Reduce the verification delay time to 1s

Signed-off-by: ZePan110 <ze.pan@intel.com>

.github/workflows/_run-docker-compose.yml

@@ -204,6 +204,10 @@ jobs:
           if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi
 
           echo "Cleaning up images ..."
+          df -h
+          sleep 1
+          docker system df
+          sleep 1
           if [[ "${{ inputs.hardware }}" == "xeon"* ]]; then
               docker system prune -a -f
           else
@@ -213,7 +217,13 @@ jobs:
               docker images --filter reference="opea/comps-base" -q | xargs -r docker rmi && sleep 1s
               docker system prune -f
           fi
+          sleep 5
           docker images
+          sleep 1
+          df -h
+          sleep 1
+          docker system df
+          sleep 1
 
       - name: Publish pipeline artifact
         if: ${{ !cancelled() }}

.github/workflows/pr-link-path-scan.yml

@@ -23,7 +23,7 @@ jobs:
       - name: Check the Validity of Hyperlinks
         run: |
           cd ${{github.workspace}}
-          delay=15
+          delay=1
           fail="FALSE"
           merged_commit=$(git log -1 --format='%H')
           changed_files="$(git diff --name-status --diff-filter=ARM ${{ github.event.pull_request.base.sha }} ${merged_commit} | awk '/\.md$/ {print $NF}')"
@@ -80,6 +80,7 @@ jobs:
       - name: Checking Relative Path Validity
         run: |
           cd ${{github.workspace}}
+          delay=1
           fail="FALSE"
           repo_name=${{ github.event.pull_request.head.repo.full_name }}
           branch="https://github.com/$repo_name/blob/${{ github.event.pull_request.head.ref }}"
@@ -111,14 +112,15 @@ jobs:
                 if [[ "$png_line" == *#* ]]; then
                   if [ -n "changed_files" ] && echo "$changed_files" | grep -q "^${refer_path}$"; then
                     url_dev=$branch$(echo "$real_path" | sed 's|.*/GenAIExamples||')$png_path
+                    sleep $delay
                     response=$(curl -I -L -s -o /dev/null -w "%{http_code}" "$url_dev")
                     if [ "$response" -ne 200 ]; then
-                      echo "**********Validation failed, try again**********"
+                      echo "**********Validation failed ($response), try again**********"
                       response_retry=$(curl -s -o /dev/null -w "%{http_code}" "$url_dev")
                       if [ "$response_retry" -eq 200 ]; then
                         echo "*****Retry successfully*****"
                       else
-                        echo "Invalid path from ${{github.workspace}}/$refer_path: $png_path"
+                        echo "Invalid path ($response_retry) from ${{github.workspace}}/$refer_path: $png_path"
                         fail="TRUE"
                       fi
                     else

AvatarChatbot/docker_compose/amd/gpu/rocm/set_env.sh

@@ -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

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

@@ -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

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

@@ -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

AvatarChatbot/tests/README.md

@@ -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
+```

AvatarChatbot/tests/test_compose_on_gaudi.sh

@@ -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

AvatarChatbot/tests/test_compose_on_rocm.sh

@@ -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

AvatarChatbot/tests/test_compose_on_xeon.sh

@@ -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

ChatQnA/docker_compose/amd/gpu/rocm/compose.yaml

@@ -16,7 +16,7 @@ services:
       - chatqna-redis-vector-db
       - chatqna-tei-embedding-service
     ports:
-      - "${CHATQNA_REDIS_DATAPREP_PORT}:5000"
+      - "${CHATQNA_REDIS_DATAPREP_PORT:-18103}:5000"
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}

ChatQnA/docker_compose/amd/gpu/rocm/compose_faqgen.yaml

@@ -16,7 +16,7 @@ services:
       - chatqna-redis-vector-db
       - chatqna-tei-embedding-service
     ports:
-      - "${CHATQNA_REDIS_DATAPREP_PORT}:5000"
+      - "${CHATQNA_REDIS_DATAPREP_PORT:-18103}:5000"
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}

ChatQnA/docker_compose/amd/gpu/rocm/compose_faqgen_vllm.yaml

@@ -16,7 +16,7 @@ services:
       - chatqna-redis-vector-db
       - chatqna-tei-embedding-service
     ports:
-      - "${CHATQNA_REDIS_DATAPREP_PORT}:5000"
+      - "${CHATQNA_REDIS_DATAPREP_PORT:-18103}:5000"
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}

ChatQnA/docker_compose/amd/gpu/rocm/compose_vllm.yaml

@@ -16,7 +16,7 @@ services:
       - chatqna-redis-vector-db
       - chatqna-tei-embedding-service
     ports:
-      - "${CHATQNA_REDIS_DATAPREP_PORT:-5000}:5000"
+      - "${CHATQNA_REDIS_DATAPREP_PORT:-18103}:5000"
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}

ChatQnA/docker_compose/amd/gpu/rocm/set_env.sh

@@ -2,17 +2,17 @@
 
 # Copyright (C) 2025 Advanced Micro Devices, Inc.
 
-export HOST_IP=''
-export HOST_IP_EXTERNAL=''
+export HOST_IP=${ip_address}
+export HOST_IP_EXTERNAL=${ip_address}
 
 export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
 export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
 export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
 
-export CHATQNA_BACKEND_SERVICE_PORT=18102
-export CHATQNA_FRONTEND_SERVICE_PORT=18101
-export CHATQNA_NGINX_PORT=18104
+export CHATQNA_BACKEND_SERVICE_PORT=8888
+export CHATQNA_FRONTEND_SERVICE_PORT=5173
+export CHATQNA_NGINX_PORT=80
 export CHATQNA_REDIS_DATAPREP_PORT=18103
 export CHATQNA_REDIS_RETRIEVER_PORT=7000
 export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001

ChatQnA/docker_compose/amd/gpu/rocm/set_env_faqgen.sh

@@ -2,18 +2,18 @@
 
 # Copyright (C) 2025 Advanced Micro Devices, Inc.
 
-export HOST_IP=''
-export HOST_IP_EXTERNAL=''
+export HOST_IP=${ip_address}
+export HOST_IP_EXTERNAL=${ip_address}
 
 export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
 export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
 export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
 
-export CHATQNA_BACKEND_SERVICE_PORT=18102
-export CHATQNA_FRONTEND_SERVICE_PORT=18101
+export CHATQNA_BACKEND_SERVICE_PORT=8888
+export CHATQNA_FRONTEND_SERVICE_PORT=5173
 export CHATQNA_LLM_FAQGEN_PORT=18011
-export CHATQNA_NGINX_PORT=18104
+export CHATQNA_NGINX_PORT=80
 export CHATQNA_REDIS_DATAPREP_PORT=18103
 export CHATQNA_REDIS_RETRIEVER_PORT=7000
 export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001

ChatQnA/docker_compose/amd/gpu/rocm/set_env_faqgen_vllm.sh

@@ -2,18 +2,18 @@
 
 # Copyright (C) 2025 Advanced Micro Devices, Inc.
 
-export HOST_IP=''
-export HOST_IP_EXTERNAL=''
+export HOST_IP=${ip_address}
+export HOST_IP_EXTERNAL=${ip_address}
 
 export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
 export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
 export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
 
-export CHATQNA_BACKEND_SERVICE_PORT=18102
-export CHATQNA_FRONTEND_SERVICE_PORT=18101
+export CHATQNA_BACKEND_SERVICE_PORT=8888
+export CHATQNA_FRONTEND_SERVICE_PORT=5173
 export CHATQNA_LLM_FAQGEN_PORT=18011
-export CHATQNA_NGINX_PORT=18104
+export CHATQNA_NGINX_PORT=80
 export CHATQNA_REDIS_DATAPREP_PORT=18103
 export CHATQNA_REDIS_RETRIEVER_PORT=7000
 export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001

ChatQnA/docker_compose/amd/gpu/rocm/set_env_vllm.sh

@@ -2,17 +2,17 @@
 
 # Copyright (C) 2025 Advanced Micro Devices, Inc.
 
-export HOST_IP=''
-export HOST_IP_EXTERNAL=''
+export HOST_IP=${ip_address}
+export HOST_IP_EXTERNAL=${ip_address}
 
 export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
 export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
 export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
 
-export CHATQNA_BACKEND_SERVICE_PORT=18102
-export CHATQNA_FRONTEND_SERVICE_PORT=18101
-export CHATQNA_NGINX_PORT=18104
+export CHATQNA_BACKEND_SERVICE_PORT=8888
+export CHATQNA_FRONTEND_SERVICE_PORT=5173
+export CHATQNA_NGINX_PORT=80
 export CHATQNA_REDIS_DATAPREP_PORT=18103
 export CHATQNA_REDIS_RETRIEVER_PORT=7000
 export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001

ChatQnA/docker_compose/intel/cpu/xeon/grafana/dashboards/download_opea_dashboard.sh

@@ -1,6 +1,8 @@
 # Copyright (C) 2025 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
-rm *.json
+if ls *.json 1> /dev/null 2>&1; then
+    rm *.json
+fi
 wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/chatqna_megaservice_grafana.json
 wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/qdrant_grafana.json
 wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/milvus_grafana.json

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

@@ -7,6 +7,9 @@ pushd "../../../../../" > /dev/null
 source .set_env.sh
 popd > /dev/null
 
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export HF_TOKEN=${HF_TOKEN}
+export host_ip=${ip_address}
 export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
 export RERANK_MODEL_ID="BAAI/bge-reranker-base"
 export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"

ChatQnA/docker_compose/intel/hpu/gaudi/README.md

@@ -43,7 +43,7 @@ Some HuggingFace resources, such as some models, are only accessible if you have
 
