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Integrate AvatarChatbot set_env to ut scripts. (opea-project#1961)
Signed-off-by: ZePan110 <ze.pan@intel.com> Signed-off-by: cogniware-devops <ambarish.desai@cogniware.ai>
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‎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"
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# export AUDIO='assets/audio/eg3_ref.wav' # audio file path is optional, will use base64str in the post request as input if is 'None'
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export AUDIO='None'
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export FACESIZE=96
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export OUTFILE="/outputs/result.mp4"
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export OUTFILE="./outputs/result.mp4"
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export GFPGAN_MODEL_VERSION=1.4 # latest version, can roll back to v1.3 if needed
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export UPSCALE_FACTOR=1
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export FPS=10
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export FPS=5

‎AvatarChatbot/docker_compose/intel/cpu/xeon/set_env.sh‎

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

‎AvatarChatbot/docker_compose/intel/hpu/gaudi/set_env.sh‎

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

‎AvatarChatbot/tests/README.md‎

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# AvatarChatbot E2E test scripts
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## Set the required environment variable
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```bash
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export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token"
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```
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## Run test
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On Intel Xeon with TGI:
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```bash
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bash test_compose_on_xeon.sh
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```
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On Intel Gaudi with TGI:
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```bash
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bash test_compose_on_gaudi.sh
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```
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On AMD ROCm with TGI:
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```bash
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bash test_compose_on_rocm.sh
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```

‎AvatarChatbot/tests/test_compose_on_gaudi.sh‎

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

‎AvatarChatbot/tests/test_compose_on_rocm.sh‎

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

‎AvatarChatbot/tests/test_compose_on_xeon.sh‎

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

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