[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

.github/code_spell_ignore.txt

@@ -1,3 +1,2 @@
 ModelIn
 modelin
-pressEnter

.github/workflows/_build_comps_base_image.yml

@@ -1,65 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-name: Build Comps Base Image
-permissions: read-all
-on:
-  workflow_call:
-    inputs:
-      node:
-        required: true
-        type: string
-      build:
-        default: true
-        required: false
-        type: boolean
-      tag:
-        default: "latest"
-        required: false
-        type: string
-      opea_branch:
-        default: "main"
-        required: false
-        type: string
-      inject_commit:
-        default: false
-        required: false
-        type: boolean
-
-jobs:
-  pre-build-image-check:
-    runs-on: ubuntu-latest
-    outputs:
-      should_skip: ${{ steps.check-skip.outputs.should_skip }}
-    steps:
-      - name: Check if job should be skipped
-        id: check-skip
-        run: |
-          should_skip=false
-          if [[ "${{ inputs.node }}" == "gaudi3" || "${{ inputs.node }}" == "rocm" || "${{ inputs.node }}" == "arc" ]]; then
-            should_skip=true
-          fi
-          echo "should_skip=$should_skip"
-          echo "should_skip=$should_skip" >> $GITHUB_OUTPUT
-
-  build-images:
-    needs: [ pre-build-image-check ]
-    if: ${{ needs.pre-build-image-check.outputs.should_skip == 'false' && fromJSON(inputs.build) }}
-    runs-on: "docker-build-${{ inputs.node }}"
-    steps:
-      - name: Clean Up Working Directory
-        run: sudo rm -rf ${{github.workspace}}/*
-
-      - name: Clone Required Repo
-        run: |
-          git clone --depth 1 --branch ${{ inputs.opea_branch }} https://github.com/opea-project/GenAIComps.git
-          cd GenAIComps && git rev-parse HEAD && cd ../ && ls -l
-
-      - name: Build Image
-        uses: opea-project/validation/actions/image-build@main
-        with:
-          work_dir: ${{ github.workspace }}/GenAIComps
-          docker_compose_path: ${{ github.workspace }}/GenAIComps/.github/workflows/docker/compose/base-compose.yaml
-          registry: ${OPEA_IMAGE_REPO}opea
-          inject_commit: ${{ inputs.inject_commit }}
-          tag: ${{ inputs.tag }}

.github/workflows/_build_image.yml

@@ -1,103 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-name: Build Images
-permissions: read-all
-on:
-  workflow_call:
-    inputs:
-      node:
-        required: true
-        type: string
-      build:
-        default: true
-        required: false
-        type: boolean
-      example:
-        required: true
-        type: string
-      services:
-        default: ""
-        required: false
-        type: string
-      tag:
-        default: "latest"
-        required: false
-        type: string
-      opea_branch:
-        default: "main"
-        required: false
-        type: string
-      inject_commit:
-        default: false
-        required: false
-        type: boolean
-
-jobs:
-  pre-build-image-check:
-    runs-on: ubuntu-latest
-    outputs:
-      should_skip: ${{ steps.check-skip.outputs.should_skip }}
-    steps:
-      - name: Check if job should be skipped
-        id: check-skip
-        run: |
-          should_skip=false
-          if [[ "${{ inputs.node }}" == "gaudi3" || "${{ inputs.node }}" == "rocm" || "${{ inputs.node }}" == "arc" ]]; then
-            should_skip=true
-          fi
-          echo "should_skip=$should_skip"
-          echo "should_skip=$should_skip" >> $GITHUB_OUTPUT
-
-  build-images:
-    needs: [ pre-build-image-check ]
-    if: ${{ needs.pre-build-image-check.outputs.should_skip == 'false' && fromJSON(inputs.build) }}
-    runs-on: "docker-build-${{ inputs.node }}"
-    steps:
-      - name: Clean Up Working Directory
-        run: sudo rm -rf ${{github.workspace}}/*
-
-      - name: Get Checkout Ref
-        run: |
-          if [ "${{ github.event_name }}" == "pull_request" ] || [ "${{ github.event_name }}" == "pull_request_target" ]; then
-            echo "CHECKOUT_REF=refs/pull/${{ github.event.number }}/merge" >> $GITHUB_ENV
-          else
-            echo "CHECKOUT_REF=${{ github.ref }}" >> $GITHUB_ENV
-          fi
-
-      - name: Checkout out GenAIExamples
-        uses: actions/checkout@v4
-        with:
-          ref: ${{ env.CHECKOUT_REF }}
-          fetch-depth: 0
-
-      - name: Clone Required Repo
-        run: |
-          cd ${{ github.workspace }}/${{ inputs.example }}/docker_image_build
-          docker_compose_path=${{ github.workspace }}/${{ inputs.example }}/docker_image_build/build.yaml
-          if [[ $(grep -c "vllm:" ${docker_compose_path}) != 0 ]]; then
-              git clone https://github.com/vllm-project/vllm.git && cd vllm
-              # Get the latest tag
-              VLLM_VER=$(git describe --tags "$(git rev-list --tags --max-count=1)")
-              echo "Check out vLLM tag ${VLLM_VER}"
-              git checkout ${VLLM_VER} &> /dev/null && cd ../
-          fi
-          if [[ $(grep -c "vllm-gaudi:" ${docker_compose_path}) != 0 ]]; then
-              git clone https://github.com/HabanaAI/vllm-fork.git && cd vllm-fork
-              # Get the latest tag
-              VLLM_VER=$(git describe --tags "$(git rev-list --tags --max-count=1)")
-              echo "Check out vLLM tag ${VLLM_VER}"
-              git checkout ${VLLM_VER} &> /dev/null && cd ../
-          fi
-          git clone --depth 1 --branch ${{ inputs.opea_branch }} https://github.com/opea-project/GenAIComps.git
-          cd GenAIComps && git rev-parse HEAD && cd ../
-
-      - name: Build Image
-        uses: opea-project/validation/actions/image-build@main
-        with:
-          work_dir: ${{ github.workspace }}/${{ inputs.example }}/docker_image_build
-          docker_compose_path: ${{ github.workspace }}/${{ inputs.example }}/docker_image_build/build.yaml
-          service_list: ${{ inputs.services }}
-          registry: ${OPEA_IMAGE_REPO}opea
-          inject_commit: ${{ inputs.inject_commit }}
-          tag: ${{ inputs.tag }}

.github/workflows/_example-workflow.yml

@@ -43,39 +43,68 @@ on:
       inject_commit:
         default: false
         required: false
-        type: boolean
-      use_model_cache:
-        default: false
-        required: false
-        type: boolean
+        type: string
 
 jobs:
 ####################################################################################################
 # Image Build
 ####################################################################################################
   build-images:
-    uses: ./.github/workflows/_build_image.yml
-    with:
-      node: ${{ inputs.node }}
-      build: ${{ fromJSON(inputs.build) }}
-      example: ${{ inputs.example }}
-      services: ${{ inputs.services }}
-      tag: ${{ inputs.tag }}
-      opea_branch: ${{ inputs.opea_branch }}
-      inject_commit: ${{ inputs.inject_commit }}
+    runs-on: "docker-build-${{ inputs.node }}"
+    steps:
+      - name: Clean Up Working Directory
+        run: sudo rm -rf ${{github.workspace}}/*
+
+      - name: Get Checkout Ref
+        run: |
+          if [ "${{ github.event_name }}" == "pull_request" ] || [ "${{ github.event_name }}" == "pull_request_target" ]; then
+            echo "CHECKOUT_REF=refs/pull/${{ github.event.number }}/merge" >> $GITHUB_ENV
+          else
+            echo "CHECKOUT_REF=${{ github.ref }}" >> $GITHUB_ENV
+          fi
+
+      - name: Checkout out GenAIExamples
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ env.CHECKOUT_REF }}
+          fetch-depth: 0
+
+      - name: Clone Required Repo
+        run: |
+          cd ${{ github.workspace }}/${{ inputs.example }}/docker_image_build
+          docker_compose_path=${{ github.workspace }}/${{ inputs.example }}/docker_image_build/build.yaml
+          if [[ $(grep -c "vllm:" ${docker_compose_path}) != 0 ]]; then
+              git clone --depth 1 https://github.com/vllm-project/vllm.git
+              cd vllm && git rev-parse HEAD && cd ../
+          fi
+          if [[ $(grep -c "vllm-gaudi:" ${docker_compose_path}) != 0 ]]; then
+               git clone --depth 1 --branch v0.6.4.post2+Gaudi-1.19.0 https://github.com/HabanaAI/vllm-fork.git
+          fi
+          git clone --depth 1 --branch ${{ inputs.opea_branch }} https://github.com/opea-project/GenAIComps.git
+          cd GenAIComps && git rev-parse HEAD && cd ../
+
+      - name: Build Image
+        if: ${{ fromJSON(inputs.build) }}
+        uses: opea-project/validation/actions/image-build@main
+        with:
+          work_dir: ${{ github.workspace }}/${{ inputs.example }}/docker_image_build
+          docker_compose_path: ${{ github.workspace }}/${{ inputs.example }}/docker_image_build/build.yaml
+          service_list: ${{ inputs.services }}
+          registry: ${OPEA_IMAGE_REPO}opea
+          inject_commit: ${{ inputs.inject_commit }}
+          tag: ${{ inputs.tag }}
 
 ####################################################################################################
 # Docker Compose Test
 ####################################################################################################
   test-example-compose:
     needs: [build-images]
-    if: ${{ inputs.test_compose }}
+    if: ${{ fromJSON(inputs.test_compose) }}
     uses: ./.github/workflows/_run-docker-compose.yml
     with:
       tag: ${{ inputs.tag }}
       example: ${{ inputs.example }}
       hardware: ${{ inputs.node }}
-      use_model_cache: ${{ inputs.use_model_cache }}
     secrets: inherit
 
 
@@ -97,7 +126,7 @@ jobs:
 ####################################################################################################
   test-gmc-pipeline:
     needs: [build-images]
-    if: false # ${{ fromJSON(inputs.test_gmc) }}
+    if: ${{ fromJSON(inputs.test_gmc) }}
     uses: ./.github/workflows/_gmc-e2e.yml
     with:
       example: ${{ inputs.example }}

.github/workflows/_helm-e2e.yml

@@ -97,7 +97,6 @@ jobs:
 
   helm-test:
     needs: [get-test-case]
-    if: ${{ needs.get-test-case.outputs.value_files != '[]' }}
     strategy:
       matrix:
         value_file: ${{ fromJSON(needs.get-test-case.outputs.value_files) }}
@@ -134,7 +133,7 @@ jobs:
           CHART_NAME="${example,,}"  # CodeGen
           echo "CHART_NAME=$CHART_NAME" >> $GITHUB_ENV
           echo "RELEASE_NAME=${CHART_NAME}$(date +%Y%m%d%H%M%S)" >> $GITHUB_ENV
-          echo "NAMESPACE=${CHART_NAME}-$(head -c 4 /dev/urandom | xxd -p)" >> $GITHUB_ENV
+          echo "NAMESPACE=${CHART_NAME}-$(date +%Y%m%d%H%M%S)" >> $GITHUB_ENV
           echo "ROLLOUT_TIMEOUT_SECONDS=600s" >> $GITHUB_ENV
           echo "TEST_TIMEOUT_SECONDS=600s" >> $GITHUB_ENV
           echo "KUBECTL_TIMEOUT_SECONDS=60s" >> $GITHUB_ENV
@@ -173,7 +172,7 @@ jobs:
             $RELEASE_NAME \
             oci://ghcr.io/opea-project/charts/${CHART_NAME} \
             --set global.HUGGINGFACEHUB_API_TOKEN=${HFTOKEN} \
-            --set global.modelUseHostPath=/data2/hf_model \
+            --set global.modelUseHostPath=/home/sdp/.cache/huggingface/hub \
             --set GOOGLE_API_KEY=${{ env.GOOGLE_API_KEY}} \
             --set GOOGLE_CSE_ID=${{ env.GOOGLE_CSE_ID}} \
             --set web-retriever.GOOGLE_API_KEY=${{ env.GOOGLE_API_KEY}} \

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

@@ -28,10 +28,6 @@ on:
         required: false
         type: string
         default: ""
-      use_model_cache:
-        required: false
-        type: boolean
-        default: false
 jobs:
   get-test-case:
     runs-on: ubuntu-latest
@@ -64,14 +60,9 @@ jobs:
           cd ${{ github.workspace }}/${{ inputs.example }}/tests
           run_test_cases=""
 
-          if [ "${{ inputs.hardware }}" == "gaudi2" ] || [ "${{ inputs.hardware }}" == "gaudi3" ]; then
-            hardware="gaudi"
-          else
-            hardware="${{ inputs.hardware }}"
-          fi
-          default_test_case=$(find . -type f -name "test_compose_on_$hardware.sh" | cut -d/ -f2)
+          default_test_case=$(find . -type f -name "test_compose_on_${{ inputs.hardware }}.sh" | cut -d/ -f2)
           if [ "$default_test_case" ]; then run_test_cases="$default_test_case"; fi
-          other_test_cases=$(find . -type f -name "test_compose_*_on_$hardware.sh" | cut -d/ -f2)
+          other_test_cases=$(find . -type f -name "test_compose_*_on_${{ inputs.hardware }}.sh" | cut -d/ -f2)
           echo "default_test_case=$default_test_case"
           echo "other_test_cases=$other_test_cases"
 
@@ -94,17 +85,12 @@ jobs:
               fi
           done
 
-          if [ -z "$run_test_cases" ] && [[ $(printf '%s\n' "${changed_files[@]}" | grep ${{ inputs.example }} | grep /tests/) ]]; then
-              run_test_cases=$other_test_cases
-          fi
-
           test_cases=$(echo $run_test_cases | tr ' ' '\n' | sort -u | jq -R '.' | jq -sc '.')
           echo "test_cases=$test_cases"
           echo "test_cases=$test_cases" >> $GITHUB_OUTPUT
 
   compose-test:
     needs: [get-test-case]
-    if: ${{ needs.get-test-case.outputs.test_cases != '[""]' }}
     strategy:
       matrix:
         test_case: ${{ fromJSON(needs.get-test-case.outputs.test_cases) }}
@@ -115,11 +101,6 @@ jobs:
       - name: Clean up Working Directory
         run: |
           sudo rm -rf ${{github.workspace}}/* || true
-
-          # clean up containers use ports
-          cid=$(docker ps --format '{{.Names}} : {{.Ports}}' | grep -v ' : $' | grep -v 5000 | awk -F' : ' '{print $1}')
-          if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi
-
           docker system prune -f
           docker rmi $(docker images --filter reference="*/*/*:latest" -q) || true
           docker rmi $(docker images --filter reference="*/*:ci" -q) || true
@@ -145,7 +126,6 @@ jobs:
         shell: bash
         env:
           HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
-          HF_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
           GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
           GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
           PINECONE_KEY: ${{ secrets.PINECONE_KEY }}
@@ -158,19 +138,10 @@ jobs:
           example: ${{ inputs.example }}
           hardware: ${{ inputs.hardware }}
           test_case: ${{ matrix.test_case }}
-          use_model_cache: ${{ inputs.use_model_cache }}
         run: |
           cd ${{ github.workspace }}/$example/tests
           if [[ "$IMAGE_REPO" == "" ]]; then export IMAGE_REPO="${OPEA_IMAGE_REPO}opea"; fi
-          if [[ "$use_model_cache" == "true" ]]; then
-            if [ -d "/data2/hf_model" ]; then
-              export model_cache="/data2/hf_model"
-            else
-              echo "Model cache directory /data2/hf_model does not exist"
-              export model_cache="~/.cache/huggingface/hub"
-            fi
-          fi
-          if [ -f "${test_case}" ]; then timeout 60m bash "${test_case}"; else echo "Test script {${test_case}} not found, skip test!"; fi
+          if [ -f ${test_case} ]; then timeout 30m bash ${test_case}; else echo "Test script {${test_case}} not found, skip test!"; fi
 
       - name: Clean up container after test
         shell: bash
@@ -180,11 +151,6 @@ jobs:
           export test_case=${{ matrix.test_case }}
           export hardware=${{ inputs.hardware }}
           bash ${{ github.workspace }}/.github/workflows/scripts/docker_compose_clean_up.sh "containers"
-
-          # clean up containers use ports
-          cid=$(docker ps --format '{{.Names}} : {{.Ports}}' | grep -v ' : $' | grep -v 5000 | awk -F' : ' '{print $1}')
-          if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi
-
           docker system prune -f
           docker rmi $(docker images --filter reference="*:5000/*/*" -q) || true
 

.github/workflows/daily_check_issue_and_pr.yml

@@ -1,28 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-name: Check stale issue and pr
-
-on:
-  schedule:
-    - cron: "30 22 * * *"
-
-jobs:
-  close-issues:
-    runs-on: ubuntu-latest
-    permissions:
-      issues: write
-      pull-requests: write
-    steps:
-      - uses: actions/stale@v9
-        with:
-          days-before-issue-stale: 30
-          days-before-pr-stale: 30
-          days-before-issue-close: 7
-          days-before-pr-close: 7
-          stale-issue-message: "This issue is stale because it has been open 30 days with no activity. Remove stale label or comment or this will be closed in 7 days."
-          stale-pr-message: "This PR is stale because it has been open 30 days with no activity. Remove stale label or comment or this will be closed in 7 days."
-          close-issue-message: "This issue was closed because it has been stalled for 7 days with no activity."
-          close-pr-message: "This PR was closed because it has been stalled for 7 days with no activity."
-          repo-token: ${{ secrets.ACTION_TOKEN }}
-          start-date: "2025-03-01T00:00:00Z"

