">>> Checking text data with Content-Type: application/json" echo ">>> Checking text data with Content-Type: application/json"
validate_services \ validate_services \
"${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \
"[DONE]" \ "[DONE]" \
"docsum-backend-server" \ "docsum-backend-server" \
"docsum-backend-server" \ "docsum-backend-server" \
@@ -197,7 +183,7 @@ function validate_megaservice_json() {
echo ">>> Checking audio data" echo ">>> Checking audio data"
validate_services \ validate_services \
"${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \
"[DONE]" \ "[DONE]" \
"docsum-backend-server" \ "docsum-backend-server" \
"docsum-backend-server" \ "docsum-backend-server" \
@@ -205,7 +191,7 @@ function validate_megaservice_json() {
echo ">>> Checking video data" echo ">>> Checking video data"
validate_services \ validate_services \
"${host_ip}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \ "${HOST_IP}:${DOCSUM_BACKEND_SERVER_PORT}/v1/docsum" \
"[DONE]" \ "[DONE]" \
"docsum-backend-server" \ "docsum-backend-server" \
"docsum-backend-server" \ "docsum-backend-server" \

15
InstructionTuning/tests/README.md Normal file
View File

@@ -0,0 +1,15 @@
# Translation E2E test scripts
## Set the required environment variable
```bash
export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token"
```
## Run test
On Intel Xeon:
```bash
bash test_compose_on_xeon.sh
```