 ### Configure the Deployment Environment
 
-To set up environment variables for deploying ChatQnA services, source the _setup_env.sh_ script in this directory:
+To set up environment variables for deploying ChatQnA services, source the _setup_env.sh_ script in this directory (If using faqgen or guardrails, source the _set_env_faqgen.sh_):
 
 ```
 source ./set_env.sh

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

@@ -4,12 +4,20 @@
 # SPDX-License-Identifier: Apache-2.0
 
 # Function to prompt for input and set environment variables
+NON_INTERACTIVE=${NON_INTERACTIVE:-false}
+
 prompt_for_env_var() {
   local var_name="$1"
   local prompt_message="$2"
   local default_value="$3"
   local mandatory="$4"
 
+  if [[ "$NON_INTERACTIVE" == "true" ]]; then
+    echo "Non-interactive environment detected. Setting $var_name to default: $default_value"
+    export "$var_name"="$default_value"
+    return
+  fi
+
   if [[ "$mandatory" == "true" ]]; then
     while [[ -z "$value" ]]; do
       read -p "$prompt_message [default: \"${default_value}\"]: " value
@@ -34,7 +42,7 @@ popd > /dev/null
 
 # Prompt the user for each required environment variable
 prompt_for_env_var "EMBEDDING_MODEL_ID" "Enter the EMBEDDING_MODEL_ID" "BAAI/bge-base-en-v1.5" false
-prompt_for_env_var "HUGGINGFACEHUB_API_TOKEN" "Enter the HUGGINGFACEHUB_API_TOKEN" "" true
+prompt_for_env_var "HUGGINGFACEHUB_API_TOKEN" "Enter the HUGGINGFACEHUB_API_TOKEN" "${HF_TOKEN}" true
 prompt_for_env_var "RERANK_MODEL_ID" "Enter the RERANK_MODEL_ID" "BAAI/bge-reranker-base" false
 prompt_for_env_var "LLM_MODEL_ID" "Enter the LLM_MODEL_ID" "meta-llama/Meta-Llama-3-8B-Instruct" false
 prompt_for_env_var "INDEX_NAME" "Enter the INDEX_NAME" "rag-redis" false
@@ -42,34 +50,40 @@ prompt_for_env_var "NUM_CARDS" "Enter the number of Gaudi devices" "1" false
 prompt_for_env_var "host_ip" "Enter the host_ip" "$(curl ifconfig.me)" false
 
 #Query for enabling http_proxy
-prompt_for_env_var "http_proxy" "Enter the http_proxy." "" false
+prompt_for_env_var "http_proxy" "Enter the http_proxy." "${http_proxy}" false
 
 #Query for enabling https_proxy
-prompt_for_env_var "https_proxy" "Enter the https_proxy." "" false
+prompt_for_env_var "http_proxy" "Enter the http_proxy." "${https_proxy}" false
 
 #Query for enabling no_proxy
-prompt_for_env_var "no_proxy" "Enter the no_proxy." "" false
+prompt_for_env_var "no_proxy" "Enter the no_proxy." "${no_proxy}" false
 
 # Query for enabling logging
-read -p "Enable logging? (yes/no): " logging && logging=$(echo "$logging" | tr '[:upper:]' '[:lower:]')
-if [[ "$logging" == "yes" || "$logging" == "y" ]]; then
-  export LOGFLAG=true
+if [[ "$NON_INTERACTIVE" == "true" ]]; then
+  # Query for enabling logging
+  prompt_for_env_var "LOGFLAG" "Enable logging? (yes/no): " "true" false
+  export JAEGER_IP=$(ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+')
+  export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=grpc://$JAEGER_IP:4317
+  export TELEMETRY_ENDPOINT=http://$JAEGER_IP:4318/v1/traces
+  telemetry_flag=true
 else
-  export LOGFLAG=false
-fi
-
-# Query for enabling OpenTelemetry Tracing Endpoint
-read -p "Enable OpenTelemetry Tracing Endpoint? (yes/no): " telemetry && telemetry=$(echo "$telemetry" | tr '[:upper:]' '[:lower:]')
-if [[ "$telemetry" == "yes" || "$telemetry" == "y" ]]; then
-    export JAEGER_IP=$(ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+')
-    export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=grpc://$JAEGER_IP:4317
-    export TELEMETRY_ENDPOINT=http://$JAEGER_IP:4318/v1/traces
-    telemetry_flag=true
-    pushd "grafana/dashboards" > /dev/null
-    source download_opea_dashboard.sh
-    popd > /dev/null
-else
-    telemetry_flag=false
+  # Query for enabling logging
+  read -p "Enable logging? (yes/no): " logging && logging=$(echo "$logging" | tr '[:upper:]' '[:lower:]')
+  if [[ "$logging" == "yes" || "$logging" == "y" ]]; then
+    export LOGFLAG=true
+  else
+    export LOGFLAG=false
+  fi
+  # Query for enabling OpenTelemetry Tracing Endpoint
+  read -p "Enable OpenTelemetry Tracing Endpoint? (yes/no): " telemetry && telemetry=$(echo "$telemetry" | tr '[:upper:]' '[:lower:]')
+  if [[ "$telemetry" == "yes" || "$telemetry" == "y" ]]; then
+      export JAEGER_IP=$(ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+')
+      export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=grpc://$JAEGER_IP:4317
+      export TELEMETRY_ENDPOINT=http://$JAEGER_IP:4318/v1/traces
+      telemetry_flag=true
+  else
+      telemetry_flag=false
+  fi
 fi
 
 # Generate the .env file

ChatQnA/docker_compose/intel/hpu/gaudi/set_env_faqgen.sh

@@ -0,0 +1,32 @@
+#!/usr/bin/env bash
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+pushd "../../../../../" > /dev/null
+source .set_env.sh
+popd > /dev/null
+
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export HF_TOKEN=${HF_TOKEN}
+export host_ip=${ip_address}
+export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
+export RERANK_MODEL_ID="BAAI/bge-reranker-base"
+export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
+export INDEX_NAME="rag-redis"
+export NUM_CARDS=1
+export VLLM_SKIP_WARMUP=true
+export LOGFLAG=True
+export http_proxy=${http_proxy}
+export https_proxy=${https_proxy}
+export no_proxy="${ip_address},redis-vector-db,dataprep-redis-service,tei-embedding-service,retriever,tei-reranking-service,tgi-service,vllm-service,guardrails,llm-faqgen,chatqna-gaudi-backend-server,chatqna-gaudi-ui-server,chatqna-gaudi-nginx-server"
+
+export LLM_ENDPOINT_PORT=8010
+export LLM_SERVER_PORT=9001
+export CHATQNA_BACKEND_PORT=8888
+export CHATQNA_REDIS_VECTOR_PORT=6377
+export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8006
+export CHATQNA_FRONTEND_SERVICE_PORT=5175
+export NGINX_PORT=80
+export FAQGen_COMPONENT_NAME="OpeaFaqGenvLLM"
+export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"

ChatQnA/tests/README.md

@@ -0,0 +1,123 @@
+# ChatQnA 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_tgi_on_xeon.sh
+```
+
+On Intel Xeon with vLLM:
+
+```bash
+bash test_compose_on_xeon.sh
+```
+
+On Intel Xeon with MariaDB Vector:
+
+```bash
+bash test_compose_mariadb_on_xeon.sh
+```
+
+On Intel Xeon with Pinecone:
+
+```bash
+bash test_compose_pinecone_on_xeon.sh
+```
+
+On Intel Xeon with Milvus
+
+```bash
+bash test_compose_milvus_on_xeon.sh
+```
+
+On Intel Xeon with Qdrant
+
+```bash
+bash test_compose_qdrant_on_xeon.sh
+```
+
+On Intel Xeon without Rerank:
+
+```bash
+bash test_compose_without_rerank_on_xeon.sh
+```
+
+On Intel Gaudi with TGI:
+
+```bash
+bash test_compose_tgi_on_gaudi.sh
+```
+
+On Intel Gaudi with vLLM:
+
+```bash
+bash test_compose_on_gaudi.sh
+```
+
+On Intel Gaudi with Guardrails:
+
+```bash
+bash test_compose_guardrails_on_gaudi.sh
+```
+
+On Intel Gaudi without Rerank:
+
+```bash
+bash test_compose_without_rerank_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
+```
+
+Test FAQ Generation On Intel Xeon with TGI:
+
+```bash
+bash test_compose_faqgen_tgi_on_xeon.sh
+```
+
+Test FAQ Generation On Intel Xeon with vLLM:
+
+```bash
+bash test_compose_faqgen_on_xeon.sh
+```
+
+Test FAQ Generation On Intel Gaudi with TGI:
+
+```bash
+bash test_compose_faqgen_tgi_on_gaudi.sh
+```
+
+Test FAQ Generation On Intel Gaudi with vLLM:
+
+```bash
+bash test_compose_faqgen_on_gaudi.sh
+```
+
+Test FAQ Generation On AMD ROCm with TGI:
+
+```bash
+bash test_compose_faqgen_on_rocm.sh
+```
+
+Test FAQ Generation On AMD ROCm with vLLM:
+
+```bash
+bash test_compose_faqgen_vllm_on_rocm.sh
+```

ChatQnA/tests/test_compose_faqgen_on_gaudi.sh

@@ -36,27 +36,7 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export NUM_CARDS=1
-    export INDEX_NAME="rag-redis"
-    export host_ip=${ip_address}
-    export LLM_ENDPOINT_PORT=8010
-    export LLM_SERVER_PORT=9001
-    export CHATQNA_BACKEND_PORT=8888
-    export CHATQNA_REDIS_VECTOR_PORT=6377
-    export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8006
-    export CHATQNA_FRONTEND_SERVICE_PORT=5175
-    export NGINX_PORT=80
-    export FAQGen_COMPONENT_NAME="OpeaFaqGenvLLM"
-    export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
-    export HF_TOKEN=${HF_TOKEN}
-    export VLLM_SKIP_WARMUP=true
-    export LOGFLAG=True
-    export http_proxy=${http_proxy}
-    export https_proxy=${https_proxy}
-    export no_proxy="${ip_address},redis-vector-db,dataprep-redis-service,tei-embedding-service,retriever,tei-reranking-service,tgi-service,vllm-service,guardrails,llm-faqgen,chatqna-gaudi-backend-server,chatqna-gaudi-ui-server,chatqna-gaudi-nginx-server"
+    source set_env_faqgen.sh
 
     # Start Docker Containers
     docker compose -f compose_faqgen.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_faqgen_on_rocm.sh

@@ -15,44 +15,7 @@ WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
 ip_address=$(hostname -I | awk '{print $1}')
 
-export HOST_IP=${ip_address}
-export HOST_IP_EXTERNAL=${ip_address}
-
-export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
-
-export CHATQNA_BACKEND_SERVICE_PORT=8888
-export CHATQNA_FRONTEND_SERVICE_PORT=5173
-export CHATQNA_LLM_FAQGEN_PORT=18011
-export CHATQNA_NGINX_PORT=80
-export CHATQNA_REDIS_DATAPREP_PORT=18103
-export CHATQNA_REDIS_RETRIEVER_PORT=7000
-export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001
-export CHATQNA_REDIS_VECTOR_PORT=6379
-export CHATQNA_TEI_EMBEDDING_PORT=18090
-export CHATQNA_TEI_RERANKING_PORT=18808
-export CHATQNA_TGI_SERVICE_PORT=18008
-
-export CHATQNA_BACKEND_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_BACKEND_SERVICE_PORT}/v1/chatqna"
-export CHATQNA_BACKEND_SERVICE_IP=${HOST_IP}
-export CHATQNA_DATAPREP_DELETE_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/delete"
-export CHATQNA_DATAPREP_GET_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/get"
-export CHATQNA_DATAPREP_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/ingest"
-export CHATQNA_EMBEDDING_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_FRONTEND_SERVICE_IP=${HOST_IP}
-export CHATQNA_LLM_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_LLM_ENDPOINT="http://${HOST_IP}:${CHATQNA_TGI_SERVICE_PORT}"
-export CHATQNA_MEGA_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_REDIS_URL="redis://${HOST_IP}:${CHATQNA_REDIS_VECTOR_PORT}"
-export CHATQNA_RERANK_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_RETRIEVER_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_TEI_EMBEDDING_ENDPOINT="http://${HOST_IP}:${CHATQNA_TEI_EMBEDDING_PORT}"
-
-export CHATQNA_BACKEND_SERVICE_NAME=chatqna
-export CHATQNA_INDEX_NAME="rag-redis"
-export FAQGen_COMPONENT_NAME="OpeaFaqGenTgi"
+source $WORKPATH/docker_compose/amd/gpu/rocm/set_env_faqgen.sh
 
 export PATH="~/miniconda3/bin:$PATH"
 

ChatQnA/tests/test_compose_faqgen_on_xeon.sh

@@ -37,26 +37,16 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export INDEX_NAME="rag-redis"
-    export host_ip=${ip_address}
-    export LLM_ENDPOINT_PORT=8010
     export LLM_SERVER_PORT=9001
-    export CHATQNA_BACKEND_PORT=8888
     export CHATQNA_REDIS_VECTOR_PORT=6377
     export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8006
     export CHATQNA_FRONTEND_SERVICE_PORT=5175
-    export NGINX_PORT=80
-    export FAQGen_COMPONENT_NAME="OpeaFaqGenvLLM"
-    export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
-    export HF_TOKEN=${HF_TOKEN}
     export VLLM_SKIP_WARMUP=true
     export LOGFLAG=True
     export http_proxy=${http_proxy}
     export https_proxy=${https_proxy}
     export no_proxy="${ip_address},redis-vector-db,dataprep-redis-service,tei-embedding-service,retriever,tei-reranking-service,tgi-service,vllm-service,guardrails,llm-faqgen,chatqna-xeon-backend-server,chatqna-xeon-ui-server,chatqna-xeon-nginx-server"
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_faqgen.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_faqgen_tgi_on_gaudi.sh

@@ -33,25 +33,8 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export INDEX_NAME="rag-redis"
-    export host_ip=${ip_address}
-    export LLM_ENDPOINT_PORT=8010
-    export LLM_SERVER_PORT=9001
-    export CHATQNA_BACKEND_PORT=8888
-    export CHATQNA_REDIS_VECTOR_PORT=6377
-    export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8006
-    export CHATQNA_FRONTEND_SERVICE_PORT=5175
-    export NGINX_PORT=80
     export FAQGen_COMPONENT_NAME="OpeaFaqGenTgi"
-    export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
-    export HF_TOKEN=${HF_TOKEN}
-    export LOGFLAG=True
-    export http_proxy=${http_proxy}
-    export https_proxy=${https_proxy}
-    export no_proxy="${ip_address},redis-vector-db,dataprep-redis-service,tei-embedding-service,retriever,tei-reranking-service,tgi-service,vllm-service,guardrails,llm-faqgen,chatqna-gaudi-backend-server,chatqna-gaudi-ui-server,chatqna-gaudi-nginx-server"
+    source set_env_faqgen.sh
 
     # Start Docker Containers
     docker compose -f compose_faqgen_tgi.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_faqgen_tgi_on_xeon.sh

@@ -37,25 +37,16 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export INDEX_NAME="rag-redis"
-    export host_ip=${ip_address}
-    export LLM_ENDPOINT_PORT=8010
     export LLM_SERVER_PORT=9001
-    export CHATQNA_BACKEND_PORT=8888
     export CHATQNA_REDIS_VECTOR_PORT=6377
     export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8006
     export CHATQNA_FRONTEND_SERVICE_PORT=5175
-    export NGINX_PORT=80
     export FAQGen_COMPONENT_NAME="OpeaFaqGenTgi"
-    export LLM_ENDPOINT="http://${host_ip}:${LLM_ENDPOINT_PORT}"
-    export HF_TOKEN=${HF_TOKEN}
     export LOGFLAG=True
     export http_proxy=${http_proxy}
     export https_proxy=${https_proxy}
     export no_proxy="${ip_address},redis-vector-db,dataprep-redis-service,tei-embedding-service,retriever,tei-reranking-service,tgi-service,vllm-service,guardrails,llm-faqgen,chatqna-xeon-backend-server,chatqna-xeon-ui-server,chatqna-xeon-nginx-server"
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_faqgen_tgi.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_faqgen_vllm_on_rocm.sh

@@ -14,41 +14,7 @@ WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
 ip_address=$(hostname -I | awk '{print $1}')
 
-export HOST_IP=${ip_address}
-export HOST_IP_EXTERNAL=${ip_address}
-
-export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
-
-export CHATQNA_BACKEND_SERVICE_PORT=8888
-export CHATQNA_FRONTEND_SERVICE_PORT=5173
-export CHATQNA_LLM_FAQGEN_PORT=18011
-export CHATQNA_NGINX_PORT=80
-export CHATQNA_REDIS_DATAPREP_PORT=18103
-export CHATQNA_REDIS_RETRIEVER_PORT=7000
-export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001
-export CHATQNA_REDIS_VECTOR_PORT=6379
-export CHATQNA_TEI_EMBEDDING_PORT=18090
-export CHATQNA_TEI_RERANKING_PORT=18808
-export CHATQNA_VLLM_SERVICE_PORT=18008
-
-export CHATQNA_BACKEND_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_BACKEND_SERVICE_PORT}/v1/chatqna"
-export CHATQNA_BACKEND_SERVICE_IP=${HOST_IP_EXTERNAL}
-export CHATQNA_DATAPREP_DELETE_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/delete"
-export CHATQNA_DATAPREP_GET_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/get"
-export CHATQNA_DATAPREP_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/ingest"
-export CHATQNA_FRONTEND_SERVICE_IP=${HOST_IP}
-export CHATQNA_MEGA_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_REDIS_URL="redis://${HOST_IP}:${CHATQNA_REDIS_VECTOR_PORT}"
-export CHATQNA_TEI_EMBEDDING_ENDPOINT="http://${HOST_IP}:${CHATQNA_TEI_EMBEDDING_PORT}"
-export LLM_ENDPOINT="http://${HOST_IP}:${CHATQNA_VLLM_SERVICE_PORT}"
-
-export CHATQNA_BACKEND_SERVICE_NAME=chatqna
-export CHATQNA_INDEX_NAME="rag-redis"
-export CHATQNA_TYPE="CHATQNA_FAQGEN"
-export FAQGen_COMPONENT_NAME="OpeaFaqGenvLLM"
+source $WORKPATH/docker_compose/amd/gpu/rocm/set_env_faqgen_vllm.sh
 
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}

ChatQnA/tests/test_compose_guardrails_on_gaudi.sh

@@ -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}"
@@ -36,14 +36,8 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export NUM_CARDS=1
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export host_ip=${ip_address}
     export GURADRAILS_MODEL_ID="meta-llama/Meta-Llama-Guard-2-8B"
+    source set_env_faqgen.sh
 
     # Start Docker Containers
     docker compose -f compose_guardrails.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_mariadb_on_xeon.sh

@@ -2,7 +2,7 @@
 # Copyright (C) 2025 MariaDB Foundation
 # 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}"
@@ -39,14 +39,8 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
-    export MARIADB_DATABASE="vectordb"
-    export MARIADB_USER="chatqna"
     export MARIADB_PASSWORD="test"
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export host_ip=${ip_address}
+    source set_env_mariadb.sh
 
     # Start Docker Containers
     docker compose -f compose_mariadb.yaml up -d > ${LOG_PATH}/start_services_with_compose.log
@@ -140,7 +134,7 @@ function validate_megaservice() {
 
 function stop_docker() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
-    docker compose down
+    docker compose -f compose_mariadb.yaml down
 }
 
 function main() {

ChatQnA/tests/test_compose_milvus_on_xeon.sh

@@ -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}"
@@ -39,11 +39,8 @@ function build_docker_images() {
 }
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon/
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
     export LOGFLAG=true
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_milvus.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_on_gaudi.sh

@@ -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}"
@@ -36,16 +36,10 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export NUM_CARDS=1
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+    export NON_INTERACTIVE=true
     export host_ip=${ip_address}
-    export JAEGER_IP=$(ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+')
-    export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=grpc://$JAEGER_IP:4317
-    export TELEMETRY_ENDPOINT=http://$JAEGER_IP:4318/v1/traces
+    export telemetry=yes
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose.yaml -f compose.telemetry.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_on_rocm.sh

@@ -15,41 +15,7 @@ WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
 ip_address=$(hostname -I | awk '{print $1}')
 
-export HOST_IP=${ip_address}
-export HOST_IP_EXTERNAL=${ip_address}
-
-export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
-
-export CHATQNA_BACKEND_SERVICE_PORT=8888
-export CHATQNA_FRONTEND_SERVICE_PORT=5173
-export CHATQNA_NGINX_PORT=80
-export CHATQNA_REDIS_DATAPREP_PORT=18103
-export CHATQNA_REDIS_RETRIEVER_PORT=7000
-export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001
-export CHATQNA_REDIS_VECTOR_PORT=6379
-export CHATQNA_TEI_EMBEDDING_PORT=18090
-export CHATQNA_TEI_RERANKING_PORT=18808
-export CHATQNA_TGI_SERVICE_PORT=18008
-
-export CHATQNA_BACKEND_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_BACKEND_SERVICE_PORT}/v1/chatqna"
-export CHATQNA_BACKEND_SERVICE_IP=${HOST_IP}
-export CHATQNA_DATAPREP_DELETE_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/delete"
-export CHATQNA_DATAPREP_GET_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/get"
-export CHATQNA_DATAPREP_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/ingest"
-export CHATQNA_EMBEDDING_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_FRONTEND_SERVICE_IP=${HOST_IP}
-export CHATQNA_LLM_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_MEGA_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_REDIS_URL="redis://${HOST_IP}:${CHATQNA_REDIS_VECTOR_PORT}"
-export CHATQNA_RERANK_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_RETRIEVER_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_TEI_EMBEDDING_ENDPOINT="http://${HOST_IP}:${CHATQNA_TEI_EMBEDDING_PORT}"
-
-export CHATQNA_BACKEND_SERVICE_NAME=chatqna
-export CHATQNA_INDEX_NAME="rag-redis"
+source $WORKPATH/docker_compose/amd/gpu/rocm/set_env.sh
 
 export PATH="~/miniconda3/bin:$PATH"
 

ChatQnA/tests/test_compose_on_xeon.sh

@@ -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}"
@@ -40,15 +40,7 @@ function build_docker_images() {
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
 
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export host_ip=${ip_address}
-    export JAEGER_IP=$(ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+')
-    export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=grpc://$JAEGER_IP:4317
-    export TELEMETRY_ENDPOINT=http://$JAEGER_IP:4318/v1/traces
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose.yaml -f compose.telemetry.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_pinecone_on_xeon.sh

@@ -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}"
@@ -41,14 +41,11 @@ function build_docker_images() {
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon/
     export no_proxy=${no_proxy},${ip_address}
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
     export PINECONE_API_KEY=${PINECONE_KEY_LANGCHAIN_TEST}
     export PINECONE_INDEX_NAME="langchain-test"
     export INDEX_NAME="langchain-test"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
     export LOGFLAG=true
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_pinecone.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_qdrant_on_xeon.sh

@@ -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}"
@@ -40,11 +40,8 @@ function build_docker_images() {
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
 
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
     export INDEX_NAME="rag-qdrant"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+    source set_env.sh
 
     sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
 

ChatQnA/tests/test_compose_tgi_on_gaudi.sh

@@ -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}"
@@ -32,15 +32,10 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export NUM_CARDS=1
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export JAEGER_IP=$(ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+')
-    export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=grpc://$JAEGER_IP:4317
-    export TELEMETRY_ENDPOINT=http://$JAEGER_IP:4318/v1/traces
+    export NON_INTERACTIVE=true
+    export host_ip=${ip_address}
+    export telemetry=yes
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_tgi.yaml -f compose_tgi.telemetry.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_tgi_on_xeon.sh

@@ -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}"
@@ -33,14 +33,7 @@ function build_docker_images() {
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
 
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export JAEGER_IP=$(ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+')
-    export OTEL_EXPORTER_OTLP_TRACES_ENDPOINT=grpc://$JAEGER_IP:4317
-    export TELEMETRY_ENDPOINT=http://$JAEGER_IP:4318/v1/traces
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_tgi.yaml -f compose_tgi.telemetry.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_vllm_on_rocm.sh

@@ -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=${IMAGE_REPO}"
@@ -14,42 +14,7 @@ WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
 ip_address=$(hostname -I | awk '{print $1}')
 
-export HOST_IP=${ip_address}
-export HOST_IP_EXTERNAL=${ip_address}
-
-export CHATQNA_EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export CHATQNA_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export CHATQNA_LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-export CHATQNA_RERANK_MODEL_ID="BAAI/bge-reranker-base"
-
-export CHATQNA_BACKEND_SERVICE_PORT=8888
-export CHATQNA_FRONTEND_SERVICE_PORT=5173
-export CHATQNA_NGINX_PORT=80
-export CHATQNA_REDIS_DATAPREP_PORT=18103
-export CHATQNA_REDIS_RETRIEVER_PORT=7000
-export CHATQNA_REDIS_VECTOR_INSIGHT_PORT=8001
-export CHATQNA_REDIS_VECTOR_PORT=6379
-export CHATQNA_TEI_EMBEDDING_PORT=18090
-export CHATQNA_TEI_RERANKING_PORT=18808
-export CHATQNA_VLLM_SERVICE_PORT=18008
-
-export CHATQNA_BACKEND_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_BACKEND_SERVICE_PORT}/v1/chatqna"
-export CHATQNA_BACKEND_SERVICE_IP=${HOST_IP_EXTERNAL}
-export CHATQNA_DATAPREP_DELETE_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/delete"
-export CHATQNA_DATAPREP_GET_FILE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/get"
-export CHATQNA_DATAPREP_SERVICE_ENDPOINT="http://${HOST_IP_EXTERNAL}:${CHATQNA_REDIS_DATAPREP_PORT}/v1/dataprep/ingest"
-export CHATQNA_EMBEDDING_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_FRONTEND_SERVICE_IP=${HOST_IP}
-export CHATQNA_LLM_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_MEGA_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_REDIS_URL="redis://${HOST_IP}:${CHATQNA_REDIS_VECTOR_PORT}"
-export CHATQNA_RERANK_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_RETRIEVER_SERVICE_HOST_IP=${HOST_IP}
-export CHATQNA_TEI_EMBEDDING_ENDPOINT="http://${HOST_IP}:${CHATQNA_TEI_EMBEDDING_PORT}"
-
-export CHATQNA_BACKEND_SERVICE_NAME=chatqna
-export CHATQNA_INDEX_NAME="rag-redis"
-
+source $WORKPATH/docker_compose/amd/gpu/rocm/set_env_vllm.sh
 
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}

ChatQnA/tests/test_compose_without_rerank_on_gaudi.sh

@@ -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}"
@@ -36,11 +36,8 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export NUM_CARDS=1
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+    export NON_INTERACTIVE=true
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_without_rerank.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

ChatQnA/tests/test_compose_without_rerank_on_xeon.sh

@@ -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}"
@@ -41,10 +41,7 @@ function build_docker_images() {
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon
 
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f compose_without_rerank.yaml up -d > ${LOG_PATH}/start_services_with_compose.log

CodeGen/Dockerfile

@@ -1,8 +1,9 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+ARG IMAGE_REPO=opea
 ARG BASE_TAG=latest
-FROM opea/comps-base:$BASE_TAG
+FROM $IMAGE_REPO/comps-base:$BASE_TAG
 
 COPY ./codegen.py $HOME/codegen.py
 

CodeGen/docker_compose/amd/gpu/rocm/set_env.sh

@@ -5,8 +5,8 @@
 # SPDX-License-Identifier: Apache-2.0
 
 ### The IP address or domain name of the server on which the application is running
-export HOST_IP=''
-export EXTERNAL_HOST_IP=''
+export HOST_IP=${ip_address}
+export EXTERNAL_HOST_IP=${ip_address}
 
 ### The port of the TGI service. On this port, the TGI service will accept connections
 export CODEGEN_TGI_SERVICE_PORT=8028
@@ -27,7 +27,7 @@ export CODEGEN_TGI_LLM_ENDPOINT="http://${HOST_IP}:${CODEGEN_TGI_SERVICE_PORT}"
 export CODEGEN_MEGA_SERVICE_HOST_IP=${HOST_IP}
 
 ### The port for CodeGen backend service
-export CODEGEN_BACKEND_SERVICE_PORT=18150
+export CODEGEN_BACKEND_SERVICE_PORT=7778
 
 ### The URL of CodeGen backend service, used by the frontend service
 export CODEGEN_BACKEND_SERVICE_URL="http://${EXTERNAL_HOST_IP}:${CODEGEN_BACKEND_SERVICE_PORT}/v1/codegen"
@@ -36,4 +36,4 @@ export CODEGEN_BACKEND_SERVICE_URL="http://${EXTERNAL_HOST_IP}:${CODEGEN_BACKEND
 export CODEGEN_LLM_SERVICE_HOST_IP=${HOST_IP}
 
 ### The CodeGen service UI port
-export CODEGEN_UI_SERVICE_PORT=18151
+export CODEGEN_UI_SERVICE_PORT=5173

CodeGen/docker_compose/amd/gpu/rocm/set_env_vllm.sh

@@ -5,8 +5,8 @@
 # SPDX-License-Identifier: Apache-2.0
 
 ### The IP address or domain name of the server on which the application is running
-export HOST_IP=''
-export EXTERNAL_HOST_IP=''
+export HOST_IP=${ip_address}
+export EXTERNAL_HOST_IP=${ip_address}
 
 ### The port of the vLLM service. On this port, the TGI service will accept connections
 export CODEGEN_VLLM_SERVICE_PORT=8028
@@ -25,7 +25,7 @@ export CODEGEN_LLM_SERVICE_PORT=9000
 export CODEGEN_MEGA_SERVICE_HOST_IP=${HOST_IP}
 
 ### The port for CodeGen backend service
-export CODEGEN_BACKEND_SERVICE_PORT=18150
+export CODEGEN_BACKEND_SERVICE_PORT=7778
 
 ### The URL of CodeGen backend service, used by the frontend service
 export CODEGEN_BACKEND_SERVICE_URL="http://${EXTERNAL_HOST_IP}:${CODEGEN_BACKEND_SERVICE_PORT}/v1/codegen"
@@ -34,4 +34,4 @@ export CODEGEN_BACKEND_SERVICE_URL="http://${EXTERNAL_HOST_IP}:${CODEGEN_BACKEND
 export CODEGEN_LLM_SERVICE_HOST_IP=${HOST_IP}
 
 ### The CodeGen service UI port
-export CODEGEN_UI_SERVICE_PORT=18151
+export CODEGEN_UI_SERVICE_PORT=5173

CodeGen/docker_compose/intel/cpu/xeon/README.md

@@ -6,22 +6,10 @@ This README provides instructions for deploying the CodeGen application using Do
 
 - [Overview](#overview)
 - [Prerequisites](#prerequisites)
-- [Quick Start](#quick-start)
-- [Available Deployment Options](#available-deployment-options)
-  - [Default: vLLM-based Deployment (`--profile codegen-xeon-vllm`)](#default-vllm-based-deployment---profile-codegen-xeon-vllm)
-  - [TGI-based Deployment (`--profile codegen-xeon-tgi`)](#tgi-based-deployment---profile-codegen-xeon-tgi)
-- [Configuration Parameters](#configuration-parameters)
-  - [Environment Variables](#environment-variables)
-  - [Compose Profiles](#compose-profiles)
+- [Quick Start Deployment](#quick-start-deployment)
 - [Building Custom Images (Optional)](#building-custom-images-optional)
 - [Validate Services](#validate-services)
-  - [Check Container Status](#check-container-status)
-  - [Run Validation Script/Commands](#run-validation-scriptcommands)
 - [Accessing the User Interface (UI)](#accessing-the-user-interface-ui)
-  - [Gradio UI (Default)](#gradio-ui-default)
-  - [Svelte UI (Optional)](#svelte-ui-optional)
-  - [React UI (Optional)](#react-ui-optional)
-  - [VS Code Extension (Optional)](#vs-code-extension-optional)
 - [Troubleshooting](#troubleshooting)
 - [Stopping the Application](#stopping-the-application)
 - [Next Steps](#next-steps)
@@ -43,27 +31,37 @@ This guide focuses on running the pre-configured CodeGen service using Docker Co
   cd GenAIExamples/CodeGen/docker_compose/intel/cpu/xeon
   ```
 
