sharepoint memory issue debugging

Co-authored-by: eric-zadara <eric-zadara@users.noreply.github.com>

.github/CODEOWNERS

@@ -1 +1,3 @@
 * @onyx-dot-app/onyx-core-team
+# Helm charts Owners
+/helm/ @justin-tahara

.github/actions/custom-build-and-push/action.yml

@@ -35,6 +35,16 @@ inputs:
   cache-to:
     description: 'Cache destinations'
     required: false
+  outputs:
+    description: 'Output destinations'
+    required: false
+  provenance:
+    description: 'Generate provenance attestation'
+    required: false
+    default: 'false'
+  build-args:
+    description: 'Build arguments'
+    required: false
   retry-wait-time:
     description: 'Time to wait before attempt 2 in seconds'
     required: false
@@ -62,6 +72,9 @@ runs:
         no-cache: ${{ inputs.no-cache }}
         cache-from: ${{ inputs.cache-from }}
         cache-to: ${{ inputs.cache-to }}
+        outputs: ${{ inputs.outputs }}
+        provenance: ${{ inputs.provenance }}
+        build-args: ${{ inputs.build-args }}
 
     - name: Wait before attempt 2
       if: steps.buildx1.outcome != 'success'
@@ -85,6 +98,9 @@ runs:
         no-cache: ${{ inputs.no-cache }}
         cache-from: ${{ inputs.cache-from }}
         cache-to: ${{ inputs.cache-to }}
+        outputs: ${{ inputs.outputs }}
+        provenance: ${{ inputs.provenance }}
+        build-args: ${{ inputs.build-args }}
 
     - name: Wait before attempt 3
       if: steps.buildx1.outcome != 'success' && steps.buildx2.outcome != 'success'
@@ -108,6 +124,9 @@ runs:
         no-cache: ${{ inputs.no-cache }}
         cache-from: ${{ inputs.cache-from }}
         cache-to: ${{ inputs.cache-to }}
+        outputs: ${{ inputs.outputs }}
+        provenance: ${{ inputs.provenance }}
+        build-args: ${{ inputs.build-args }}
 
     - name: Report failure
       if: steps.buildx1.outcome != 'success' && steps.buildx2.outcome != 'success' && steps.buildx3.outcome != 'success'

.github/workflows/docker-build-push-backend-container-on-tag.yml

@@ -142,15 +142,25 @@ jobs:
       # can re-enable when they figure it out
       # https://github.com/aquasecurity/trivy/discussions/7538
       # https://github.com/aquasecurity/trivy-action/issues/389
+      # Security: Using pinned digest (0.65.0@sha256:a22415a38938a56c379387a8163fcb0ce38b10ace73e593475d3658d578b2436)
+      # Security: No Docker socket mount needed for remote registry scanning
       - name: Run Trivy vulnerability scanner
-        uses: aquasecurity/trivy-action@master
-        env:
-          TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
-          TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
-          TRIVY_USERNAME: ${{ secrets.DOCKER_USERNAME }}
-          TRIVY_PASSWORD: ${{ secrets.DOCKER_TOKEN }}
+        uses: nick-fields/retry@v3
         with:
-          # To run locally: trivy image --severity HIGH,CRITICAL onyxdotapp/onyx-backend
-          image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-          severity: "CRITICAL,HIGH"
-          trivyignores: ./backend/.trivyignore
+          timeout_minutes: 30
+          max_attempts: 3
+          retry_wait_seconds: 10
+          command: |
+            docker run --rm -v $HOME/.cache/trivy:/root/.cache/trivy \
+              -v ${{ github.workspace }}/backend/.trivyignore:/tmp/.trivyignore:ro \
+              -e TRIVY_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-db:2" \
+              -e TRIVY_JAVA_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-java-db:1" \
+              -e TRIVY_USERNAME="${{ secrets.DOCKER_USERNAME }}" \
+              -e TRIVY_PASSWORD="${{ secrets.DOCKER_TOKEN }}" \
+              aquasec/trivy@sha256:a22415a38938a56c379387a8163fcb0ce38b10ace73e593475d3658d578b2436 \
+              image \
+              --skip-version-check \
+              --timeout 20m \
+              --severity CRITICAL,HIGH \
+              --ignorefile /tmp/.trivyignore \
+              docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}

.github/workflows/docker-build-push-cloud-web-container-on-tag.yml

@@ -139,12 +139,20 @@ jobs:
       # https://github.com/aquasecurity/trivy/discussions/7538
       # https://github.com/aquasecurity/trivy-action/issues/389
       - name: Run Trivy vulnerability scanner
-        uses: aquasecurity/trivy-action@master
-        env:
-          TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
-          TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
-          TRIVY_USERNAME: ${{ secrets.DOCKER_USERNAME }}
-          TRIVY_PASSWORD: ${{ secrets.DOCKER_TOKEN }}
+        uses: nick-fields/retry@v3
         with:
-          image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-          severity: "CRITICAL,HIGH"
+          timeout_minutes: 30
+          max_attempts: 3
+          retry_wait_seconds: 10
+          command: |
+            docker run --rm -v $HOME/.cache/trivy:/root/.cache/trivy \
+              -e TRIVY_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-db:2" \
+              -e TRIVY_JAVA_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-java-db:1" \
+              -e TRIVY_USERNAME="${{ secrets.DOCKER_USERNAME }}" \
+              -e TRIVY_PASSWORD="${{ secrets.DOCKER_TOKEN }}" \
+              aquasec/trivy@sha256:a22415a38938a56c379387a8163fcb0ce38b10ace73e593475d3658d578b2436 \
+              image \
+              --skip-version-check \
+              --timeout 20m \
+              --severity CRITICAL,HIGH \
+              docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}

.github/workflows/docker-build-push-model-server-container-on-tag.yml

@@ -99,7 +99,7 @@ jobs:
     needs: [check_model_server_changes]
     if: needs.check_model_server_changes.outputs.changed == 'true'
     runs-on:
-      [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-arm64"]
+      [runs-on, runner=8cpu-linux-arm64, "run-id=${{ github.run_id }}-arm64"]
     env:
       PLATFORM_PAIR: linux-arm64
     steps:
@@ -164,13 +164,20 @@ jobs:
           fi
 
       - name: Run Trivy vulnerability scanner
-        uses: aquasecurity/trivy-action@master
-        env:
-          TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
-          TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
-          TRIVY_USERNAME: ${{ secrets.DOCKER_USERNAME }}
-          TRIVY_PASSWORD: ${{ secrets.DOCKER_TOKEN }}
+        uses: nick-fields/retry@v3
         with:
-          image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-          severity: "CRITICAL,HIGH"
-          timeout: "10m"
+          timeout_minutes: 30
+          max_attempts: 3
+          retry_wait_seconds: 10
+          command: |
+            docker run --rm -v $HOME/.cache/trivy:/root/.cache/trivy \
+              -e TRIVY_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-db:2" \
+              -e TRIVY_JAVA_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-java-db:1" \
+              -e TRIVY_USERNAME="${{ secrets.DOCKER_USERNAME }}" \
+              -e TRIVY_PASSWORD="${{ secrets.DOCKER_TOKEN }}" \
+              aquasec/trivy@sha256:a22415a38938a56c379387a8163fcb0ce38b10ace73e593475d3658d578b2436 \
+              image \
+              --skip-version-check \
+              --timeout 20m \
+              --severity CRITICAL,HIGH \
+              docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}

.github/workflows/docker-build-push-web-container-on-tag.yml

@@ -150,12 +150,20 @@ jobs:
       # https://github.com/aquasecurity/trivy/discussions/7538
       # https://github.com/aquasecurity/trivy-action/issues/389
       - name: Run Trivy vulnerability scanner
-        uses: aquasecurity/trivy-action@master
-        env:
-          TRIVY_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-db:2"
-          TRIVY_JAVA_DB_REPOSITORY: "public.ecr.aws/aquasecurity/trivy-java-db:1"
-          TRIVY_USERNAME: ${{ secrets.DOCKER_USERNAME }}
-          TRIVY_PASSWORD: ${{ secrets.DOCKER_TOKEN }}
+        uses: nick-fields/retry@v3
         with:
-          image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-          severity: "CRITICAL,HIGH"
+          timeout_minutes: 30
+          max_attempts: 3
+          retry_wait_seconds: 10
+          command: |
+            docker run --rm -v $HOME/.cache/trivy:/root/.cache/trivy \
+              -e TRIVY_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-db:2" \
+              -e TRIVY_JAVA_DB_REPOSITORY="public.ecr.aws/aquasecurity/trivy-java-db:1" \
+              -e TRIVY_USERNAME="${{ secrets.DOCKER_USERNAME }}" \
+              -e TRIVY_PASSWORD="${{ secrets.DOCKER_TOKEN }}" \
+              aquasec/trivy@sha256:a22415a38938a56c379387a8163fcb0ce38b10ace73e593475d3658d578b2436 \
+              image \
+              --skip-version-check \
+              --timeout 20m \
+              --severity CRITICAL,HIGH \
+              docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}

.github/workflows/helm-chart-releases.yml

@@ -0,0 +1,50 @@
+name: Release Onyx Helm Charts
+
+on:
+  push:
+    branches:
+      - main
+
+permissions: write-all
+
+jobs:
+  release:
+    permissions:
+      contents: write
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Install Helm CLI
+        uses: azure/setup-helm@v4
+        with:
+          version: v3.12.1
+
+      - name: Add required Helm repositories
+        run: |
+          helm repo add bitnami https://charts.bitnami.com/bitnami
+          helm repo add onyx-vespa https://onyx-dot-app.github.io/vespa-helm-charts
+          helm repo add keda https://kedacore.github.io/charts
+          helm repo update
+
+      - name: Build chart dependencies
+        run: |
+          set -euo pipefail
+          for chart_dir in deployment/helm/charts/*; do
+            if [ -f "$chart_dir/Chart.yaml" ]; then
+              echo "Building dependencies for $chart_dir"
+              helm dependency build "$chart_dir"
+            fi
+          done
+
+      - name: Publish Helm charts to gh-pages
+        uses: stefanprodan/helm-gh-pages@v1.7.0
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          charts_dir: deployment/helm/charts
+          branch: gh-pages
+          commit_username: ${{ github.actor }}
+          commit_email: ${{ github.actor }}@users.noreply.github.com

.github/workflows/pr-external-dependency-unit-tests.yml

@@ -21,6 +21,9 @@ env:
   CONFLUENCE_USER_NAME: ${{ secrets.CONFLUENCE_USER_NAME }}
   CONFLUENCE_ACCESS_TOKEN: ${{ secrets.CONFLUENCE_ACCESS_TOKEN }}
 
+  # LLMs
+  OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+
 jobs:
   discover-test-dirs:
     runs-on: ubuntu-latest
@@ -85,8 +88,6 @@ jobs:
         shell: script -q -e -c "bash --noprofile --norc -eo pipefail {0}"
         run: |
           py.test \
-            -n 8 \
-            --dist loadfile \
             --durations=8 \
             -o junit_family=xunit2 \
             -xv \

.github/workflows/pr-helm-chart-testing.yml

@@ -53,9 +53,154 @@ jobs:
       if: steps.list-changed.outputs.changed == 'true'
       uses: helm/kind-action@v1.12.0
 
-    - name: Run chart-testing (install)
+    - name: Pre-install cluster status check
       if: steps.list-changed.outputs.changed == 'true'
-      run: ct install --all --helm-extra-set-args="--set=nginx.enabled=false" --debug --config ct.yaml
+      run: |
+        echo "=== Pre-install Cluster Status ==="
+        kubectl get nodes -o wide
+        kubectl get pods --all-namespaces
+        kubectl get storageclass
+
+    - name: Add Helm repositories and update
+      if: steps.list-changed.outputs.changed == 'true'
+      run: |
+        echo "=== Adding Helm repositories ==="
+        helm repo add bitnami https://charts.bitnami.com/bitnami
+        helm repo add vespa https://onyx-dot-app.github.io/vespa-helm-charts
+        helm repo update
+
+    - name: Pre-pull critical images
+      if: steps.list-changed.outputs.changed == 'true'
+      run: |
+        echo "=== Pre-pulling critical images to avoid timeout ==="
+        # Get kind cluster name
+        KIND_CLUSTER=$(kubectl config current-context | sed 's/kind-//')
+        echo "Kind cluster: $KIND_CLUSTER"
+        
+        # Pre-pull images that are likely to be used
+        echo "Pre-pulling PostgreSQL image..."
+        docker pull postgres:15-alpine || echo "Failed to pull postgres:15-alpine"
+        kind load docker-image postgres:15-alpine --name $KIND_CLUSTER || echo "Failed to load postgres image"
+        
+        echo "Pre-pulling Redis image..."
+        docker pull redis:7-alpine || echo "Failed to pull redis:7-alpine"
+        kind load docker-image redis:7-alpine --name $KIND_CLUSTER || echo "Failed to load redis image"
+        
+        echo "Pre-pulling Onyx images..."
+        docker pull docker.io/onyxdotapp/onyx-web-server:latest || echo "Failed to pull onyx web server"
+        docker pull docker.io/onyxdotapp/onyx-backend:latest || echo "Failed to pull onyx backend"
+        kind load docker-image docker.io/onyxdotapp/onyx-web-server:latest --name $KIND_CLUSTER || echo "Failed to load onyx web server"
+        kind load docker-image docker.io/onyxdotapp/onyx-backend:latest --name $KIND_CLUSTER || echo "Failed to load onyx backend"
+        
+        echo "=== Images loaded into Kind cluster ==="
+        docker exec $KIND_CLUSTER-control-plane crictl images | grep -E "(postgres|redis|onyx)" || echo "Some images may still be loading..."
+
+    - name: Validate chart dependencies
+      if: steps.list-changed.outputs.changed == 'true'
+      run: |
+        echo "=== Validating chart dependencies ==="
+        cd deployment/helm/charts/onyx
+        helm dependency update
+        helm lint .
+
+    - name: Run chart-testing (install) with enhanced monitoring
+      timeout-minutes: 25
+      if: steps.list-changed.outputs.changed == 'true'
+      run: |
+        echo "=== Starting chart installation with monitoring ==="
+        
+        # Function to monitor cluster state
+        monitor_cluster() {
+          while true; do
+            echo "=== Cluster Status Check at $(date) ==="
+            # Only show non-running pods to reduce noise
+            NON_RUNNING_PODS=$(kubectl get pods --all-namespaces --field-selector=status.phase!=Running,status.phase!=Succeeded --no-headers 2>/dev/null | wc -l)
+            if [ "$NON_RUNNING_PODS" -gt 0 ]; then
+              echo "Non-running pods:"
+              kubectl get pods --all-namespaces --field-selector=status.phase!=Running,status.phase!=Succeeded
+            else
+              echo "All pods running successfully"
+            fi
+            # Only show recent events if there are issues
+            RECENT_EVENTS=$(kubectl get events --sort-by=.lastTimestamp --all-namespaces --field-selector=type!=Normal 2>/dev/null | tail -5)
+            if [ -n "$RECENT_EVENTS" ]; then
+              echo "Recent warnings/errors:"
+              echo "$RECENT_EVENTS"
+            fi
+            sleep 60
+          done
+        }
+        
+        # Start monitoring in background
+        monitor_cluster &
+        MONITOR_PID=$!
+        
+        # Set up cleanup
+        cleanup() {
+          echo "=== Cleaning up monitoring process ==="
+          kill $MONITOR_PID 2>/dev/null || true
+          echo "=== Final cluster state ==="
+          kubectl get pods --all-namespaces
+          kubectl get events --all-namespaces --sort-by=.lastTimestamp | tail -20
+        }
+        
+        # Trap cleanup on exit
+        trap cleanup EXIT
+        
+        # Run the actual installation with detailed logging
+        echo "=== Starting ct install ==="
+        ct install --all \
+          --helm-extra-set-args="\
+            --set=nginx.enabled=false \
+            --set=minio.enabled=false \
+            --set=vespa.enabled=false \
+            --set=slackbot.enabled=false \
+            --set=postgresql.enabled=true \
+            --set=postgresql.primary.persistence.enabled=false \
+            --set=redis.enabled=true \
+            --set=webserver.replicaCount=1 \
+            --set=api.replicaCount=0 \
+            --set=inferenceCapability.replicaCount=0 \
+            --set=indexCapability.replicaCount=0 \
+            --set=celery_beat.replicaCount=0 \
+            --set=celery_worker_heavy.replicaCount=0 \
+            --set=celery_worker_docfetching.replicaCount=0 \
+            --set=celery_worker_docprocessing.replicaCount=0 \
+            --set=celery_worker_light.replicaCount=0 \
+            --set=celery_worker_monitoring.replicaCount=0 \
+            --set=celery_worker_primary.replicaCount=0 \
+            --set=celery_worker_user_files_indexing.replicaCount=0" \
+          --helm-extra-args="--timeout 900s --debug" \
+          --debug --config ct.yaml
+        
+        echo "=== Installation completed successfully ==="
+        kubectl get pods --all-namespaces
+
+    - name: Post-install verification
+      if: steps.list-changed.outputs.changed == 'true'
+      run: |
+        echo "=== Post-install verification ==="
+        kubectl get pods --all-namespaces
+        kubectl get services --all-namespaces
+        # Only show issues if they exist
+        kubectl describe pods --all-namespaces | grep -A 5 -B 2 "Failed\|Error\|Warning" || echo "No pod issues found"
+
+    - name: Cleanup on failure
+      if: failure() && steps.list-changed.outputs.changed == 'true'
+      run: |
+        echo "=== Cleanup on failure ==="
+        echo "=== Final cluster state ==="
+        kubectl get pods --all-namespaces
+        kubectl get events --all-namespaces --sort-by=.lastTimestamp | tail -10
+        
+        echo "=== Pod descriptions for debugging ==="
+        kubectl describe pods --all-namespaces | grep -A 10 -B 3 "Failed\|Error\|Warning\|Pending" || echo "No problematic pods found"
+        
+        echo "=== Recent logs for debugging ==="
+        kubectl logs --all-namespaces --tail=50 | grep -i "error\|timeout\|failed\|pull" || echo "No error logs found"
+        
+        echo "=== Helm releases ==="
+        helm list --all-namespaces
       # the following would install only changed charts, but we only have one chart so 
       # don't worry about that for now
       # run: ct install --target-branch ${{ github.event.repository.default_branch }}

.github/workflows/pr-integration-tests.yml

@@ -11,6 +11,12 @@ on:
       - "release/**"
 
 env:
+  # Private Registry Configuration
+  PRIVATE_REGISTRY: experimental-registry.blacksmith.sh:5000
+  PRIVATE_REGISTRY_USERNAME: ${{ secrets.PRIVATE_REGISTRY_USERNAME }}
+  PRIVATE_REGISTRY_PASSWORD: ${{ secrets.PRIVATE_REGISTRY_PASSWORD }}
+
+  # Test Environment Variables
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
   SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
   CONFLUENCE_TEST_SPACE_URL: ${{ secrets.CONFLUENCE_TEST_SPACE_URL }}
@@ -19,18 +25,42 @@ env:
   JIRA_BASE_URL: ${{ secrets.JIRA_BASE_URL }}
   JIRA_USER_EMAIL: ${{ secrets.JIRA_USER_EMAIL }}
   JIRA_API_TOKEN: ${{ secrets.JIRA_API_TOKEN }}
-  PLATFORM_PAIR: linux-amd64
+  PERM_SYNC_SHAREPOINT_CLIENT_ID: ${{ secrets.PERM_SYNC_SHAREPOINT_CLIENT_ID }}
+  PERM_SYNC_SHAREPOINT_PRIVATE_KEY: ${{ secrets.PERM_SYNC_SHAREPOINT_PRIVATE_KEY }}
+  PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD: ${{ secrets.PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD }}
+  PERM_SYNC_SHAREPOINT_DIRECTORY_ID: ${{ secrets.PERM_SYNC_SHAREPOINT_DIRECTORY_ID }}
 
 jobs:
-  integration-tests:
-    # See https://runs-on.com/runners/linux/
-    runs-on:
-      [
-        runs-on,
-        runner=32cpu-linux-x64,
-        disk=large,
-        "run-id=${{ github.run_id }}",
-      ]
+  discover-test-dirs:
+    runs-on: blacksmith-2vcpu-ubuntu-2404-arm
+    outputs:
+      test-dirs: ${{ steps.set-matrix.outputs.test-dirs }}
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Discover test directories
+        id: set-matrix
+        run: |
+          # Find all leaf-level directories in both test directories
+          tests_dirs=$(find backend/tests/integration/tests -mindepth 1 -maxdepth 1 -type d ! -name "__pycache__" -exec basename {} \; | sort)
+          connector_dirs=$(find backend/tests/integration/connector_job_tests -mindepth 1 -maxdepth 1 -type d ! -name "__pycache__" -exec basename {} \; | sort)
+
+          # Create JSON array with directory info
+          all_dirs=""
+          for dir in $tests_dirs; do
+            all_dirs="$all_dirs{\"path\":\"tests/$dir\",\"name\":\"tests-$dir\"},"
+          done
+          for dir in $connector_dirs; do
+            all_dirs="$all_dirs{\"path\":\"connector_job_tests/$dir\",\"name\":\"connector-$dir\"},"
+          done
+
+          # Remove trailing comma and wrap in array
+          all_dirs="[${all_dirs%,}]"
+          echo "test-dirs=$all_dirs" >> $GITHUB_OUTPUT
+
+  prepare-build:
+    runs-on: blacksmith-2vcpu-ubuntu-2404-arm
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
@@ -43,12 +73,12 @@ jobs:
           cache-dependency-path: |
             backend/requirements/default.txt
             backend/requirements/dev.txt
-            backend/requirements/ee.txt
-      - run: |
+
+      - name: Install Python dependencies
+        run: |
           python -m pip install --upgrade pip
           pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
           pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
-          pip install --retries 5 --timeout 30 -r backend/requirements/ee.txt
 
       - name: Generate OpenAPI schema
         working-directory: ./backend
@@ -66,132 +96,155 @@ jobs:
             -i /local/openapi.json \
             -g python \
             -o /local/onyx_openapi_client \
-            --package-name onyx_openapi_client
+            --package-name onyx_openapi_client \
+            --skip-validate-spec \
+            --openapi-normalizer "SIMPLIFY_ONEOF_ANYOF=true,SET_OAS3_NULLABLE=true"
+
+      - name: Upload OpenAPI artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: openapi-artifacts
+          path: backend/generated/
+
+  build-backend-image:
+    runs-on: blacksmith-16vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
 
       - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+        uses: useblacksmith/setup-docker-builder@v1
 
+      - name: Build and push Backend Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile
+          platforms: linux/arm64
+          tags: ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }}
+          push: true
+
+  build-model-server-image:
+    runs-on: blacksmith-16vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push Model Server Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile.model_server
+          platforms: linux/arm64
+          tags: ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }}
+          push: true
+          outputs: type=registry
+          provenance: false
+
+  build-integration-image:
+    needs: prepare-build
+    runs-on: blacksmith-16vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      - name: Download OpenAPI artifacts
+        uses: actions/download-artifact@v4
+        with:
+          name: openapi-artifacts
+          path: backend/generated/
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push integration test Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/tests/integration/Dockerfile
+          platforms: linux/arm64
+          tags: ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }}
+          push: true
+
+  integration-tests:
+    needs:
+      [
+        discover-test-dirs,
+        build-backend-image,
+        build-model-server-image,
+        build-integration-image,
+      ]
+    runs-on: blacksmith-8vcpu-ubuntu-2404-arm
+
+    strategy:
+      fail-fast: false
+      matrix:
+        test-dir: ${{ fromJson(needs.discover-test-dirs.outputs.test-dirs) }}
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      # needed for pulling Vespa, Redis, Postgres, and Minio images
+      # otherwise, we hit the "Unauthenticated users" limit
+      # https://docs.docker.com/docker-hub/usage/
       - name: Login to Docker Hub
         uses: docker/login-action@v3
         with:
           username: ${{ secrets.DOCKER_USERNAME }}
           password: ${{ secrets.DOCKER_TOKEN }}
 
-      # tag every docker image with "test" so that we can spin up the correct set
-      # of images during testing
-
-      # We don't need to build the Web Docker image since it's not yet used
-      # in the integration tests. We have a separate action to verify that it builds
-      # successfully.
-      - name: Pull Web Docker image
+      - name: Pull Docker images
         run: |
-          docker pull onyxdotapp/onyx-web-server:latest
-          docker tag onyxdotapp/onyx-web-server:latest onyxdotapp/onyx-web-server:test
+          # Pull all images from registry in parallel
+          echo "Pulling Docker images in parallel..."
+          # Pull images from private registry
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }}) &
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }}) &
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }}) &
 
-      # we use the runs-on cache for docker builds
-      # in conjunction with runs-on runners, it has better speed and unlimited caching
-      # https://runs-on.com/caching/s3-cache-for-github-actions/
-      # https://runs-on.com/caching/docker/
-      # https://github.com/moby/buildkit#s3-cache-experimental
+          # Wait for all background jobs to complete
+          wait
+          echo "All Docker images pulled successfully"
 
-      # images are built and run locally for testing purposes. Not pushed.
-      - name: Build Backend Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-backend:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build Model Server Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile.model_server
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-model-server:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build integration test Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/tests/integration/Dockerfile
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-integration:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/integration-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/integration-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      # Start containers for multi-tenant tests
-      - name: Start Docker containers for multi-tenant tests
-        run: |
-          cd deployment/docker_compose
-          ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
-          MULTI_TENANT=true \
-          AUTH_TYPE=cloud \
-          REQUIRE_EMAIL_VERIFICATION=false \
-          DISABLE_TELEMETRY=true \
-          IMAGE_TAG=test \
-          DEV_MODE=true \
-          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack up -d
-        id: start_docker_multi_tenant
-
-      # In practice, `cloud` Auth type would require OAUTH credentials to be set.
-      - name: Run Multi-Tenant Integration Tests
-        run: |
-          echo "Waiting for 3 minutes to ensure API server is ready..."
-          sleep 180
-          echo "Running integration tests..."
-          docker run --rm --network onyx-stack_default \
-            --name test-runner \
-            -e POSTGRES_HOST=relational_db \
-            -e POSTGRES_USER=postgres \
-            -e POSTGRES_PASSWORD=password \
-            -e DB_READONLY_USER=db_readonly_user \
-            -e DB_READONLY_PASSWORD=password \
-            -e POSTGRES_DB=postgres \
-            -e POSTGRES_USE_NULL_POOL=true \
-            -e VESPA_HOST=index \
-            -e REDIS_HOST=cache \
-            -e API_SERVER_HOST=api_server \
-            -e OPENAI_API_KEY=${OPENAI_API_KEY} \
-            -e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
-            -e TEST_WEB_HOSTNAME=test-runner \
-            -e AUTH_TYPE=cloud \
-            -e MULTI_TENANT=true \
-            -e REQUIRE_EMAIL_VERIFICATION=false \
-            -e DISABLE_TELEMETRY=true \
-            -e IMAGE_TAG=test \
-            -e DEV_MODE=true \
-            onyxdotapp/onyx-integration:test \
-            /app/tests/integration/multitenant_tests
-        continue-on-error: true
-        id: run_multitenant_tests
-
-      - name: Check multi-tenant test results
-        run: |
-          if [ ${{ steps.run_multitenant_tests.outcome }} == 'failure' ]; then
-            echo "Multi-tenant integration tests failed. Exiting with error."
-            exit 1
-          else
-            echo "All multi-tenant integration tests passed successfully."
-          fi
-
-      - name: Stop multi-tenant Docker containers
-        run: |
-          cd deployment/docker_compose
-          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack down -v
+          # Re-tag to remove registry prefix for docker-compose
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }} onyxdotapp/onyx-backend:test
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }} onyxdotapp/onyx-model-server:test
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }} onyxdotapp/onyx-integration:test
 
       # NOTE: Use pre-ping/null pool to reduce flakiness due to dropped connections
+      # NOTE: don't need web server for integration tests
       - name: Start Docker containers
         run: |
           cd deployment/docker_compose
@@ -204,7 +257,16 @@ jobs:
           IMAGE_TAG=test \
           INTEGRATION_TESTS_MODE=true \
           CHECK_TTL_MANAGEMENT_TASK_FREQUENCY_IN_HOURS=0.001 \
-          docker compose -f docker-compose.dev.yml -p onyx-stack up -d
+          docker compose -f docker-compose.dev.yml -p onyx-stack up \
+            relational_db \
+            index \
+            cache \
+            minio \
+            api_server \
+            inference_model_server \
+            indexing_model_server \
+            background \
+            -d
         id: start_docker
 
       - name: Wait for service to be ready
@@ -247,48 +309,44 @@ jobs:
           docker compose -f docker-compose.mock-it-services.yml \
             -p mock-it-services-stack up -d
 
-      # NOTE: Use pre-ping/null to reduce flakiness due to dropped connections
-      - name: Run Standard Integration Tests
-        run: |
-          echo "Running integration tests..."
-          docker run --rm --network onyx-stack_default \
-            --name test-runner \
-            -e POSTGRES_HOST=relational_db \
-            -e POSTGRES_USER=postgres \
-            -e POSTGRES_PASSWORD=password \
-            -e DB_READONLY_USER=db_readonly_user \
-            -e DB_READONLY_PASSWORD=password \
-            -e POSTGRES_DB=postgres \
-            -e POSTGRES_POOL_PRE_PING=true \
-            -e POSTGRES_USE_NULL_POOL=true \
-            -e VESPA_HOST=index \
-            -e REDIS_HOST=cache \
-            -e API_SERVER_HOST=api_server \
-            -e OPENAI_API_KEY=${OPENAI_API_KEY} \
-            -e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
-            -e CONFLUENCE_TEST_SPACE_URL=${CONFLUENCE_TEST_SPACE_URL} \
-            -e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
-            -e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
-            -e JIRA_BASE_URL=${JIRA_BASE_URL} \
-            -e JIRA_USER_EMAIL=${JIRA_USER_EMAIL} \
-            -e JIRA_API_TOKEN=${JIRA_API_TOKEN} \
-            -e TEST_WEB_HOSTNAME=test-runner \
-            -e MOCK_CONNECTOR_SERVER_HOST=mock_connector_server \
-            -e MOCK_CONNECTOR_SERVER_PORT=8001 \
-            onyxdotapp/onyx-integration:test \
-            /app/tests/integration/tests \
-            /app/tests/integration/connector_job_tests
-        continue-on-error: true
-        id: run_tests
-
-      - name: Check test results
-        run: |
-          if [ ${{ steps.run_tests.outcome }} == 'failure' ]; then
-            echo "Integration tests failed. Exiting with error."
-            exit 1
-          else
-            echo "All integration tests passed successfully."
-          fi
+      - name: Run Integration Tests for ${{ matrix.test-dir.name }}
+        uses: nick-fields/retry@v3
+        with:
+          timeout_minutes: 20
+          max_attempts: 3
+          retry_wait_seconds: 10
+          command: |
+            echo "Running integration tests for ${{ matrix.test-dir.path }}..."
+            docker run --rm --network onyx-stack_default \
+              --name test-runner \
+              -e POSTGRES_HOST=relational_db \
+              -e POSTGRES_USER=postgres \
+              -e POSTGRES_PASSWORD=password \
+              -e POSTGRES_DB=postgres \
+              -e DB_READONLY_USER=db_readonly_user \
+              -e DB_READONLY_PASSWORD=password \
+              -e POSTGRES_POOL_PRE_PING=true \
+              -e POSTGRES_USE_NULL_POOL=true \
+              -e VESPA_HOST=index \
+              -e REDIS_HOST=cache \
+              -e API_SERVER_HOST=api_server \
+              -e OPENAI_API_KEY=${OPENAI_API_KEY} \
+              -e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
+              -e CONFLUENCE_TEST_SPACE_URL=${CONFLUENCE_TEST_SPACE_URL} \
+              -e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
+              -e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
+              -e JIRA_BASE_URL=${JIRA_BASE_URL} \
+              -e JIRA_USER_EMAIL=${JIRA_USER_EMAIL} \
+              -e JIRA_API_TOKEN=${JIRA_API_TOKEN} \
+              -e PERM_SYNC_SHAREPOINT_CLIENT_ID=${PERM_SYNC_SHAREPOINT_CLIENT_ID} \
+              -e PERM_SYNC_SHAREPOINT_PRIVATE_KEY="${PERM_SYNC_SHAREPOINT_PRIVATE_KEY}" \
+              -e PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD=${PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD} \
+              -e PERM_SYNC_SHAREPOINT_DIRECTORY_ID=${PERM_SYNC_SHAREPOINT_DIRECTORY_ID} \
+              -e TEST_WEB_HOSTNAME=test-runner \
+              -e MOCK_CONNECTOR_SERVER_HOST=mock_connector_server \
+              -e MOCK_CONNECTOR_SERVER_PORT=8001 \
+              onyxdotapp/onyx-integration:test \
+              /app/tests/integration/${{ matrix.test-dir.path }}
 
       # ------------------------------------------------------------
       # Always gather logs BEFORE "down":
@@ -308,7 +366,7 @@ jobs:
         if: always()
         uses: actions/upload-artifact@v4
         with:
-          name: docker-all-logs
+          name: docker-all-logs-${{ matrix.test-dir.name }}
           path: ${{ github.workspace }}/docker-compose.log
       # ------------------------------------------------------------
 