.github/workflows/dockerhub-description.yml

@@ -1,984 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-name: Update Docker Hub Description
-on:
-  schedule:
-    - cron: "0 0 * * 0"
-  workflow_dispatch:
-
-jobs:
-  dockerHubDescription:
-    runs-on: ubuntu-latest
-    steps:
-    - name: Checkout current repository
-      uses: actions/checkout@v4
-
-    - name: Description for audioqna
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/audioqna
-        short-description: "The docker image served as an audioqna gateway and using language modeling to generate answers to user queries by converting audio input to text, and then using text-to-speech (TTS) to convert those answers back to speech for interaction."
-        readme-filepath: AudioQnA/README.md
-        enable-url-completion: true
-
-    - name: Description for audioqna-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/audioqna-ui
-        short-description: "The docker image acted as the audioqna UI entry for enabling seamless interaction with users"
-        readme-filepath: AudioQnA/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for audioqna-multilang
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/audioqna-multilang
-        short-description: "The docker image served as an audioqna gateway and using language modeling to generate answers to user queries by converting multilingual audio input to text, and then use multilingual text-to-speech (TTS) to convert those answers back to speech for interaction."
-        readme-filepath: AudioQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for avatarchatbot
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/avatarchatbot
-        short-description: "The docker image served as a avatarchatbot gateway and interacted with users by understanding their questions and providing relevant answers."
-        readme-filepath: AvatarChatbot/README.md
-        enable-url-completion: false
-
-    - name: Description for chatqna
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/chatqna
-        short-description: "The docker image served as a chatqna gateway and interacted with users by understanding their questions and providing relevant answers."
-        readme-filepath: ChatQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for chatqna-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/chatqna-ui
-        short-description: "The docker image acted as the chatqna UI entry for facilitating interaction with users for question answering"
-        readme-filepath: ChatQnA/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for chatqna-conversation-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/chatqna-conversation-ui
-        short-description: "The purpose of the docker image is to provide a user interface for chat-based Q&A using React. It allows for interaction with users and supports continuing conversations with a history that is stored in the browser's local storage."
-        readme-filepath: ChatQnA/ui/react/README.md
-        enable-url-completion: false
-
-    - name: Description for codegen
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/codegen
-        short-description: "The docker image served as the codegen gateway to provide service of the automatic creation of source code from a higher-level representation"
-        readme-filepath: CodeGen/README.md
-        enable-url-completion: false
-
-    - name: Description for codegen-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/codegen-ui
-        short-description: "The docker image acted as the codegen UI entry for facilitating interaction with users for automatically generating code from user's description"
-        readme-filepath: CodeGen/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for codegen-react-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/codegen-react-ui
-        short-description: "The purpose of the docker image is to provide a user interface for Codegen using React. It allows generating the appropriate code based on the current user input."
-        readme-filepath: CodeGen/ui/react/README.md
-        enable-url-completion: false
-
-    - name: Description for codetrans
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/codetrans
-        short-description: "The docker image served as a codetrans gateway to provide service of converting source code written in one programming language into an equivalent version in another programming language"
-        readme-filepath: CodeTrans/README.md
-        enable-url-completion: false
-
-    - name: Description for codetrans-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/codetrans-ui
-        short-description: "The docker image acted as the codetrans UI entry for facilitating interaction with users for translating one programming language to another one"
-        readme-filepath:  CodeTrans/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for doc-index-retriever
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/doc-index-retriever
-        short-description: "The docker image acts as a DocRetriever gateway, It uses different methods to match user queries with a set of free text records."
-        readme-filepath: DocIndexRetriever/README.md
-        enable-url-completion: false
-
-    - name: Description for docsum
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/docsum
-        short-description: "The docker image served as a docsum gateway to provide service of capturing the main points and essential details of the original text"
-        readme-filepath: Docsum/README.md
-        enable-url-completion: false
-
-    - name: Description for docsum-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/docsum-ui
-        short-description: "The docker image acted as the docsum UI entry for facilitating interaction with users for document summarization"
-        readme-filepath: Docsum/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for docsum-react-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/docsum-react-ui
-        short-description: "The purpose of the docker image is to provide a user interface for document summary using React. It allows upload a file or paste text and then click on “Generate Summary” to get a condensed summary of the generated content and automatically scroll to the bottom of the summary."
-        readme-filepath: Docsum/ui/react/README.md
-        enable-url-completion: false
-
-    - name: Description for docsum-gradio-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/docsum-gradio-ui
-        short-description: "The purpose of the docker image is to provides a user interface for summarizing documents and text using a Dockerized frontend application. Users can upload files or paste text to generate summaries."
-        readme-filepath: Docsum/ui/gradio/README.md
-        enable-url-completion: false
-
-    - name: Description for edgecraftrag
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/edgecraftrag
-        short-description: "The docker image served as an Edge Craft RAG (EC-RAG) gateway, delivering a customizable and production-ready Retrieval-Augmented Generation system optimized for edge solutions."
-        readme-filepath: EdgeCraftRag/README.md
-        enable-url-completion: false
-
-    - name: Description for edgecraftrag-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/edgecraftrag-ui
-        short-description: "The docker image acted as the Edge Craft RAG (EC-RAG) UI entry. It ensuring high-quality, performant interactions tailored for edge environments."
-        readme-filepath: EdgeCraftRag/README.md
-        enable-url-completion: false
-
-    - name: Description for edgecraftrag-server
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/edgecraftrag-server
-        short-description: "The docker image served as an Edge Craft RAG (EC-RAG) server, delivering a customizable and production-ready Retrieval-Augmented Generation system optimized for edge solutions."
-        readme-filepath: EdgeCraftRag/README.md
-        enable-url-completion: false
-
-    - name: Description for graphrag
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/graphrag
-        short-description: "The docker image served as a GraphRAG gateway, leveraging a knowledge graph derived from source documents to address both local and global queries."
-        readme-filepath: GraphRag/README.md
-        enable-url-completion: false
-
-    - name: Description for graphrag-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/graphrag-ui
-        short-description: "The docker image acted as the GraphRAG UI entry for facilitating interaction with users"
-        readme-filepath: GraphRag/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for graphrag-react-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/graphrag-react-ui
-        short-description: "The purpose of the docker image is to provide a user interface for GraphRAG using React."
-        readme-filepath: GraphRag/ui/react/README.md
-        enable-url-completion: false
-
-    - name: Description for multimodalqna
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/multimodalqna
-        short-description: "The docker image served as a multimodalqna gateway and dynamically fetches the most relevant multimodal information (frames, transcripts, and/or subtitles) from the user's video collection to solve the problem."
-        readme-filepath: MultimodalQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for multimodalqna-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/multimodalqna-ui
-        short-description: "The docker image serves as the multimodalqna UI entry point for easy interaction with users. Answers to questions are generated from videos uploaded by users."
-        readme-filepath: MultimodalQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for productivity-suite-react-ui-server
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/productivity-suite-react-ui-server
-        short-description: "The purpose of the docker image is to provide a user interface for Productivity Suite Application using React. It allows interaction by uploading documents and inputs."
-        readme-filepath: ProductivitySuite/ui/react/README.md
-        enable-url-completion: false
-
-    - name: Description for searchqna
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/searchqna
-        short-description: "The docker image served as the searchqna gateway to provide service of retrieving accurate and relevant answers to user queries from a knowledge base or dataset"
-        readme-filepath: SearchQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for searchqna-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/searchqna-ui
-        short-description: "The docker image acted as the searchqna UI entry for facilitating interaction with users for question answering"
-        readme-filepath: SearchQnA/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for translation
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/translation
-        short-description: "The docker image served as the translation gateway to provide service of language translation"
-        readme-filepath: Translation/README.md
-        enable-url-completion: false
-
-    - name: Description for translation-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/translation-ui
-        short-description: "The docker image acted as the translation UI entry for facilitating interaction with users for language translation"
-        readme-filepath: Translation/ui/svelte/README.md
-        enable-url-completion: false
-
-    - name: Description for videoqna
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/videoqna
-        short-description: "The docker image acts as videoqna gateway, interacting with the user by retrieving videos based on user prompts"
-        readme-filepath: VideoQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for videoqna-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/videoqna-ui
-        short-description: "The docker image serves as the user interface entry point for the videoqna, facilitating interaction with the user and retrieving the video based on user prompts."
-        readme-filepath: VideoQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for visualqna
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/visualqna
-        short-description: "The docker image acts as a videoqna gateway, outputting answers in natural language based on a combination of images and questions"
-        readme-filepath: VisualQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for visualqna-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/visualqna-ui
-        short-description: "The docker image serves as the user interface portal for VisualQnA, facilitating interaction with the user and outputting answers in natural language based on a combination of images and questions from the user."
-        readme-filepath: VisualQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/agent-ui
-        short-description: "The docker image exposed the OPEA agent microservice UI entry for GenAI application use."
-        readme-filepath: AgentQnA/README.md
-        enable-url-completion: false
-
-    - name: Description for text2image-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/text2image-ui
-        short-description: "The docker image exposed the OPEA text-to-image microservice UI entry for GenAI application use."
-        readme-filepath: Text2Image/README.md
-        enable-url-completion: false
-
-    - name: Description for text2sql-react-ui
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/text2sql-react-ui
-        short-description: "The docker image exposed the OPEA text to Structured Query Language microservice react UI entry for GenAI application use."
-        readme-filepath: DBQnA/README.md
-        enable-url-completion: false
-
-    - name: Checkout GenAIComps
-      uses: actions/checkout@v4
-      with:
-        repository: opea-project/GenAIComps
-        path: GenAIComps
-
-    - name: Description for agent
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/agent
-        short-description: "The docker image exposed the OPEA agent microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/agent/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/asr
-        short-description: "The docker image exposed the OPEA Audio-Speech-Recognition microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/asr/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/animation
-        short-description: "The purpose of the Docker image is to expose the OPEA Avatar Animation microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/animation/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/chathistory-mongo
-        short-description: "The docker image exposes OPEA Chat History microservice which based on MongoDB database, designed to allow user to store, retrieve and manage chat conversations"
-        readme-filepath: GenAIComps/comps/chathistory/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/dataprep
-        short-description: "The docker image exposed the OPEA dataprep microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/dataprep/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/embedding
-        short-description: "The docker image exposed the OPEA mosec embedding microservice  for GenAI application use."
-        readme-filepath: GenAIComps/comps/embeddings/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/embedding-multimodal-clip
-        short-description: "The docker image exposed the OPEA mosec embedding microservice base on Langchain framework for GenAI application use."
-        readme-filepath: GenAIComps/comps/third_parties/clip/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/embedding-multimodal-bridgetower
-        short-description: "The docker image exposes OPEA multimodal embedded microservices based on bridgetower for use by GenAI applications."
-        readme-filepath: GenAIComps/comps/third_parties/bridgetower/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/embedding-multimodal-bridgetower-gaudi
-        short-description: "The docker image exposes OPEA multimodal embedded microservices based on bridgetower for use by GenAI applications on the Gaudi."
-        readme-filepath: GenAIComps/comps/third_parties/bridgetower/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/feedbackmanagement-mongo
-        short-description: "The docker image exposes that the OPEA feedback management microservice uses a MongoDB database for GenAI applications."
-        readme-filepath: GenAIComps/comps/feedback_management/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/finetuning
-        short-description: "The docker image exposed the OPEA Fine-tuning microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/finetuning/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/finetuning-gaudi
-        short-description: "The docker image exposed the OPEA Fine-tuning microservice for GenAI application use on the Gaudi."
-        readme-filepath: GenAIComps/comps/finetuning/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/gpt-sovits
-        short-description: "The docker image exposed the OPEA GPT-SoVITS service for GenAI application use."
-        readme-filepath: GenAIComps/comps/tts/src/integrations/dependency/gpt-sovits/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/guardrails
-        short-description: "The docker image exposed the OPEA guardrail microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/guardrails/src/guardrails/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/guardrails-toxicity-predictionguard
-        short-description: "The docker image exposed the OPEA guardrail microservice to provide toxicity detection for GenAI application use."
-        readme-filepath: GenAIComps/comps/guardrails/src/toxicity_detection/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/guardrails-pii-predictionguard
-        short-description: "The docker image exposed the OPEA guardrail microservice to provide PII detection for GenAI application use."
-        readme-filepath: GenAIComps/comps/guardrails/src/pii_detection/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/guardrails-injection-predictionguard
-        short-description: "The docker image exposed the OPEA guardrail microservice to provide injection predictionguard for GenAI application use."
-        readme-filepath: GenAIComps/comps/guardrails/src/prompt_injection/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/guardrails-hallucination-detection
-        short-description: "The docker image exposed the OPEA guardrail microservice to provide hallucination detection for GenAI application use."
-        readme-filepath: GenAIComps/comps/guardrails/src/hallucination_detection/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/guardrails-factuality-predictionguard
-        short-description: "The docker image exposed the OPEA guardrail microservice to provide factuality predictionguard for GenAI application use."
-        readme-filepath: GenAIComps/comps/guardrails/src/factuality_alignment/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/guardrails-bias-detection
-        short-description: "The docker image exposed the OPEA guardrail microservice to provide bias detection for GenAI application use."
-        readme-filepath: GenAIComps/comps/guardrails/src/bias_detection/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/image2image-gaudi
-        short-description: "The purpose of the Docker image is to expose the OPEA Image-to-Image microservice for GenAI application use on the Gaudi."
-        readme-filepath: GenAIComps/comps/image2image/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/image2image
-        short-description: "The purpose of the Docker image is to expose the OPEA Image-to-Image microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/image2image/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/image2video-gaudi
-        short-description: "The purpose of the Docker image is to expose the OPEA image-to-video microservice for GenAI application use on the Gaudi."
-        readme-filepath: GenAIComps/comps/image2image/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/image2video
-        short-description: "The purpose of the Docker image is to expose the OPEA image-to-video microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/image2video/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/llm-textgen
-        short-description: "The docker image exposed the OPEA LLM microservice upon textgen docker image for GenAI application use."
-        readme-filepath: GenAIComps/comps/llms/src/text-generation/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/llm-textgen-gaudi
-        short-description: "The docker image exposed the OPEA LLM microservice upon textgen docker image for GenAI application use on the Gaudi2."
-        readme-filepath: GenAIComps/comps/llms/src/text-generation/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/llm-eval
-        short-description: "The docker image exposed the OPEA LLM microservice upon eval docker image for GenAI application use."
-        readme-filepath: GenAIComps/comps/llms/utils/lm-eval/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/llm-docsum
-        short-description: "The docker image exposed the OPEA LLM microservice upon docsum docker image for GenAI application use."
-        readme-filepath: GenAIComps/comps/llms/src/doc-summarization/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/llm-faqgen
-        short-description: "This docker image is designed to build a frequently asked questions microservice using the HuggingFace Text Generation Inference(TGI) framework. The microservice accepts document input and generates a FAQ."
-        readme-filepath: GenAIComps/comps/llms/src/faq-generation/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/lvm
-        short-description: "The docker image exposed the OPEA large visual model (LVM) microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/lvms/src/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/lvm-llava
-        short-description: "The docker image exposed the OPEA microservice running LLaVA as a large visual model (LVM) server for GenAI application use."
-        readme-filepath: GenAIComps/comps/lvms/src/integrations/dependency/llava/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/lvm-video-llama
-        short-description: "The docker image exposed the OPEA microservice running Video-Llama as a large visual model (LVM) for GenAI application use."
-        readme-filepath: GenAIComps/comps/lvms/src/integrations/dependency/video-llama/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/lvm-predictionguard
-        short-description: "The docker image exposed the OPEA microservice running predictionguard as a large visual model (LVM) server for GenAI application use."
-        readme-filepath: GenAIComps/comps/lvms/src/integrations/dependency/predictionguard/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/llava-gaudi
-        short-description: "The docker image exposed the OPEA microservice running LLaVA as a large visual model (LVM) service for GenAI application use on the Gaudi2."
-        readme-filepath: GenAIComps/comps/lvms/src/integrations/dependency/llava/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/lvm-llama-vision
-        short-description: "The docker image exposed the OPEA microservice running Llama Vision as the base large visual model service for GenAI application use."
-        readme-filepath: GenAIComps/comps/lvms/src/integrations/dependency/llama-vision/README.md
-        enable-url-completion: false
-
-    - name: Description for
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/lvm-llama-vision-tp
-        short-description: "The docker image exposed the OPEA microservice running Llama Vision with deepspeed as the base large visual model service for GenAI application use."
-        readme-filepath: GenAIComps/comps/lvms/src/integrations/dependency/llama-vision/README.md
-        enable-url-completion: false
-
-    - name: Description for lvm-llama-vision-guard
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/lvm-llama-vision-guard
-        short-description: "The docker image exposed the OPEA microservice running Llama Vision Guard as the base large visual model service for GenAI application use."
-        readme-filepath: GenAIComps/comps/lvms/src/integrations/dependency/llama-vision/README.md
-        enable-url-completion: false
-
-    - name: Description for promptregistry-mongo
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/promptregistry-mongo
-        short-description: "The docker image exposes the OPEA Prompt Registry microservices which based on MongoDB database, designed to store and retrieve user's preferred prompts."
-        readme-filepath: GenAIComps/comps/prompt_registry/src/README.md
-        enable-url-completion: false
-
-    - name: Description for reranking
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/reranking
-        short-description: "The docker image exposed the OPEA reranking microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/rerankings/src/README.md
-        enable-url-completion: false
-
-    - name: Description for retriever
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/retriever
-        short-description: "The docker image exposed the OPEA retrieval microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/retrievers/README.md
-        enable-url-completion: false
-
-    - name: Description for text2image
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/text2image
-        short-description: "The docker image exposed the OPEA text-to-image microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/text2image/src/README.md
-        enable-url-completion: false
-
-    - name: Description for text2image-gaudi
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/text2image-gaudi
-        short-description: "The docker image exposed the OPEA text-to-image microservice for GenAI application use on the Gaudi."
-        readme-filepath: GenAIComps/comps/text2image/src/README.md
-        enable-url-completion: false
-
-    - name: Description for text2sql
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/text2sql
-        short-description: "The docker image exposed the OPEA text to Structured Query Language microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/text2sql/src/README.md
-        enable-url-completion: false
-
-    - name: Description for tts
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/tts
-        short-description: "The docker image exposed the OPEA Text-To-Speech microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/tts/src/README.md
-        enable-url-completion: false
-
-    - name: Description for speecht5
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/speecht5
-        short-description: "The docker image exposed the OPEA SpeechT5 service for GenAI application use."
-        readme-filepath: GenAIComps/comps/tts/src/README.md
-        enable-url-completion: false
-
-    - name: Description for speecht5-gaudi
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/speecht5-gaudi
-        short-description: "The docker image exposed the OPEA SpeechT5 service on Gaudi2 for GenAI application use."
-        readme-filepath: GenAIComps/comps/tts/src/README.md
-        enable-url-completion: false
-
-    - name: Description for gpt-sovits
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/gpt-sovits
-        short-description: "The docker image exposed the OPEA gpt-sovits service for GenAI application use."
-        readme-filepath: GenAIComps/comps/tts/src/integrations/dependency/gpt-sovits/README.md
-        enable-url-completion: false
-
-    - name: Description for nginx
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/nginx
-        short-description: "The docker image exposed the OPEA nginx microservice for GenAI application use."
-        readme-filepath: GenAIComps/comps/third_parties/nginx/deployment/kubernetes/README.md
-        enable-url-completion: false
-
-    - name: Description for vectorstore-pathway
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/vectorstore-pathway
-        short-description: "The docker image exposed the OPEA Vectorstores microservice with Pathway for GenAI application use."
-        readme-filepath: GenAIComps/comps/third_parties/pathway/src/README.md
-        enable-url-completion: false
-
-    - name: Description for wav2lip
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/wav2lip
-        short-description: "The docker image exposed the OPEA Generate lip movements from audio files microservice with Pathway for GenAI application use."
-        readme-filepath: GenAIComps/comps/third_parties/wav2lip/deployment/kubernetes/README.md
-        enable-url-completion: false
-
-    - name: Description for wav2lip-gaudi
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/wav2lip-gaudi
-        short-description: "The docker image exposed the OPEA Generate lip movements from audio files microservice with Pathway for GenAI application use on the Gaudi2."
-        readme-filepath: GenAIComps/comps/third_parties/wav2lip/deployment/kubernetes/README.md
-        enable-url-completion: false
-
-    - name: Description for vllm-arc
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/vllm-arc
-        short-description: "The docker image powered by vllm-project for deploying and serving vllm Models on Arc."
-        readme-filepath: GenAIComps/comps/third_parties/vllm/README.md
-        enable-url-completion: false
-
-    - name: Description for whisper-gaudi
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/whisper-gaudi
-        short-description: "The docker image exposed the OPEA Whisper service on Gaudi2 for GenAI application use."
-        readme-filepath: GenAIComps/comps/asr/src/README.md
-        enable-url-completion: false
-
-    - name: Description for whisper
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/whisper
-        short-description: "The docker image exposed the OPEA Whisper service for GenAI application use."
-        readme-filepath: GenAIComps/comps/asr/src/README.md
-        enable-url-completion: false
-
-    - name: Description for web-retriever
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/web-retriever
-        short-description: "The docker image exposed the OPEA retrieval microservice based on chroma vectordb for GenAI application use."
-        readme-filepath: GenAIComps/comps/web_retrievers/src/README.md
-        enable-url-completion: false
-
-    - name: Checkout vllm-openvino
-      uses: actions/checkout@v4
-      with:
-        repository: vllm-project/vllm
-        path: vllm
-
-    - name: Description for vllm-openvino
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/vllm-openvino
-        short-description: "The docker image powered by vllm-project for deploying and serving vllm Models of the Openvino Framework."
-        readme-filepath: vllm/README.md
-        enable-url-completion: false
-
-    - name: Checkout vllm-gaudi
-      uses: actions/checkout@v4
-      with:
-        repository: HabanaAI/vllm-fork
-        ref: habana_main
-        path: vllm-fork
-
-    - name: Description for vllm-gaudi
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/vllm-gaudi
-        short-description: "The docker image powered by vllm-project for deploying and serving vllm Models on Gaudi2."
-        readme-filepath: vllm-fork/README.md
-        enable-url-completion: false
-
-    - name: Description for vllm
-      uses: peter-evans/dockerhub-description@v4
-      with:
-        username: ${{ secrets.DOCKERHUB_USER }}
-        password: ${{ secrets.DOCKERHUB_TOKEN }}
-        repository: opea/vllm
-        short-description: "The docker image powered by vllm-project for deploying and serving vllm Models."
-        readme-filepath: vllm-fork/README.md
-        enable-url-completion: false

.github/workflows/manual-docker-publish.yml

@@ -41,11 +41,9 @@ jobs:
 
   publish:
     needs: [get-image-list]
-    if: ${{ needs.get-image-list.outputs.matrix != '' }}
     strategy:
       matrix:
         image: ${{ fromJSON(needs.get-image-list.outputs.matrix) }}
-      fail-fast: false
     runs-on: "docker-build-${{ inputs.node }}"
     steps:
       - uses: docker/login-action@v3.2.0

.github/workflows/manual-docker-scan.yml

@@ -12,7 +12,7 @@ on:
         type: string
       examples:
         default: ""
-        description: 'List of examples to publish "AgentQnA,AudioQnA,ChatQnA,CodeGen,CodeTrans,DocIndexRetriever,DocSum,InstructionTuning,MultimodalQnA,ProductivitySuite,RerankFinetuning,SearchQnA,Translation,VideoQnA,VisualQnA"'
+        description: 'List of examples to publish "AgentQnA,AudioQnA,ChatQnA,CodeGen,CodeTrans,DocIndexRetriever,DocSum,FaqGen,InstructionTuning,MultimodalQnA,ProductivitySuite,RerankFinetuning,SearchQnA,Translation,VideoQnA,VisualQnA"'
         required: false
         type: string
       images:
@@ -47,7 +47,6 @@ jobs:
   scan-docker:
     needs: get-image-list
     runs-on: "docker-build-${{ inputs.node }}"
-    if: ${{ needs.get-image-list.outputs.matrix != '' }}
     strategy:
       matrix:
         image: ${{ fromJson(needs.get-image-list.outputs.matrix) }}

.github/workflows/manual-example-workflow.yml

@@ -7,7 +7,7 @@ on:
     inputs:
       nodes:
         default: "gaudi,xeon"
-        description: "Hardware to run test gaudi,gaudi3,xeon,rocm,arc"
+        description: "Hardware to run test"
         required: true
         type: string
       examples:
@@ -20,6 +20,11 @@ on:
         description: "Tag to apply to images"
         required: true
         type: string
+      deploy_gmc:
+        default: false
+        description: 'Whether to deploy gmc'
+        required: true
+        type: boolean
       build:
         default: true
         description: 'Build test required images for Examples'
@@ -35,6 +40,11 @@ on:
         description: 'Test examples with helm charts'
         required: false
         type: boolean
+      test_gmc:
+        default: false
+        description: 'Test examples with gmc'
+        required: false
+        type: boolean
       opea_branch:
         default: "main"
         description: 'OPEA branch for image build'
@@ -42,14 +52,9 @@ on:
         type: string
       inject_commit:
         default: false
-        description: "inject commit to docker images"
+        description: "inject commit to docker images true or false"
         required: false
-        type: boolean
-      use_model_cache:
-        default: false
-        description: "use model cache"
-        required: false
-        type: boolean
+        type: string
 
 permissions: read-all
 jobs:
@@ -69,20 +74,23 @@ jobs:
         nodes_json=$(printf '%s\n' "${nodes[@]}" | sort -u | jq -R '.' | jq -sc '.')
         echo "nodes=$nodes_json" >> $GITHUB_OUTPUT
 
-  build-comps-base:
+  build-deploy-gmc:
     needs: [get-test-matrix]
+    if: ${{ fromJSON(inputs.deploy_gmc) }}
     strategy:
       matrix:
         node: ${{ fromJson(needs.get-test-matrix.outputs.nodes) }}
-    uses: ./.github/workflows/_build_comps_base_image.yml
+      fail-fast: false
+    uses: ./.github/workflows/_gmc-workflow.yml
     with:
       node: ${{ matrix.node }}
-      build: ${{ fromJSON(inputs.build) }}
       tag: ${{ inputs.tag }}
       opea_branch: ${{ inputs.opea_branch }}
+    secrets: inherit
 
   run-examples:
-    needs: [get-test-matrix, build-comps-base]
+    needs: [get-test-matrix, build-deploy-gmc]
+    if: always()
     strategy:
       matrix:
         example: ${{ fromJson(needs.get-test-matrix.outputs.examples) }}
@@ -96,7 +104,7 @@ jobs:
       build: ${{ fromJSON(inputs.build) }}
       test_compose: ${{ fromJSON(inputs.test_compose) }}
       test_helmchart: ${{ fromJSON(inputs.test_helmchart) }}
+      test_gmc: ${{ fromJSON(inputs.test_gmc) }}
       opea_branch: ${{ inputs.opea_branch }}
       inject_commit: ${{ inputs.inject_commit }}
-      use_model_cache: ${{ inputs.use_model_cache }}
     secrets: inherit

.github/workflows/manual-freeze-tag.yml

@@ -25,9 +25,9 @@ jobs:
 
       - name: Set up Git
         run: |
-          git config --global user.name "CICD-at-OPEA"
-          git config --global user.email "CICD@opea.dev"
-          git remote set-url origin https://CICD-at-OPEA:"${{ secrets.ACTION_TOKEN }}"@github.com/opea-project/GenAIExamples.git
+          git config --global user.name "NeuralChatBot"
+          git config --global user.email "grp_neural_chat_bot@intel.com"
+          git remote set-url origin https://NeuralChatBot:"${{ secrets.ACTION_TOKEN }}"@github.com/opea-project/GenAIExamples.git
 
       - name: Run script
         run: |

.github/workflows/manual-image-build.yml

@@ -32,9 +32,9 @@ on:
         type: string
       inject_commit:
         default: false
-        description: "inject commit to docker images"
+        description: "inject commit to docker images true or false"
         required: false
-        type: boolean
+        type: string
 
 jobs:
   get-test-matrix:
@@ -51,7 +51,6 @@ jobs:
 
   image-build:
     needs: get-test-matrix
-    if: ${{ needs.get-test-matrix.outputs.nodes != '' }}
     strategy:
       matrix:
         node: ${{ fromJson(needs.get-test-matrix.outputs.nodes) }}

.github/workflows/manual-reset-local-registry.yml

@@ -33,7 +33,6 @@ jobs:
 
   clean-up:
     needs: get-build-matrix
-    if: ${{ needs.get-image-list.outputs.matrix != '' }}
     strategy:
       matrix:
         node: ${{ fromJson(needs.get-build-matrix.outputs.nodes) }}
@@ -48,7 +47,6 @@ jobs:
 
   build:
     needs: [get-build-matrix, clean-up]
-    if: ${{ needs.get-image-list.outputs.matrix != '' }}
     strategy:
       matrix:
         example: ${{ fromJson(needs.get-build-matrix.outputs.examples) }}

.github/workflows/nightly-docker-build-publish.yml

@@ -32,15 +32,8 @@ jobs:
           echo "TAG=$TAG" >> $GITHUB_OUTPUT
           echo "PUBLISH_TAGS=$PUBLISH_TAGS" >> $GITHUB_OUTPUT
 
-  build-comps-base:
-    needs: [get-build-matrix]
-    uses: ./.github/workflows/_build_comps_base_image.yml
-    with:
-      node: gaudi
-
   build-and-test:
     needs: get-build-matrix
-    if: ${{ needs.get-build-matrix.outputs.examples_json != '' }}
     strategy:
       matrix:
         example: ${{ fromJSON(needs.get-build-matrix.outputs.examples_json) }}
@@ -50,7 +43,6 @@ jobs:
       node: gaudi
       example: ${{ matrix.example }}
       test_compose: true
-      inject_commit: true
     secrets: inherit
 
   get-image-list:
@@ -61,11 +53,9 @@ jobs:
 
   publish:
     needs: [get-build-matrix, get-image-list, build-and-test]
-    if: always() && ${{ needs.get-image-list.outputs.matrix != '' }}
     strategy:
       matrix:
         image: ${{ fromJSON(needs.get-image-list.outputs.matrix) }}
-      fail-fast: false
     runs-on: "docker-build-gaudi"
     steps:
       - uses: docker/login-action@v3.2.0

.github/workflows/pr-chart-e2e.yml

@@ -65,7 +65,7 @@ jobs:
 
   helm-chart-test:
     needs: [job1]
-    if: always() && ${{ fromJSON(needs.job1.outputs.run_matrix).length != 0 }}
+    if: always() && ${{ needs.job1.outputs.run_matrix.example.length > 0 }}
     uses: ./.github/workflows/_helm-e2e.yml
     strategy:
       matrix: ${{ fromJSON(needs.job1.outputs.run_matrix) }}

.github/workflows/pr-docker-compose-e2e.yml

@@ -32,16 +32,15 @@ jobs:
 
   example-test:
     needs: [get-test-matrix]
-    if: ${{ needs.get-test-matrix.outputs.run_matrix != '' }}
     strategy:
       matrix: ${{ fromJSON(needs.get-test-matrix.outputs.run_matrix) }}
       fail-fast: false
+    if: ${{ !github.event.pull_request.draft }}
     uses: ./.github/workflows/_run-docker-compose.yml
     with:
       registry: "opea"
       tag: "ci"
       example: ${{ matrix.example }}
       hardware: ${{ matrix.hardware }}
-      use_model_cache: true
       diff_excluded_files: '\.github|\.md|\.txt|kubernetes|gmc|assets|benchmark'
     secrets: inherit

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

@@ -76,7 +76,13 @@ jobs:
           cd ${{github.workspace}}
           fail="FALSE"
           repo_name=${{ github.event.pull_request.head.repo.full_name }}
-          branch="https://github.com/$repo_name/blob/${{ github.event.pull_request.head.ref }}"
+          if [ "$(echo "$repo_name"|cut -d'/' -f1)" != "opea-project" ]; then
+            owner=$(echo "${{ github.event.pull_request.head.repo.full_name }}" |cut -d'/' -f1)
+            branch="https://github.com/$owner/GenAIExamples/tree/${{ github.event.pull_request.head.ref }}"
+          else
+            branch="https://github.com/opea-project/GenAIExamples/blob/${{ github.event.pull_request.head.ref }}"
+          fi
+          link_head="https://github.com/opea-project/GenAIExamples/blob/main"
 
           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}')"

.github/workflows/push-image-build.yml

@@ -24,7 +24,6 @@ jobs:
 
   image-build:
     needs: job1
-    if: ${{ needs.job1.outputs.run_matrix != '{"include":[]}' }}
     strategy:
       matrix: ${{ fromJSON(needs.job1.outputs.run_matrix) }}
       fail-fast: false

.github/workflows/push-infra-issue-creation.yml

@@ -54,6 +54,6 @@ jobs:
 
             ${{ env.changed_files }}
 
-            Please verify if the helm charts need to be changed accordingly.
+            Please verify if the helm charts and manifests need to be changed accordingly.
 