-## Quick Start
+## Quick Start Deployment
 
 This uses the default vLLM-based deployment profile (`codegen-xeon-vllm`).
 
 1.  **Configure Environment:**
     Set required environment variables in your shell:
 
-    ```bash
-    # Replace with your host's external IP address (do not use localhost or 127.0.0.1)
-    export HOST_IP="your_external_ip_address"
-    # Replace with your Hugging Face Hub API token
-    export HUGGINGFACEHUB_API_TOKEN="your_huggingface_token"
+        ```bash
+        # Replace with your host's external IP address (do not use localhost or 127.0.0.1)
+        export HOST_IP="your_external_ip_address"
+        # Replace with your Hugging Face Hub API token
+        export HUGGINGFACEHUB_API_TOKEN="your_huggingface_token"
 
-    # Optional: Configure proxy if needed
-    # export http_proxy="your_http_proxy"
-    # export https_proxy="your_https_proxy"
-    # export no_proxy="localhost,127.0.0.1,${HOST_IP}" # Add other hosts if necessary
-    source ../../../set_env.sh
-    ```
+        # Optional: Configure proxy if needed
+        # export http_proxy="your_http_proxy"
+        # export https_proxy="your_https_proxy"
+        # export no_proxy="localhost,127.0.0.1,${HOST_IP}" # Add other hosts if necessary
+        source ../../set_env.sh
+        ```
 
-    _Note: The compose file might read additional variables from a `.env` file or expect them defined elsewhere. Ensure all required variables like ports (`LLM_SERVICE_PORT`, `MEGA_SERVICE_PORT`, etc.) are set if not using defaults from the compose file._
+        _Note: The compose file might read additional variables from set_env.sh. Ensure all required variables like ports (`LLM_SERVICE_PORT`, `MEGA_SERVICE_PORT`, etc.) are set if not using defaults from the compose file._
+
+    For instance, edit the set_env.sh to change the LLM model
+
+        ```
+        export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
+        ```
+        can be changed to other model if needed
+        ```
+        export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-32B-Instruct"
+        ```
 
 2.  **Start Services (vLLM Profile):**
 
@@ -74,17 +72,17 @@ This uses the default vLLM-based deployment profile (`codegen-xeon-vllm`).
 3.  **Validate:**
     Wait several minutes for models to download (especially the first time) and services to initialize. Check container logs (`docker compose logs -f <service_name>`) or proceed to the validation steps below.
 
-## Available Deployment Options
+### Available Deployment Options
 
 The `compose.yaml` file uses Docker Compose profiles to select the LLM serving backend.
 
-### Default: vLLM-based Deployment (`--profile codegen-xeon-vllm`)
+#### Default: vLLM-based Deployment (`--profile codegen-xeon-vllm`)
 
 - **Profile:** `codegen-xeon-vllm`
 - **Description:** Uses vLLM optimized for Intel CPUs as the LLM serving engine. This is the default profile used in the Quick Start.
 - **Services Deployed:** `codegen-vllm-server`, `codegen-llm-server`, `codegen-tei-embedding-server`, `codegen-retriever-server`, `redis-vector-db`, `codegen-dataprep-server`, `codegen-backend-server`, `codegen-gradio-ui-server`.
 