@@ -317,3 +375,157 @@ jobs:
         run: |
           cd deployment/docker_compose
           docker compose -f docker-compose.dev.yml -p onyx-stack down -v
+
+
+  multitenant-tests:
+    needs:
+      [
+        build-backend-image,
+        build-model-server-image,
+        build-integration-image,
+      ]
+    runs-on: blacksmith-8vcpu-ubuntu-2404-arm
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKER_USERNAME }}
+          password: ${{ secrets.DOCKER_TOKEN }}
+
+      - name: Pull Docker images
+        run: |
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }}) &
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }}) &
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }}) &
+          wait
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }} onyxdotapp/onyx-backend:test
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }} onyxdotapp/onyx-model-server:test
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }} onyxdotapp/onyx-integration:test
+
+      - name: Start Docker containers for multi-tenant tests
+        run: |
+          cd deployment/docker_compose
+          ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
+          MULTI_TENANT=true \
+          AUTH_TYPE=cloud \
+          REQUIRE_EMAIL_VERIFICATION=false \
+          DISABLE_TELEMETRY=true \
+          IMAGE_TAG=test \
+          DEV_MODE=true \
+          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack up \
+            relational_db \
+            index \
+            cache \
+            minio \
+            api_server \
+            inference_model_server \
+            indexing_model_server \
+            background \
+            -d
+        id: start_docker_multi_tenant
+
+      - name: Wait for service to be ready (multi-tenant)
+        run: |
+          echo "Starting wait-for-service script for multi-tenant..."
+          docker logs -f onyx-stack-api_server-1 &
+          start_time=$(date +%s)
+          timeout=300
+          while true; do
+            current_time=$(date +%s)
+            elapsed_time=$((current_time - start_time))
+            if [ $elapsed_time -ge $timeout ]; then
+              echo "Timeout reached. Service did not become ready in 5 minutes."
+              exit 1
+            fi
+            response=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:8080/health || echo "curl_error")
+            if [ "$response" = "200" ]; then
+              echo "Service is ready!"
+              break
+            elif [ "$response" = "curl_error" ]; then
+              echo "Curl encountered an error; retrying..."
+            else
+              echo "Service not ready yet (HTTP $response). Retrying in 5 seconds..."
+            fi
+            sleep 5
+          done
+          echo "Finished waiting for service."
+
+      - name: Run Multi-Tenant Integration Tests
+        run: |
+          echo "Running multi-tenant integration tests..."
+          docker run --rm --network onyx-stack_default \
+            --name test-runner \
+            -e POSTGRES_HOST=relational_db \
+            -e POSTGRES_USER=postgres \
+            -e POSTGRES_PASSWORD=password \
+            -e DB_READONLY_USER=db_readonly_user \
+            -e DB_READONLY_PASSWORD=password \
+            -e POSTGRES_DB=postgres \
+            -e POSTGRES_USE_NULL_POOL=true \
+            -e VESPA_HOST=index \
+            -e REDIS_HOST=cache \
+            -e API_SERVER_HOST=api_server \
+            -e OPENAI_API_KEY=${OPENAI_API_KEY} \
+            -e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
+            -e TEST_WEB_HOSTNAME=test-runner \
+            -e AUTH_TYPE=cloud \
+            -e MULTI_TENANT=true \
+            -e SKIP_RESET=true \
+            -e REQUIRE_EMAIL_VERIFICATION=false \
+            -e DISABLE_TELEMETRY=true \
+            -e IMAGE_TAG=test \
+            -e DEV_MODE=true \
+            onyxdotapp/onyx-integration:test \
+            /app/tests/integration/multitenant_tests
+
+      - name: Dump API server logs (multi-tenant)
+        if: always()
+        run: |
+          cd deployment/docker_compose
+          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack logs --no-color api_server > $GITHUB_WORKSPACE/api_server_multitenant.log || true
+
+      - name: Dump all-container logs (multi-tenant)
+        if: always()
+        run: |
+          cd deployment/docker_compose
+          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack logs --no-color > $GITHUB_WORKSPACE/docker-compose-multitenant.log || true
+
+      - name: Upload logs (multi-tenant)
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: docker-all-logs-multitenant
+          path: ${{ github.workspace }}/docker-compose-multitenant.log
+
+      - name: Stop multi-tenant Docker containers
+        if: always()
+        run: |
+          cd deployment/docker_compose
+          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack down -v
+
+  required: 
+    runs-on: blacksmith-2vcpu-ubuntu-2404-arm
+    needs: [integration-tests, multitenant-tests]
+    if: ${{ always() }}
+    steps:
+      - uses: actions/github-script@v7
+        with:
+          script: |
+            const needs = ${{ toJSON(needs) }};
+            const failed = Object.values(needs).some(n => n.result !== 'success');
+            if (failed) {
+              core.setFailed('One or more upstream jobs failed or were cancelled.');
+            } else {
+              core.notice('All required jobs succeeded.');
+            }

.github/workflows/pr-labeler.yml

@@ -0,0 +1,38 @@
+name: PR Labeler
+
+on:
+  pull_request_target:
+    branches:
+      - main
+    types:
+      - opened
+      - reopened
+      - synchronize
+      - edited
+
+permissions:
+  contents: read
+  pull-requests: write
+
+jobs:
+  validate_pr_title:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check PR title for Conventional Commits
+        env:
+          PR_TITLE: ${{ github.event.pull_request.title }}
+        run: |
+          echo "PR Title: $PR_TITLE"
+          if [[ ! "$PR_TITLE" =~ ^(feat|fix|docs|test|ci|refactor|perf|chore|revert|build)(\(.+\))?:\ .+ ]]; then
+            echo "::error::❌ Your PR title does not follow the Conventional Commits format.
+              This check ensures that all pull requests use clear, consistent titles that help automate changelogs and improve project history.
+
+              Please update your PR title to follow the Conventional Commits style.  
+              Here is a link to a blog explaining the reason why we've included the Conventional Commits style into our PR titles: https://xfuture-blog.com/working-with-conventional-commits
+
+              **Here are some examples of valid PR titles:**
+              - feat: add user authentication
+              - fix(login): handle null password error
+              - docs(readme): update installation instructions"
+            exit 1
+          fi

.github/workflows/pr-labeller.yml

@@ -1,20 +0,0 @@
-name: PR Labeller
-
-on:
-  pull_request_target:
-    branches: [main]
-    types: [opened, reopened, synchronize, edited, labeled, unlabeled]
-
-permissions:
-  contents: read
-  pull-requests: write
-
-jobs:
-  validate_pr_title:
-    runs-on: ubuntu-latest
-    steps:
-    - name: PR Conventional Commit Validation
-      uses: ytanikin/pr-conventional-commits@1.4.0
-      with:
-        task_types: '["feat","fix","docs","test","ci","refactor","perf","chore","revert","build"]'
-        add_label: 'true'

.github/workflows/pr-mit-integration-tests.yml

@@ -5,12 +5,15 @@ concurrency:
 
 on:
   merge_group:
-  pull_request:
-    branches:
-      - main
-      - "release/**"
+    types: [checks_requested]
 
 env:
+  # Private Registry Configuration
+  PRIVATE_REGISTRY: experimental-registry.blacksmith.sh:5000
+  PRIVATE_REGISTRY_USERNAME: ${{ secrets.PRIVATE_REGISTRY_USERNAME }}
+  PRIVATE_REGISTRY_PASSWORD: ${{ secrets.PRIVATE_REGISTRY_PASSWORD }}
+
+  # Test Environment Variables
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
   SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
   CONFLUENCE_TEST_SPACE_URL: ${{ secrets.CONFLUENCE_TEST_SPACE_URL }}
@@ -19,21 +22,46 @@ env:
   JIRA_BASE_URL: ${{ secrets.JIRA_BASE_URL }}
   JIRA_USER_EMAIL: ${{ secrets.JIRA_USER_EMAIL }}
   JIRA_API_TOKEN: ${{ secrets.JIRA_API_TOKEN }}
-  PLATFORM_PAIR: linux-amd64
+  PERM_SYNC_SHAREPOINT_CLIENT_ID: ${{ secrets.PERM_SYNC_SHAREPOINT_CLIENT_ID }}
+  PERM_SYNC_SHAREPOINT_PRIVATE_KEY: ${{ secrets.PERM_SYNC_SHAREPOINT_PRIVATE_KEY }}
+  PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD: ${{ secrets.PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD }}
+  PERM_SYNC_SHAREPOINT_DIRECTORY_ID: ${{ secrets.PERM_SYNC_SHAREPOINT_DIRECTORY_ID }}
+
 jobs:
-  integration-tests-mit:
-    # See https://runs-on.com/runners/linux/
-    runs-on:
-      [
-        runs-on,
-        runner=32cpu-linux-x64,
-        disk=large,
-        "run-id=${{ github.run_id }}",
-      ]
+  discover-test-dirs:
+    runs-on: blacksmith-2vcpu-ubuntu-2404-arm
+    outputs:
+      test-dirs: ${{ steps.set-matrix.outputs.test-dirs }}
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-        
+
+      - name: Discover test directories
+        id: set-matrix
+        run: |
+          # Find all leaf-level directories in both test directories
+          tests_dirs=$(find backend/tests/integration/tests -mindepth 1 -maxdepth 1 -type d ! -name "__pycache__" -exec basename {} \; | sort)
+          connector_dirs=$(find backend/tests/integration/connector_job_tests -mindepth 1 -maxdepth 1 -type d ! -name "__pycache__" -exec basename {} \; | sort)
+
+          # Create JSON array with directory info
+          all_dirs=""
+          for dir in $tests_dirs; do
+            all_dirs="$all_dirs{\"path\":\"tests/$dir\",\"name\":\"tests-$dir\"},"
+          done
+          for dir in $connector_dirs; do
+            all_dirs="$all_dirs{\"path\":\"connector_job_tests/$dir\",\"name\":\"connector-$dir\"},"
+          done
+
+          # Remove trailing comma and wrap in array
+          all_dirs="[${all_dirs%,}]"
+          echo "test-dirs=$all_dirs" >> $GITHUB_OUTPUT
+
+  prepare-build:
+    runs-on: blacksmith-2vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
       - name: Setup Python
         uses: actions/setup-python@v5
         with:
@@ -42,7 +70,9 @@ jobs:
           cache-dependency-path: |
             backend/requirements/default.txt
             backend/requirements/dev.txt
-      - run: |
+
+      - name: Install Python dependencies
+        run: |
           python -m pip install --upgrade pip
           pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
           pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
@@ -63,72 +93,156 @@ jobs:
             -i /local/openapi.json \
             -g python \
             -o /local/onyx_openapi_client \
-            --package-name onyx_openapi_client
-            
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+            --package-name onyx_openapi_client \
+            --skip-validate-spec \
+            --openapi-normalizer "SIMPLIFY_ONEOF_ANYOF=true,SET_OAS3_NULLABLE=true"
 
+      - name: Upload OpenAPI artifacts
+        uses: actions/upload-artifact@v4
+        with:
+          name: openapi-artifacts
+          path: backend/generated/
+
+  build-backend-image:
+    runs-on: blacksmith-16vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push Backend Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile
+          platforms: linux/arm64
+          tags: ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }}
+          push: true
+
+  build-model-server-image:
+    runs-on: blacksmith-16vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push Model Server Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile.model_server
+          platforms: linux/arm64
+          tags: ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }}
+          push: true
+          outputs: type=registry
+          provenance: false
+
+  build-integration-image:
+    needs: prepare-build
+    runs-on: blacksmith-16vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      - name: Download OpenAPI artifacts
+        uses: actions/download-artifact@v4
+        with:
+          name: openapi-artifacts
+          path: backend/generated/
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push integration test Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/tests/integration/Dockerfile
+          platforms: linux/arm64
+          tags: ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }}
+          push: true
+
+  integration-tests-mit:
+    needs:
+      [
+        discover-test-dirs,
+        build-backend-image,
+        build-model-server-image,
+        build-integration-image,
+      ]
+    # See https://docs.blacksmith.sh/blacksmith-runners/overview
+    runs-on: blacksmith-8vcpu-ubuntu-2404-arm
+
+    strategy:
+      fail-fast: false
+      matrix:
+        test-dir: ${{ fromJson(needs.discover-test-dirs.outputs.test-dirs) }}
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Login to Private Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.PRIVATE_REGISTRY }}
+          username: ${{ env.PRIVATE_REGISTRY_USERNAME }}
+          password: ${{ env.PRIVATE_REGISTRY_PASSWORD }}
+
+      # needed for pulling Vespa, Redis, Postgres, and Minio images
+      # otherwise, we hit the "Unauthenticated users" limit
+      # https://docs.docker.com/docker-hub/usage/
       - name: Login to Docker Hub
         uses: docker/login-action@v3
         with:
           username: ${{ secrets.DOCKER_USERNAME }}
           password: ${{ secrets.DOCKER_TOKEN }}
 
-      # tag every docker image with "test" so that we can spin up the correct set
-      # of images during testing
-
-      # We don't need to build the Web Docker image since it's not yet used
-      # in the integration tests. We have a separate action to verify that it builds
-      # successfully.
-      - name: Pull Web Docker image
+      - name: Pull Docker images
         run: |
-          docker pull onyxdotapp/onyx-web-server:latest
-          docker tag onyxdotapp/onyx-web-server:latest onyxdotapp/onyx-web-server:test
+          # Pull all images from registry in parallel
+          echo "Pulling Docker images in parallel..."
+          # Pull images from private registry
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }}) &
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }}) &
+          (docker pull ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }}) &
 
-      # we use the runs-on cache for docker builds
-      # in conjunction with runs-on runners, it has better speed and unlimited caching
-      # https://runs-on.com/caching/s3-cache-for-github-actions/
-      # https://runs-on.com/caching/docker/
-      # https://github.com/moby/buildkit#s3-cache-experimental
+          # Wait for all background jobs to complete
+          wait
+          echo "All Docker images pulled successfully"
 
-      # images are built and run locally for testing purposes. Not pushed.
-      - name: Build Backend Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-backend:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/mit-integration-tests/backend-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/mit-integration-tests/backend-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build Model Server Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile.model_server
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-model-server:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/mit-integration-tests/model-server-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/mit-integration-tests/model-server-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build integration test Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/tests/integration/Dockerfile
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-integration:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/mit-integration-tests/integration-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/mit-integration-tests/integration-${{ env.PLATFORM_PAIR }}/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
+          # Re-tag to remove registry prefix for docker-compose
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-backend:test-${{ github.run_id }} onyxdotapp/onyx-backend:test
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-model-server:test-${{ github.run_id }} onyxdotapp/onyx-model-server:test
+          docker tag ${{ env.PRIVATE_REGISTRY }}/integration-test-onyx-integration:test-${{ github.run_id }} onyxdotapp/onyx-integration:test
 
       # NOTE: Use pre-ping/null pool to reduce flakiness due to dropped connections
+      # NOTE: don't need web server for integration tests
       - name: Start Docker containers
         run: |
           cd deployment/docker_compose
@@ -139,7 +253,16 @@ jobs:
           DISABLE_TELEMETRY=true \
           IMAGE_TAG=test \
           INTEGRATION_TESTS_MODE=true \
-          docker compose -f docker-compose.dev.yml -p onyx-stack up -d
+          docker compose -f docker-compose.dev.yml -p onyx-stack up \
+            relational_db \
+            index \
+            cache \
+            minio \
+            api_server \
+            inference_model_server \
+            indexing_model_server \
+            background \
+            -d
         id: start_docker
 
       - name: Wait for service to be ready
@@ -183,47 +306,44 @@ jobs:
             -p mock-it-services-stack up -d
 
       # NOTE: Use pre-ping/null to reduce flakiness due to dropped connections
-      - name: Run Standard Integration Tests
-        run: |
-          echo "Running integration tests..."
-          docker run --rm --network onyx-stack_default \
-            --name test-runner \
-            -e POSTGRES_HOST=relational_db \
-            -e POSTGRES_USER=postgres \
-            -e POSTGRES_PASSWORD=password \
-            -e POSTGRES_DB=postgres \
-            -e DB_READONLY_USER=db_readonly_user \
-            -e DB_READONLY_PASSWORD=password \
-            -e POSTGRES_POOL_PRE_PING=true \
-            -e POSTGRES_USE_NULL_POOL=true \
-            -e VESPA_HOST=index \
-            -e REDIS_HOST=cache \
-            -e API_SERVER_HOST=api_server \
-            -e OPENAI_API_KEY=${OPENAI_API_KEY} \
-            -e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
-            -e CONFLUENCE_TEST_SPACE_URL=${CONFLUENCE_TEST_SPACE_URL} \
-            -e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
-            -e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
-            -e JIRA_BASE_URL=${JIRA_BASE_URL} \
-            -e JIRA_USER_EMAIL=${JIRA_USER_EMAIL} \
-            -e JIRA_API_TOKEN=${JIRA_API_TOKEN} \
-            -e TEST_WEB_HOSTNAME=test-runner \
-            -e MOCK_CONNECTOR_SERVER_HOST=mock_connector_server \
-            -e MOCK_CONNECTOR_SERVER_PORT=8001 \
-            onyxdotapp/onyx-integration:test \
-            /app/tests/integration/tests \
-            /app/tests/integration/connector_job_tests
-        continue-on-error: true
-        id: run_tests
-
-      - name: Check test results
-        run: |
-          if [ ${{ steps.run_tests.outcome }} == 'failure' ]; then
-            echo "Integration tests failed. Exiting with error."
-            exit 1
-          else
-            echo "All integration tests passed successfully."
-          fi
+      - name: Run Integration Tests for ${{ matrix.test-dir.name }}
+        uses: nick-fields/retry@v3
+        with:
+          timeout_minutes: 20
+          max_attempts: 3
+          retry_wait_seconds: 10
+          command: |
+            echo "Running integration tests for ${{ matrix.test-dir.path }}..."
+            docker run --rm --network onyx-stack_default \
+              --name test-runner \
+              -e POSTGRES_HOST=relational_db \
+              -e POSTGRES_USER=postgres \
+              -e POSTGRES_PASSWORD=password \
+              -e POSTGRES_DB=postgres \
+              -e DB_READONLY_USER=db_readonly_user \
+              -e DB_READONLY_PASSWORD=password \
+              -e POSTGRES_POOL_PRE_PING=true \
+              -e POSTGRES_USE_NULL_POOL=true \
+              -e VESPA_HOST=index \
+              -e REDIS_HOST=cache \
+              -e API_SERVER_HOST=api_server \
+              -e OPENAI_API_KEY=${OPENAI_API_KEY} \
+              -e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
+              -e CONFLUENCE_TEST_SPACE_URL=${CONFLUENCE_TEST_SPACE_URL} \
+              -e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
+              -e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
+              -e JIRA_BASE_URL=${JIRA_BASE_URL} \
+              -e JIRA_USER_EMAIL=${JIRA_USER_EMAIL} \
+              -e JIRA_API_TOKEN=${JIRA_API_TOKEN} \
+              -e PERM_SYNC_SHAREPOINT_CLIENT_ID=${PERM_SYNC_SHAREPOINT_CLIENT_ID} \
+              -e PERM_SYNC_SHAREPOINT_PRIVATE_KEY="${PERM_SYNC_SHAREPOINT_PRIVATE_KEY}" \
+              -e PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD=${PERM_SYNC_SHAREPOINT_CERTIFICATE_PASSWORD} \
+              -e PERM_SYNC_SHAREPOINT_DIRECTORY_ID=${PERM_SYNC_SHAREPOINT_DIRECTORY_ID} \
+              -e TEST_WEB_HOSTNAME=test-runner \
+              -e MOCK_CONNECTOR_SERVER_HOST=mock_connector_server \
+              -e MOCK_CONNECTOR_SERVER_PORT=8001 \
+              onyxdotapp/onyx-integration:test \
+              /app/tests/integration/${{ matrix.test-dir.path }}
 
       # ------------------------------------------------------------
       # Always gather logs BEFORE "down":
@@ -243,7 +363,7 @@ jobs:
         if: always()
         uses: actions/upload-artifact@v4
         with:
-          name: docker-all-logs
+          name: docker-all-logs-${{ matrix.test-dir.name }}
           path: ${{ github.workspace }}/docker-compose.log
       # ------------------------------------------------------------
 
@@ -252,3 +372,20 @@ jobs:
         run: |
           cd deployment/docker_compose
           docker compose -f docker-compose.dev.yml -p onyx-stack down -v
+
+  
+  required: 
+    runs-on: blacksmith-2vcpu-ubuntu-2404-arm
+    needs: [integration-tests-mit]
+    if: ${{ always() }}
+    steps:
+      - uses: actions/github-script@v7
+        with:
+          script: |
+            const needs = ${{ toJSON(needs) }};
+            const failed = Object.values(needs).some(n => n.result !== 'success');
+            if (failed) {
+              core.setFailed('One or more upstream jobs failed or were cancelled.');
+            } else {
+              core.notice('All required jobs succeeded.');
+            }

.github/workflows/pr-playwright-tests.yml

@@ -6,44 +6,165 @@ concurrency:
 on: push
 
 env:
+  # AWS ECR Configuration
+  AWS_REGION: ${{ secrets.AWS_REGION || 'us-west-2' }}
+  ECR_REGISTRY: ${{ secrets.ECR_REGISTRY }}
+  AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID_ECR }}
+  AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY_ECR }}
+  BUILDX_NO_DEFAULT_ATTESTATIONS: 1
+  
+  # Test Environment Variables
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
   SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
   GEN_AI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+  EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
+
+  # for federated slack tests
+  SLACK_CLIENT_ID: ${{ secrets.SLACK_CLIENT_ID }}
+  SLACK_CLIENT_SECRET: ${{ secrets.SLACK_CLIENT_SECRET }}
+
   MOCK_LLM_RESPONSE: true
-  PYTEST_PLAYWRIGHT_SKIP_INITIAL_RESET: true
 
 jobs:
-  playwright-tests:
-    name: Playwright Tests
+  build-web-image:
+    runs-on: blacksmith-8vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
 
-    # See https://runs-on.com/runners/linux/
-    runs-on:
-      [
-        runs-on,
-        runner=32cpu-linux-x64,
-        disk=large,
-        "run-id=${{ github.run_id }}",
-      ]
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v4
+        with:
+          aws-access-key-id: ${{ env.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ env.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ env.AWS_REGION }}
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v2
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push Web Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./web
+          file: ./web/Dockerfile
+          platforms: linux/arm64
+          tags: ${{ env.ECR_REGISTRY }}/integration-test-onyx-web-server:playwright-test-${{ github.run_id }}
+          provenance: false
+          sbom: false
+          push: true
+
+  build-backend-image:
+    runs-on: blacksmith-8vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v4
+        with:
+          aws-access-key-id: ${{ env.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ env.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ env.AWS_REGION }}
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v2
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push Backend Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile
+          platforms: linux/arm64
+          tags: ${{ env.ECR_REGISTRY }}/integration-test-onyx-backend:playwright-test-${{ github.run_id }}
+          provenance: false
+          sbom: false
+          push: true
+
+  build-model-server-image:
+    runs-on: blacksmith-8vcpu-ubuntu-2404-arm
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v4
+        with:
+          aws-access-key-id: ${{ env.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ env.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ env.AWS_REGION }}
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v2
+
+      - name: Set up Docker Buildx
+        uses: useblacksmith/setup-docker-builder@v1
+
+      - name: Build and push Model Server Docker image
+        uses: useblacksmith/build-push-action@v2
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile.model_server
+          platforms: linux/arm64
+          tags: ${{ env.ECR_REGISTRY }}/integration-test-onyx-model-server:playwright-test-${{ github.run_id }}
+          provenance: false
+          sbom: false
+          push: true
+
+  playwright-tests:
+    needs: [build-web-image, build-backend-image, build-model-server-image]
+    name: Playwright Tests
+    runs-on: blacksmith-8vcpu-ubuntu-2404-arm
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
         with:
           fetch-depth: 0
 
-      - name: Set up Python
-        uses: actions/setup-python@v5
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v4
         with:
-          python-version: "3.11"
-          cache: "pip"
-          cache-dependency-path: |
-            backend/requirements/default.txt
-            backend/requirements/dev.txt
-            backend/requirements/model_server.txt
-      - run: |
-          python -m pip install --upgrade pip
-          pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
-          pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
-          pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
+          aws-access-key-id: ${{ env.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ env.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ env.AWS_REGION }}
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v2
+
+      # needed for pulling Vespa, Redis, Postgres, and Minio images
+      # otherwise, we hit the "Unauthenticated users" limit
+      # https://docs.docker.com/docker-hub/usage/
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKER_USERNAME }}
+          password: ${{ secrets.DOCKER_TOKEN }}
+
+      - name: Pull Docker images
+        run: |
+          # Pull all images from ECR in parallel
+          echo "Pulling Docker images in parallel..."
+          (docker pull ${{ env.ECR_REGISTRY }}/integration-test-onyx-web-server:playwright-test-${{ github.run_id }}) &
+          (docker pull ${{ env.ECR_REGISTRY }}/integration-test-onyx-backend:playwright-test-${{ github.run_id }}) &
+          (docker pull ${{ env.ECR_REGISTRY }}/integration-test-onyx-model-server:playwright-test-${{ github.run_id }}) &
+
+          # Wait for all background jobs to complete
+          wait
+          echo "All Docker images pulled successfully"
+
+          # Re-tag with expected names for docker-compose
+          docker tag ${{ env.ECR_REGISTRY }}/integration-test-onyx-web-server:playwright-test-${{ github.run_id }} onyxdotapp/onyx-web-server:test
+          docker tag ${{ env.ECR_REGISTRY }}/integration-test-onyx-backend:playwright-test-${{ github.run_id }} onyxdotapp/onyx-backend:test
+          docker tag ${{ env.ECR_REGISTRY }}/integration-test-onyx-model-server:playwright-test-${{ github.run_id }} onyxdotapp/onyx-model-server:test
 
       - name: Setup node
         uses: actions/setup-node@v4
@@ -58,68 +179,13 @@ jobs:
         working-directory: ./web
         run: npx playwright install --with-deps
 
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-
-      - name: Login to Docker Hub
-        uses: docker/login-action@v3
-        with:
-          username: ${{ secrets.DOCKER_USERNAME }}
-          password: ${{ secrets.DOCKER_TOKEN }}
-
-      # tag every docker image with "test" so that we can spin up the correct set
-      # of images during testing
-
-      # we use the runs-on cache for docker builds
-      # in conjunction with runs-on runners, it has better speed and unlimited caching
-      # https://runs-on.com/caching/s3-cache-for-github-actions/
-      # https://runs-on.com/caching/docker/
-      # https://github.com/moby/buildkit#s3-cache-experimental
-
-      # images are built and run locally for testing purposes. Not pushed.
-
-      - name: Build Web Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./web
-          file: ./web/Dockerfile
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-web-server:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/web-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/web-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build Backend Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-backend:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build Model Server Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile.model_server
-          platforms: linux/amd64
-          tags: onyxdotapp/onyx-model-server:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
-          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
       - name: Start Docker containers
         run: |
           cd deployment/docker_compose
           ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
           AUTH_TYPE=basic \
-          GEN_AI_API_KEY=${{ secrets.OPENAI_API_KEY }} \
+          GEN_AI_API_KEY=${{ env.OPENAI_API_KEY }} \
+          EXA_API_KEY=${{ env.EXA_API_KEY }} \
           REQUIRE_EMAIL_VERIFICATION=false \
           DISABLE_TELEMETRY=true \
           IMAGE_TAG=test \
@@ -160,12 +226,6 @@ jobs:
           done
           echo "Finished waiting for service."
 
-      - name: Run pytest playwright test init
-        working-directory: ./backend
-        env:
-          PYTEST_IGNORE_SKIP: true
-        run: pytest -s tests/integration/tests/playwright/test_playwright.py
-
       - name: Run Playwright tests
         working-directory: ./web
         run: npx playwright test

.github/workflows/pr-python-checks.yml

@@ -48,6 +48,8 @@ jobs:
           -g python \
           -o /local/onyx_openapi_client \
           --package-name onyx_openapi_client \
+          --skip-validate-spec \
+          --openapi-normalizer "SIMPLIFY_ONEOF_ANYOF=true,SET_OAS3_NULLABLE=true"
             
     - name: Run MyPy
       run: |

.gitignore

@@ -17,12 +17,26 @@ backend/tests/regression/answer_quality/test_data.json
 backend/tests/regression/search_quality/eval-*
 backend/tests/regression/search_quality/search_eval_config.yaml
 backend/tests/regression/search_quality/*.json
+backend/onyx/evals/data/
+*.log
 
 # secret files
 .env
 jira_test_env
+settings.json
 
 # others
 /deployment/data/nginx/app.conf
 *.sw?
 /backend/tests/regression/answer_quality/search_test_config.yaml
+*.egg-info
+
+# Local .terraform directories
+**/.terraform/*
+
+# Local .tfstate files
+*.tfstate
+*.tfstate.*
+
+# Local .terraform.lock.hcl file
+.terraform.lock.hcl

.mcp.json.template

@@ -0,0 +1,8 @@
+{
+  "mcpServers": {
+    "onyx-mcp": {
+      "type": "http",
+      "url": "http://localhost:8000/mcp"
+    }
+  }
+}

.vscode/env_template.txt

@@ -23,6 +23,9 @@ DISABLE_LLM_DOC_RELEVANCE=False
 # Useful if you want to toggle auth on/off (google_oauth/OIDC specifically)
 OAUTH_CLIENT_ID=<REPLACE THIS>
 OAUTH_CLIENT_SECRET=<REPLACE THIS>
+OPENID_CONFIG_URL=<REPLACE THIS>
+SAML_CONF_DIR=/<ABSOLUTE PATH TO ONYX>/onyx/backend/ee/onyx/configs/saml_config
+
 # Generally not useful for dev, we don't generally want to set up an SMTP server for dev
 REQUIRE_EMAIL_VERIFICATION=False
 
@@ -46,7 +49,6 @@ PYTHONUNBUFFERED=1
 
 
 # Internet Search
-BING_API_KEY=<REPLACE THIS>
 EXA_API_KEY=<REPLACE THIS>
 
 
@@ -65,3 +67,12 @@ S3_ENDPOINT_URL=http://localhost:9004
 S3_FILE_STORE_BUCKET_NAME=onyx-file-store-bucket
 S3_AWS_ACCESS_KEY_ID=minioadmin
 S3_AWS_SECRET_ACCESS_KEY=minioadmin
+
+# Show extra/uncommon connectors
+SHOW_EXTRA_CONNECTORS=True
+
+# Local langsmith tracing
+LANGSMITH_TRACING="true"
+LANGSMITH_ENDPOINT="https://api.smith.langchain.com"
+LANGSMITH_API_KEY=<REPLACE_THIS>
+LANGSMITH_PROJECT=<REPLACE_THIS>

.vscode/launch.template.jsonc

@@ -24,21 +24,23 @@
           "Celery primary",
           "Celery light",
           "Celery heavy",
-          "Celery indexing",
-          "Celery user files indexing",
+          "Celery docfetching",
+          "Celery docprocessing",
           "Celery beat",
           "Celery monitoring"
         ],
         "presentation": {
           "group": "1"
-        }
+        },
+        "stopAll": true
       },
       {
         "name": "Web / Model / API",
         "configurations": ["Web Server", "Model Server", "API Server"],
         "presentation": {
           "group": "1"
-        }
+        },
+        "stopAll": true
       },
       {
         "name": "Celery (all)",
@@ -48,13 +50,13 @@
           "Celery heavy",
           "Celery docfetching",
           "Celery docprocessing",
-          "Celery user files indexing",
           "Celery beat",
           "Celery monitoring"
         ],
         "presentation": {
           "group": "1"
-        }
+        },
+        "stopAll": true
       }
     ],
     "configurations": [
@@ -190,7 +192,7 @@
           "--loglevel=INFO",
           "--hostname=light@%n",
           "-Q",
-          "vespa_metadata_sync,connector_deletion,doc_permissions_upsert"
+          "vespa_metadata_sync,connector_deletion,doc_permissions_upsert,index_attempt_cleanup"
         ],
         "presentation": {
           "group": "2"
@@ -383,6 +385,28 @@
           "group": "3"
         }
       },
+      {
+        "name": "Eval CLI",
+        "type": "debugpy",
+        "request": "launch",
+        "program": "${workspaceFolder}/backend/onyx/evals/eval_cli.py",
+        "cwd": "${workspaceFolder}/backend",
+        "console": "integratedTerminal",
+        "justMyCode": false,
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "presentation": {
+          "group": "3"
+        },
+        "env": {
+          "LOG_LEVEL": "INFO",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
+        },
+        "args": [
+            "--verbose"
+        ],
+        "consoleTitle": "Eval CLI Console"
+    },
       {
         // Celery jobs launched through a single background script (legacy)
         // Recommend using the "Celery (all)" compound launch instead.
@@ -429,7 +453,7 @@
       },
       "args": [
         "--filename",
-        "generated/openapi.json",
+        "generated/openapi.json"
       ]
     },
     {
@@ -464,4 +488,4 @@
       }
     ]
   }
-  
+ 