             > This issue was created automatically by CI.

.github/workflows/scripts/docker_compose_clean_up.sh

@@ -30,20 +30,13 @@ case "$1" in
         echo "$ports"
         for port in $ports; do
           if [[ $port =~ [a-zA-Z_-] ]]; then
-            echo "Search port value $port from the test case..."
-            port_fix=$(grep -E "export $port=" tests/$test_case | cut -d'=' -f2)
-            if [[ "$port_fix" == "" ]]; then
-              echo "Can't find the port value from the test case, use the default value in yaml..."
-              port_fix=$(yq '.services[].ports[]' $yaml_file | grep $port | cut -d':' -f2 |  grep -o '[0-9a-zA-Z]\+')
-            fi
-            port=$port_fix
+            port=$(grep -E "export $port=" tests/$test_case | cut -d'=' -f2)
           fi
           if [[ $port =~ [0-9] ]]; then
             if [[ $port == 5000 ]]; then
               echo "Error: Port 5000 is used by local docker registry, please DO NOT use it in docker compose deployment!!!"
               exit 1
             fi
-            echo "Check port $port..."
             cid=$(docker ps --filter "publish=${port}" --format "{{.ID}}")
             if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && echo "release $port"; fi
           fi

.github/workflows/scripts/get_test_matrix.sh

@@ -12,7 +12,6 @@ run_matrix="{\"include\":["
 
 examples=$(printf '%s\n' "${changed_files[@]}" | grep '/' | cut -d'/' -f1 | sort -u)
 for example in ${examples}; do
-    if [[ ! -d $WORKSPACE/$example ]]; then continue; fi
     cd $WORKSPACE/$example
     if [[ ! $(find . -type f | grep ${test_mode}) ]]; then continue; fi
     cd tests
@@ -27,10 +26,7 @@ for example in ${examples}; do
 
     run_hardware=""
     if [[ $(printf '%s\n' "${changed_files[@]}" | grep ${example} | cut -d'/' -f2 | grep -E '\.py|Dockerfile*|ui|docker_image_build' ) ]]; then
-        echo "run test on all hardware if megaservice or ui code change..."
-        run_hardware=$hardware_list
-    elif [[ $(printf '%s\n' "${changed_files[@]}" | grep ${example} | grep 'tests'| cut -d'/' -f3 | grep -vE '^test_|^_test' ) ]]; then
-        echo "run test on all hardware if common test scripts change..."
+        # run test on all hardware if megaservice or ui code change
         run_hardware=$hardware_list
     else
         for hardware in ${hardware_list}; do

.github/workflows/weekly-update-images.yml

@@ -1,9 +1,11 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-name: Weekly update 3rd party images
+name: Weekly update base images and 3rd party images
 
 on:
+  schedule:
+    - cron: "0 0 * * 0"
   workflow_dispatch:
 
 permissions:
@@ -14,8 +16,8 @@ jobs:
   freeze-images:
     runs-on: ubuntu-latest
     env:
-      USER_NAME: "CICD-at-OPEA"
-      USER_EMAIL: "CICD@opea.dev"
+      USER_NAME: "NeuralChatBot"
+      USER_EMAIL: "grp_neural_chat_bot@intel.com"
       BRANCH_NAME: "update_images_tag"
     steps:
       - name: Checkout repository

AgentQnA/README.md

@@ -1,16 +1,8 @@
 # Agents for Question Answering
 
-## Table of contents
-
-1. [Overview](#overview)
-2. [Deploy with Docker](#deploy-with-docker)
-3. [Launch the UI](#launch-the-ui)
-4. [Validate Services](#validate-services)
-5. [Register Tools](#how-to-register-other-tools-with-the-ai-agent)
-
 ## Overview
 
-This example showcases a hierarchical multi-agent system for question-answering applications. The architecture diagram below shows a supervisor agent that interfaces with the user and dispatches tasks to two worker agents to gather information and come up with answers. The worker RAG agent uses the retrieval tool to retrieve relevant documents from a knowledge base - a vector database. The worker SQL agent retrieves relevant data from a SQL database. Although not included in this example by default, other tools such as a web search tool or a knowledge graph query tool can be used by the supervisor agent to gather information from additional sources.
+This example showcases a hierarchical multi-agent system for question-answering applications. The architecture diagram is shown below. The supervisor agent interfaces with the user and dispatch tasks to two worker agents to gather information and come up with answers. The worker RAG agent uses the retrieval tool to retrieve relevant documents from the knowledge base (a vector database). The worker SQL agent retrieve relevant data from the SQL database. Although not included in this example, but other tools such as a web search tool or a knowledge graph query tool can be used by the supervisor agent to gather information from additional sources.
 ![Architecture Overview](assets/img/agent_qna_arch.png)
 
 The AgentQnA 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.
@@ -83,169 +75,201 @@ flowchart LR
 
 ```
 
-### Why should AI Agents be used for question-answering?
+### Why Agent for question answering?
 
-1. **Improve relevancy of retrieved context.**
-   RAG agents can rephrase user queries, decompose user queries, and iterate to get the most relevant context for answering a user's question. Compared to conventional RAG, RAG agents significantly improve the correctness and relevancy of the answer because of the iterations it goes through.
-2. **Expand scope of skills.**
-   The supervisor agent interacts with multiple worker agents that specialize in different skills (e.g., retrieve documents, write SQL queries, etc.). Thus, it can answer questions with different methods.
-3. **Hierarchical multi-agents improve performance.**
-   Expert worker agents, such as RAG agents and SQL agents, can provide high-quality output for different aspects of a complex query, and the supervisor agent can aggregate the information to provide a comprehensive answer. If only one agent is used and all tools are provided to this single agent, it can lead to large overhead or not use the best tool to provide accurate answers.
+1. Improve relevancy of retrieved context.
+   RAG agent can rephrase user queries, decompose user queries, and iterate to get the most relevant context for answering user's questions. Compared to conventional RAG, RAG agent can significantly improve the correctness and relevancy of the answer.
+2. Expand scope of the agent.
+   The supervisor agent can interact with multiple worker agents that specialize in different domains with different skills (e.g., retrieve documents, write SQL queries, etc.), and thus can answer questions in multiple domains.
+3. Hierarchical multi-agents can improve performance.
+   Expert worker agents, such as RAG agent and SQL agent, can provide high-quality output for different aspects of a complex query, and the supervisor agent can aggregate the information together to provide a comprehensive answer. If we only use one agent and provide all the tools to this single agent, it may get overwhelmed and not able to provide accurate answers.
 
-## Deploy with docker
+## Deployment with docker
 
-### 1. Set up environment </br>
+1. Build agent docker image [Optional]
 
-#### First, clone the `GenAIExamples` repo.
+> [!NOTE]
+> the step is optional. The docker images will be automatically pulled when running the docker compose commands. This step is only needed if pulling images failed.
+
+First, clone the opea GenAIComps repo.
 
 ```
 export WORKDIR=<your-work-directory>
 cd $WORKDIR
-git clone https://github.com/opea-project/GenAIExamples.git
+git clone https://github.com/opea-project/GenAIComps.git
 ```
 
-#### Second, set up environment variables.
-
-##### For proxy environments only
+Then build the agent docker image. Both the supervisor agent and the worker agent will use the same docker image, but when we launch the two agents we will specify different strategies and register different tools.
 
 ```
-export http_proxy="Your_HTTP_Proxy"
-export https_proxy="Your_HTTPs_Proxy"
-# Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
-export no_proxy="Your_No_Proxy"
+cd GenAIComps
+docker build -t opea/agent:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/agent/src/Dockerfile .
 ```
 
-##### For using open-source llms
+2. Set up environment for this example </br>
 
-```
-export HUGGINGFACEHUB_API_TOKEN=<your-HF-token>
-export HF_CACHE_DIR=<directory-where-llms-are-downloaded> #so that no need to redownload every time
-```
+   First, clone this repo.
 
-##### [Optional] OPANAI_API_KEY to use OpenAI models
+   ```
+   export WORKDIR=<your-work-directory>
+   cd $WORKDIR
+   git clone https://github.com/opea-project/GenAIExamples.git
+   ```
 
-```
-export OPENAI_API_KEY=<your-openai-key>
-```
+   Second, set up env vars.
 
-#### Third, set up environment variables for the selected hardware using the corresponding `set_env.sh`
+   ```
+   # Example: host_ip="192.168.1.1" or export host_ip="External_Public_IP"
+   export host_ip=$(hostname -I | awk '{print $1}')
+   # if you are in a proxy environment, also set the proxy-related environment variables
+   export http_proxy="Your_HTTP_Proxy"
+   export https_proxy="Your_HTTPs_Proxy"
+   # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
+   export no_proxy="Your_No_Proxy"
 
-##### Gaudi
+   export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
+   # for using open-source llms
+   export HUGGINGFACEHUB_API_TOKEN=<your-HF-token>
+   export HF_CACHE_DIR=<directory-where-llms-are-downloaded> #so that no need to redownload every time
 
-```
-source $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/set_env.sh
-```
+   # optional: OPANAI_API_KEY if you want to use OpenAI models
+   export OPENAI_API_KEY=<your-openai-key>
+   ```
 
-##### Xeon
+3. Deploy the retrieval tool (i.e., DocIndexRetriever mega-service)
 
-```
-source $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon/set_env.sh
-```
+   First, launch the mega-service.
 
-### 2. Launch the multi-agent system. </br>
+   ```
+   cd $WORKDIR/GenAIExamples/AgentQnA/retrieval_tool
+   bash launch_retrieval_tool.sh
+   ```
 
-Two options are provided for the `llm_engine` of the agents: 1. open-source LLMs on Gaudi, 2. OpenAI models via API calls.
+   Then, ingest data into the vector database. Here we provide an example. You can ingest your own data.
 
-#### Gaudi
+   ```
+   bash run_ingest_data.sh
+   ```
 
-On Gaudi, `meta-llama/Meta-Llama-3.1-70B-Instruct` will be served using vllm.
-By default, both the RAG agent and SQL agent will be launched to support the React Agent.  
-The React Agent requires the DocIndexRetriever's [`compose.yaml`](../DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml) file, so two `compose.yaml` files need to be run with docker compose to start the multi-agent system.
+4. Prepare SQL database
+   In this example, we will use the Chinook SQLite database. Run the commands below.
 
-> **Note**: To enable the web search tool, skip this step and proceed to the "[Optional] Web Search Tool Support" section.
+   ```
+   # Download data
+   cd $WORKDIR
+   git clone https://github.com/lerocha/chinook-database.git
+   cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite $WORKDIR/GenAIExamples/AgentQnA/tests/
+   ```
 
-```bash
-cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/
-docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml up -d
-```
+5. Launch other tools. </br>
+   In this example, we will use some of the mock APIs provided in the Meta CRAG KDD Challenge to demonstrate the benefits of gaining additional context from mock knowledge graphs.
 
-To enable Open Telemetry Tracing, compose.telemetry.yaml file need to be merged along with default compose.yaml file.
-Gaudi example with Open Telemetry feature:
+   ```
+   docker run -d -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
+   ```
 
-```bash
-cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/
-docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml -f compose.telemetry.yaml up -d
-```
+6. Launch multi-agent system. </br>
+   We provide two options for `llm_engine` of the agents: 1. open-source LLMs on Intel Gaudi2, 2. OpenAI models via API calls.
 
-##### [Optional] Web Search Tool Support
+   ::::{tab-set}
+   :::{tab-item} Gaudi
+   :sync: Gaudi
 
-<details>
-<summary> Instructions </summary>
-A web search tool is supported in this example and can be enabled by running docker compose with the `compose.webtool.yaml` file.
-The Google Search API is used. Follow the [instructions](https://python.langchain.com/docs/integrations/tools/google_search) to create an API key and enable the Custom Search API on a Google account. The environment variables `GOOGLE_CSE_ID` and `GOOGLE_API_KEY` need to be set.
+   On Gaudi2 we will serve `meta-llama/Meta-Llama-3.1-70B-Instruct` using vllm.
 
-```bash
-cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/
-export GOOGLE_CSE_ID="YOUR_ID"
-export GOOGLE_API_KEY="YOUR_API_KEY"
-docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml -f compose.webtool.yaml up -d
-```
+   First build vllm-gaudi docker image.
 
-</details>
+   ```bash
+   cd $WORKDIR
+   git clone https://github.com/vllm-project/vllm.git
+   cd ./vllm
+   git checkout v0.6.6
+   docker build --no-cache -f Dockerfile.hpu -t opea/vllm-gaudi:latest --shm-size=128g . --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy
+   ```
 
-#### Xeon
+   Then launch vllm on Gaudi2 with the command below.
 
-On Xeon, only OpenAI models are supported.
-By default, both the RAG Agent and SQL Agent will be launched to support the React Agent.  
-The React Agent requires the DocIndexRetriever's [`compose.yaml`](../DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml) file, so two `compose yaml` files need to be run with docker compose to start the multi-agent system.
+   ```bash
+   vllm_port=8086
+   model="meta-llama/Meta-Llama-3.1-70B-Instruct"
+   docker run -d --runtime=habana --rm --name "vllm-gaudi-server" -e HABANA_VISIBLE_DEVICES=0,1,2,3 -p $vllm_port:8000 -v $vllm_volume:/data -e HF_TOKEN=$HF_TOKEN -e HUGGING_FACE_HUB_TOKEN=$HF_TOKEN -e HF_HOME=/data -e OMPI_MCA_btl_vader_single_copy_mechanism=none -e PT_HPU_ENABLE_LAZY_COLLECTIVES=true -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e no_proxy=$no_proxy -e VLLM_SKIP_WARMUP=true --cap-add=sys_nice --ipc=host opea/vllm-gaudi:latest --model ${model} --max-seq-len-to-capture 16384 --tensor-parallel-size 4
+   ```
 
-```bash
-export OPENAI_API_KEY=<your-openai-key>
-cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon
-docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose_openai.yaml up -d
-```
+   Then launch Agent microservices.
 
-### 3. Ingest Data into the vector database
+   ```bash
+   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/
+   bash launch_agent_service_gaudi.sh
+   ```
 
-The `run_ingest_data.sh` script will use an example jsonl file to ingest example documents into a vector database. Other ways to ingest data and other types of documents supported can be found in the OPEA dataprep microservice located in the opea-project/GenAIComps repo.
+   :::
+   :::{tab-item} Xeon
+   :sync: Xeon
 
-```bash
-cd  $WORKDIR/GenAIExamples/AgentQnA/retrieval_tool/
-bash run_ingest_data.sh
-```
+   To use OpenAI models, run commands below.
 
-> **Note**: This is a one-time operation.
+   ```
+   export OPENAI_API_KEY=<your-openai-key>
+   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon
+   bash launch_agent_service_openai.sh
+   ```
 
-## Launch the UI
+   :::
+   ::::
 
-Open a web browser to http://localhost:5173 to access the UI. Ensure the environment variable `AGENT_URL` is set to http://$ip_address:9090/v1/chat/completions in [ui/svelte/.env](./ui/svelte/.env) or else the UI may not work properly.
-
-The AgentQnA UI can be deployed locally or using Docker. To customize deployment, refer to the [AgentQnA UI Guide](./ui/svelte/README.md).
-
-## [Optional] Deploy using Helm Charts
+## Deploy using Helm Chart
 
 Refer to the [AgentQnA helm chart](./kubernetes/helm/README.md) for instructions on deploying AgentQnA on Kubernetes.
 
-## Validate Services
+## Validate services
 
-1. First look at logs for each of the agent docker containers:
+First look at logs of the agent docker containers:
 
-```bash
+```
 # worker RAG agent
 docker logs rag-agent-endpoint
 
 # worker SQL agent
 docker logs sql-agent-endpoint
+```
 
+```
 # supervisor agent
 docker logs react-agent-endpoint
 ```
 
-Look for the message "HTTP server setup successful" to confirm the agent docker container has started successfully.</p>
+You should see something like "HTTP server setup successful" if the docker containers are started successfully.</p>
 
-2. Use python to validate each agent is working properly:
+Second, validate worker RAG agent:
 
-```bash
-# RAG worker agent
-python $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "Tell me about Michael Jackson song Thriller" --agent_role "worker" --ext_port 9095
-
-# SQL agent
-python $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "How many employees in company" --agent_role "worker" --ext_port 9096
-
-# supervisor agent: this will test a two-turn conversation
-python $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --agent_role "supervisor" --ext_port 9090
+```
+curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "Michael Jackson song Thriller"
+    }'
 ```
 
-## How to register other tools with the AI agent
+Third, validate worker SQL agent:
 
-The [tools](./tools) folder contains YAML and Python files for additional tools for the supervisor and worker agents. Refer to the "Provide your own tools" section in the instructions [here](https://github.com/opea-project/GenAIComps/tree/main/comps/agent/src/README.md) to add tools and customize the AI agents.
+```
+curl http://${host_ip}:9096/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "How many employees are in the company"
+    }'
+```
+
+Finally, validate supervisor agent:
+
+```
+curl http://${host_ip}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "How many albums does Iron Maiden have?"
+    }'
+```
+
+## Deploy AgentQnA UI
+
+The AgentQnA UI can be deployed locally or using Docker.
+
+For detailed instructions on deploying AgentQnA UI, refer to the [AgentQnA UI Guide](./ui/svelte/README.md).
+
+## How to register your own tools with agent
+
+You can take a look at the tools yaml and python files in this example. For more details, please refer to the "Provide your own tools" section in the instructions [here](https://github.com/opea-project/GenAIComps/tree/main/comps/agent/src/README.md).

AgentQnA/docker_compose/amd/gpu/rocm/README.md

@@ -1,342 +1,101 @@
-# Build Mega Service of AgentQnA on AMD ROCm GPU
+# Single node on-prem deployment with Docker Compose on AMD GPU
 
-## Build Docker Images
+This example showcases a hierarchical multi-agent system for question-answering applications. We deploy the example on Xeon. For LLMs, we use OpenAI models via API calls. For instructions on using open-source LLMs, please refer to the deployment guide [here](../../../../README.md).
 
-### 1. Build Docker Image
+## Deployment with docker
 
-- #### Create application install directory and go to it:
+1. First, clone this repo.
+   ```
+   export WORKDIR=<your-work-directory>
+   cd $WORKDIR
+   git clone https://github.com/opea-project/GenAIExamples.git
+   ```
+2. Set up environment for this example </br>
 
-  ```bash
-  mkdir ~/agentqna-install && cd agentqna-install
-  ```
+   ```
+   # Example: host_ip="192.168.1.1" or export host_ip="External_Public_IP"
+   export host_ip=$(hostname -I | awk '{print $1}')
+   # if you are in a proxy environment, also set the proxy-related environment variables
+   export http_proxy="Your_HTTP_Proxy"
+   export https_proxy="Your_HTTPs_Proxy"
+   # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
+   export no_proxy="Your_No_Proxy"
 
-- #### Clone the repository GenAIExamples (the default repository branch "main" is used here):
+   export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
+   #OPANAI_API_KEY if you want to use OpenAI models
+   export OPENAI_API_KEY=<your-openai-key>
+   # Set AMD GPU settings
+   export AGENTQNA_CARD_ID="card1"
+   export AGENTQNA_RENDER_ID="renderD136"
+   ```
 
-  ```bash
-  git clone https://github.com/opea-project/GenAIExamples.git
-  ```
+3. Deploy the retrieval tool (i.e., DocIndexRetriever mega-service)
 
-  If you need to use a specific branch/tag of the GenAIExamples repository, then (v1.3 replace with its own value):
+   First, launch the mega-service.
 
-  ```bash
-  git clone https://github.com/opea-project/GenAIExamples.git && cd GenAIExamples && git checkout v1.3
-  ```
+   ```
+   cd $WORKDIR/GenAIExamples/AgentQnA/retrieval_tool
+   bash launch_retrieval_tool.sh
+   ```
 
-  We remind you that when using a specific version of the code, you need to use the README from this version:
+   Then, ingest data into the vector database. Here we provide an example. You can ingest your own data.
 
-- #### Go to build directory:
+   ```
+   bash run_ingest_data.sh
+   ```
 
-  ```bash
-  cd ~/agentqna-install/GenAIExamples/AgentQnA/docker_image_build
-  ```
+4. Launch Tool service
+   In this example, we will use some of the mock APIs provided in the Meta CRAG KDD Challenge to demonstrate the benefits of gaining additional context from mock knowledge graphs.
+   ```
+   docker run -d -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
+   ```
+5. Launch `Agent` service
 
-- Cleaning up the GenAIComps repository if it was previously cloned in this directory.
-  This is necessary if the build was performed earlier and the GenAIComps folder exists and is not empty:
+   ```
+   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
+   bash launch_agent_service_tgi_rocm.sh
+   ```
 
-  ```bash
-  echo Y | rm -R GenAIComps
-  ```
+6. [Optional] Build `Agent` docker image if pulling images failed.
 
-- #### Clone the repository GenAIComps (the default repository branch "main" is used here):
+   ```
+   git clone https://github.com/opea-project/GenAIComps.git
+   cd GenAIComps
+   docker build -t opea/agent:latest -f comps/agent/src/Dockerfile .
+   ```
 
-```bash
-git clone https://github.com/opea-project/GenAIComps.git
+## Validate services
+
+First look at logs of the agent docker containers:
+
+```
+# worker agent
+docker logs rag-agent-endpoint
 ```
 
-We remind you that when using a specific version of the code, you need to use the README from this version.
-
-- #### Setting the list of images for the build (from the build file.yaml)
-
-  If you want to deploy a vLLM-based or TGI-based application, then the set of services is installed as follows:
-
-  #### vLLM-based application
-
-  ```bash
-  service_list="vllm-rocm agent agent-ui"
-  ```
-
-  #### TGI-based application
-
-  ```bash
-  service_list="agent agent-ui"
-  ```
-
-- #### Optional. Pull TGI Docker Image (Do this if you want to use TGI)
-
-  ```bash
-  docker pull ghcr.io/huggingface/text-generation-inference:2.3.1-rocm
-  ```
-
-- #### Build Docker Images
-
-  ```bash
-  docker compose -f build.yaml build ${service_list} --no-cache
-  ```
-
-- #### Build DocIndexRetriever Docker Images
-
-  ```bash
-  cd ~/agentqna-install/GenAIExamples/DocIndexRetriever/docker_image_build/
-  git clone https://github.com/opea-project/GenAIComps.git
-  service_list="doc-index-retriever dataprep embedding retriever reranking"
-  docker compose -f build.yaml build ${service_list} --no-cache
-  ```
-
-- #### Pull DocIndexRetriever Docker Images
-
-  ```bash
-  docker pull redis/redis-stack:7.2.0-v9
-  docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
-  ```
-
-  After the build, we check the list of images with the command:
-
-  ```bash
-  docker image ls
-  ```
-
-  The list of images should include:
-
-  ##### vLLM-based application:
-
-  - opea/vllm-rocm:latest
-  - opea/agent:latest
-  - redis/redis-stack:7.2.0-v9
-  - ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
-  - opea/embedding:latest
-  - opea/retriever:latest
-  - opea/reranking:latest
-  - opea/doc-index-retriever:latest
-
-  ##### TGI-based application:
-
-  - ghcr.io/huggingface/text-generation-inference:2.3.1-rocm
-  - opea/agent:latest
-  - redis/redis-stack:7.2.0-v9
-  - ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
-  - opea/embedding:latest
-  - opea/retriever:latest
-  - opea/reranking:latest
-  - opea/doc-index-retriever:latest
-
----
-
-## Deploy the AgentQnA Application
-
-### Docker Compose Configuration for AMD GPUs
-
-To enable GPU support for AMD GPUs, the following configuration is added to the Docker Compose file:
-
-- compose_vllm.yaml - for vLLM-based application
-- compose.yaml - for TGI-based
-
-```yaml
-shm_size: 1g
-devices:
-  - /dev/kfd:/dev/kfd
-  - /dev/dri:/dev/dri
-cap_add:
-  - SYS_PTRACE
-group_add:
-  - video
-security_opt:
-  - seccomp:unconfined
+```
+# supervisor agent
+docker logs react-agent-endpoint
 ```
 
-This configuration forwards all available GPUs to the container. To use a specific GPU, specify its `cardN` and `renderN` device IDs. For example:
+You should see something like "HTTP server setup successful" if the docker containers are started successfully.</p>
 
-```yaml
-shm_size: 1g
-devices:
-  - /dev/kfd:/dev/kfd
-  - /dev/dri/card0:/dev/dri/card0
-  - /dev/dri/render128:/dev/dri/render128
-cap_add:
-  - SYS_PTRACE
-group_add:
-  - video
-security_opt:
-  - seccomp:unconfined
+Second, validate worker agent:
+
+```
+curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "query": "Most recent album by Taylor Swift"
+    }'
 ```
 
-**How to Identify GPU Device IDs:**
-Use AMD GPU driver utilities to determine the correct `cardN` and `renderN` IDs for your GPU.
+Third, validate supervisor agent:
 