-### TGI-based Deployment (`--profile codegen-xeon-tgi`)
+#### TGI-based Deployment (`--profile codegen-xeon-tgi`)
 
 - **Profile:** `codegen-xeon-tgi`
 - **Description:** Uses Hugging Face Text Generation Inference (TGI) optimized for Intel CPUs as the LLM serving engine.
@@ -95,24 +93,24 @@ The `compose.yaml` file uses Docker Compose profiles to select the LLM serving b
   docker compose --profile codegen-xeon-tgi up -d
   ```
 
-## Configuration Parameters
+### Configuration Parameters
 
-### Environment Variables
+#### Environment Variables
 
 Key parameters are configured via environment variables set before running `docker compose up`.
 
-| Environment Variable                    | Description                                                                                                         | Default (Set Externally)                                                                         |
-| :-------------------------------------- | :------------------------------------------------------------------------------------------------------------------ | :----------------------------------------------------------------------------------------------- |
-| `HOST_IP`                               | External IP address of the host machine. **Required.**                                                              | `your_external_ip_address`                                                                       |
-| `HUGGINGFACEHUB_API_TOKEN`              | Your Hugging Face Hub token for model access. **Required.**                                                         | `your_huggingface_token`                                                                         |
-| `LLM_MODEL_ID`                          | Hugging Face model ID for the CodeGen LLM (used by TGI/vLLM service). Configured within `compose.yaml` environment. | `Qwen/Qwen2.5-Coder-7B-Instruct`                                                                 |
-| `EMBEDDING_MODEL_ID`                    | Hugging Face model ID for the embedding model (used by TEI service). Configured within `compose.yaml` environment.  | `BAAI/bge-base-en-v1.5`                                                                          |
-| `LLM_ENDPOINT`                          | Internal URL for the LLM serving endpoint (used by `codegen-llm-server`). Configured in `compose.yaml`.             | `http://codegen-tgi-server:80/generate` or `http://codegen-vllm-server:8000/v1/chat/completions` |
-| `TEI_EMBEDDING_ENDPOINT`                | Internal URL for the Embedding service. Configured in `compose.yaml`.                                               | `http://codegen-tei-embedding-server:80/embed`                                                   |
-| `DATAPREP_ENDPOINT`                     | Internal URL for the Data Preparation service. Configured in `compose.yaml`.                                        | `http://codegen-dataprep-server:80/dataprep`                                                     |
-| `BACKEND_SERVICE_ENDPOINT`              | External URL for the CodeGen Gateway (MegaService). Derived from `HOST_IP` and port `7778`.                         | `http://${HOST_IP}:7778/v1/codegen`                                                              |
-| `*_PORT` (Internal)                     | Internal container ports (e.g., `80`, `6379`). Defined in `compose.yaml`.                                           | N/A                                                                                              |
-| `http_proxy` / `https_proxy`/`no_proxy` | Network proxy settings (if required).                                                                               | `""`                                                                                             |
+| Environment Variable                    | Description                                                                                                         | Default (Set Externally)                       |
+| :-------------------------------------- | :------------------------------------------------------------------------------------------------------------------ | :--------------------------------------------- | ------------------------------------ |
+| `HOST_IP`                               | External IP address of the host machine. **Required.**                                                              | `your_external_ip_address`                     |
+| `HUGGINGFACEHUB_API_TOKEN`              | Your Hugging Face Hub token for model access. **Required.**                                                         | `your_huggingface_token`                       |
+| `LLM_MODEL_ID`                          | Hugging Face model ID for the CodeGen LLM (used by TGI/vLLM service). Configured within `compose.yaml` environment. | `Qwen/Qwen2.5-Coder-7B-Instruct`               |
+| `EMBEDDING_MODEL_ID`                    | Hugging Face model ID for the embedding model (used by TEI service). Configured within `compose.yaml` environment.  | `BAAI/bge-base-en-v1.5`                        |
+| `LLM_ENDPOINT`                          | Internal URL for the LLM serving endpoint (used by `codegen-llm-server`). Configured in `compose.yaml`.             | `http://codegen-vllm                           | tgi-server:9000/v1/chat/completions` |
+| `TEI_EMBEDDING_ENDPOINT`                | Internal URL for the Embedding service. Configured in `compose.yaml`.                                               | `http://codegen-tei-embedding-server:80/embed` |
+| `DATAPREP_ENDPOINT`                     | Internal URL for the Data Preparation service. Configured in `compose.yaml`.                                        | `http://codegen-dataprep-server:80/dataprep`   |
+| `BACKEND_SERVICE_ENDPOINT`              | External URL for the CodeGen Gateway (MegaService). Derived from `HOST_IP` and port `7778`.                         | `http://${HOST_IP}:7778/v1/codegen`            |
+| `*_PORT` (Internal)                     | Internal container ports (e.g., `80`, `6379`). Defined in `compose.yaml`.                                           | N/A                                            |
+| `http_proxy` / `https_proxy`/`no_proxy` | Network proxy settings (if required).                                                                               | `""`                                           |
 
 Most of these parameters are in `set_env.sh`, you can either modify this file or overwrite the env variables by setting them.
 
@@ -120,7 +118,7 @@ Most of these parameters are in `set_env.sh`, you can either modify this file or
 source CodeGen/docker_compose/set_env.sh
 ```
 
-### Compose Profiles
+#### Compose Profiles
 
 Docker Compose profiles (`codegen-xeon-vllm`, `codegen-xeon-tgi`) control which LLM serving backend (vLLM or TGI) and its associated dependencies are started. Only one profile should typically be active.
 
@@ -152,11 +150,11 @@ Check logs for specific services: `docker compose logs <service_name>`
 
 Use `curl` commands to test the main service endpoints. Ensure `HOST_IP` is correctly set in your environment.
 
-1.  **Validate LLM Serving Endpoint (Example for vLLM on default port 8000 internally, exposed differently):**
+1.  **Validate LLM Serving Endpoint (Example for vLLM on default port 9000 internally, exposed differently):**
 
     ```bash
     # This command structure targets the OpenAI-compatible vLLM endpoint
-    curl http://${HOST_IP}:8000/v1/chat/completions \
+    curl http://${HOST_IP}:9000/v1/chat/completions \
        -X POST \
        -H 'Content-Type: application/json' \
        -d '{"model": "Qwen/Qwen2.5-Coder-7B-Instruct", "messages": [{"role": "user", "content": "Implement a basic Python class"}], "max_tokens":32}'
@@ -179,8 +177,8 @@ Multiple UI options can be configured via the `compose.yaml`.
 ### Gradio UI (Default)
 
 Access the default Gradio UI by navigating to:
-`http://{HOST_IP}:8080`
-_(Port `8080` is the default host mapping for `codegen-gradio-ui-server`)_
+`http://{HOST_IP}:5173`
+_(Port `5173` is the default host mapping for `codegen-gradio-ui-server`)_
 
 ![Gradio UI - Code Generation](../../../../assets/img/codegen_gradio_ui_main.png)
 ![Gradio UI - Resource Management](../../../../assets/img/codegen_gradio_ui_dataprep.png)

CodeGen/docker_compose/intel/hpu/gaudi/README.md

@@ -6,23 +6,10 @@ This README provides instructions for deploying the CodeGen application using Do
 