AGENTS.md

@@ -0,0 +1,295 @@
+# AGENTS.md
+
+This file provides guidance to Codex when working with code in this repository.
+
+## KEY NOTES
+
+- If you run into any missing python dependency errors, try running your command with `workon onyx &&` in front
+to assume the python venv.
+- To make tests work, check the `.env` file at the root of the project to find an OpenAI key.
+- If using `playwright` to explore the frontend, you can usually log in with username `a@test.com` and password
+`a`. The app can be accessed at `http://localhost:3000`.
+- You should assume that all Onyx services are running. To verify, you can check the `backend/log` directory to
+make sure we see logs coming out from the relevant service.
+- To connect to the Postgres database, use: `docker exec -it onyx-stack-relational_db-1 psql -U postgres -c "<SQL>"`
+- When making calls to the backend, always go through the frontend. E.g. make a call to `http://localhost:3000/api/persona` not `http://localhost:8080/api/persona`
+- Put ALL db operations under the `backend/onyx/db` / `backend/ee/onyx/db` directories. Don't run queries
+outside of those directories.
+
+## Project Overview
+
+**Onyx** (formerly Danswer) is an open-source Gen-AI and Enterprise Search platform that connects to company documents, apps, and people. It features a modular architecture with both Community Edition (MIT licensed) and Enterprise Edition offerings.
+
+
+### Background Workers (Celery)
+
+Onyx uses Celery for asynchronous task processing with multiple specialized workers:
+
+#### Worker Types
+
+1. **Primary Worker** (`celery_app.py`)
+   - Coordinates core background tasks and system-wide operations
+   - Handles connector management, document sync, pruning, and periodic checks
+   - Runs with 4 threads concurrency
+   - Tasks: connector deletion, vespa sync, pruning, LLM model updates, user file sync
+
+2. **Docfetching Worker** (`docfetching`)
+   - Fetches documents from external data sources (connectors)
+   - Spawns docprocessing tasks for each document batch
+   - Implements watchdog monitoring for stuck connectors
+   - Configurable concurrency (default from env)
+
+3. **Docprocessing Worker** (`docprocessing`)
+   - Processes fetched documents through the indexing pipeline:
+     - Upserts documents to PostgreSQL
+     - Chunks documents and adds contextual information
+     - Embeds chunks via model server
+     - Writes chunks to Vespa vector database
+     - Updates document metadata
+   - Configurable concurrency (default from env)
+
+4. **Light Worker** (`light`)
+   - Handles lightweight, fast operations
+   - Tasks: vespa operations, document permissions sync, external group sync
+   - Higher concurrency for quick tasks
+
+5. **Heavy Worker** (`heavy`)
+   - Handles resource-intensive operations
+   - Primary task: document pruning operations
+   - Runs with 4 threads concurrency
+
+6. **KG Processing Worker** (`kg_processing`)
+   - Handles Knowledge Graph processing and clustering
+   - Builds relationships between documents
+   - Runs clustering algorithms
+   - Configurable concurrency
+
+7. **Monitoring Worker** (`monitoring`)
+   - System health monitoring and metrics collection
+   - Monitors Celery queues, process memory, and system status
+   - Single thread (monitoring doesn't need parallelism)
+   - Cloud-specific monitoring tasks
+
+8. **Beat Worker** (`beat`)
+   - Celery's scheduler for periodic tasks
+   - Uses DynamicTenantScheduler for multi-tenant support
+   - Schedules tasks like:
+     - Indexing checks (every 15 seconds)
+     - Connector deletion checks (every 20 seconds)
+     - Vespa sync checks (every 20 seconds)
+     - Pruning checks (every 20 seconds)
+     - KG processing (every 60 seconds)
+     - Monitoring tasks (every 5 minutes)
+     - Cleanup tasks (hourly)
+
+#### Key Features
+
+- **Thread-based Workers**: All workers use thread pools (not processes) for stability
+- **Tenant Awareness**: Multi-tenant support with per-tenant task isolation. There is a 
+middleware layer that automatically finds the appropriate tenant ID when sending tasks 
+via Celery Beat.
+- **Task Prioritization**: High, Medium, Low priority queues
+- **Monitoring**: Built-in heartbeat and liveness checking
+- **Failure Handling**: Automatic retry and failure recovery mechanisms
+- **Redis Coordination**: Inter-process communication via Redis
+- **PostgreSQL State**: Task state and metadata stored in PostgreSQL
+
+
+#### Important Notes
+
+**Defining Tasks**: 
+- Always use `@shared_task` rather than `@celery_app`
+- Put tasks under `background/celery/tasks/` or `ee/background/celery/tasks`
+
+**Defining APIs**:
+When creating new FastAPI APIs, do NOT use the `response_model` field. Instead, just type the
+function.
+
+**Testing Updates**:
+If you make any updates to a celery worker and you want to test these changes, you will need
+to ask me to restart the celery worker. There is no auto-restart on code-change mechanism.
+
+### Code Quality
+```bash
+# Install and run pre-commit hooks
+pre-commit install
+pre-commit run --all-files
+```
+
+NOTE: Always make sure everything is strictly typed (both in Python and Typescript).
+
+## Architecture Overview
+
+### Technology Stack
+- **Backend**: Python 3.11, FastAPI, SQLAlchemy, Alembic, Celery
+- **Frontend**: Next.js 15+, React 18, TypeScript, Tailwind CSS
+- **Database**: PostgreSQL with Redis caching
+- **Search**: Vespa vector database
+- **Auth**: OAuth2, SAML, multi-provider support
+- **AI/ML**: LangChain, LiteLLM, multiple embedding models
+
+### Directory Structure
+
+```
+backend/
+├── onyx/
+│   ├── auth/                    # Authentication & authorization
+│   ├── chat/                    # Chat functionality & LLM interactions
+│   ├── connectors/              # Data source connectors
+│   ├── db/                      # Database models & operations
+│   ├── document_index/          # Vespa integration
+│   ├── federated_connectors/    # External search connectors
+│   ├── llm/                     # LLM provider integrations
+│   └── server/                  # API endpoints & routers
+├── ee/                          # Enterprise Edition features
+├── alembic/                     # Database migrations
+└── tests/                       # Test suites
+
+web/
+├── src/app/                     # Next.js app router pages
+├── src/components/              # Reusable React components
+└── src/lib/                     # Utilities & business logic
+```
+
+## Database & Migrations
+
+### Running Migrations
+```bash
+# Standard migrations
+alembic upgrade head
+
+# Multi-tenant (Enterprise)
+alembic -n schema_private upgrade head
+```
+
+### Creating Migrations
+```bash
+# Auto-generate migration
+alembic revision --autogenerate -m "description"
+
+# Multi-tenant migration
+alembic -n schema_private revision --autogenerate -m "description"
+```
+
+## Testing Strategy
+
+There are 4 main types of tests within Onyx:
+
+### Unit Tests
+These should not assume any Onyx/external services are available to be called.
+Interactions with the outside world should be mocked using `unittest.mock`. Generally, only 
+write these for complex, isolated modules e.g. `citation_processing.py`.
+
+To run them:
+
+```bash
+python -m dotenv -f .vscode/.env run -- pytest -xv backend/tests/unit
+```
+
+### External Dependency Unit Tests
+These tests assume that all external dependencies of Onyx are available and callable (e.g. Postgres, Redis, 
+MinIO/S3, Vespa are running + OpenAI can be called + any request to the internet is fine + etc.).
+
+However, the actual Onyx containers are not running and with these tests we call the function to test directly.
+We can also mock components/calls at will. 
+
+The goal with these tests are to minimize mocking while giving some flexibility to mock things that are flakey, 
+need strictly controlled behavior, or need to have their internal behavior validated (e.g. verify a function is called
+with certain args, something that would be impossible with proper integration tests).
+
+A great example of this type of test is `backend/tests/external_dependency_unit/connectors/confluence/test_confluence_group_sync.py`.
+
+To run them:
+
+```bash
+python -m dotenv -f .vscode/.env run -- pytest backend/tests/external_dependency_unit
+```
+
+### Integration Tests
+Standard integration tests. Every test in `backend/tests/integration` runs against a real Onyx deployment. We cannot 
+mock anything in these tests. Prefer writing integration tests (or External Dependency Unit Tests if mocking/internal 
+verification is necessary) over any other type of test.
+
+Tests are parallelized at a directory level.
+
+When writing integration tests, make sure to check the root `conftest.py` for useful fixtures + the `backend/tests/integration/common_utils` directory for utilities. Prefer (if one exists), calling the appropriate Manager 
+class in the utils over directly calling the APIs with a library like `requests`. Prefer using fixtures rather than
+calling the utilities directly (e.g. do NOT create admin users with 
+`admin_user = UserManager.create(name="admin_user")`, instead use the `admin_user` fixture).
+
+A great example of this type of test is `backend/tests/integration/dev_apis/test_simple_chat_api.py`.
+
+To run them:
+
+```bash
+python -m dotenv -f .vscode/.env run -- pytest backend/tests/integration
+```
+
+### Playwright (E2E) Tests
+These tests are an even more complete version of the Integration Tests mentioned above. Has all services of Onyx 
+running, *including* the Web Server.
+
+Use these tests for anything that requires significant frontend <-> backend coordination.
+
+Tests are located at `web/tests/e2e`. Tests are written in TypeScript.
+
+To run them:
+
+```bash
+npx playwright test <TEST_NAME>
+```
+
+
+## Logs
+
+When (1) writing integration tests or (2) doing live tests (e.g. curl / playwright) you can get access
+to logs via the `backend/log/<service_name>_debug.log` file. All Onyx services (api_server, web_server, celery_X)
+will be tailing their logs to this file. 
+
+
+## Security Considerations
+
+- Never commit API keys or secrets to repository
+- Use encrypted credential storage for connector credentials
+- Follow RBAC patterns for new features
+- Implement proper input validation with Pydantic models
+- Use parameterized queries to prevent SQL injection
+
+## AI/LLM Integration
+
+- Multiple LLM providers supported via LiteLLM
+- Configurable models per feature (chat, search, embeddings)
+- Streaming support for real-time responses
+- Token management and rate limiting
+- Custom prompts and agent actions
+
+## UI/UX Patterns
+
+- Tailwind CSS with design system in `web/src/components/ui/`
+- Radix UI and Headless UI for accessible components
+- SWR for data fetching and caching
+- Form validation with react-hook-form
+- Error handling with popup notifications
+
+## Creating a Plan
+When creating a plan in the `plans` directory, make sure to include at least these elements:
+
+**Issues to Address**
+What the change is meant to do.
+
+**Important Notes**
+Things you come across in your research that are important to the implementation.
+
+**Implementation strategy**
+How you are going to make the changes happen. High level approach.
+
+**Tests**
+What unit (use rarely), external dependency unit, integration, and playwright tests you plan to write to 
+verify the correct behavior. Don't overtest. Usually, a given change only needs one type of test.
+
+Do NOT include these: *Timeline*, *Rollback plan*
+
+This is a minimal list - feel free to include more. Do NOT write code as part of your plan.
+Keep it high level. You can reference certain files or functions though.
+
+Before writing your plan, make sure to do research. Explore the relevant sections in the codebase.

CLAUDE.md

@@ -0,0 +1,295 @@
+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## KEY NOTES
+
+- If you run into any missing python dependency errors, try running your command with `workon onyx &&` in front
+to assume the python venv.
+- To make tests work, check the `.env` file at the root of the project to find an OpenAI key.
+- If using `playwright` to explore the frontend, you can usually log in with username `a@test.com` and password
+`a`. The app can be accessed at `http://localhost:3000`.
+- You should assume that all Onyx services are running. To verify, you can check the `backend/log` directory to
+make sure we see logs coming out from the relevant service.
+- To connect to the Postgres database, use: `docker exec -it onyx-stack-relational_db-1 psql -U postgres -c "<SQL>"`
+- When making calls to the backend, always go through the frontend. E.g. make a call to `http://localhost:3000/api/persona` not `http://localhost:8080/api/persona`
+- Put ALL db operations under the `backend/onyx/db` / `backend/ee/onyx/db` directories. Don't run queries
+outside of those directories.
+
+## Project Overview
+
+**Onyx** (formerly Danswer) is an open-source Gen-AI and Enterprise Search platform that connects to company documents, apps, and people. It features a modular architecture with both Community Edition (MIT licensed) and Enterprise Edition offerings.
+
+
+### Background Workers (Celery)
+
+Onyx uses Celery for asynchronous task processing with multiple specialized workers:
+
+#### Worker Types
+
+1. **Primary Worker** (`celery_app.py`)
+   - Coordinates core background tasks and system-wide operations
+   - Handles connector management, document sync, pruning, and periodic checks
+   - Runs with 4 threads concurrency
+   - Tasks: connector deletion, vespa sync, pruning, LLM model updates, user file sync
+
+2. **Docfetching Worker** (`docfetching`)
+   - Fetches documents from external data sources (connectors)
+   - Spawns docprocessing tasks for each document batch
+   - Implements watchdog monitoring for stuck connectors
+   - Configurable concurrency (default from env)
+
+3. **Docprocessing Worker** (`docprocessing`)
+   - Processes fetched documents through the indexing pipeline:
+     - Upserts documents to PostgreSQL
+     - Chunks documents and adds contextual information
+     - Embeds chunks via model server
+     - Writes chunks to Vespa vector database
+     - Updates document metadata
+   - Configurable concurrency (default from env)
+
+4. **Light Worker** (`light`)
+   - Handles lightweight, fast operations
+   - Tasks: vespa operations, document permissions sync, external group sync
+   - Higher concurrency for quick tasks
+
+5. **Heavy Worker** (`heavy`)
+   - Handles resource-intensive operations
+   - Primary task: document pruning operations
+   - Runs with 4 threads concurrency
+
+6. **KG Processing Worker** (`kg_processing`)
+   - Handles Knowledge Graph processing and clustering
+   - Builds relationships between documents
+   - Runs clustering algorithms
+   - Configurable concurrency
+
+7. **Monitoring Worker** (`monitoring`)
+   - System health monitoring and metrics collection
+   - Monitors Celery queues, process memory, and system status
+   - Single thread (monitoring doesn't need parallelism)
+   - Cloud-specific monitoring tasks
+
+8. **Beat Worker** (`beat`)
+   - Celery's scheduler for periodic tasks
+   - Uses DynamicTenantScheduler for multi-tenant support
+   - Schedules tasks like:
+     - Indexing checks (every 15 seconds)
+     - Connector deletion checks (every 20 seconds)
+     - Vespa sync checks (every 20 seconds)
+     - Pruning checks (every 20 seconds)
+     - KG processing (every 60 seconds)
+     - Monitoring tasks (every 5 minutes)
+     - Cleanup tasks (hourly)
+
+#### Key Features
+
+- **Thread-based Workers**: All workers use thread pools (not processes) for stability
+- **Tenant Awareness**: Multi-tenant support with per-tenant task isolation. There is a 
+middleware layer that automatically finds the appropriate tenant ID when sending tasks 
+via Celery Beat.
+- **Task Prioritization**: High, Medium, Low priority queues
+- **Monitoring**: Built-in heartbeat and liveness checking
+- **Failure Handling**: Automatic retry and failure recovery mechanisms
+- **Redis Coordination**: Inter-process communication via Redis
+- **PostgreSQL State**: Task state and metadata stored in PostgreSQL
+
+
+#### Important Notes
+
+**Defining Tasks**: 
+- Always use `@shared_task` rather than `@celery_app`
+- Put tasks under `background/celery/tasks/` or `ee/background/celery/tasks`
+
+**Defining APIs**:
+When creating new FastAPI APIs, do NOT use the `response_model` field. Instead, just type the
+function.
+
+**Testing Updates**:
+If you make any updates to a celery worker and you want to test these changes, you will need
+to ask me to restart the celery worker. There is no auto-restart on code-change mechanism.
+
+### Code Quality
+```bash
+# Install and run pre-commit hooks
+pre-commit install
+pre-commit run --all-files
+```
+
+NOTE: Always make sure everything is strictly typed (both in Python and Typescript).
+
+## Architecture Overview
+
+### Technology Stack
+- **Backend**: Python 3.11, FastAPI, SQLAlchemy, Alembic, Celery
+- **Frontend**: Next.js 15+, React 18, TypeScript, Tailwind CSS
+- **Database**: PostgreSQL with Redis caching
+- **Search**: Vespa vector database
+- **Auth**: OAuth2, SAML, multi-provider support
+- **AI/ML**: LangChain, LiteLLM, multiple embedding models
+
+### Directory Structure
+
+```
+backend/
+├── onyx/
+│   ├── auth/                    # Authentication & authorization
+│   ├── chat/                    # Chat functionality & LLM interactions
+│   ├── connectors/              # Data source connectors
+│   ├── db/                      # Database models & operations
+│   ├── document_index/          # Vespa integration
+│   ├── federated_connectors/    # External search connectors
+│   ├── llm/                     # LLM provider integrations
+│   └── server/                  # API endpoints & routers
+├── ee/                          # Enterprise Edition features
+├── alembic/                     # Database migrations
+└── tests/                       # Test suites
+
+web/
+├── src/app/                     # Next.js app router pages
+├── src/components/              # Reusable React components
+└── src/lib/                     # Utilities & business logic
+```
+
+## Database & Migrations
+
+### Running Migrations
+```bash
+# Standard migrations
+alembic upgrade head
+
+# Multi-tenant (Enterprise)
+alembic -n schema_private upgrade head
+```
+
+### Creating Migrations
+```bash
+# Auto-generate migration
+alembic revision --autogenerate -m "description"
+
+# Multi-tenant migration
+alembic -n schema_private revision --autogenerate -m "description"
+```
+
+## Testing Strategy
+
+There are 4 main types of tests within Onyx:
+
+### Unit Tests
+These should not assume any Onyx/external services are available to be called.
+Interactions with the outside world should be mocked using `unittest.mock`. Generally, only 
+write these for complex, isolated modules e.g. `citation_processing.py`.
+
+To run them:
+
+```bash
+python -m dotenv -f .vscode/.env run -- pytest -xv backend/tests/unit
+```
+
+### External Dependency Unit Tests
+These tests assume that all external dependencies of Onyx are available and callable (e.g. Postgres, Redis, 
+MinIO/S3, Vespa are running + OpenAI can be called + any request to the internet is fine + etc.).
+
+However, the actual Onyx containers are not running and with these tests we call the function to test directly.
+We can also mock components/calls at will. 
+
+The goal with these tests are to minimize mocking while giving some flexibility to mock things that are flakey, 
+need strictly controlled behavior, or need to have their internal behavior validated (e.g. verify a function is called
+with certain args, something that would be impossible with proper integration tests).
+
+A great example of this type of test is `backend/tests/external_dependency_unit/connectors/confluence/test_confluence_group_sync.py`.
+
+To run them:
+
+```bash
+python -m dotenv -f .vscode/.env run -- pytest backend/tests/external_dependency_unit
+```
+
+### Integration Tests
+Standard integration tests. Every test in `backend/tests/integration` runs against a real Onyx deployment. We cannot 
+mock anything in these tests. Prefer writing integration tests (or External Dependency Unit Tests if mocking/internal 
+verification is necessary) over any other type of test.
+
+Tests are parallelized at a directory level.
+
+When writing integration tests, make sure to check the root `conftest.py` for useful fixtures + the `backend/tests/integration/common_utils` directory for utilities. Prefer (if one exists), calling the appropriate Manager 
+class in the utils over directly calling the APIs with a library like `requests`. Prefer using fixtures rather than
+calling the utilities directly (e.g. do NOT create admin users with 
+`admin_user = UserManager.create(name="admin_user")`, instead use the `admin_user` fixture).
+
+A great example of this type of test is `backend/tests/integration/dev_apis/test_simple_chat_api.py`.
+
+To run them:
+
+```bash
+python -m dotenv -f .vscode/.env run -- pytest backend/tests/integration
+```
+
+### Playwright (E2E) Tests
+These tests are an even more complete version of the Integration Tests mentioned above. Has all services of Onyx 
+running, *including* the Web Server.
+
+Use these tests for anything that requires significant frontend <-> backend coordination.
+
+Tests are located at `web/tests/e2e`. Tests are written in TypeScript.
+
+To run them:
+
+```bash
+npx playwright test <TEST_NAME>
+```
+
+
+## Logs
+
+When (1) writing integration tests or (2) doing live tests (e.g. curl / playwright) you can get access
+to logs via the `backend/log/<service_name>_debug.log` file. All Onyx services (api_server, web_server, celery_X)
+will be tailing their logs to this file. 
+
+
+## Security Considerations
+
+- Never commit API keys or secrets to repository
+- Use encrypted credential storage for connector credentials
+- Follow RBAC patterns for new features
+- Implement proper input validation with Pydantic models
+- Use parameterized queries to prevent SQL injection
+
+## AI/LLM Integration
+
+- Multiple LLM providers supported via LiteLLM
+- Configurable models per feature (chat, search, embeddings)
+- Streaming support for real-time responses
+- Token management and rate limiting
+- Custom prompts and agent actions
+
+## UI/UX Patterns
+
+- Tailwind CSS with design system in `web/src/components/ui/`
+- Radix UI and Headless UI for accessible components
+- SWR for data fetching and caching
+- Form validation with react-hook-form
+- Error handling with popup notifications
+
+## Creating a Plan
+When creating a plan in the `plans` directory, make sure to include at least these elements:
+
+**Issues to Address**
+What the change is meant to do.
+
+**Important Notes**
+Things you come across in your research that are important to the implementation.
+
+**Implementation strategy**
+How you are going to make the changes happen. High level approach.
+
+**Tests**
+What unit (use rarely), external dependency unit, integration, and playwright tests you plan to write to 
+verify the correct behavior. Don't overtest. Usually, a given change only needs one type of test.
+
+Do NOT include these: *Timeline*, *Rollback plan*
+
+This is a minimal list - feel free to include more. Do NOT write code as part of your plan.
+Keep it high level. You can reference certain files or functions though.
+
+Before writing your plan, make sure to do research. Explore the relevant sections in the codebase.

CONTRIBUTING.md

@@ -103,10 +103,10 @@ If using PowerShell, the command slightly differs:
 Install the required python dependencies:
 
 ```bash
-pip install -r onyx/backend/requirements/default.txt
-pip install -r onyx/backend/requirements/dev.txt
-pip install -r onyx/backend/requirements/ee.txt
-pip install -r onyx/backend/requirements/model_server.txt
+pip install -r backend/requirements/default.txt
+pip install -r backend/requirements/dev.txt
+pip install -r backend/requirements/ee.txt
+pip install -r backend/requirements/model_server.txt
 ```
 
 Install Playwright for Python (headless browser required by the Web Connector)

CONTRIBUTING_VSCODE.md

@@ -5,7 +5,7 @@ This guide explains how to set up and use VSCode's debugging capabilities with t
 ## Initial Setup
 
 1. **Environment Setup**:
-   - Copy `.vscode/.env.template` to `.vscode/.env`
+   - Copy `.vscode/env_template.txt` to `.vscode/.env`
    - Fill in the necessary environment variables in `.vscode/.env`
 2. **launch.json**:
    - Copy `.vscode/launch.template.jsonc` to `.vscode/launch.json`
@@ -17,10 +17,9 @@ Before starting, make sure the Docker Daemon is running.
 1. Open the Debug view in VSCode (Cmd+Shift+D on macOS)
 2. From the dropdown at the top, select "Clear and Restart External Volumes and Containers" and press the green play button
 3. From the dropdown at the top, select "Run All Onyx Services" and press the green play button
-4. CD into web, run "npm i" followed by npm run dev.
-5. Now, you can navigate to onyx in your browser (default is http://localhost:3000) and start using the app
-6. You can set breakpoints by clicking to the left of line numbers to help debug while the app is running
-7. Use the debug toolbar to step through code, inspect variables, etc.
+4. Now, you can navigate to onyx in your browser (default is http://localhost:3000) and start using the app
+5. You can set breakpoints by clicking to the left of line numbers to help debug while the app is running
+6. Use the debug toolbar to step through code, inspect variables, etc.
 
 ## Features
 

README.md

@@ -57,7 +57,7 @@ https://private-user-images.githubusercontent.com/32520769/414509312-48392e83-95
 **To try it out for free and get started in seconds, check out [Onyx Cloud](https://cloud.onyx.app/signup)**.
 
 Onyx can also be run locally (even on a laptop) or deployed on a virtual machine with a single
-`docker compose` command. Checkout our [docs](https://docs.onyx.app/quickstart) to learn more.
+`docker compose` command. Checkout our [docs](https://docs.onyx.app/deployment/getting_started/quickstart) to learn more.
 
 We also have built-in support for high-availability/scalable deployment on Kubernetes.
 References [here](https://github.com/onyx-dot-app/onyx/tree/main/deployment).
@@ -97,7 +97,7 @@ Keep knowledge and access up to sync across 40+ connectors:
 - Websites
 - And more ...
 
-See the full list [here](https://docs.onyx.app/connectors).
+See the full list [here](https://docs.onyx.app/admin/connectors/overview).
 
 
 ## 📚 Licensing
@@ -113,5 +113,4 @@ To try the Onyx Enterprise Edition:
 
 
 ## 💡 Contributing
-Looking to contribute? Please check out the [Contribution Guide](CONTRIBUTING.md) for more details.
-
+Looking to contribute? Please check out the [Contribution Guide](CONTRIBUTING.md) for more details.

backend/Dockerfile

@@ -12,7 +12,8 @@ ARG ONYX_VERSION=0.0.0-dev
 # DO_NOT_TRACK is used to disable telemetry for Unstructured
 ENV ONYX_VERSION=${ONYX_VERSION} \
     DANSWER_RUNNING_IN_DOCKER="true" \
-    DO_NOT_TRACK="true"
+    DO_NOT_TRACK="true" \
+    PLAYWRIGHT_BROWSERS_PATH="/app/.cache/ms-playwright"
 
 
 RUN echo "ONYX_VERSION: ${ONYX_VERSION}"
@@ -116,6 +117,14 @@ COPY ./assets /app/assets
 
 ENV PYTHONPATH=/app
 
+# Create non-root user for security best practices
+RUN groupadd -g 1001 onyx && \
+    useradd -u 1001 -g onyx -m -s /bin/bash onyx && \
+    chown -R onyx:onyx /app && \
+    mkdir -p /var/log/onyx && \
+    chmod 755 /var/log/onyx && \
+    chown onyx:onyx /var/log/onyx
+
 # Default command which does nothing
 # This container is used by api server and background which specify their own CMD
 CMD ["tail", "-f", "/dev/null"]

backend/Dockerfile.model_server

@@ -9,11 +9,36 @@ visit https://github.com/onyx-dot-app/onyx."
 # Default ONYX_VERSION, typically overriden during builds by GitHub Actions.
 ARG ONYX_VERSION=0.0.0-dev
 ENV ONYX_VERSION=${ONYX_VERSION} \
-    DANSWER_RUNNING_IN_DOCKER="true"
-
+    DANSWER_RUNNING_IN_DOCKER="true" \
+    HF_HOME=/app/.cache/huggingface
 
 RUN echo "ONYX_VERSION: ${ONYX_VERSION}"
 
+# Create non-root user for security best practices
+RUN mkdir -p /app && \
+    groupadd -g 1001 onyx && \
+    useradd -u 1001 -g onyx -m -s /bin/bash onyx  && \
+    chown -R onyx:onyx /app && \
+    mkdir -p /var/log/onyx && \
+    chmod 755 /var/log/onyx && \
+    chown onyx:onyx /var/log/onyx
+
+# --- add toolchain needed for Rust/Python builds (fastuuid) ---
+ENV RUSTUP_HOME=/usr/local/rustup \
+    CARGO_HOME=/usr/local/cargo \
+    PATH=/usr/local/cargo/bin:$PATH
+
+RUN set -eux; \
+    apt-get update && apt-get install -y --no-install-recommends \
+        build-essential \
+        pkg-config \
+        curl \
+        ca-certificates \
+    && rm -rf /var/lib/apt/lists/* \
+    # Install latest stable Rust (supports Cargo.lock v4)
+    && curl -sSf https://sh.rustup.rs | sh -s -- -y --profile minimal --default-toolchain stable \
+    && rustc --version && cargo --version
+
 COPY ./requirements/model_server.txt /tmp/requirements.txt
 RUN pip install --no-cache-dir --upgrade \
         --retries 5 \
@@ -38,9 +63,11 @@ snapshot_download('mixedbread-ai/mxbai-rerank-xsmall-v1'); \
 from sentence_transformers import SentenceTransformer; \
 SentenceTransformer(model_name_or_path='nomic-ai/nomic-embed-text-v1', trust_remote_code=True);"
 
-# In case the user has volumes mounted to /root/.cache/huggingface that they've downloaded while
-# running Onyx, don't overwrite it with the built in cache folder
-RUN mv /root/.cache/huggingface /root/.cache/temp_huggingface
+# In case the user has volumes mounted to /app/.cache/huggingface that they've downloaded while
+# running Onyx, move the current contents of the cache folder to a temporary location to ensure 
+# it's preserved in order to combine with the user's cache contents
+RUN mv /app/.cache/huggingface /app/.cache/temp_huggingface && \
+    chown -R onyx:onyx /app
 
 WORKDIR /app
 

backend/alembic/versions/3fc5d75723b3_add_doc_metadata_field_in_document_model.py

