audioqna trigger ut

Signed-off-by: Xinyao Wang <xinyao.wang@intel.com>

.github/CODEOWNERS

@@ -1,4 +1,3 @@
-* liang1.lv@intel.com feng.tian@intel.com suyue.chen@intel.com
 /.github/ suyue.chen@intel.com ze.pan@intel.com
 /AgentQnA/ kaokao.lv@intel.com minmin.hou@intel.com
 /AudioQnA/ sihan.chen@intel.com wenjiao.yue@intel.com
@@ -20,4 +19,5 @@
 /Text2Image/ wenjiao.yue@intel.com xinyu.ye@intel.com
 /Translation/ liang1.lv@intel.com sihan.chen@intel.com
 /VideoQnA/ huiling.bao@intel.com xinyao.wang@intel.com
-/VisualQnA/ liang1.lv@intel.com sihan.chen@intel.com
+/VisualQnA/ liang1.lv@intel.com sihan.chen@intel.com
+/*/ liang1.lv@intel.com feng.tian@intel.com suyue.chen@intel.com

.github/ISSUE_TEMPLATE/1_bug_template.yml

@@ -66,7 +66,6 @@ body:
       options:
         - label: Pull docker images from hub.docker.com
         - label: Build docker images from source
-        - label: Other
     validations:
       required: true
 
@@ -75,11 +74,10 @@ body:
     attributes:
       label: Deploy method
       options:
+        - label: Docker compose
         - label: Docker
-        - label: Docker Compose
-        - label: Kubernetes Helm Charts
-        - label: Kubernetes GMC
-        - label: Other
+        - label: Kubernetes
+        - label: Helm
     validations:
       required: true
 
@@ -90,7 +88,6 @@ body:
       options:
         - Single Node
         - Multiple Nodes
-        - Other
       default: 0
     validations:
       required: true
@@ -130,12 +127,3 @@ body:
       render: shell
     validations:
       required: false
-
-
-  - type: textarea
-    id: attachments
-    attributes:
-      label: Attachments
-      description: Attach any relevant files or screenshots.
-    validations:
-      required: false

.github/ISSUE_TEMPLATE/2_feature_template.yml

@@ -66,7 +66,6 @@ body:
       options:
         - Single Node
         - Multiple Nodes
-        - Other
       default: 0
     validations:
       required: true

.github/license_template.txt

@@ -1,2 +1,2 @@
-Copyright (C) 2025 Intel Corporation
+Copyright (C) 2024 Intel Corporation
 SPDX-License-Identifier: Apache-2.0

.github/workflows/_example-workflow.yml

@@ -28,7 +28,7 @@ on:
         default: false
         required: false
         type: boolean
-      test_helmchart:
+      test_k8s:
         default: false
         required: false
         type: boolean
@@ -74,14 +74,15 @@ jobs:
           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
+              git clone 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
+               git clone https://github.com/HabanaAI/vllm-fork.git
+               cd vllm-fork && git checkout 3c39626 && cd ../
           fi
-          git clone --depth 1 --branch ${{ inputs.opea_branch }} https://github.com/opea-project/GenAIComps.git
-          cd GenAIComps && git rev-parse HEAD && cd ../
+          git clone https://github.com/opea-project/GenAIComps.git
+          cd GenAIComps && git checkout ${{ inputs.opea_branch }} && git rev-parse HEAD && cd ../
 
       - name: Build Image
         if: ${{ fromJSON(inputs.build) }}
@@ -109,16 +110,16 @@ jobs:
 
 
 ####################################################################################################
-# helmchart Test
+# K8S Test
 ####################################################################################################
-  test-helmchart:
-    if: ${{ fromJSON(inputs.test_helmchart) }}
-    uses: ./.github/workflows/_helm-e2e.yml
+  test-k8s-manifest:
+    needs: [build-images]
+    if: ${{ fromJSON(inputs.test_k8s) }}
+    uses: ./.github/workflows/_manifest-e2e.yml
     with:
       example: ${{ inputs.example }}
       hardware: ${{ inputs.node }}
       tag: ${{ inputs.tag }}
-      mode: "CD"
     secrets: inherit
 
 ####################################################################################################

.github/workflows/_get-test-matrix.yml

@@ -60,11 +60,9 @@ jobs:
             base_commit=$(git rev-parse HEAD~1) # push event
           fi
           merged_commit=$(git log -1 --format='%H')
-          echo "print all changed files..."
-          git diff --name-only ${base_commit} ${merged_commit}
           changed_files="$(git diff --name-only ${base_commit} ${merged_commit} | \
           grep -vE '${{ inputs.diff_excluded_files }}')" || true
-          echo "filtered changed_files=$changed_files"
+          echo "changed_files=$changed_files"
           export changed_files=$changed_files
           export test_mode=${{ inputs.test_mode }}
           export WORKSPACE=${{ github.workspace }}

.github/workflows/_helm-e2e.yml

@@ -1,233 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-name: Helm Chart E2e Test For Call
-permissions: read-all
-on:
-  workflow_call:
-    inputs:
-      example:
-        default: "chatqna"
-        required: true
-        type: string
-        description: "example to test, chatqna or common/asr"
-      hardware:
-        default: "xeon"
-        required: true
-        type: string
-      dockerhub:
-        default: "false"
-        required: false
-        type: string
-        description: "Set to true if you want to use released docker images at dockerhub. By default using internal docker registry."
-      mode:
-        default: "CD"
-        description: "Whether the test range is CI, CD or CICD"
-        required: false
-        type: string
-      tag:
-        default: "latest"
-        required: false
-        type: string
-      version:
-        default: "0-latest"
-        required: false
-        type: string
-
-jobs:
-  get-test-case:
-    runs-on: ubuntu-latest
-    outputs:
-      value_files: ${{ steps.get-test-files.outputs.value_files }}
-      CHECKOUT_REF: ${{ steps.get-checkout-ref.outputs.CHECKOUT_REF }}
-    steps:
-      - name: Get checkout ref
-        id: get-checkout-ref
-        run: |
-          if [ "${{ github.event_name }}" == "pull_request" ] || [ "${{ github.event_name }}" == "pull_request_target" ]; then
-            CHECKOUT_REF=refs/pull/${{ github.event.number }}/merge
-          else
-            CHECKOUT_REF=${{ github.ref }}
-          fi
-          echo "CHECKOUT_REF=${CHECKOUT_REF}" >> $GITHUB_OUTPUT
-          echo "checkout ref ${CHECKOUT_REF}"
-
-      - name: Checkout Repo
-        uses: actions/checkout@v4
-        with:
-          ref: ${{ steps.get-checkout-ref.outputs.CHECKOUT_REF }}
-          fetch-depth: 0
-
-      - name: Get test Services
-        id: get-test-files
-        run: |
-          set -x
-          if [ "${{ inputs.mode }}" = "CI" ]; then
-            base_commit=${{ github.event.pull_request.base.sha }}
-            merged_commit=$(git log -1 --format='%H')
-            values_files=$(git diff --name-only ${base_commit} ${merged_commit} | \
-            grep "${{ inputs.example }}/kubernetes/helm" | \
-            grep "values.yaml" |\
-            sort -u)
-            echo $values_files
-          elif [ "${{ inputs.mode }}" = "CD" ]; then
-            values_files=$(ls ${{ inputs.example }}/kubernetes/helm/*values.yaml || true)
-          fi
-          value_files="["
-          for file in ${values_files}; do
-            if [ -f "$file" ]; then
-              filename=$(basename "$file")
-              if [[ "$filename" == *"gaudi"* ]]; then
-                if [[ "${{ inputs.hardware }}" == "gaudi" ]]; then
-                  value_files="${value_files}\"${filename}\","
-                fi
-              elif [[ "$filename" == *"nv"* ]]; then
-                continue
-              else
-                if [[ "${{ inputs.hardware }}" == "xeon" ]]; then
-                  value_files="${value_files}\"${filename}\","
-                fi
-              fi
-            fi
-          done
-          value_files="${value_files%,}]"
-
-          echo "value_files=${value_files}"
-          echo "value_files=${value_files}" >> $GITHUB_OUTPUT
-
-  helm-test:
-    needs: [get-test-case]
-    strategy:
-      matrix:
-        value_file: ${{ fromJSON(needs.get-test-case.outputs.value_files) }}
-      fail-fast: false
-    runs-on: k8s-${{ inputs.hardware }}
-    continue-on-error: true
-    steps:
-      - name: Clean Up Working Directory
-        run: |
-          echo "value_file=${{ matrix.value_file }}"
-          sudo rm -rf ${{github.workspace}}/*
-
-      - name: Get checkout ref
-        id: get-checkout-ref
-        run: |
-          if [ "${{ github.event_name }}" == "pull_request" ] || [ "${{ github.event_name }}" == "pull_request_target" ]; then
-            CHECKOUT_REF=refs/pull/${{ github.event.number }}/merge
-          else
-            CHECKOUT_REF=${{ github.ref }}
-          fi
-          echo "CHECKOUT_REF=${CHECKOUT_REF}" >> $GITHUB_OUTPUT
-          echo "checkout ref ${CHECKOUT_REF}"
-
-      - name: Checkout Repo
-        uses: actions/checkout@v4
-        with:
-          ref: ${{ steps.get-checkout-ref.outputs.CHECKOUT_REF }}
-          fetch-depth: 0
-
-      - name: Set variables
-        env:
-          example: ${{ inputs.example }}
-        run: |
-          CHART_NAME="${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}-$(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
-          echo "should_cleanup=false" >> $GITHUB_ENV
-          echo "skip_validate=false" >> $GITHUB_ENV
-          echo "CHART_FOLDER=${example}/kubernetes/helm" >> $GITHUB_ENV
-
-      - name: Helm install
-        id: install
-        env:
-          GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
-          GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }}
-          HUGGINGFACEHUB_API_TOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
-          HFTOKEN: ${{ secrets.HUGGINGFACEHUB_API_TOKEN }}
-          value_file: ${{ matrix.value_file }}
-        run: |
-          set -xe
-          echo "should_cleanup=true" >> $GITHUB_ENV
-          if [[ ! -f ${{ github.workspace }}/${{ env.CHART_FOLDER }}/${value_file} ]]; then
-            echo "No value file found, exiting test!"
-            echo "skip_validate=true" >> $GITHUB_ENV
-            echo "should_cleanup=false" >> $GITHUB_ENV
-            exit 0
-          fi
-
-          for img in `helm template -n $NAMESPACE $RELEASE_NAME oci://ghcr.io/opea-project/charts/${CHART_NAME} -f ${{ inputs.example }}/kubernetes/helm/${value_file} --version ${{ inputs.version }} | grep 'image:' | grep 'opea/' | awk '{print $2}' | xargs`;
-          do
-            # increase helm install wait for for vllm-gaudi case
-            if [[ $img == *"vllm-gaudi"* ]]; then
-              ROLLOUT_TIMEOUT_SECONDS=900s
-            fi
-          done
-          if ! helm install \
-            --create-namespace \
-            --namespace $NAMESPACE \
-            $RELEASE_NAME \
-            oci://ghcr.io/opea-project/charts/${CHART_NAME} \
-            --set global.HUGGINGFACEHUB_API_TOKEN=${HFTOKEN} \
-            --set global.modelUseHostPath=/home/sdp/.cache/huggingface/hub \
-            --set GOOGLE_API_KEY=${{ env.GOOGLE_API_KEY}} \
-            --set GOOGLE_CSE_ID=${{ env.GOOGLE_CSE_ID}} \
-            --set web-retriever.GOOGLE_API_KEY=${{ env.GOOGLE_API_KEY}} \
-            --set web-retriever.GOOGLE_CSE_ID=${{ env.GOOGLE_CSE_ID}} \
-            -f ${{ inputs.example }}/kubernetes/helm/${value_file} \
-            --version ${{ inputs.version }} \
-            --wait --timeout "$ROLLOUT_TIMEOUT_SECONDS"; then
-            echo "Failed to install chart ${{ inputs.example }}"
-            echo "skip_validate=true" >> $GITHUB_ENV
-            .github/workflows/scripts/k8s-utils.sh dump_pods_status $NAMESPACE
-            exit 1
-          fi
-
-      - name: Validate e2e test
-        if: always()
-        run: |
-          set -xe
-          if $skip_validate; then
-            echo "Skip validate"
-          else
-            LOG_PATH=/home/$(whoami)/helm-logs
-            chart=${{ env.CHART_NAME }}
-            helm test -n $NAMESPACE $RELEASE_NAME --logs --timeout "$TEST_TIMEOUT_SECONDS" | tee ${LOG_PATH}/charts-${chart}.log
-            exit_code=$?
-            if [ $exit_code -ne 0 ]; then
-                echo "Chart ${chart} test failed, please check the logs in ${LOG_PATH}!"
-                exit 1
-            fi
-
-            echo "Checking response results, make sure the output is reasonable. "
-            teststatus=false
-            if [[ -f $LOG_PATH/charts-${chart}.log ]] && \
-            [[ $(grep -c "^Phase:.*Failed" $LOG_PATH/charts-${chart}.log) != 0 ]]; then
-                teststatus=false
-                ${{ github.workspace }}/.github/workflows/scripts/k8s-utils.sh dump_all_pod_logs $NAMESPACE
-            else
-                teststatus=true
-            fi
-
-            if [ $teststatus == false ]; then
-                echo "Response check failed, please check the logs in artifacts!"
-                exit 1
-            else
-                echo "Response check succeeded!"
-                exit 0
-            fi
-          fi
-
-      - name: Helm uninstall
-        if: always()
-        run: |
-          if $should_cleanup; then
-            helm uninstall $RELEASE_NAME --namespace $NAMESPACE
-            if ! kubectl delete ns $NAMESPACE --timeout=$KUBECTL_TIMEOUT_SECONDS; then
-              kubectl delete pods --namespace $NAMESPACE --force --grace-period=0 --all
-              kubectl delete ns $NAMESPACE --force --grace-period=0 --timeout=$KUBECTL_TIMEOUT_SECONDS
-            fi
-          fi