 - [Overview](#overview)
 - [Prerequisites](#prerequisites)
-- [Quick Start](#quick-start)
-- [Available Deployment Options](#available-deployment-options)
-  - [Default: vLLM-based Deployment (`--profile codegen-gaudi-vllm`)](#default-vllm-based-deployment---profile-codegen-gaudi-vllm)
-  - [TGI-based Deployment (`--profile codegen-gaudi-tgi`)](#tgi-based-deployment---profile-codegen-gaudi-tgi)
-- [Configuration Parameters](#configuration-parameters)
-  - [Environment Variables](#environment-variables)
-  - [Compose Profiles](#compose-profiles)
-  - [Docker Compose Gaudi Configuration](#docker-compose-gaudi-configuration)
+- [Quick Start Deployment](#quick-start-deployment)
 - [Building Custom Images (Optional)](#building-custom-images-optional)
 - [Validate Services](#validate-services)
-  - [Check Container Status](#check-container-status)
-  - [Run Validation Script/Commands](#run-validation-scriptcommands)
 - [Accessing the User Interface (UI)](#accessing-the-user-interface-ui)
-  - [Gradio UI (Default)](#gradio-ui-default)
-  - [Svelte UI (Optional)](#svelte-ui-optional)
-  - [React UI (Optional)](#react-ui-optional)
-  - [VS Code Extension (Optional)](#vs-code-extension-optional)
 - [Troubleshooting](#troubleshooting)
 - [Stopping the Application](#stopping-the-application)
 - [Next Steps](#next-steps)
@@ -44,7 +31,7 @@ This guide focuses on running the pre-configured CodeGen service using Docker Co
   cd GenAIExamples/CodeGen/docker_compose/intel/hpu/gaudi
   ```
 
-## Quick Start
+## Quick Start Deployment
 
 This uses the default vLLM-based deployment profile (`codegen-gaudi-vllm`).
 
@@ -61,10 +48,21 @@ This uses the default vLLM-based deployment profile (`codegen-gaudi-vllm`).
     # export http_proxy="your_http_proxy"
     # export https_proxy="your_https_proxy"
     # export no_proxy="localhost,127.0.0.1,${HOST_IP}" # Add other hosts if necessary
-    source ../../../set_env.sh
+    source ../../set_env.sh
     ```
 
-    _Note: Ensure all required variables like ports (`LLM_SERVICE_PORT`, `MEGA_SERVICE_PORT`, etc.) are set if not using defaults from the compose file._
+    _Note: The compose file might read additional variables from set_env.sh. Ensure all required variables like ports (`LLM_SERVICE_PORT`, `MEGA_SERVICE_PORT`, etc.) are set if not using defaults from the compose file._
+    For instance, edit the set_env.sh to change the LLM model
+
+    ```
+    export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
+    ```
+
+    can be changed to other model if needed
+
+    ```
+    export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-32B-Instruct"
+    ```
 
 2.  **Start Services (vLLM Profile):**
 
@@ -104,18 +102,18 @@ The `compose.yaml` file uses Docker Compose profiles to select the LLM serving b
 
 Key parameters are configured via environment variables set before running `docker compose up`.
 
-| Environment Variable                    | Description                                                                                                         | Default (Set Externally)                                                                         |
-| :-------------------------------------- | :------------------------------------------------------------------------------------------------------------------ | :----------------------------------------------------------------------------------------------- |
-| `HOST_IP`                               | External IP address of the host machine. **Required.**                                                              | `your_external_ip_address`                                                                       |
-| `HUGGINGFACEHUB_API_TOKEN`              | Your Hugging Face Hub token for model access. **Required.**                                                         | `your_huggingface_token`                                                                         |
-| `LLM_MODEL_ID`                          | Hugging Face model ID for the CodeGen LLM (used by TGI/vLLM service). Configured within `compose.yaml` environment. | `Qwen/Qwen2.5-Coder-7B-Instruct`                                                                 |
-| `EMBEDDING_MODEL_ID`                    | Hugging Face model ID for the embedding model (used by TEI service). Configured within `compose.yaml` environment.  | `BAAI/bge-base-en-v1.5`                                                                          |
-| `LLM_ENDPOINT`                          | Internal URL for the LLM serving endpoint (used by `codegen-llm-server`). Configured in `compose.yaml`.             | `http://codegen-tgi-server:80/generate` or `http://codegen-vllm-server:8000/v1/chat/completions` |
-| `TEI_EMBEDDING_ENDPOINT`                | Internal URL for the Embedding service. Configured in `compose.yaml`.                                               | `http://codegen-tei-embedding-server:80/embed`                                                   |
-| `DATAPREP_ENDPOINT`                     | Internal URL for the Data Preparation service. Configured in `compose.yaml`.                                        | `http://codegen-dataprep-server:80/dataprep`                                                     |
-| `BACKEND_SERVICE_ENDPOINT`              | External URL for the CodeGen Gateway (MegaService). Derived from `HOST_IP` and port `7778`.                         | `http://${HOST_IP}:7778/v1/codegen`                                                              |
-| `*_PORT` (Internal)                     | Internal container ports (e.g., `80`, `6379`). Defined in `compose.yaml`.                                           | N/A                                                                                              |
-| `http_proxy` / `https_proxy`/`no_proxy` | Network proxy settings (if required).                                                                               | `""`                                                                                             |
+| Environment Variable                    | Description                                                                                                         | Default (Set Externally)                       |
+| :-------------------------------------- | :------------------------------------------------------------------------------------------------------------------ | :--------------------------------------------- | ------------------------------------ |
+| `HOST_IP`                               | External IP address of the host machine. **Required.**                                                              | `your_external_ip_address`                     |
+| `HUGGINGFACEHUB_API_TOKEN`              | Your Hugging Face Hub token for model access. **Required.**                                                         | `your_huggingface_token`                       |
+| `LLM_MODEL_ID`                          | Hugging Face model ID for the CodeGen LLM (used by TGI/vLLM service). Configured within `compose.yaml` environment. | `Qwen/Qwen2.5-Coder-7B-Instruct`               |
+| `EMBEDDING_MODEL_ID`                    | Hugging Face model ID for the embedding model (used by TEI service). Configured within `compose.yaml` environment.  | `BAAI/bge-base-en-v1.5`                        |
+| `LLM_ENDPOINT`                          | Internal URL for the LLM serving endpoint (used by `llm-codegen-vllm-server`). Configured in `compose.yaml`.        | http://codegen-vllm                            | tgi-server:9000/v1/chat/completions` |
+| `TEI_EMBEDDING_ENDPOINT`                | Internal URL for the Embedding service. Configured in `compose.yaml`.                                               | `http://codegen-tei-embedding-server:80/embed` |
+| `DATAPREP_ENDPOINT`                     | Internal URL for the Data Preparation service. Configured in `compose.yaml`.                                        | `http://codegen-dataprep-server:80/dataprep`   |
+| `BACKEND_SERVICE_ENDPOINT`              | External URL for the CodeGen Gateway (MegaService). Derived from `HOST_IP` and port `7778`.                         | `http://${HOST_IP}:7778/v1/codegen`            |
+| `*_PORT` (Internal)                     | Internal container ports (e.g., `80`, `6379`). Defined in `compose.yaml`.                                           | N/A                                            |
+| `http_proxy` / `https_proxy`/`no_proxy` | Network proxy settings (if required).                                                                               | `""`                                           |
 
 Most of these parameters are in `set_env.sh`, you can either modify this file or overwrite the env variables by setting them.
 
@@ -172,11 +170,11 @@ Check logs: `docker compose logs <service_name>`. Pay attention to `vllm-gaudi-s
 
 Use `curl` commands targeting the main service endpoints. Ensure `HOST_IP` is correctly set.
 
-1.  **Validate LLM Serving Endpoint (Example for vLLM on default port 8000 internally, exposed differently):**
+1.  **Validate LLM Serving Endpoint (Example for vLLM on default port 9000 internally, exposed differently):**
 
     ```bash
     # This command structure targets the OpenAI-compatible vLLM endpoint
-    curl http://${HOST_IP}:8000/v1/chat/completions \
+    curl http://${HOST_IP}:9000/v1/chat/completions \
        -X POST \
        -H 'Content-Type: application/json' \
        -d '{"model": "Qwen/Qwen2.5-Coder-7B-Instruct", "messages": [{"role": "user", "content": "Implement a basic Python class"}], "max_tokens":32}'
@@ -197,8 +195,8 @@ UI options are similar to the Xeon deployment.
 ### Gradio UI (Default)
 
 Access the default Gradio UI:
-`http://{HOST_IP}:8080`
-_(Port `8080` is the default host mapping)_
+`http://{HOST_IP}:5173`
+_(Port `5173` is the default host mapping)_
 
 ![Gradio UI](../../../../assets/img/codegen_gradio_ui_main.png)
 

CodeGen/docker_compose/intel/set_env.sh

@@ -0,0 +1,51 @@
+#!/usr/bin/env bash
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+pushd "../../" > /dev/null
+source .set_env.sh
+popd > /dev/null
+
+export HOST_IP=$(hostname -I | awk '{print $1}')
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+if [ -z "${HUGGINGFACEHUB_API_TOKEN}" ]; then
+    echo "Error: HUGGINGFACEHUB_API_TOKEN is not set. Please set HUGGINGFACEHUB_API_TOKEN"
+fi
+
+if [ -z "${HOST_IP}" ]; then
+    echo "Error: HOST_IP is not set. Please set HOST_IP first."
+fi
+
+export no_proxy=${no_proxy},${HOST_IP}
+export http_proxy=${http_proxy}
+export https_proxy=${https_proxy}
+
+export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
+export LLM_SERVICE_PORT=9000
+export LLM_ENDPOINT="http://${HOST_IP}:8028"
+export LLM_SERVICE_HOST_IP=${HOST_IP}
+export TGI_LLM_ENDPOINT="http://${HOST_IP}:8028"
+
+export MEGA_SERVICE_PORT=7778
+export MEGA_SERVICE_HOST_IP=${HOST_IP}
+export BACKEND_SERVICE_ENDPOINT="http://${HOST_IP}:7778/v1/codegen"
+
+export REDIS_DB_PORT=6379
+export REDIS_INSIGHTS_PORT=8001
+export REDIS_RETRIEVER_PORT=7000
+export REDIS_URL="redis://${HOST_IP}:${REDIS_DB_PORT}"
+export RETRIEVAL_SERVICE_HOST_IP=${HOST_IP}
+export RETRIEVER_COMPONENT_NAME="OPEA_RETRIEVER_REDIS"
+export INDEX_NAME="CodeGen"
+
+export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
+export EMBEDDER_PORT=6000
+export TEI_EMBEDDER_PORT=8090
+export TEI_EMBEDDING_HOST_IP=${HOST_IP}
+export TEI_EMBEDDING_ENDPOINT="http://${HOST_IP}:${TEI_EMBEDDER_PORT}"
+
+export DATAPREP_REDIS_PORT=6007
+export DATAPREP_ENDPOINT="http://${HOST_IP}:${DATAPREP_REDIS_PORT}/v1/dataprep"
+export LOGFLAG=false
+export MODEL_CACHE=${model_cache:-"./data"}
+export NUM_CARDS=1

CodeGen/docker_compose/set_env.sh

@@ -1,50 +0,0 @@
-#!/usr/bin/env bash
-
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-pushd "../../" > /dev/null
-source .set_env.sh
-popd > /dev/null
-
-export host_ip=$(hostname -I | awk '{print $1}')
-if [ -z "${HUGGINGFACEHUB_API_TOKEN}" ]; then
-    echo "Error: HUGGINGFACEHUB_API_TOKEN is not set. Please set HUGGINGFACEHUB_API_TOKEN"
-fi
-
-if [ -z "${host_ip}" ]; then
-    echo "Error: host_ip is not set. Please set host_ip first."
-fi
-
-export no_proxy=${no_proxy},${host_ip}
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-
-export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-32B-Instruct"
-export LLM_SERVICE_PORT=9000
-export LLM_ENDPOINT="http://${host_ip}:8028"
-export LLM_SERVICE_HOST_IP=${host_ip}
-export TGI_LLM_ENDPOINT="http://${host_ip}:8028"
-
-export MEGA_SERVICE_PORT=7778
-export MEGA_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:7778/v1/codegen"
-
-export REDIS_DB_PORT=6379
-export REDIS_INSIGHTS_PORT=8001
-export REDIS_RETRIEVER_PORT=7000
-export REDIS_URL="redis://${host_ip}:${REDIS_DB_PORT}"
-export RETRIEVAL_SERVICE_HOST_IP=${host_ip}
-export RETRIEVER_COMPONENT_NAME="OPEA_RETRIEVER_REDIS"
-export INDEX_NAME="CodeGen"
-
-export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export EMBEDDER_PORT=6000
-export TEI_EMBEDDER_PORT=8090
-export TEI_EMBEDDING_HOST_IP=${host_ip}
-export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:${TEI_EMBEDDER_PORT}"
-
-export DATAPREP_REDIS_PORT=6007
-export DATAPREP_ENDPOINT="http://${host_ip}:${DATAPREP_REDIS_PORT}/v1/dataprep"
-export LOGFLAG=false
-export MODEL_CACHE="./data"
-export NUM_CARDS=1

CodeGen/docker_image_build/build.yaml

@@ -5,6 +5,8 @@ services:
   codegen:
     build:
       args:
+        IMAGE_REPO: ${REGISTRY}
+        BASE_TAG: ${TAG}
         http_proxy: ${http_proxy}
         https_proxy: ${https_proxy}
         no_proxy: ${no_proxy}
@@ -39,6 +41,7 @@ services:
     build:
       context: GenAIComps
       dockerfile: comps/third_parties/vllm/src/Dockerfile.amd_gpu
+    extends: codegen
     image: ${REGISTRY:-opea}/vllm-rocm:${TAG:-latest}
   vllm:
     build:

CodeGen/tests/README.md

@@ -0,0 +1,33 @@
+# CodeGen 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
+```
+
+On AMD ROCm with vLLM:
+
+```bash
+bash test_compose_vllm_on_rocm.sh
+```

CodeGen/tests/test_compose_on_gaudi.sh

@@ -10,36 +10,20 @@ echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
 export REGISTRY=${IMAGE_REPO}
 export TAG=${IMAGE_TAG}
 export MODEL_CACHE=${model_cache:-"./data"}
-export REDIS_DB_PORT=6379
-export REDIS_INSIGHTS_PORT=8001
-export REDIS_RETRIEVER_PORT=7000
-export EMBEDDER_PORT=6000
-export TEI_EMBEDDER_PORT=8090
-export DATAPREP_REDIS_PORT=6007
 
 WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
 ip_address=$(hostname -I | awk '{print $1}')
-
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-export no_proxy=${no_proxy},${ip_address}
-
+source $WORKPATH/docker_compose/intel/set_env.sh
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}
-    # If the opea_branch isn't main, replace the git clone branch in Dockerfile.
-    if [[ "${opea_branch}" != "main" ]]; then
-        cd $WORKPATH
-        OLD_STRING="RUN git clone --depth 1 https://github.com/opea-project/GenAIComps.git"
-        NEW_STRING="RUN git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git"
-        find . -type f -name "Dockerfile*" | while read -r file; do
-            echo "Processing file: $file"
-            sed -i "s|$OLD_STRING|$NEW_STRING|g" "$file"
-        done
-    fi
 
     cd $WORKPATH/docker_image_build
     git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
 
     # Download Gaudi vllm of latest tag
     git clone https://github.com/HabanaAI/vllm-fork.git && cd vllm-fork
@@ -60,28 +44,6 @@ function start_services() {
 
     cd $WORKPATH/docker_compose/intel/hpu/gaudi
 
-    export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
-    export LLM_ENDPOINT="http://${ip_address}:8028"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export MEGA_SERVICE_PORT=7778
-    export MEGA_SERVICE_HOST_IP=${ip_address}
-    export LLM_SERVICE_HOST_IP=${ip_address}
-    export BACKEND_SERVICE_ENDPOINT="http://${ip_address}:${MEGA_SERVICE_PORT}/v1/codegen"
-    export NUM_CARDS=1
-    export host_ip=${ip_address}
-
-    export REDIS_URL="redis://${host_ip}:${REDIS_DB_PORT}"
-    export RETRIEVAL_SERVICE_HOST_IP=${host_ip}
-    export RETRIEVER_COMPONENT_NAME="OPEA_RETRIEVER_REDIS"
-    export INDEX_NAME="CodeGen"
-
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export TEI_EMBEDDING_HOST_IP=${host_ip}
-    export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:${TEI_EMBEDDER_PORT}"
-    export DATAPREP_ENDPOINT="http://${host_ip}:${DATAPREP_REDIS_PORT}/v1/dataprep"
-
-    export INDEX_NAME="CodeGen"
-
     # Start Docker Containers
     docker compose --profile ${compose_profile} up -d | tee ${LOG_PATH}/start_services_with_compose.log
 
@@ -250,24 +212,36 @@ function main() {
         stop_docker "${docker_compose_profiles[${i}]}"
     done
 
-    # build docker images
+    echo "::group::build_docker_images"
     if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
 
     # loop all profiles
     for ((i = 0; i < len_profiles; i++)); do
         echo "Process [${i}]: ${docker_compose_profiles[$i]}, ${docker_llm_container_names[${i}]}"
+
+        echo "::group::start_services"
         start_services "${docker_compose_profiles[${i}]}" "${docker_llm_container_names[${i}]}"
+        echo "::endgroup::"
         docker ps -a
 
+        echo "::group::validate_microservices"
         validate_microservices "${docker_llm_container_names[${i}]}"
+        echo "::endgroup::"
+
+        echo "::group::validate_megaservice"
         validate_megaservice
+        echo "::endgroup::"
+
+        echo "::group::validate_gradio"
         validate_gradio
+        echo "::endgroup::"
 
         stop_docker "${docker_compose_profiles[${i}]}"
         sleep 5s
     done
 
-    echo y | docker system prune
+    docker system prune -f
 }
 
 main

CodeGen/tests/test_compose_on_rocm.sh

@@ -17,19 +17,13 @@ ip_address=$(hostname -I | awk '{print $1}')
 
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}
-    # If the opea_branch isn't main, replace the git clone branch in Dockerfile.
-    if [[ "${opea_branch}" != "main" ]]; then
-        cd $WORKPATH
-        OLD_STRING="RUN git clone --depth 1 https://github.com/opea-project/GenAIComps.git"
-        NEW_STRING="RUN git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git"
-        find . -type f -name "Dockerfile*" | while read -r file; do
-            echo "Processing file: $file"
-            sed -i "s|$OLD_STRING|$NEW_STRING|g" "$file"
-        done
-    fi
 
     cd $WORKPATH/docker_image_build
     git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
 
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
     service_list="codegen codegen-ui llm-textgen"
@@ -41,18 +35,7 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/amd/gpu/rocm/
-
-    export CODEGEN_LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
-    export CODEGEN_TGI_SERVICE_PORT=8028
-    export CODEGEN_TGI_LLM_ENDPOINT="http://${ip_address}:${CODEGEN_TGI_SERVICE_PORT}"
-    export CODEGEN_LLM_SERVICE_PORT=9000
-    export CODEGEN_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export CODEGEN_MEGA_SERVICE_HOST_IP=${ip_address}
-    export CODEGEN_LLM_SERVICE_HOST_IP=${ip_address}
-    export CODEGEN_BACKEND_SERVICE_PORT=7778
-    export CODEGEN_BACKEND_SERVICE_URL="http://${ip_address}:${CODEGEN_BACKEND_SERVICE_PORT}/v1/codegen"
-    export CODEGEN_UI_SERVICE_PORT=5173
-    export HOST_IP=${ip_address}
+    source set_env.sh
 
     sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
 
@@ -164,18 +147,35 @@ function stop_docker() {
 
 function main() {
 
+    echo "::group::stop_docker"
     stop_docker
+    echo "::endgroup::"
 
+    echo "::group::build_docker_images"
     if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
+
+    echo "::group::start_services"
     start_services
+    echo "::endgroup::"
 
+    echo "::group::validate_microservices"
     validate_microservices
-    validate_megaservice
-    validate_frontend
+    echo "::endgroup::"
 
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::validate_frontend"
+    validate_frontend
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
     stop_docker
-    echo y | docker system prune
-    cd $WORKPATH
+    echo "::endgroup::"
+
+    docker system prune -f
 
 }
 

CodeGen/tests/test_compose_on_xeon.sh

@@ -10,36 +10,21 @@ echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
 export REGISTRY=${IMAGE_REPO}
 export TAG=${IMAGE_TAG}
 export MODEL_CACHE=${model_cache:-"./data"}
-export REDIS_DB_PORT=6379
-export REDIS_INSIGHTS_PORT=8001
-export REDIS_RETRIEVER_PORT=7000
-export EMBEDDER_PORT=6000
-export TEI_EMBEDDER_PORT=8090
-export DATAPREP_REDIS_PORT=6007
 
 WORKPATH=$(dirname "$PWD")
 LOG_PATH="$WORKPATH/tests"
 ip_address=$(hostname -I | awk '{print $1}')
-
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-export no_proxy=${no_proxy},${ip_address}
+source $WORKPATH/docker_compose/intel/set_env.sh
 
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}
-    # If the opea_branch isn't main, replace the git clone branch in Dockerfile.
-    if [[ "${opea_branch}" != "main" ]]; then
-        cd $WORKPATH
-        OLD_STRING="RUN git clone --depth 1 https://github.com/opea-project/GenAIComps.git"
-        NEW_STRING="RUN git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git"
-        find . -type f -name "Dockerfile*" | while read -r file; do
-            echo "Processing file: $file"
-            sed -i "s|$OLD_STRING|$NEW_STRING|g" "$file"
-        done
-    fi
 
     cd $WORKPATH/docker_image_build
     git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
 
     git clone https://github.com/vllm-project/vllm.git && cd vllm
     VLLM_VER="v0.8.3"
@@ -62,25 +47,6 @@ function start_services() {
 
     cd $WORKPATH/docker_compose/intel/cpu/xeon/
 
-    export LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
-    export LLM_ENDPOINT="http://${ip_address}:8028"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export MEGA_SERVICE_PORT=7778
-    export MEGA_SERVICE_HOST_IP=${ip_address}
-    export LLM_SERVICE_HOST_IP=${ip_address}
-    export BACKEND_SERVICE_ENDPOINT="http://${ip_address}:${MEGA_SERVICE_PORT}/v1/codegen"
-    export host_ip=${ip_address}
-
-    export REDIS_URL="redis://${host_ip}:${REDIS_DB_PORT}"
-    export RETRIEVAL_SERVICE_HOST_IP=${host_ip}
-    export RETRIEVER_COMPONENT_NAME="OPEA_RETRIEVER_REDIS"
-    export INDEX_NAME="CodeGen"
-
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export TEI_EMBEDDING_HOST_IP=${host_ip}
-    export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:${TEI_EMBEDDER_PORT}"
-    export DATAPREP_ENDPOINT="http://${host_ip}:${DATAPREP_REDIS_PORT}/v1/dataprep"
-
     # Start Docker Containers
     docker compose --profile ${compose_profile} up -d > ${LOG_PATH}/start_services_with_compose.log
 
@@ -256,17 +222,28 @@ function main() {
     for ((i = 0; i < len_profiles; i++)); do
         echo "Process [${i}]: ${docker_compose_profiles[$i]}, ${docker_llm_container_names[${i}]}"
         docker ps -a
-        start_services "${docker_compose_profiles[${i}]}" "${docker_llm_container_names[${i}]}"
 
+        echo "::group::start_services"
+        start_services "${docker_compose_profiles[${i}]}" "${docker_llm_container_names[${i}]}"
+        echo "::endgroup::"
+
+        echo "::group::validate_microservices"
         validate_microservices "${docker_llm_container_names[${i}]}"
+        echo "::endgroup::"
+
+        echo "::group::validate_megaservice"
         validate_megaservice
+        echo "::endgroup::"
+
+        echo "::group::validate_gradio"
         validate_gradio
+        echo "::endgroup::"
 
         stop_docker "${docker_compose_profiles[${i}]}"
         sleep 5s
     done
 
-    echo y | docker system prune
+    docker system prune -f
 }
 
 main

CodeGen/tests/test_compose_vllm_on_rocm.sh

@@ -17,19 +17,13 @@ ip_address=$(hostname -I | awk '{print $1}')
 
 function build_docker_images() {
     opea_branch=${opea_branch:-"main"}
-    # If the opea_branch isn't main, replace the git clone branch in Dockerfile.
-    if [[ "${opea_branch}" != "main" ]]; then
-        cd $WORKPATH
-        OLD_STRING="RUN git clone --depth 1 https://github.com/opea-project/GenAIComps.git"
-        NEW_STRING="RUN git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git"
-        find . -type f -name "Dockerfile*" | while read -r file; do
-            echo "Processing file: $file"
-            sed -i "s|$OLD_STRING|$NEW_STRING|g" "$file"
-        done
-    fi
 
     cd $WORKPATH/docker_image_build
     git clone --depth 1 --branch ${opea_branch} https://github.com/opea-project/GenAIComps.git
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
 
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
     service_list="vllm-rocm llm-textgen codegen codegen-ui"
@@ -40,18 +34,7 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/amd/gpu/rocm/
-
-    export CODEGEN_LLM_MODEL_ID="Qwen/Qwen2.5-Coder-7B-Instruct"
-    export CODEGEN_VLLM_SERVICE_PORT=8028
-    export CODEGEN_VLLM_ENDPOINT="http://${ip_address}:${CODEGEN_VLLM_SERVICE_PORT}"
-    export CODEGEN_LLM_SERVICE_PORT=9000
-    export CODEGEN_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export CODEGEN_MEGA_SERVICE_HOST_IP=${ip_address}
-    export CODEGEN_LLM_SERVICE_HOST_IP=${ip_address}
-    export CODEGEN_BACKEND_SERVICE_PORT=7778
-    export CODEGEN_BACKEND_SERVICE_URL="http://${ip_address}:${CODEGEN_BACKEND_SERVICE_PORT}/v1/codegen"
-    export CODEGEN_UI_SERVICE_PORT=5173
-    export HOST_IP=${ip_address}
+    source set_env_vllm.sh
 
     sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
 
@@ -164,17 +147,35 @@ function stop_docker() {
 
 function main() {
 
+    echo "::group::stop_docker"
     stop_docker
+    echo "::endgroup::"
+
+    echo "::group::build_docker_images"
     if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
+
+    echo "::group::start_services"
     start_services
+    echo "::endgroup::"
 
+    echo "::group::validate_microservices"
     validate_microservices
-    validate_megaservice
-    validate_frontend
+    echo "::endgroup::"
 
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::validate_frontend"
+    validate_frontend
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
     stop_docker
-    echo y | docker system prune
-    cd $WORKPATH
+    echo "::endgroup::"
+
+    docker system prune -f
 
 }
 

CodeTrans/README.md

@@ -22,12 +22,11 @@ This Code Translation use case demonstrates Text Generation Inference across mul
 
 The table below lists currently available deployment options. They outline in detail the implementation of this example on selected hardware.
 
-| Category               | Deployment Option    | Description                                                       |
-| ---------------------- | -------------------- | ----------------------------------------------------------------- |
-| On-premise Deployments | Docker compose       | [CodeTrans deployment on Xeon](./docker_compose/intel/cpu/xeon)   |
-|                        |                      | [CodeTrans deployment on Gaudi](./docker_compose/intel/hpu/gaudi) |
-|                        |                      | [CodeTrans deployment on AMD ROCm](./docker_compose/amd/gpu/rocm) |
-|                        | Kubernetes           | [Helm Charts](./kubernetes/helm)                                  |
-|                        |                      | [GMC](./kubernetes/gmc)                                           |
-|                        | Azure                | Work-in-progress                                                  |
-|                        | Intel Tiber AI Cloud | Work-in-progress                                                  |
+| Category               | Deployment Option    | Description                                                                 |
+| ---------------------- | -------------------- | --------------------------------------------------------------------------- |
+| On-premise Deployments | Docker compose       | [CodeTrans deployment on Xeon](./docker_compose/intel/cpu/xeon/README.md)   |
+|                        |                      | [CodeTrans deployment on Gaudi](./docker_compose/intel/hpu/gaudi/README.md) |
+|                        |                      | [CodeTrans deployment on AMD ROCm](./docker_compose/amd/gpu/rocm/README.md) |
+|                        | Kubernetes           | [Helm Charts](./kubernetes/helm/README.md)                                  |
+|                        | Azure                | Work-in-progress                                                            |
+|                        | Intel Tiber AI Cloud | Work-in-progress                                                            |

CodeTrans/README_miscellaneous.md

@@ -44,3 +44,38 @@ Some HuggingFace resources, such as some models, are only accessible if the deve
 
 2. (Docker only) If all microservices work well, check the port ${host_ip}:7777, the port may be allocated by other users, you can modify the `compose.yaml`.
 3. (Docker only) If you get errors like "The container name is in use", change container name in `compose.yaml`.
+
+## Monitoring OPEA Services with Prometheus and Grafana Dashboard
+
+OPEA microservice deployment can easily be monitored through Grafana dashboards using data collected via Prometheus. Follow the [README](https://github.com/opea-project/GenAIEval/blob/main/evals/benchmark/grafana/README.md) to setup Prometheus and Grafana servers and import dashboards to monitor the OPEA services.
+
+![example dashboards](./assets/img/example_dashboards.png)
+![tgi dashboard](./assets/img/tgi_dashboard.png)
+
+## Tracing with OpenTelemetry and Jaeger
+
+> NOTE: This feature is disabled by default. Please use the compose.telemetry.yaml file to enable this feature.
+
+OPEA microservice and [TGI](https://huggingface.co/docs/text-generation-inference/en/index)/[TEI](https://huggingface.co/docs/text-embeddings-inference/en/index) serving can easily be traced through [Jaeger](https://www.jaegertracing.io/) dashboards in conjunction with [OpenTelemetry](https://opentelemetry.io/) Tracing feature. Follow the [README](https://github.com/opea-project/GenAIComps/tree/main/comps/cores/telemetry#tracing) to trace additional functions if needed.
+
+Tracing data is exported to http://{EXTERNAL_IP}:4318/v1/traces via Jaeger.
+Users could also get the external IP via below command.
+
+```bash
+ip route get 8.8.8.8 | grep -oP 'src \K[^ ]+'
+```
+
+Access the Jaeger dashboard UI at http://{EXTERNAL_IP}:16686
+
+For TGI serving on Gaudi, users could see different services like opea, TEI and TGI.
+![Screenshot from 2024-12-27 11-58-18](https://github.com/user-attachments/assets/6126fa70-e830-4780-bd3f-83cb6eff064e)
+
+Here is a screenshot for one tracing of TGI serving request.
+![Screenshot from 2024-12-27 11-26-25](https://github.com/user-attachments/assets/3a7c51c6-f422-41eb-8e82-c3df52cd48b8)
+
+There are also OPEA related tracings. Users could understand the time breakdown of each service request by looking into each opea:schedule operation.
+![image](https://github.com/user-attachments/assets/6137068b-b374-4ff8-b345-993343c0c25f)
+
+There could be asynchronous function such as `llm/MicroService_asyn_generate` and user needs to check the trace of the asynchronous function in another operation like
+opea:llm_generate_stream.
+![image](https://github.com/user-attachments/assets/a973d283-198f-4ce2-a7eb-58515b77503e)

CodeTrans/docker_compose/intel/cpu/xeon/README.md

@@ -46,7 +46,7 @@ export http_proxy="Your_HTTP_Proxy"           # http proxy if any
 export https_proxy="Your_HTTPs_Proxy"         # https proxy if any
 export no_proxy=localhost,127.0.0.1,$host_ip  # additional no proxies if needed
 export NGINX_PORT=${your_nginx_port}          # your usable port for nginx, 80 for example
-source ./set_env.sh
+source docker_compose/intel/set_env.sh
 ```
 