@@ -0,0 +1,30 @@
+"""add_doc_metadata_field_in_document_model
+
+Revision ID: 3fc5d75723b3
+Revises: 2f95e36923e6
+Create Date: 2025-07-28 18:45:37.985406
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision = "3fc5d75723b3"
+down_revision = "2f95e36923e6"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.add_column(
+        "document",
+        sa.Column(
+            "doc_metadata", postgresql.JSONB(astext_type=sa.Text()), nullable=True
+        ),
+    )
+
+
+def downgrade() -> None:
+    op.drop_column("document", "doc_metadata")

backend/alembic/versions/505c488f6662_merge_default_assistants_into_unified.py

@@ -0,0 +1,380 @@
+"""merge_default_assistants_into_unified
+
+Revision ID: 505c488f6662
+Revises: d09fc20a3c66
+Create Date: 2025-09-09 19:00:56.816626
+
+"""
+
+import json
+from typing import Any
+from typing import NamedTuple
+from uuid import UUID
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "505c488f6662"
+down_revision = "d09fc20a3c66"
+branch_labels = None
+depends_on = None
+
+# Constants for the unified assistant
+UNIFIED_ASSISTANT_NAME = "Assistant"
+UNIFIED_ASSISTANT_DESCRIPTION = (
+    "Your AI assistant with search, web browsing, and image generation capabilities."
+)
+UNIFIED_ASSISTANT_NUM_CHUNKS = 25
+UNIFIED_ASSISTANT_DISPLAY_PRIORITY = 0
+UNIFIED_ASSISTANT_LLM_FILTER_EXTRACTION = True
+UNIFIED_ASSISTANT_LLM_RELEVANCE_FILTER = False
+UNIFIED_ASSISTANT_RECENCY_BIAS = "AUTO"  # NOTE: needs to be capitalized
+UNIFIED_ASSISTANT_CHUNKS_ABOVE = 0
+UNIFIED_ASSISTANT_CHUNKS_BELOW = 0
+UNIFIED_ASSISTANT_DATETIME_AWARE = True
+
+# NOTE: tool specific prompts are handled on the fly and automatically injected
+# into the prompt before passing to the LLM.
+DEFAULT_SYSTEM_PROMPT = """
+You are a highly capable, thoughtful, and precise assistant. Your goal is to deeply understand the \
+user's intent, ask clarifying questions when needed, think step-by-step through complex problems, \
+provide clear and accurate answers, and proactively anticipate helpful follow-up information. Always \
+prioritize being truthful, nuanced, insightful, and efficient.
+The current date is [[CURRENT_DATETIME]]
+
+You use different text styles, bolding, emojis (sparingly), block quotes, and other formatting to make \
+your responses more readable and engaging.
+You use proper Markdown and LaTeX to format your responses for math, scientific, and chemical formulas, \
+symbols, etc.: '$$\\n[expression]\\n$$' for standalone cases and '\\( [expression] \\)' when inline.
+For code you prefer to use Markdown and specify the language.
+You can use Markdown horizontal rules (---) to separate sections of your responses.
+You can use Markdown tables to format your responses for data, lists, and other structured information.
+""".strip()
+
+
+INSERT_DICT: dict[str, Any] = {
+    "name": UNIFIED_ASSISTANT_NAME,
+    "description": UNIFIED_ASSISTANT_DESCRIPTION,
+    "system_prompt": DEFAULT_SYSTEM_PROMPT,
+    "num_chunks": UNIFIED_ASSISTANT_NUM_CHUNKS,
+    "display_priority": UNIFIED_ASSISTANT_DISPLAY_PRIORITY,
+    "llm_filter_extraction": UNIFIED_ASSISTANT_LLM_FILTER_EXTRACTION,
+    "llm_relevance_filter": UNIFIED_ASSISTANT_LLM_RELEVANCE_FILTER,
+    "recency_bias": UNIFIED_ASSISTANT_RECENCY_BIAS,
+    "chunks_above": UNIFIED_ASSISTANT_CHUNKS_ABOVE,
+    "chunks_below": UNIFIED_ASSISTANT_CHUNKS_BELOW,
+    "datetime_aware": UNIFIED_ASSISTANT_DATETIME_AWARE,
+}
+
+GENERAL_ASSISTANT_ID = -1
+ART_ASSISTANT_ID = -3
+
+
+class UserRow(NamedTuple):
+    """Typed representation of user row from database query."""
+
+    id: UUID
+    chosen_assistants: list[int] | None
+    visible_assistants: list[int] | None
+    hidden_assistants: list[int] | None
+    pinned_assistants: list[int] | None
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+
+    # Start transaction
+    conn.execute(sa.text("BEGIN"))
+
+    try:
+        # Step 1: Create or update the unified assistant (ID 0)
+        search_assistant = conn.execute(
+            sa.text("SELECT * FROM persona WHERE id = 0")
+        ).fetchone()
+
+        if search_assistant:
+            # Update existing Search assistant to be the unified assistant
+            conn.execute(
+                sa.text(
+                    """
+                    UPDATE persona
+                    SET name = :name,
+                        description = :description,
+                        system_prompt = :system_prompt,
+                        num_chunks = :num_chunks,
+                        is_default_persona = true,
+                        is_visible = true,
+                        deleted = false,
+                        display_priority = :display_priority,
+                        llm_filter_extraction = :llm_filter_extraction,
+                        llm_relevance_filter = :llm_relevance_filter,
+                        recency_bias = :recency_bias,
+                        chunks_above = :chunks_above,
+                        chunks_below = :chunks_below,
+                        datetime_aware = :datetime_aware,
+                        starter_messages = null
+                    WHERE id = 0
+                """
+                ),
+                INSERT_DICT,
+            )
+        else:
+            # Create new unified assistant with ID 0
+            conn.execute(
+                sa.text(
+                    """
+                    INSERT INTO persona (
+                        id, name, description, system_prompt, num_chunks,
+                        is_default_persona, is_visible, deleted, display_priority,
+                        llm_filter_extraction, llm_relevance_filter, recency_bias,
+                        chunks_above, chunks_below, datetime_aware, starter_messages,
+                        builtin_persona
+                    ) VALUES (
+                        0, :name, :description, :system_prompt, :num_chunks,
+                        true, true, false, :display_priority, :llm_filter_extraction,
+                        :llm_relevance_filter, :recency_bias, :chunks_above, :chunks_below,
+                        :datetime_aware, null, true
+                    )
+                """
+                ),
+                INSERT_DICT,
+            )
+
+        # Step 2: Mark ALL builtin assistants as deleted (except the unified assistant ID 0)
+        conn.execute(
+            sa.text(
+                """
+                UPDATE persona
+                SET deleted = true, is_visible = false, is_default_persona = false
+                WHERE builtin_persona = true AND id != 0
+            """
+            )
+        )
+
+        # Step 3: Add all built-in tools to the unified assistant
+        # First, get the tool IDs for SearchTool, ImageGenerationTool, and WebSearchTool
+        search_tool = conn.execute(
+            sa.text("SELECT id FROM tool WHERE in_code_tool_id = 'SearchTool'")
+        ).fetchone()
+
+        if not search_tool:
+            raise ValueError(
+                "SearchTool not found in database. Ensure tools migration has run first."
+            )
+
+        image_gen_tool = conn.execute(
+            sa.text("SELECT id FROM tool WHERE in_code_tool_id = 'ImageGenerationTool'")
+        ).fetchone()
+
+        if not image_gen_tool:
+            raise ValueError(
+                "ImageGenerationTool not found in database. Ensure tools migration has run first."
+            )
+
+        # WebSearchTool is optional - may not be configured
+        web_search_tool = conn.execute(
+            sa.text("SELECT id FROM tool WHERE in_code_tool_id = 'WebSearchTool'")
+        ).fetchone()
+
+        # Clear existing tool associations for persona 0
+        conn.execute(sa.text("DELETE FROM persona__tool WHERE persona_id = 0"))
+
+        # Add tools to the unified assistant
+        conn.execute(
+            sa.text(
+                """
+                INSERT INTO persona__tool (persona_id, tool_id)
+                VALUES (0, :tool_id)
+                ON CONFLICT DO NOTHING
+            """
+            ),
+            {"tool_id": search_tool[0]},
+        )
+
+        conn.execute(
+            sa.text(
+                """
+                INSERT INTO persona__tool (persona_id, tool_id)
+                VALUES (0, :tool_id)
+                ON CONFLICT DO NOTHING
+            """
+            ),
+            {"tool_id": image_gen_tool[0]},
+        )
+
+        if web_search_tool:
+            conn.execute(
+                sa.text(
+                    """
+                    INSERT INTO persona__tool (persona_id, tool_id)
+                    VALUES (0, :tool_id)
+                    ON CONFLICT DO NOTHING
+                """
+                ),
+                {"tool_id": web_search_tool[0]},
+            )
+
+        # Step 4: Migrate existing chat sessions from all builtin assistants to unified assistant
+        conn.execute(
+            sa.text(
+                """
+                UPDATE chat_session
+                SET persona_id = 0
+                WHERE persona_id IN (
+                    SELECT id FROM persona WHERE builtin_persona = true AND id != 0
+                )
+            """
+            )
+        )
+
+        # Step 5: Migrate user preferences - remove references to all builtin assistants
+        # First, get all builtin assistant IDs (except 0)
+        builtin_assistants_result = conn.execute(
+            sa.text(
+                """
+                SELECT id FROM persona
+                WHERE builtin_persona = true AND id != 0
+            """
+            )
+        ).fetchall()
+        builtin_assistant_ids = [row[0] for row in builtin_assistants_result]
+
+        # Get all users with preferences
+        users_result = conn.execute(
+            sa.text(
+                """
+                SELECT id, chosen_assistants, visible_assistants,
+                       hidden_assistants, pinned_assistants
+                FROM "user"
+            """
+            )
+        ).fetchall()
+
+        for user_row in users_result:
+            user = UserRow(*user_row)
+            user_id: UUID = user.id
+            updates: dict[str, Any] = {}
+
+            # Remove all builtin assistants from chosen_assistants
+            if user.chosen_assistants:
+                new_chosen: list[int] = [
+                    assistant_id
+                    for assistant_id in user.chosen_assistants
+                    if assistant_id not in builtin_assistant_ids
+                ]
+                if new_chosen != user.chosen_assistants:
+                    updates["chosen_assistants"] = json.dumps(new_chosen)
+
+            # Remove all builtin assistants from visible_assistants
+            if user.visible_assistants:
+                new_visible: list[int] = [
+                    assistant_id
+                    for assistant_id in user.visible_assistants
+                    if assistant_id not in builtin_assistant_ids
+                ]
+                if new_visible != user.visible_assistants:
+                    updates["visible_assistants"] = json.dumps(new_visible)
+
+            # Add all builtin assistants to hidden_assistants
+            if user.hidden_assistants:
+                new_hidden: list[int] = list(user.hidden_assistants)
+                for old_id in builtin_assistant_ids:
+                    if old_id not in new_hidden:
+                        new_hidden.append(old_id)
+                if new_hidden != user.hidden_assistants:
+                    updates["hidden_assistants"] = json.dumps(new_hidden)
+            else:
+                updates["hidden_assistants"] = json.dumps(builtin_assistant_ids)
+
+            # Remove all builtin assistants from pinned_assistants
+            if user.pinned_assistants:
+                new_pinned: list[int] = [
+                    assistant_id
+                    for assistant_id in user.pinned_assistants
+                    if assistant_id not in builtin_assistant_ids
+                ]
+                if new_pinned != user.pinned_assistants:
+                    updates["pinned_assistants"] = json.dumps(new_pinned)
+
+            # Apply updates if any
+            if updates:
+                set_clause = ", ".join([f"{k} = :{k}" for k in updates.keys()])
+                updates["user_id"] = str(user_id)  # Convert UUID to string for SQL
+                conn.execute(
+                    sa.text(f'UPDATE "user" SET {set_clause} WHERE id = :user_id'),
+                    updates,
+                )
+
+        # Commit transaction
+        conn.execute(sa.text("COMMIT"))
+
+    except Exception as e:
+        # Rollback on error
+        conn.execute(sa.text("ROLLBACK"))
+        raise e
+
+
+def downgrade() -> None:
+    conn = op.get_bind()
+
+    # Start transaction
+    conn.execute(sa.text("BEGIN"))
+
+    try:
+        # Only restore General (ID -1) and Art (ID -3) assistants
+        # Step 1: Keep Search assistant (ID 0) as default but restore original state
+        conn.execute(
+            sa.text(
+                """
+                UPDATE persona
+                SET is_default_persona = true,
+                    is_visible = true,
+                    deleted = false
+                WHERE id = 0
+            """
+            )
+        )
+
+        # Step 2: Restore General assistant (ID -1)
+        conn.execute(
+            sa.text(
+                """
+                UPDATE persona
+                SET deleted = false,
+                    is_visible = true,
+                    is_default_persona = true
+                WHERE id = :general_assistant_id
+            """
+            ),
+            {"general_assistant_id": GENERAL_ASSISTANT_ID},
+        )
+
+        # Step 3: Restore Art assistant (ID -3)
+        conn.execute(
+            sa.text(
+                """
+                UPDATE persona
+                SET deleted = false,
+                    is_visible = true,
+                    is_default_persona = true
+                WHERE id = :art_assistant_id
+            """
+            ),
+            {"art_assistant_id": ART_ASSISTANT_ID},
+        )
+
+        # Note: We don't restore the original tool associations, names, or descriptions
+        # as those would require more complex logic to determine original state.
+        # We also cannot restore original chat session persona_ids as we don't
+        # have the original mappings.
+        # Other builtin assistants remain deleted as per the requirement.
+
+        # Commit transaction
+        conn.execute(sa.text("COMMIT"))
+
+    except Exception as e:
+        # Rollback on error
+        conn.execute(sa.text("ROLLBACK"))
+        raise e

backend/alembic/versions/5ae8240accb3_add_research_agent_database_tables_and_.py

@@ -0,0 +1,115 @@
+"""add research agent database tables and chat message research fields
+
+Revision ID: 5ae8240accb3
+Revises: b558f51620b4
+Create Date: 2025-08-06 14:29:24.691388
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+from sqlalchemy.dialects import postgresql
+
+
+# revision identifiers, used by Alembic.
+revision = "5ae8240accb3"
+down_revision = "b558f51620b4"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # Add research_type and research_plan columns to chat_message table
+    op.add_column(
+        "chat_message",
+        sa.Column("research_type", sa.String(), nullable=True),
+    )
+    op.add_column(
+        "chat_message",
+        sa.Column("research_plan", postgresql.JSONB(), nullable=True),
+    )
+
+    # Create research_agent_iteration table
+    op.create_table(
+        "research_agent_iteration",
+        sa.Column("id", sa.Integer(), autoincrement=True, nullable=False),
+        sa.Column(
+            "primary_question_id",
+            sa.Integer(),
+            sa.ForeignKey("chat_message.id", ondelete="CASCADE"),
+            nullable=False,
+        ),
+        sa.Column("iteration_nr", sa.Integer(), nullable=False),
+        sa.Column(
+            "created_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.func.now(),
+            nullable=False,
+        ),
+        sa.Column("purpose", sa.String(), nullable=True),
+        sa.Column("reasoning", sa.String(), nullable=True),
+        sa.PrimaryKeyConstraint("id"),
+        sa.UniqueConstraint(
+            "primary_question_id",
+            "iteration_nr",
+            name="_research_agent_iteration_unique_constraint",
+        ),
+    )
+
+    # Create research_agent_iteration_sub_step table
+    op.create_table(
+        "research_agent_iteration_sub_step",
+        sa.Column("id", sa.Integer(), autoincrement=True, nullable=False),
+        sa.Column(
+            "primary_question_id",
+            sa.Integer(),
+            sa.ForeignKey("chat_message.id", ondelete="CASCADE"),
+            nullable=False,
+        ),
+        sa.Column(
+            "parent_question_id",
+            sa.Integer(),
+            sa.ForeignKey("research_agent_iteration_sub_step.id", ondelete="CASCADE"),
+            nullable=True,
+        ),
+        sa.Column("iteration_nr", sa.Integer(), nullable=False),
+        sa.Column("iteration_sub_step_nr", sa.Integer(), nullable=False),
+        sa.Column(
+            "created_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.func.now(),
+            nullable=False,
+        ),
+        sa.Column("sub_step_instructions", sa.String(), nullable=True),
+        sa.Column(
+            "sub_step_tool_id",
+            sa.Integer(),
+            sa.ForeignKey("tool.id"),
+            nullable=True,
+        ),
+        sa.Column("reasoning", sa.String(), nullable=True),
+        sa.Column("sub_answer", sa.String(), nullable=True),
+        sa.Column("cited_doc_results", postgresql.JSONB(), nullable=True),
+        sa.Column("claims", postgresql.JSONB(), nullable=True),
+        sa.Column("generated_images", postgresql.JSONB(), nullable=True),
+        sa.Column("additional_data", postgresql.JSONB(), nullable=True),
+        sa.PrimaryKeyConstraint("id"),
+        sa.ForeignKeyConstraint(
+            ["primary_question_id", "iteration_nr"],
+            [
+                "research_agent_iteration.primary_question_id",
+                "research_agent_iteration.iteration_nr",
+            ],
+            ondelete="CASCADE",
+        ),
+    )
+
+
+def downgrade() -> None:
+    # Drop tables in reverse order
+    op.drop_table("research_agent_iteration_sub_step")
+    op.drop_table("research_agent_iteration")
+
+    # Remove columns from chat_message table
+    op.drop_column("chat_message", "research_plan")
+    op.drop_column("chat_message", "research_type")

backend/alembic/versions/62c3a055a141_add_file_names_to_file_connector_config.py

@@ -0,0 +1,132 @@
+"""add file names to file connector config
+
+Revision ID: 62c3a055a141
+Revises: 3fc5d75723b3
+Create Date: 2025-07-30 17:01:24.417551
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+import json
+import os
+import logging
+
+
+# revision identifiers, used by Alembic.
+revision = "62c3a055a141"
+down_revision = "3fc5d75723b3"
+branch_labels = None
+depends_on = None
+
+SKIP_FILE_NAME_MIGRATION = (
+    os.environ.get("SKIP_FILE_NAME_MIGRATION", "true").lower() == "true"
+)
+
+logger = logging.getLogger("alembic.runtime.migration")
+
+
+def upgrade() -> None:
+    if SKIP_FILE_NAME_MIGRATION:
+        logger.info(
+            "Skipping file name migration. Hint: set SKIP_FILE_NAME_MIGRATION=false to run this migration"
+        )
+        return
+    logger.info("Running file name migration")
+    # Get connection
+    conn = op.get_bind()
+
+    # Get all FILE connectors with their configs
+    file_connectors = conn.execute(
+        sa.text(
+            """
+            SELECT id, connector_specific_config
+            FROM connector
+            WHERE source = 'FILE'
+        """
+        )
+    ).fetchall()
+
+    for connector_id, config in file_connectors:
+        # Parse config if it's a string
+        if isinstance(config, str):
+            config = json.loads(config)
+
+        # Get file_locations list
+        file_locations = config.get("file_locations", [])
+
+        # Get display names for each file_id
+        file_names = []
+        for file_id in file_locations:
+            result = conn.execute(
+                sa.text(
+                    """
+                    SELECT display_name
+                    FROM file_record
+                    WHERE file_id = :file_id
+                """
+                ),
+                {"file_id": file_id},
+            ).fetchone()
+
+            if result:
+                file_names.append(result[0])
+            else:
+                file_names.append(file_id)  # Should not happen
+
+        # Add file_names to config
+        new_config = dict(config)
+        new_config["file_names"] = file_names
+
+        # Update the connector
+        conn.execute(
+            sa.text(
+                """
+                UPDATE connector
+                SET connector_specific_config = :new_config
+                WHERE id = :connector_id
+            """
+            ),
+            {"connector_id": connector_id, "new_config": json.dumps(new_config)},
+        )
+
+
+def downgrade() -> None:
+    # Get connection
+    conn = op.get_bind()
+
+    # Remove file_names from all FILE connectors
+    file_connectors = conn.execute(
+        sa.text(
+            """
+            SELECT id, connector_specific_config
+            FROM connector
+            WHERE source = 'FILE'
+        """
+        )
+    ).fetchall()
+
+    for connector_id, config in file_connectors:
+        # Parse config if it's a string
+        if isinstance(config, str):
+            config = json.loads(config)
+
+        # Remove file_names if it exists
+        if "file_names" in config:
+            new_config = dict(config)
+            del new_config["file_names"]
+
+            # Update the connector
+            conn.execute(
+                sa.text(
+                    """
+                    UPDATE connector
+                    SET connector_specific_config = :new_config
+                    WHERE id = :connector_id
+                """
+                ),
+                {
+                    "connector_id": connector_id,
+                    "new_config": json.dumps(new_config),
+                },
+            )

backend/alembic/versions/7ed603b64d5a_add_mcp_server_and_connection_config_.py

@@ -0,0 +1,249 @@
+"""add_mcp_server_and_connection_config_models
+
+Revision ID: 7ed603b64d5a
+Revises: b329d00a9ea6
+Create Date: 2025-07-28 17:35:59.900680
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+from sqlalchemy.dialects import postgresql
+from onyx.db.enums import MCPAuthenticationType
+
+# revision identifiers, used by Alembic.
+revision = "7ed603b64d5a"
+down_revision = "b329d00a9ea6"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    """Create tables and columns for MCP Server support"""
+
+    # 1. MCP Server main table (no FK constraints yet to avoid circular refs)
+    op.create_table(
+        "mcp_server",
+        sa.Column("id", sa.Integer(), primary_key=True),
+        sa.Column("owner", sa.String(), nullable=False),
+        sa.Column("name", sa.String(), nullable=False),
+        sa.Column("description", sa.String(), nullable=True),
+        sa.Column("server_url", sa.String(), nullable=False),
+        sa.Column(
+            "auth_type",
+            sa.Enum(
+                MCPAuthenticationType,
+                name="mcp_authentication_type",
+                native_enum=False,
+            ),
+            nullable=False,
+        ),
+        sa.Column("admin_connection_config_id", sa.Integer(), nullable=True),
+        sa.Column(
+            "created_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.text("now()"),  # type: ignore
+            nullable=False,
+        ),
+        sa.Column(
+            "updated_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.text("now()"),  # type: ignore
+            nullable=False,
+        ),
+    )
+
+    # 2. MCP Connection Config table (can reference mcp_server now that it exists)
+    op.create_table(
+        "mcp_connection_config",
+        sa.Column("id", sa.Integer(), primary_key=True),
+        sa.Column("mcp_server_id", sa.Integer(), nullable=True),
+        sa.Column("user_email", sa.String(), nullable=False, default=""),
+        sa.Column("config", sa.LargeBinary(), nullable=False),
+        sa.Column(
+            "created_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.text("now()"),  # type: ignore
+            nullable=False,
+        ),
+        sa.Column(
+            "updated_at",
+            sa.DateTime(timezone=True),
+            server_default=sa.text("now()"),  # type: ignore
+            nullable=False,
+        ),
+        sa.ForeignKeyConstraint(
+            ["mcp_server_id"], ["mcp_server.id"], ondelete="CASCADE"
+        ),
+    )
+
+    # Helpful indexes
+    op.create_index(
+        "ix_mcp_connection_config_server_user",
+        "mcp_connection_config",
+        ["mcp_server_id", "user_email"],
+    )
+    op.create_index(
+        "ix_mcp_connection_config_user_email",
+        "mcp_connection_config",
+        ["user_email"],
+    )
+
+    # 3. Add the back-references from mcp_server to connection configs
+    op.create_foreign_key(
+        "mcp_server_admin_config_fk",
+        "mcp_server",
+        "mcp_connection_config",
+        ["admin_connection_config_id"],
+        ["id"],
+        ondelete="SET NULL",
+    )
+
+    # 4. Association / access-control tables
+    op.create_table(
+        "mcp_server__user",
+        sa.Column("mcp_server_id", sa.Integer(), primary_key=True),
+        sa.Column("user_id", sa.UUID(), primary_key=True),
+        sa.ForeignKeyConstraint(
+            ["mcp_server_id"], ["mcp_server.id"], ondelete="CASCADE"
+        ),
+        sa.ForeignKeyConstraint(["user_id"], ["user.id"], ondelete="CASCADE"),
+    )
+
+    op.create_table(
+        "mcp_server__user_group",
+        sa.Column("mcp_server_id", sa.Integer(), primary_key=True),
+        sa.Column("user_group_id", sa.Integer(), primary_key=True),
+        sa.ForeignKeyConstraint(
+            ["mcp_server_id"], ["mcp_server.id"], ondelete="CASCADE"
+        ),
+        sa.ForeignKeyConstraint(["user_group_id"], ["user_group.id"]),
+    )
+
+    # 5. Update existing `tool` table – allow tools to belong to an MCP server
+    op.add_column(
+        "tool",
+        sa.Column("mcp_server_id", sa.Integer(), nullable=True),
+    )
+    # Add column for MCP tool input schema
+    op.add_column(
+        "tool",
+        sa.Column("mcp_input_schema", postgresql.JSONB(), nullable=True),
+    )
+    op.create_foreign_key(
+        "tool_mcp_server_fk",
+        "tool",
+        "mcp_server",
+        ["mcp_server_id"],
+        ["id"],
+        ondelete="CASCADE",
+    )
+
+    # 6. Update persona__tool foreign keys to cascade delete
+    # This ensures that when a tool is deleted (including via MCP server deletion),
+    # the corresponding persona__tool rows are also deleted
+    op.drop_constraint(
+        "persona__tool_tool_id_fkey", "persona__tool", type_="foreignkey"
+    )
+    op.drop_constraint(
+        "persona__tool_persona_id_fkey", "persona__tool", type_="foreignkey"
+    )
+
+    op.create_foreign_key(
+        "persona__tool_persona_id_fkey",
+        "persona__tool",
+        "persona",
+        ["persona_id"],
+        ["id"],
+        ondelete="CASCADE",
+    )
+    op.create_foreign_key(
+        "persona__tool_tool_id_fkey",
+        "persona__tool",
+        "tool",
+        ["tool_id"],
+        ["id"],
+        ondelete="CASCADE",
+    )
+
+    # 7. Update research_agent_iteration_sub_step foreign key to SET NULL on delete
+    # This ensures that when a tool is deleted, the sub_step_tool_id is set to NULL
+    # instead of causing a foreign key constraint violation
+    op.drop_constraint(
+        "research_agent_iteration_sub_step_sub_step_tool_id_fkey",
+        "research_agent_iteration_sub_step",
+        type_="foreignkey",
+    )
+    op.create_foreign_key(
+        "research_agent_iteration_sub_step_sub_step_tool_id_fkey",
+        "research_agent_iteration_sub_step",
+        "tool",
+        ["sub_step_tool_id"],
+        ["id"],
+        ondelete="SET NULL",
+    )
+
+
+def downgrade() -> None:
+    """Drop all MCP-related tables / columns"""
+
+    # # # 1. Drop FK & columns from tool
+    # op.drop_constraint("tool_mcp_server_fk", "tool", type_="foreignkey")
+    op.execute("DELETE FROM tool WHERE mcp_server_id IS NOT NULL")
+
+    op.drop_constraint(
+        "research_agent_iteration_sub_step_sub_step_tool_id_fkey",
+        "research_agent_iteration_sub_step",
+        type_="foreignkey",
+    )
+    op.create_foreign_key(
+        "research_agent_iteration_sub_step_sub_step_tool_id_fkey",
+        "research_agent_iteration_sub_step",
+        "tool",
+        ["sub_step_tool_id"],
+        ["id"],
+    )
+
+    # Restore original persona__tool foreign keys (without CASCADE)
+    op.drop_constraint(
+        "persona__tool_persona_id_fkey", "persona__tool", type_="foreignkey"
+    )
+    op.drop_constraint(
+        "persona__tool_tool_id_fkey", "persona__tool", type_="foreignkey"
+    )
+
+    op.create_foreign_key(
+        "persona__tool_persona_id_fkey",
+        "persona__tool",
+        "persona",
+        ["persona_id"],
+        ["id"],
+    )
+    op.create_foreign_key(
+        "persona__tool_tool_id_fkey",
+        "persona__tool",
+        "tool",
+        ["tool_id"],
+        ["id"],
+    )
+    op.drop_column("tool", "mcp_input_schema")
+    op.drop_column("tool", "mcp_server_id")
+
+    # 2. Drop association tables
+    op.drop_table("mcp_server__user_group")
+    op.drop_table("mcp_server__user")
+
+    # 3. Drop FK from mcp_server to connection configs
+    op.drop_constraint("mcp_server_admin_config_fk", "mcp_server", type_="foreignkey")
+
+    # 4. Drop connection config indexes & table
+    op.drop_index(
+        "ix_mcp_connection_config_user_email", table_name="mcp_connection_config"
+    )
+    op.drop_index(
+        "ix_mcp_connection_config_server_user", table_name="mcp_connection_config"
+    )
+    op.drop_table("mcp_connection_config")
+
+    # 5. Finally drop mcp_server table
+    op.drop_table("mcp_server")

backend/alembic/versions/8818cf73fa1a_drop_include_citations.py

@@ -0,0 +1,38 @@
+"""drop include citations
+
+Revision ID: 8818cf73fa1a
+Revises: 7ed603b64d5a
+Create Date: 2025-09-02 19:43:50.060680
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+# revision identifiers, used by Alembic.
+revision = "8818cf73fa1a"
+down_revision = "7ed603b64d5a"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.drop_column("prompt", "include_citations")
+
+
+def downgrade() -> None:
+    op.add_column(
+        "prompt",
+        sa.Column(
+            "include_citations",
+            sa.BOOLEAN(),
+            autoincrement=False,
+            nullable=True,
+        ),
+    )
+    # Set include_citations based on prompt name: FALSE for ImageGeneration, TRUE for others
+    op.execute(
+        sa.text(
+            "UPDATE prompt SET include_citations = CASE WHEN name = 'ImageGeneration' THEN FALSE ELSE TRUE END"
+        )
+    )

backend/alembic/versions/90e3b9af7da4_tag_fix.py

@@ -0,0 +1,341 @@
+"""tag-fix
+
+Revision ID: 90e3b9af7da4
+Revises: 62c3a055a141
+Create Date: 2025-08-01 20:58:14.607624
+
+"""
+
+import json
+import logging
+import os
+
+from typing import cast
+from typing import Generator
+
+from alembic import op
+import sqlalchemy as sa
+
+from onyx.document_index.factory import get_default_document_index
+from onyx.document_index.vespa_constants import DOCUMENT_ID_ENDPOINT
+from onyx.db.search_settings import SearchSettings
+from onyx.configs.app_configs import AUTH_TYPE
+from onyx.configs.constants import AuthType
+from onyx.document_index.vespa.shared_utils.utils import get_vespa_http_client
+
+logger = logging.getLogger("alembic.runtime.migration")
+
+
+# revision identifiers, used by Alembic.
+revision = "90e3b9af7da4"
+down_revision = "62c3a055a141"
+branch_labels = None
+depends_on = None
+
+SKIP_TAG_FIX = os.environ.get("SKIP_TAG_FIX", "true").lower() == "true"
+
+# override for cloud
+if AUTH_TYPE == AuthType.CLOUD:
+    SKIP_TAG_FIX = True
+
+
+def set_is_list_for_known_tags() -> None:
+    """
+    Sets is_list to true for all tags that are known to be lists.
+    """
+    LIST_METADATA: list[tuple[str, str]] = [
+        ("CLICKUP", "tags"),
+        ("CONFLUENCE", "labels"),
+        ("DISCOURSE", "tags"),
+        ("FRESHDESK", "emails"),
+        ("GITHUB", "assignees"),
+        ("GITHUB", "labels"),
+        ("GURU", "tags"),
+        ("GURU", "folders"),
+        ("HUBSPOT", "associated_contact_ids"),
+        ("HUBSPOT", "associated_company_ids"),
+        ("HUBSPOT", "associated_deal_ids"),
+        ("HUBSPOT", "associated_ticket_ids"),
+        ("JIRA", "labels"),
+        ("MEDIAWIKI", "categories"),
+        ("ZENDESK", "labels"),
+        ("ZENDESK", "content_tags"),
+    ]
+
+    bind = op.get_bind()
+    for source, key in LIST_METADATA:
+        bind.execute(
+            sa.text(
+                f"""
+                UPDATE tag
+                SET is_list = true
+                WHERE tag_key = '{key}'
+                AND source = '{source}'
+                """
+            )
+        )
+
+
+def set_is_list_for_list_tags() -> None:
+    """
+    Sets is_list to true for all tags which have multiple values for a given
+    document, key, and source triplet. This only works if we remove old tags
+    from the database.
+    """
+    bind = op.get_bind()
+    bind.execute(
+        sa.text(
+            """
+            UPDATE tag
+            SET is_list = true
+            FROM (
+                SELECT DISTINCT tag.tag_key, tag.source
+                FROM tag
+                JOIN document__tag ON tag.id = document__tag.tag_id
+                GROUP BY tag.tag_key, tag.source, document__tag.document_id
+                HAVING count(*) > 1
+            ) AS list_tags
+            WHERE tag.tag_key = list_tags.tag_key
+            AND tag.source = list_tags.source
+            """
+        )
+    )
+
+
+def log_list_tags() -> None:
+    bind = op.get_bind()
+    result = bind.execute(
+        sa.text(
+            """
+            SELECT DISTINCT source, tag_key
+            FROM tag
+            WHERE is_list
+            ORDER BY source, tag_key
+            """
+        )
+    ).fetchall()
+    logger.info(
+        "List tags:\n" + "\n".join(f"  {source}: {key}" for source, key in result)
+    )
+
+
+def remove_old_tags() -> None:
+    """
+    Removes old tags from the database.
+    Previously, there was a bug where if a document got indexed with a tag and then
+    the document got reindexed, the old tag would not be removed.
+    This function removes those old tags by comparing it against the tags in vespa.
+    """
+    current_search_settings, future_search_settings = active_search_settings()
+    document_index = get_default_document_index(
+        current_search_settings, future_search_settings
+    )
+
+    # Get the index name
+    if hasattr(document_index, "index_name"):
+        index_name = document_index.index_name
+    else:
+        # Default index name if we can't get it from the document_index
+        index_name = "danswer_index"
+
+    for batch in _get_batch_documents_with_multiple_tags():
+        n_deleted = 0
+
+        for document_id in batch:
+            true_metadata = _get_vespa_metadata(document_id, index_name)
+            tags = _get_document_tags(document_id)
+
+            # identify document__tags to delete
+            to_delete: list[str] = []
+            for tag_id, tag_key, tag_value in tags:
+                true_val = true_metadata.get(tag_key, "")
+                if (isinstance(true_val, list) and tag_value not in true_val) or (
+                    isinstance(true_val, str) and tag_value != true_val
+                ):
+                    to_delete.append(str(tag_id))
+
+            if not to_delete:
+                continue
+
+            # delete old document__tags
+            bind = op.get_bind()
+            result = bind.execute(
+                sa.text(
+                    f"""
+                    DELETE FROM document__tag
+                    WHERE document_id = '{document_id}'
+                    AND tag_id IN ({','.join(to_delete)})
+                    """
+                )
+            )
+            n_deleted += result.rowcount
+        logger.info(f"Processed {len(batch)} documents and deleted {n_deleted} tags")
+
+
+def active_search_settings() -> tuple[SearchSettings, SearchSettings | None]:
+    result = op.get_bind().execute(
+        sa.text(
+            """
+        SELECT * FROM search_settings WHERE status = 'PRESENT' ORDER BY id DESC LIMIT 1
+        """
+        )
+    )
+    search_settings_fetch = result.fetchall()
+    search_settings = (
+        SearchSettings(**search_settings_fetch[0]._asdict())
+        if search_settings_fetch
+        else None
+    )
+
+    result2 = op.get_bind().execute(
+        sa.text(
+            """
+        SELECT * FROM search_settings WHERE status = 'FUTURE' ORDER BY id DESC LIMIT 1
+        """
+        )
+    )
+    search_settings_future_fetch = result2.fetchall()
+    search_settings_future = (
+        SearchSettings(**search_settings_future_fetch[0]._asdict())
+        if search_settings_future_fetch
+        else None
+    )
+
+    if not isinstance(search_settings, SearchSettings):
+        raise RuntimeError(
+            "current search settings is of type " + str(type(search_settings))
+        )
+    if (
+        not isinstance(search_settings_future, SearchSettings)
+        and search_settings_future is not None
+    ):
+        raise RuntimeError(
+            "future search settings is of type " + str(type(search_settings_future))
+        )
+
+    return search_settings, search_settings_future
+
+
+def _get_batch_documents_with_multiple_tags(
+    batch_size: int = 128,
+) -> Generator[list[str], None, None]:
+    """
+    Returns a list of document ids which contain a one to many tag.
+    The document may either contain a list metadata value, or may contain leftover
+    old tags from reindexing.
+    """
+    offset_clause = ""
+    bind = op.get_bind()
+
+    while True:
+        batch = bind.execute(
+            sa.text(
+                f"""
+                SELECT DISTINCT document__tag.document_id
+                FROM tag
+                JOIN document__tag ON tag.id = document__tag.tag_id
+                GROUP BY tag.tag_key, tag.source, document__tag.document_id
+                HAVING count(*) > 1 {offset_clause}
+                ORDER BY document__tag.document_id
+                LIMIT {batch_size}
+                """
+            )
+        ).fetchall()
+        if not batch:
+            break
+        doc_ids = [document_id for document_id, in batch]
+        yield doc_ids
+        offset_clause = f"AND document__tag.document_id > '{doc_ids[-1]}'"
+
+
+def _get_vespa_metadata(
+    document_id: str, index_name: str
+) -> dict[str, str | list[str]]:
+    url = DOCUMENT_ID_ENDPOINT.format(index_name=index_name)
+
+    # Document-Selector language
+    selection = (
+        f"{index_name}.document_id=='{document_id}' and {index_name}.chunk_id==0"
+    )
+
+    params: dict[str, str | int] = {
+        "selection": selection,
+        "wantedDocumentCount": 1,
+        "fieldSet": f"{index_name}:metadata",
+    }
+
+    with get_vespa_http_client() as client:
+        resp = client.get(url, params=params)
+        resp.raise_for_status()
+
+    docs = resp.json().get("documents", [])
+    if not docs:
+        raise RuntimeError(f"No chunk-0 found for document {document_id}")
+
+    # for some reason, metadata is a string
+    metadata = docs[0]["fields"]["metadata"]
+    return json.loads(metadata)
+
+
+def _get_document_tags(document_id: str) -> list[tuple[int, str, str]]:
+    bind = op.get_bind()
+    result = bind.execute(
+        sa.text(
+            f"""
+            SELECT tag.id, tag.tag_key, tag.tag_value
+            FROM tag
+            JOIN document__tag ON tag.id = document__tag.tag_id
+            WHERE document__tag.document_id = '{document_id}'
+            """
+        )
+    ).fetchall()
+    return cast(list[tuple[int, str, str]], result)
+
+
+def upgrade() -> None:
+    op.add_column(
+        "tag",
+        sa.Column("is_list", sa.Boolean(), nullable=False, server_default="false"),
+    )
+    op.drop_constraint(
+        constraint_name="_tag_key_value_source_uc",
+        table_name="tag",
+        type_="unique",
+    )
+    op.create_unique_constraint(
+        constraint_name="_tag_key_value_source_list_uc",
+        table_name="tag",
+        columns=["tag_key", "tag_value", "source", "is_list"],
+    )
+    set_is_list_for_known_tags()
+
+    if SKIP_TAG_FIX:
+        logger.warning(
+            "Skipping removal of old tags. "
+            "This can cause issues when using the knowledge graph, or "
+            "when filtering for documents by tags."
+        )
+        log_list_tags()
+        return
+
+    remove_old_tags()
+    set_is_list_for_list_tags()
+
+    # debug
+    log_list_tags()
+
+
+def downgrade() -> None:
+    # the migration adds and populates the is_list column, and removes old bugged tags
+    # there isn't a point in adding back the bugged tags, so we just drop the column
+    op.drop_constraint(
+        constraint_name="_tag_key_value_source_list_uc",
+        table_name="tag",
+        type_="unique",
+    )
+    op.create_unique_constraint(
+        constraint_name="_tag_key_value_source_uc",
+        table_name="tag",
+        columns=["tag_key", "tag_value", "source"],
+    )
+    op.drop_column("tag", "is_list")

