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Integrate AvatarChatbot set_env to ut scripts. (#1961)

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Signed-off-by: ZePan110 <ze.pan@intel.com>
This commit is contained in:
ZePan110
2025-05-16 15:18:06 +08:00
committed by GitHub
parent c8abbc4958
commit 22174e68a5
7 changed files with 94 additions and 106 deletions
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4
AvatarChatbot/docker_compose/amd/gpu/rocm/set_env.sh
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@@ -41,7 +41,7 @@ export FACE="/home/user/comps/animation/src/assets/img/avatar5.png"
# export AUDIO='assets/audio/eg3_ref.wav' # audio file path is optional, will use base64str in the post request as input if is 'None'
export AUDIO='None'
export FACESIZE=96
export OUTFILE="/outputs/result.mp4"
export OUTFILE="./outputs/result.mp4"
export GFPGAN_MODEL_VERSION=1.4 # latest version, can roll back to v1.3 if needed
export UPSCALE_FACTOR=1
export FPS=10
export FPS=5

29
AvatarChatbot/docker_compose/intel/cpu/xeon/set_env.sh
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@@ -5,3 +5,32 @@
pushd "../../../../../" > /dev/null
source .set_env.sh
popd > /dev/null
export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
export host_ip=$(hostname -I | awk '{print $1}')
export LLM_MODEL_ID=Intel/neural-chat-7b-v3-3
export WAV2LIP_ENDPOINT=http://$host_ip:7860
export MEGA_SERVICE_HOST_IP=${host_ip}
export WHISPER_SERVER_HOST_IP=${host_ip}
export WHISPER_SERVER_PORT=7066
export SPEECHT5_SERVER_HOST_IP=${host_ip}
export SPEECHT5_SERVER_PORT=7055
export LLM_SERVER_HOST_IP=${host_ip}
export LLM_SERVER_PORT=3006
export ANIMATION_SERVICE_HOST_IP=${host_ip}
export ANIMATION_SERVICE_PORT=3008
export MEGA_SERVICE_PORT=8888
export DEVICE="cpu"
export WAV2LIP_PORT=7860
export INFERENCE_MODE='wav2lip+gfpgan'
export CHECKPOINT_PATH='/usr/local/lib/python3.11/site-packages/Wav2Lip/checkpoints/wav2lip_gan.pth'
export FACE="/home/user/comps/animation/src/assets/img/avatar5.png"
# export AUDIO='assets/audio/eg3_ref.wav' # audio file path is optional, will use base64str in the post request as input if is 'None'
export AUDIO='None'
export FACESIZE=96
export OUTFILE="/outputs/result.mp4"
export GFPGAN_MODEL_VERSION=1.4 # latest version, can roll back to v1.3 if needed
export UPSCALE_FACTOR=1
export FPS=10

32
AvatarChatbot/docker_compose/intel/hpu/gaudi/set_env.sh
View File

@@ -5,3 +5,35 @@
pushd "../../../../../" > /dev/null
source .set_env.sh
popd > /dev/null
export HUGGINGFACEHUB_API_TOKEN=$HUGGINGFACEHUB_API_TOKEN
export host_ip=$(hostname -I | awk '{print $1}')
export LLM_MODEL_ID=Intel/neural-chat-7b-v3-3
export WAV2LIP_ENDPOINT=http://$host_ip:7860
export MEGA_SERVICE_HOST_IP=${host_ip}
export WHISPER_SERVER_HOST_IP=${host_ip}
export WHISPER_SERVER_PORT=7066
export SPEECHT5_SERVER_HOST_IP=${host_ip}
export SPEECHT5_SERVER_PORT=7055
export LLM_SERVER_HOST_IP=${host_ip}
export LLM_SERVER_PORT=3006
export ANIMATION_SERVICE_HOST_IP=${host_ip}
export ANIMATION_SERVICE_PORT=3008
export MEGA_SERVICE_PORT=8888
export DEVICE="hpu"
export WAV2LIP_PORT=7860
export INFERENCE_MODE='wav2lip+gfpgan'
export CHECKPOINT_PATH='/usr/local/lib/python3.10/dist-packages/Wav2Lip/checkpoints/wav2lip_gan.pth'
export FACE="/home/user/comps/animation/src/assets/img/avatar1.jpg"
# export AUDIO='assets/audio/eg3_ref.wav' # audio file path is optional, will use base64str in the post request as input if is 'None'
export AUDIO='None'
export FACESIZE=96
export OUTFILE="/outputs/result.mp4"
export GFPGAN_MODEL_VERSION=1.4 # latest version, can roll back to v1.3 if needed
export UPSCALE_FACTOR=1
export FPS=10