 Consult the section on [CodeTrans Service configuration](#codetrans-configuration) for information on how service specific configuration parameters affect deployments.

CodeTrans/docker_compose/intel/hpu/gaudi/README.md

@@ -46,7 +46,7 @@ export http_proxy="Your_HTTP_Proxy"           # http proxy if any
 export https_proxy="Your_HTTPs_Proxy"         # https proxy if any
 export no_proxy=localhost,127.0.0.1,$host_ip  # additional no proxies if needed
 export NGINX_PORT=${your_nginx_port}          # your usable port for nginx, 80 for example
-source ./set_env.sh
+source docker_compose/intel/set_env.sh
 ```
 
 Consult the section on [CodeTrans Service configuration](#codetrans-configuration) for information on how service specific configuration parameters affect deployments.

CodeTrans/docker_compose/intel/set_env.sh

@@ -2,7 +2,7 @@
 
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
-pushd "../../" > /dev/null
+pushd "../../../" > /dev/null
 source .set_env.sh
 popd > /dev/null
 

CodeTrans/tests/test_compose_on_gaudi.sh

@@ -37,12 +37,12 @@ function build_docker_images() {
 }
 
 function start_services() {
-    cd $WORKPATH/docker_compose
+    cd $WORKPATH/docker_compose/intel
     export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
     export NGINX_PORT=80
     export host_ip=${ip_address}
     source set_env.sh
-    cd intel/hpu/gaudi
+    cd hpu/gaudi
 
     sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
 

CodeTrans/tests/test_compose_on_xeon.sh

@@ -39,13 +39,13 @@ function build_docker_images() {
 }
 
 function start_services() {
-    cd $WORKPATH/docker_compose
+    cd $WORKPATH/docker_compose/intel
     export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 
     export NGINX_PORT=80
     export host_ip=${ip_address}
     source set_env.sh
-    cd intel/cpu/xeon/
+    cd cpu/xeon/
 
     sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
 

CodeTrans/tests/test_compose_tgi_on_gaudi.sh

@@ -34,13 +34,13 @@ function build_docker_images() {
 }
 
 function start_services() {
-    cd $WORKPATH/docker_compose
+    cd $WORKPATH/docker_compose/intel
     export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 
     export NGINX_PORT=80
     export host_ip=${ip_address}
     source set_env.sh
-    cd intel/hpu/gaudi/
+    cd hpu/gaudi/
 
     sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
 

CodeTrans/tests/test_compose_tgi_on_xeon.sh

@@ -34,13 +34,13 @@ function build_docker_images() {
 }
 
 function start_services() {
-    cd $WORKPATH/docker_compose
+    cd $WORKPATH/docker_compose/intel
     export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 
     export NGINX_PORT=80
     export host_ip=${ip_address}
     source set_env.sh
-    cd intel/cpu/xeon/
+    cd cpu/xeon/
 
     sed -i "s/backend_address/$ip_address/g" $WORKPATH/ui/svelte/.env
 

DocIndexRetriever/Dockerfile

@@ -1,8 +1,9 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+ARG IMAGE_REPO=opea
 ARG BASE_TAG=latest
-FROM opea/comps-base:$BASE_TAG
+FROM $IMAGE_REPO/comps-base:$BASE_TAG
 
 COPY ./retrieval_tool.py $HOME/retrieval_tool.py
 

DocIndexRetriever/docker_compose/intel/cpu/xeon/README.md

@@ -2,7 +2,11 @@
 
 DocRetriever are the most widely adopted use case for leveraging the different methodologies to match user query against a set of free-text records. DocRetriever is essential to RAG system, which bridges the knowledge gap by dynamically fetching relevant information from external sources, ensuring that responses generated remain factual and current. The core of this architecture are vector databases, which are instrumental in enabling efficient and semantic retrieval of information. These databases store data as vectors, allowing RAG to swiftly access the most pertinent documents or data points based on semantic similarity.
 
-## 1. Build Images for necessary microservices. (Optional after docker image release)
+\_Note:
+
+As the related docker images were published to Docker Hub, you can ignore the below step 1 and 2， quick start from step 3.
+
+## 1. Build Images for necessary microservices. (Optional)
 
 - Embedding TEI Image
 
@@ -30,7 +34,7 @@ DocRetriever are the most widely adopted use case for leveraging the different m
   docker build -t opea/dataprep:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/src/Dockerfile .
   ```
 
-## 2. Build Images for MegaService
+## 2. Build Images for MegaService (Optional)
 
 ```bash
 cd ..
@@ -44,6 +48,19 @@ docker build --no-cache -t opea/doc-index-retriever:latest --build-arg https_pro
 ```bash
 export host_ip="YOUR IP ADDR"
 export HUGGINGFACEHUB_API_TOKEN=${your_hf_api_token}
+```
+
+Set environment variables by
+
+```
+cd GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon
+source set_env.sh
+```
+
+Note: set_env.sh will help to set all required variables. Please ensure all required variables like ports (LLM_SERVICE_PORT, MEGA_SERVICE_PORT, etc.) are set if not using defaults from the compose file.
+or Set environment variables manually
+
+```
 export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
 export RERANK_MODEL_ID="BAAI/bge-reranker-base"
 export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006"

DocIndexRetriever/docker_image_build/build.yaml

@@ -5,6 +5,8 @@ services:
   doc-index-retriever:
     build:
       args:
+        IMAGE_REPO: ${REGISTRY:-opea}
+        BASE_TAG: ${TAG:-latest}
         http_proxy: ${http_proxy}
         https_proxy: ${https_proxy}
         no_proxy: ${no_proxy}

DocIndexRetriever/tests/test_compose_milvus_on_gaudi.sh

@@ -20,17 +20,15 @@ function build_docker_images() {
     if [ ! -d "GenAIComps" ] ; then
         git clone --single-branch --branch "${opea_branch:-"main"}" https://github.com/opea-project/GenAIComps.git
     fi
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
+
     service_list="dataprep embedding retriever reranking doc-index-retriever"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
-    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
-    docker pull ghcr.io/huggingface/tei-gaudi:1.5.0
-    docker pull quay.io/coreos/etcd:v3.5.5
-    docker pull minio/minio:RELEASE.2023-03-20T20-16-18Z
-    docker pull milvusdb/milvus:v2.4.6
     docker images && sleep 1s
-
-    echo "Docker images built!"
 }
 
 function start_services() {
@@ -112,19 +110,27 @@ function stop_docker() {
 
 function main() {
 
+    echo "::group::stop_docker"
     stop_docker
-    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
-    echo "Dump current docker ps"
-    docker ps
-    start_time=$(date +%s)
-    start_services
-    end_time=$(date +%s)
-    duration=$((end_time-start_time))
-    echo "Mega service start duration is $duration s"
-    validate_megaservice
+    echo "::endgroup::"
 
+    echo "::group::build_docker_images"
+    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
+
+    echo "::group::start_services"
+    start_services
+    echo "::endgroup::"
+
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
     stop_docker
-    echo y | docker system prune
+    echo "::endgroup::"
+
+    docker system prune -f
 