.github/workflows/_manifest-e2e.yml

@@ -0,0 +1,185 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+name: Single Kubernetes Manifest E2e Test For Call
+on:
+  workflow_call:
+    inputs:
+      example:
+        default: "ChatQnA"
+        description: "The example to test on K8s"
+        required: true
+        type: string
+      hardware:
+        default: "xeon"
+        description: "Nodes to run the test, xeon or gaudi"
+        required: true
+        type: string
+      tag:
+        default: "latest"
+        description: "Tag to apply to images, default is latest"
+        required: false
+        type: string
+
+jobs:
+  get-test-case:
+    runs-on: ubuntu-latest
+    outputs:
+      test_cases: ${{ steps.test-case-matrix.outputs.test_cases }}
+      CHECKOUT_REF: ${{ steps.get-checkout-ref.outputs.CHECKOUT_REF }}
+    steps:
+      - name: Get checkout ref
+        id: get-checkout-ref
+        run: |
+          if [ "${{ github.event_name }}" == "pull_request" ] || [ "${{ github.event_name }}" == "pull_request_target" ]; then
+            CHECKOUT_REF=refs/pull/${{ github.event.number }}/merge
+          else
+            CHECKOUT_REF=${{ github.ref }}
+          fi
+          echo "CHECKOUT_REF=${CHECKOUT_REF}" >> $GITHUB_OUTPUT
+          echo "checkout ref ${CHECKOUT_REF}"
+
+      - name: Checkout out Repo
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ steps.get-checkout-ref.outputs.CHECKOUT_REF }}
+          fetch-depth: 0
+
+      - name: Get test matrix
+        shell: bash
+        id: test-case-matrix
+        run: |
+          example_l=$(echo ${{ inputs.example }} | tr '[:upper:]' '[:lower:]')
+          cd ${{ github.workspace }}/${{ inputs.example }}/tests
+          run_test_cases=""
+
+          default_test_case=$(find . -type f -name "test_manifest_on_${{ inputs.hardware }}.sh" | cut -d/ -f2)
+          if [ "$default_test_case" ]; then run_test_cases="$default_test_case"; fi
+          other_test_cases=$(find . -type f -name "test_manifest_*_on_${{ inputs.hardware }}.sh" | cut -d/ -f2)
+          echo "default_test_case=$default_test_case"
+          echo "other_test_cases=$other_test_cases"
+
+          if [ "${{ inputs.tag }}" == "ci" ]; then
+            base_commit=$(curl -H "Authorization: token ${{ secrets.GITHUB_TOKEN }}" \
+            "https://api.github.com/repos/opea-project/GenAIExamples/commits?sha=${{ github.event.pull_request.base.ref }}" | jq -r '.[0].sha')
+            merged_commit=$(git log -1 --format='%H')
+            changed_files="$(git diff --name-only ${base_commit} ${merged_commit} | grep -vE '${{ inputs.diff_excluded_files }}')" || true
+          fi
+
+          for test_case in $other_test_cases; do
+            if [ "${{ inputs.tag }}" == "ci" ]; then
+              flag=${test_case%_on_*}
+              flag=${flag#test_compose_}
+              if [[ $(printf '%s\n' "${changed_files[@]}" | grep ${{ inputs.example }} | grep ${flag}) ]]; then
+                run_test_cases="$run_test_cases $test_case"
+              fi
+            else
+              run_test_cases="$run_test_cases $test_case"
+            fi
+          done
+
+          test_cases=$(echo $run_test_cases | tr ' ' '\n' | sort -u | jq -R '.' | jq -sc '.')
+          echo "test_cases=$test_cases"
+          echo "test_cases=$test_cases" >> $GITHUB_OUTPUT
+
+  manifest-test:
+    needs: [get-test-case]
+    strategy:
+      matrix:
+        test_case: ${{ fromJSON(needs.get-test-case.outputs.test_cases) }}
+      fail-fast: false
+    runs-on: "k8s-${{ inputs.hardware }}"
+    continue-on-error: true
+    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
+          echo "checkout ref ${{ env.CHECKOUT_REF }}"
+
+      - name: Checkout out Repo
+        uses: actions/checkout@v4
+        with:
+          ref: ${{ env.CHECKOUT_REF }}
+          fetch-depth: 0
+
+      - name: Set variables
+        env:
+          test_case: ${{ matrix.test_case }}
+        run: |
+          echo "IMAGE_REPO=${OPEA_IMAGE_REPO}opea" >> $GITHUB_ENV
+          echo "IMAGE_TAG=${{ inputs.tag }}" >> $GITHUB_ENV
+          lower_example=$(echo "${{ inputs.example }}" | tr '[:upper:]' '[:lower:]')
+          name=$(echo "$test_case" | cut -d/ -f2 | cut -d'_' -f3- |cut -d'_' -f1 | grep -v 'on' | sed 's/^/-/')
+          echo "NAMESPACE=$lower_example$name-$(tr -dc a-z0-9 </dev/urandom | head -c 16)" >> $GITHUB_ENV
+          echo "ROLLOUT_TIMEOUT_SECONDS=1800s" >> $GITHUB_ENV
+          echo "KUBECTL_TIMEOUT_SECONDS=60s" >> $GITHUB_ENV
+          echo "continue_test=true" >> $GITHUB_ENV
+          echo "should_cleanup=false" >> $GITHUB_ENV
+          echo "skip_validate=true" >> $GITHUB_ENV
+          echo "NAMESPACE=$NAMESPACE"
+
+      - name: Kubectl install
+        id: install
+        env:
+          test_case: ${{ matrix.test_case }}
+        run: |
+          set -x
+          echo "test_case=$test_case"
+          if [[ ! -f ${{ github.workspace }}/${{ inputs.example }}/tests/${test_case} ]]; then
+            echo "No test script found, exist test!"
+            exit 0
+          else
+            ${{ github.workspace }}/${{ inputs.example }}/tests/${test_case} init_${{ inputs.example }}
+            echo "should_cleanup=true" >> $GITHUB_ENV
+            kubectl create ns $NAMESPACE
+            ${{ github.workspace }}/${{ inputs.example }}/tests/${test_case} install_${{ inputs.example }} $NAMESPACE
+            echo "Testing ${{ inputs.example }}, waiting for pod ready..."
+            if kubectl rollout status deployment --namespace "$NAMESPACE" --timeout "$ROLLOUT_TIMEOUT_SECONDS"; then
+              echo "Testing manifests ${{ inputs.example }}, waiting for pod ready done!"
+              echo "skip_validate=false" >> $GITHUB_ENV
+            else
+              echo "Timeout waiting for pods in namespace $NAMESPACE to be ready!"
+              .github/workflows/scripts/k8s-utils.sh dump_pods_status $NAMESPACE
+              exit 1
+            fi
+            sleep 60
+          fi
+
+      - name: Validate e2e test
+        if: always()
+        env:
+          test_case: ${{ matrix.test_case }}
+        run: |
+          if $skip_validate; then
+            echo "Skip validate"
+          else
+            if ${{ github.workspace }}/${{ inputs.example }}/tests/${test_case} validate_${{ inputs.example }} $NAMESPACE ; then
+              echo "Validate ${test_case} successful!"
+            else
+              echo "Validate ${test_case} failure!!!"
+              echo "Check the logs in 'Dump logs when e2e test failed' step!!!"
+              exit 1
+            fi
+          fi
+
+      - name: Dump logs when e2e test failed
+        if: failure()
+        run: |
+          .github/workflows/scripts/k8s-utils.sh dump_all_pod_logs $NAMESPACE
+
+      - name: Kubectl uninstall
+        if: always()
+        run: |
+          if $should_cleanup; then
+            if ! kubectl delete ns $NAMESPACE --timeout=$KUBECTL_TIMEOUT_SECONDS; then
+              kubectl delete pods --namespace $NAMESPACE --force --grace-period=0 --all
+              kubectl delete ns $NAMESPACE --force --grace-period=0 --timeout=$KUBECTL_TIMEOUT_SECONDS
+            fi
+          fi