backend/alembic/versions/abbfec3a5ac5_merge_prompt_into_persona.py

@@ -0,0 +1,225 @@
+"""merge prompt into persona
+
+Revision ID: abbfec3a5ac5
+Revises: 8818cf73fa1a
+Create Date: 2024-12-19 12:00:00.000000
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision = "abbfec3a5ac5"
+down_revision = "8818cf73fa1a"
+branch_labels = None
+depends_on = None
+
+
+MAX_PROMPT_LENGTH = 5_000_000
+
+
+def upgrade() -> None:
+    """NOTE: Prompts without any Personas will just be lost."""
+    # Step 1: Add new columns to persona table (only if they don't exist)
+
+    # Check if columns exist before adding them
+    connection = op.get_bind()
+    inspector = sa.inspect(connection)
+    existing_columns = [col["name"] for col in inspector.get_columns("persona")]
+
+    if "system_prompt" not in existing_columns:
+        op.add_column(
+            "persona",
+            sa.Column(
+                "system_prompt", sa.String(length=MAX_PROMPT_LENGTH), nullable=True
+            ),
+        )
+
+    if "task_prompt" not in existing_columns:
+        op.add_column(
+            "persona",
+            sa.Column(
+                "task_prompt", sa.String(length=MAX_PROMPT_LENGTH), nullable=True
+            ),
+        )
+
+    if "datetime_aware" not in existing_columns:
+        op.add_column(
+            "persona",
+            sa.Column(
+                "datetime_aware", sa.Boolean(), nullable=False, server_default="true"
+            ),
+        )
+
+    # Step 2: Migrate data from prompt table to persona table (only if tables exist)
+    existing_tables = inspector.get_table_names()
+
+    if "prompt" in existing_tables and "persona__prompt" in existing_tables:
+        # For personas that have associated prompts, copy the prompt data
+        op.execute(
+            """
+            UPDATE persona
+            SET
+                system_prompt = p.system_prompt,
+                task_prompt = p.task_prompt,
+                datetime_aware = p.datetime_aware
+            FROM (
+                -- Get the first prompt for each persona (in case there are multiple)
+                SELECT DISTINCT ON (pp.persona_id)
+                    pp.persona_id,
+                    pr.system_prompt,
+                    pr.task_prompt,
+                    pr.datetime_aware
+                FROM persona__prompt pp
+                JOIN prompt pr ON pp.prompt_id = pr.id
+            ) p
+            WHERE persona.id = p.persona_id
+        """
+        )
+
+        # Step 3: Update chat_message references
+        # Since chat messages referenced prompt_id, we need to update them to use persona_id
+        # This is complex as we need to map from prompt_id to persona_id
+
+        # Check if chat_message has prompt_id column
+        chat_message_columns = [
+            col["name"] for col in inspector.get_columns("chat_message")
+        ]
+        if "prompt_id" in chat_message_columns:
+            op.execute(
+                """
+                ALTER TABLE chat_message
+                DROP CONSTRAINT IF EXISTS chat_message__prompt_fk
+            """
+            )
+            op.drop_column("chat_message", "prompt_id")
+
+    # Step 4: Handle personas without prompts - set default values if needed (always run this)
+    op.execute(
+        """
+        UPDATE persona
+        SET
+            system_prompt = COALESCE(system_prompt, ''),
+            task_prompt = COALESCE(task_prompt, '')
+        WHERE system_prompt IS NULL OR task_prompt IS NULL
+    """
+    )
+
+    # Step 5: Drop the persona__prompt association table (if it exists)
+    if "persona__prompt" in existing_tables:
+        op.drop_table("persona__prompt")
+
+    # Step 6: Drop the prompt table (if it exists)
+    if "prompt" in existing_tables:
+        op.drop_table("prompt")
+
+    # Step 7: Make system_prompt and task_prompt non-nullable after migration (only if they exist)
+    op.alter_column(
+        "persona",
+        "system_prompt",
+        existing_type=sa.String(length=MAX_PROMPT_LENGTH),
+        nullable=False,
+        server_default=None,
+    )
+
+    op.alter_column(
+        "persona",
+        "task_prompt",
+        existing_type=sa.String(length=MAX_PROMPT_LENGTH),
+        nullable=False,
+        server_default=None,
+    )
+
+
+def downgrade() -> None:
+    # Step 1: Recreate the prompt table
+    op.create_table(
+        "prompt",
+        sa.Column("id", sa.Integer(), nullable=False),
+        sa.Column("user_id", postgresql.UUID(as_uuid=True), nullable=True),
+        sa.Column("name", sa.String(), nullable=False),
+        sa.Column("description", sa.String(), nullable=False),
+        sa.Column("system_prompt", sa.String(length=MAX_PROMPT_LENGTH), nullable=False),
+        sa.Column("task_prompt", sa.String(length=MAX_PROMPT_LENGTH), nullable=False),
+        sa.Column(
+            "datetime_aware", sa.Boolean(), nullable=False, server_default="true"
+        ),
+        sa.Column(
+            "default_prompt", sa.Boolean(), nullable=False, server_default="false"
+        ),
+        sa.Column("deleted", sa.Boolean(), nullable=False, server_default="false"),
+        sa.ForeignKeyConstraint(["user_id"], ["user.id"], ondelete="CASCADE"),
+        sa.PrimaryKeyConstraint("id"),
+    )
+
+    # Step 2: Recreate the persona__prompt association table
+    op.create_table(
+        "persona__prompt",
+        sa.Column("persona_id", sa.Integer(), nullable=False),
+        sa.Column("prompt_id", sa.Integer(), nullable=False),
+        sa.ForeignKeyConstraint(
+            ["persona_id"],
+            ["persona.id"],
+        ),
+        sa.ForeignKeyConstraint(
+            ["prompt_id"],
+            ["prompt.id"],
+        ),
+        sa.PrimaryKeyConstraint("persona_id", "prompt_id"),
+    )
+
+    # Step 3: Migrate data back from persona to prompt table
+    op.execute(
+        """
+        INSERT INTO prompt (
+            name,
+            description,
+            system_prompt,
+            task_prompt,
+            datetime_aware,
+            default_prompt,
+            deleted,
+            user_id
+        )
+        SELECT
+            CONCAT('Prompt for ', name),
+            description,
+            system_prompt,
+            task_prompt,
+            datetime_aware,
+            is_default_persona,
+            deleted,
+            user_id
+        FROM persona
+        WHERE system_prompt IS NOT NULL AND system_prompt != ''
+        RETURNING id, name
+        """
+    )
+
+    # Step 4: Re-establish persona__prompt relationships
+    op.execute(
+        """
+        INSERT INTO persona__prompt (persona_id, prompt_id)
+        SELECT
+            p.id as persona_id,
+            pr.id as prompt_id
+        FROM persona p
+        JOIN prompt pr ON pr.name = CONCAT('Prompt for ', p.name)
+        WHERE p.system_prompt IS NOT NULL AND p.system_prompt != ''
+    """
+    )
+
+    # Step 5: Add prompt_id column back to chat_message
+    op.add_column("chat_message", sa.Column("prompt_id", sa.Integer(), nullable=True))
+
+    # Step 6: Re-establish foreign key constraint
+    op.create_foreign_key(
+        "chat_message__prompt_fk", "chat_message", "prompt", ["prompt_id"], ["id"]
+    )
+
+    # Step 7: Remove columns from persona table
+    op.drop_column("persona", "datetime_aware")
+    op.drop_column("persona", "task_prompt")
+    op.drop_column("persona", "system_prompt")

backend/alembic/versions/b329d00a9ea6_adding_assistant_specific_user_.py

@@ -0,0 +1,38 @@
+"""Adding assistant-specific user preferences
+
+Revision ID: b329d00a9ea6
+Revises: f9b8c7d6e5a4
+Create Date: 2025-08-26 23:14:44.592985
+
+"""
+
+from alembic import op
+import fastapi_users_db_sqlalchemy
+import sqlalchemy as sa
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision = "b329d00a9ea6"
+down_revision = "f9b8c7d6e5a4"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.create_table(
+        "assistant__user_specific_config",
+        sa.Column("assistant_id", sa.Integer(), nullable=False),
+        sa.Column(
+            "user_id",
+            fastapi_users_db_sqlalchemy.generics.GUID(),
+            nullable=False,
+        ),
+        sa.Column("disabled_tool_ids", postgresql.ARRAY(sa.Integer()), nullable=False),
+        sa.ForeignKeyConstraint(["assistant_id"], ["persona.id"], ondelete="CASCADE"),
+        sa.ForeignKeyConstraint(["user_id"], ["user.id"], ondelete="CASCADE"),
+        sa.PrimaryKeyConstraint("assistant_id", "user_id"),
+    )
+
+
+def downgrade() -> None:
+    op.drop_table("assistant__user_specific_config")

backend/alembic/versions/b558f51620b4_pause_finished_user_file_connectors.py

@@ -0,0 +1,33 @@
+"""Pause finished user file connectors
+
+Revision ID: b558f51620b4
+Revises: 90e3b9af7da4
+Create Date: 2025-08-15 17:17:02.456704
+
+"""
+
+from alembic import op
+
+
+# revision identifiers, used by Alembic.
+revision = "b558f51620b4"
+down_revision = "90e3b9af7da4"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # Set all user file connector credential pairs with ACTIVE status to PAUSED
+    # This ensures user files don't continue to run indexing tasks after processing
+    op.execute(
+        """
+        UPDATE connector_credential_pair
+        SET status = 'PAUSED'
+        WHERE is_user_file = true
+        AND status = 'ACTIVE'
+        """
+    )
+
+
+def downgrade() -> None:
+    pass

backend/alembic/versions/b7ec9b5b505f_adjust_prompt_length.py

@@ -0,0 +1,43 @@
+"""adjust prompt length
+
+Revision ID: b7ec9b5b505f
+Revises: abbfec3a5ac5
+Create Date: 2025-09-10 18:51:15.629197
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "b7ec9b5b505f"
+down_revision = "abbfec3a5ac5"
+branch_labels = None
+depends_on = None
+
+
+MAX_PROMPT_LENGTH = 5_000_000
+
+
+def upgrade() -> None:
+    # NOTE: need to run this since the previous migration PREVIOUSLY set the length to 8000
+    op.alter_column(
+        "persona",
+        "system_prompt",
+        existing_type=sa.String(length=8000),
+        type_=sa.String(length=MAX_PROMPT_LENGTH),
+        existing_nullable=False,
+    )
+    op.alter_column(
+        "persona",
+        "task_prompt",
+        existing_type=sa.String(length=8000),
+        type_=sa.String(length=MAX_PROMPT_LENGTH),
+        existing_nullable=False,
+    )
+
+
+def downgrade() -> None:
+    # Downgrade not necessary
+    pass

backend/alembic/versions/bd7c3bf8beba_migrate_agent_responses_to_research_.py

@@ -0,0 +1,147 @@
+"""migrate_agent_sub_questions_to_research_iterations
+
+Revision ID: bd7c3bf8beba
+Revises: f8a9b2c3d4e5
+Create Date: 2025-08-18 11:33:27.098287
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "bd7c3bf8beba"
+down_revision = "f8a9b2c3d4e5"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # Get connection to execute raw SQL
+    connection = op.get_bind()
+
+    # First, insert data into research_agent_iteration table
+    # This creates one iteration record per primary_question_id using the earliest time_created
+    connection.execute(
+        sa.text(
+            """
+            INSERT INTO research_agent_iteration (primary_question_id, created_at, iteration_nr, purpose, reasoning)
+            SELECT
+                primary_question_id,
+                MIN(time_created) as created_at,
+                1 as iteration_nr,
+                'Generating and researching subquestions' as purpose,
+                '(No previous reasoning)' as reasoning
+            FROM agent__sub_question
+            JOIN chat_message on agent__sub_question.primary_question_id = chat_message.id
+            WHERE primary_question_id IS NOT NULL
+                AND chat_message.is_agentic = true
+            GROUP BY primary_question_id
+            ON CONFLICT DO NOTHING;
+        """
+        )
+    )
+
+    # Then, insert data into research_agent_iteration_sub_step table
+    # This migrates each sub-question as a sub-step
+    connection.execute(
+        sa.text(
+            """
+            INSERT INTO research_agent_iteration_sub_step (
+                primary_question_id,
+                iteration_nr,
+                iteration_sub_step_nr,
+                created_at,
+                sub_step_instructions,
+                sub_step_tool_id,
+                sub_answer,
+                cited_doc_results
+            )
+            SELECT
+                primary_question_id,
+                1 as iteration_nr,
+                level_question_num as iteration_sub_step_nr,
+                time_created as created_at,
+                sub_question as sub_step_instructions,
+                1 as sub_step_tool_id,
+                sub_answer,
+                sub_question_doc_results as cited_doc_results
+            FROM agent__sub_question
+            JOIN chat_message on agent__sub_question.primary_question_id = chat_message.id
+            WHERE chat_message.is_agentic = true
+            AND primary_question_id IS NOT NULL
+            ON CONFLICT DO NOTHING;
+        """
+        )
+    )
+
+    # Update chat_message records: set legacy agentic type and answer purpose for existing agentic messages
+    connection.execute(
+        sa.text(
+            """
+            UPDATE chat_message
+            SET research_answer_purpose = 'ANSWER'
+            WHERE is_agentic = true
+            AND research_type IS NULL and
+                message_type = 'ASSISTANT';
+        """
+        )
+    )
+    connection.execute(
+        sa.text(
+            """
+            UPDATE chat_message
+            SET research_type = 'LEGACY_AGENTIC'
+            WHERE is_agentic = true
+            AND research_type IS NULL;
+        """
+        )
+    )
+
+
+def downgrade() -> None:
+    # Get connection to execute raw SQL
+    connection = op.get_bind()
+
+    # Note: This downgrade removes all research agent iteration data
+    # There's no way to perfectly restore the original agent__sub_question data
+    # if it was deleted after this migration
+
+    # Delete all research_agent_iteration_sub_step records that were migrated
+    connection.execute(
+        sa.text(
+            """
+            DELETE FROM research_agent_iteration_sub_step
+            USING chat_message
+            WHERE research_agent_iteration_sub_step.primary_question_id = chat_message.id
+            AND chat_message.research_type = 'LEGACY_AGENTIC';
+        """
+        )
+    )
+
+    # Delete all research_agent_iteration records that were migrated
+    connection.execute(
+        sa.text(
+            """
+            DELETE FROM research_agent_iteration
+            USING chat_message
+            WHERE research_agent_iteration.primary_question_id = chat_message.id
+            AND chat_message.research_type = 'LEGACY_AGENTIC';
+        """
+        )
+    )
+
+    # Revert chat_message updates: clear research fields for legacy agentic messages
+    connection.execute(
+        sa.text(
+            """
+            UPDATE chat_message
+            SET research_type = NULL,
+                research_answer_purpose = NULL
+            WHERE is_agentic = true
+            AND research_type = 'LEGACY_AGENTIC'
+            AND message_type = 'ASSISTANT';
+        """
+        )
+    )

backend/alembic/versions/d09fc20a3c66_seed_builtin_tools.py

@@ -0,0 +1,152 @@
+"""seed_builtin_tools
+
+Revision ID: d09fc20a3c66
+Revises: b7ec9b5b505f
+Create Date: 2025-09-09 19:32:16.824373
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "d09fc20a3c66"
+down_revision = "b7ec9b5b505f"
+branch_labels = None
+depends_on = None
+
+
+# Tool definitions - core tools that should always be seeded
+# Names/in_code_tool_id are the same as the class names in the tool_implementations package
+BUILT_IN_TOOLS = [
+    {
+        "name": "SearchTool",
+        "display_name": "Internal Search",
+        "description": "The Search Action allows the Assistant to search through connected knowledge to help build an answer.",
+        "in_code_tool_id": "SearchTool",
+    },
+    {
+        "name": "ImageGenerationTool",
+        "display_name": "Image Generation",
+        "description": (
+            "The Image Generation Action allows the assistant to use DALL-E 3 or GPT-IMAGE-1 to generate images. "
+            "The action will be used when the user asks the assistant to generate an image."
+        ),
+        "in_code_tool_id": "ImageGenerationTool",
+    },
+    {
+        "name": "WebSearchTool",
+        "display_name": "Web Search",
+        "description": (
+            "The Web Search Action allows the assistant "
+            "to perform internet searches for up-to-date information."
+        ),
+        "in_code_tool_id": "WebSearchTool",
+    },
+    {
+        "name": "KnowledgeGraphTool",
+        "display_name": "Knowledge Graph Search",
+        "description": (
+            "The Knowledge Graph Search Action allows the assistant to search the "
+            "Knowledge Graph for information. This tool can (for now) only be active in the KG Beta Assistant, "
+            "and it requires the Knowledge Graph to be enabled."
+        ),
+        "in_code_tool_id": "KnowledgeGraphTool",
+    },
+    {
+        "name": "OktaProfileTool",
+        "display_name": "Okta Profile",
+        "description": (
+            "The Okta Profile Action allows the assistant to fetch the current user's information from Okta. "
+            "This may include the user's name, email, phone number, address, and other details such as their "
+            "manager and direct reports."
+        ),
+        "in_code_tool_id": "OktaProfileTool",
+    },
+]
+
+
+def upgrade() -> None:
+    conn = op.get_bind()
+
+    # Start transaction
+    conn.execute(sa.text("BEGIN"))
+
+    try:
+        # Get existing tools to check what already exists
+        existing_tools = conn.execute(
+            sa.text(
+                "SELECT in_code_tool_id FROM tool WHERE in_code_tool_id IS NOT NULL"
+            )
+        ).fetchall()
+        existing_tool_ids = {row[0] for row in existing_tools}
+
+        # Insert or update built-in tools
+        for tool in BUILT_IN_TOOLS:
+            in_code_id = tool["in_code_tool_id"]
+
+            # Handle historical rename: InternetSearchTool -> WebSearchTool
+            if (
+                in_code_id == "WebSearchTool"
+                and "WebSearchTool" not in existing_tool_ids
+                and "InternetSearchTool" in existing_tool_ids
+            ):
+                # Rename the existing InternetSearchTool row in place and update fields
+                conn.execute(
+                    sa.text(
+                        """
+                        UPDATE tool
+                        SET name = :name,
+                            display_name = :display_name,
+                            description = :description,
+                            in_code_tool_id = :in_code_tool_id
+                        WHERE in_code_tool_id = 'InternetSearchTool'
+                        """
+                    ),
+                    tool,
+                )
+                # Keep the local view of existing ids in sync to avoid duplicate insert
+                existing_tool_ids.discard("InternetSearchTool")
+                existing_tool_ids.add("WebSearchTool")
+                continue
+
+            if in_code_id in existing_tool_ids:
+                # Update existing tool
+                conn.execute(
+                    sa.text(
+                        """
+                        UPDATE tool
+                        SET name = :name,
+                            display_name = :display_name,
+                            description = :description
+                        WHERE in_code_tool_id = :in_code_tool_id
+                        """
+                    ),
+                    tool,
+                )
+            else:
+                # Insert new tool
+                conn.execute(
+                    sa.text(
+                        """
+                        INSERT INTO tool (name, display_name, description, in_code_tool_id)
+                        VALUES (:name, :display_name, :description, :in_code_tool_id)
+                        """
+                    ),
+                    tool,
+                )
+
+        # Commit transaction
+        conn.execute(sa.text("COMMIT"))
+
+    except Exception as e:
+        # Rollback on error
+        conn.execute(sa.text("ROLLBACK"))
+        raise e
+
+
+def downgrade() -> None:
+    # We don't remove the tools on downgrade since it's totally fine to just
+    # have them around. If we upgrade again, it will be a no-op.
+    pass

backend/alembic/versions/f8a9b2c3d4e5_add_research_answer_purpose_to_chat_message.py

@@ -0,0 +1,30 @@
+"""add research_answer_purpose to chat_message
+
+Revision ID: f8a9b2c3d4e5
+Revises: 5ae8240accb3
+Create Date: 2025-01-27 12:00:00.000000
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "f8a9b2c3d4e5"
+down_revision = "5ae8240accb3"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # Add research_answer_purpose column to chat_message table
+    op.add_column(
+        "chat_message",
+        sa.Column("research_answer_purpose", sa.String(), nullable=True),
+    )
+
+
+def downgrade() -> None:
+    # Remove research_answer_purpose column from chat_message table
+    op.drop_column("chat_message", "research_answer_purpose")

backend/alembic/versions/f9b8c7d6e5a4_update_parent_question_id_foreign_key_to_research_agent_iteration.py

@@ -0,0 +1,69 @@
+"""remove foreign key constraints from research_agent_iteration_sub_step
+
+Revision ID: f9b8c7d6e5a4
+Revises: bd7c3bf8beba
+Create Date: 2025-01-27 12:00:00.000000
+
+"""
+
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "f9b8c7d6e5a4"
+down_revision = "bd7c3bf8beba"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # Drop the existing foreign key constraint for parent_question_id
+    op.drop_constraint(
+        "research_agent_iteration_sub_step_parent_question_id_fkey",
+        "research_agent_iteration_sub_step",
+        type_="foreignkey",
+    )
+
+    # Drop the parent_question_id column entirely
+    op.drop_column("research_agent_iteration_sub_step", "parent_question_id")
+
+    # Drop the foreign key constraint for primary_question_id to chat_message.id
+    # (keep the column as it's needed for the composite foreign key)
+    op.drop_constraint(
+        "research_agent_iteration_sub_step_primary_question_id_fkey",
+        "research_agent_iteration_sub_step",
+        type_="foreignkey",
+    )
+
+
+def downgrade() -> None:
+    # Restore the foreign key constraint for primary_question_id to chat_message.id
+    op.create_foreign_key(
+        "research_agent_iteration_sub_step_primary_question_id_fkey",
+        "research_agent_iteration_sub_step",
+        "chat_message",
+        ["primary_question_id"],
+        ["id"],
+        ondelete="CASCADE",
+    )
+
+    # Add back the parent_question_id column
+    op.add_column(
+        "research_agent_iteration_sub_step",
+        sa.Column(
+            "parent_question_id",
+            sa.Integer(),
+            nullable=True,
+        ),
+    )
+
+    # Restore the foreign key constraint pointing to research_agent_iteration_sub_step.id
+    op.create_foreign_key(
+        "research_agent_iteration_sub_step_parent_question_id_fkey",
+        "research_agent_iteration_sub_step",
+        "research_agent_iteration_sub_step",
+        ["parent_question_id"],
+        ["id"],
+        ondelete="CASCADE",
+    )

backend/ee/onyx/background/celery/apps/primary.py

@@ -1,133 +1,4 @@
-from datetime import datetime
-from datetime import timezone
-from uuid import UUID
-
-from celery import shared_task
-from celery import Task
-
-from ee.onyx.background.celery_utils import should_perform_chat_ttl_check
-from ee.onyx.background.task_name_builders import name_chat_ttl_task
-from ee.onyx.server.reporting.usage_export_generation import create_new_usage_report
 from onyx.background.celery.apps.primary import celery_app
-from onyx.configs.app_configs import JOB_TIMEOUT
-from onyx.configs.constants import OnyxCeleryTask
-from onyx.db.chat import delete_chat_session
-from onyx.db.chat import get_chat_sessions_older_than
-from onyx.db.engine.sql_engine import get_session_with_current_tenant
-from onyx.db.enums import TaskStatus
-from onyx.db.tasks import mark_task_as_finished_with_id
-from onyx.db.tasks import register_task
-from onyx.server.settings.store import load_settings
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-# mark as EE for all tasks in this file
-
-
-@shared_task(
-    name=OnyxCeleryTask.PERFORM_TTL_MANAGEMENT_TASK,
-    ignore_result=True,
-    soft_time_limit=JOB_TIMEOUT,
-    bind=True,
-    trail=False,
-)
-def perform_ttl_management_task(
-    self: Task, retention_limit_days: int, *, tenant_id: str
-) -> None:
-    task_id = self.request.id
-    if not task_id:
-        raise RuntimeError("No task id defined for this task; cannot identify it")
-
-    start_time = datetime.now(tz=timezone.utc)
-
-    user_id: UUID | None = None
-    session_id: UUID | None = None
-    try:
-        with get_session_with_current_tenant() as db_session:
-            # we generally want to move off this, but keeping for now
-            register_task(
-                db_session=db_session,
-                task_name=name_chat_ttl_task(retention_limit_days, tenant_id),
-                task_id=task_id,
-                status=TaskStatus.STARTED,
-                start_time=start_time,
-            )
-
-            old_chat_sessions = get_chat_sessions_older_than(
-                retention_limit_days, db_session
-            )
-
-        for user_id, session_id in old_chat_sessions:
-            # one session per delete so that we don't blow up if a deletion fails.
-            with get_session_with_current_tenant() as db_session:
-                delete_chat_session(
-                    user_id,
-                    session_id,
-                    db_session,
-                    include_deleted=True,
-                    hard_delete=True,
-                )
-
-        with get_session_with_current_tenant() as db_session:
-            mark_task_as_finished_with_id(
-                db_session=db_session,
-                task_id=task_id,
-                success=True,
-            )
-
-    except Exception:
-        logger.exception(
-            "delete_chat_session exceptioned. "
-            f"user_id={user_id} session_id={session_id}"
-        )
-        with get_session_with_current_tenant() as db_session:
-            mark_task_as_finished_with_id(
-                db_session=db_session,
-                task_id=task_id,
-                success=False,
-            )
-        raise
-
-
-#####
-# Periodic Tasks
-#####
-
-
-@celery_app.task(
-    name=OnyxCeleryTask.CHECK_TTL_MANAGEMENT_TASK,
-    ignore_result=True,
-    soft_time_limit=JOB_TIMEOUT,
-)
-def check_ttl_management_task(*, tenant_id: str) -> None:
-    """Runs periodically to check if any ttl tasks should be run and adds them
-    to the queue"""
-
-    settings = load_settings()
-    retention_limit_days = settings.maximum_chat_retention_days
-    with get_session_with_current_tenant() as db_session:
-        if should_perform_chat_ttl_check(retention_limit_days, db_session):
-            perform_ttl_management_task.apply_async(
-                kwargs=dict(
-                    retention_limit_days=retention_limit_days, tenant_id=tenant_id
-                ),
-            )
-
-
-@celery_app.task(
-    name=OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
-    ignore_result=True,
-    soft_time_limit=JOB_TIMEOUT,
-)
-def autogenerate_usage_report_task(*, tenant_id: str) -> None:
-    """This generates usage report under the /admin/generate-usage/report endpoint"""
-    with get_session_with_current_tenant() as db_session:
-        create_new_usage_report(
-            db_session=db_session,
-            user_id=None,
-            period=None,
-        )
 
 
 celery_app.autodiscover_tasks(
@@ -135,5 +6,7 @@ celery_app.autodiscover_tasks(
         "ee.onyx.background.celery.tasks.doc_permission_syncing",
         "ee.onyx.background.celery.tasks.external_group_syncing",
         "ee.onyx.background.celery.tasks.cloud",
+        "ee.onyx.background.celery.tasks.ttl_management",
+        "ee.onyx.background.celery.tasks.usage_reporting",
     ]
 )

backend/ee/onyx/background/celery/tasks/beat_schedule.py

@@ -23,7 +23,7 @@ ee_beat_system_tasks: list[dict] = []
 ee_beat_task_templates: list[dict] = [
     {
         "name": "autogenerate-usage-report",
-        "task": OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
+        "task": OnyxCeleryTask.GENERATE_USAGE_REPORT_TASK,
         "schedule": timedelta(days=30),
         "options": {
             "priority": OnyxCeleryPriority.MEDIUM,
@@ -57,7 +57,7 @@ if not MULTI_TENANT:
     ee_tasks_to_schedule = [
         {
             "name": "autogenerate-usage-report",
-            "task": OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
+            "task": OnyxCeleryTask.GENERATE_USAGE_REPORT_TASK,
             "schedule": timedelta(days=30),  # TODO: change this to config flag
             "options": {
                 "priority": OnyxCeleryPriority.MEDIUM,

backend/ee/onyx/background/celery/tasks/doc_permission_syncing/tasks.py

@@ -47,6 +47,7 @@ from onyx.connectors.factory import validate_ccpair_for_user
 from onyx.db.connector import mark_cc_pair_as_permissions_synced
 from onyx.db.connector_credential_pair import get_connector_credential_pair_from_id
 from onyx.db.document import get_document_ids_for_connector_credential_pair
+from onyx.db.document import get_documents_for_connector_credential_pair_limited_columns
 from onyx.db.document import upsert_document_by_connector_credential_pair
 from onyx.db.engine.sql_engine import get_session_with_current_tenant
 from onyx.db.engine.sql_engine import get_session_with_tenant
@@ -58,7 +59,9 @@ from onyx.db.models import ConnectorCredentialPair
 from onyx.db.sync_record import insert_sync_record
 from onyx.db.sync_record import update_sync_record_status
 from onyx.db.users import batch_add_ext_perm_user_if_not_exists
+from onyx.db.utils import DocumentRow
 from onyx.db.utils import is_retryable_sqlalchemy_error
+from onyx.db.utils import SortOrder
 from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from onyx.redis.redis_connector import RedisConnector
 from onyx.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
@@ -498,16 +501,31 @@ def connector_permission_sync_generator_task(
             # this is can be used to determine documents that are "missing" and thus
             # should no longer be accessible. The decision as to whether we should find
             # every document during the doc sync process is connector-specific.
-            def fetch_all_existing_docs_fn() -> list[str]:
-                return get_document_ids_for_connector_credential_pair(
+            def fetch_all_existing_docs_fn(
+                sort_order: SortOrder | None = None,
+            ) -> list[DocumentRow]:
+                result = get_documents_for_connector_credential_pair_limited_columns(
+                    db_session=db_session,
+                    connector_id=cc_pair.connector.id,
+                    credential_id=cc_pair.credential.id,
+                    sort_order=sort_order,
+                )
+                return list(result)
+
+            def fetch_all_existing_docs_ids_fn() -> list[str]:
+                result = get_document_ids_for_connector_credential_pair(
                     db_session=db_session,
                     connector_id=cc_pair.connector.id,
                     credential_id=cc_pair.credential.id,
                 )
+                return result
 
             doc_sync_func = sync_config.doc_sync_config.doc_sync_func
             document_external_accesses = doc_sync_func(
-                cc_pair, fetch_all_existing_docs_fn, callback
+                cc_pair,
+                fetch_all_existing_docs_fn,
+                fetch_all_existing_docs_ids_fn,
+                callback,
             )
 