-### Set deploy environment variables
-
-#### Setting variables in the operating system environment:
-
-```bash
-### Replace the string 'server_address' with your local server IP address
-export host_ip='server_address'
-### Replace the string 'your_huggingfacehub_token' with your HuggingFacehub repository access token.
-export HUGGINGFACEHUB_API_TOKEN='your_huggingfacehub_token'
-### Replace the string 'your_langchain_api_key' with your LANGCHAIN API KEY.
-export LANGCHAIN_API_KEY='your_langchain_api_key'
-export LANGCHAIN_TRACING_V2=""
+```
+curl http://${host_ip}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "query": "Most recent album by Taylor Swift"
+    }'
 ```
 
-### Start the services:
+## How to register your own tools with agent
 
-#### If you use vLLM
-
-```bash
-cd ~/agentqna-install/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-bash launch_agent_service_vllm_rocm.sh
-```
-
-#### If you use TGI
-
-```bash
-cd ~/agentqna-install/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-bash launch_agent_service_tgi_rocm.sh
-```
-
-All containers should be running and should not restart:
-
-##### If you use vLLM:
-
-- dataprep-redis-server
-- doc-index-retriever-server
-- embedding-server
-- rag-agent-endpoint
-- react-agent-endpoint
-- redis-vector-db
-- reranking-tei-xeon-server
-- retriever-redis-server
-- sql-agent-endpoint
-- tei-embedding-server
-- tei-reranking-server
-- vllm-service
-
-##### If you use TGI:
-
-- dataprep-redis-server
-- doc-index-retriever-server
-- embedding-server
-- rag-agent-endpoint
-- react-agent-endpoint
-- redis-vector-db
-- reranking-tei-xeon-server
-- retriever-redis-server
-- sql-agent-endpoint
-- tei-embedding-server
-- tei-reranking-server
-- tgi-service
-
----
-
-## Validate the Services
-
-### 1. Validate the vLLM/TGI Service
-
-#### If you use vLLM:
-
-```bash
-DATA='{"model": "Intel/neural-chat-7b-v3-3t", '\
-'"messages": [{"role": "user", "content": "What is Deep Learning?"}], "max_tokens": 256}'
-
-curl http://${HOST_IP}:${VLLM_SERVICE_PORT}/v1/chat/completions \
-  -X POST \
-  -d "$DATA" \
-  -H 'Content-Type: application/json'
-```
-
-Checking the response from the service. The response should be similar to JSON:
-
-```json
-{
-  "id": "chatcmpl-142f34ef35b64a8db3deedd170fed951",
-  "object": "chat.completion",
-  "created": 1742270316,
-  "model": "Intel/neural-chat-7b-v3-3",
-  "choices": [
-    {
-      "index": 0,
-      "message": {
-        "role": "assistant",
-        "content": "",
-        "tool_calls": []
-      },
-      "logprobs": null,
-      "finish_reason": "length",
-      "stop_reason": null
-    }
-  ],
-  "usage": { "prompt_tokens": 66, "total_tokens": 322, "completion_tokens": 256, "prompt_tokens_details": null },
-  "prompt_logprobs": null
-}
-```
-
-If the service response has a meaningful response in the value of the "choices.message.content" key,
-then we consider the vLLM service to be successfully launched
-
-#### If you use TGI:
-
-```bash
-DATA='{"inputs":"What is Deep Learning?",'\
-'"parameters":{"max_new_tokens":256,"do_sample": true}}'
-
-curl http://${HOST_IP}:${TGI_SERVICE_PORT}/generate \
-  -X POST \
-  -d "$DATA" \
-  -H 'Content-Type: application/json'
-```
-
-Checking the response from the service. The response should be similar to JSON:
-
-```json
-{
-  "generated_text": " "
-}
-```
-
-If the service response has a meaningful response in the value of the "generated_text" key,
-then we consider the TGI service to be successfully launched
-
-### 2. Validate Agent Services
-
-#### Validate Rag Agent Service
-
-```bash
-export agent_port=${WORKER_RAG_AGENT_PORT}
-prompt="Tell me about Michael Jackson song Thriller"
-python3 ~/agentqna-install/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port
-```
-
-The response must contain the meaningful text of the response to the request from the "prompt" variable
-
-#### Validate Sql Agent Service
-
-```bash
-export agent_port=${WORKER_SQL_AGENT_PORT}
-prompt="How many employees are there in the company?"
-python3 ~/agentqna-install/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port
-```
-
-The answer should make sense - "8 employees in the company"
-
-#### Validate React (Supervisor) Agent Service
-
-```bash
-export agent_port=${SUPERVISOR_REACT_AGENT_PORT}
-python3 ~/agentqna-install/GenAIExamples/AgentQnA/tests/test.py --agent_role "supervisor" --ext_port $agent_port --stream
-```
-
-The response should contain "Iron Maiden"
-
-### 3. Stop application
-
-#### If you use vLLM
-
-```bash
-cd ~/agentqna-install/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-bash stop_agent_service_vllm_rocm.sh
-```
-
-#### If you use TGI
-
-```bash
-cd ~/agentqna-install/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-bash stop_agent_service_tgi_rocm.sh
-```
+You can take a look at the tools yaml and python files in this example. For more details, please refer to the "Provide your own tools" section in the instructions [here](https://github.com/opea-project/GenAIComps/tree/main/comps/agent/src/README.md).

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

@@ -1,24 +1,26 @@
-# Copyright (C) 2025 Advanced Micro Devices, Inc.
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
 
 services:
-  tgi-service:
-    image: ghcr.io/huggingface/text-generation-inference:3.0.0-rocm
-    container_name: tgi-service
+  agent-tgi-server:
+    image: ${AGENTQNA_TGI_IMAGE}
+    container_name: agent-tgi-server
     ports:
-      - "${TGI_SERVICE_PORT-8085}:80"
+      - "${AGENTQNA_TGI_SERVICE_PORT-8085}:80"
     volumes:
-      - "${MODEL_CACHE:-./data}:/data"
+      - /var/opea/agent-service/:/data
     environment:
       no_proxy: ${no_proxy}
       http_proxy: ${http_proxy}
       https_proxy: ${https_proxy}
-      TGI_LLM_ENDPOINT: "http://${ip_address}:${TGI_SERVICE_PORT}"
+      TGI_LLM_ENDPOINT: "http://${HOST_IP}:${AGENTQNA_TGI_SERVICE_PORT}"
       HUGGING_FACE_HUB_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
       HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-    shm_size: 32g
+    shm_size: 1g
     devices:
       - /dev/kfd:/dev/kfd
-      - /dev/dri:/dev/dri
+      - /dev/dri/${AGENTQNA_CARD_ID}:/dev/dri/${AGENTQNA_CARD_ID}
+      - /dev/dri/${AGENTQNA_RENDER_ID}:/dev/dri/${AGENTQNA_RENDER_ID}
     cap_add:
       - SYS_PTRACE
     group_add:
@@ -32,14 +34,14 @@ services:
     image: opea/agent:latest
     container_name: rag-agent-endpoint
     volumes:
-      - "${TOOLSET_PATH}:/home/user/tools/"
+      # - ${WORKDIR}/GenAIExamples/AgentQnA/docker_image_build/GenAIComps/comps/agent/langchain/:/home/user/comps/agent/langchain/
+      - ${TOOLSET_PATH}:/home/user/tools/
     ports:
-      - "${WORKER_RAG_AGENT_PORT:-9095}:9095"
+      - "9095:9095"
     ipc: host
     environment:
       ip_address: ${ip_address}
       strategy: rag_agent_llama
-      with_memory: false
       recursion_limit: ${recursion_limit_worker}
       llm_engine: tgi
       HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
@@ -59,49 +61,21 @@ services:
       LANGCHAIN_PROJECT: "opea-worker-agent-service"
       port: 9095
 
-  worker-sql-agent:
-    image: opea/agent:latest
-    container_name: sql-agent-endpoint
-    volumes:
-      - "${WORKDIR}/tests/Chinook_Sqlite.sqlite:/home/user/chinook-db/Chinook_Sqlite.sqlite:rw"
-    ports:
-      - "${WORKER_SQL_AGENT_PORT:-9096}:9096"
-    ipc: host
-    environment:
-      ip_address: ${ip_address}
-      strategy: sql_agent_llama
-      with_memory: false
-      db_name: ${db_name}
-      db_path: ${db_path}
-      use_hints: false
-      recursion_limit: ${recursion_limit_worker}
-      llm_engine: vllm
-      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      llm_endpoint_url: ${LLM_ENDPOINT_URL}
-      model: ${LLM_MODEL_ID}
-      temperature: ${temperature}
-      max_new_tokens: ${max_new_tokens}
-      stream: false
-      require_human_feedback: false
-      no_proxy: ${no_proxy}
-      http_proxy: ${http_proxy}
-      https_proxy: ${https_proxy}
-      port: 9096
-
   supervisor-react-agent:
     image: opea/agent:latest
     container_name: react-agent-endpoint
     depends_on:
+      - agent-tgi-server
       - worker-rag-agent
     volumes:
-      - "${TOOLSET_PATH}:/home/user/tools/"
+      # - ${WORKDIR}/GenAIExamples/AgentQnA/docker_image_build/GenAIComps/comps/agent/langchain/:/home/user/comps/agent/langchain/
+      - ${TOOLSET_PATH}:/home/user/tools/
     ports:
-      - "${SUPERVISOR_REACT_AGENT_PORT:-9090}:9090"
+      - "${AGENTQNA_FRONTEND_PORT}:9090"
     ipc: host
     environment:
       ip_address: ${ip_address}
-      strategy: react_llama
-      with_memory: true
+      strategy: react_langgraph
       recursion_limit: ${recursion_limit_supervisor}
       llm_engine: tgi
       HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
@@ -109,7 +83,7 @@ services:
       model: ${LLM_MODEL_ID}
       temperature: ${temperature}
       max_new_tokens: ${max_new_tokens}
-      stream: true
+      stream: false
       tools: /home/user/tools/supervisor_agent_tools.yaml
       require_human_feedback: false
       no_proxy: ${no_proxy}
@@ -118,7 +92,6 @@ services:
       LANGCHAIN_API_KEY: ${LANGCHAIN_API_KEY}
       LANGCHAIN_TRACING_V2: ${LANGCHAIN_TRACING_V2}
       LANGCHAIN_PROJECT: "opea-supervisor-agent-service"
-      CRAG_SERVER: ${CRAG_SERVER}
-      WORKER_AGENT_URL: ${WORKER_AGENT_URL}
-      SQL_AGENT_URL: ${SQL_AGENT_URL}
+      CRAG_SERVER: $CRAG_SERVER
+      WORKER_AGENT_URL: $WORKER_AGENT_URL
       port: 9090

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

@@ -1,128 +0,0 @@
-# Copyright (C) 2025 Advanced Micro Devices, Inc.
-
-services:
-  vllm-service:
-    image: ${REGISTRY:-opea}/vllm-rocm:${TAG:-latest}
-    container_name: vllm-service
-    ports:
-      - "${VLLM_SERVICE_PORT:-8081}:8011"
-    environment:
-      no_proxy: ${no_proxy}
-      http_proxy: ${http_proxy}
-      https_proxy: ${https_proxy}
-      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      HF_HUB_DISABLE_PROGRESS_BARS: 1
-      HF_HUB_ENABLE_HF_TRANSFER: 0
-      WILM_USE_TRITON_FLASH_ATTENTION: 0
-      PYTORCH_JIT: 0
-    volumes:
-      - "${MODEL_CACHE:-./data}:/data"
-    shm_size: 20G
-    devices:
-      - /dev/kfd:/dev/kfd
-      - /dev/dri/:/dev/dri/
-    cap_add:
-      - SYS_PTRACE
-    group_add:
-      - video
-    security_opt:
-      - seccomp:unconfined
-      - apparmor=unconfined
-    command: "--model ${VLLM_LLM_MODEL_ID} --swap-space 16 --disable-log-requests --dtype float16 --tensor-parallel-size 4 --host 0.0.0.0 --port 8011 --num-scheduler-steps 1 --distributed-executor-backend \"mp\""
-    ipc: host
-
-  worker-rag-agent:
-    image: opea/agent:latest
-    container_name: rag-agent-endpoint
-    volumes:
-      - ${TOOLSET_PATH}:/home/user/tools/
-    ports:
-      - "${WORKER_RAG_AGENT_PORT:-9095}:9095"
-    ipc: host
-    environment:
-      ip_address: ${ip_address}
-      strategy: rag_agent_llama
-      with_memory: false
-      recursion_limit: ${recursion_limit_worker}
-      llm_engine: vllm
-      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      llm_endpoint_url: ${LLM_ENDPOINT_URL}
-      model: ${LLM_MODEL_ID}
-      temperature: ${temperature}
-      max_new_tokens: ${max_new_tokens}
-      stream: false
-      tools: /home/user/tools/worker_agent_tools.yaml
-      require_human_feedback: false
-      RETRIEVAL_TOOL_URL: ${RETRIEVAL_TOOL_URL}
-      no_proxy: ${no_proxy}
-      http_proxy: ${http_proxy}
-      https_proxy: ${https_proxy}
-      LANGCHAIN_API_KEY: ${LANGCHAIN_API_KEY}
-      LANGCHAIN_TRACING_V2: ${LANGCHAIN_TRACING_V2}
-      LANGCHAIN_PROJECT: "opea-worker-agent-service"
-      port: 9095
-
-  worker-sql-agent:
-    image: opea/agent:latest
-    container_name: sql-agent-endpoint
-    volumes:
-      - "${WORKDIR}/tests/Chinook_Sqlite.sqlite:/home/user/chinook-db/Chinook_Sqlite.sqlite:rw"
-    ports:
-      - "${WORKER_SQL_AGENT_PORT:-9096}:9096"
-    ipc: host
-    environment:
-      ip_address: ${ip_address}
-      strategy: sql_agent_llama
-      with_memory: false
-      db_name: ${db_name}
-      db_path: ${db_path}
-      use_hints: false
-      recursion_limit: ${recursion_limit_worker}
-      llm_engine: vllm
-      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      llm_endpoint_url: ${LLM_ENDPOINT_URL}
-      model: ${LLM_MODEL_ID}
-      temperature: ${temperature}
-      max_new_tokens: ${max_new_tokens}
-      stream: false
-      require_human_feedback: false
-      no_proxy: ${no_proxy}
-      http_proxy: ${http_proxy}
-      https_proxy: ${https_proxy}
-      port: 9096
-
-  supervisor-react-agent:
-    image: opea/agent:latest
-    container_name: react-agent-endpoint
-    depends_on:
-      - worker-rag-agent
-    volumes:
-      - ${TOOLSET_PATH}:/home/user/tools/
-    ports:
-      - "${SUPERVISOR_REACT_AGENT_PORT:-9090}:9090"
-    ipc: host
-    environment:
-      ip_address: ${ip_address}
-      strategy: react_llama
-      with_memory: true
-      recursion_limit: ${recursion_limit_supervisor}
-      llm_engine: vllm
-      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      llm_endpoint_url: ${LLM_ENDPOINT_URL}
-      model: ${LLM_MODEL_ID}
-      temperature: ${temperature}
-      max_new_tokens: ${max_new_tokens}
-      stream: true
-      tools: /home/user/tools/supervisor_agent_tools.yaml
-      require_human_feedback: false
-      no_proxy: ${no_proxy}
-      http_proxy: ${http_proxy}
-      https_proxy: ${https_proxy}
-      LANGCHAIN_API_KEY: ${LANGCHAIN_API_KEY}
-      LANGCHAIN_TRACING_V2: ${LANGCHAIN_TRACING_V2}
-      LANGCHAIN_PROJECT: "opea-supervisor-agent-service"
-      CRAG_SERVER: ${CRAG_SERVER}
-      WORKER_AGENT_URL: ${WORKER_AGENT_URL}
-      SQL_AGENT_URL: ${SQL_AGENT_URL}
-      port: 9090

AgentQnA/docker_compose/amd/gpu/rocm/launch_agent_service_tgi_rocm.sh

@@ -1,87 +1,47 @@
 # Copyright (C) 2024 Advanced Micro Devices, Inc.
 # SPDX-License-Identifier: Apache-2.0
 
-# Before start script:
-# export host_ip="your_host_ip_or_host_name"
-# export HUGGINGFACEHUB_API_TOKEN="your_huggingface_api_token"
-# export LANGCHAIN_API_KEY="your_langchain_api_key"
-# export LANGCHAIN_TRACING_V2=""
-
-# Set server hostname or IP address
+WORKPATH=$(dirname "$PWD")/..
 export ip_address=${host_ip}
+export HUGGINGFACEHUB_API_TOKEN=${your_hf_api_token}
+export AGENTQNA_TGI_IMAGE=ghcr.io/huggingface/text-generation-inference:2.3.1-rocm
+export AGENTQNA_TGI_SERVICE_PORT="8085"
 
-# Set services IP ports
-export TGI_SERVICE_PORT="18110"
-export WORKER_RAG_AGENT_PORT="18111"
-export WORKER_SQL_AGENT_PORT="18112"
-export SUPERVISOR_REACT_AGENT_PORT="18113"
-export CRAG_SERVER_PORT="18114"
-
-export WORKPATH=$(dirname "$PWD")
-export WORKDIR=${WORKPATH}/../../../
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-export HF_CACHE_DIR="./data"
-export MODEL_CACHE="./data"
-export TOOLSET_PATH=${WORKPATH}/../../../tools/
-export recursion_limit_worker=12
-export LLM_ENDPOINT_URL=http://${ip_address}:${TGI_SERVICE_PORT}
+# LLM related environment variables
+export AGENTQNA_CARD_ID="card1"
+export AGENTQNA_RENDER_ID="renderD136"
+export HF_CACHE_DIR=${HF_CACHE_DIR}
+ls $HF_CACHE_DIR
+export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
+#export NUM_SHARDS=4
+export LLM_ENDPOINT_URL="http://${ip_address}:${AGENTQNA_TGI_SERVICE_PORT}"
 export temperature=0.01
 export max_new_tokens=512
-export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
-export LANGCHAIN_API_KEY=${LANGCHAIN_API_KEY}
-export LANGCHAIN_TRACING_V2=${LANGCHAIN_TRACING_V2}
-export db_name=Chinook
-export db_path="sqlite:////home/user/chinook-db/Chinook_Sqlite.sqlite"
+
+# agent related environment variables
+export AGENTQNA_WORKER_AGENT_SERVICE_PORT="9095"
+export TOOLSET_PATH=/home/huggingface/datamonsters/amd-opea/GenAIExamples/AgentQnA/tools/
+echo "TOOLSET_PATH=${TOOLSET_PATH}"
 export recursion_limit_worker=12
 export recursion_limit_supervisor=10
-export CRAG_SERVER=http://${ip_address}:${CRAG_SERVER_PORT}
-export WORKER_AGENT_URL="http://${ip_address}:${WORKER_RAG_AGENT_PORT}/v1/chat/completions"
-export SQL_AGENT_URL="http://${ip_address}:${WORKER_SQL_AGENT_PORT}/v1/chat/completions"
-export HF_CACHE_DIR=${HF_CACHE_DIR}
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export no_proxy=${no_proxy}
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export RERANK_MODEL_ID="BAAI/bge-reranker-base"
+export WORKER_AGENT_URL="http://${ip_address}:${AGENTQNA_WORKER_AGENT_SERVICE_PORT}/v1/chat/completions"
+export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
+export CRAG_SERVER=http://${ip_address}:18881
+
+export AGENTQNA_FRONTEND_PORT="9090"
+
+#retrieval_tool
 export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006"
 export TEI_RERANKING_ENDPOINT="http://${host_ip}:8808"
-export REDIS_URL="redis://${host_ip}:6379"
+export REDIS_URL="redis://${host_ip}:26379"
 export INDEX_NAME="rag-redis"
-export RERANK_TYPE="tei"
 export MEGA_SERVICE_HOST_IP=${host_ip}
 export EMBEDDING_SERVICE_HOST_IP=${host_ip}
 export RETRIEVER_SERVICE_HOST_IP=${host_ip}
 export RERANK_SERVICE_HOST_IP=${host_ip}
 export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8889/v1/retrievaltool"
 export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
-export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6008/v1/dataprep/get"
-export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6009/v1/dataprep/delete"
+export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/get"
+export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/delete"
 
-echo ${WORKER_RAG_AGENT_PORT} > ${WORKPATH}/WORKER_RAG_AGENT_PORT_tmp
-echo ${WORKER_SQL_AGENT_PORT} > ${WORKPATH}/WORKER_SQL_AGENT_PORT_tmp
-echo ${SUPERVISOR_REACT_AGENT_PORT} > ${WORKPATH}/SUPERVISOR_REACT_AGENT_PORT_tmp
-echo ${CRAG_SERVER_PORT} > ${WORKPATH}/CRAG_SERVER_PORT_tmp
-
-echo "Downloading chinook data..."
-echo Y | rm -R chinook-database
-git clone https://github.com/lerocha/chinook-database.git
-echo Y | rm -R ../../../../../AgentQnA/tests/Chinook_Sqlite.sqlite
-cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite ../../../../../AgentQnA/tests
-
-docker compose -f ../../../../../DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml up -d
 docker compose -f compose.yaml up -d
-
-n=0
-until [[ "$n" -ge 100 ]]; do
-    docker logs tgi-service > ${WORKPATH}/tgi_service_start.log
-    if grep -q Connected ${WORKPATH}/tgi_service_start.log; then
-        break
-    fi
-    sleep 10s
-    n=$((n+1))
-done
-
-echo "Starting CRAG server"
-docker run -d --runtime=runc --name=kdd-cup-24-crag-service -p=${CRAG_SERVER_PORT}:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0

AgentQnA/docker_compose/amd/gpu/rocm/launch_agent_service_vllm_rocm.sh

@@ -1,88 +0,0 @@
-# Copyright (C) 2024 Advanced Micro Devices, Inc.
-# SPDX-License-Identifier: Apache-2.0
-
-# Before start script:
-# export host_ip="your_host_ip_or_host_name"
-# export HUGGINGFACEHUB_API_TOKEN="your_huggingface_api_token"
-# export LANGCHAIN_API_KEY="your_langchain_api_key"
-# export LANGCHAIN_TRACING_V2=""
-
-# Set server hostname or IP address
-export ip_address=${host_ip}
-
-# Set services IP ports
-export VLLM_SERVICE_PORT="18110"
-export WORKER_RAG_AGENT_PORT="18111"
-export WORKER_SQL_AGENT_PORT="18112"
-export SUPERVISOR_REACT_AGENT_PORT="18113"
-export CRAG_SERVER_PORT="18114"
-
-export WORKPATH=$(dirname "$PWD")
-export WORKDIR=${WORKPATH}/../../../
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export VLLM_LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-export HF_CACHE_DIR="./data"
-export MODEL_CACHE="./data"
-export TOOLSET_PATH=${WORKPATH}/../../../tools/
-export recursion_limit_worker=12
-export LLM_ENDPOINT_URL=http://${ip_address}:${VLLM_SERVICE_PORT}
-export LLM_MODEL_ID=${VLLM_LLM_MODEL_ID}
-export temperature=0.01
-export max_new_tokens=512
-export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
-export LANGCHAIN_API_KEY=${LANGCHAIN_API_KEY}
-export LANGCHAIN_TRACING_V2=${LANGCHAIN_TRACING_V2}
-export db_name=Chinook
-export db_path="sqlite:////home/user/chinook-db/Chinook_Sqlite.sqlite"
-export recursion_limit_worker=12
-export recursion_limit_supervisor=10
-export CRAG_SERVER=http://${ip_address}:${CRAG_SERVER_PORT}
-export WORKER_AGENT_URL="http://${ip_address}:${WORKER_RAG_AGENT_PORT}/v1/chat/completions"
-export SQL_AGENT_URL="http://${ip_address}:${WORKER_SQL_AGENT_PORT}/v1/chat/completions"
-export HF_CACHE_DIR=${HF_CACHE_DIR}
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export no_proxy=${no_proxy}
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006"
-export TEI_RERANKING_ENDPOINT="http://${host_ip}:8808"
-export REDIS_URL="redis://${host_ip}:6379"
-export INDEX_NAME="rag-redis"
-export RERANK_TYPE="tei"
-export MEGA_SERVICE_HOST_IP=${host_ip}
-export EMBEDDING_SERVICE_HOST_IP=${host_ip}
-export RETRIEVER_SERVICE_HOST_IP=${host_ip}
-export RERANK_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8889/v1/retrievaltool"
-export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
-export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6008/v1/dataprep/get"
-export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6009/v1/dataprep/delete"
-
-echo ${WORKER_RAG_AGENT_PORT} > ${WORKPATH}/WORKER_RAG_AGENT_PORT_tmp
-echo ${WORKER_SQL_AGENT_PORT} > ${WORKPATH}/WORKER_SQL_AGENT_PORT_tmp
-echo ${SUPERVISOR_REACT_AGENT_PORT} > ${WORKPATH}/SUPERVISOR_REACT_AGENT_PORT_tmp
-echo ${CRAG_SERVER_PORT} > ${WORKPATH}/CRAG_SERVER_PORT_tmp
-
-echo "Downloading chinook data..."
-echo Y | rm -R chinook-database
-git clone https://github.com/lerocha/chinook-database.git
-echo Y | rm -R ../../../../../AgentQnA/tests/Chinook_Sqlite.sqlite
-cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite ../../../../../AgentQnA/tests
-
-docker compose -f ../../../../../DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml up -d
-docker compose -f compose_vllm.yaml up -d
-
-n=0
-until [[ "$n" -ge 500 ]]; do
-    docker logs vllm-service >& "${WORKPATH}"/vllm-service_start.log
-    if grep -q "Application startup complete" "${WORKPATH}"/vllm-service_start.log; then
-        break
-    fi
-    sleep 20s
-    n=$((n+1))
-done
-
-echo "Starting CRAG server"
-docker run -d --runtime=runc --name=kdd-cup-24-crag-service -p=${CRAG_SERVER_PORT}:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0

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

@@ -6,7 +6,7 @@
 WORKPATH=$(dirname "$PWD")/..
 export ip_address=${host_ip}
 export HUGGINGFACEHUB_API_TOKEN=${your_hf_api_token}
-export AGENTQNA_TGI_IMAGE=ghcr.io/huggingface/text-generation-inference:2.4.1-rocm
+export AGENTQNA_TGI_IMAGE=ghcr.io/huggingface/text-generation-inference:2.3.1-rocm
 export AGENTQNA_TGI_SERVICE_PORT="19001"
 
 # LLM related environment variables
@@ -14,7 +14,7 @@ export AGENTQNA_CARD_ID="card1"
 export AGENTQNA_RENDER_ID="renderD136"
 export HF_CACHE_DIR=${HF_CACHE_DIR}
 ls $HF_CACHE_DIR
-export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
+export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct"
 export NUM_SHARDS=4
 export LLM_ENDPOINT_URL="http://${ip_address}:${AGENTQNA_TGI_SERVICE_PORT}"
 export temperature=0.01
@@ -44,19 +44,3 @@ export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8889/v1/retrievaltool"
 export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
 export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/get"
 export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/delete"
-
-echo "Removing chinook data..."
-echo Y | rm -R chinook-database
-if [ -d "chinook-database" ]; then
-    rm -rf chinook-database
-fi
-echo "Chinook data removed!"
-
-echo "Stopping CRAG server"
-docker rm kdd-cup-24-crag-service --force
-
-echo "Stopping Agent services"
-docker compose -f compose.yaml down
-
-echo "Stopping Retrieval services"
-docker compose -f ../../../../../DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml down