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

@@ -89,7 +89,7 @@ jobs:
           echo "test_cases=$test_cases"
           echo "test_cases=$test_cases" >> $GITHUB_OUTPUT
 
-  compose-test:
+  run-test:
     needs: [get-test-case]
     strategy:
       matrix:
@@ -132,9 +132,9 @@ jobs:
           PINECONE_KEY_LANGCHAIN_TEST: ${{ secrets.PINECONE_KEY_LANGCHAIN_TEST }}
           SDK_BASE_URL: ${{ secrets.SDK_BASE_URL }}
           SERVING_TOKEN: ${{ secrets.SERVING_TOKEN }}
-          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
           IMAGE_REPO: ${{ inputs.registry }}
           IMAGE_TAG: ${{ inputs.tag }}
+          opea_branch: "refactor_comps"
           example: ${{ inputs.example }}
           hardware: ${{ inputs.hardware }}
           test_case: ${{ matrix.test_case }}

.github/workflows/check-online-doc-build.yml

@@ -13,7 +13,7 @@ on:
 
 jobs:
   build:
-    runs-on: ubuntu-22.04
+    runs-on: ubuntu-latest
     steps:
 
     - name: Checkout

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

@@ -35,9 +35,9 @@ on:
         description: 'Test examples with docker compose'
         required: false
         type: boolean
-      test_helmchart:
-        default: true
-        description: 'Test examples with helm charts'
+      test_k8s:
+        default: false
+        description: 'Test examples with k8s'
         required: false
         type: boolean
       test_gmc:
@@ -103,7 +103,7 @@ jobs:
       tag: ${{ inputs.tag }}
       build: ${{ fromJSON(inputs.build) }}
       test_compose: ${{ fromJSON(inputs.test_compose) }}
-      test_helmchart: ${{ fromJSON(inputs.test_helmchart) }}
+      test_k8s: ${{ fromJSON(inputs.test_k8s) }}
       test_gmc: ${{ fromJSON(inputs.test_gmc) }}
       opea_branch: ${{ inputs.opea_branch }}
       inject_commit: ${{ inputs.inject_commit }}

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

@@ -1,76 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-name: E2E Test with Helm Charts
-
-on:
-  pull_request_target:
-    branches: [main]
-    types: [opened, reopened, ready_for_review, synchronize] # added `ready_for_review` since draft is skipped
-    paths:
-      - "!**.md"
-      - "**/helm/**"
-  workflow_dispatch:
-
-concurrency:
-  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
-  cancel-in-progress: true
-
-jobs:
-  job1:
-    name: Get-Test-Matrix
-    runs-on: ubuntu-latest
-    outputs:
-      run_matrix: ${{ steps.get-test-matrix.outputs.run_matrix }}
-    steps:
-      - name: Checkout Repo
-        uses: actions/checkout@v4
-        with:
-          ref: "refs/pull/${{ github.event.number }}/merge"
-          fetch-depth: 0
-
-      - name: Get Test Matrix
-        id: get-test-matrix
-        run: |
-          set -x
-          echo "base_commit=${{ github.event.pull_request.base.sha }}"
-          base_commit=${{ github.event.pull_request.base.sha }}
-          merged_commit=$(git log -1 --format='%H')
-          values_files=$(git diff --name-only ${base_commit} ${merged_commit} | \
-          grep "values.yaml" | \
-          sort -u ) #CodeGen/kubernetes/helm/cpu-values.yaml
-          run_matrix="{\"include\":["
-          for values_file in ${values_files}; do
-            if [ -f "$values_file" ]; then
-              valuefile=$(basename "$values_file")   # cpu-values.yaml
-              example=$(echo "$values_file" | cut -d'/' -f1) # CodeGen
-              if [[ "$valuefile" == *"gaudi"* ]]; then
-                hardware="gaudi"
-              elif [[ "$valuefile" == *"nv"* ]]; then
-                continue
-              else
-                hardware="xeon"
-              fi
-              echo "example=${example}, hardware=${hardware}, valuefile=${valuefile}"
-              if [[ $(echo ${run_matrix} | grep -c "{\"example\":\"${example}\",\"hardware\":\"${hardware}\"},") == 0 ]]; then
-                run_matrix="${run_matrix}{\"example\":\"${example}\",\"hardware\":\"${hardware}\"},"
-                echo "------------------ add one values file ------------------"
-              fi
-            fi
-          done
-          run_matrix="${run_matrix%,}"
-          run_matrix=$run_matrix"]}"
-          echo "run_matrix="${run_matrix}""
-          echo "run_matrix="${run_matrix}"" >> $GITHUB_OUTPUT
-
-  helm-chart-test:
-    needs: [job1]
-    if: always() && ${{ needs.job1.outputs.run_matrix.example.length > 0 }}
-    uses: ./.github/workflows/_helm-e2e.yml
-    strategy:
-      matrix: ${{ fromJSON(needs.job1.outputs.run_matrix) }}
-    with:
-      example: ${{ matrix.example }}
-      hardware: ${{ matrix.hardware }}
-      mode: "CI"
-    secrets: inherit

.github/workflows/pr-check-duplicated-image.yml

@@ -5,7 +5,7 @@ name: Check Duplicated Images
 
 on:
   pull_request:
-    branches: [main]
+    branches: [main, genaicomps_refactor]
     types: [opened, reopened, ready_for_review, synchronize]
     paths:
       - "**/docker_image_build/*.yaml"

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

@@ -4,8 +4,8 @@
 name: E2E test with docker compose
 
 on:
-  pull_request_target:
-    branches: ["main", "*rc"]
+  pull_request:
+    branches: ["main", "*rc", "genaicomps_refactor"]
     types: [opened, reopened, ready_for_review, synchronize] # added `ready_for_review` since draft is skipped
     paths:
       - "**/Dockerfile**"
@@ -28,7 +28,7 @@ jobs:
     if: ${{ !github.event.pull_request.draft }}
     uses: ./.github/workflows/_get-test-matrix.yml
     with:
-      diff_excluded_files: '\.github|\.md|\.txt|kubernetes|gmc|assets|benchmark'
+      diff_excluded_files: '.github|*.md|*.txt|kubernetes|manifest|gmc|assets|benchmark'
 
   example-test:
     needs: [get-test-matrix]
@@ -42,5 +42,5 @@ jobs:
       tag: "ci"
       example: ${{ matrix.example }}
       hardware: ${{ matrix.hardware }}
-      diff_excluded_files: '\.github|\.md|\.txt|kubernetes|gmc|assets|benchmark'
+      diff_excluded_files: '.github|*.md|*.txt|kubernetes|manifest|gmc|assets|benchmark'
     secrets: inherit

.github/workflows/pr-dockerfile-path-and-build-yaml-scan.yml

@@ -5,7 +5,7 @@ name: Compose file and dockerfile path checking
 
 on:
   pull_request:
-    branches: [main]
+    branches: [main, genaicomps_refactor]
     types: [opened, reopened, ready_for_review, synchronize]
 
 jobs:
@@ -21,7 +21,8 @@ jobs:
       - name: Clone Repo GenAIComps
         run: |
           cd ..
-          git clone --depth 1 https://github.com/opea-project/GenAIComps.git
+          git clone https://github.com/opea-project/GenAIComps.git
+          cd GenAIComps && git checkout refactor_comps
 
       - name: Check for Missing Dockerfile Paths in GenAIComps
         run: |
@@ -60,7 +61,7 @@ jobs:
           shopt -s globstar
           no_add="FALSE"
           cd ${{github.workspace}}
-          Dockerfiles=$(realpath $(find ./ -name '*Dockerfile*' ! -path '*/tests/*'))
+          Dockerfiles=$(realpath $(find ./ -name '*Dockerfile*'))
           if [ -n "$Dockerfiles" ]; then
             for dockerfile in $Dockerfiles; do
               service=$(echo "$dockerfile" | awk -F '/GenAIExamples/' '{print $2}' | awk -F '/' '{print $2}')

.github/workflows/pr-gmc-e2e.yaml

@@ -8,10 +8,11 @@ on:
     branches: ["main", "*rc"]
     types: [opened, reopened, ready_for_review, synchronize] # added `ready_for_review` since draft is skipped
     paths:
-      - "**/kubernetes/gmc/**"
+      - "**/kubernetes/**/gmc/**"
       - "**/tests/test_gmc**"
       - "!**.md"
       - "!**.txt"
+      - "!**/kubernetes/**/manifest/**"
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
@@ -21,7 +22,7 @@ jobs:
   job1:
     uses: ./.github/workflows/_get-test-matrix.yml
     with:
-      diff_excluded_files: '\.github|docker_compose|assets|\.md|\.txt'
+      diff_excluded_files: '.github|docker_compose|manifest|assets|*.md|*.txt'
       test_mode: "gmc"
 
   gmc-test:

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

@@ -5,7 +5,7 @@ name: Check hyperlinks and relative path validity
 
 on:
   pull_request:
-    branches: [main]
+    branches: [main, genaicomps_refactor]
     types: [opened, reopened, ready_for_review, synchronize]
 
 jobs:

.github/workflows/pr-manifest-e2e.yml.disabled

@@ -0,0 +1,42 @@
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+name: E2E test with manifests
+
+on:
+  pull_request_target:
+    branches: ["main", "*rc"]
+    types: [opened, reopened, ready_for_review, synchronize] # added `ready_for_review` since draft is skipped
+    paths:
+      - "**/Dockerfile**"
+      - "**.py"
+      - "**/kubernetes/**/manifest/**"
+      - "**/tests/test_manifest**"
+      - "!**.md"
+      - "!**.txt"
+      - "!**/kubernetes/**/gmc/**"
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  job1:
+    uses: ./.github/workflows/_get-test-matrix.yml
+    with:
+      diff_excluded_files: '.github|docker_compose|gmc|assets|*.md|*.txt|benchmark'
+      test_mode: "manifest"
+
+  run-example:
+    needs: job1
+    strategy:
+      matrix: ${{ fromJSON(needs.job1.outputs.run_matrix) }}
+      fail-fast: false
+    uses: ./.github/workflows/_example-workflow.yml
+    with:
+      node: ${{ matrix.hardware }}
+      example: ${{ matrix.example }}
+      tag: ${{ github.event.pull_request.head.sha }}
+      test_k8s: true
+    secrets: inherit

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

@@ -40,7 +40,7 @@ jobs:
       - name: Create Issue
         uses: daisy-ycguo/create-issue-action@stable
         with:
-          token: ${{ secrets.ACTION_TOKEN }}
+          token: ${{ secrets.Infra_Issue_Token }}
           owner: opea-project
           repo: GenAIInfra
           title: |

.github/workflows/scripts/check_duplicated_image.py

@@ -9,8 +9,6 @@ import sys
 import yaml
 
 images = {}
-dockerfiles = {}
-errors = []
 
 
 def check_docker_compose_build_definition(file_path):
@@ -32,26 +30,18 @@ def check_docker_compose_build_definition(file_path):
                 if not os.path.isfile(dockerfile):
                     # dockerfile not exists in the current repo context, assume it's in 3rd party context
                     dockerfile = os.path.normpath(os.path.join(context, build.get("dockerfile", "")))
-                item = {"file_path": file_path, "service": service, "dockerfile": dockerfile, "image": image}
+                item = {"file_path": file_path, "service": service, "dockerfile": dockerfile}
                 if image in images and dockerfile != images[image]["dockerfile"]:
-                    errors.append(
-                        f"ERROR: !!! Found Conflicts !!!\n"
-                        f"Image: {image}, Dockerfile: {dockerfile}, defined in Service: {service}, File: {file_path}\n"
+                    print("ERROR: !!! Found Conflicts !!!")
+                    print(f"Image: {image}, Dockerfile: {dockerfile}, defined in Service: {service}, File: {file_path}")
+                    print(
                         f"Image: {image}, Dockerfile: {images[image]['dockerfile']}, defined in Service: {images[image]['service']}, File: {images[image]['file_path']}"
                     )
+                    sys.exit(1)
                 else:
                     # print(f"Add Image: {image} Dockerfile: {dockerfile}")
                     images[image] = item
 
-                if dockerfile in dockerfiles and image != dockerfiles[dockerfile]["image"]:
-                    errors.append(
-                        f"WARNING: Different images using the same Dockerfile\n"
-                        f"Dockerfile: {dockerfile}, Image: {image}, defined in Service: {service}, File: {file_path}\n"
-                        f"Dockerfile: {dockerfile}, Image: {dockerfiles[dockerfile]['image']}, defined in Service: {dockerfiles[dockerfile]['service']}, File: {dockerfiles[dockerfile]['file_path']}"
-                    )
-                else:
-                    dockerfiles[dockerfile] = item
-
 
 def parse_arg():
     parser = argparse.ArgumentParser(
@@ -66,12 +56,6 @@ def main():
     for file_path in args.files:
         check_docker_compose_build_definition(file_path)
     print("SUCCESS: No Conlicts Found.")
-    if errors:
-        for error in errors:
-            print(error)
-        sys.exit(1)
-    else:
-        print("SUCCESS: No Conflicts Found.")
     return 0
 
 

.github/workflows/scripts/docker_compose_clean_up.sh

@@ -26,20 +26,14 @@ case "$1" in
         echo "Release all ports used by the services in $yaml_file ..."
         pip install jq yq
         ports=$(yq '.services[].ports[] | split(":")[0]' $yaml_file | grep -o '[0-9a-zA-Z_-]\+')
-        echo "All ports list..."
         echo "$ports"
         for port in $ports; do
           if [[ $port =~ [a-zA-Z_-] ]]; then
             port=$(grep -E "export $port=" tests/$test_case | cut -d'=' -f2)
           fi
-          if [[ $port =~ [0-9] ]]; then
-            if [[ $port == 5000 ]]; then
-              echo "Error: Port 5000 is used by local docker registry, please DO NOT use it in docker compose deployment!!!"
-              exit 1
-            fi
-            cid=$(docker ps --filter "publish=${port}" --format "{{.ID}}")
-            if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && echo "release $port"; fi
-          fi
+          echo $port
+          cid=$(docker ps --filter "publish=${port}" --format "{{.ID}}")
+          if [[ ! -z "$cid" ]]; then docker stop $cid && docker rm $cid && sleep 1s; fi
         done
         ;;
     *)

.github/workflows/scripts/get_test_matrix.sh

@@ -17,15 +17,15 @@ for example in ${examples}; do
     cd tests
     ls -l
     if [[ "$test_mode" == "docker_image_build" ]]; then
-        hardware_list="gaudi xeon"
+        find_name="test_manifest_on_*.sh"
     else
         find_name="test_${test_mode}*_on_*.sh"
-        hardware_list=$(find . -type f -name "${find_name}" | cut -d/ -f2 | cut -d. -f1 | awk -F'_on_' '{print $2}'| sort -u)
     fi
+    hardware_list=$(find . -type f -name "${find_name}" | cut -d/ -f2 | cut -d. -f1 | awk -F'_on_' '{print $2}'| sort -u)
     echo -e "Test supported hardware list: \n${hardware_list}"
 
     run_hardware=""
-    if [[ $(printf '%s\n' "${changed_files[@]}" | grep ${example} | cut -d'/' -f2 | grep -E '\.py|Dockerfile*|ui|docker_image_build' ) ]]; then
+    if [[ $(printf '%s\n' "${changed_files[@]}" | grep ${example} | cut -d'/' -f2 | grep -E '*.py|Dockerfile*|ui|docker_image_build' ) ]]; then
         # run test on all hardware if megaservice or ui code change
         run_hardware=$hardware_list
     else

.github/workflows/scripts/k8s-utils.sh

@@ -2,7 +2,7 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-set -e
+#set -xe
 
 function dump_pod_log() {
     pod_name=$1
@@ -12,7 +12,7 @@ function dump_pod_log() {
     kubectl describe pod $pod_name -n $namespace
     echo "-----------------------------------"
     echo "#kubectl logs $pod_name -n $namespace"
-    kubectl logs $pod_name -n $namespace --all-containers --prefix=true
+    kubectl logs $pod_name -n $namespace
     echo "-----------------------------------"
 }
 
@@ -44,13 +44,8 @@ function dump_pods_status() {
 
 function dump_all_pod_logs() {
     namespace=$1
-    echo "------SUMMARY of POD STATUS in NS $namespace------"
-    kubectl get pods -n $namespace -o wide
-    echo "------SUMMARY of SVC STATUS in NS $namespace------"
-    kubectl get services -n $namespace -o wide
-    echo "------SUMMARY of endpoint STATUS in NS $namespace------"
-    kubectl get endpoints -n $namespace -o wide
     echo "-----DUMP POD STATUS AND LOG in NS $namespace------"
+
     pods=$(kubectl get pods -n $namespace -o jsonpath='{.items[*].metadata.name}')
     for pod_name in $pods
     do

.pre-commit-config.yaml

@@ -7,7 +7,7 @@ ci:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v5.0.0
+    rev: v4.6.0
     hooks:
       - id: end-of-file-fixer
         files: (.*\.(py|md|rst|yaml|yml|json|ts|js|html|svelte|sh))$
@@ -100,18 +100,18 @@ repos:
           - prettier@3.2.5
 
   - repo: https://github.com/psf/black.git
-    rev: 24.10.0
+    rev: 24.4.2
     hooks:
       - id: black
         files: (.*\.py)$
 
   - repo: https://github.com/asottile/blacken-docs
-    rev: 1.19.1
+    rev: 1.18.0
     hooks:
       - id: blacken-docs
         args: [--line-length=120, --skip-errors]
         additional_dependencies:
-          - black==24.10.0
+          - black==24.4.2
 
   - repo: https://github.com/codespell-project/codespell
     rev: v2.3.0
@@ -122,7 +122,7 @@ repos:
           - tomli
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.6
+    rev: v0.5.0
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix, --no-cache]

AgentQnA/README.md

@@ -2,8 +2,8 @@
 
 ## Overview
 
-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)
+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 the worker agent and other tools to gather information and come up with answers. The worker agent uses the retrieval tool to generate answers to the queries posted by the supervisor agent. Other tools used by the supervisor agent may include APIs to interface knowledge graphs, SQL databases, external knowledge bases, etc.
+![Architecture Overview](assets/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.
 
@@ -38,7 +38,6 @@ flowchart LR
     end
     AG_REACT([Agent MicroService - react]):::blue
     AG_RAG([Agent MicroService - rag]):::blue
-    AG_SQL([Agent MicroService - sql]):::blue
     LLM_gen{{LLM Service <br>}}
     DP([Data Preparation MicroService]):::blue
     TEI_RER{{Reranking service<br>}}
@@ -52,7 +51,6 @@ flowchart LR
     direction LR
     a[User Input Query] --> AG_REACT
     AG_REACT --> AG_RAG
-    AG_REACT --> AG_SQL
     AG_RAG --> DocIndexRetriever-MegaService
     EM ==> RET
     RET ==> RER
@@ -61,7 +59,6 @@ flowchart LR
     %% Embedding service flow
     direction LR
     AG_RAG <-.-> LLM_gen
-    AG_SQL <-.-> LLM_gen
     AG_REACT <-.-> LLM_gen
     EM <-.-> TEI_EM
     RET <-.-> R_RET
@@ -78,11 +75,11 @@ flowchart LR
 ### Why Agent for question answering?
 