             task_logger.info(

backend/ee/onyx/background/celery/tasks/ttl_management/tasks.py

@@ -0,0 +1,106 @@
+from datetime import datetime
+from datetime import timezone
+from uuid import UUID
+
+from celery import shared_task
+from celery import Task
+
+from ee.onyx.background.celery_utils import should_perform_chat_ttl_check
+from ee.onyx.background.task_name_builders import name_chat_ttl_task
+from onyx.configs.app_configs import JOB_TIMEOUT
+from onyx.configs.constants import OnyxCeleryTask
+from onyx.db.chat import delete_chat_session
+from onyx.db.chat import get_chat_sessions_older_than
+from onyx.db.engine.sql_engine import get_session_with_current_tenant
+from onyx.db.enums import TaskStatus
+from onyx.db.tasks import mark_task_as_finished_with_id
+from onyx.db.tasks import register_task
+from onyx.server.settings.store import load_settings
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+@shared_task(
+    name=OnyxCeleryTask.PERFORM_TTL_MANAGEMENT_TASK,
+    ignore_result=True,
+    soft_time_limit=JOB_TIMEOUT,
+    bind=True,
+    trail=False,
+)
+def perform_ttl_management_task(
+    self: Task, retention_limit_days: int, *, tenant_id: str
+) -> None:
+    task_id = self.request.id
+    if not task_id:
+        raise RuntimeError("No task id defined for this task; cannot identify it")
+
+    start_time = datetime.now(tz=timezone.utc)
+
+    user_id: UUID | None = None
+    session_id: UUID | None = None
+    try:
+        with get_session_with_current_tenant() as db_session:
+            # we generally want to move off this, but keeping for now
+            register_task(
+                db_session=db_session,
+                task_name=name_chat_ttl_task(retention_limit_days, tenant_id),
+                task_id=task_id,
+                status=TaskStatus.STARTED,
+                start_time=start_time,
+            )
+
+            old_chat_sessions = get_chat_sessions_older_than(
+                retention_limit_days, db_session
+            )
+
+        for user_id, session_id in old_chat_sessions:
+            # one session per delete so that we don't blow up if a deletion fails.
+            with get_session_with_current_tenant() as db_session:
+                delete_chat_session(
+                    user_id,
+                    session_id,
+                    db_session,
+                    include_deleted=True,
+                    hard_delete=True,
+                )
+
+        with get_session_with_current_tenant() as db_session:
+            mark_task_as_finished_with_id(
+                db_session=db_session,
+                task_id=task_id,
+                success=True,
+            )
+
+    except Exception:
+        logger.exception(
+            "delete_chat_session exceptioned. "
+            f"user_id={user_id} session_id={session_id}"
+        )
+        with get_session_with_current_tenant() as db_session:
+            mark_task_as_finished_with_id(
+                db_session=db_session,
+                task_id=task_id,
+                success=False,
+            )
+        raise
+
+
+@shared_task(
+    name=OnyxCeleryTask.CHECK_TTL_MANAGEMENT_TASK,
+    ignore_result=True,
+    soft_time_limit=JOB_TIMEOUT,
+)
+def check_ttl_management_task(*, tenant_id: str) -> None:
+    """Runs periodically to check if any ttl tasks should be run and adds them
+    to the queue"""
+
+    settings = load_settings()
+    retention_limit_days = settings.maximum_chat_retention_days
+    with get_session_with_current_tenant() as db_session:
+        if should_perform_chat_ttl_check(retention_limit_days, db_session):
+            perform_ttl_management_task.apply_async(
+                kwargs=dict(
+                    retention_limit_days=retention_limit_days, tenant_id=tenant_id
+                ),
+            )

backend/ee/onyx/background/celery/tasks/usage_reporting/tasks.py

@@ -0,0 +1,46 @@
+from datetime import datetime
+from uuid import UUID
+
+from celery import shared_task
+from celery import Task
+
+from ee.onyx.server.reporting.usage_export_generation import create_new_usage_report
+from onyx.configs.app_configs import JOB_TIMEOUT
+from onyx.configs.constants import OnyxCeleryTask
+from onyx.db.engine.sql_engine import get_session_with_current_tenant
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+@shared_task(
+    name=OnyxCeleryTask.GENERATE_USAGE_REPORT_TASK,
+    ignore_result=True,
+    soft_time_limit=JOB_TIMEOUT,
+    bind=True,
+    trail=False,
+)
+def generate_usage_report_task(
+    self: Task,
+    *,
+    tenant_id: str,
+    user_id: str | None = None,
+    period_from: str | None = None,
+    period_to: str | None = None,
+) -> None:
+    """User-initiated usage report generation task"""
+    # Parse period if provided
+    period = None
+    if period_from and period_to:
+        period = (
+            datetime.fromisoformat(period_from),
+            datetime.fromisoformat(period_to),
+        )
+
+    # Generate the report
+    with get_session_with_current_tenant() as db_session:
+        create_new_usage_report(
+            db_session=db_session,
+            user_id=UUID(user_id) if user_id else None,
+            period=period,
+        )

backend/ee/onyx/chat/process_message.py

@@ -1,38 +0,0 @@
-from ee.onyx.server.query_and_chat.models import OneShotQAResponse
-from onyx.chat.models import AllCitations
-from onyx.chat.models import LLMRelevanceFilterResponse
-from onyx.chat.models import OnyxAnswerPiece
-from onyx.chat.models import QADocsResponse
-from onyx.chat.models import StreamingError
-from onyx.chat.process_message import ChatPacketStream
-from onyx.server.query_and_chat.models import ChatMessageDetail
-from onyx.utils.timing import log_function_time
-
-
-@log_function_time()
-def gather_stream_for_answer_api(
-    packets: ChatPacketStream,
-) -> OneShotQAResponse:
-    response = OneShotQAResponse()
-
-    answer = ""
-    for packet in packets:
-        if isinstance(packet, OnyxAnswerPiece) and packet.answer_piece:
-            answer += packet.answer_piece
-        elif isinstance(packet, QADocsResponse):
-            response.docs = packet
-            # Extraneous, provided for backwards compatibility
-            response.rephrase = packet.rephrased_query
-        elif isinstance(packet, StreamingError):
-            response.error_msg = packet.error
-        elif isinstance(packet, ChatMessageDetail):
-            response.chat_message_id = packet.message_id
-        elif isinstance(packet, LLMRelevanceFilterResponse):
-            response.llm_selected_doc_indices = packet.llm_selected_doc_indices
-        elif isinstance(packet, AllCitations):
-            response.citations = packet.citations
-
-    if answer:
-        response.answer = answer
-
-    return response

backend/ee/onyx/configs/app_configs.py

@@ -71,6 +71,19 @@ GOOGLE_DRIVE_PERMISSION_GROUP_SYNC_FREQUENCY = int(
 )
 
 
+#####
+# GitHub
+#####
+# In seconds, default is 5 minutes
+GITHUB_PERMISSION_DOC_SYNC_FREQUENCY = int(
+    os.environ.get("GITHUB_PERMISSION_DOC_SYNC_FREQUENCY") or 5 * 60
+)
+# In seconds, default is 5 minutes
+GITHUB_PERMISSION_GROUP_SYNC_FREQUENCY = int(
+    os.environ.get("GITHUB_PERMISSION_GROUP_SYNC_FREQUENCY") or 5 * 60
+)
+
+
 #####
 # Slack
 #####
@@ -89,6 +102,19 @@ TEAMS_PERMISSION_DOC_SYNC_FREQUENCY = int(
     os.environ.get("TEAMS_PERMISSION_DOC_SYNC_FREQUENCY") or 5 * 60
 )
 
+#####
+# SharePoint
+#####
+# In seconds, default is 30 minutes
+SHAREPOINT_PERMISSION_DOC_SYNC_FREQUENCY = int(
+    os.environ.get("SHAREPOINT_PERMISSION_DOC_SYNC_FREQUENCY") or 30 * 60
+)
+
+# In seconds, default is 5 minutes
+SHAREPOINT_PERMISSION_GROUP_SYNC_FREQUENCY = int(
+    os.environ.get("SHAREPOINT_PERMISSION_GROUP_SYNC_FREQUENCY") or 5 * 60
+)
+
 
 ####
 # Celery Job Frequency

backend/ee/onyx/document_index/vespa/app_config/cloud-services.xml.jinja

@@ -18,9 +18,9 @@
             <!-- <document type="danswer_chunk" mode="index" /> -->
 {{ document_elements }}
         </documents>
-        <nodes count="75">
-            <resources vcpu="8.0" memory="64.0Gb" architecture="arm64" storage-type="local"
-                disk="474.0Gb" />
+        <nodes count="60">
+            <resources vcpu="8.0" memory="128.0Gb" architecture="arm64" storage-type="local"
+                disk="475.0Gb" />
         </nodes>
         <engine>
             <proton>

backend/ee/onyx/external_permissions/confluence/doc_sync.py

@@ -6,6 +6,7 @@ https://confluence.atlassian.com/conf85/check-who-can-view-a-page-1283360557.htm
 from collections.abc import Generator
 
 from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from ee.onyx.external_permissions.utils import generic_doc_sync
 from onyx.access.models import DocExternalAccess
 from onyx.configs.constants import DocumentSource
@@ -25,6 +26,7 @@ CONFLUENCE_DOC_SYNC_LABEL = "confluence_doc_sync"
 def confluence_doc_sync(
     cc_pair: ConnectorCredentialPair,
     fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: IndexingHeartbeatInterface | None,
 ) -> Generator[DocExternalAccess, None, None]:
     """
@@ -43,7 +45,7 @@ def confluence_doc_sync(
 
     yield from generic_doc_sync(
         cc_pair=cc_pair,
-        fetch_all_existing_docs_fn=fetch_all_existing_docs_fn,
+        fetch_all_existing_docs_ids_fn=fetch_all_existing_docs_ids_fn,
         callback=callback,
         doc_source=DocumentSource.CONFLUENCE,
         slim_connector=confluence_connector,

backend/ee/onyx/external_permissions/github/doc_sync.py

@@ -0,0 +1,294 @@
+import json
+from collections.abc import Generator
+
+from github import Github
+from github.Repository import Repository
+
+from ee.onyx.external_permissions.github.utils import fetch_repository_team_slugs
+from ee.onyx.external_permissions.github.utils import form_collaborators_group_id
+from ee.onyx.external_permissions.github.utils import form_organization_group_id
+from ee.onyx.external_permissions.github.utils import (
+    form_outside_collaborators_group_id,
+)
+from ee.onyx.external_permissions.github.utils import get_external_access_permission
+from ee.onyx.external_permissions.github.utils import get_repository_visibility
+from ee.onyx.external_permissions.github.utils import GitHubVisibility
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
+from onyx.access.models import DocExternalAccess
+from onyx.access.utils import build_ext_group_name_for_onyx
+from onyx.configs.constants import DocumentSource
+from onyx.connectors.github.connector import DocMetadata
+from onyx.connectors.github.connector import GithubConnector
+from onyx.db.models import ConnectorCredentialPair
+from onyx.db.utils import DocumentRow
+from onyx.db.utils import SortOrder
+from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+GITHUB_DOC_SYNC_LABEL = "github_doc_sync"
+
+
+def github_doc_sync(
+    cc_pair: ConnectorCredentialPair,
+    fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
+    callback: IndexingHeartbeatInterface | None = None,
+) -> Generator[DocExternalAccess, None, None]:
+    """
+    Sync GitHub documents with external access permissions.
+
+    This function checks each repository for visibility/team changes and updates
+    document permissions accordingly without using checkpoints.
+    """
+    logger.info(f"Starting GitHub document sync for CC pair ID: {cc_pair.id}")
+
+    # Initialize GitHub connector with credentials
+    github_connector: GithubConnector = GithubConnector(
+        **cc_pair.connector.connector_specific_config
+    )
+
+    github_connector.load_credentials(cc_pair.credential.credential_json)
+    logger.info("GitHub connector credentials loaded successfully")
+
+    if not github_connector.github_client:
+        logger.error("GitHub client initialization failed")
+        raise ValueError("github_client is required")
+
+    # Get all repositories from GitHub API
+    logger.info("Fetching all repositories from GitHub API")
+    try:
+        repos = []
+        if github_connector.repositories:
+            if "," in github_connector.repositories:
+                # Multiple repositories specified
+                repos = github_connector.get_github_repos(
+                    github_connector.github_client
+                )
+            else:
+                # Single repository
+                repos = [
+                    github_connector.get_github_repo(github_connector.github_client)
+                ]
+        else:
+            # All repositories
+            repos = github_connector.get_all_repos(github_connector.github_client)
+
+        logger.info(f"Found {len(repos)} repositories to check")
+    except Exception as e:
+        logger.error(f"Failed to fetch repositories: {e}")
+        raise
+
+    repo_to_doc_list_map: dict[str, list[DocumentRow]] = {}
+    # sort order is ascending because we want to get the oldest documents first
+    existing_docs: list[DocumentRow] = fetch_all_existing_docs_fn(
+        sort_order=SortOrder.ASC
+    )
+    logger.info(f"Found {len(existing_docs)} documents to check")
+    for doc in existing_docs:
+        try:
+            doc_metadata = DocMetadata.model_validate_json(json.dumps(doc.doc_metadata))
+            if doc_metadata.repo not in repo_to_doc_list_map:
+                repo_to_doc_list_map[doc_metadata.repo] = []
+            repo_to_doc_list_map[doc_metadata.repo].append(doc)
+        except Exception as e:
+            logger.error(f"Failed to parse doc metadata: {e} for doc {doc.id}")
+            continue
+    logger.info(f"Found {len(repo_to_doc_list_map)} documents to check")
+    # Process each repository individually
+    for repo in repos:
+        try:
+            logger.info(f"Processing repository: {repo.id} (name: {repo.name})")
+            repo_doc_list: list[DocumentRow] = repo_to_doc_list_map.get(
+                repo.full_name, []
+            )
+            if not repo_doc_list:
+                logger.warning(
+                    f"No documents found for repository {repo.id} ({repo.name})"
+                )
+                continue
+
+            current_external_group_ids = repo_doc_list[0].external_user_group_ids or []
+            # Check if repository has any permission changes
+            has_changes = _check_repository_for_changes(
+                repo=repo,
+                github_client=github_connector.github_client,
+                current_external_group_ids=current_external_group_ids,
+            )
+
+            if has_changes:
+                logger.info(
+                    f"Repository {repo.id} ({repo.name}) has changes, updating documents"
+                )
+
+                # Get new external access permissions for this repository
+                new_external_access = get_external_access_permission(
+                    repo, github_connector.github_client
+                )
+
+                logger.info(
+                    f"Found {len(repo_doc_list)} documents for repository {repo.full_name}"
+                )
+
+                # Yield updated external access for each document
+                for doc in repo_doc_list:
+                    if callback:
+                        callback.progress(GITHUB_DOC_SYNC_LABEL, 1)
+
+                    yield DocExternalAccess(
+                        doc_id=doc.id,
+                        external_access=new_external_access,
+                    )
+            else:
+                logger.info(
+                    f"Repository {repo.id} ({repo.name}) has no changes, skipping"
+                )
+        except Exception as e:
+            logger.error(f"Error processing repository {repo.id} ({repo.name}): {e}")
+
+    logger.info(f"GitHub document sync completed for CC pair ID: {cc_pair.id}")
+
+
+def _check_repository_for_changes(
+    repo: Repository,
+    github_client: Github,
+    current_external_group_ids: list[str],
+) -> bool:
+    """
+    Check if repository has any permission changes (visibility or team updates).
+    """
+    logger.info(f"Checking repository {repo.id} ({repo.name}) for changes")
+
+    # Check for repository visibility changes using the sample document data
+    if _is_repo_visibility_changed_from_groups(
+        repo=repo,
+        current_external_group_ids=current_external_group_ids,
+    ):
+        logger.info(f"Repository {repo.id} ({repo.name}) has visibility changes")
+        return True
+
+    # Check for team membership changes if repository is private
+    if get_repository_visibility(
+        repo
+    ) == GitHubVisibility.PRIVATE and _teams_updated_from_groups(
+        repo=repo,
+        github_client=github_client,
+        current_external_group_ids=current_external_group_ids,
+    ):
+        logger.info(f"Repository {repo.id} ({repo.name}) has team changes")
+        return True
+
+    logger.info(f"Repository {repo.id} ({repo.name}) has no changes")
+    return False
+
+
+def _is_repo_visibility_changed_from_groups(
+    repo: Repository,
+    current_external_group_ids: list[str],
+) -> bool:
+    """
+    Check if repository visibility has changed by analyzing existing external group IDs.
+
+    Args:
+        repo: GitHub repository object
+        current_external_group_ids: List of external group IDs from existing document
+
+    Returns:
+        True if visibility has changed
+    """
+    current_repo_visibility = get_repository_visibility(repo)
+    logger.info(f"Current repository visibility: {current_repo_visibility.value}")
+
+    # Build expected group IDs for current visibility
+    collaborators_group_id = build_ext_group_name_for_onyx(
+        source=DocumentSource.GITHUB,
+        ext_group_name=form_collaborators_group_id(repo.id),
+    )
+
+    org_group_id = None
+    if repo.organization:
+        org_group_id = build_ext_group_name_for_onyx(
+            source=DocumentSource.GITHUB,
+            ext_group_name=form_organization_group_id(repo.organization.id),
+        )
+
+    # Determine existing visibility from group IDs
+    has_collaborators_group = collaborators_group_id in current_external_group_ids
+    has_org_group = org_group_id and org_group_id in current_external_group_ids
+
+    if has_collaborators_group:
+        existing_repo_visibility = GitHubVisibility.PRIVATE
+    elif has_org_group:
+        existing_repo_visibility = GitHubVisibility.INTERNAL
+    else:
+        existing_repo_visibility = GitHubVisibility.PUBLIC
+
+    logger.info(f"Inferred existing visibility: {existing_repo_visibility.value}")
+
+    visibility_changed = existing_repo_visibility != current_repo_visibility
+    if visibility_changed:
+        logger.info(
+            f"Visibility changed for repo {repo.id} ({repo.name}): "
+            f"{existing_repo_visibility.value} -> {current_repo_visibility.value}"
+        )
+
+    return visibility_changed
+
+
+def _teams_updated_from_groups(
+    repo: Repository,
+    github_client: Github,
+    current_external_group_ids: list[str],
+) -> bool:
+    """
+    Check if repository team memberships have changed using existing group IDs.
+    """
+    # Fetch current team slugs for the repository
+    current_teams = fetch_repository_team_slugs(repo=repo, github_client=github_client)
+    logger.info(
+        f"Current teams for repository {repo.id} (name: {repo.name}): {current_teams}"
+    )
+
+    # Build group IDs to exclude from team comparison (non-team groups)
+    collaborators_group_id = build_ext_group_name_for_onyx(
+        source=DocumentSource.GITHUB,
+        ext_group_name=form_collaborators_group_id(repo.id),
+    )
+    outside_collaborators_group_id = build_ext_group_name_for_onyx(
+        source=DocumentSource.GITHUB,
+        ext_group_name=form_outside_collaborators_group_id(repo.id),
+    )
+    non_team_group_ids = {collaborators_group_id, outside_collaborators_group_id}
+
+    # Extract existing team IDs from current external group IDs
+    existing_team_ids = set()
+    for group_id in current_external_group_ids:
+        # Skip all non-team groups, keep only team groups
+        if group_id not in non_team_group_ids:
+            existing_team_ids.add(group_id)
+
+    # Note: existing_team_ids from DB are already prefixed (e.g., "github__team-slug")
+    # but current_teams from API are raw team slugs, so we need to add the prefix
+    current_team_ids = set()
+    for team_slug in current_teams:
+        team_group_id = build_ext_group_name_for_onyx(
+            source=DocumentSource.GITHUB,
+            ext_group_name=team_slug,
+        )
+        current_team_ids.add(team_group_id)
+
+    logger.info(
+        f"Existing team IDs: {existing_team_ids}, Current team IDs: {current_team_ids}"
+    )
+
+    # Compare actual team IDs to detect changes
+    teams_changed = current_team_ids != existing_team_ids
+    if teams_changed:
+        logger.info(
+            f"Team changes detected for repo {repo.id} (name: {repo.name}): "
+            f"existing={existing_team_ids}, current={current_team_ids}"
+        )
+
+    return teams_changed

backend/ee/onyx/external_permissions/github/group_sync.py

@@ -0,0 +1,46 @@
+from collections.abc import Generator
+
+from github import Repository
+
+from ee.onyx.db.external_perm import ExternalUserGroup
+from ee.onyx.external_permissions.github.utils import get_external_user_group
+from onyx.connectors.github.connector import GithubConnector
+from onyx.db.models import ConnectorCredentialPair
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+def github_group_sync(
+    tenant_id: str,
+    cc_pair: ConnectorCredentialPair,
+) -> Generator[ExternalUserGroup, None, None]:
+    github_connector: GithubConnector = GithubConnector(
+        **cc_pair.connector.connector_specific_config
+    )
+    github_connector.load_credentials(cc_pair.credential.credential_json)
+    if not github_connector.github_client:
+        raise ValueError("github_client is required")
+
+    logger.info("Starting GitHub group sync...")
+    repos: list[Repository.Repository] = []
+    if github_connector.repositories:
+        if "," in github_connector.repositories:
+            # Multiple repositories specified
+            repos = github_connector.get_github_repos(github_connector.github_client)
+        else:
+            # Single repository (backward compatibility)
+            repos = [github_connector.get_github_repo(github_connector.github_client)]
+    else:
+        # All repositories
+        repos = github_connector.get_all_repos(github_connector.github_client)
+
+    for repo in repos:
+        try:
+            for external_group in get_external_user_group(
+                repo, github_connector.github_client
+            ):
+                logger.info(f"External group: {external_group}")
+                yield external_group
+        except Exception as e:
+            logger.error(f"Error processing repository {repo.id} ({repo.name}): {e}")

backend/ee/onyx/external_permissions/github/utils.py

@@ -0,0 +1,488 @@
+from collections.abc import Callable
+from enum import Enum
+from typing import List
+from typing import Optional
+from typing import Tuple
+from typing import TypeVar
+
+from github import Github
+from github import RateLimitExceededException
+from github.GithubException import GithubException
+from github.NamedUser import NamedUser
+from github.Organization import Organization
+from github.PaginatedList import PaginatedList
+from github.Repository import Repository
+from github.Team import Team
+from pydantic import BaseModel
+
+from ee.onyx.db.external_perm import ExternalUserGroup
+from onyx.access.models import ExternalAccess
+from onyx.access.utils import build_ext_group_name_for_onyx
+from onyx.configs.constants import DocumentSource
+from onyx.connectors.github.rate_limit_utils import sleep_after_rate_limit_exception
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+class GitHubVisibility(Enum):
+    """GitHub repository visibility options."""
+
+    PUBLIC = "public"
+    PRIVATE = "private"
+    INTERNAL = "internal"
+
+
+MAX_RETRY_COUNT = 3
+
+T = TypeVar("T")
+
+# Higher-order function to wrap GitHub operations with retry and exception handling
+
+
+def _run_with_retry(
+    operation: Callable[[], T],
+    description: str,
+    github_client: Github,
+    retry_count: int = 0,
+) -> Optional[T]:
+    """Execute a GitHub operation with retry on rate limit and exception handling."""
+    logger.debug(f"Starting operation '{description}', attempt {retry_count + 1}")
+    try:
+        result = operation()
+        logger.debug(f"Operation '{description}' completed successfully")
+        return result
+    except RateLimitExceededException:
+        if retry_count < MAX_RETRY_COUNT:
+            sleep_after_rate_limit_exception(github_client)
+            logger.warning(
+                f"Rate limit exceeded while {description}. Retrying... "
+                f"(attempt {retry_count + 1}/{MAX_RETRY_COUNT})"
+            )
+            return _run_with_retry(
+                operation, description, github_client, retry_count + 1
+            )
+        else:
+            error_msg = f"Max retries exceeded for {description}"
+            logger.exception(error_msg)
+            raise RuntimeError(error_msg)
+    except GithubException as e:
+        logger.warning(f"GitHub API error during {description}: {e}")
+        return None
+    except Exception as e:
+        logger.exception(f"Unexpected error during {description}: {e}")
+        return None
+
+
+class UserInfo(BaseModel):
+    """Represents a GitHub user with their basic information."""
+
+    login: str
+    name: Optional[str] = None
+    email: Optional[str] = None
+
+
+class TeamInfo(BaseModel):
+    """Represents a GitHub team with its members."""
+
+    name: str
+    slug: str
+    members: List[UserInfo]
+
+
+def _fetch_organization_members(
+    github_client: Github, org_name: str, retry_count: int = 0
+) -> List[UserInfo]:
+    """Fetch all organization members including owners and regular members."""
+    org_members: List[UserInfo] = []
+    logger.info(f"Fetching organization members for {org_name}")
+
+    org = _run_with_retry(
+        lambda: github_client.get_organization(org_name),
+        f"get organization {org_name}",
+        github_client,
+    )
+    if not org:
+        logger.error(f"Failed to fetch organization {org_name}")
+        raise RuntimeError(f"Failed to fetch organization {org_name}")
+
+    member_objs: PaginatedList[NamedUser] | list[NamedUser] = (
+        _run_with_retry(
+            lambda: org.get_members(filter_="all"),
+            f"get members for organization {org_name}",
+            github_client,
+        )
+        or []
+    )
+
+    for member in member_objs:
+        user_info = UserInfo(login=member.login, name=member.name, email=member.email)
+        org_members.append(user_info)
+
+    logger.info(f"Fetched {len(org_members)} members for organization {org_name}")
+    return org_members
+
+
+def _fetch_repository_teams_detailed(
+    repo: Repository, github_client: Github, retry_count: int = 0
+) -> List[TeamInfo]:
+    """Fetch teams with access to the repository and their members."""
+    teams_data: List[TeamInfo] = []
+    logger.info(f"Fetching teams for repository {repo.full_name}")
+
+    team_objs: PaginatedList[Team] | list[Team] = (
+        _run_with_retry(
+            lambda: repo.get_teams(),
+            f"get teams for repository {repo.full_name}",
+            github_client,
+        )
+        or []
+    )
+
+    for team in team_objs:
+        logger.info(
+            f"Processing team {team.name} (slug: {team.slug}) for repository {repo.full_name}"
+        )
+
+        members: PaginatedList[NamedUser] | list[NamedUser] = (
+            _run_with_retry(
+                lambda: team.get_members(),
+                f"get members for team {team.name}",
+                github_client,
+            )
+            or []
+        )
+
+        team_members = []
+        for m in members:
+            user_info = UserInfo(login=m.login, name=m.name, email=m.email)
+            team_members.append(user_info)
+
+        team_info = TeamInfo(name=team.name, slug=team.slug, members=team_members)
+        teams_data.append(team_info)
+        logger.info(f"Team {team.name} has {len(team_members)} members")
+
+    logger.info(f"Fetched {len(teams_data)} teams for repository {repo.full_name}")
+    return teams_data
+
+
+def fetch_repository_team_slugs(
+    repo: Repository, github_client: Github, retry_count: int = 0
+) -> List[str]:
+    """Fetch team slugs with access to the repository."""
+    logger.info(f"Fetching team slugs for repository {repo.full_name}")
+    teams_data: List[str] = []
+
+    team_objs: PaginatedList[Team] | list[Team] = (
+        _run_with_retry(
+            lambda: repo.get_teams(),
+            f"get teams for repository {repo.full_name}",
+            github_client,
+        )
+        or []
+    )
+
+    for team in team_objs:
+        teams_data.append(team.slug)
+
+    logger.info(f"Fetched {len(teams_data)} team slugs for repository {repo.full_name}")
+    return teams_data
+
+
+def _get_collaborators_and_outside_collaborators(
+    github_client: Github,
+    repo: Repository,
+) -> Tuple[List[UserInfo], List[UserInfo]]:
+    """Fetch and categorize collaborators into regular and outside collaborators."""
+    collaborators: List[UserInfo] = []
+    outside_collaborators: List[UserInfo] = []
+    logger.info(f"Fetching collaborators for repository {repo.full_name}")
+
+    repo_collaborators: PaginatedList[NamedUser] | list[NamedUser] = (
+        _run_with_retry(
+            lambda: repo.get_collaborators(),
+            f"get collaborators for repository {repo.full_name}",
+            github_client,
+        )
+        or []
+    )
+
+    for collaborator in repo_collaborators:
+        is_outside = False
+
+        # Check if collaborator is outside the organization
+        if repo.organization:
+            org: Organization | None = _run_with_retry(
+                lambda: github_client.get_organization(repo.organization.login),
+                f"get organization {repo.organization.login}",
+                github_client,
+            )
+
+            if org is not None:
+                org_obj = org
+                membership = _run_with_retry(
+                    lambda: org_obj.has_in_members(collaborator),
+                    f"check membership for {collaborator.login} in org {org_obj.login}",
+                    github_client,
+                )
+                is_outside = membership is not None and not membership
+
+        info = UserInfo(
+            login=collaborator.login, name=collaborator.name, email=collaborator.email
+        )
+        if repo.organization and is_outside:
+            outside_collaborators.append(info)
+        else:
+            collaborators.append(info)
+
+    logger.info(
+        f"Categorized {len(collaborators)} regular and {len(outside_collaborators)} outside collaborators for {repo.full_name}"
+    )
+    return collaborators, outside_collaborators
+
+
+def form_collaborators_group_id(repository_id: int) -> str:
+    """Generate group ID for repository collaborators."""
+    if not repository_id:
+        logger.exception("Repository ID is required to generate collaborators group ID")
+        raise ValueError("Repository ID must be set to generate group ID.")
+    group_id = f"{repository_id}_collaborators"
+    return group_id
+
+
+def form_organization_group_id(organization_id: int) -> str:
+    """Generate group ID for organization using organization ID."""
+    if not organization_id:
+        logger.exception(
+            "Organization ID is required to generate organization group ID"
+        )
+        raise ValueError("Organization ID must be set to generate group ID.")
+    group_id = f"{organization_id}_organization"
+    return group_id
+
+
+def form_outside_collaborators_group_id(repository_id: int) -> str:
+    """Generate group ID for outside collaborators."""
+    if not repository_id:
+        logger.exception(
+            "Repository ID is required to generate outside collaborators group ID"
+        )
+        raise ValueError("Repository ID must be set to generate group ID.")
+    group_id = f"{repository_id}_outside_collaborators"
+    return group_id
+
+
+def get_repository_visibility(repo: Repository) -> GitHubVisibility:
+    """
+    Get the visibility of a repository.
+    Returns GitHubVisibility enum member.
+    """
+    if hasattr(repo, "visibility"):
+        visibility = repo.visibility
+        logger.info(
+            f"Repository {repo.full_name} visibility from attribute: {visibility}"
+        )
+        try:
+            return GitHubVisibility(visibility)
+        except ValueError:
+            logger.warning(
+                f"Unknown visibility '{visibility}' for repo {repo.full_name}, defaulting to private"
+            )
+            return GitHubVisibility.PRIVATE
+
+    logger.info(f"Repository {repo.full_name} is private")
+    return GitHubVisibility.PRIVATE
+
+
+def get_external_access_permission(
+    repo: Repository, github_client: Github, add_prefix: bool = False
+) -> ExternalAccess:
+    """
+    Get the external access permission for a repository.
+    Uses group-based permissions for efficiency and scalability.
+
+    add_prefix: When this method is called during the initial permission sync via the connector,
+                the group ID isn't prefixed with the source while inserting the document record.
+                So in that case, set add_prefix to True, allowing the method itself to handle
+                prefixing. However, when the same method is invoked from doc_sync, our system
+                already adds the prefix to the group ID while processing the ExternalAccess object.
+    """
+    # We maintain collaborators, and outside collaborators as two separate groups
+    # instead of adding individual user emails to ExternalAccess.external_user_emails for two reasons:
+    # 1. Changes in repo collaborators (additions/removals) would require updating all documents.
+    # 2. Repo permissions can change without updating the repo's updated_at timestamp,
+    #    forcing full permission syncs for all documents every time, which is inefficient.
+
+    repo_visibility = get_repository_visibility(repo)
+    logger.info(
+        f"Generating ExternalAccess for {repo.full_name}: visibility={repo_visibility.value}"
+    )
+
+    if repo_visibility == GitHubVisibility.PUBLIC:
+        logger.info(
+            f"Repository {repo.full_name} is public - allowing access to all users"
+        )
+        return ExternalAccess(
+            external_user_emails=set(),
+            external_user_group_ids=set(),
+            is_public=True,
+        )
+    elif repo_visibility == GitHubVisibility.PRIVATE:
+        logger.info(
+            f"Repository {repo.full_name} is private - setting up restricted access"
+        )
+
+        collaborators_group_id = form_collaborators_group_id(repo.id)
+        outside_collaborators_group_id = form_outside_collaborators_group_id(repo.id)
+        if add_prefix:
+            collaborators_group_id = build_ext_group_name_for_onyx(
+                source=DocumentSource.GITHUB,
+                ext_group_name=collaborators_group_id,
+            )
+            outside_collaborators_group_id = build_ext_group_name_for_onyx(
+                source=DocumentSource.GITHUB,
+                ext_group_name=outside_collaborators_group_id,
+            )
+        group_ids = {collaborators_group_id, outside_collaborators_group_id}
+
+        team_slugs = fetch_repository_team_slugs(repo, github_client)
+        if add_prefix:
+            team_slugs = [
+                build_ext_group_name_for_onyx(
+                    source=DocumentSource.GITHUB,
+                    ext_group_name=slug,
+                )
+                for slug in team_slugs
+            ]
+        group_ids.update(team_slugs)
+
+        logger.info(f"ExternalAccess groups for {repo.full_name}: {group_ids}")
+        return ExternalAccess(
+            external_user_emails=set(),
+            external_user_group_ids=group_ids,
+            is_public=False,
+        )
+    else:
+        # Internal repositories - accessible to organization members
+        logger.info(
+            f"Repository {repo.full_name} is internal - accessible to org members"
+        )
+        org_group_id = form_organization_group_id(repo.organization.id)
+        if add_prefix:
+            org_group_id = build_ext_group_name_for_onyx(
+                source=DocumentSource.GITHUB,
+                ext_group_name=org_group_id,
+            )
+        group_ids = {org_group_id}
+        logger.info(f"ExternalAccess groups for {repo.full_name}: {group_ids}")
+        return ExternalAccess(
+            external_user_emails=set(),
+            external_user_group_ids=group_ids,
+            is_public=False,
+        )
+
+
+def get_external_user_group(
+    repo: Repository, github_client: Github
+) -> list[ExternalUserGroup]:
+    """
+    Get the external user group for a repository.
+    Creates ExternalUserGroup objects with actual user emails for each permission group.
+    """
+    repo_visibility = get_repository_visibility(repo)
+    logger.info(
+        f"Generating ExternalUserGroups for {repo.full_name}: visibility={repo_visibility.value}"
+    )
+
+    if repo_visibility == GitHubVisibility.PRIVATE:
+        logger.info(f"Processing private repository {repo.full_name}")
+
+        collaborators, outside_collaborators = (
+            _get_collaborators_and_outside_collaborators(github_client, repo)
+        )
+        teams = _fetch_repository_teams_detailed(repo, github_client)
+        external_user_groups = []
+
+        user_emails = set()
+        for collab in collaborators:
+            if collab.email:
+                user_emails.add(collab.email)
+            else:
+                logger.error(f"Collaborator {collab.login} has no email")
+
+        if user_emails:
+            collaborators_group = ExternalUserGroup(
+                id=form_collaborators_group_id(repo.id),
+                user_emails=list(user_emails),
+            )
+            external_user_groups.append(collaborators_group)
+            logger.info(f"Created collaborators group with {len(user_emails)} emails")
+
+        # Create group for outside collaborators
+        user_emails = set()
+        for collab in outside_collaborators:
+            if collab.email:
+                user_emails.add(collab.email)
+            else:
+                logger.error(f"Outside collaborator {collab.login} has no email")
+
+        if user_emails:
+            outside_collaborators_group = ExternalUserGroup(
+                id=form_outside_collaborators_group_id(repo.id),
+                user_emails=list(user_emails),
+            )
+            external_user_groups.append(outside_collaborators_group)
+            logger.info(
+                f"Created outside collaborators group with {len(user_emails)} emails"
+            )
+
+        # Create groups for teams
+        for team in teams:
+            user_emails = set()
+            for member in team.members:
+                if member.email:
+                    user_emails.add(member.email)
+                else:
+                    logger.error(f"Team member {member.login} has no email")
+
+            if user_emails:
+                team_group = ExternalUserGroup(
+                    id=team.slug,
+                    user_emails=list(user_emails),
+                )
+                external_user_groups.append(team_group)
+                logger.info(
+                    f"Created team group {team.name} with {len(user_emails)} emails"
+                )
+
+        logger.info(
+            f"Created {len(external_user_groups)} ExternalUserGroups for private repository {repo.full_name}"
+        )
+        return external_user_groups
+
+    if repo_visibility == GitHubVisibility.INTERNAL:
+        logger.info(f"Processing internal repository {repo.full_name}")
+
+        org_group_id = form_organization_group_id(repo.organization.id)
+        org_members = _fetch_organization_members(
+            github_client, repo.organization.login
+        )
+
+        user_emails = set()
+        for member in org_members:
+            if member.email:
+                user_emails.add(member.email)
+            else:
+                logger.error(f"Org member {member.login} has no email")
+
+        org_group = ExternalUserGroup(
+            id=org_group_id,
+            user_emails=list(user_emails),
+        )
+        logger.info(
+            f"Created organization group with {len(user_emails)} emails for internal repository {repo.full_name}"
+        )
+        return [org_group]
+
+    logger.info(f"Repository {repo.full_name} is public - no user groups needed")
+    return []