 }
 

DocIndexRetriever/tests/test_compose_milvus_on_xeon.sh

@@ -20,16 +20,15 @@ function build_docker_images() {
     if [ ! -d "GenAIComps" ] ; then
         git clone --single-branch --branch "${opea_branch:-"main"}" https://github.com/opea-project/GenAIComps.git
     fi
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
+
     service_list="dataprep embedding retriever reranking doc-index-retriever"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
-    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
-    docker pull quay.io/coreos/etcd:v3.5.5
-    docker pull minio/minio:RELEASE.2023-03-20T20-16-18Z
-    docker pull milvusdb/milvus:v2.4.6
     docker images && sleep 1s
-
-    echo "Docker images built!"
 }
 
 function start_services() {
@@ -111,19 +110,27 @@ function stop_docker() {
 
 function main() {
 
+    echo "::group::stop_docker"
     stop_docker
-    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
-    echo "Dump current docker ps"
-    docker ps
-    start_time=$(date +%s)
-    start_services
-    end_time=$(date +%s)
-    duration=$((end_time-start_time))
-    echo "Mega service start duration is $duration s"
-    validate_megaservice
+    echo "::endgroup::"
 
+    echo "::group::build_docker_images"
+    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
+
+    echo "::group::start_services"
+    start_services
+    echo "::endgroup::"
+
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
     stop_docker
-    echo y | docker system prune
+    echo "::endgroup::"
+
+    docker system prune -f
 
 }
 

DocIndexRetriever/tests/test_compose_on_gaudi.sh

@@ -21,14 +21,15 @@ function build_docker_images() {
     if [ ! -d "GenAIComps" ] ; then
         git clone --single-branch --branch "${opea_branch:-"main"}" https://github.com/opea-project/GenAIComps.git
     fi
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
 
     echo "Build all the images with --no-cache, check docker_image_build.log for details..."
     docker compose -f build.yaml build --no-cache > ${LOG_PATH}/docker_image_build.log
 
-    docker pull redis/redis-stack:7.2.0-v9
-    docker pull ghcr.io/huggingface/tei-gaudi:1.5.0
     docker images && sleep 1s
-    echo "Docker images built!"
 }
 
 function start_services() {
@@ -103,19 +104,27 @@ function stop_docker() {
 
 function main() {
 
+    echo "::group::stop_docker"
     stop_docker
-    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
-    echo "Dump current docker ps"
-    docker ps
-    start_time=$(date +%s)
-    start_services
-    end_time=$(date +%s)
-    duration=$((end_time-start_time))
-    echo "Mega service start duration is $duration s"
-    validate_megaservice
+    echo "::endgroup::"
 
+    echo "::group::build_docker_images"
+    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
+
+    echo "::group::start_services"
+    start_services
+    echo "::endgroup::"
+
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
     stop_docker
-    echo y | docker system prune
+    echo "::endgroup::"
+
+    docker system prune -f
 
 }
 

DocIndexRetriever/tests/test_compose_on_xeon.sh

@@ -21,14 +21,15 @@ function build_docker_images() {
     if [ ! -d "GenAIComps" ] ; then
         git clone --single-branch --branch "${opea_branch:-"main"}" https://github.com/opea-project/GenAIComps.git
     fi
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
+
     service_list="dataprep embedding retriever reranking doc-index-retriever"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
-    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
-    docker pull redis/redis-stack:7.2.0-v9
     docker images && sleep 1s
-
-    echo "Docker images built!"
 }
 
 function start_services() {
@@ -110,20 +111,27 @@ function stop_docker() {
 
 function main() {
 
+    echo "::group::stop_docker"
     stop_docker
+    echo "::endgroup::"
+
+    echo "::group::build_docker_images"
     if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
-    echo "Dump current docker ps"
-    docker ps
+    echo "::endgroup::"
 
-    start_time=$(date +%s)
+    echo "::group::start_services"
     start_services
-    end_time=$(date +%s)
-    duration=$((end_time-start_time))
-    echo "Mega service start duration is $duration s"
-    validate_megaservice
+    echo "::endgroup::"
 
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
     stop_docker
-    echo y | docker system prune
+    echo "::endgroup::"
+
+    docker system prune -f
 
 }
 

DocIndexRetriever/tests/test_compose_without_rerank_on_xeon.sh

@@ -21,6 +21,11 @@ function build_docker_images() {
     if [ ! -d "GenAIComps" ] ; then
         git clone --single-branch --branch "${opea_branch:-"main"}" https://github.com/opea-project/GenAIComps.git
     fi
+    pushd GenAIComps
+    echo "GenAIComps test commit is $(git rev-parse HEAD)"
+    docker build --no-cache -t ${REGISTRY}/comps-base:${TAG} --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
+    popd && sleep 1s
+
     service_list="dataprep embedding retriever doc-index-retriever"
     docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log
 
@@ -114,19 +119,27 @@ function stop_docker() {
 
 function main() {
 
+    echo "::group::stop_docker"
     stop_docker
-    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
-    echo "Dump current docker ps"
-    docker ps
-    start_time=$(date +%s)
-    start_services
-    end_time=$(date +%s)
-    duration=$((end_time-start_time))
-    echo "Mega service start duration is $duration s"
-    validate_megaservice
+    echo "::endgroup::"
 
+    echo "::group::build_docker_images"
+    if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi
+    echo "::endgroup::"
+
+    echo "::group::start_services"
+    start_services
+    echo "::endgroup::"
+
+    echo "::group::validate_megaservice"
+    validate_megaservice
+    echo "::endgroup::"
+
+    echo "::group::stop_docker"
     stop_docker
-    echo y | docker system prune
+    echo "::endgroup::"
+
+    docker system prune -f
 
 }
 

DocSum/docker_compose/intel/cpu/xeon/README.md

@@ -27,9 +27,9 @@ Clone the GenAIExample repository and access the ChatQnA Intel Xeon platform Doc
 
 ```bash
 git clone https://github.com/opea-project/GenAIExamples.git
-cd GenAIExamples/DocSum/docker_compose
+cd GenAIExamples/DocSum/docker_compose/intel
 source set_env.sh
-cd intel/cpu/xeon/
+cd cpu/xeon/
 ```
 
 NOTE: by default vLLM does "warmup" at start, to optimize its performance for the specified model and the underlying platform, which can take long time. For development (and e.g. autoscaling) it can be skipped with `export VLLM_SKIP_WARMUP=true`.
@@ -49,6 +49,7 @@ Some HuggingFace resources, such as some models, are only accessible if you have
 To deploy the DocSum services, execute the `docker compose up` command with the appropriate arguments. For a default deployment, execute:
 
 ```bash
+cd cpu/xeon/
 docker compose up -d
 ```
 

DocSum/docker_compose/intel/hpu/gaudi/README.md

@@ -29,9 +29,9 @@ Clone the GenAIExample repository and access the DocSum Intel® Gaudi® platform
 
 ```bash
 git clone https://github.com/opea-project/GenAIExamples.git
-cd GenAIExamples/DocSum/docker_compose
+cd GenAIExamples/DocSum/docker_compose/intel
 source set_env.sh
-cd intel/hpu/gaudi/
+cd hpu/gaudi/
 ```
 
 NOTE: by default vLLM does "warmup" at start, to optimize its performance for the specified model and the underlying platform, which can take long time. For development (and e.g. autoscaling) it can be skipped with `export VLLM_SKIP_WARMUP=true`.
@@ -51,6 +51,7 @@ Some HuggingFace resources, such as some models, are only accessible if you have
 To deploy the DocSum services, execute the `docker compose up` command with the appropriate arguments. For a default deployment, execute:
 
 ```bash
+cd hpu/gaudi/
 docker compose up -d
 ```
 

DocSum/tests/test_compose_on_gaudi.sh

@@ -16,7 +16,7 @@ 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
+source $WORKPATH/docker_compose/intel/set_env.sh
 
 export MODEL_CACHE=${model_cache:-"./data"}
 

DocSum/tests/test_compose_on_xeon.sh

@@ -17,7 +17,7 @@ echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
 export REGISTRY=${IMAGE_REPO}
 export TAG=${IMAGE_TAG}
 
-source $WORKPATH/docker_compose/set_env.sh
+source $WORKPATH/docker_compose/intel/set_env.sh
 export MODEL_CACHE=${model_cache:-"./data"}
 
 export MAX_INPUT_TOKENS=2048

DocSum/tests/test_compose_tgi_on_gaudi.sh

@@ -16,7 +16,7 @@ echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
 export REGISTRY=${IMAGE_REPO}
 export TAG=${IMAGE_TAG}
 
-source $WORKPATH/docker_compose/set_env.sh
+source $WORKPATH/docker_compose/intel/set_env.sh
 export MODEL_CACHE=${model_cache:-"./data"}
 
 export MAX_INPUT_TOKENS=2048

DocSum/tests/test_compose_tgi_on_xeon.sh

@@ -16,7 +16,7 @@ echo "TAG=IMAGE_TAG=${IMAGE_TAG}"
 export REGISTRY=${IMAGE_REPO}
 export TAG=${IMAGE_TAG}
 
-source $WORKPATH/docker_compose/set_env.sh
+source $WORKPATH/docker_compose/intel/set_env.sh
 export MODEL_CACHE=${model_cache:-"./data"}
 
 export MAX_INPUT_TOKENS=2048

EdgeCraftRAG/docker_compose/intel/gpu/arc/set_env.sh

@@ -5,3 +5,13 @@
 pushd "../../../../../" > /dev/null
 source .set_env.sh
 popd > /dev/null
+
+export MODEL_PATH=${MODEL_PATH}
+export DOC_PATH=${DOC_PATH}
+export UI_TMPFILE_PATH=${UI_TMPFILE_PATH}
+export HOST_IP=${HOST_IP}
+export LLM_MODEL=${LLM_MODEL}
+export HF_ENDPOINT=${HF_ENDPOINT}
+export vLLM_ENDPOINT=${vLLM_ENDPOINT}
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export no_proxy="localhost, 127.0.0.1, 192.168.1.1"

EdgeCraftRAG/tests/README.md

@@ -0,0 +1,21 @@
+# EdgeCraftRAG E2E test scripts
+
+## Set the required environment variable
+
+```bash
+export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token"
+```
+
+## Run test
+
+On Intel ARC with TGI:
+
+```bash
+bash test_compose_on_arc.sh
+```
+
+On Intel ARC with vLLM:
+
+```bash
+bash test_compose_vllm_on_arc.sh
+```

EdgeCraftRAG/tests/test_compose_on_arc.sh

@@ -46,18 +46,10 @@ function build_docker_images() {
 }
 
 function start_services() {
-    export MODEL_PATH=${MODEL_PATH}
-    export DOC_PATH=${DOC_PATH}
     export UI_UPLOAD_PATH=${UI_UPLOAD_PATH}
-    export HOST_IP=${HOST_IP}
-    export LLM_MODEL=${LLM_MODEL}
-    export HF_ENDPOINT=${HF_ENDPOINT}
-    export vLLM_ENDPOINT=${vLLM_ENDPOINT}
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export no_proxy="localhost, 127.0.0.1, 192.168.1.1"
 
     cd $WORKPATH/docker_compose/intel/gpu/arc
-
+    source set_env.sh
     # Start Docker Containers
     docker compose -f $COMPOSE_FILE up -d > ${LOG_PATH}/start_services_with_compose.log
     sleep 20

EdgeCraftRAG/tests/test_compose_vllm_on_arc.sh

@@ -53,17 +53,8 @@ function build_docker_images() {
 }
 
 function start_services() {
-    export MODEL_PATH=${MODEL_PATH}
-    export DOC_PATH=${DOC_PATH}
-    export UI_TMPFILE_PATH=${UI_TMPFILE_PATH}
-    export HOST_IP=${HOST_IP}
-    export LLM_MODEL=${LLM_MODEL}
-    export HF_ENDPOINT=${HF_ENDPOINT}
-    export vLLM_ENDPOINT=${vLLM_ENDPOINT}
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export no_proxy="localhost, 127.0.0.1, 192.168.1.1"
-
     cd $WORKPATH/docker_compose/intel/gpu/arc
+    source set_env.sh
 
     # Start Docker Containers
     docker compose -f $COMPOSE_FILE up -d > ${LOG_PATH}/start_services_with_compose.log

ProductivitySuite/docker_compose/intel/cpu/xeon/README.md

@@ -137,7 +137,6 @@ export BACKEND_SERVICE_ENDPOINT_DOCSUM="http://${host_ip}:8890/v1/docsum"
 export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
 export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/get"
 export CHAT_HISTORY_CREATE_ENDPOINT="http://${host_ip}:6012/v1/chathistory/create"
-export CHAT_HISTORY_CREATE_ENDPOINT="http://${host_ip}:6012/v1/chathistory/create"
 export CHAT_HISTORY_DELETE_ENDPOINT="http://${host_ip}:6012/v1/chathistory/delete"
 export CHAT_HISTORY_GET_ENDPOINT="http://${host_ip}:6012/v1/chathistory/get"
 export PROMPT_SERVICE_GET_ENDPOINT="http://${host_ip}:6018/v1/prompt/get"

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

@@ -18,7 +18,6 @@ export BACKEND_SERVICE_ENDPOINT_DOCSUM="http://${host_ip}:8890/v1/docsum"
 export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
 export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/get"
 export CHAT_HISTORY_CREATE_ENDPOINT="http://${host_ip}:6012/v1/chathistory/create"
-export CHAT_HISTORY_CREATE_ENDPOINT="http://${host_ip}:6012/v1/chathistory/create"
 export CHAT_HISTORY_DELETE_ENDPOINT="http://${host_ip}:6012/v1/chathistory/delete"
 export CHAT_HISTORY_GET_ENDPOINT="http://${host_ip}:6012/v1/chathistory/get"
 export PROMPT_SERVICE_GET_ENDPOINT="http://${host_ip}:6018/v1/prompt/get"

ProductivitySuite/tests/README.md

@@ -0,0 +1,15 @@
+# ProductivitySuite 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
+```