27
AvatarChatbot/tests/README.md Normal file
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@@ -0,0 +1,27 @@
# AvatarChatbot E2E test scripts
## Set the required environment variable
```bash
export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token"
```
## Run test
On Intel Xeon with TGI:
```bash
bash test_compose_on_xeon.sh
```
On Intel Gaudi with TGI:
```bash
bash test_compose_on_gaudi.sh
```
On AMD ROCm with TGI:
```bash
bash test_compose_on_rocm.sh
```

32
AvatarChatbot/tests/test_compose_on_gaudi.sh
View File

@@ -45,37 +45,7 @@ function build_docker_images() {
function start_services() {
cd $WORKPATH/docker_compose/intel/hpu/gaudi
export HUGGINGFACEHUB_API_TOKEN=$HUGGINGFACEHUB_API_TOKEN
export host_ip=$(hostname -I | awk '{print $1}')
export LLM_MODEL_ID=Intel/neural-chat-7b-v3-3
export WAV2LIP_ENDPOINT=http://$host_ip:7860
export MEGA_SERVICE_HOST_IP=${host_ip}
export WHISPER_SERVER_HOST_IP=${host_ip}
export WHISPER_SERVER_PORT=7066
export SPEECHT5_SERVER_HOST_IP=${host_ip}
export SPEECHT5_SERVER_PORT=7055
export LLM_SERVER_HOST_IP=${host_ip}
export LLM_SERVER_PORT=3006
export ANIMATION_SERVICE_HOST_IP=${host_ip}
export ANIMATION_SERVICE_PORT=3008
export MEGA_SERVICE_PORT=8888
export DEVICE="hpu"
export WAV2LIP_PORT=7860
export INFERENCE_MODE='wav2lip+gfpgan'
export CHECKPOINT_PATH='/usr/local/lib/python3.10/dist-packages/Wav2Lip/checkpoints/wav2lip_gan.pth'
export FACE="/home/user/comps/animation/src/assets/img/avatar1.jpg"
# export AUDIO='assets/audio/eg3_ref.wav' # audio file path is optional, will use base64str in the post request as input if is 'None'
export AUDIO='None'
export FACESIZE=96
export OUTFILE="/outputs/result.mp4"
export GFPGAN_MODEL_VERSION=1.4 # latest version, can roll back to v1.3 if needed
export UPSCALE_FACTOR=1
export FPS=10
source set_env.sh
# Start Docker Containers
docker compose up -d > ${LOG_PATH}/start_services_with_compose.log