backend/ee/onyx/external_permissions/gmail/doc_sync.py

@@ -3,6 +3,7 @@ from datetime import datetime
 from datetime import timezone
 
 from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from onyx.access.models import DocExternalAccess
 from onyx.connectors.gmail.connector import GmailConnector
 from onyx.connectors.interfaces import GenerateSlimDocumentOutput
@@ -35,6 +36,7 @@ def _get_slim_doc_generator(
 def gmail_doc_sync(
     cc_pair: ConnectorCredentialPair,
     fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: IndexingHeartbeatInterface | None,
 ) -> Generator[DocExternalAccess, None, None]:
     """

backend/ee/onyx/external_permissions/google_drive/doc_sync.py

@@ -8,6 +8,7 @@ from ee.onyx.external_permissions.google_drive.permission_retrieval import (
     get_permissions_by_ids,
 )
 from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from onyx.access.models import DocExternalAccess
 from onyx.access.models import ExternalAccess
 from onyx.connectors.google_drive.connector import GoogleDriveConnector
@@ -169,6 +170,7 @@ def get_external_access_for_raw_gdrive_file(
 def gdrive_doc_sync(
     cc_pair: ConnectorCredentialPair,
     fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: IndexingHeartbeatInterface | None,
 ) -> Generator[DocExternalAccess, None, None]:
     """

backend/ee/onyx/external_permissions/jira/doc_sync.py

@@ -1,6 +1,7 @@
 from collections.abc import Generator
 
 from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from ee.onyx.external_permissions.utils import generic_doc_sync
 from onyx.access.models import DocExternalAccess
 from onyx.configs.constants import DocumentSource
@@ -17,6 +18,7 @@ JIRA_DOC_SYNC_TAG = "jira_doc_sync"
 def jira_doc_sync(
     cc_pair: ConnectorCredentialPair,
     fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: IndexingHeartbeatInterface | None = None,
 ) -> Generator[DocExternalAccess, None, None]:
     jira_connector = JiraConnector(
@@ -26,7 +28,7 @@ def jira_doc_sync(
 
     yield from generic_doc_sync(
         cc_pair=cc_pair,
-        fetch_all_existing_docs_fn=fetch_all_existing_docs_fn,
+        fetch_all_existing_docs_ids_fn=fetch_all_existing_docs_ids_fn,
         callback=callback,
         doc_source=DocumentSource.JIRA,
         slim_connector=jira_connector,

backend/ee/onyx/external_permissions/perm_sync_types.py

@@ -2,27 +2,45 @@ from collections.abc import Callable
 from collections.abc import Generator
 from typing import Optional
 from typing import Protocol
-from typing import TYPE_CHECKING
 
+from ee.onyx.db.external_perm import ExternalUserGroup  # noqa
+from onyx.access.models import DocExternalAccess  # noqa
 from onyx.context.search.models import InferenceChunk
-
-# Avoid circular imports
-if TYPE_CHECKING:
-    from ee.onyx.db.external_perm import ExternalUserGroup  # noqa
-    from onyx.access.models import DocExternalAccess  # noqa
-    from onyx.db.models import ConnectorCredentialPair  # noqa
-    from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface  # noqa
+from onyx.db.models import ConnectorCredentialPair  # noqa
+from onyx.db.utils import DocumentRow
+from onyx.db.utils import SortOrder
+from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface  # noqa
 
 
 class FetchAllDocumentsFunction(Protocol):
-    """Protocol for a function that fetches all document IDs for a connector credential pair."""
+    """Protocol for a function that fetches documents for a connector credential pair.
 
-    def __call__(self) -> list[str]:
+    This protocol defines the interface for functions that retrieve documents
+    from the database, typically used in permission synchronization workflows.
+    """
+
+    def __call__(
+        self,
+        sort_order: SortOrder | None,
+    ) -> list[DocumentRow]:
         """
-        Returns a list of document IDs for a connector credential pair.
+        Fetches documents for a connector credential pair.
+        """
+        ...
 
-        This is typically used to determine which documents should no longer be
-        accessible during the document sync process.
+
+class FetchAllDocumentsIdsFunction(Protocol):
+    """Protocol for a function that fetches document IDs for a connector credential pair.
+
+    This protocol defines the interface for functions that retrieve document IDs
+    from the database, typically used in permission synchronization workflows.
+    """
+
+    def __call__(
+        self,
+    ) -> list[str]:
+        """
+        Fetches document IDs for a connector credential pair.
         """
         ...
 
@@ -30,19 +48,20 @@ class FetchAllDocumentsFunction(Protocol):
 # Defining the input/output types for the sync functions
 DocSyncFuncType = Callable[
     [
-        "ConnectorCredentialPair",
+        ConnectorCredentialPair,
         FetchAllDocumentsFunction,
-        Optional["IndexingHeartbeatInterface"],
+        FetchAllDocumentsIdsFunction,
+        Optional[IndexingHeartbeatInterface],
     ],
-    Generator["DocExternalAccess", None, None],
+    Generator[DocExternalAccess, None, None],
 ]
 
 GroupSyncFuncType = Callable[
     [
         str,  # tenant_id
-        "ConnectorCredentialPair",  # cc_pair
+        ConnectorCredentialPair,  # cc_pair
     ],
-    Generator["ExternalUserGroup", None, None],
+    Generator[ExternalUserGroup, None, None],
 ]
 
 # list of chunks to be censored and the user email. returns censored chunks

backend/ee/onyx/external_permissions/sharepoint/doc_sync.py

@@ -0,0 +1,36 @@
+from collections.abc import Generator
+
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
+from ee.onyx.external_permissions.utils import generic_doc_sync
+from onyx.access.models import DocExternalAccess
+from onyx.configs.constants import DocumentSource
+from onyx.connectors.sharepoint.connector import SharepointConnector
+from onyx.db.models import ConnectorCredentialPair
+from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+SHAREPOINT_DOC_SYNC_TAG = "sharepoint_doc_sync"
+
+
+def sharepoint_doc_sync(
+    cc_pair: ConnectorCredentialPair,
+    fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
+    callback: IndexingHeartbeatInterface | None = None,
+) -> Generator[DocExternalAccess, None, None]:
+    sharepoint_connector = SharepointConnector(
+        **cc_pair.connector.connector_specific_config,
+    )
+    sharepoint_connector.load_credentials(cc_pair.credential.credential_json)
+
+    yield from generic_doc_sync(
+        cc_pair=cc_pair,
+        fetch_all_existing_docs_ids_fn=fetch_all_existing_docs_ids_fn,
+        callback=callback,
+        doc_source=DocumentSource.SHAREPOINT,
+        slim_connector=sharepoint_connector,
+        label=SHAREPOINT_DOC_SYNC_TAG,
+    )

backend/ee/onyx/external_permissions/sharepoint/group_sync.py

@@ -0,0 +1,63 @@
+from collections.abc import Generator
+
+from office365.sharepoint.client_context import ClientContext  # type: ignore[import-untyped]
+
+from ee.onyx.db.external_perm import ExternalUserGroup
+from ee.onyx.external_permissions.sharepoint.permission_utils import (
+    get_sharepoint_external_groups,
+)
+from onyx.connectors.sharepoint.connector import acquire_token_for_rest
+from onyx.connectors.sharepoint.connector import SharepointConnector
+from onyx.db.models import ConnectorCredentialPair
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+def sharepoint_group_sync(
+    tenant_id: str,
+    cc_pair: ConnectorCredentialPair,
+) -> Generator[ExternalUserGroup, None, None]:
+    """Sync SharePoint groups and their members"""
+
+    # Get site URLs from connector config
+    connector_config = cc_pair.connector.connector_specific_config
+
+    # Create SharePoint connector instance and load credentials
+    connector = SharepointConnector(**connector_config)
+    connector.load_credentials(cc_pair.credential.credential_json)
+
+    if not connector.msal_app:
+        raise RuntimeError("MSAL app not initialized in connector")
+
+    if not connector.sp_tenant_domain:
+        raise RuntimeError("Tenant domain not initialized in connector")
+
+    # Get site descriptors from connector (either configured sites or all sites)
+    site_descriptors = connector.site_descriptors or connector.fetch_sites()
+
+    if not site_descriptors:
+        raise RuntimeError("No SharePoint sites found for group sync")
+
+    logger.info(f"Processing {len(site_descriptors)} sites for group sync")
+
+    msal_app = connector.msal_app
+    sp_tenant_domain = connector.sp_tenant_domain
+    # Process each site
+    for site_descriptor in site_descriptors:
+        logger.debug(f"Processing site: {site_descriptor.url}")
+
+        # Create client context for the site using connector's MSAL app
+        ctx = ClientContext(site_descriptor.url).with_access_token(
+            lambda: acquire_token_for_rest(msal_app, sp_tenant_domain)
+        )
+
+        # Get external groups for this site
+        external_groups = get_sharepoint_external_groups(ctx, connector.graph_client)
+
+        # Yield each group
+        for group in external_groups:
+            logger.debug(
+                f"Found group: {group.id} with {len(group.user_emails)} members"
+            )
+            yield group

backend/ee/onyx/external_permissions/sharepoint/permission_utils.py

@@ -0,0 +1,684 @@
+import re
+from collections import deque
+from typing import Any
+from urllib.parse import unquote
+from urllib.parse import urlparse
+
+from office365.graph_client import GraphClient  # type: ignore[import-untyped]
+from office365.onedrive.driveitems.driveItem import DriveItem  # type: ignore[import-untyped]
+from office365.runtime.client_request import ClientRequestException  # type: ignore
+from office365.sharepoint.client_context import ClientContext  # type: ignore[import-untyped]
+from office365.sharepoint.permissions.securable_object import RoleAssignmentCollection  # type: ignore[import-untyped]
+from pydantic import BaseModel
+
+from ee.onyx.db.external_perm import ExternalUserGroup
+from onyx.access.models import ExternalAccess
+from onyx.access.utils import build_ext_group_name_for_onyx
+from onyx.configs.constants import DocumentSource
+from onyx.connectors.sharepoint.connector import sleep_and_retry
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+# These values represent different types of SharePoint principals used in permission assignments
+USER_PRINCIPAL_TYPE = 1  # Individual user accounts
+ANONYMOUS_USER_PRINCIPAL_TYPE = 3  # Anonymous/unauthenticated users (public access)
+AZURE_AD_GROUP_PRINCIPAL_TYPE = 4  # Azure Active Directory security groups
+SHAREPOINT_GROUP_PRINCIPAL_TYPE = 8  # SharePoint site groups (local to the site)
+MICROSOFT_DOMAIN = ".onmicrosoft"
+# Limited Access role type, limited access is a travel through permission not a actual permission
+LIMITED_ACCESS_ROLE_TYPES = [1, 9]
+LIMITED_ACCESS_ROLE_NAMES = ["Limited Access", "Web-Only Limited Access"]
+
+
+class SharepointGroup(BaseModel):
+    model_config = {"frozen": True}
+
+    name: str
+    login_name: str
+    principal_type: int
+
+
+class GroupsResult(BaseModel):
+    groups_to_emails: dict[str, set[str]]
+    found_public_group: bool
+
+
+def _get_azuread_group_guid_by_name(
+    graph_client: GraphClient, group_name: str
+) -> str | None:
+    try:
+        # Search for groups by display name
+        groups = sleep_and_retry(
+            graph_client.groups.filter(f"displayName eq '{group_name}'").get(),
+            "get_azuread_group_guid_by_name",
+        )
+
+        if groups and len(groups) > 0:
+            return groups[0].id
+
+        return None
+
+    except Exception as e:
+        logger.error(f"Failed to get Azure AD group GUID for name {group_name}: {e}")
+        return None
+
+
+def _extract_guid_from_claims_token(claims_token: str) -> str | None:
+
+    try:
+        # Pattern to match GUID in claims token
+        # Claims tokens often have format: c:0o.c|provider|GUID_suffix
+        guid_pattern = r"([0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12})"
+
+        match = re.search(guid_pattern, claims_token, re.IGNORECASE)
+        if match:
+            return match.group(1)
+
+        return None
+
+    except Exception as e:
+        logger.error(f"Failed to extract GUID from claims token {claims_token}: {e}")
+        return None
+
+
+def _get_group_guid_from_identifier(
+    graph_client: GraphClient, identifier: str
+) -> str | None:
+    try:
+        # Check if it's already a GUID
+        guid_pattern = r"^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$"
+        if re.match(guid_pattern, identifier, re.IGNORECASE):
+            return identifier
+
+        # Check if it's a SharePoint claims token
+        if identifier.startswith("c:0") and "|" in identifier:
+            guid = _extract_guid_from_claims_token(identifier)
+            if guid:
+                logger.info(f"Extracted GUID {guid} from claims token {identifier}")
+                return guid
+
+        # Try to search by display name as fallback
+        return _get_azuread_group_guid_by_name(graph_client, identifier)
+
+    except Exception as e:
+        logger.error(f"Failed to get group GUID from identifier {identifier}: {e}")
+        return None
+
+
+def _get_security_group_owners(graph_client: GraphClient, group_id: str) -> list[str]:
+    try:
+        # Get group owners using Graph API
+        group = graph_client.groups[group_id]
+        owners = sleep_and_retry(
+            group.owners.get_all(page_loaded=lambda _: None),
+            "get_security_group_owners",
+        )
+
+        owner_emails: list[str] = []
+        logger.info(f"Owners: {owners}")
+
+        for owner in owners:
+            owner_data = owner.to_json()
+
+            # Extract email from the JSON data
+            mail: str | None = owner_data.get("mail")
+            user_principal_name: str | None = owner_data.get("userPrincipalName")
+
+            # Check if owner is a user and has an email
+            if mail:
+                if MICROSOFT_DOMAIN in mail:
+                    mail = mail.replace(MICROSOFT_DOMAIN, "")
+                owner_emails.append(mail)
+            elif user_principal_name:
+                if MICROSOFT_DOMAIN in user_principal_name:
+                    user_principal_name = user_principal_name.replace(
+                        MICROSOFT_DOMAIN, ""
+                    )
+                owner_emails.append(user_principal_name)
+
+        logger.info(
+            f"Retrieved {len(owner_emails)} owners from security group {group_id}"
+        )
+        return owner_emails
+
+    except Exception as e:
+        logger.error(f"Failed to get security group owners for group {group_id}: {e}")
+        return []
+
+
+def _get_sharepoint_list_item_id(drive_item: DriveItem) -> str | None:
+
+    try:
+        # First try to get the list item directly from the drive item
+        if hasattr(drive_item, "listItem"):
+            list_item = drive_item.listItem
+            if list_item:
+                # Load the list item properties to get the ID
+                sleep_and_retry(list_item.get(), "get_sharepoint_list_item_id")
+                if hasattr(list_item, "id") and list_item.id:
+                    return str(list_item.id)
+
+        # The SharePoint list item ID is typically available in the sharepointIds property
+        sharepoint_ids = getattr(drive_item, "sharepoint_ids", None)
+        if sharepoint_ids and hasattr(sharepoint_ids, "listItemId"):
+            return sharepoint_ids.listItemId
+
+        # Alternative: try to get it from the properties
+        properties = getattr(drive_item, "properties", None)
+        if properties:
+            # Sometimes the SharePoint list item ID is in the properties
+            for prop_name, prop_value in properties.items():
+                if "listitemid" in prop_name.lower():
+                    return str(prop_value)
+
+        return None
+    except Exception as e:
+        logger.error(
+            f"Error getting SharePoint list item ID for item {drive_item.id}: {e}"
+        )
+        raise e
+
+
+def _is_public_item(drive_item: DriveItem) -> bool:
+    is_public = False
+    try:
+        permissions = sleep_and_retry(
+            drive_item.permissions.get_all(page_loaded=lambda _: None), "is_public_item"
+        )
+        for permission in permissions:
+            if permission.link and (
+                permission.link.scope == "anonymous"
+                or permission.link.scope == "organization"
+            ):
+                is_public = True
+                break
+        return is_public
+    except Exception as e:
+        logger.error(f"Failed to check if item {drive_item.id} is public: {e}")
+        return False
+
+
+def _is_public_login_name(login_name: str) -> bool:
+    # Patterns that indicate public access
+    # This list is derived from the below link
+    # https://learn.microsoft.com/en-us/answers/questions/2085339/guid-in-the-loginname-of-site-user-everyone-except
+    public_login_patterns: list[str] = [
+        "c:0-.f|rolemanager|spo-grid-all-users/",
+        "c:0(.s|true",
+    ]
+    for pattern in public_login_patterns:
+        if pattern in login_name:
+            logger.info(f"Login name {login_name} is public")
+            return True
+    return False
+
+
+# AD groups allows same display name for multiple groups, so we need to add the GUID to the name
+def _get_group_name_with_suffix(
+    login_name: str, group_name: str, graph_client: GraphClient
+) -> str:
+    ad_group_suffix = _get_group_guid_from_identifier(graph_client, login_name)
+    return f"{group_name}_{ad_group_suffix}"
+
+
+def _get_sharepoint_groups(
+    client_context: ClientContext, group_name: str, graph_client: GraphClient
+) -> tuple[set[SharepointGroup], set[str]]:
+
+    groups: set[SharepointGroup] = set()
+    user_emails: set[str] = set()
+
+    def process_users(users: list[Any]) -> None:
+        nonlocal groups, user_emails
+
+        for user in users:
+            logger.debug(f"User: {user.to_json()}")
+            if user.principal_type == USER_PRINCIPAL_TYPE and hasattr(
+                user, "user_principal_name"
+            ):
+                if user.user_principal_name:
+                    email = user.user_principal_name
+                    if MICROSOFT_DOMAIN in email:
+                        email = email.replace(MICROSOFT_DOMAIN, "")
+                    user_emails.add(email)
+                else:
+                    logger.warning(
+                        f"User don't have a user principal name: {user.login_name}"
+                    )
+            elif user.principal_type in [
+                AZURE_AD_GROUP_PRINCIPAL_TYPE,
+                SHAREPOINT_GROUP_PRINCIPAL_TYPE,
+            ]:
+                name = user.title
+                if user.principal_type == AZURE_AD_GROUP_PRINCIPAL_TYPE:
+                    name = _get_group_name_with_suffix(
+                        user.login_name, name, graph_client
+                    )
+                groups.add(
+                    SharepointGroup(
+                        login_name=user.login_name,
+                        principal_type=user.principal_type,
+                        name=name,
+                    )
+                )
+
+    group = client_context.web.site_groups.get_by_name(group_name)
+    sleep_and_retry(
+        group.users.get_all(page_loaded=process_users), "get_sharepoint_groups"
+    )
+
+    return groups, user_emails
+
+
+def _get_azuread_groups(
+    graph_client: GraphClient, group_name: str
+) -> tuple[set[SharepointGroup], set[str]]:
+
+    group_id = _get_group_guid_from_identifier(graph_client, group_name)
+    if not group_id:
+        logger.error(f"Failed to get Azure AD group GUID for name {group_name}")
+        return set(), set()
+    group = graph_client.groups[group_id]
+    groups: set[SharepointGroup] = set()
+    user_emails: set[str] = set()
+
+    def process_members(members: list[Any]) -> None:
+        nonlocal groups, user_emails
+
+        for member in members:
+            member_data = member.to_json()
+            logger.debug(f"Member: {member_data}")
+            # Check for user-specific attributes
+            user_principal_name = member_data.get("userPrincipalName")
+            mail = member_data.get("mail")
+            display_name = member_data.get("displayName") or member_data.get(
+                "display_name"
+            )
+
+            # Check object attributes directly (if available)
+            is_user = False
+            is_group = False
+
+            # Users typically have userPrincipalName or mail
+            if user_principal_name or (mail and "@" in str(mail)):
+                is_user = True
+            # Groups typically have displayName but no userPrincipalName
+            elif display_name and not user_principal_name:
+                # Additional check: try to access group-specific properties
+                if (
+                    hasattr(member, "groupTypes")
+                    or member_data.get("groupTypes") is not None
+                ):
+                    is_group = True
+                # Or check if it has an 'id' field typical for groups
+                elif member_data.get("id") and not user_principal_name:
+                    is_group = True
+
+            # Check the object type name (fallback)
+            if not is_user and not is_group:
+                obj_type = type(member).__name__.lower()
+                if "user" in obj_type:
+                    is_user = True
+                elif "group" in obj_type:
+                    is_group = True
+
+            # Process based on identification
+            if is_user:
+                if user_principal_name:
+                    email = user_principal_name
+                    if MICROSOFT_DOMAIN in email:
+                        email = email.replace(MICROSOFT_DOMAIN, "")
+                    user_emails.add(email)
+                elif mail:
+                    email = mail
+                    if MICROSOFT_DOMAIN in email:
+                        email = email.replace(MICROSOFT_DOMAIN, "")
+                    user_emails.add(email)
+                logger.info(f"Added user: {user_principal_name or mail}")
+            elif is_group:
+                if not display_name:
+                    logger.error(f"No display name for group: {member_data.get('id')}")
+                    continue
+                name = _get_group_name_with_suffix(
+                    member_data.get("id", ""), display_name, graph_client
+                )
+                groups.add(
+                    SharepointGroup(
+                        login_name=member_data.get("id", ""),  # Use ID for groups
+                        principal_type=AZURE_AD_GROUP_PRINCIPAL_TYPE,
+                        name=name,
+                    )
+                )
+                logger.info(f"Added group: {name}")
+            else:
+                # Log unidentified members for debugging
+                logger.warning(f"Could not identify member type for: {member_data}")
+
+    sleep_and_retry(
+        group.members.get_all(page_loaded=process_members), "get_azuread_groups"
+    )
+
+    owner_emails = _get_security_group_owners(graph_client, group_id)
+    user_emails.update(owner_emails)
+
+    return groups, user_emails
+
+
+def _get_groups_and_members_recursively(
+    client_context: ClientContext,
+    graph_client: GraphClient,
+    groups: set[SharepointGroup],
+    is_group_sync: bool = False,
+) -> GroupsResult:
+    """
+    Get all groups and their members recursively.
+    """
+    group_queue: deque[SharepointGroup] = deque(groups)
+    visited_groups: set[str] = set()
+    visited_group_name_to_emails: dict[str, set[str]] = {}
+    found_public_group = False
+    while group_queue:
+        group = group_queue.popleft()
+        if group.login_name in visited_groups:
+            continue
+        visited_groups.add(group.login_name)
+        visited_group_name_to_emails[group.name] = set()
+        logger.info(
+            f"Processing group: {group.name} principal type: {group.principal_type}"
+        )
+        if group.principal_type == SHAREPOINT_GROUP_PRINCIPAL_TYPE:
+            group_info, user_emails = _get_sharepoint_groups(
+                client_context, group.login_name, graph_client
+            )
+            visited_group_name_to_emails[group.name].update(user_emails)
+            if group_info:
+                group_queue.extend(group_info)
+        if group.principal_type == AZURE_AD_GROUP_PRINCIPAL_TYPE:
+            try:
+                # if the site is public, we have default groups assigned to it, so we return early
+                if _is_public_login_name(group.login_name):
+                    found_public_group = True
+                    if not is_group_sync:
+                        return GroupsResult(
+                            groups_to_emails={}, found_public_group=True
+                        )
+                    else:
+                        # we don't want to sync public groups, so we skip them
+                        continue
+                group_info, user_emails = _get_azuread_groups(
+                    graph_client, group.login_name
+                )
+                visited_group_name_to_emails[group.name].update(user_emails)
+                if group_info:
+                    group_queue.extend(group_info)
+            except ClientRequestException as e:
+                # If the group is not found, we skip it. There is a chance that group is still referenced
+                # in sharepoint but it is removed from Azure AD. There is no actual documentation on this, but based on
+                # our testing we have seen this happen.
+                if e.response is not None and e.response.status_code == 404:
+                    logger.warning(f"Group {group.login_name} not found")
+                    continue
+                raise e
+
+    return GroupsResult(
+        groups_to_emails=visited_group_name_to_emails,
+        found_public_group=found_public_group,
+    )
+
+
+def get_external_access_from_sharepoint(
+    client_context: ClientContext,
+    graph_client: GraphClient,
+    drive_name: str | None,
+    drive_item: DriveItem | None,
+    site_page: dict[str, Any] | None,
+    add_prefix: bool = False,
+) -> ExternalAccess:
+    """
+    Get external access information from SharePoint.
+    """
+    groups: set[SharepointGroup] = set()
+    user_emails: set[str] = set()
+    group_ids: set[str] = set()
+
+    # Add all members to a processing set first
+    def add_user_and_group_to_sets(
+        role_assignments: RoleAssignmentCollection,
+    ) -> None:
+        nonlocal user_emails, groups
+        for assignment in role_assignments:
+            logger.debug(f"Assignment: {assignment.to_json()}")
+            if assignment.role_definition_bindings:
+                is_limited_access = True
+                for role_definition_binding in assignment.role_definition_bindings:
+                    if (
+                        role_definition_binding.role_type_kind
+                        not in LIMITED_ACCESS_ROLE_TYPES
+                        or role_definition_binding.name not in LIMITED_ACCESS_ROLE_NAMES
+                    ):
+                        is_limited_access = False
+                        break
+
+                # Skip if the role is only Limited Access, because this is not a actual permission its a travel through permission
+                if is_limited_access:
+                    logger.info(
+                        "Skipping assignment because it has only Limited Access role"
+                    )
+                    continue
+            if assignment.member:
+                member = assignment.member
+                if member.principal_type == USER_PRINCIPAL_TYPE and hasattr(
+                    member, "user_principal_name"
+                ):
+                    email = member.user_principal_name
+                    if MICROSOFT_DOMAIN in email:
+                        email = email.replace(MICROSOFT_DOMAIN, "")
+                    user_emails.add(email)
+                elif member.principal_type in [
+                    AZURE_AD_GROUP_PRINCIPAL_TYPE,
+                    SHAREPOINT_GROUP_PRINCIPAL_TYPE,
+                ]:
+                    name = member.title
+                    if member.principal_type == AZURE_AD_GROUP_PRINCIPAL_TYPE:
+                        name = _get_group_name_with_suffix(
+                            member.login_name, name, graph_client
+                        )
+                    groups.add(
+                        SharepointGroup(
+                            login_name=member.login_name,
+                            principal_type=member.principal_type,
+                            name=name,
+                        )
+                    )
+
+    if drive_item and drive_name:
+        # Here we check if the item have have any public links, if so we return early
+        is_public = _is_public_item(drive_item)
+        if is_public:
+            logger.info(f"Item {drive_item.id} is public")
+            return ExternalAccess(
+                external_user_emails=set(),
+                external_user_group_ids=set(),
+                is_public=True,
+            )
+
+        item_id = _get_sharepoint_list_item_id(drive_item)
+
+        if not item_id:
+            raise RuntimeError(
+                f"Failed to get SharePoint list item ID for item {drive_item.id}"
+            )
+
+        if drive_name == "Shared Documents":
+            drive_name = "Documents"
+
+        item = client_context.web.lists.get_by_title(drive_name).items.get_by_id(
+            item_id
+        )
+
+        sleep_and_retry(
+            item.role_assignments.expand(["Member", "RoleDefinitionBindings"]).get_all(
+                page_loaded=add_user_and_group_to_sets,
+            ),
+            "get_external_access_from_sharepoint",
+        )
+    elif site_page:
+        site_url = site_page.get("webUrl")
+        # Prefer server-relative URL to avoid OData filters that break on apostrophes
+        server_relative_url = unquote(urlparse(site_url).path)
+        file_obj = client_context.web.get_file_by_server_relative_url(
+            server_relative_url
+        )
+        item = file_obj.listItemAllFields
+
+        sleep_and_retry(
+            item.role_assignments.expand(["Member", "RoleDefinitionBindings"]).get_all(
+                page_loaded=add_user_and_group_to_sets,
+            ),
+            "get_external_access_from_sharepoint",
+        )
+    else:
+        raise RuntimeError("No drive item or site page provided")
+
+    groups_and_members: GroupsResult = _get_groups_and_members_recursively(
+        client_context, graph_client, groups
+    )
+
+    # If the site is public, w have default groups assigned to it, so we return early
+    if groups_and_members.found_public_group:
+        return ExternalAccess(
+            external_user_emails=set(),
+            external_user_group_ids=set(),
+            is_public=True,
+        )
+
+    for group_name, _ in groups_and_members.groups_to_emails.items():
+        if add_prefix:
+            group_name = build_ext_group_name_for_onyx(
+                group_name, DocumentSource.SHAREPOINT
+            )
+        group_ids.add(group_name.lower())
+
+    logger.info(f"User emails: {len(user_emails)}")
+    logger.info(f"Group IDs: {len(group_ids)}")
+
+    return ExternalAccess(
+        external_user_emails=user_emails,
+        external_user_group_ids=group_ids,
+        is_public=False,
+    )
+
+
+def get_sharepoint_external_groups(
+    client_context: ClientContext, graph_client: GraphClient
+) -> list[ExternalUserGroup]:
+
+    groups: set[SharepointGroup] = set()
+
+    def add_group_to_sets(role_assignments: RoleAssignmentCollection) -> None:
+        nonlocal groups
+        for assignment in role_assignments:
+            if assignment.role_definition_bindings:
+                is_limited_access = True
+                for role_definition_binding in assignment.role_definition_bindings:
+                    if (
+                        role_definition_binding.role_type_kind
+                        not in LIMITED_ACCESS_ROLE_TYPES
+                        or role_definition_binding.name not in LIMITED_ACCESS_ROLE_NAMES
+                    ):
+                        is_limited_access = False
+                        break
+
+                # Skip if the role assignment is only Limited Access, because this is not a actual permission its
+                #  a travel through permission
+                if is_limited_access:
+                    logger.info(
+                        "Skipping assignment because it has only Limited Access role"
+                    )
+                    continue
+            if assignment.member:
+                member = assignment.member
+                if member.principal_type in [
+                    AZURE_AD_GROUP_PRINCIPAL_TYPE,
+                    SHAREPOINT_GROUP_PRINCIPAL_TYPE,
+                ]:
+                    name = member.title
+                    if member.principal_type == AZURE_AD_GROUP_PRINCIPAL_TYPE:
+                        name = _get_group_name_with_suffix(
+                            member.login_name, name, graph_client
+                        )
+
+                    groups.add(
+                        SharepointGroup(
+                            login_name=member.login_name,
+                            principal_type=member.principal_type,
+                            name=name,
+                        )
+                    )
+
+    sleep_and_retry(
+        client_context.web.role_assignments.expand(
+            ["Member", "RoleDefinitionBindings"]
+        ).get_all(page_loaded=add_group_to_sets),
+        "get_sharepoint_external_groups",
+    )
+    groups_and_members: GroupsResult = _get_groups_and_members_recursively(
+        client_context, graph_client, groups, is_group_sync=True
+    )
+
+    # get all Azure AD groups because if any group is assigned to the drive item, we don't want to miss them
+    # We can't assign sharepoint groups to drive items or drives, so we don't need to get all sharepoint groups
+    azure_ad_groups = sleep_and_retry(
+        graph_client.groups.get_all(page_loaded=lambda _: None),
+        "get_sharepoint_external_groups:get_azure_ad_groups",
+    )
+    logger.info(f"Azure AD Groups: {len(azure_ad_groups)}")
+    identified_groups: set[str] = set(groups_and_members.groups_to_emails.keys())
+    ad_groups_to_emails: dict[str, set[str]] = {}
+    for group in azure_ad_groups:
+        # If the group is already identified, we don't need to get the members
+        if group.display_name in identified_groups:
+            continue
+        # AD groups allows same display name for multiple groups, so we need to add the GUID to the name
+        name = group.display_name
+        name = _get_group_name_with_suffix(group.id, name, graph_client)
+
+        members = sleep_and_retry(
+            group.members.get_all(page_loaded=lambda _: None),
+            "get_sharepoint_external_groups:get_azure_ad_groups:get_members",
+        )
+        for member in members:
+            member_data = member.to_json()
+            user_principal_name = member_data.get("userPrincipalName")
+            mail = member_data.get("mail")
+            if not ad_groups_to_emails.get(name):
+                ad_groups_to_emails[name] = set()
+            if user_principal_name:
+                if MICROSOFT_DOMAIN in user_principal_name:
+                    user_principal_name = user_principal_name.replace(
+                        MICROSOFT_DOMAIN, ""
+                    )
+                ad_groups_to_emails[name].add(user_principal_name)
+            elif mail:
+                if MICROSOFT_DOMAIN in mail:
+                    mail = mail.replace(MICROSOFT_DOMAIN, "")
+                ad_groups_to_emails[name].add(mail)
+
+    external_user_groups: list[ExternalUserGroup] = []
+    for group_name, emails in groups_and_members.groups_to_emails.items():
+        external_user_group = ExternalUserGroup(
+            id=group_name,
+            user_emails=list(emails),
+        )
+        external_user_groups.append(external_user_group)
+
+    for group_name, emails in ad_groups_to_emails.items():
+        external_user_group = ExternalUserGroup(
+            id=group_name,
+            user_emails=list(emails),
+        )
+        external_user_groups.append(external_user_group)
+
+    return external_user_groups