ProductivitySuite/tests/test_compose_on_xeon.sh

@@ -29,33 +29,12 @@ function build_docker_images() {
 
 function start_services() {
     cd $WORKPATH/docker_compose/intel/cpu/xeon/
-
-    export DB_NAME="opea"
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-    export LLM_MODEL_ID_CODEGEN="Intel/neural-chat-7b-v3-3"
-    export INDEX_NAME="rag-redis"
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export BACKEND_SERVICE_ENDPOINT_CHATQNA="http://${ip_address}:8888/v1/chatqna"
-    export DATAPREP_DELETE_FILE_ENDPOINT="http://${ip_address}:6007/v1/dataprep/delete"
-    export BACKEND_SERVICE_ENDPOINT_CODEGEN="http://${ip_address}:7778/v1/codegen"
-    export BACKEND_SERVICE_ENDPOINT_DOCSUM="http://${ip_address}:8890/v1/docsum"
-    export DATAPREP_SERVICE_ENDPOINT="http://${ip_address}:6007/v1/dataprep/ingest"
-    export DATAPREP_GET_FILE_ENDPOINT="http://${ip_address}:6007/v1/dataprep/get"
-    export CHAT_HISTORY_CREATE_ENDPOINT="http://${ip_address}:6012/v1/chathistory/create"
-    export CHAT_HISTORY_CREATE_ENDPOINT="http://${ip_address}:6012/v1/chathistory/create"
-    export CHAT_HISTORY_DELETE_ENDPOINT="http://${ip_address}:6012/v1/chathistory/delete"
-    export CHAT_HISTORY_GET_ENDPOINT="http://${ip_address}:6012/v1/chathistory/get"
-    export PROMPT_SERVICE_GET_ENDPOINT="http://${ip_address}:6018/v1/prompt/get"
-    export PROMPT_SERVICE_CREATE_ENDPOINT="http://${ip_address}:6018/v1/prompt/create"
-    export PROMPT_SERVICE_DELETE_ENDPOINT="http://${ip_address}:6018/v1/prompt/delete"
-    export KEYCLOAK_SERVICE_ENDPOINT="http://${ip_address}:8080"
-    export DocSum_COMPONENT_NAME="OpeaDocSumTgi"
     export host_ip=${ip_address}
     export LOGFLAG=True
     export no_proxy="$no_proxy,tgi_service_codegen,llm_codegen,tei-embedding-service,tei-reranking-service,chatqna-xeon-backend-server,retriever,tgi-service,redis-vector-db,whisper,llm-docsum-tgi,docsum-xeon-backend-server,mongo,codegen"
 
+    source set_env.sh
+
     # Start Docker Containers
     docker compose up -d > ${LOG_PATH}/start_services_with_compose.log
     sleep 30s

SearchQnA/README.md

@@ -30,66 +30,38 @@ The architecture of the SearchQnA Application is illustrated below:
 The SearchQnA example is implemented using the component-level microservices defined in [GenAIComps](https://github.com/opea-project/GenAIComps). The flow chart below shows the information flow between different microservices for this example.
 
 ```mermaid
----
-config:
-  flowchart:
-    nodeSpacing: 400
-    rankSpacing: 100
-    curve: linear
-  themeVariables:
-    fontSize: 50px
----
+%% Orange are microservices from third parties that are 'wrapped' as OPEA components.
 flowchart LR
-    %% Colors %%
-    classDef blue fill:#ADD8E6,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5
-    classDef orange fill:#FBAA60,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5
-    classDef orchid fill:#C26DBC,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5
-    classDef invisible fill:transparent,stroke:transparent;
-    style SearchQnA-MegaService stroke:#000000
+    User["User"] --> Nginx["Nginx<br>searchqna-nginx-server"]
+    Nginx --> UI["UI<br>searchqna-ui-server"] & Gateway & User
+    UI --> Nginx
+    Gateway --> Nginx & Embedding
+    Embedding --> Retriever
+    Retriever --> Reranker
+    Reranker --> LLM
+    LLM --> Gateway
+    LLM <-.-> TGI_Service["LLM<br>tgi-service"]
+    Embedding <-.-> TEI_Embedding["TEI Embedding<br>tei-embedding-server"]
+    Reranker <-.-> TEI_Reranker["TEI Reranker<br>tei-reranking-server"]
 
-    %% Subgraphs %%
-    subgraph SearchQnA-MegaService["SearchQnA MegaService "]
-        direction LR
-        EM([Embedding MicroService]):::blue
-        RET([Web Retrieval MicroService]):::blue
-        RER([Rerank MicroService]):::blue
-        LLM([LLM MicroService]):::blue
-    end
-    subgraph UserInterface[" User Interface "]
-        direction LR
-        a([User Input Query]):::orchid
-        UI([UI server<br>]):::orchid
-    end
-
-
-
-    TEI_RER{{Reranking service<br>}}
-    TEI_EM{{Embedding service <br>}}
-    VDB{{Vector DB<br><br>}}
-    R_RET{{Web Retriever service <br>}}
-    LLM_gen{{LLM Service <br>}}
-    GW([SearchQnA GateWay<br>]):::orange
-
-    %% Questions interaction
-    direction LR
-    a[User Input Query] --> UI
-    UI --> GW
-    GW <==> SearchQnA-MegaService
-    EM ==> RET
-    RET ==> RER
-    RER ==> LLM
-
-    %% Embedding service flow
-    direction LR
-    EM <-.-> TEI_EM
-    RET <-.-> R_RET
-    RER <-.-> TEI_RER
-    LLM <-.-> LLM_gen
+     TEI_Embedding:::ext
+     TEI_Reranker:::ext
+     TGI_Service:::ext
 
+ subgraph MegaService["MegaService"]
+        LLM["LLM<br>llm-textgen-server"]
+        Reranker["Reranker<br>reranking-tei-server"]
+        Retriever["Retriever<br>web-retriever-server"]
+        Embedding["Embedding<br>embedding-server"]
+  end
+ subgraph Backend["searchqna-backend-server"]
     direction TB
-    %% Vector DB interaction
-    R_RET <-.-> VDB
-
+        MegaService
+        Gateway["Backend Endpoint"]
+ end
+    classDef default fill:#fff,stroke:#000,color:#000
+    classDef ext fill:#f9cb9c,stroke:#000,color:#000
+    style MegaService margin-top:20px,margin-bottom:20px
 ```
 
 This SearchQnA use case performs Search-augmented Question Answering across multiple platforms. Currently, we provide the example for Intel® Gaudi® 2 and Intel® Xeon® Scalable Processors, and we invite contributions from other hardware vendors to expand OPEA ecosystem.
@@ -98,8 +70,8 @@ This SearchQnA use case performs Search-augmented Question Answering across mult
 
 The table below lists the available deployment options and their implementation details for different hardware platforms.
 
-| Category               | Deployment Option      | Description                                                    |
-| ---------------------- | ---------------------- | -------------------------------------------------------------- |
-| On-premise Deployments | Docker Compose (Xeon)  | [DocSum deployment on Xeon](./docker_compose/intel/cpu/xeon)   |
-|                        | Docker Compose (Gaudi) | [DocSum deployment on Gaudi](./docker_compose/intel/hpu/gaudi) |
-|                        | Docker Compose (ROCm)  | [DocSum deployment on AMD ROCm](./docker_compose/amd/gpu/rocm) |
+| Category               | Deployment Option      | Description                                                                 |
+| ---------------------- | ---------------------- | --------------------------------------------------------------------------- |
+| On-premise Deployments | Docker Compose (Xeon)  | [SearchQnA deployment on Xeon](./docker_compose/intel/cpu/xeon/README.md)   |
+|                        | Docker Compose (Gaudi) | [SearchQnA deployment on Gaudi](./docker_compose/intel/hpu/gaudi/README.md) |
+|                        | Docker Compose (ROCm)  | [SearchQnA deployment on AMD ROCm](./docker_compose/amd/gpu/rocm/README.md) |

SearchQnA/docker_compose/amd/gpu/rocm/compose.yaml

@@ -170,7 +170,25 @@ services:
       no_proxy: ${no_proxy}
       https_proxy: ${https_proxy}
       http_proxy: ${http_proxy}
-      BACKEND_BASE_URL: ${SEARCH_BACKEND_SERVICE_ENDPOINT}
+    ipc: host
+    restart: always
+  search-nginx-server:
+    image: ${REGISTRY:-opea}/nginx:${TAG:-latest}
+    container_name: search-nginx-server
+    depends_on:
+      - search-backend-server
+      - search-ui-server
+    ports:
+      - "${NGINX_PORT:-80}:80"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - FRONTEND_SERVICE_IP=search-ui-server
+      - FRONTEND_SERVICE_PORT=5173
+      - BACKEND_SERVICE_NAME=search
+      - BACKEND_SERVICE_IP=search-backend-server
+      - BACKEND_SERVICE_PORT=8888
     ipc: host
     restart: always
 

SearchQnA/docker_compose/amd/gpu/rocm/compose_vllm.yaml

@@ -176,10 +176,27 @@ services:
       no_proxy: ${no_proxy}
       https_proxy: ${https_proxy}
       http_proxy: ${http_proxy}
-      BACKEND_BASE_URL: ${SEARCH_BACKEND_SERVICE_ENDPOINT}
     ipc: host
     restart: always
-
+  search-nginx-server:
+    image: ${REGISTRY:-opea}/nginx:${TAG:-latest}
+    container_name: search-nginx-server
+    depends_on:
+      - search-backend-server
+      - search-ui-server
+    ports:
+      - "${NGINX_PORT:-80}:80"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - FRONTEND_SERVICE_IP=search-ui-server
+      - FRONTEND_SERVICE_PORT=5173
+      - BACKEND_SERVICE_NAME=search
+      - BACKEND_SERVICE_IP=search-backend-server
+      - BACKEND_SERVICE_PORT=8888
+    ipc: host
+    restart: always
 networks:
   default:
     driver: bridge

SearchQnA/docker_compose/amd/gpu/rocm/set_env.sh

@@ -2,8 +2,8 @@
 
 # Copyright (C) 2025 Advanced Micro Devices, Inc.
 
-export HOST_IP=''
-export EXTERNAL_HOST_IP=''
+export HOST_IP=${ip_address}
+export EXTERNAL_HOST_IP=${ip_address}
 
 export SEARCH_EMBEDDING_MODEL_ID='BAAI/bge-base-en-v1.5'
 export SEARCH_GOOGLE_API_KEY=${GOOGLE_API_KEY}
@@ -12,9 +12,9 @@ export SEARCH_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 export SEARCH_LLM_MODEL_ID='Intel/neural-chat-7b-v3-3'
 export SEARCH_RERANK_MODEL_ID='BAAI/bge-reranker-base'
 
-export SEARCH_BACKEND_SERVICE_PORT=18142
+export SEARCH_BACKEND_SERVICE_PORT=3008
 export SEARCH_EMBEDDING_SERVICE_PORT=3002
-export SEARCH_FRONTEND_SERVICE_PORT=18143
+export SEARCH_FRONTEND_SERVICE_PORT=5173
 export SEARCH_LLM_SERVICE_PORT=3007
 export SEARCH_RERANK_SERVICE_PORT=3005
 export SEARCH_TEI_EMBEDDING_PORT=3001

SearchQnA/docker_compose/amd/gpu/rocm/set_env_vllm.sh

@@ -2,8 +2,8 @@
 
 # Copyright (C) 2025 Advanced Micro Devices, Inc.
 
-export HOST_IP=''
-export EXTERNAL_HOST_IP=''
+export HOST_IP=${ip_address}
+export EXTERNAL_HOST_IP=${ip_address}
 
 export SEARCH_EMBEDDING_MODEL_ID='BAAI/bge-base-en-v1.5'
 export SEARCH_GOOGLE_API_KEY=${GOOGLE_API_KEY}
@@ -12,11 +12,11 @@ export SEARCH_HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 export SEARCH_LLM_MODEL_ID='Intel/neural-chat-7b-v3-3'
 export SEARCH_RERANK_MODEL_ID='BAAI/bge-reranker-base'
 
-export MODEL_PATH="./data"
+export MODEL_CACHE="./data"
 
-export SEARCH_BACKEND_SERVICE_PORT=18142
+export SEARCH_BACKEND_SERVICE_PORT=3008
 export SEARCH_EMBEDDING_SERVICE_PORT=3002
-export SEARCH_FRONTEND_SERVICE_PORT=18143
+export SEARCH_FRONTEND_SERVICE_PORT=5173
 export SEARCH_LLM_SERVICE_PORT=3007
 export SEARCH_RERANK_SERVICE_PORT=3005
 export SEARCH_TEI_EMBEDDING_PORT=3001

SearchQnA/docker_compose/intel/cpu/xeon/compose.yaml

@@ -168,10 +168,27 @@ services:
       - no_proxy=${no_proxy}
       - https_proxy=${https_proxy}
       - http_proxy=${http_proxy}
-      - BACKEND_BASE_URL=${BACKEND_SERVICE_ENDPOINT}
     ipc: host
     restart: always
-
+  searchqna-xeon-nginx-server:
+    image: ${REGISTRY:-opea}/nginx:${TAG:-latest}
+    container_name: searchqna-xeon-nginx-server
+    depends_on:
+      - searchqna-xeon-backend-server
+      - searchqna-xeon-ui-server
+    ports:
+      - "${NGINX_PORT:-80}:80"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - FRONTEND_SERVICE_IP=searchqna-xeon-ui-server
+      - FRONTEND_SERVICE_PORT=5173
+      - BACKEND_SERVICE_NAME=searchqna
+      - BACKEND_SERVICE_IP=searchqna-xeon-backend-server
+      - BACKEND_SERVICE_PORT=8888
+    ipc: host
+    restart: always
 
 networks:
   default:

SearchQnA/docker_compose/intel/hpu/gaudi/compose.yaml

@@ -187,7 +187,25 @@ services:
       - no_proxy=${no_proxy}
       - https_proxy=${https_proxy}
       - http_proxy=${http_proxy}
-      - BACKEND_BASE_URL=${BACKEND_SERVICE_ENDPOINT}
+    ipc: host
+    restart: always
+  searchqna-gaudi-nginx-server:
+    image: ${REGISTRY:-opea}/nginx:${TAG:-latest}
+    container_name: searchqna-gaudi-nginx-server
+    depends_on:
+      - searchqna-gaudi-backend-server
+      - searchqna-gaudi-ui-server
+    ports:
+      - "${NGINX_PORT:-80}:80"
+    environment:
+      - no_proxy=${no_proxy}
+      - https_proxy=${https_proxy}
+      - http_proxy=${http_proxy}
+      - FRONTEND_SERVICE_IP=searchqna-gaudi-ui-server
+      - FRONTEND_SERVICE_PORT=5173
+      - BACKEND_SERVICE_NAME=searchqna
+      - BACKEND_SERVICE_IP=searchqna-gaudi-backend-server
+      - BACKEND_SERVICE_PORT=8888
     ipc: host
     restart: always
 

SearchQnA/docker_compose/intel/set_env.sh

@@ -2,11 +2,13 @@
 
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
-pushd "../../" > /dev/null
+pushd "../../../" > /dev/null
 source .set_env.sh
 popd > /dev/null
 
-
+export GOOGLE_CSE_ID=$GOOGLE_CSE_ID
+export GOOGLE_API_KEY=$GOOGLE_API_KEY
+export HUGGINGFACEHUB_API_TOKEN=$HUGGINGFACEHUB_API_TOKEN
 export EMBEDDING_MODEL_ID=BAAI/bge-base-en-v1.5
 export TEI_EMBEDDING_ENDPOINT=http://${host_ip}:3001
 export RERANK_MODEL_ID=BAAI/bge-reranker-base

SearchQnA/docker_image_build/build.yaml

@@ -46,3 +46,9 @@ services:
       context: GenAIComps
       dockerfile: comps/third_parties/vllm/src/Dockerfile.amd_gpu
     image: ${REGISTRY:-opea}/vllm-rocm:${TAG:-latest}
+  nginx:
+    build:
+      context: GenAIComps
+      dockerfile: comps/third_parties/nginx/src/Dockerfile
+    extends: searchqna
+    image: ${REGISTRY:-opea}/nginx:${TAG:-latest}

SearchQnA/tests/README.md

@@ -0,0 +1,33 @@
+# SearchQnA 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
+```
+
+On AMD ROCm with vLLM:
+
+```bash
+bash test_compose_vllm_on_rocm.sh
+```