44
AvatarChatbot/tests/test_compose_on_rocm.sh
View File

@@ -2,7 +2,7 @@
# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
set -e
set -xe
IMAGE_REPO=${IMAGE_REPO:-"opea"}
IMAGE_TAG=${IMAGE_TAG:-"latest"}
echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}"
@@ -42,48 +42,8 @@ function build_docker_images() {
function start_services() {
cd $WORKPATH/docker_compose/amd/gpu/rocm
export HUGGINGFACEHUB_API_TOKEN=$HUGGINGFACEHUB_API_TOKEN
export OPENAI_API_KEY=$OPENAI_API_KEY
export host_ip=${ip_address}
export TGI_SERVICE_PORT=3006
export TGI_LLM_ENDPOINT=http://${host_ip}:${TGI_SERVICE_PORT}
export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
export ASR_ENDPOINT=http://${host_ip}:7066
export TTS_ENDPOINT=http://${host_ip}:7055
export WAV2LIP_ENDPOINT=http://${host_ip}:7860
export MEGA_SERVICE_HOST_IP=${host_ip}
export ASR_SERVICE_HOST_IP=${host_ip}
export TTS_SERVICE_HOST_IP=${host_ip}
export LLM_SERVICE_HOST_IP=${host_ip}
export ANIMATION_SERVICE_HOST_IP=${host_ip}
export WHISPER_SERVER_HOST_IP=${host_ip}
export WHISPER_SERVER_PORT=7066
export SPEECHT5_SERVER_HOST_IP=${host_ip}
export SPEECHT5_SERVER_PORT=7055
export MEGA_SERVICE_PORT=8888
export ASR_SERVICE_PORT=3001
export TTS_SERVICE_PORT=3002
export LLM_SERVICE_PORT=3006
export ANIMATION_SERVICE_PORT=3008
export DEVICE="cpu"
export WAV2LIP_PORT=7860
export INFERENCE_MODE='wav2lip+gfpgan'
export CHECKPOINT_PATH='/usr/local/lib/python3.11/site-packages/Wav2Lip/checkpoints/wav2lip_gan.pth'
export FACE="/home/user/comps/animation/src/assets/img/avatar5.png"
# export AUDIO='assets/audio/eg3_ref.wav' # audio file path is optional, will use base64str in the post request as input if is 'None'
export AUDIO='None'
export FACESIZE=96
export OUTFILE="./outputs/result.mp4"
export GFPGAN_MODEL_VERSION=1.4 # latest version, can roll back to v1.3 if needed
export UPSCALE_FACTOR=1
export FPS=5
source set_env.sh
# Start Docker Containers
docker compose up -d --force-recreate

32
AvatarChatbot/tests/test_compose_on_xeon.sh
View File

@@ -45,37 +45,7 @@ function build_docker_images() {
function start_services() {
cd $WORKPATH/docker_compose/intel/cpu/xeon
export HUGGINGFACEHUB_API_TOKEN=$HUGGINGFACEHUB_API_TOKEN
export host_ip=$(hostname -I | awk '{print $1}')
export LLM_MODEL_ID=Intel/neural-chat-7b-v3-3
export WAV2LIP_ENDPOINT=http://$host_ip:7860
export MEGA_SERVICE_HOST_IP=${host_ip}
export WHISPER_SERVER_HOST_IP=${host_ip}
export WHISPER_SERVER_PORT=7066
export SPEECHT5_SERVER_HOST_IP=${host_ip}
export SPEECHT5_SERVER_PORT=7055
export LLM_SERVER_HOST_IP=${host_ip}
export LLM_SERVER_PORT=3006
export ANIMATION_SERVICE_HOST_IP=${host_ip}
export ANIMATION_SERVICE_PORT=3008
export MEGA_SERVICE_PORT=8888
export DEVICE="cpu"
export WAV2LIP_PORT=7860
export INFERENCE_MODE='wav2lip+gfpgan'
export CHECKPOINT_PATH='/usr/local/lib/python3.11/site-packages/Wav2Lip/checkpoints/wav2lip_gan.pth'
export FACE="/home/user/comps/animation/src/assets/img/avatar5.png"
# export AUDIO='assets/audio/eg3_ref.wav' # audio file path is optional, will use base64str in the post request as input if is 'None'
export AUDIO='None'
export FACESIZE=96
export OUTFILE="/outputs/result.mp4"
export GFPGAN_MODEL_VERSION=1.4 # latest version, can roll back to v1.3 if needed
export UPSCALE_FACTOR=1
export FPS=10
source set_env.sh
# Start Docker Containers
docker compose up -d