AgentQnA/docker_compose/amd/gpu/rocm/stop_agent_service_vllm_rocm.sh

@@ -1,84 +0,0 @@
-# Copyright (C) 2024 Advanced Micro Devices, Inc.
-# SPDX-License-Identifier: Apache-2.0
-
-
-# Before start script:
-# export host_ip="your_host_ip_or_host_name"
-# export HUGGINGFACEHUB_API_TOKEN="your_huggingface_api_token"
-# export LANGCHAIN_API_KEY="your_langchain_api_key"
-# export LANGCHAIN_TRACING_V2=""
-
-# Set server hostname or IP address
-export ip_address=${host_ip}
-
-# Set services IP ports
-export VLLM_SERVICE_PORT="18110"
-export WORKER_RAG_AGENT_PORT="18111"
-export WORKER_SQL_AGENT_PORT="18112"
-export SUPERVISOR_REACT_AGENT_PORT="18113"
-export CRAG_SERVER_PORT="18114"
-
-export WORKPATH=$(dirname "$PWD")
-export WORKDIR=${WORKPATH}/../../../
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export VLLM_LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-export HF_CACHE_DIR="./data"
-export MODEL_CACHE="./data"
-export TOOLSET_PATH=${WORKPATH}/../../../tools/
-export recursion_limit_worker=12
-export LLM_ENDPOINT_URL=http://${ip_address}:${VLLM_SERVICE_PORT}
-export LLM_MODEL_ID=${VLLM_LLM_MODEL_ID}
-export temperature=0.01
-export max_new_tokens=512
-export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
-export LANGCHAIN_API_KEY=${LANGCHAIN_API_KEY}
-export LANGCHAIN_TRACING_V2=${LANGCHAIN_TRACING_V2}
-export db_name=Chinook
-export db_path="sqlite:////home/user/chinook-db/Chinook_Sqlite.sqlite"
-export recursion_limit_worker=12
-export recursion_limit_supervisor=10
-export CRAG_SERVER=http://${ip_address}:${CRAG_SERVER_PORT}
-export WORKER_AGENT_URL="http://${ip_address}:${WORKER_RAG_AGENT_PORT}/v1/chat/completions"
-export SQL_AGENT_URL="http://${ip_address}:${WORKER_SQL_AGENT_PORT}/v1/chat/completions"
-export HF_CACHE_DIR=${HF_CACHE_DIR}
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export no_proxy=${no_proxy}
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006"
-export TEI_RERANKING_ENDPOINT="http://${host_ip}:8808"
-export REDIS_URL="redis://${host_ip}:6379"
-export INDEX_NAME="rag-redis"
-export RERANK_TYPE="tei"
-export MEGA_SERVICE_HOST_IP=${host_ip}
-export EMBEDDING_SERVICE_HOST_IP=${host_ip}
-export RETRIEVER_SERVICE_HOST_IP=${host_ip}
-export RERANK_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8889/v1/retrievaltool"
-export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
-export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6008/v1/dataprep/get"
-export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6009/v1/dataprep/delete"
-
-echo ${WORKER_RAG_AGENT_PORT} > ${WORKPATH}/WORKER_RAG_AGENT_PORT_tmp
-echo ${WORKER_SQL_AGENT_PORT} > ${WORKPATH}/WORKER_SQL_AGENT_PORT_tmp
-echo ${SUPERVISOR_REACT_AGENT_PORT} > ${WORKPATH}/SUPERVISOR_REACT_AGENT_PORT_tmp
-echo ${CRAG_SERVER_PORT} > ${WORKPATH}/CRAG_SERVER_PORT_tmp
-
-echo "Removing chinook data..."
-echo Y | rm -R chinook-database
-if [ -d "chinook-database" ]; then
-    rm -rf chinook-database
-fi
-echo "Chinook data removed!"
-
-echo "Stopping CRAG server"
-docker rm kdd-cup-24-crag-service --force
-
-echo "Stopping Agent services"
-docker compose -f compose_vllm.yaml down
-
-echo "Stopping Retrieval services"
-docker compose -f ../../../../../DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml down

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

@@ -1,3 +1,123 @@
 # Single node on-prem deployment with Docker Compose on Xeon Scalable processors
 
-This example showcases a hierarchical multi-agent system for question-answering applications. To deploy the example on Xeon, OpenAI LLM models via API calls are used. For instructions, refer to the deployment guide [here](../../../../README.md).
+This example showcases a hierarchical multi-agent system for question-answering applications. We deploy the example on Xeon. For LLMs, we use OpenAI models via API calls. For instructions on using open-source LLMs, please refer to the deployment guide [here](../../../../README.md).
+
+## Deployment with docker
+
+1. First, clone this repo.
+   ```
+   export WORKDIR=<your-work-directory>
+   cd $WORKDIR
+   git clone https://github.com/opea-project/GenAIExamples.git
+   ```
+2. Set up environment for this example </br>
+
+   ```
+   # Example: host_ip="192.168.1.1" or export host_ip="External_Public_IP"
+   export host_ip=$(hostname -I | awk '{print $1}')
+   # if you are in a proxy environment, also set the proxy-related environment variables
+   export http_proxy="Your_HTTP_Proxy"
+   export https_proxy="Your_HTTPs_Proxy"
+   # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
+   export no_proxy="Your_No_Proxy"
+
+   export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
+   #OPANAI_API_KEY if you want to use OpenAI models
+   export OPENAI_API_KEY=<your-openai-key>
+   ```
+
+3. Deploy the retrieval tool (i.e., DocIndexRetriever mega-service)
+
+   First, launch the mega-service.
+
+   ```
+   cd $WORKDIR/GenAIExamples/AgentQnA/retrieval_tool
+   bash launch_retrieval_tool.sh
+   ```
+
+   Then, ingest data into the vector database. Here we provide an example. You can ingest your own data.
+
+   ```
+   bash run_ingest_data.sh
+   ```
+
+4. Prepare SQL database
+   In this example, we will use the SQLite database provided in the [TAG-Bench](https://github.com/TAG-Research/TAG-Bench/tree/main). Run the commands below.
+
+   ```
+   # Download data
+   cd $WORKDIR
+   git clone https://github.com/TAG-Research/TAG-Bench.git
+   cd TAG-Bench/setup
+   chmod +x get_dbs.sh
+   ./get_dbs.sh
+   ```
+
+5. Launch Tool service
+   In this example, we will use some of the mock APIs provided in the Meta CRAG KDD Challenge to demonstrate the benefits of gaining additional context from mock knowledge graphs.
+   ```
+   docker run -d -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
+   ```
+6. Launch multi-agent system
+
+   The configurations of the supervisor agent and the worker agents are defined in the docker-compose yaml file. We currently use openAI GPT-4o-mini as LLM.
+
+   ```
+   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon
+   bash launch_agent_service_openai.sh
+   ```
+
+7. [Optional] Build `Agent` docker image if pulling images failed.
+
+   ```
+   git clone https://github.com/opea-project/GenAIComps.git
+   cd GenAIComps
+   docker build -t opea/agent:latest -f comps/agent/src/Dockerfile .
+   ```
+
+## Validate services
+
+First look at logs of the agent docker containers:
+
+```
+# worker RAG agent
+docker logs rag-agent-endpoint
+
+# worker SQL agent
+docker logs sql-agent-endpoint
+```
+
+```
+# supervisor agent
+docker logs react-agent-endpoint
+```
+
+You should see something like "HTTP server setup successful" if the docker containers are started successfully.</p>
+
+Second, validate worker RAG agent:
+
+```
+curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "Michael Jackson song Thriller"
+    }'
+```
+
+Third, validate worker SQL agent:
+
+```
+curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "How many employees are in the company?"
+    }'
+```
+
+Finally, validate supervisor agent:
+
+```
+curl http://${host_ip}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "How many albums does Iron Maiden have?"
+    }'
+```
+
+## How to register your own tools with agent
+
+You can take a look at the tools yaml and python files in this example. For more details, please refer to the "Provide your own tools" section in the instructions [here](https://github.com/opea-project/GenAIComps/tree/main/comps/agent/src/README.md).

AgentQnA/docker_compose/intel/cpu/xeon/compose_openai.yaml

@@ -13,7 +13,6 @@ services:
     environment:
       ip_address: ${ip_address}
       strategy: rag_agent
-      with_memory: false
       recursion_limit: ${recursion_limit_worker}
       llm_engine: openai
       OPENAI_API_KEY: ${OPENAI_API_KEY}
@@ -36,17 +35,17 @@ services:
     image: opea/agent:latest
     container_name: sql-agent-endpoint
     volumes:
-      - ${WORKDIR}/GenAIExamples/AgentQnA/tests:/home/user/chinook-db # SQL database
+      - ${WORKDIR}/TAG-Bench/:/home/user/TAG-Bench # SQL database
     ports:
       - "9096:9096"
     ipc: host
     environment:
       ip_address: ${ip_address}
       strategy: sql_agent
-      with_memory: false
       db_name: ${db_name}
       db_path: ${db_path}
       use_hints: false
+      hints_file: /home/user/TAG-Bench/${db_name}_hints.csv
       recursion_limit: ${recursion_limit_worker}
       llm_engine: openai
       OPENAI_API_KEY: ${OPENAI_API_KEY}
@@ -65,7 +64,6 @@ services:
     container_name: react-agent-endpoint
     depends_on:
       - worker-rag-agent
-      - worker-sql-agent
     volumes:
       - ${TOOLSET_PATH}:/home/user/tools/
     ports:
@@ -73,15 +71,14 @@ services:
     ipc: host
     environment:
       ip_address: ${ip_address}
-      strategy: react_llama
-      with_memory: true
+      strategy: react_langgraph
       recursion_limit: ${recursion_limit_supervisor}
       llm_engine: openai
       OPENAI_API_KEY: ${OPENAI_API_KEY}
       model: ${model}
       temperature: ${temperature}
       max_new_tokens: ${max_new_tokens}
-      stream: true
+      stream: false
       tools: /home/user/tools/supervisor_agent_tools.yaml
       require_human_feedback: false
       no_proxy: ${no_proxy}
@@ -92,23 +89,4 @@ services:
       LANGCHAIN_PROJECT: "opea-supervisor-agent-service"
       CRAG_SERVER: $CRAG_SERVER
       WORKER_AGENT_URL: $WORKER_AGENT_URL
-      SQL_AGENT_URL: $SQL_AGENT_URL
       port: 9090
-  mock-api:
-    image: docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
-    container_name: mock-api
-    ports:
-      - "8080:8000"
-    ipc: host
-  agent-ui:
-    image: opea/agent-ui
-    container_name: agent-ui
-    volumes:
-      - ${WORKDIR}/GenAIExamples/AgentQnA/ui/svelte/.env:/home/user/svelte/.env # test db
-    ports:
-      - "5173:5173"
-    ipc: host
-
-networks:
-  default:
-    driver: bridge

AgentQnA/docker_compose/intel/cpu/xeon/launch_agent_service_openai.sh

@@ -0,0 +1,22 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+pushd "../../../../../" > /dev/null
+source .set_env.sh
+popd > /dev/null
+export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
+export ip_address=$(hostname -I | awk '{print $1}')
+export recursion_limit_worker=12
+export recursion_limit_supervisor=10
+export model="gpt-4o-mini-2024-07-18"
+export temperature=0
+export max_new_tokens=4096
+export OPENAI_API_KEY=${OPENAI_API_KEY}
+export WORKER_AGENT_URL="http://${ip_address}:9095/v1/chat/completions"
+export SQL_AGENT_URL="http://${ip_address}:9096/v1/chat/completions"
+export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
+export CRAG_SERVER=http://${ip_address}:8080
+export db_name=california_schools
+export db_path="sqlite:////home/user/TAG-Bench/dev_folder/dev_databases/${db_name}/${db_name}.sqlite"
+
+docker compose -f compose_openai.yaml up -d

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

@@ -1,57 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-pushd "../../../../../" > /dev/null
-source .set_env.sh
-popd > /dev/null
-
-if [[ -z "${WORKDIR}" ]]; then
-	echo "Please set WORKDIR environment variable"
-	exit 0
-fi
-echo "WORKDIR=${WORKDIR}"
-export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
-export ip_address=$(hostname -I | awk '{print $1}')
-export recursion_limit_worker=12
-export recursion_limit_supervisor=10
-export model="gpt-4o-mini-2024-07-18"
-export temperature=0
-export max_new_tokens=4096
-export OPENAI_API_KEY=${OPENAI_API_KEY}
-export WORKER_AGENT_URL="http://${ip_address}:9095/v1/chat/completions"
-export SQL_AGENT_URL="http://${ip_address}:9096/v1/chat/completions"
-export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
-export CRAG_SERVER=http://${ip_address}:8080
-export db_name=Chinook
-export db_path="sqlite:////home/user/chinook-db/Chinook_Sqlite.sqlite"
-
-if [ ! -f $WORKDIR/GenAIExamples/AgentQnA/tests/Chinook_Sqlite.sqlite ]; then
-    echo "Download Chinook_Sqlite!"
-    wget  -O $WORKDIR/GenAIExamples/AgentQnA/tests/Chinook_Sqlite.sqlite  https://github.com/lerocha/chinook-database/releases/download/v1.4.5/Chinook_Sqlite.sqlite
-fi
-
-# retriever
-export host_ip=$(hostname -I | awk '{print $1}')
-export HF_CACHE_DIR=${HF_CACHE_DIR}
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export no_proxy=${no_proxy}
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006"
-export TEI_RERANKING_ENDPOINT="http://${host_ip}:8808"
-export REDIS_URL="redis://${host_ip}:6379"
-export INDEX_NAME="rag-redis"
-export RERANK_TYPE="tei"
-export MEGA_SERVICE_HOST_IP=${host_ip}
-export EMBEDDING_SERVICE_HOST_IP=${host_ip}
-export RETRIEVER_SERVICE_HOST_IP=${host_ip}
-export RERANK_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8889/v1/retrievaltool"
-export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
-export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6008/v1/dataprep/get"
-export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6009/v1/dataprep/delete"
-
-
-export no_proxy="$no_proxy,rag-agent-endpoint,sql-agent-endpoint,react-agent-endpoint,agent-ui"

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

@@ -1,3 +1,147 @@
 # Single node on-prem deployment AgentQnA on Gaudi
 
-This example showcases a hierarchical multi-agent system for question-answering applications. To deploy the example on Gaudi using open-source LLMs, refer to the deployment guide [here](../../../../README.md).
+This example showcases a hierarchical multi-agent system for question-answering applications. We deploy the example on Gaudi using open-source LLMs.
+For more details, please refer to the deployment guide [here](../../../../README.md).
+
+## Deployment with docker
+
+1. First, clone this repo.
+   ```
+   export WORKDIR=<your-work-directory>
+   cd $WORKDIR
+   git clone https://github.com/opea-project/GenAIExamples.git
+   ```
+2. Set up environment for this example </br>
+
+   ```
+   # Example: host_ip="192.168.1.1" or export host_ip="External_Public_IP"
+   export host_ip=$(hostname -I | awk '{print $1}')
+   # if you are in a proxy environment, also set the proxy-related environment variables
+   export http_proxy="Your_HTTP_Proxy"
+   export https_proxy="Your_HTTPs_Proxy"
+   # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
+   export no_proxy="Your_No_Proxy"
+
+   export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
+   # for using open-source llms
+   export HUGGINGFACEHUB_API_TOKEN=<your-HF-token>
+   # Example export HF_CACHE_DIR=$WORKDIR so that no need to redownload every time
+   export HF_CACHE_DIR=<directory-where-llms-are-downloaded>
+
+   ```
+
+3. Deploy the retrieval tool (i.e., DocIndexRetriever mega-service)
+
+   First, launch the mega-service.
+
+   ```
+   cd $WORKDIR/GenAIExamples/AgentQnA/retrieval_tool
+   bash launch_retrieval_tool.sh
+   ```
+
+   Then, ingest data into the vector database. Here we provide an example. You can ingest your own data.
+
+   ```
+   bash run_ingest_data.sh
+   ```
+
+4. Prepare SQL database
+   In this example, we will use the Chinook SQLite database. Run the commands below.
+
+   ```
+   # Download data
+   cd $WORKDIR
+   git clone https://github.com/lerocha/chinook-database.git
+   cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite $WORKDIR/GenAIExamples/AgentQnA/tests/
+   ```
+
+5. Launch Tool service
+   In this example, we will use some of the mock APIs provided in the Meta CRAG KDD Challenge to demonstrate the benefits of gaining additional context from mock knowledge graphs.
+   ```
+   docker run -d -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
+   ```
+6. Launch multi-agent system
+
+   On Gaudi2 we will serve `meta-llama/Meta-Llama-3.1-70B-Instruct` using vllm.
+
+   First build vllm-gaudi docker image.
+
+   ```bash
+   cd $WORKDIR
+   git clone https://github.com/vllm-project/vllm.git
+   cd ./vllm
+   git checkout v0.6.6
+   docker build --no-cache -f Dockerfile.hpu -t opea/vllm-gaudi:latest --shm-size=128g . --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy
+   ```
+
+   Then launch vllm on Gaudi2 with the command below.
+
+   ```bash
+   vllm_port=8086
+   model="meta-llama/Meta-Llama-3.1-70B-Instruct"
+   docker run -d --runtime=habana --rm --name "vllm-gaudi-server" -e HABANA_VISIBLE_DEVICES=0,1,2,3 -p $vllm_port:8000 -v $vllm_volume:/data -e HF_TOKEN=$HF_TOKEN -e HUGGING_FACE_HUB_TOKEN=$HF_TOKEN -e HF_HOME=/data -e OMPI_MCA_btl_vader_single_copy_mechanism=none -e PT_HPU_ENABLE_LAZY_COLLECTIVES=true -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e no_proxy=$no_proxy -e VLLM_SKIP_WARMUP=true --cap-add=sys_nice --ipc=host opea/vllm-gaudi:latest --model ${model} --max-seq-len-to-capture 16384 --tensor-parallel-size 4
+   ```
+
+   Then launch Agent microservices.
+
+   ```bash
+   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/
+   bash launch_agent_service_gaudi.sh
+   ```
+
+7. [Optional] Build `Agent` docker image if pulling images failed.
+
+   If docker image pulling failed in Step 6 above, build the agent docker image with the commands below. After image build, try Step 6 again.
+
+   ```
+   git clone https://github.com/opea-project/GenAIComps.git
+   cd GenAIComps
+   docker build -t opea/agent:latest -f comps/agent/src/Dockerfile .
+   ```
+
+## Validate services
+
+First look at logs of the agent docker containers:
+
+```
+# worker RAG agent
+docker logs rag-agent-endpoint
+
+# worker SQL agent
+docker logs sql-agent-endpoint
+```
+
+```
+# supervisor agent
+docker logs react-agent-endpoint
+```
+
+You should see something like "HTTP server setup successful" if the docker containers are started successfully.</p>
+
+Second, validate worker RAG agent:
+
+```
+curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "Michael Jackson song Thriller"
+    }'
+```
+
+Third, validate worker SQL agent:
+
+```
+curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "How many employees are in the company?"
+    }'
+```
+
+Finally, validate supervisor agent:
+
+```
+curl http://${host_ip}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "messages": "How many albums does Iron Maiden have?"
+    }'
+```
+
+## How to register your own tools with agent
+
+You can take a look at the tools yaml and python files in this example. For more details, please refer to the "Provide your own tools" section in the instructions [here](https://github.com/opea-project/GenAIComps/tree/main/comps/agent/src/README.md).

AgentQnA/docker_compose/intel/hpu/gaudi/compose.telemetry.yaml

@@ -1,93 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-services:
-  tei-embedding-service:
-    command: --model-id ${EMBEDDING_MODEL_ID} --auto-truncate --otlp-endpoint $OTEL_EXPORTER_OTLP_TRACES_ENDPOINT
-  tei-reranking-service:
-    command: --model-id ${RERANK_MODEL_ID} --auto-truncate --otlp-endpoint $OTEL_EXPORTER_OTLP_TRACES_ENDPOINT
-  jaeger:
-    image: jaegertracing/all-in-one:1.67.0
-    container_name: jaeger
-    ports:
-      - "16686:16686"
-      - "4317:4317"
-      - "4318:4318"
-      - "9411:9411"
-    ipc: host
-    environment:
-      no_proxy: ${no_proxy}
-      http_proxy: ${http_proxy}
-      https_proxy: ${https_proxy}
-      COLLECTOR_ZIPKIN_HOST_PORT: 9411
-    restart: unless-stopped
-  prometheus:
-    image: prom/prometheus:v2.52.0
-    container_name: prometheus
-    user: root
-    volumes:
-      - ./prometheus.yaml:/etc/prometheus/prometheus.yaml
-      - ./prometheus_data:/prometheus
-    command:
-      - '--config.file=/etc/prometheus/prometheus.yaml'
-    ports:
-      - '9091:9090'
-    ipc: host
-    restart: unless-stopped
-  grafana:
-    image: grafana/grafana:11.0.0
-    container_name: grafana
-    volumes:
-      - ./grafana_data:/var/lib/grafana
-      - ./grafana/dashboards:/var/lib/grafana/dashboards
-      - ./grafana/provisioning:/etc/grafana/provisioning
-    user: root
-    environment:
-      GF_SECURITY_ADMIN_PASSWORD: admin
-      GF_RENDERING_CALLBACK_URL: http://grafana:3000/
-      GF_LOG_FILTERS: rendering:debug
-    depends_on:
-      - prometheus
-    ports:
-      - '3000:3000'
-    ipc: host
-    restart: unless-stopped
-  node-exporter:
-    image: prom/node-exporter
-    container_name: node-exporter
-    volumes:
-      - /proc:/host/proc:ro
-      - /sys:/host/sys:ro
-      - /:/rootfs:ro
-    command:
-      - '--path.procfs=/host/proc'
-      - '--path.sysfs=/host/sys'
-      - --collector.filesystem.ignored-mount-points
-      - "^/(sys|proc|dev|host|etc|rootfs/var/lib/docker/containers|rootfs/var/lib/docker/overlay2|rootfs/run/docker/netns|rootfs/var/lib/docker/aufs)($$|/)"
-    ports:
-      - 9100:9100
-    restart: always
-    deploy:
-      mode: global
-  gaudi-exporter:
-    image: vault.habana.ai/gaudi-metric-exporter/metric-exporter:1.19.2-32
-    container_name: gaudi-exporter
-    volumes:
-      - /proc:/host/proc:ro
-      - /sys:/host/sys:ro
-      - /:/rootfs:ro
-      - /dev:/dev
-    ports:
-      - 41612:41611
-    restart: always
-    deploy:
-      mode: global
-  worker-rag-agent:
-    environment:
-      - TELEMETRY_ENDPOINT=${TELEMETRY_ENDPOINT}
-  worker-sql-agent:
-    environment:
-      - TELEMETRY_ENDPOINT=${TELEMETRY_ENDPOINT}
-  supervisor-react-agent:
-    environment:
-      - TELEMETRY_ENDPOINT=${TELEMETRY_ENDPOINT}

AgentQnA/docker_compose/intel/hpu/gaudi/compose.webtool.yaml

@@ -1,9 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-services:
-  supervisor-react-agent:
-    environment:
-      - tools=/home/user/tools/supervisor_agent_webtools.yaml
-      - GOOGLE_CSE_ID=${GOOGLE_CSE_ID}
-      - GOOGLE_API_KEY=${GOOGLE_API_KEY}

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

@@ -13,7 +13,6 @@ services:
     environment:
       ip_address: ${ip_address}
       strategy: rag_agent_llama
-      with_memory: false
       recursion_limit: ${recursion_limit_worker}
       llm_engine: vllm
       HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
@@ -44,7 +43,6 @@ services:
     environment:
       ip_address: ${ip_address}
       strategy: sql_agent_llama
-      with_memory: false
       db_name: ${db_name}
       db_path: ${db_path}
       use_hints: false
@@ -76,7 +74,6 @@ services:
     environment:
       ip_address: ${ip_address}
       strategy: react_llama
-      with_memory: true
       recursion_limit: ${recursion_limit_supervisor}
       llm_engine: vllm
       HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
@@ -84,7 +81,7 @@ services:
       model: ${LLM_MODEL_ID}
       temperature: ${temperature}
       max_new_tokens: ${max_new_tokens}
-      stream: true
+      stream: false
       tools: /home/user/tools/supervisor_agent_tools.yaml
       require_human_feedback: false
       no_proxy: ${no_proxy}
@@ -97,47 +94,3 @@ services:
       WORKER_AGENT_URL: $WORKER_AGENT_URL
       SQL_AGENT_URL: $SQL_AGENT_URL
       port: 9090
-  mock-api:
-    image: docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
-    container_name: mock-api
-    ports:
-      - "8080:8000"
-    ipc: host
-  agent-ui:
-    image: opea/agent-ui
-    container_name: agent-ui
-    volumes:
-      - ${WORKDIR}/GenAIExamples/AgentQnA/ui/svelte/.env:/home/user/svelte/.env
-    environment:
-      host_ip: ${host_ip}
-    ports:
-      - "5173:5173"
-    ipc: host
-  vllm-service:
-    image: ${REGISTRY:-opea}/vllm-gaudi:${TAG:-latest}
-    container_name: vllm-gaudi-server
-    ports:
-      - "8086:8000"
-    volumes:
-      - "./data:/data"
-    environment:
-      no_proxy: ${no_proxy}
-      http_proxy: ${http_proxy}
-      https_proxy: ${https_proxy}
-      HF_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
-      HABANA_VISIBLE_DEVICES: all
-      OMPI_MCA_btl_vader_single_copy_mechanism: none
-      LLM_MODEL_ID: ${LLM_MODEL_ID}
-      VLLM_TORCH_PROFILER_DIR: "/mnt"
-      VLLM_SKIP_WARMUP: true
-      PT_HPU_ENABLE_LAZY_COLLECTIVES: true