 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.
+   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. Use tools to get additional knowledge.
+   For example, knowledge graphs and SQL databases can be exposed as APIs for Agents to gather knowledge that may be missing in the retrieval vector database.
+3. Hierarchical agent can further improve performance.
+   Expert worker agents, such as retrieval agent, knowledge graph agent, SQL agent, etc., 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.
 
 ## Deployment with docker
 
@@ -103,7 +100,7 @@ Then build the agent docker image. Both the supervisor agent and the worker agen
 
 ```
 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 .
+docker build -t opea/agent-langchain:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/agent/langchain/Dockerfile .
 ```
 
 2. Set up environment for this example </br>
@@ -151,55 +148,28 @@ docker build -t opea/agent:latest --build-arg https_proxy=$https_proxy --build-a
    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 other tools. </br>
+4. 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.
 
    ```
    docker run -d -p=8080:8000 docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0
    ```
 
-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.
+5. Launch agent services</br>
+   We provide two options for `llm_engine` of the agents: 1. open-source LLMs, 2. OpenAI models via API calls.
+
+   Deploy it on Gaudi or Xeon respectively
 
    ::::{tab-set}
    :::{tab-item} Gaudi
    :sync: Gaudi
 
-   On Gaudi2 we will serve `meta-llama/Meta-Llama-3.1-70B-Instruct` using vllm.
+   To use open-source LLMs on Gaudi2, run commands below.
 
-   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
+   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi
+   bash launch_tgi_gaudi.sh
+   bash launch_agent_service_tgi_gaudi.sh
    ```
 
    :::
@@ -209,7 +179,6 @@ docker build -t opea/agent:latest --build-arg https_proxy=$https_proxy --build-a
    To use OpenAI models, run commands below.
 
    ```
-   export OPENAI_API_KEY=<your-openai-key>
    cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon
    bash launch_agent_service_openai.sh
    ```
@@ -217,20 +186,13 @@ docker build -t opea/agent:latest --build-arg https_proxy=$https_proxy --build-a
    :::
    ::::
 
-## Deploy using Helm Chart
-
-Refer to the [AgentQnA helm chart](./kubernetes/helm/README.md) for instructions on deploying AgentQnA on Kubernetes.
-
 ## Validate services
 
 First look at logs of the agent docker containers:
 
 ```
-# worker RAG agent
+# worker agent
 docker logs rag-agent-endpoint
-
-# worker SQL agent
-docker logs sql-agent-endpoint
 ```
 
 ```
@@ -240,36 +202,22 @@ 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:
+Second, validate worker agent:
 
 ```
 curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
-     "messages": "Michael Jackson song Thriller"
+     "query": "Most recent album by Taylor Swift"
     }'
 ```
 
-Third, validate worker SQL agent:
-
-```
-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:
+Third, 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?"
+     "query": "Most recent album by Taylor Swift"
     }'
 ```
 
-## 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).
+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/langchain/README.md).

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

@@ -1,101 +0,0 @@
-# Single node on-prem deployment with Docker Compose on AMD GPU
-
-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>
-   # Set AMD GPU settings
-   export AGENTQNA_CARD_ID="card1"
-   export AGENTQNA_RENDER_ID="renderD136"
-   ```
-
-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. 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
-
-   ```
-   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-   bash launch_agent_service_tgi_rocm.sh
-   ```
-
-6. [Optional] Build `Agent` docker image if pulling images failed.
-
-   ```
-   git clone https://github.com/opea-project/GenAIComps.git
-   cd GenAIComps
-   docker build -t opea/agent:latest -f comps/agent/src/Dockerfile .
-   ```
-
-## Validate services
-
-First look at logs of the agent docker containers:
-
-```
-# worker agent
-docker logs rag-agent-endpoint
-```
-
-```
-# supervisor agent
-docker logs react-agent-endpoint
-```
-
-You should see something like "HTTP server setup successful" if the docker containers are started successfully.</p>
-
-Second, validate worker agent:
-
-```
-curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
-     "query": "Most recent album by Taylor Swift"
-    }'
-```
-
-Third, validate supervisor agent:
-
-```
-curl http://${host_ip}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
-     "query": "Most recent album by Taylor Swift"
-    }'
-```
-
-## 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/compose.yaml

@@ -31,7 +31,7 @@ services:
     command: --model-id ${LLM_MODEL_ID} --max-input-length 4096 --max-total-tokens 8192
 
   worker-rag-agent:
-    image: opea/agent:latest
+    image: opea/agent-langchain:latest
     container_name: rag-agent-endpoint
     volumes:
       # - ${WORKDIR}/GenAIExamples/AgentQnA/docker_image_build/GenAIComps/comps/agent/langchain/:/home/user/comps/agent/langchain/
@@ -49,7 +49,7 @@ services:
       model: ${LLM_MODEL_ID}
       temperature: ${temperature}
       max_new_tokens: ${max_new_tokens}
-      stream: false
+      streaming: false
       tools: /home/user/tools/worker_agent_tools.yaml
       require_human_feedback: false
       RETRIEVAL_TOOL_URL: ${RETRIEVAL_TOOL_URL}
@@ -62,7 +62,7 @@ services:
       port: 9095
 
   supervisor-react-agent:
-    image: opea/agent:latest
+    image: opea/agent-langchain:latest
     container_name: react-agent-endpoint
     depends_on:
       - agent-tgi-server
@@ -83,7 +83,7 @@ services:
       model: ${LLM_MODEL_ID}
       temperature: ${temperature}
       max_new_tokens: ${max_new_tokens}
-      stream: false
+      streaming: false
       tools: /home/user/tools/supervisor_agent_tools.yaml
       require_human_feedback: false
       no_proxy: ${no_proxy}

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

@@ -40,8 +40,8 @@ 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}:6007/v1/dataprep/get"
-export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/delete"
+export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep"
+export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/get_file"
+export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/delete_file"
 
 docker compose -f compose.yaml up -d

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

@@ -41,6 +41,6 @@ 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}:6007/v1/dataprep/get"
-export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/delete"
+export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep"
+export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/get_file"
+export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6007/v1/dataprep/delete_file"

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

@@ -41,38 +41,26 @@ This example showcases a hierarchical multi-agent system for question-answering
    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
+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
    ```
-6. Launch multi-agent system
+5. Launch `Agent` service
 
-   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.
+   The configurations of the supervisor agent and the worker agent are defined in the docker-compose yaml file. We currently use openAI GPT-4o-mini as LLM, and llama3.1-70B-instruct (served by TGI-Gaudi) in Gaudi example. To use openai llm, run command below.
 
    ```
    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.
+6. [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 .
+   docker build -t opea/agent-langchain:latest -f comps/agent/langchain/Dockerfile .
    ```
 
 ## Validate services
@@ -80,11 +68,8 @@ This example showcases a hierarchical multi-agent system for question-answering
 First look at logs of the agent docker containers:
 
 ```
-# worker RAG agent
+# worker agent
 docker logs rag-agent-endpoint
-
-# worker SQL agent
-docker logs sql-agent-endpoint
 ```
 
 ```
@@ -94,30 +79,22 @@ 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:
+Second, validate worker agent:
 
 ```
 curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
-     "messages": "Michael Jackson song Thriller"
+     "query": "Most recent album by Taylor Swift"
     }'
 ```
 
-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:
+Third, 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?"
+     "query": "Most recent album by Taylor Swift"
     }'
 ```
 
 ## 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).
+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/langchain/README.md).

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

@@ -3,7 +3,7 @@
 
 services:
   worker-rag-agent:
-    image: opea/agent:latest
+    image: opea/agent-langchain:latest
     container_name: rag-agent-endpoint
     volumes:
       - ${TOOLSET_PATH}:/home/user/tools/
@@ -19,7 +19,7 @@ services:
       model: ${model}
       temperature: ${temperature}
       max_new_tokens: ${max_new_tokens}
-      stream: false
+      streaming: false
       tools: /home/user/tools/worker_agent_tools.yaml
       require_human_feedback: false
       RETRIEVAL_TOOL_URL: ${RETRIEVAL_TOOL_URL}
@@ -31,36 +31,9 @@ services:
       LANGCHAIN_PROJECT: "opea-worker-agent-service"
       port: 9095
 
-  worker-sql-agent:
-    image: opea/agent:latest
-    container_name: sql-agent-endpoint
-    volumes:
-      - ${WORKDIR}/TAG-Bench/:/home/user/TAG-Bench # SQL database
-    ports:
-      - "9096:9096"
-    ipc: host
-    environment:
-      ip_address: ${ip_address}
-      strategy: sql_agent
-      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}
-      model: ${model}
-      temperature: 0
-      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
+    image: opea/agent-langchain:latest
     container_name: react-agent-endpoint
     depends_on:
       - worker-rag-agent
@@ -78,7 +51,7 @@ services:
       model: ${model}
       temperature: ${temperature}
       max_new_tokens: ${max_new_tokens}
-      stream: false
+      streaming: false
       tools: /home/user/tools/supervisor_agent_tools.yaml
       require_human_feedback: false
       no_proxy: ${no_proxy}

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

@@ -13,10 +13,7 @@ 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/hpu/gaudi/README.md

@@ -1,6 +1,6 @@
 # Single node on-prem deployment AgentQnA on Gaudi
 
-This example showcases a hierarchical multi-agent system for question-answering applications. We deploy the example on Gaudi using open-source LLMs.
+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
@@ -45,58 +45,27 @@ For more details, please refer to the deployment guide [here](../../../../README
    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
+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
    ```
-6. Launch multi-agent system
+5. Launch `Agent` service
 
-   On Gaudi2 we will serve `meta-llama/Meta-Llama-3.1-70B-Instruct` using vllm.
+   To use open-source LLMs on Gaudi2, run commands below.
 
-   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
+   ```
+   cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi
+   bash launch_tgi_gaudi.sh
+   bash launch_agent_service_tgi_gaudi.sh
    ```
 
-   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.
+6. [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 .
+   docker build -t opea/agent-langchain:latest -f comps/agent/langchain/Dockerfile .
    ```
 
 ## Validate services
@@ -104,11 +73,8 @@ For more details, please refer to the deployment guide [here](../../../../README
 First look at logs of the agent docker containers:
 
 ```
-# worker RAG agent
+# worker agent
 docker logs rag-agent-endpoint
-
-# worker SQL agent
-docker logs sql-agent-endpoint
 ```
 
 ```
@@ -118,30 +84,22 @@ 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:
+Second, validate worker agent:
 
 ```
 curl http://${host_ip}:9095/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
-     "messages": "Michael Jackson song Thriller"
+     "query": "Most recent album by Taylor Swift"
     }'
 ```
 
-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:
+Third, 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?"
+     "query": "Most recent album by Taylor Swift"
     }'
 ```
 
 ## 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).
+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/langchain/README.md).