-    healthcheck:
-      test: ["CMD-SHELL", "curl -f http://$host_ip:8086/health || exit 1"]
-      interval: 10s
-      timeout: 10s
-      retries: 100
-    runtime: habana
-    cap_add:
-      - SYS_NICE
-    ipc: host
-    command: --model $LLM_MODEL_ID --tensor-parallel-size 4 --host 0.0.0.0 --port 8000 --block-size 128 --max-num-seqs 256 --max-seq_len-to-capture 16384

AgentQnA/docker_compose/intel/hpu/gaudi/grafana/dashboards/download_opea_dashboard.sh

@@ -1,10 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-rm *.json
-wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/chatqna_megaservice_grafana.json
-mv chatqna_megaservice_grafana.json agentqna_microervices_grafana.json
-wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/vllm_grafana.json
-wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/tgi_grafana.json
-wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/node_grafana.json
-wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/gaudi_grafana.json

AgentQnA/docker_compose/intel/hpu/gaudi/grafana/provisioning/dashboards/local.yaml

@@ -1,14 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-apiVersion: 1
-
-providers:
-- name: 'default'
-  orgId: 1
-  folder: ''
-  type: file
-  disableDeletion: false
-  updateIntervalSeconds: 10 #how often Grafana will scan for changed dashboards
-  options:
-    path: /var/lib/grafana/dashboards

AgentQnA/docker_compose/intel/hpu/gaudi/grafana/provisioning/datasources/datasource.yml

@@ -1,54 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-# config file version
-apiVersion: 1
-
-# list of datasources that should be deleted from the database
-deleteDatasources:
-  - name: Prometheus
-    orgId: 1
-
-# list of datasources to insert/update depending
-# what's available in the database
-datasources:
-  # <string, required> name of the datasource. Required
-- name: Prometheus
-  # <string, required> datasource type. Required
-  type: prometheus
-  # <string, required> access mode. direct or proxy. Required
-  access: proxy
-  # <int> org id. will default to orgId 1 if not specified
-  orgId: 1
-  # <string> url
-  url: http://prometheus:9090
-  # <string> database password, if used
-  password:
-  # <string> database user, if used
-  user:
-  # <string> database name, if used
-  database:
-  # <bool> enable/disable basic auth
-  basicAuth: false
-  # <string> basic auth username, if used
-  basicAuthUser:
-  # <string> basic auth password, if used
-  basicAuthPassword:
-  # <bool> enable/disable with credentials headers
-  withCredentials:
-  # <bool> mark as default datasource. Max one per org
-  isDefault: true
-  # <map> fields that will be converted to json and stored in json_data
-  jsonData:
-     httpMethod: GET
-     graphiteVersion: "1.1"
-     tlsAuth: false
-     tlsAuthWithCACert: false
-  # <string> json object of data that will be encrypted.
-  secureJsonData:
-    tlsCACert: "..."
-    tlsClientCert: "..."
-    tlsClientKey: "..."
-  version: 1
-  # <bool> allow users to edit datasources from the UI.
-  editable: true

AgentQnA/docker_compose/intel/hpu/gaudi/launch_agent_service_gaudi.sh

@@ -0,0 +1,36 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+pushd "../../../../../" > /dev/null
+source .set_env.sh
+popd > /dev/null
+WORKPATH=$(dirname "$PWD")/..
+# export WORKDIR=$WORKPATH/../../
+echo "WORKDIR=${WORKDIR}"
+export ip_address=$(hostname -I | awk '{print $1}')
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+
+# LLM related environment variables
+export HF_CACHE_DIR=${HF_CACHE_DIR}
+ls $HF_CACHE_DIR
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_MODEL_ID="meta-llama/Meta-Llama-3.1-70B-Instruct"
+export NUM_SHARDS=4
+export LLM_ENDPOINT_URL="http://${ip_address}:8086"
+export temperature=0
+export max_new_tokens=4096
+
+# agent related environment variables
+export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
+echo "TOOLSET_PATH=${TOOLSET_PATH}"
+export recursion_limit_worker=12
+export recursion_limit_supervisor=10
+export WORKER_AGENT_URL="http://${ip_address}:9095/v1/chat/completions"
+export SQL_AGENT_URL="http://${ip_address}:9096/v1/chat/completions"
+export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
+export CRAG_SERVER=http://${ip_address}:8080
+
+export db_name=Chinook
+export db_path="sqlite:////home/user/chinook-db/Chinook_Sqlite.sqlite"
+
+docker compose -f compose.yaml up -d

AgentQnA/docker_compose/intel/hpu/gaudi/launch_tgi_gaudi.sh

@@ -0,0 +1,25 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+# LLM related environment variables
+export HF_CACHE_DIR=${HF_CACHE_DIR}
+ls $HF_CACHE_DIR
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
+export LLM_MODEL_ID="meta-llama/Meta-Llama-3.1-70B-Instruct"
+export NUM_SHARDS=4
+
+docker compose -f tgi_gaudi.yaml up -d
+
+sleep 5s
+echo "Waiting tgi gaudi ready"
+n=0
+until [[ "$n" -ge 100 ]] || [[ $ready == true ]]; do
+    docker logs tgi-server &> tgi-gaudi-service.log
+    n=$((n+1))
+    if grep -q Connected tgi-gaudi-service.log; then
+        break
+    fi
+    sleep 5s
+done
+sleep 5s
+echo "Service started successfully"

AgentQnA/docker_compose/intel/hpu/gaudi/prometheus.yaml

@@ -1,55 +0,0 @@
-# Copyright (C) 2025 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-global:
-  scrape_interval: 5s
-  external_labels:
-    monitor: "my-monitor"
-scrape_configs:
-  - job_name: "prometheus"
-    static_configs:
-      - targets: ["prometheus:9090"]
-  - job_name: "vllm"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["vllm-gaudi-server:8000"]
-  - job_name: "tgi"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["tgi-gaudi-server:80"]
-  - job_name: "tei-embedding"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["tei-embedding-server:80"]
-  - job_name: "tei-reranking"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["tei-reranking-server:80"]
-  - job_name: "retriever"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["retriever:7000"]
-  - job_name: "dataprep-redis-service"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["dataprep-redis-service:5000"]
-  - job_name: "prometheus-node-exporter"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["node-exporter:9100"]
-  - job_name: "prometheus-gaudi-exporter"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["gaudi-exporter:41611"]
-  - job_name: "supervisor-react-agent"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["react-agent-endpoint:9090"]
-  - job_name: "worker-rag-agent"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["rag-agent-endpoint:9095"]
-  - job_name: "worker-sql-agent"
-    metrics_path: /metrics
-    static_configs:
-      - targets: ["sql-agent-endpoint:9096"]

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

@@ -1,72 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-pushd "../../../../../" > /dev/null
-source .set_env.sh
-popd > /dev/null
-WORKPATH=$(dirname "$PWD")/..
-# export WORKDIR=$WORKPATH/../../
-if [[ -z "${WORKDIR}" ]]; then
-	echo "Please set WORKDIR environment variable"
-	exit 0
-fi
-echo "WORKDIR=${WORKDIR}"
-export ip_address=$(hostname -I | awk '{print $1}')
-
-# LLM related environment variables
-export HF_CACHE_DIR=${HF_CACHE_DIR}
-ls $HF_CACHE_DIR
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export HF_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export LLM_MODEL_ID="meta-llama/Llama-3.3-70B-Instruct"
-export NUM_SHARDS=4
-export LLM_ENDPOINT_URL="http://${ip_address}:8086"
-export temperature=0
-export max_new_tokens=4096
-
-# agent related environment variables
-export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
-echo "TOOLSET_PATH=${TOOLSET_PATH}"
-export recursion_limit_worker=12
-export recursion_limit_supervisor=10
-export WORKER_AGENT_URL="http://${ip_address}:9095/v1/chat/completions"
-export SQL_AGENT_URL="http://${ip_address}:9096/v1/chat/completions"
-export RETRIEVAL_TOOL_URL="http://${ip_address}:8889/v1/retrievaltool"
-export CRAG_SERVER=http://${ip_address}:8080
-
-export db_name=Chinook
-export db_path="sqlite:////home/user/chinook-db/Chinook_Sqlite.sqlite"
-if [ ! -f $WORKDIR/GenAIExamples/AgentQnA/tests/Chinook_Sqlite.sqlite ]; then
-    echo "Download Chinook_Sqlite!"
-    wget  -O $WORKDIR/GenAIExamples/AgentQnA/tests/Chinook_Sqlite.sqlite  https://github.com/lerocha/chinook-database/releases/download/v1.4.5/Chinook_Sqlite.sqlite
-fi
-
-# configure agent ui
-echo "AGENT_URL = 'http://$ip_address:9090/v1/chat/completions'" | tee ${WORKDIR}/GenAIExamples/AgentQnA/ui/svelte/.env
-
-# retriever
-export host_ip=$(hostname -I | awk '{print $1}')
-export no_proxy=${no_proxy}
-export http_proxy=${http_proxy}
-export https_proxy=${https_proxy}
-export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006"
-export TEI_RERANKING_ENDPOINT="http://${host_ip}:8808"
-export REDIS_URL="redis://${host_ip}:6379"
-export INDEX_NAME="rag-redis"
-export RERANK_TYPE="tei"
-export MEGA_SERVICE_HOST_IP=${host_ip}
-export EMBEDDING_SERVICE_HOST_IP=${host_ip}
-export RETRIEVER_SERVICE_HOST_IP=${host_ip}
-export RERANK_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8889/v1/retrievaltool"
-export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
-export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6008/v1/dataprep/get"
-export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6009/v1/dataprep/delete"
-# Set OpenTelemetry Tracing Endpoint
-export JAEGER_IP=$(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 no_proxy="$no_proxy,rag-agent-endpoint,sql-agent-endpoint,react-agent-endpoint,agent-ui,vllm-gaudi-server,jaeger,grafana,prometheus,node-exporter,gaudi-exporter,127.0.0.1,localhost,0.0.0.0,$host_ip,,$JAEGER_IP"

AgentQnA/docker_compose/intel/hpu/gaudi/tgi_gaudi.yaml

@@ -3,7 +3,7 @@
 
 services:
   tgi-server:
-    image: ghcr.io/huggingface/tgi-gaudi:2.3.1
+    image: ghcr.io/huggingface/tgi-gaudi:2.0.6
     container_name: tgi-server
     ports:
       - "8085:80"

AgentQnA/docker_image_build/build.yaml

@@ -17,12 +17,3 @@ services:
       dockerfile: ./docker/Dockerfile
     extends: agent
     image: ${REGISTRY:-opea}/agent-ui:${TAG:-latest}
-  vllm-rocm:
-    build:
-      args:
-        http_proxy: ${http_proxy}
-        https_proxy: ${https_proxy}
-        no_proxy: ${no_proxy}
-      context: GenAIComps
-      dockerfile: comps/third_parties/vllm/src/Dockerfile.amd_gpu
-    image: ${REGISTRY:-opea}/vllm-rocm:${TAG:-latest}

AgentQnA/tests/_test_compose_openai_on_xeon.sh

@@ -20,30 +20,23 @@ function stop_agent_and_api_server() {
 
 function stop_retrieval_tool() {
     echo "Stopping Retrieval tool"
-    local RETRIEVAL_TOOL_PATH=$WORKPATH/../DocIndexRetriever
-    cd $RETRIEVAL_TOOL_PATH/docker_compose/intel/cpu/xeon/
-    container_list=$(cat compose.yaml | grep container_name | cut -d':' -f2)
-    for container_name in $container_list; do
-        cid=$(docker ps -aq --filter "name=$container_name")
-        echo "Stopping container $container_name"
-        if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
-    done
+    docker compose -f $WORKDIR/GenAIExamples/AgentQnA/retrieval_tool/docker/docker-compose-retrieval-tool.yaml down
 }
 
 echo "=================== #1 Building docker images===================="
-bash step1_build_images.sh
+bash 1_build_images.sh
 echo "=================== #1 Building docker images completed===================="
 
 echo "=================== #2 Start retrieval tool===================="
-bash step2_start_retrieval_tool.sh
+bash 2_start_retrieval_tool.sh
 echo "=================== #2 Retrieval tool started===================="
 
 echo "=================== #3 Ingest data and validate retrieval===================="
-bash step3_ingest_data_and_validate_retrieval.sh
+bash 3_ingest_data_and_validate_retrieval.sh
 echo "=================== #3 Data ingestion and validation completed===================="
 
 echo "=================== #4 Start agent and API server===================="
-bash step4_launch_and_validate_agent_openai.sh
+bash 4_launch_and_validate_agent_openai.sh
 echo "=================== #4 Agent test passed ===================="
 
 echo "=================== #5 Stop agent and API server===================="

AgentQnA/tests/step1_build_images.sh

@@ -22,7 +22,7 @@ function build_docker_images_for_retrieval_tool(){
     echo "Build all the images with --no-cache..."
     service_list="doc-index-retriever dataprep embedding retriever reranking"
     docker compose -f build.yaml build ${service_list} --no-cache
-    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.6
+    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
 
     docker images && sleep 1s
 }
@@ -42,8 +42,7 @@ function build_vllm_docker_image() {
         git clone https://github.com/HabanaAI/vllm-fork.git
     fi
     cd ./vllm-fork
-    VLLM_VER=$(git describe --tags "$(git rev-list --tags --max-count=1)")
-    git checkout ${VLLM_VER} &> /dev/null
+    git checkout v0.6.4.post2+Gaudi-1.19.0
     docker build --no-cache -f Dockerfile.hpu -t opea/vllm-gaudi:ci --shm-size=128g . --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy
     if [ $? -ne 0 ]; then
         echo "opea/vllm-gaudi:ci failed"

AgentQnA/tests/step1_build_images_rocm_vllm.sh

@@ -1,64 +0,0 @@
-#!/bin/bash
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-set -e
-export WORKPATH=$(dirname "$PWD")
-export WORKDIR=${WORKPATH}/../../
-echo "WORKDIR=${WORKDIR}"
-export ip_address=$(hostname -I | awk '{print $1}')
-
-
-function get_genai_comps() {
-    if [ ! -d "GenAIComps" ] ; then
-        git clone --depth 1 --branch ${opea_branch:-"main"} https://github.com/opea-project/GenAIComps.git
-    fi
-}
-
-
-function build_docker_images_for_retrieval_tool(){
-    cd $WORKPATH/../DocIndexRetriever/docker_image_build/
-    get_genai_comps
-    echo "Build all the images with --no-cache..."
-    service_list="doc-index-retriever dataprep embedding retriever reranking"
-    docker compose -f build.yaml build ${service_list} --no-cache
-    docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
-
-    docker images && sleep 3s
-}
-
-function build_agent_docker_image() {
-    cd $WORKPATH/docker_image_build/
-    get_genai_comps
-    echo "Build agent image with --no-cache..."
-    docker compose -f build.yaml build --no-cache
-
-    docker images && sleep 3s
-}
-
-#function build_vllm_docker_image() {
-#    echo "Building the vllm docker image"
-#    cd $WORKPATH/
-#    docker build --no-cache -t opea/llm-vllm-rocm:ci -f Dockerfile-vllm-rocm .
-#
-#    docker images && sleep 3s
-#}
-
-
-function main() {
-    echo "==================== Build docker images for retrieval tool ===================="
-    build_docker_images_for_retrieval_tool
-    echo "==================== Build docker images for retrieval tool completed ===================="
-
-    echo "==================== Build agent docker image ===================="
-    build_agent_docker_image
-    echo "==================== Build agent docker image completed ===================="
-
-#    echo "==================== Build vllm docker image ===================="
-#    build_vllm_docker_image
-#    echo "==================== Build vllm docker image completed ===================="
-
-    docker image ls | grep vllm
-}
-
-main

AgentQnA/tests/step2_start_retrieval_tool.sh

@@ -9,7 +9,7 @@ echo "WORKDIR=${WORKDIR}"
 export ip_address=$(hostname -I | awk '{print $1}')
 export host_ip=${ip_address}
 
-export HF_CACHE_DIR=${model_cache:-"$WORKDIR/hf_cache"}
+export HF_CACHE_DIR=$WORKDIR/hf_cache
 if [ ! -d "$HF_CACHE_DIR" ]; then
     echo "Creating HF_CACHE directory"
     mkdir -p "$HF_CACHE_DIR"

AgentQnA/tests/step2_start_retrieval_tool_rocm_vllm.sh

@@ -1,49 +0,0 @@
-#!/bin/bash
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-set -e
-WORKPATH=$(dirname "$PWD")
-export WORKDIR=$WORKPATH/../
-echo "WORKDIR=${WORKDIR}"
-export ip_address=$(hostname -I | awk '{print $1}')
-export host_ip=${ip_address}
-
-export HF_CACHE_DIR=$WORKPATH/hf_cache
-if [ ! -d "$HF_CACHE_DIR" ]; then
-    echo "Creating HF_CACHE directory"
-    mkdir -p "$HF_CACHE_DIR"
-fi
-
-function start_retrieval_tool() {
-    echo "Starting Retrieval tool"
-    cd $WORKPATH/../DocIndexRetriever/docker_compose/intel/cpu/xeon
-    host_ip=$(hostname -I | awk '{print $1}')
-    export HF_CACHE_DIR=${HF_CACHE_DIR}
-    export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-    export no_proxy=${no_proxy}
-    export http_proxy=${http_proxy}
-    export https_proxy=${https_proxy}
-    export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5"
-    export RERANK_MODEL_ID="BAAI/bge-reranker-base"
-    export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006"
-    export TEI_RERANKING_ENDPOINT="http://${host_ip}:8808"
-    export REDIS_URL="redis://${host_ip}:6379"
-    export INDEX_NAME="rag-redis"
-    export RERANK_TYPE="tei"
-    export MEGA_SERVICE_HOST_IP=${host_ip}
-    export EMBEDDING_SERVICE_HOST_IP=${host_ip}
-    export RETRIEVER_SERVICE_HOST_IP=${host_ip}
-    export RERANK_SERVICE_HOST_IP=${host_ip}
-    export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8889/v1/retrievaltool"
-    export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/ingest"
-    export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6008/v1/dataprep/get"
-    export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6009/v1/dataprep/delete"
-
-    docker compose -f compose.yaml up -d
-}
-
-echo "==================== Start retrieval tool ===================="
-start_retrieval_tool
-sleep 20 # needed for downloading the models
-echo "==================== Retrieval tool started ===================="

AgentQnA/tests/step3_ingest_data_and_validate_retrieval_rocm_vllm.sh

@@ -1,68 +0,0 @@
-#!/bin/bash
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-set -e
-
-WORKPATH=$(dirname "$PWD")
-export WORKDIR=$WORKPATH/../../
-echo "WORKDIR=${WORKDIR}"
-export ip_address=$(hostname -I | awk '{print $1}')
-export host_ip=$ip_address
-echo "ip_address=${ip_address}"
-
-
-function validate() {
-    local CONTENT="$1"
-    local EXPECTED_RESULT="$2"
-    local SERVICE_NAME="$3"
-
-    if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
-        echo "[ $SERVICE_NAME ] Content is as expected: $CONTENT"
-        echo 0
-    else
-        echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
-        echo 1
-    fi
-}
-
-function ingest_data_and_validate() {
-    echo "Ingesting data"
-    cd $WORKPATH/retrieval_tool/
-    echo $PWD
-    local CONTENT=$(bash run_ingest_data.sh)
-    local EXIT_CODE=$(validate "$CONTENT" "Data preparation succeeded" "dataprep-redis-server")
-    echo "$EXIT_CODE"
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    echo "return value is $EXIT_CODE"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs dataprep-redis-server
-        return 1
-    fi
-}
-
-function validate_retrieval_tool() {
-    echo "----------------Test retrieval tool ----------------"
-    local CONTENT=$(http_proxy="" curl http://${ip_address}:8889/v1/retrievaltool -X POST -H "Content-Type: application/json" -d '{
-     "text": "Who sang Thriller"
-    }')
-    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "retrieval-tool")
-
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs retrievaltool-xeon-backend-server
-        exit 1
-    fi
-}
-
-function main(){
-
-    echo "==================== Ingest data ===================="
-    ingest_data_and_validate
-    echo "==================== Data ingestion completed ===================="
-
-    echo "==================== Validate retrieval tool ===================="
-    validate_retrieval_tool
-    echo "==================== Retrieval tool validated ===================="
-}
-
-main

AgentQnA/tests/step4_launch_and_validate_agent_openai.sh

@@ -11,22 +11,13 @@ echo "WORKDIR=${WORKDIR}"
 export ip_address=$(hostname -I | awk '{print $1}')
 export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
 
-
-function download_chinook_data(){
-    echo "Downloading chinook data..."
-    cd $WORKDIR
-    git clone https://github.com/lerocha/chinook-database.git
-    cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite $WORKDIR/GenAIExamples/AgentQnA/tests/
-}
-
 function start_agent_and_api_server() {
     echo "Starting CRAG server"
     docker run -d --runtime=runc --name=kdd-cup-24-crag-service -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
 
     echo "Starting Agent services"
-    cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon/
+    cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon
     bash launch_agent_service_openai.sh
-    sleep 2m
 }
 
 function validate() {
@@ -44,64 +35,19 @@ function validate() {
 }
 
 function validate_agent_service() {
-    # # test worker rag agent
-    echo "======================Testing worker rag agent======================"
-    export agent_port="9095"
-    prompt="Tell me about Michael Jackson song Thriller"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port)
-    # echo $CONTENT
-    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "rag-agent-endpoint")
-    echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
+    echo "----------------Test agent ----------------"
+    local CONTENT=$(http_proxy="" curl http://${ip_address}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "query": "Tell me about Michael Jackson song thriller"
+    }')
+    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "react-agent-endpoint")
+    docker logs react-agent-endpoint
     if [ "$EXIT_CODE" == "1" ]; then
-        docker logs rag-agent-endpoint
-        exit 1
-    fi
-
-    # # test worker sql agent
-    echo "======================Testing worker sql agent======================"
-    export agent_port="9096"
-    prompt="How many employees are there in the company?"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port)
-    local EXIT_CODE=$(validate "$CONTENT" "8" "sql-agent-endpoint")
-    echo $CONTENT
-    # echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs sql-agent-endpoint
-        exit 1
-    fi
-
-    # test supervisor react agent
-    echo "======================Testing supervisor react agent======================"
-    export agent_port="9090"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --agent_role "supervisor" --ext_port $agent_port --stream)
-    local EXIT_CODE=$(validate "$CONTENT" "Iron" "react-agent-endpoint")
-    # echo $CONTENT
-    echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs react-agent-endpoint
         exit 1
     fi
 
 }
 
-function remove_chinook_data(){
-    echo "Removing chinook data..."
-    cd $WORKDIR
-    if [ -d "chinook-database" ]; then
-        rm -rf chinook-database
-    fi
-    echo "Chinook data removed!"
-}
-
-
 function main() {
-    echo "==================== Prepare data ===================="
-    download_chinook_data
-    echo "==================== Data prepare done ===================="
-
     echo "==================== Start agent ===================="
     start_agent_and_api_server
     echo "==================== Agent started ===================="
@@ -111,9 +57,4 @@ function main() {
     echo "==================== Agent service validated ===================="
 }
 
-
-remove_chinook_data
-
 main
-
-remove_chinook_data

AgentQnA/tests/step4_launch_and_validate_agent_rocm_vllm.sh

@@ -1,120 +0,0 @@
-#!/bin/bash
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-set -e
-
-WORKPATH=$(dirname "$PWD")
-export LOG_PATH=${WORKPATH}
-export WORKDIR=$WORKPATH/../../
-echo "WORKDIR=${WORKDIR}"
-export ip_address=$(hostname -I | awk '{print $1}')
-export host_ip=${ip_address}
-export TOOLSET_PATH=$WORKPATH/tools/
-
-export HF_CACHE_DIR=$WORKPATH/data2/huggingface
-if [ ! -d "$HF_CACHE_DIR" ]; then
-    HF_CACHE_DIR=$WORKDIR/hf_cache
-    mkdir -p "$HF_CACHE_DIR"
-fi
-
-function download_chinook_data(){
-    echo "Downloading chinook data..."
-    cd $WORKDIR
-    git clone https://github.com/lerocha/chinook-database.git
-    cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite ${WORKPATH}/tests/
-}
-
-function start_agent_and_api_server() {
-    echo "Starting Agent services"
-    cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-    bash launch_agent_service_vllm_rocm.sh
-}
-
-function validate() {
-    local CONTENT="$1"
-    local EXPECTED_RESULT="$2"
-    local SERVICE_NAME="$3"
-
-    if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
-        echo "[ $SERVICE_NAME ] Content is as expected: $CONTENT"
-        echo 0
-    else
-        echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
-        echo 1
-    fi
-}
-
-function validate_agent_service() {
-    # # test worker rag agent
-    echo "======================Testing worker rag agent======================"
-    export agent_port=$(cat ${WORKPATH}/docker_compose/amd/gpu/WORKER_RAG_AGENT_PORT_tmp)
-    prompt="Tell me about Michael Jackson song Thriller"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port)
-    # echo $CONTENT
-    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "rag-agent-endpoint")
-    echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs rag-agent-endpoint
-        exit 1
-    fi
-
-     # test worker sql agent
-    echo "======================Testing worker sql agent======================"
-    export agent_port=$(cat ${WORKPATH}/docker_compose/amd/gpu/WORKER_SQL_AGENT_PORT_tmp)
-    prompt="How many employees are there in the company?"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port)
-    local EXIT_CODE=$(validate "$CONTENT" "8" "sql-agent-endpoint")
-    echo $CONTENT
-    # echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs sql-agent-endpoint
-        exit 1
-    fi
-
-    # test supervisor react agent
-    echo "======================Testing supervisor react agent======================"
-    export agent_port=$(cat ${WORKPATH}/docker_compose/amd/gpu/SUPERVISOR_REACT_AGENT_PORT_tmp)
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --agent_role "supervisor" --ext_port $agent_port --stream)
-    local EXIT_CODE=$(validate "$CONTENT" "Iron" "react-agent-endpoint")
-    # echo $CONTENT
-    echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs react-agent-endpoint
-        exit 1
-    fi
-
-}
-
-function remove_chinook_data(){
-    echo "Removing chinook data..."
-    cd $WORKDIR
-    if [ -d "chinook-database" ]; then
-        rm -rf chinook-database
-    fi
-    echo "Chinook data removed!"
-}
-
-function main() {
-    echo "==================== Prepare data ===================="
-    download_chinook_data
-    echo "==================== Data prepare done ===================="
-
-    echo "==================== Start agent ===================="
-    start_agent_and_api_server
-    echo "==================== Agent started ===================="
-
-    echo "==================== Validate agent service ===================="
-    validate_agent_service
-    echo "==================== Agent service validated ===================="
-}
-
-
-remove_chinook_data
-
-main
-
-remove_chinook_data

AgentQnA/tests/step4_launch_and_validate_agent_tgi.sh

@@ -11,9 +11,9 @@ export ip_address=$(hostname -I | awk '{print $1}')
 export TOOLSET_PATH=$WORKPATH/tools/
 export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 HF_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-model="meta-llama/Llama-3.3-70B-Instruct" #"meta-llama/Meta-Llama-3.1-70B-Instruct"
+model="meta-llama/Meta-Llama-3.1-70B-Instruct"
 
-export HF_CACHE_DIR=${model_cache:-"/data2/huggingface"}
+export HF_CACHE_DIR=/data2/huggingface
 if [ ! -d "$HF_CACHE_DIR" ]; then
     HF_CACHE_DIR=$WORKDIR/hf_cache
     mkdir -p "$HF_CACHE_DIR"
@@ -27,20 +27,18 @@ vllm_volume=${HF_CACHE_DIR}
 function start_tgi(){
     echo "Starting tgi-gaudi server"
     cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi
-    source set_env.sh
-    docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml tgi_gaudi.yaml -f compose.telemetry.yaml up -d
+    bash launch_tgi_gaudi.sh
 
 }
 
-function start_all_services() {
+function start_vllm_service_70B() {
 
     echo "token is ${HF_TOKEN}"
 
     echo "start vllm gaudi service"
     echo "**************model is $model**************"
-    cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi
-    source set_env.sh
-    docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml -f compose.telemetry.yaml up -d
+    vllm_image=opea/vllm-gaudi:ci
+    docker run -d --runtime=habana --rm --name "vllm-gaudi-server" -e HABANA_VISIBLE_DEVICES=0,1,2,3 -p $vllm_port:8000 -v $vllm_volume:/data -e HF_TOKEN=$HF_TOKEN -e HUGGING_FACE_HUB_TOKEN=$HF_TOKEN -e HF_HOME=/data -e OMPI_MCA_btl_vader_single_copy_mechanism=none -e PT_HPU_ENABLE_LAZY_COLLECTIVES=true -e http_proxy=$http_proxy -e https_proxy=$https_proxy -e no_proxy=$no_proxy -e VLLM_SKIP_WARMUP=true --cap-add=sys_nice --ipc=host $vllm_image --model ${model} --max-seq-len-to-capture 16384 --tensor-parallel-size 4
     sleep 5s
     echo "Waiting vllm gaudi ready"
     n=0
@@ -62,6 +60,23 @@ function start_all_services() {
     echo "Service started successfully"
 }
 
+
+function prepare_data() {
+    cd $WORKDIR
+
+    echo "Downloading data..."
+    git clone https://github.com/TAG-Research/TAG-Bench.git
+    cd TAG-Bench/setup
+    chmod +x get_dbs.sh
+    ./get_dbs.sh
+
+    echo "Split data..."
+    cd $WORKPATH/tests/sql_agent_test
+    bash run_data_split.sh
+
+    echo "Data preparation done!"
+}
+
 function download_chinook_data(){
     echo "Downloading chinook data..."
     cd $WORKDIR
@@ -69,6 +84,15 @@ function download_chinook_data(){
     cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite $WORKDIR/GenAIExamples/AgentQnA/tests/
 }
 
+function start_agent_and_api_server() {
+    echo "Starting CRAG server"
+    docker run -d --runtime=runc --name=kdd-cup-24-crag-service -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
+
+    echo "Starting Agent services"
+    cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi
+    bash launch_agent_service_gaudi.sh
+    sleep 2m
+}
 
 function validate() {
     local CONTENT="$1"
@@ -88,9 +112,8 @@ function validate_agent_service() {
     # # test worker rag agent
     echo "======================Testing worker rag agent======================"
     export agent_port="9095"
-    export agent_ip="127.0.0.1"
     prompt="Tell me about Michael Jackson song Thriller"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ip_addr $agent_ip  --ext_port $agent_port)
+    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt")
     # echo $CONTENT
     local EXIT_CODE=$(validate "$CONTENT" "Thriller" "rag-agent-endpoint")
     echo $EXIT_CODE
@@ -104,7 +127,7 @@ function validate_agent_service() {
     echo "======================Testing worker sql agent======================"
     export agent_port="9096"
     prompt="How many employees are there in the company?"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ip_addr $agent_ip --ext_port $agent_port)
+    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt")
     local EXIT_CODE=$(validate "$CONTENT" "8" "sql-agent-endpoint")
     echo $CONTENT
     # echo $EXIT_CODE
@@ -117,8 +140,9 @@ function validate_agent_service() {
     # test supervisor react agent
     echo "======================Testing supervisor react agent======================"
     export agent_port="9090"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --agent_role "supervisor" --ip_addr $agent_ip  --ext_port $agent_port --stream)
-    local EXIT_CODE=$(validate "$CONTENT" "Iron" "react-agent-endpoint")
+    prompt="How many albums does Iron Maiden have?"
+    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt")
+    local EXIT_CODE=$(validate "$CONTENT" "21" "react-agent-endpoint")
     # echo $CONTENT
     echo $EXIT_CODE
     local EXIT_CODE="${EXIT_CODE:0-1}"
@@ -129,6 +153,15 @@ function validate_agent_service() {
 
 }
 
+function remove_data() {
+    echo "Removing data..."
+    cd $WORKDIR
+    if [ -d "TAG-Bench" ]; then
+        rm -rf TAG-Bench
+    fi
+    echo "Data removed!"
+}
+
 function remove_chinook_data(){
     echo "Removing chinook data..."
     cd $WORKDIR
@@ -138,77 +171,26 @@ function remove_chinook_data(){
     echo "Chinook data removed!"
 }
 
-export host_ip=$ip_address
-echo "ip_address=${ip_address}"
-
-
-function validate() {
-    local CONTENT="$1"
-    local EXPECTED_RESULT="$2"
-    local SERVICE_NAME="$3"
-
-    if echo "$CONTENT" | grep -q "$EXPECTED_RESULT"; then
-        echo "[ $SERVICE_NAME ] Content is as expected: $CONTENT"
-        echo 0
-    else
-        echo "[ $SERVICE_NAME ] Content does not match the expected result: $CONTENT"
-        echo 1
-    fi
-}
-
-function ingest_data_and_validate() {
-    echo "Ingesting data"
-    cd $WORKDIR/GenAIExamples/AgentQnA/retrieval_tool/
-    echo $PWD
-    local CONTENT=$(bash run_ingest_data.sh)
-    local EXIT_CODE=$(validate "$CONTENT" "Data preparation succeeded" "dataprep-redis-server")
-    echo "$EXIT_CODE"
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    echo "return value is $EXIT_CODE"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs dataprep-redis-server
-        return 1
-    fi
-}
-
-function validate_retrieval_tool() {
-    echo "----------------Test retrieval tool ----------------"
-    local CONTENT=$(http_proxy="" curl http://${ip_address}:8889/v1/retrievaltool -X POST -H "Content-Type: application/json" -d '{
-     "text": "Who sang Thriller"
-    }')
-    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "retrieval-tool")
-
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs retrievaltool-xeon-backend-server
-        exit 1
-    fi
-}
-
 function main() {
     echo "==================== Prepare data ===================="
     download_chinook_data
     echo "==================== Data prepare done ===================="
 
-    echo "==================== Start all services ===================="
-    start_all_services
-    echo "==================== all services started ===================="
+    echo "==================== Start VLLM service ===================="
+    start_vllm_service_70B
+    echo "==================== VLLM service started ===================="
 
-    echo "==================== Ingest data ===================="
-    ingest_data_and_validate
-    echo "==================== Data ingestion completed ===================="
-
-    echo "==================== Validate retrieval tool ===================="
-    validate_retrieval_tool
-    echo "==================== Retrieval tool validated ===================="
+    echo "==================== Start agent ===================="
+    start_agent_and_api_server
+    echo "==================== Agent started ===================="
 
     echo "==================== Validate agent service ===================="
     validate_agent_service
     echo "==================== Agent service validated ===================="
 }
 
-
+remove_data
 remove_chinook_data
-
 main
-
+remove_data
 remove_chinook_data

AgentQnA/tests/step4a_launch_and_validate_agent_tgi_on_rocm.sh

@@ -2,30 +2,26 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-set -e
+set -ex
 
 WORKPATH=$(dirname "$PWD")
-export LOG_PATH=${WORKPATH}
 export WORKDIR=$WORKPATH/../../
 echo "WORKDIR=${WORKDIR}"
 export ip_address=$(hostname -I | awk '{print $1}')
-export host_ip=${ip_address}
-export TOOLSET_PATH=$WORKPATH/tools/
+export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
+export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 
-export HF_CACHE_DIR=$WORKPATH/data2/huggingface
+export HF_CACHE_DIR=$WORKDIR/hf_cache
 if [ ! -d "$HF_CACHE_DIR" ]; then
-    HF_CACHE_DIR=$WORKDIR/hf_cache
     mkdir -p "$HF_CACHE_DIR"
 fi
+ls $HF_CACHE_DIR
 
-function download_chinook_data(){
-    echo "Downloading chinook data..."
-    cd $WORKDIR
-    git clone https://github.com/lerocha/chinook-database.git
-    cp chinook-database/ChinookDatabase/DataSources/Chinook_Sqlite.sqlite ${WORKPATH}/tests/
-}
 
 function start_agent_and_api_server() {
+    echo "Starting CRAG server"
+    docker run -d --runtime=runc --name=kdd-cup-24-crag-service -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
+
     echo "Starting Agent services"
     cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
     bash launch_agent_service_tgi_rocm.sh
@@ -46,63 +42,28 @@ function validate() {
 }
 
 function validate_agent_service() {
-    # # test worker rag agent
-    echo "======================Testing worker rag agent======================"
-    export agent_port=$(cat ${WORKPATH}/docker_compose/amd/gpu/WORKER_RAG_AGENT_PORT_tmp)
-    prompt="Tell me about Michael Jackson song Thriller"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port)
-    # echo $CONTENT
-    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "rag-agent-endpoint")
-    echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
+    echo "----------------Test agent ----------------"
+    local CONTENT=$(http_proxy="" curl http://${ip_address}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "query": "Tell me about Michael Jackson song thriller"
+    }')
+    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "react-agent-endpoint")
+    docker logs rag-agent-endpoint
     if [ "$EXIT_CODE" == "1" ]; then
-        docker logs rag-agent-endpoint
         exit 1
     fi
 
-     # test worker sql agent
-    echo "======================Testing worker sql agent======================"
-    export agent_port=$(cat ${WORKPATH}/docker_compose/amd/gpu/WORKER_SQL_AGENT_PORT_tmp)
-    prompt="How many employees are there in the company?"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port)
-    local EXIT_CODE=$(validate "$CONTENT" "8" "sql-agent-endpoint")
-    echo $CONTENT
-    # echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
+    local CONTENT=$(http_proxy="" curl http://${ip_address}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+     "query": "Tell me about Michael Jackson song thriller"
+    }')
+    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "react-agent-endpoint")
+    docker logs react-agent-endpoint
     if [ "$EXIT_CODE" == "1" ]; then
-        docker logs sql-agent-endpoint
         exit 1
     fi
 
-    # test supervisor react agent
-    echo "======================Testing supervisor react agent======================"
-    export agent_port=$(cat ${WORKPATH}/docker_compose/amd/gpu/SUPERVISOR_REACT_AGENT_PORT_tmp)
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --agent_role "supervisor" --ext_port $agent_port --stream)
-    local EXIT_CODE=$(validate "$CONTENT" "Iron" "react-agent-endpoint")
-    # echo $CONTENT
-    echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs react-agent-endpoint
-        exit 1
-    fi
-
-}
-
-function remove_chinook_data(){
-    echo "Removing chinook data..."
-    cd $WORKDIR
-    if [ -d "chinook-database" ]; then
-        rm -rf chinook-database
-    fi
-    echo "Chinook data removed!"
 }
 
 function main() {
-    echo "==================== Prepare data ===================="
-    download_chinook_data
-    echo "==================== Data prepare done ===================="
-
     echo "==================== Start agent ===================="
     start_agent_and_api_server
     echo "==================== Agent started ===================="
@@ -112,9 +73,4 @@ function main() {
     echo "==================== Agent service validated ===================="
 }
 
-
-remove_chinook_data
-
 main
-
-remove_chinook_data

AgentQnA/tests/test.py

@@ -1,20 +1,34 @@
-# Copyright (C) 2025 Intel Corporation
+# Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
 import argparse
-import json
-import uuid
+import os
 
 import requests
 
 
+def generate_answer_agent_api(url, prompt):
+    proxies = {"http": ""}
+    payload = {
+        "messages": prompt,
+    }
+    response = requests.post(url, json=payload, proxies=proxies)
+    answer = response.json()["text"]
+    return answer
+
+
 def process_request(url, query, is_stream=False):
     proxies = {"http": ""}
-    content = json.dumps(query) if query is not None else None
+
+    payload = {
+        "messages": query,
+    }
+
     try:
-        resp = requests.post(url=url, data=content, proxies=proxies, stream=is_stream)
+        resp = requests.post(url=url, json=payload, proxies=proxies, stream=is_stream)
         if not is_stream:
             ret = resp.json()["text"]
+            print(ret)
         else:
             for line in resp.iter_lines(decode_unicode=True):
                 print(line)
@@ -24,54 +38,19 @@ def process_request(url, query, is_stream=False):
         return ret
     except requests.exceptions.RequestException as e:
         ret = f"An error occurred:{e}"
-        return None
-
-
-def test_worker_agent(args):
-    url = f"http://{args.ip_addr}:{args.ext_port}/v1/chat/completions"
-    query = {"role": "user", "messages": args.prompt, "stream": "false"}
-    ret = process_request(url, query)
-    print("Response: ", ret)
-
-
-def add_message_and_run(url, user_message, thread_id, stream=False):
-    print("User message: ", user_message)
-    query = {"role": "user", "messages": user_message, "thread_id": thread_id, "stream": stream}
-    ret = process_request(url, query, is_stream=stream)
-    print("Response: ", ret)
-
-
-def test_chat_completion_multi_turn(args):
-    url = f"http://{args.ip_addr}:{args.ext_port}/v1/chat/completions"
-    thread_id = f"{uuid.uuid4()}"
-
-    # first turn
-    print("===============First turn==================")
-    user_message = "Which artist has the most albums in the database?"
-    add_message_and_run(url, user_message, thread_id, stream=args.stream)
-    print("===============End of first turn==================")
-
-    # second turn
-    print("===============Second turn==================")
-    user_message = "Give me a few examples of the artist's albums?"
-    add_message_and_run(url, user_message, thread_id, stream=args.stream)
-    print("===============End of second turn==================")
+        print(ret)
+        return False
 
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser()
-    parser.add_argument("--ip_addr", type=str, default="127.0.0.1", help="endpoint ip address")
-    parser.add_argument("--ext_port", type=str, default="9090", help="endpoint port")
-    parser.add_argument("--stream", action="store_true", help="streaming mode")
-    parser.add_argument("--prompt", type=str, help="prompt message")
-    parser.add_argument("--agent_role", type=str, default="supervisor", help="supervisor or worker")
-    args, _ = parser.parse_known_args()
+    parser.add_argument("--prompt", type=str)
+    parser.add_argument("--stream", action="store_true")
+    args = parser.parse_args()
 
-    print(args)
+    ip_address = os.getenv("ip_address", "localhost")
+    agent_port = os.getenv("agent_port", "9090")
+    url = f"http://{ip_address}:{agent_port}/v1/chat/completions"
+    prompt = args.prompt
 
-    if args.agent_role == "supervisor":
-        test_chat_completion_multi_turn(args)
-    elif args.agent_role == "worker":
-        test_worker_agent(args)
-    else:
-        raise ValueError("Invalid agent role")
+    process_request(url, prompt, args.stream)

AgentQnA/tests/test_compose_on_gaudi.sh

@@ -1,6 +1,7 @@
 #!/bin/bash
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
+
 set -xe
 
 WORKPATH=$(dirname "$PWD")
@@ -9,22 +10,6 @@ echo "WORKDIR=${WORKDIR}"
 export ip_address=$(hostname -I | awk '{print $1}')
 export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
 export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
-export no_proxy="$no_proxy,rag-agent-endpoint,sql-agent-endpoint,react-agent-endpoint,agent-ui,vllm-gaudi-server,jaeger,grafana,prometheus,127.0.0.1,localhost,0.0.0.0,$ip_address"
-
-
-function get_genai_comps() {
-    if [ ! -d "GenAIComps" ] ; then
-        git clone --depth 1 --branch ${opea_branch:-"main"} https://github.com/opea-project/GenAIComps.git
-    fi
-}
-
-
-function build_agent_docker_image() {
-    cd $WORKDIR/GenAIExamples/AgentQnA/docker_image_build/
-    get_genai_comps
-    echo "Build agent image with --no-cache..."
-    docker compose -f build.yaml build --no-cache
-}
 
 function stop_crag() {
     cid=$(docker ps -aq --filter "name=kdd-cup-24-crag-service")
@@ -34,7 +19,12 @@ function stop_crag() {
 
 function stop_agent_docker() {
     cd $WORKPATH/docker_compose/intel/hpu/gaudi/
-    docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml down
+    container_list=$(cat compose.yaml | grep container_name | cut -d':' -f2)
+    for container_name in $container_list; do
+        cid=$(docker ps -aq --filter "name=$container_name")
+        echo "Stopping container $container_name"
+        if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
+    done
 }
 
 function stop_llm(){
@@ -70,21 +60,33 @@ function stop_retrieval_tool() {
 echo "workpath: $WORKPATH"
 echo "=================== Stop containers ===================="
 stop_crag
+stop_llm
 stop_agent_docker
+stop_retrieval_tool
 
 cd $WORKPATH/tests
 
 echo "=================== #1 Building docker images===================="
-build_agent_docker_image
+bash step1_build_images.sh
 echo "=================== #1 Building docker images completed===================="
 
-echo "=================== #4 Start agent, API server, retrieval, and ingest data===================="
-bash $WORKPATH/tests/step4_launch_and_validate_agent_gaudi.sh
-echo "=================== #4 Agent, retrieval test passed ===================="
+echo "=================== #2 Start retrieval tool===================="
+bash step2_start_retrieval_tool.sh
+echo "=================== #2 Retrieval tool started===================="
+
+echo "=================== #3 Ingest data and validate retrieval===================="
+bash step3_ingest_data_and_validate_retrieval.sh
+echo "=================== #3 Data ingestion and validation completed===================="
+
+echo "=================== #4 Start agent and API server===================="
+bash step4_launch_and_validate_agent_tgi.sh
+echo "=================== #4 Agent test passed ===================="
 
 echo "=================== #5 Stop agent and API server===================="
 stop_crag
 stop_agent_docker
+stop_retrieval_tool
+stop_llm
 echo "=================== #5 Agent and API server stopped===================="
 
 echo y | docker system prune

AgentQnA/tests/test_compose_on_rocm.sh

@@ -5,13 +5,11 @@
 set -xe
 
 WORKPATH=$(dirname "$PWD")
-ls $WORKPATH
 export WORKDIR=$WORKPATH/../../
 echo "WORKDIR=${WORKDIR}"
 export ip_address=$(hostname -I | awk '{print $1}')
 export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export TOOLSET_PATH=$WORKPATH/tools/
-export MODEL_CACHE="./data"
+export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
 
 function stop_crag() {
     cid=$(docker ps -aq --filter "name=kdd-cup-24-crag-service")
@@ -21,7 +19,13 @@ function stop_crag() {
 
 function stop_agent_docker() {
     cd $WORKPATH/docker_compose/amd/gpu/rocm
-    bash stop_agent_service_tgi_rocm.sh
+    # docker compose -f compose.yaml down
+    container_list=$(cat compose.yaml | grep container_name | cut -d':' -f2)
+    for container_name in $container_list; do
+        cid=$(docker ps -aq --filter "name=$container_name")
+        echo "Stopping container $container_name"
+        if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
+    done
 }
 
 function stop_retrieval_tool() {

AgentQnA/tests/test_compose_vllm_on_rocm.sh

@@ -1,66 +0,0 @@
-#!/bin/bash
-# Copyright (C) 2024 Advanced Micro Devices, Inc.
-# SPDX-License-Identifier: Apache-2.0
-
-set -e
-
-WORKPATH=$(dirname "$PWD")
-export LOG_PATH=${WORKPATH}
-export WORKDIR=${WORKPATH}/../../
-echo "WORKDIR=${WORKDIR}"
-export ip_address=$(hostname -I | awk '{print $1}')
-export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-export TOOLSET_PATH=$WORKPATH/tools/