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

@@ -3,9 +3,10 @@
 
 services:
   worker-rag-agent:
-    image: opea/agent:latest
+    image: opea/agent-langchain:latest
     container_name: rag-agent-endpoint
     volumes:
+      # - ${WORKDIR}/GenAIExamples/AgentQnA/docker_image_build/GenAIComps/comps/agent/langchain/:/home/user/comps/agent/langchain/
       - ${TOOLSET_PATH}:/home/user/tools/
     ports:
       - "9095:9095"
@@ -14,13 +15,13 @@ services:
       ip_address: ${ip_address}
       strategy: rag_agent_llama
       recursion_limit: ${recursion_limit_worker}
-      llm_engine: vllm
+      llm_engine: tgi
       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
+      streaming: false
       tools: /home/user/tools/worker_agent_tools.yaml
       require_human_feedback: false
       RETRIEVAL_TOOL_URL: ${RETRIEVAL_TOOL_URL}
@@ -32,41 +33,14 @@ services:
       LANGCHAIN_PROJECT: "opea-worker-agent-service"
       port: 9095
 
-  worker-sql-agent:
-    image: opea/agent:latest
-    container_name: sql-agent-endpoint
-    volumes:
-      - ${WORKDIR}/GenAIExamples/AgentQnA/tests:/home/user/chinook-db # test db
-    ports:
-      - "9096:9096"
-    ipc: host
-    environment:
-      ip_address: ${ip_address}
-      strategy: sql_agent_llama
-      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
+    image: opea/agent-langchain:latest
     container_name: react-agent-endpoint
     depends_on:
       - worker-rag-agent
-      - worker-sql-agent
     volumes:
+      # - ${WORKDIR}/GenAIExamples/AgentQnA/docker_image_build/GenAIComps/comps/agent/langchain/:/home/user/comps/agent/langchain/
       - ${TOOLSET_PATH}:/home/user/tools/
     ports:
       - "9090:9090"
@@ -75,13 +49,13 @@ services:
       ip_address: ${ip_address}
       strategy: react_llama
       recursion_limit: ${recursion_limit_supervisor}
-      llm_engine: vllm
+      llm_engine: tgi
       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
+      streaming: false
       tools: /home/user/tools/supervisor_agent_tools.yaml
       require_human_feedback: false
       no_proxy: ${no_proxy}
@@ -92,5 +66,4 @@ 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

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

@@ -16,8 +16,8 @@ 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://${ip_address}:8086"
-export temperature=0
+export LLM_ENDPOINT_URL="http://${ip_address}:8085"
+export temperature=0.01
 export max_new_tokens=4096
 
 # agent related environment variables
@@ -26,11 +26,7 @@ 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_image_build/build.yaml

@@ -2,18 +2,12 @@
 # SPDX-License-Identifier: Apache-2.0
 
 services:
-  agent:
+  agent-langchain:
     build:
       context: GenAIComps
-      dockerfile: comps/agent/src/Dockerfile
+      dockerfile: comps/agent/langchain/Dockerfile
       args:
         http_proxy: ${http_proxy}
         https_proxy: ${https_proxy}
         no_proxy: ${no_proxy}
-    image: ${REGISTRY:-opea}/agent:${TAG:-latest}
-  agent-ui:
-    build:
-      context: ../ui
-      dockerfile: ./docker/Dockerfile
-    extends: agent
-    image: ${REGISTRY:-opea}/agent-ui:${TAG:-latest}
+    image: ${REGISTRY:-opea}/agent-langchain:${TAG:-latest}

AgentQnA/kubernetes/helm/README.md

@@ -1,11 +0,0 @@
-# Deploy AgentQnA on Kubernetes cluster
-
-- You should have Helm (version >= 3.15) installed. Refer to the [Helm Installation Guide](https://helm.sh/docs/intro/install/) for more information.
-- For more deploy options, refer to [helm charts README](https://github.com/opea-project/GenAIInfra/tree/main/helm-charts#readme).
-
-## Deploy on Gaudi
-
-```
-export HFTOKEN="insert-your-huggingface-token-here"
-helm install agentqna oci://ghcr.io/opea-project/charts/agentqna  --set global.HUGGINGFACEHUB_API_TOKEN=${HFTOKEN} -f gaudi-values.yaml
-```

AgentQnA/kubernetes/helm/gaudi-values.yaml

@@ -1,16 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-# Accelerate inferencing in heaviest components to improve performance
-# by overriding their subchart values
-
-vllm:
-  enabled: true
-  image:
-    repository: opea/vllm-gaudi
-supervisor:
-  llm_endpoint_url: http://{{ .Release.Name }}-vllm
-ragagent:
-  llm_endpoint_url: http://{{ .Release.Name }}-vllm
-sqlagent:
-  llm_endpoint_url: http://{{ .Release.Name }}-vllm

AgentQnA/retrieval_tool/index_data.py

@@ -53,7 +53,7 @@ def main():
     host_ip = args.host_ip
     port = args.port
     proxies = {"http": ""}
-    url = "http://{host_ip}:{port}/v1/dataprep/ingest".format(host_ip=host_ip, port=port)
+    url = "http://{host_ip}:{port}/v1/dataprep".format(host_ip=host_ip, port=port)
 
     # Split jsonl file into json files
     files = split_jsonl_into_txts(os.path.join(args.filedir, args.filename))

AgentQnA/retrieval_tool/launch_retrieval_tool.sh

@@ -13,14 +13,13 @@ 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://${host_ip}:6009/v1/dataprep/delete"
+export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6007/v1/dataprep"
+export DATAPREP_GET_FILE_ENDPOINT="http://${host_ip}:6008/v1/dataprep/get_file"
+export DATAPREP_DELETE_FILE_ENDPOINT="http://${host_ip}:6009/v1/dataprep/delete_file"
 
 docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml up -d

AgentQnA/tests/_test_compose_openai_on_xeon.sh

@@ -15,7 +15,7 @@ function stop_agent_and_api_server() {
     echo "Stopping CRAG server"
     docker stop $(docker ps -q --filter ancestor=docker.io/aicrowd/kdd-cup-24-crag-mock-api:v0)
     echo "Stopping Agent services"
-    docker stop $(docker ps -q --filter ancestor=opea/agent:latest)
+    docker stop $(docker ps -q --filter ancestor=opea/agent-langchain:latest)
 }
 
 function stop_retrieval_tool() {

AgentQnA/tests/sql_agent_test/run_data_split.sh

@@ -1,6 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-DATAPATH=$WORKDIR/TAG-Bench/tag_queries.csv
-OUTFOLDER=$WORKDIR/TAG-Bench/query_by_db
-python3 split_data.py --path $DATAPATH --output $OUTFOLDER

AgentQnA/tests/sql_agent_test/split_data.py

@@ -1,27 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-import argparse
-import os
-
-import pandas as pd
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--path", type=str, required=True)
-    parser.add_argument("--output", type=str, required=True)
-    args = parser.parse_args()
-
-    # if output folder does not exist, create it
-    if not os.path.exists(args.output):
-        os.makedirs(args.output)
-
-    # Load the data
-    data = pd.read_csv(args.path)
-
-    # Split the data by domain
-    domains = data["DB used"].unique()
-    for domain in domains:
-        domain_data = data[data["DB used"] == domain]
-        out = os.path.join(args.output, f"query_{domain}.csv")
-        domain_data.to_csv(out, index=False)

AgentQnA/tests/step1_build_images.sh

@@ -11,16 +11,17 @@ export ip_address=$(hostname -I | awk '{print $1}')
 
 function get_genai_comps() {
     if [ ! -d "GenAIComps" ] ; then
-        git clone --depth 1 --branch ${opea_branch:-"main"} https://github.com/opea-project/GenAIComps.git
+        git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
     fi
 }
 
 
 function build_docker_images_for_retrieval_tool(){
     cd $WORKDIR/GenAIExamples/DocIndexRetriever/docker_image_build/
+    # git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../
     get_genai_comps
     echo "Build all the images with --no-cache..."
-    service_list="doc-index-retriever dataprep embedding retriever reranking"
+    service_list="doc-index-retriever dataprep-redis embedding-tei retriever-redis reranking-tei"
     docker compose -f build.yaml build ${service_list} --no-cache
     docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5
 
@@ -34,25 +35,6 @@ function build_agent_docker_image() {
     docker compose -f build.yaml build --no-cache
 }
 
-function build_vllm_docker_image() {
-    echo "Building the vllm docker image"
-    cd $WORKPATH
-    echo $WORKPATH
-    if [ ! -d "./vllm-fork" ]; then
-        git clone https://github.com/HabanaAI/vllm-fork.git
-    fi
-    cd ./vllm-fork
-    git checkout v0.6.4.post2+Gaudi-1.19.0
-    docker build --no-cache -f Dockerfile.hpu -t opea/vllm-gaudi:ci --shm-size=128g . --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy
-    if [ $? -ne 0 ]; then
-        echo "opea/vllm-gaudi:ci failed"
-        exit 1
-    else
-        echo "opea/vllm-gaudi:ci successful"
-    fi
-}
-
-
 function main() {
     echo "==================== Build docker images for retrieval tool ===================="
     build_docker_images_for_retrieval_tool
@@ -61,12 +43,6 @@ function main() {
     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

@@ -7,7 +7,6 @@ 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=$WORKDIR/hf_cache
 if [ ! -d "$HF_CACHE_DIR" ]; then

AgentQnA/tests/step4_launch_and_validate_agent_tgi.sh

@@ -8,22 +8,15 @@ WORKPATH=$(dirname "$PWD")
 export WORKDIR=$WORKPATH/../../
 echo "WORKDIR=${WORKDIR}"
 export ip_address=$(hostname -I | awk '{print $1}')
-export TOOLSET_PATH=$WORKPATH/tools/
+export TOOLSET_PATH=$WORKDIR/GenAIExamples/AgentQnA/tools/
 export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-HF_TOKEN=${HUGGINGFACEHUB_API_TOKEN}
-model="meta-llama/Meta-Llama-3.1-70B-Instruct"
 