-export MODEL_CACHE="./data"
-
-function stop_crag() {
-    cid=$(docker ps -aq --filter "name=kdd-cup-24-crag-service")
-    echo "Stopping container kdd-cup-24-crag-service with cid $cid"
-    if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
-}
-
-function stop_agent_docker() {
-    cd $WORKPATH/docker_compose/amd/gpu/rocm
-    bash stop_agent_service_vllm_rocm.sh
-}
-
-function stop_retrieval_tool() {
-    echo "Stopping Retrieval tool"
-    local RETRIEVAL_TOOL_PATH=$WORKDIR/GenAIExamples/DocIndexRetriever
-    cd $RETRIEVAL_TOOL_PATH/docker_compose/intel/cpu/xeon/
-    docker compose -f compose.yaml down
-}
-
-echo "workpath: $WORKPATH"
-echo "=================== Stop containers ===================="
-stop_crag
-stop_agent_docker
-stop_retrieval_tool
-
-cd $WORKPATH/tests
-
-echo "=================== #1 Building docker images===================="
-bash step1_build_images_rocm_vllm.sh
-echo "=================== #1 Building docker images completed===================="
-
-echo "=================== #2 Start retrieval tool===================="
-bash step2_start_retrieval_tool_rocm_vllm.sh
-echo "=================== #2 Retrieval tool started===================="
-
-echo "=================== #3 Ingest data and validate retrieval===================="
-bash step3_ingest_data_and_validate_retrieval_rocm_vllm.sh
-echo "=================== #3 Data ingestion and validation completed===================="
-
-echo "=================== #4 Start agent and API server===================="
-bash step4_launch_and_validate_agent_rocm_vllm.sh
-echo "=================== #4 Agent test passed ===================="
-
-echo "=================== #5 Stop agent and API server===================="
-stop_crag
-stop_agent_docker
-stop_retrieval_tool
-echo "=================== #5 Agent and API server stopped===================="
-
-echo y | docker system prune
-
-echo "ALL DONE!!"

AgentQnA/tools/supervisor_agent_webtools.yaml

@@ -1,77 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-search_web_base:
-  description: Search a web base for a given query. Returns text related to the query.
-  callable_api: tools.py:search_web_base
-  args_schema:
-    query:
-      type: str
-      description: query
-  return_output: retrieved_data
-
-search_knowledge_base:
-  description: Search a knowledge base for a given query. Returns text related to the query.
-  callable_api: tools.py:search_knowledge_base
-  args_schema:
-    query:
-      type: str
-      description: query
-  return_output: retrieved_data
-
-search_artist_database:
-  description: Search a SQL database on artists and their music with a natural language query. Returns text related to the query.
-  callable_api: tools.py:search_sql_database
-  args_schema:
-    query:
-      type: str
-      description: natural language query
-  return_output: retrieved_data
-
-get_artist_birth_place:
-  description: Get the birth place of an artist.
-  callable_api: tools.py:get_artist_birth_place
-  args_schema:
-    artist_name:
-      type: str
-      description: artist name
-  return_output: birth_place
-
-get_billboard_rank_date:
-  description: Get Billboard ranking for a specific rank and date.
-  callable_api: tools.py:get_billboard_rank_date
-  args_schema:
-    rank:
-      type: int
-      description: the rank of interest, for example 1 for top 1
-    date:
-      type: str
-      description: date
-  return_output: billboard_info
-
-get_song_release_date:
-  description: Get the release date of a song.
-  callable_api: tools.py:get_song_release_date
-  args_schema:
-    song_name:
-      type: str
-      description: song name
-  return_output: release_date
-
-get_members:
-  description: Get the member list of a band.
-  callable_api: tools.py:get_members
-  args_schema:
-    band_name:
-      type: str
-      description: band name
-  return_output: members
-
-get_grammy_best_artist_by_year:
-  description: Get the Grammy Best New Artist for a specific year.
-  callable_api: tools.py:get_grammy_best_artist_by_year
-  args_schema:
-    year:
-      type: int
-      description: year
-  return_output: grammy_best_new_artist

AgentQnA/tools/tools.py

@@ -4,30 +4,9 @@
 import os
 
 import requests
-from comps.cores.telemetry.opea_telemetry import opea_telemetry, tracer
 from tools.pycragapi import CRAG
 
 
-@opea_telemetry
-def search_web_base(query: str) -> str:
-    import os
-
-    from langchain_core.tools import Tool
-    from langchain_google_community import GoogleSearchAPIWrapper
-
-    search = GoogleSearchAPIWrapper()
-
-    tool = Tool(
-        name="google_search",
-        description="Search Google for recent results.",
-        func=search.run,
-    )
-
-    response = tool.run(query)
-    return response
-
-
-@opea_telemetry
 def search_knowledge_base(query: str) -> str:
     """Search a knowledge base about music and singers for a given query.
 
@@ -43,7 +22,6 @@ def search_knowledge_base(query: str) -> str:
     return response.json()["text"]
 
 
-@opea_telemetry
 def search_sql_database(query: str) -> str:
     """Search a SQL database on artists and their music with a natural language query.
 
@@ -59,7 +37,6 @@ def search_sql_database(query: str) -> str:
     return response.json()["text"]
 
 
-@opea_telemetry
 def get_grammy_best_artist_by_year(year: int) -> dict:
     """Get the Grammy Best New Artist for a specific year."""
     api = CRAG()
@@ -67,21 +44,18 @@ def get_grammy_best_artist_by_year(year: int) -> dict:
     return api.music_grammy_get_best_artist_by_year(year)
 
 
-@opea_telemetry
 def get_members(band_name: str) -> dict:
     """Get the member list of a band."""
     api = CRAG()
     return api.music_get_members(band_name)
 
 
-@opea_telemetry
 def get_artist_birth_place(artist_name: str) -> dict:
     """Get the birthplace of an artist."""
     api = CRAG()
     return api.music_get_artist_birth_place(artist_name)
 
 
-@opea_telemetry
 def get_billboard_rank_date(rank: int, date: str = None) -> dict:
     """Get Billboard ranking for a specific rank and date."""
     api = CRAG()
@@ -89,7 +63,6 @@ def get_billboard_rank_date(rank: int, date: str = None) -> dict:
     return api.music_get_billboard_rank_date(rank, date)
 
 
-@opea_telemetry
 def get_song_release_date(song_name: str) -> dict:
     """Get the release date of a song."""
     api = CRAG()

AgentQnA/ui/open_webui_patches/0001-deal-opea-agent-tool-content.patch

@@ -1,77 +0,0 @@
-From 799dcc304b3aecf2e2969df47c8dcac16d2267b0 Mon Sep 17 00:00:00 2001
-From: lkk12014402 <kaokao.lv@intel.com>
-Date: Fri, 4 Apr 2025 07:40:30 +0000
-Subject: [PATCH] deal opea agent tool content.
-
----
- backend/open_webui/utils/middleware.py | 54 ++++++++++++++++++++++++++
- 1 file changed, 54 insertions(+)
-
-diff --git a/backend/open_webui/utils/middleware.py b/backend/open_webui/utils/middleware.py
-index 289d887df..afa0edf1e 100644
---- a/backend/open_webui/utils/middleware.py
-+++ b/backend/open_webui/utils/middleware.py
-@@ -1486,6 +1486,60 @@ async def process_chat_response(
-                         try:
-                             data = json.loads(data)
- 
-+                            tool_content_block = []
-+                            if data.get("tool_name"):
-+                                sources.append(
-+                                    {
-+                                        "source": {
-+                                            "name": f"TOOL:{data.get('tool_name')}"},
-+                                        "document": [data.get("tool_content")],
-+                                        "metadata": [{
-+                                            "source": f"TOOL:{data.get('tool_name')}"}],
-+                                    }
-+                                )
-+                                events.append({"sources": sources})
-+
-+                                await event_emitter(
-+                                    {
-+                                        "type": "chat:completion",
-+                                        "data": {"sources": sources},
-+                                    }
-+                                )
-+                                tool_content_block = [
-+                                    {
-+                                        "type": "tool_calls",
-+                                        "content": [
-+                                            {"id": data.get('tool_name'), "function": {"name": data.get('tool_name')}}
-+                                        ]
-+                                    }
-+                                ]
-+
-+                                await event_emitter(
-+                                    {
-+                                        "type": "chat:completion",
-+                                        "data": {
-+                                            "content": serialize_content_blocks(tool_content_block),
-+                                        },
-+                                    }
-+                                )
-+
-+                                tool_content_block = [
-+                                        {
-+                                            "type": "tool_calls",
-+                                            "content": [
-+                                                {"id": data.get('tool_name'), "function": {"name": data.get('tool_name')}}
-+                                            ],
-+                                            "results": [
-+                                                {"tool_call_id": data.get('tool_name'), "content": data.get("tool_content")}
-+                                            ]
-+                                        },
-+                                        {
-+                                            "type": "text",
-+                                            "content": "",
-+                                        }
-+                                ]
-+                                content_blocks.extend(tool_content_block)
-+
-                             data, _ = await process_filter_functions(
-                                 request=request,
-                                 filter_functions=filter_functions,
--- 
-2.34.1
-

AgentQnA/ui/svelte/.editorconfig

@@ -0,0 +1,10 @@
+[*]
+indent_style = tab
+
+[package.json]
+indent_style = space
+indent_size = 2
+
+[*.md]
+indent_style = space
+indent_size = 2

AgentQnA/ui/svelte/.env

@@ -0,0 +1 @@
+AGENT_URL = '/v1/chat/completions'

AgentQnA/ui/svelte/.eslintignore

@@ -0,0 +1,13 @@
+.DS_Store
+node_modules
+/build
+/.svelte-kit
+/package
+.env
+.env.*
+!.env.example
+
+# Ignore files for PNPM, NPM and YARN
+pnpm-lock.yaml
+package-lock.json
+yarn.lock

AgentQnA/ui/svelte/.eslintrc.cjs

@@ -0,0 +1,20 @@
+module.exports = {
+	root: true,
+	parser: "@typescript-eslint/parser",
+	extends: ["eslint:recommended", "plugin:@typescript-eslint/recommended", "prettier"],
+	plugins: ["svelte3", "@typescript-eslint", "neverthrow"],
+	ignorePatterns: ["*.cjs"],
+	overrides: [{ files: ["*.svelte"], processor: "svelte3/svelte3" }],
+	settings: {
+		"svelte3/typescript": () => require("typescript"),
+	},
+	parserOptions: {
+		sourceType: "module",
+		ecmaVersion: 2020,
+	},
+	env: {
+		browser: true,
+		es2017: true,
+		node: true,
+	},
+};

AgentQnA/ui/svelte/.prettierignore

@@ -0,0 +1,13 @@
+.DS_Store
+node_modules
+/build
+/.svelte-kit
+/package
+.env
+.env.*
+!.env.example
+
+# Ignore files for PNPM, NPM and YARN
+pnpm-lock.yaml
+package-lock.json
+yarn.lock

AgentQnA/ui/svelte/.prettierrc

@@ -0,0 +1,13 @@
+{
+	"pluginSearchDirs": [
+		"."
+	],
+	"overrides": [
+		{
+			"files": "*.svelte",
+			"options": {
+				"parser": "svelte"
+			}
+		}
+	]
+}

AgentQnA/ui/svelte/README.md

@@ -0,0 +1,60 @@
+# AgentQnA
+
+## 📸 Project Screenshots
+
+![project-screenshot](../../assets/img/agent_ui.png)
+![project-screenshot](../../assets/img/agent_ui_result.png)
+
+## 🧐 Features
+
+Here're some of the project's features:
+
+- Create Agent：Provide more precise answers based on user queries, showcase the high-quality output process of complex queries across different dimensions, and consolidate information to present comprehensive answers.
+
+## 🛠️ Get it Running
+
+1. Clone the repo.
+
+2. cd command to the current folder.
+
+   ```
+   cd AgentQnA/ui
+   ```
+
+3. Modify the required .env variables.
+
+   ```
+   AGENT_URL = ''
+   ```
+
+4. **For Local Development:**
+
+- Install the dependencies:
+
+  ```
+  npm install
+  ```
+
+- Start the development server:
+
+  ```
+  npm run dev
+  ```
+
+- The application will be available at `http://localhost:3000`.
+
+5. **For Docker Setup:**
+
+- Build the Docker image:
+
+  ```
+  docker build -t opea:agent-ui .
+  ```
+
+- Run the Docker container:
+
+  ```
+  docker run -d -p 3000:3000 --name agent-ui opea:agent-ui
+  ```
+
+- The application will be available at `http://localhost:3000`.

AgentQnA/ui/svelte/package.json

@@ -0,0 +1,60 @@
+{
+  "name": "agent-example",
+  "version": "0.0.1",
+  "private": true,
+  "scripts": {
+    "dev": "vite dev --host 0.0.0.0",
+    "build": "vite build",
+    "preview": "vite preview",
+    "check": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json",
+    "check:watch": "svelte-kit sync && svelte-check --tsconfig ./tsconfig.json --watch",
+    "lint": "prettier --check . && eslint .",
+    "format": "prettier --write ."
+  },
+  "devDependencies": {
+    "@fortawesome/free-solid-svg-icons": "6.2.0",
+    "@sveltejs/adapter-auto": "1.0.0-next.75",
+    "@sveltejs/kit": "^1.20.1",
+    "@tailwindcss/typography": "0.5.7",
+    "@types/debug": "4.1.7",
+    "@typescript-eslint/eslint-plugin": "^5.27.0",
+    "@typescript-eslint/parser": "^5.27.0",
+    "autoprefixer": "^10.4.7",
+    "daisyui": "^2.52.0",
+    "debug": "4.3.4",
+    "eslint": "^8.16.0",
+    "eslint-config-prettier": "^8.3.0",
+    "eslint-plugin-neverthrow": "1.1.4",
+    "eslint-plugin-svelte3": "^4.0.0",
+    "neverthrow": "5.0.0",
+    "pocketbase": "0.7.0",
+    "postcss": "^8.4.23",
+    "postcss-load-config": "^4.0.1",
+    "postcss-preset-env": "^8.3.2",
+    "prettier": "^2.8.8",
+    "prettier-plugin-svelte": "^2.7.0",
+    "prettier-plugin-tailwindcss": "^0.3.0",
+    "svelte": "^3.59.1",
+    "svelte-check": "^2.7.1",
+    "svelte-fa": "3.0.3",
+    "svelte-preprocess": "^4.10.7",
+    "tailwindcss": "^3.1.5",
+    "ts-pattern": "4.0.5",
+    "tslib": "^2.3.1",
+    "typescript": "^4.7.4",
+    "vite": "^4.3.9"
+  },
+  "type": "module",
+  "dependencies": {
+    "@heroicons/vue": "^2.1.5",
+    "echarts": "^5.4.2",
+    "flowbite-svelte": "^0.38.5",
+    "flowbite-svelte-icons": "^0.3.6",
+    "fuse.js": "^6.6.2",
+    "marked": "^15.0.0",
+    "ramda": "^0.29.0",
+    "sjcl": "^1.0.8",
+    "sse.js": "^0.6.1",
+    "svelte-notifications": "^0.9.98"
+  }
+}

AgentQnA/ui/svelte/postcss.config.cjs

@@ -0,0 +1,13 @@
+const tailwindcss = require("tailwindcss");
+const autoprefixer = require("autoprefixer");
+
+const config = {
+	plugins: [
+		//Some plugins, like tailwindcss/nesting, need to run before Tailwind,
+		tailwindcss(),
+		//But others, like autoprefixer, need to run after,
+		autoprefixer,
+	],
+};
+
+module.exports = config;

AgentQnA/ui/svelte/src/app.d.ts

@@ -0,0 +1,50 @@
+// Copyright (C) 2025 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+
+// See: https://kit.svelte.dev/docs/types#app
+// import { Result} from "neverthrow";
+
+declare namespace App {
+	interface Locals {
+		user?: User;
+	}
+	// interface PageData { }
+	// interface PageError {}
+	// interface Platform {}
+}
+
+interface User {
+	id?: string;
+	email: string;
+	password?: string;
+	token?: string;
+	[key: string]: any;
+}
+
+type AuthResponse = Result<User>;
+
+interface AuthAdapter {
+	login(props: { email: string; password: string }): Promise<AuthResponse>;
+	signup(props: { email: string; password: string; password_confirm: string }): Promise<AuthResponse>;
+	validate_session(props: { token: string }): Promise<AuthResponse>;
+	logout(props: { token: string; email: string }): Promise<Result<void>>;
+	forgotPassword(props: { email: string; password: string }): Promise<Result<void>>;
+}
+
+interface ChatAdapter {
+	modelList(props: {}): Promise<Result<void>>;
+	txt2img(props: {}): Promise<Result<void>>;
+}
+
+interface ChatMessage {
+	role: string;
+	content: string;
+}
+
+interface ChatMessageType {
+	model: string;
+	knowledge: string;
+	temperature: string;
+	max_new_tokens: string;
+	topk: string;
+}

AgentQnA/ui/svelte/src/app.html

@@ -0,0 +1,17 @@
+<!--
+  Copyright (C) 2025 Intel Corporation
+  SPDX-License-Identifier: Apache-2.0
+-->
+
+<!doctype html>
+<html lang="en">
+	<head>
+		<meta charset="utf-8" />
+		<link rel="icon" href="%sveltekit.assets%/favicon.png" />
+		<meta name="viewport" content="width=device-width" />
+		%sveltekit.head%
+	</head>
+	<body>
+		<div>%sveltekit.body%</div>
+	</body>
+</html>

AgentQnA/ui/svelte/src/app.postcss

@@ -0,0 +1,82 @@
+/* Write your global styles here, in PostCSS syntax */
+@tailwind base;
+@tailwind components;
+@tailwind utilities;
+
+.btn {
+	@apply flex-nowrap;
+}
+a.btn {
+	@apply no-underline;
+}
+.input {
+	@apply text-base;
+}
+
+.bg-dark-blue {
+	background-color: #004a86;
+}
+
+.bg-light-blue {
+	background-color: #0068b5;
+}
+
+.bg-turquoise {
+	background-color: #00a3f6;
+}
+
+.bg-header {
+	background-color: #ffffff;
+}
+
+.bg-button {
+	background-color: #0068b5;
+}
+
+.bg-title {
+	background-color: #f7f7f7;
+}
+
+.text-header {
+	color: #0068b5;
+}
+
+.text-button {
+	color: #0071c5;
+}
+
+.text-title-color {
+	color: rgb(38,38,38);
+}
+
+.font-intel {
+	font-family: "intel-clear","tahoma",Helvetica,"helvetica",Arial,sans-serif;
+}
+
+.font-title-intel {
+	font-family: "intel-one","intel-clear",Helvetica,Arial,sans-serif;
+}
+
+.bg-footer {
+	background-color: #e7e7e7;
+}
+
+.bg-light-green {
+	background-color: #d7f3a1;
+}
+
+.bg-purple {
+	background-color: #653171;
+}
+
+.bg-dark-blue {
+	background-color: #224678;
+}
+
+.border-input-color {
+	border-color: #605e5c;
+}
+
+.w-12\/12 {
+	width: 100%
+}

AgentQnA/ui/svelte/src/lib/assets/Agent/createSub.svelte

@@ -0,0 +1,25 @@
+<!--
+  Copyright (C) 2025 Intel Corporation
+  SPDX-License-Identifier: Apache-2.0
+-->
+
+<svg
+	t="1731984271860"
+	class="w-8 h-8"
+	viewBox="0 0 1024 1024"
+	version="1.1"
+	xmlns="http://www.w3.org/2000/svg"
+	p-id="11418"
+	width="200"
+	height="200"
+	><path
+		d="M0 0m170.666667 0l682.666666 0q170.666667 0 170.666667 170.666667l0 682.666666q0 170.666667-170.666667 170.666667l-682.666666 0q-170.666667 0-170.666667-170.666667l0-682.666666q0-170.666667 170.666667-170.666667Z"
+		fill="#1890FF"
+		fill-opacity=".1"
+		p-id="11419"
+	/><path
+		d="M404.352 552.661333a63.018667 63.018667 0 1 0 0-125.994666 63.018667 63.018667 0 0 0 0 125.994666z m0 213.333334a63.018667 63.018667 0 1 0 0-125.994667 63.018667 63.018667 0 0 0 0 125.994667z m-213.333333-426.666667a63.018667 63.018667 0 1 0 0-125.994667 63.018667 63.018667 0 0 0 0 125.994667z m669.653333-10.88H376.362667a35.669333 35.669333 0 0 1-35.114667-36.096c0-19.882667 15.786667-36.096 35.114667-36.096h484.394666c19.370667 0 35.157333 16.213333 35.157334 36.096a35.669333 35.669333 0 0 1-35.242667 36.096z m16.384 213.034667h-260.821333c-10.410667 0-18.901333-16.213333-18.901334-36.096 0-19.925333 8.490667-36.138667 18.901334-36.138667h260.864c10.410667 0 18.901333 16.213333 18.901333 36.138667-0.042667 19.882667-8.490667 36.096-18.944 36.096z m0 212.992h-260.821333c-10.410667 0-18.901333-16.213333-18.901334-36.096 0-19.925333 8.490667-36.096 18.901334-36.096h260.864c10.410667 0 18.901333 16.213333 18.901333 36.096-0.042667 19.882667-8.490667 36.096-18.944 36.096z"
+		fill="#1890FF"
+		p-id="11420"
+	/></svg
+>

AgentQnA/ui/svelte/src/lib/assets/Agent/download.svelte

@@ -0,0 +1,9 @@
+<!--
+  Copyright (C) 2025 Intel Corporation
+  SPDX-License-Identifier: Apache-2.0
+-->
+
+<svg class="w-3.5 h-3.5 me-2.5" aria-hidden="true" xmlns="http://www.w3.org/2000/svg" fill="currentColor" viewBox="0 0 20 20">
+    <path d="M14.707 7.793a1 1 0 0 0-1.414 0L11 10.086V1.5a1 1 0 0 0-2 0v8.586L6.707 7.793a1 1 0 1 0-1.414 1.414l4 4a1 1 0 0 0 1.416 0l4-4a1 1 0 0 0-.002-1.414Z"/>
+    <path d="M18 12h-2.55l-2.975 2.975a3.5 3.5 0 0 1-4.95 0L4.55 12H2a2 2 0 0 0-2 2v4a2 2 0 0 0 2 2h16a2 2 0 0 0 2-2v-4a2 2 0 0 0-2-2Zm-3 5a1 1 0 1 1 0-2 1 1 0 0 1 0 2Z"/>
+  </svg>

AgentQnA/ui/svelte/src/lib/assets/Agent/eye.svelte

@@ -0,0 +1,16 @@
+<!--
+  Copyright (C) 2025 Intel Corporation
+  SPDX-License-Identifier: Apache-2.0
+-->
+
+<svg
+						class="me-2 h-3 w-3"
+						aria-hidden="true"
+						xmlns="http://www.w3.org/2000/svg"
+						fill="currentColor"
+						viewBox="0 0 20 14"
+					>
+						<path
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AgentQnA/ui/svelte/src/lib/assets/Agent/newAI.svelte

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+  SPDX-License-Identifier: Apache-2.0
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AgentQnA/ui/svelte/src/lib/assets/Agent/resource.svelte

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+  SPDX-License-Identifier: Apache-2.0
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+</svg>

AgentQnA/ui/svelte/src/lib/assets/Agent/search.svelte

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+<!--
+  Copyright (C) 2025 Intel Corporation
+  SPDX-License-Identifier: Apache-2.0
+-->
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+			/></svg
+		>

AgentQnA/ui/svelte/src/lib/assets/Agent/searchDelete.svelte

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+<!--
+  Copyright (C) 2025 Intel Corporation
+  SPDX-License-Identifier: Apache-2.0
+-->
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+				/></svg
+			>

AgentQnA/ui/svelte/src/lib/assets/Agent/searchResult.svelte

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AgentQnA/ui/svelte/src/lib/assets/Agent/star.svelte

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AgentQnA/ui/svelte/src/lib/assets/Agent/summary.svelte

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AgentQnA/ui/svelte/src/lib/assets/Agent/taskIcon.svelte

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+<!--
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+  SPDX-License-Identifier: Apache-2.0
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AgentQnA/ui/svelte/src/lib/assets/Agent/taskResult.svelte

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AgentQnA/ui/svelte/src/lib/assets/Agent/time.svelte

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AgentQnA/ui/svelte/src/lib/assets/Agent/toolIcon.svelte

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AgentQnA/ui/svelte/src/lib/assets/icons/ActiveDislikeButtonIcon.svelte

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AgentQnA/ui/svelte/src/lib/assets/icons/ActiveLikeButtonIcon.svelte

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+  SPDX-License-Identifier: Apache-2.0
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AgentQnA/ui/svelte/src/lib/assets/icons/Folder.svelte

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+  SPDX-License-Identifier: Apache-2.0
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AgentQnA/ui/svelte/src/lib/assets/icons/Knowledge.svelte

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+  SPDX-License-Identifier: Apache-2.0
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AgentQnA/ui/svelte/src/lib/assets/icons/NoTranslate.svelte

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AgentQnA/ui/svelte/src/lib/assets/icons/OldHelp.svelte

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AgentQnA/ui/svelte/src/lib/assets/icons/Question.svelte

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AgentQnA/ui/svelte/src/lib/assets/icons/addKnowledge.svelte

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