-export HF_CACHE_DIR=/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
-echo  "HF_CACHE_DIR=$HF_CACHE_DIR"
 ls $HF_CACHE_DIR
 
-vllm_port=8086
-vllm_volume=${HF_CACHE_DIR}
-
 function start_tgi(){
     echo "Starting tgi-gaudi server"
     cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi
@@ -31,67 +24,14 @@ function start_tgi(){
 
 }
 
-function start_vllm_service_70B() {
-
-    echo "token is ${HF_TOKEN}"
-
-    echo "start vllm gaudi service"
-    echo "**************model is $model**************"
-    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 ${model} --max-seq-len-to-capture 16384 --tensor-parallel-size 4
-    sleep 5s
-    echo "Waiting vllm gaudi ready"
-    n=0
-    LOG_PATH=$PWD
-    until [[ "$n" -ge 100 ]] || [[ $ready == true ]]; do
-        docker logs vllm-gaudi-server
-        docker logs vllm-gaudi-server &> ${LOG_PATH}/vllm-gaudi-service.log
-        n=$((n+1))
-        if grep -q "Uvicorn running on" ${LOG_PATH}/vllm-gaudi-service.log; then
-            break
-        fi
-        if grep -q "No such container" ${LOG_PATH}/vllm-gaudi-service.log; then
-            echo "container vllm-gaudi-server not found"
-            exit 1
-        fi
-        sleep 5s
-    done
-    sleep 5s
-    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
-    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/hpu/gaudi
-    bash launch_agent_service_gaudi.sh
-    sleep 2m
+    bash launch_agent_service_tgi_gaudi.sh
+    sleep 10
 }
 
 function validate() {
@@ -109,76 +49,35 @@ function validate() {
 }
 
 function validate_agent_service() {
-    # # test worker rag agent
-    echo "======================Testing worker rag agent======================"
+    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"
+    # }')
     export agent_port="9095"
-    prompt="Tell me about Michael Jackson song Thriller"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt")
-    # echo $CONTENT
+    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py)
     local EXIT_CODE=$(validate "$CONTENT" "Thriller" "rag-agent-endpoint")
-    echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
+    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="9096"
-    prompt="How many employees are there in the company?"
-    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt")
-    local EXIT_CODE=$(validate "$CONTENT" "8" "sql-agent-endpoint")
-    echo $CONTENT
-    # echo $EXIT_CODE
-    local EXIT_CODE="${EXIT_CODE:0-1}"
-    if [ "$EXIT_CODE" == "1" ]; then
-        docker logs sql-agent-endpoint
-        exit 1
-    fi
-
-    # test supervisor react agent
-    echo "======================Testing supervisor react agent======================"
+    # local CONTENT=$(http_proxy="" curl http://${ip_address}:9090/v1/chat/completions -X POST -H "Content-Type: application/json" -d '{
+    #  "query": "Tell me about Michael Jackson song thriller"
+    # }')
     export agent_port="9090"
-    prompt="How many albums does Iron Maiden have?"
-    local CONTENT=$(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}"
+    local CONTENT=$(python3 $WORKDIR/GenAIExamples/AgentQnA/tests/test.py)
+    local EXIT_CODE=$(validate "$CONTENT" "Thriller" "react-agent-endpoint")
+    docker logs react-agent-endpoint
     if [ "$EXIT_CODE" == "1" ]; then
-        docker logs react-agent-endpoint
         exit 1
     fi
 
 }
 
-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
-    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 VLLM service ===================="
-    start_vllm_service_70B
-    echo "==================== VLLM service started ===================="
+    echo "==================== Start TGI ===================="
+    start_tgi
+    echo "==================== TGI started ===================="
 
     echo "==================== Start agent ===================="
     start_agent_and_api_server
@@ -189,8 +88,4 @@ function main() {
     echo "==================== Agent service validated ===================="
 }
 
-remove_data
-remove_chinook_data
 main
-remove_data
-remove_chinook_data

AgentQnA/tests/test.py

@@ -1,7 +1,6 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-import argparse
 import os
 
 import requests
@@ -10,47 +9,17 @@ import requests
 def generate_answer_agent_api(url, prompt):
     proxies = {"http": ""}
     payload = {
-        "messages": prompt,
+        "query": 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": ""}
-
-    payload = {
-        "messages": query,
-    }
-
-    try:
-        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)
-            ret = None
-
-        resp.raise_for_status()  # Raise an exception for unsuccessful HTTP status codes
-        return ret
-    except requests.exceptions.RequestException as e:
-        ret = f"An error occurred:{e}"
-        print(ret)
-        return False
-
-
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--prompt", type=str)
-    parser.add_argument("--stream", action="store_true")
-    args = parser.parse_args()
-
     ip_address = os.getenv("ip_address", "localhost")
-    agent_port = os.getenv("agent_port", "9090")
+    agent_port = os.getenv("agent_port", "9095")
     url = f"http://{ip_address}:{agent_port}/v1/chat/completions"
-    prompt = args.prompt
-
-    process_request(url, prompt, args.stream)
+    prompt = "Tell me about Michael Jackson song thriller"
+    answer = generate_answer_agent_api(url, prompt)
+    print(answer)

AgentQnA/tests/test_compose_on_gaudi.sh

@@ -2,7 +2,7 @@
 # Copyright (C) 2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-set -xe
+set -e
 
 WORKPATH=$(dirname "$PWD")
 export WORKDIR=$WORKPATH/../../
@@ -27,7 +27,7 @@ function stop_agent_docker() {
     done
 }
 
-function stop_llm(){
+function stop_tgi(){
     cd $WORKPATH/docker_compose/intel/hpu/gaudi/
     container_list=$(cat tgi_gaudi.yaml | grep container_name | cut -d':' -f2)
     for container_name in $container_list; do
@@ -36,14 +36,6 @@ function stop_llm(){
         if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
     done
 
-    cid=$(docker ps -aq --filter "name=vllm-gaudi-server")
-    echo "Stopping container $cid"
-    if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
-
-    cid=$(docker ps -aq --filter "name=test-comps-vllm-gaudi-service")
-    echo "Stopping container $cid"
-    if [[ ! -z "$cid" ]]; then docker rm $cid -f && sleep 1s; fi
-
 }
 
 function stop_retrieval_tool() {
@@ -60,7 +52,7 @@ function stop_retrieval_tool() {
 echo "workpath: $WORKPATH"
 echo "=================== Stop containers ===================="
 stop_crag
-stop_llm
+stop_tgi
 stop_agent_docker
 stop_retrieval_tool
 
@@ -86,9 +78,8 @@ 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
 
-echo "ALL DONE!!"
+echo "ALL DONE!"

AgentQnA/tests/test_compose_on_rocm.sh

@@ -2,7 +2,7 @@
 # Copyright (C) 2024 Advanced Micro Devices, Inc.
 # SPDX-License-Identifier: Apache-2.0
 
-set -xe
+set -e
 
 WORKPATH=$(dirname "$PWD")
 export WORKDIR=$WORKPATH/../../
@@ -72,4 +72,4 @@ echo "=================== #5 Agent and API server stopped===================="
 
 echo y | docker system prune
 
-echo "ALL DONE!!"
+echo "ALL DONE!"

AgentQnA/tools/supervisor_agent_tools.yaml

@@ -2,7 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 search_knowledge_base:
-  description: Search a knowledge base for a given query. Returns text related to the query.
+  description: Search knowledge base for a given query. Returns text related to the query.
   callable_api: tools.py:search_knowledge_base
   args_schema:
     query:
@@ -10,15 +10,6 @@ search_knowledge_base:
       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

AgentQnA/tools/tools.py

@@ -8,30 +8,13 @@ from tools.pycragapi import CRAG
 
 
 def search_knowledge_base(query: str) -> str:
-    """Search a knowledge base about music and singers for a given query.
-
-    Returns text related to the query.
-    """
+    """Search the knowledge base for a specific query."""
+    # use worker agent (DocGrader) to search the knowledge base
     url = os.environ.get("WORKER_AGENT_URL")
     print(url)
     proxies = {"http": ""}
     payload = {
-        "messages": query,
-    }
-    response = requests.post(url, json=payload, proxies=proxies)
-    return response.json()["text"]
-
-
-def search_sql_database(query: str) -> str:
-    """Search a SQL database on artists and their music with a natural language query.
-
-    Returns text related to the query.
-    """
-    url = os.environ.get("SQL_AGENT_URL")
-    print(url)
-    proxies = {"http": ""}
-    payload = {
-        "messages": query,
+        "query": query,
     }
     response = requests.post(url, json=payload, proxies=proxies)
     return response.json()["text"]

AgentQnA/tools/worker_agent_tools.py

@@ -12,7 +12,7 @@ def search_knowledge_base(query: str) -> str:
     print(url)
     proxies = {"http": ""}
     payload = {
-        "text": query,
+        "messages": query,
     }
     response = requests.post(url, json=payload, proxies=proxies)
     print(response)

AgentQnA/ui/docker/Dockerfile

@@ -1,26 +0,0 @@
-# Copyright (C) 2024 Intel Corporation
-# SPDX-License-Identifier: Apache-2.0
-
-# Use node 20.11.1 as the base image
-FROM node:20.11.1
-
-# Update package manager and install Git
-RUN apt-get update -y && apt-get install -y git
-
-# Copy the front-end code repository
-COPY svelte /home/user/svelte
-
-# Set the working directory
-WORKDIR /home/user/svelte
-
-# Install front-end dependencies
-RUN npm install
-
-# Build the front-end application
-RUN npm run build
-
-# Expose the port of the front-end application
-EXPOSE 5173
-
-# Run the front-end application in preview mode
-CMD ["npm", "run", "preview", "--", "--port", "5173", "--host", "0.0.0.0"]

AgentQnA/ui/svelte/.editorconfig

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

AgentQnA/ui/svelte/.env

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

AgentQnA/ui/svelte/.eslintignore

@@ -1,13 +0,0 @@
-.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

@@ -1,20 +0,0 @@
-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

@@ -1,13 +0,0 @@
-.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

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

AgentQnA/ui/svelte/README.md

@@ -1,60 +0,0 @@
-# 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

@@ -1,60 +0,0 @@
-{
-  "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

@@ -1,13 +0,0 @@
-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

@@ -1,50 +0,0 @@
-// 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

@@ -1,17 +0,0 @@
-<!--
-  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

@@ -1,82 +0,0 @@
-/* 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

@@ -1,25 +0,0 @@
-<!--
-  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

@@ -1,9 +0,0 @@
-<!--
-  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

@@ -1,16 +0,0 @@
-<!--
-  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
-							d="M10 0C4.612 0 0 5.336 0 7c0 1.742 3.546 7 10 7 6.454 0 10-5.258 10-7 0-1.664-4.612-7-10-7Zm0 10a3 3 0 1 1 0-6 3 3 0 0 1 0 6Z"
-						/>
-					</svg>

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

@@ -1,97 +0,0 @@
-<!--
-  Copyright (C) 2025 Intel Corporation
-  SPDX-License-Identifier: Apache-2.0
--->
-
-<!-- <svg class="h-11 w-11 flex-none overflow-visible" fill="none"
-	><defs
-		><filter
-			id="step-icon-2"
-			x="-3"
-			y="-1"
-			width="50"
-			height="50"
-			filterUnits="userSpaceOnUse"
-			color-interpolation-filters="sRGB"
-			><feFlood flood-opacity="0" result="BackgroundImageFix" /><feColorMatrix
-				in="SourceAlpha"
-				values="0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 127 0"
-				result="hardAlpha"
-			/><feOffset dy="2" /><feGaussianBlur stdDeviation="2.5" /><feComposite
-				in2="hardAlpha"
-				operator="out"
-			/><feColorMatrix
-				values="0 0 0 0 0.054902 0 0 0 0 0.647059 0 0 0 0 0.913725 0 0 0 0.12 0"
-			/><feBlend
-				in2="BackgroundImageFix"
-				result="effect1_dropShadow_804_95228"
-			/><feBlend
-				in="SourceGraphic"
-				in2="effect1_dropShadow_804_95228"
-				result="shape"
-			/></filter
-		></defs
-	><g filter="url(#step-icon-2)"
-		><path
-			d="M2.75 10A7.25 7.25 0 0 1 10 2.75h24A7.25 7.25 0 0 1 41.25 10v24A7.25 7.25 0 0 1 34 41.25H10A7.25 7.25 0 0 1 2.75 34V10Z"
-			fill="#EEF2FF"
-		/><path
-			d="M2.75 10A7.25 7.25 0 0 1 10 2.75h24A7.25 7.25 0 0 1 41.25 10v24A7.25 7.25 0 0 1 34 41.25H10A7.25 7.25 0 0 1 2.75 34V10Z"
-			stroke="#6366F1"
-			stroke-width="1.5"
-			stroke-linecap="round"
-			stroke-linejoin="round"
-		/></g
-	><path
-		fill-rule="evenodd"
-		clip-rule="evenodd"
-		d="M23 35.25c.69 0 1.25-.56 1.25-1.25A3.75 3.75 0 0 1 28 30.25a1.25 1.25 0 1 0 0-2.5A3.75 3.75 0 0 1 24.25 24a1.25 1.25 0 1 0-2.5 0A3.75 3.75 0 0 1 18 27.75a1.25 1.25 0 0 0 0 2.5A3.75 3.75 0 0 1 21.75 34c0 .69.56 1.25 1.25 1.25Z"
-		fill="#fff"
-	/><path
-		d="M28 27a.75.75 0 0 0 0 1.5V27Zm-4.5 7a.5.5 0 0 1-.5.5V36a2 2 0 0 0 2-2h-1.5Zm5-5a.5.5 0 0 1-.5.5V31a2 2 0 0 0 2-2h-1.5Zm-.5-.5a.5.5 0 0 1 .5.5H30a2 2 0 0 0-2-2v1.5Zm-5-5a.5.5 0 0 1 .5.5H25a2 2 0 0 0-2-2v1.5Zm-.5.5a.5.5 0 0 1 .5-.5V22a2 2 0 0 0-2 2h1.5Zm-5 5a.5.5 0 0 1 .5-.5V27a2 2 0 0 0-2 2h1.5Zm.5.5a.5.5 0 0 1-.5-.5H16a2 2 0 0 0 2 2v-1.5Zm5 5a.5.5 0 0 1-.5-.5H21a2 2 0 0 0 2 2v-1.5ZM18 31a3 3 0 0 1 3 3h1.5a4.5 4.5 0 0 0-4.5-4.5V31Zm3-7a3 3 0 0 1-3 3v1.5a4.5 4.5 0 0 0 4.5-4.5H21Zm7 3a3 3 0 0 1-3-3h-1.5a4.5 4.5 0 0 0 4.5 4.5V27Zm-3 7a3 3 0 0 1 3-3v-1.5a4.5 4.5 0 0 0-4.5 4.5H25Z"
-		fill="#6366F1"
-	/><path
-		fill-rule="evenodd"
-		clip-rule="evenodd"
-		d="M13 27.25c.69 0 1.25-.56 1.25-1.25 0-.966.784-1.75 1.75-1.75a1.25 1.25 0 1 0 0-2.5A1.75 1.75 0 0 1 14.25 20a1.25 1.25 0 1 0-2.5 0A1.75 1.75 0 0 1 10 21.75a1.25 1.25 0 0 0 0 2.5c.966 0 1.75.784 1.75 1.75 0 .69.56 1.25 1.25 1.25Z"
-		fill="#fff"
-	/><path
-		d="M16 21a.75.75 0 0 0 0 1.5V21Zm-2.5 5a.5.5 0 0 1-.5.5V28a2 2 0 0 0 2-2h-1.5Zm3-3a.5.5 0 0 1-.5.5V25a2 2 0 0 0 2-2h-1.5Zm-.5-.5a.5.5 0 0 1 .5.5H18a2 2 0 0 0-2-2v1.5Zm-3-3a.5.5 0 0 1 .5.5H15a2 2 0 0 0-2-2v1.5Zm-.5.5a.5.5 0 0 1 .5-.5V18a2 2 0 0 0-2 2h1.5Zm-3 3a.5.5 0 0 1 .5-.5V21a2 2 0 0 0-2 2h1.5Zm.5.5a.5.5 0 0 1-.5-.5H8a2 2 0 0 0 2 2v-1.5Zm3 3a.5.5 0 0 1-.5-.5H11a2 2 0 0 0 2 2v-1.5ZM10 25a1 1 0 0 1 1 1h1.5a2.5 2.5 0 0 0-2.5-2.5V25Zm1-5a1 1 0 0 1-1 1v1.5a2.5 2.5 0 0 0 2.5-2.5H11Zm5 1a1 1 0 0 1-1-1h-1.5a2.5 2.5 0 0 0 2.5 2.5V21Zm-1 5a1 1 0 0 1 1-1v-1.5a2.5 2.5 0 0 0-2.5 2.5H15Z"
-		fill="#6366F1"
-	/><path
-		opacity=".4"
-		d="M29.75 35.25h2.5a3 3 0 0 0 3-3v-20.5a3 3 0 0 0-3-3h-20.5a3 3 0 0 0-3 3v5.5M12.75 14.25h18.5"
-		stroke="#6366F1"
-		stroke-width="1.5"
-		stroke-linecap="round"
-		stroke-linejoin="round"
-	/></svg
-> -->
-
-<svg
-	t="1731984480564"
-	class="h-10 w-10"
-	viewBox="0 0 1114 1024"
-	version="1.1"
-	xmlns="http://www.w3.org/2000/svg"
-	p-id="29550"
-	width="200"
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AgentQnA/ui/svelte/src/lib/assets/Agent/resource.svelte

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

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

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

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

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

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AgentQnA/ui/svelte/src/lib/assets/icons/arrow-path-icon.svelte

@@ -1,25 +0,0 @@
-<!--
-  Copyright (C) 2025 Intel Corporation
-  SPDX-License-Identifier: Apache-2.0
--->
-
-<script lang="ts">
-  export let overrideClasses = '';
-
-  const classes = overrideClasses ? overrideClasses : 'w-4 h-4 text-gray-500';
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-
-<svg
-  class={classes}
-  xmlns="http://www.w3.org/2000/svg"
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-  viewBox="0 0 24 24"
-  stroke-width="1.5"
-  stroke="currentColor"
->
-  <path
-    stroke-linecap="round"
-    stroke-linejoin="round"
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-  />
-</svg>

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

@@ -1,33 +0,0 @@
-<!--
-  Copyright (C) 2025 Intel Corporation
-  SPDX-License-Identifier: Apache-2.0
--->
-
-<svg
-	width="45"
-	height="45"
-	viewBox="0 0 48 48"
-	fill="none"
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AgentQnA/ui/svelte/src/lib/assets/icons/chat-bubble-left-icon.svelte

@@ -1,25 +0,0 @@
-<!--
-  Copyright (C) 2025 Intel Corporation
-  SPDX-License-Identifier: Apache-2.0
--->
-
-<script lang="ts">
-  export let overrideClasses = '';
-
-  const classes = overrideClasses ? overrideClasses : `w-6 h-6`;
-</script>
-
-<svg
-  class={classes}
-  xmlns="http://www.w3.org/2000/svg"
-  fill="none"
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-  stroke-width="1.5"
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->
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-    stroke-linecap="round"
-    stroke-linejoin="round"
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-  />
-</svg>

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

@@ -1,6 +0,0 @@
-<!--
-  Copyright (C) 2025 Intel Corporation
-  SPDX-License-Identifier: Apache-2.0
--->
-
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AgentQnA/ui/svelte/src/lib/assets/icons/check-icon.svelte

@@ -1,25 +0,0 @@
-<!--
-  Copyright (C) 2025 Intel Corporation
-  SPDX-License-Identifier: Apache-2.0
--->
-
-<script lang="ts">
-  export let overrideClasses = '';
-
-  const classes = overrideClasses ? overrideClasses : `w-6 h-6`;
-</script>
-
-<svg
-  class={classes}
-  xmlns="http://www.w3.org/2000/svg"
-  fill="none"
-  viewBox="0 0 24 24"
-  stroke-width="1.5"
-  stroke="currentColor"
->
-  <path
-    stroke-linecap="round"
-    stroke-linejoin="round"
-    d="M4.5 12.75l6 6 9-13.5"
-  />
-</svg>

AgentQnA/ui/svelte/src/lib/assets/icons/csv.svg

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