backend/ee/onyx/external_permissions/slack/doc_sync.py

@@ -3,6 +3,7 @@ from collections.abc import Generator
 from slack_sdk import WebClient
 
 from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from ee.onyx.external_permissions.slack.utils import fetch_user_id_to_email_map
 from onyx.access.models import DocExternalAccess
 from onyx.access.models import ExternalAccess
@@ -130,6 +131,7 @@ def _get_slack_document_access(
 def slack_doc_sync(
     cc_pair: ConnectorCredentialPair,
     fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: IndexingHeartbeatInterface | None,
 ) -> Generator[DocExternalAccess, None, None]:
     """

backend/ee/onyx/external_permissions/sync_params.py

@@ -7,12 +7,18 @@ from pydantic import BaseModel
 from ee.onyx.configs.app_configs import CONFLUENCE_PERMISSION_DOC_SYNC_FREQUENCY
 from ee.onyx.configs.app_configs import CONFLUENCE_PERMISSION_GROUP_SYNC_FREQUENCY
 from ee.onyx.configs.app_configs import DEFAULT_PERMISSION_DOC_SYNC_FREQUENCY
+from ee.onyx.configs.app_configs import GITHUB_PERMISSION_DOC_SYNC_FREQUENCY
+from ee.onyx.configs.app_configs import GITHUB_PERMISSION_GROUP_SYNC_FREQUENCY
 from ee.onyx.configs.app_configs import GOOGLE_DRIVE_PERMISSION_GROUP_SYNC_FREQUENCY
 from ee.onyx.configs.app_configs import JIRA_PERMISSION_DOC_SYNC_FREQUENCY
+from ee.onyx.configs.app_configs import SHAREPOINT_PERMISSION_DOC_SYNC_FREQUENCY
+from ee.onyx.configs.app_configs import SHAREPOINT_PERMISSION_GROUP_SYNC_FREQUENCY
 from ee.onyx.configs.app_configs import SLACK_PERMISSION_DOC_SYNC_FREQUENCY
 from ee.onyx.configs.app_configs import TEAMS_PERMISSION_DOC_SYNC_FREQUENCY
 from ee.onyx.external_permissions.confluence.doc_sync import confluence_doc_sync
 from ee.onyx.external_permissions.confluence.group_sync import confluence_group_sync
+from ee.onyx.external_permissions.github.doc_sync import github_doc_sync
+from ee.onyx.external_permissions.github.group_sync import github_group_sync
 from ee.onyx.external_permissions.gmail.doc_sync import gmail_doc_sync
 from ee.onyx.external_permissions.google_drive.doc_sync import gdrive_doc_sync
 from ee.onyx.external_permissions.google_drive.group_sync import gdrive_group_sync
@@ -20,10 +26,13 @@ from ee.onyx.external_permissions.jira.doc_sync import jira_doc_sync
 from ee.onyx.external_permissions.perm_sync_types import CensoringFuncType
 from ee.onyx.external_permissions.perm_sync_types import DocSyncFuncType
 from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from ee.onyx.external_permissions.perm_sync_types import GroupSyncFuncType
 from ee.onyx.external_permissions.salesforce.postprocessing import (
     censor_salesforce_chunks,
 )
+from ee.onyx.external_permissions.sharepoint.doc_sync import sharepoint_doc_sync
+from ee.onyx.external_permissions.sharepoint.group_sync import sharepoint_group_sync
 from ee.onyx.external_permissions.slack.doc_sync import slack_doc_sync
 from ee.onyx.external_permissions.teams.doc_sync import teams_doc_sync
 from onyx.configs.constants import DocumentSource
@@ -63,6 +72,7 @@ class SyncConfig(BaseModel):
 def mock_doc_sync(
     cc_pair: "ConnectorCredentialPair",
     fetch_all_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: Optional["IndexingHeartbeatInterface"],
 ) -> Generator["DocExternalAccess", None, None]:
     """Mock doc sync function for testing - returns empty list since permissions are fetched during indexing"""
@@ -117,6 +127,18 @@ _SOURCE_TO_SYNC_CONFIG: dict[DocumentSource, SyncConfig] = {
             initial_index_should_sync=False,
         ),
     ),
+    DocumentSource.GITHUB: SyncConfig(
+        doc_sync_config=DocSyncConfig(
+            doc_sync_frequency=GITHUB_PERMISSION_DOC_SYNC_FREQUENCY,
+            doc_sync_func=github_doc_sync,
+            initial_index_should_sync=True,
+        ),
+        group_sync_config=GroupSyncConfig(
+            group_sync_frequency=GITHUB_PERMISSION_GROUP_SYNC_FREQUENCY,
+            group_sync_func=github_group_sync,
+            group_sync_is_cc_pair_agnostic=False,
+        ),
+    ),
     DocumentSource.SALESFORCE: SyncConfig(
         censoring_config=CensoringConfig(
             chunk_censoring_func=censor_salesforce_chunks,
@@ -138,6 +160,18 @@ _SOURCE_TO_SYNC_CONFIG: dict[DocumentSource, SyncConfig] = {
             initial_index_should_sync=True,
         ),
     ),
+    DocumentSource.SHAREPOINT: SyncConfig(
+        doc_sync_config=DocSyncConfig(
+            doc_sync_frequency=SHAREPOINT_PERMISSION_DOC_SYNC_FREQUENCY,
+            doc_sync_func=sharepoint_doc_sync,
+            initial_index_should_sync=True,
+        ),
+        group_sync_config=GroupSyncConfig(
+            group_sync_frequency=SHAREPOINT_PERMISSION_GROUP_SYNC_FREQUENCY,
+            group_sync_func=sharepoint_group_sync,
+            group_sync_is_cc_pair_agnostic=False,
+        ),
+    ),
 }
 
 

backend/ee/onyx/external_permissions/teams/doc_sync.py

@@ -1,6 +1,7 @@
 from collections.abc import Generator
 
 from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from ee.onyx.external_permissions.utils import generic_doc_sync
 from onyx.access.models import DocExternalAccess
 from onyx.configs.constants import DocumentSource
@@ -18,6 +19,7 @@ TEAMS_DOC_SYNC_LABEL = "teams_doc_sync"
 def teams_doc_sync(
     cc_pair: ConnectorCredentialPair,
     fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: IndexingHeartbeatInterface | None,
 ) -> Generator[DocExternalAccess, None, None]:
     teams_connector = TeamsConnector(
@@ -27,7 +29,7 @@ def teams_doc_sync(
 
     yield from generic_doc_sync(
         cc_pair=cc_pair,
-        fetch_all_existing_docs_fn=fetch_all_existing_docs_fn,
+        fetch_all_existing_docs_ids_fn=fetch_all_existing_docs_ids_fn,
         callback=callback,
         doc_source=DocumentSource.TEAMS,
         slim_connector=teams_connector,

backend/ee/onyx/external_permissions/utils.py

@@ -1,6 +1,6 @@
 from collections.abc import Generator
 
-from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsFunction
+from ee.onyx.external_permissions.perm_sync_types import FetchAllDocumentsIdsFunction
 from onyx.access.models import DocExternalAccess
 from onyx.access.models import ExternalAccess
 from onyx.configs.constants import DocumentSource
@@ -14,7 +14,7 @@ logger = setup_logger()
 
 def generic_doc_sync(
     cc_pair: ConnectorCredentialPair,
-    fetch_all_existing_docs_fn: FetchAllDocumentsFunction,
+    fetch_all_existing_docs_ids_fn: FetchAllDocumentsIdsFunction,
     callback: IndexingHeartbeatInterface | None,
     doc_source: DocumentSource,
     slim_connector: SlimConnector,
@@ -62,9 +62,9 @@ def generic_doc_sync(
             )
 
     logger.info(f"Querying existing document IDs for CC Pair ID: {cc_pair.id=}")
-    existing_doc_ids = set(fetch_all_existing_docs_fn())
+    existing_doc_ids: list[str] = fetch_all_existing_docs_ids_fn()
 
-    missing_doc_ids = existing_doc_ids - newly_fetched_doc_ids
+    missing_doc_ids = set(existing_doc_ids) - newly_fetched_doc_ids
 
     if not missing_doc_ids:
         return

backend/ee/onyx/main.py

@@ -17,6 +17,7 @@ from ee.onyx.server.enterprise_settings.api import (
 from ee.onyx.server.enterprise_settings.api import (
     basic_router as enterprise_settings_router,
 )
+from ee.onyx.server.evals.api import router as evals_router
 from ee.onyx.server.manage.standard_answer import router as standard_answer_router
 from ee.onyx.server.middleware.tenant_tracking import (
     add_api_server_tenant_id_middleware,
@@ -170,6 +171,7 @@ def get_application() -> FastAPI:
     include_router_with_global_prefix_prepended(application, standard_answer_router)
     include_router_with_global_prefix_prepended(application, ee_oauth_router)
     include_router_with_global_prefix_prepended(application, ee_document_cc_pair_router)
+    include_router_with_global_prefix_prepended(application, evals_router)
 
     # Enterprise-only global settings
     include_router_with_global_prefix_prepended(

backend/ee/onyx/onyxbot/slack/handlers/handle_standard_answers.py

@@ -14,7 +14,6 @@ from onyx.db.chat import create_new_chat_message
 from onyx.db.chat import get_chat_messages_by_sessions
 from onyx.db.chat import get_chat_sessions_by_slack_thread_id
 from onyx.db.chat import get_or_create_root_message
-from onyx.db.models import Prompt
 from onyx.db.models import SlackChannelConfig
 from onyx.db.models import StandardAnswer as StandardAnswerModel
 from onyx.onyxbot.slack.blocks import get_restate_blocks
@@ -81,7 +80,6 @@ def _handle_standard_answers(
     message_info: SlackMessageInfo,
     receiver_ids: list[str] | None,
     slack_channel_config: SlackChannelConfig,
-    prompt: Prompt | None,
     logger: OnyxLoggingAdapter,
     client: WebClient,
     db_session: Session,
@@ -161,7 +159,6 @@ def _handle_standard_answers(
         new_user_message = create_new_chat_message(
             chat_session_id=chat_session.id,
             parent_message=root_message,
-            prompt_id=prompt.id if prompt else None,
             message=query_msg.message,
             token_count=0,
             message_type=MessageType.USER,
@@ -182,7 +179,6 @@ def _handle_standard_answers(
         chat_message = create_new_chat_message(
             chat_session_id=chat_session.id,
             parent_message=new_user_message,
-            prompt_id=prompt.id if prompt else None,
             message=answer_message,
             token_count=0,
             message_type=MessageType.ASSISTANT,
@@ -206,7 +202,7 @@ def _handle_standard_answers(
 
         restate_question_blocks = get_restate_blocks(
             msg=query_msg.message,
-            is_bot_msg=message_info.is_bot_msg,
+            is_slash_command=message_info.is_slash_command,
         )
 
         answer_blocks = build_standard_answer_blocks(

backend/ee/onyx/server/evals/api.py

@@ -0,0 +1,32 @@
+from fastapi import APIRouter
+from fastapi import Depends
+
+from ee.onyx.auth.users import current_cloud_superuser
+from onyx.background.celery.apps.client import celery_app as client_app
+from onyx.configs.constants import OnyxCeleryTask
+from onyx.db.models import User
+from onyx.evals.models import EvalConfigurationOptions
+from onyx.server.evals.models import EvalRunAck
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+router = APIRouter(prefix="/evals")
+
+
+@router.post("/eval_run", response_model=EvalRunAck)
+def eval_run(
+    request: EvalConfigurationOptions,
+    user: User = Depends(current_cloud_superuser),
+) -> EvalRunAck:
+    """
+    Run an evaluation with the given message and optional dataset.
+    This endpoint requires a valid API key for authentication.
+    """
+    client_app.send_task(
+        OnyxCeleryTask.EVAL_RUN_TASK,
+        kwargs={
+            "configuration_dict": request.model_dump(),
+        },
+    )
+    return EvalRunAck(success=True)

backend/ee/onyx/server/query_and_chat/chat_backend.py

@@ -1,43 +1,22 @@
-import re
-from typing import cast
-from uuid import UUID
-
 from fastapi import APIRouter
 from fastapi import Depends
 from fastapi import HTTPException
 from sqlalchemy.orm import Session
 
-from ee.onyx.server.query_and_chat.models import AgentAnswer
-from ee.onyx.server.query_and_chat.models import AgentSubQuery
-from ee.onyx.server.query_and_chat.models import AgentSubQuestion
 from ee.onyx.server.query_and_chat.models import BasicCreateChatMessageRequest
 from ee.onyx.server.query_and_chat.models import (
     BasicCreateChatMessageWithHistoryRequest,
 )
-from ee.onyx.server.query_and_chat.models import ChatBasicResponse
 from onyx.auth.users import current_user
 from onyx.chat.chat_utils import combine_message_thread
 from onyx.chat.chat_utils import create_chat_chain
-from onyx.chat.models import AgentAnswerPiece
-from onyx.chat.models import AllCitations
-from onyx.chat.models import ExtendedToolResponse
-from onyx.chat.models import FinalUsedContextDocsResponse
-from onyx.chat.models import LlmDoc
-from onyx.chat.models import LLMRelevanceFilterResponse
-from onyx.chat.models import OnyxAnswerPiece
-from onyx.chat.models import QADocsResponse
-from onyx.chat.models import RefinedAnswerImprovement
-from onyx.chat.models import StreamingError
-from onyx.chat.models import SubQueryPiece
-from onyx.chat.models import SubQuestionIdentifier
-from onyx.chat.models import SubQuestionPiece
-from onyx.chat.process_message import ChatPacketStream
+from onyx.chat.models import ChatBasicResponse
+from onyx.chat.process_message import gather_stream
 from onyx.chat.process_message import stream_chat_message_objects
 from onyx.configs.chat_configs import CHAT_TARGET_CHUNK_PERCENTAGE
 from onyx.configs.constants import MessageType
 from onyx.context.search.models import OptionalSearchSetting
 from onyx.context.search.models import RetrievalDetails
-from onyx.context.search.models import SavedSearchDoc
 from onyx.db.chat import create_chat_session
 from onyx.db.chat import create_new_chat_message
 from onyx.db.chat import get_or_create_root_message
@@ -46,7 +25,6 @@ from onyx.db.models import User
 from onyx.llm.factory import get_llms_for_persona
 from onyx.natural_language_processing.utils import get_tokenizer
 from onyx.secondary_llm_flows.query_expansion import thread_based_query_rephrase
-from onyx.server.query_and_chat.models import ChatMessageDetail
 from onyx.server.query_and_chat.models import CreateChatMessageRequest
 from onyx.utils.logger import setup_logger
 
@@ -55,180 +33,6 @@ logger = setup_logger()
 router = APIRouter(prefix="/chat")
 
 
-def _get_final_context_doc_indices(
-    final_context_docs: list[LlmDoc] | None,
-    top_docs: list[SavedSearchDoc] | None,
-) -> list[int] | None:
-    """
-    this function returns a list of indices of the simple search docs
-    that were actually fed to the LLM.
-    """
-    if final_context_docs is None or top_docs is None:
-        return None
-
-    final_context_doc_ids = {doc.document_id for doc in final_context_docs}
-    return [
-        i for i, doc in enumerate(top_docs) if doc.document_id in final_context_doc_ids
-    ]
-
-
-def _convert_packet_stream_to_response(
-    packets: ChatPacketStream,
-    chat_session_id: UUID,
-) -> ChatBasicResponse:
-    response = ChatBasicResponse()
-    final_context_docs: list[LlmDoc] = []
-
-    answer = ""
-
-    # accumulate stream data with these dicts
-    agent_sub_questions: dict[tuple[int, int], AgentSubQuestion] = {}
-    agent_answers: dict[tuple[int, int], AgentAnswer] = {}
-    agent_sub_queries: dict[tuple[int, int, int], AgentSubQuery] = {}
-
-    for packet in packets:
-        if isinstance(packet, OnyxAnswerPiece) and packet.answer_piece:
-            answer += packet.answer_piece
-        elif isinstance(packet, QADocsResponse):
-            response.top_documents = packet.top_documents
-
-            # This is a no-op if agent_sub_questions hasn't already been filled
-            if packet.level is not None and packet.level_question_num is not None:
-                id = (packet.level, packet.level_question_num)
-                if id in agent_sub_questions:
-                    agent_sub_questions[id].document_ids = [
-                        saved_search_doc.document_id
-                        for saved_search_doc in packet.top_documents
-                    ]
-        elif isinstance(packet, StreamingError):
-            response.error_msg = packet.error
-        elif isinstance(packet, ChatMessageDetail):
-            response.message_id = packet.message_id
-        elif isinstance(packet, LLMRelevanceFilterResponse):
-            response.llm_selected_doc_indices = packet.llm_selected_doc_indices
-
-            # TODO: deprecate `llm_chunks_indices`
-            response.llm_chunks_indices = packet.llm_selected_doc_indices
-        elif isinstance(packet, FinalUsedContextDocsResponse):
-            final_context_docs = packet.final_context_docs
-        elif isinstance(packet, AllCitations):
-            response.cited_documents = {
-                citation.citation_num: citation.document_id
-                for citation in packet.citations
-            }
-        # agentic packets
-        elif isinstance(packet, SubQuestionPiece):
-            if packet.level is not None and packet.level_question_num is not None:
-                id = (packet.level, packet.level_question_num)
-                if agent_sub_questions.get(id) is None:
-                    agent_sub_questions[id] = AgentSubQuestion(
-                        level=packet.level,
-                        level_question_num=packet.level_question_num,
-                        sub_question=packet.sub_question,
-                        document_ids=[],
-                    )
-                else:
-                    agent_sub_questions[id].sub_question += packet.sub_question
-
-        elif isinstance(packet, AgentAnswerPiece):
-            if packet.level is not None and packet.level_question_num is not None:
-                id = (packet.level, packet.level_question_num)
-                if agent_answers.get(id) is None:
-                    agent_answers[id] = AgentAnswer(
-                        level=packet.level,
-                        level_question_num=packet.level_question_num,
-                        answer=packet.answer_piece,
-                        answer_type=packet.answer_type,
-                    )
-                else:
-                    agent_answers[id].answer += packet.answer_piece
-        elif isinstance(packet, SubQueryPiece):
-            if packet.level is not None and packet.level_question_num is not None:
-                sub_query_id = (
-                    packet.level,
-                    packet.level_question_num,
-                    packet.query_id,
-                )
-                if agent_sub_queries.get(sub_query_id) is None:
-                    agent_sub_queries[sub_query_id] = AgentSubQuery(
-                        level=packet.level,
-                        level_question_num=packet.level_question_num,
-                        sub_query=packet.sub_query,
-                        query_id=packet.query_id,
-                    )
-                else:
-                    agent_sub_queries[sub_query_id].sub_query += packet.sub_query
-        elif isinstance(packet, ExtendedToolResponse):
-            # we shouldn't get this ... it gets intercepted and translated to QADocsResponse
-            logger.warning(
-                "_convert_packet_stream_to_response: Unexpected chat packet type ExtendedToolResponse!"
-            )
-        elif isinstance(packet, RefinedAnswerImprovement):
-            response.agent_refined_answer_improvement = (
-                packet.refined_answer_improvement
-            )
-        else:
-            logger.warning(
-                f"_convert_packet_stream_to_response - Unrecognized chat packet: type={type(packet)}"
-            )
-
-    response.final_context_doc_indices = _get_final_context_doc_indices(
-        final_context_docs, response.top_documents
-    )
-
-    # organize / sort agent metadata for output
-    if len(agent_sub_questions) > 0:
-        response.agent_sub_questions = cast(
-            dict[int, list[AgentSubQuestion]],
-            SubQuestionIdentifier.make_dict_by_level(agent_sub_questions),
-        )
-
-    if len(agent_answers) > 0:
-        # return the agent_level_answer from the first level or the last one depending
-        # on agent_refined_answer_improvement
-        response.agent_answers = cast(
-            dict[int, list[AgentAnswer]],
-            SubQuestionIdentifier.make_dict_by_level(agent_answers),
-        )
-        if response.agent_answers:
-            selected_answer_level = (
-                0
-                if not response.agent_refined_answer_improvement
-                else len(response.agent_answers) - 1
-            )
-            level_answers = response.agent_answers[selected_answer_level]
-            for level_answer in level_answers:
-                if level_answer.answer_type != "agent_level_answer":
-                    continue
-
-                answer = level_answer.answer
-                break
-
-    if len(agent_sub_queries) > 0:
-        # subqueries are often emitted with trailing whitespace ... clean it up here
-        # perhaps fix at the source?
-        for v in agent_sub_queries.values():
-            v.sub_query = v.sub_query.strip()
-
-        response.agent_sub_queries = (
-            AgentSubQuery.make_dict_by_level_and_question_index(agent_sub_queries)
-        )
-
-    response.answer = answer
-    if answer:
-        response.answer_citationless = remove_answer_citations(answer)
-
-    response.chat_session_id = chat_session_id
-
-    return response
-
-
-def remove_answer_citations(answer: str) -> str:
-    pattern = r"\s*\[\[\d+\]\]\(http[s]?://[^\s]+\)"
-
-    return re.sub(pattern, "", answer)
-
-
 @router.post("/send-message-simple-api")
 def handle_simplified_chat_message(
     chat_message_req: BasicCreateChatMessageRequest,
@@ -289,7 +93,6 @@ def handle_simplified_chat_message(
         parent_message_id=parent_message.id,
         message=chat_message_req.message,
         file_descriptors=[],
-        prompt_id=None,
         search_doc_ids=chat_message_req.search_doc_ids,
         retrieval_options=retrieval_options,
         # Simple API does not support reranking, hide complexity from user
@@ -310,7 +113,7 @@ def handle_simplified_chat_message(
         enforce_chat_session_id_for_search_docs=False,
     )
 
-    return _convert_packet_stream_to_response(packets, chat_session_id)
+    return gather_stream(packets)
 
 
 @router.post("/send-message-simple-with-history")
@@ -377,7 +180,6 @@ def handle_send_message_simple_with_history(
         chat_message = create_new_chat_message(
             chat_session_id=chat_session.id,
             parent_message=chat_message,
-            prompt_id=req.prompt_id,
             message=msg.message,
             token_count=len(llm_tokenizer.encode(msg.message)),
             message_type=msg.role,
@@ -410,7 +212,6 @@ def handle_send_message_simple_with_history(
         parent_message_id=chat_message.id,
         message=query,
         file_descriptors=[],
-        prompt_id=req.prompt_id,
         search_doc_ids=req.search_doc_ids,
         retrieval_options=retrieval_options,
         # Simple API does not support reranking, hide complexity from user
@@ -430,4 +231,4 @@ def handle_send_message_simple_with_history(
         enforce_chat_session_id_for_search_docs=False,
     )
 
-    return _convert_packet_stream_to_response(packets, chat_session.id)
+    return gather_stream(packets)

backend/ee/onyx/server/query_and_chat/models.py

@@ -6,10 +6,8 @@ from pydantic import BaseModel
 from pydantic import Field
 from pydantic import model_validator
 
-from onyx.chat.models import CitationInfo
 from onyx.chat.models import PersonaOverrideConfig
 from onyx.chat.models import QADocsResponse
-from onyx.chat.models import SubQuestionIdentifier
 from onyx.chat.models import ThreadMessage
 from onyx.configs.constants import DocumentSource
 from onyx.context.search.enums import LLMEvaluationType
@@ -17,8 +15,9 @@ from onyx.context.search.enums import SearchType
 from onyx.context.search.models import ChunkContext
 from onyx.context.search.models import RerankingDetails
 from onyx.context.search.models import RetrievalDetails
-from onyx.context.search.models import SavedSearchDoc
 from onyx.server.manage.models import StandardAnswer
+from onyx.server.query_and_chat.streaming_models import CitationInfo
+from onyx.server.query_and_chat.streaming_models import SubQuestionIdentifier
 
 
 class StandardAnswerRequest(BaseModel):
@@ -74,7 +73,6 @@ class BasicCreateChatMessageRequest(ChunkContext):
 class BasicCreateChatMessageWithHistoryRequest(ChunkContext):
     # Last element is the new query. All previous elements are historical context
     messages: list[ThreadMessage]
-    prompt_id: int | None
     persona_id: int
     retrieval_options: RetrievalDetails | None = None
     query_override: str | None = None
@@ -156,33 +154,6 @@ class AgentSubQuery(SubQuestionIdentifier):
         return sorted_dict
 
 
-class ChatBasicResponse(BaseModel):
-    # This is built piece by piece, any of these can be None as the flow could break
-    answer: str | None = None
-    answer_citationless: str | None = None
-
-    top_documents: list[SavedSearchDoc] | None = None
-
-    error_msg: str | None = None
-    message_id: int | None = None
-    llm_selected_doc_indices: list[int] | None = None
-    final_context_doc_indices: list[int] | None = None
-    # this is a map of the citation number to the document id
-    cited_documents: dict[int, str] | None = None
-
-    # FOR BACKWARDS COMPATIBILITY
-    llm_chunks_indices: list[int] | None = None
-
-    # agentic fields
-    agent_sub_questions: dict[int, list[AgentSubQuestion]] | None = None
-    agent_answers: dict[int, list[AgentAnswer]] | None = None
-    agent_sub_queries: dict[int, dict[int, list[AgentSubQuery]]] | None = None
-    agent_refined_answer_improvement: bool | None = None
-
-    # Chat session ID for tracking conversation continuity
-    chat_session_id: UUID | None = None
-
-
 class OneShotQARequest(ChunkContext):
     # Supports simplier APIs that don't deal with chat histories or message edits
     # Easier APIs to work with for developers
@@ -190,10 +161,8 @@ class OneShotQARequest(ChunkContext):
     persona_id: int | None = None
 
     messages: list[ThreadMessage]
-    prompt_id: int | None = None
     retrieval_options: RetrievalDetails = Field(default_factory=RetrievalDetails)
     rerank_settings: RerankingDetails | None = None
-    return_contexts: bool = False
 
     # allows the caller to specify the exact search query they want to use
     # can be used if the message sent to the LLM / query should not be the same
@@ -210,11 +179,9 @@ class OneShotQARequest(ChunkContext):
     def check_persona_fields(self) -> "OneShotQARequest":
         if self.persona_override_config is None and self.persona_id is None:
             raise ValueError("Exactly one of persona_config or persona_id must be set")
-        elif self.persona_override_config is not None and (
-            self.persona_id is not None or self.prompt_id is not None
-        ):
+        elif self.persona_override_config is not None and (self.persona_id is not None):
             raise ValueError(
-                "If persona_override_config is set, persona_id and prompt_id cannot be set"
+                "If persona_override_config is set, persona_id cannot be set"
             )
         return self
 
@@ -225,6 +192,5 @@ class OneShotQAResponse(BaseModel):
     rephrase: str | None = None
     citations: list[CitationInfo] | None = None
     docs: QADocsResponse | None = None
-    llm_selected_doc_indices: list[int] | None = None
     error_msg: str | None = None
     chat_message_id: int | None = None

backend/ee/onyx/server/query_and_chat/query_backend.py

@@ -8,7 +8,6 @@ from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 from sqlalchemy.orm import Session
 
-from ee.onyx.chat.process_message import gather_stream_for_answer_api
 from ee.onyx.onyxbot.slack.handlers.handle_standard_answers import (
     oneoff_standard_answers,
 )
@@ -20,8 +19,10 @@ from ee.onyx.server.query_and_chat.models import StandardAnswerResponse
 from onyx.auth.users import current_user
 from onyx.chat.chat_utils import combine_message_thread
 from onyx.chat.chat_utils import prepare_chat_message_request
+from onyx.chat.models import AnswerStream
 from onyx.chat.models import PersonaOverrideConfig
-from onyx.chat.process_message import ChatPacketStream
+from onyx.chat.models import QADocsResponse
+from onyx.chat.process_message import gather_stream
 from onyx.chat.process_message import stream_chat_message_objects
 from onyx.configs.onyxbot_configs import MAX_THREAD_CONTEXT_PERCENTAGE
 from onyx.context.search.models import SavedSearchDocWithContent
@@ -30,7 +31,6 @@ from onyx.context.search.pipeline import SearchPipeline
 from onyx.context.search.utils import dedupe_documents
 from onyx.context.search.utils import drop_llm_indices
 from onyx.context.search.utils import relevant_sections_to_indices
-from onyx.db.chat import get_prompt_by_id
 from onyx.db.engine.sql_engine import get_session
 from onyx.db.models import Persona
 from onyx.db.models import User
@@ -39,6 +39,7 @@ from onyx.llm.factory import get_default_llms
 from onyx.llm.factory import get_llms_for_persona
 from onyx.llm.factory import get_main_llm_from_tuple
 from onyx.natural_language_processing.utils import get_tokenizer
+from onyx.server.query_and_chat.streaming_models import CitationInfo
 from onyx.server.utils import get_json_line
 from onyx.utils.logger import setup_logger
 
@@ -140,7 +141,7 @@ def get_answer_stream(
     query_request: OneShotQARequest,
     user: User | None = Depends(current_user),
     db_session: Session = Depends(get_session),
-) -> ChatPacketStream:
+) -> AnswerStream:
     query = query_request.messages[0].message
     logger.notice(f"Received query for Answer API: {query}")
 
@@ -150,14 +151,6 @@ def get_answer_stream(
     ):
         raise KeyError("Must provide persona ID or Persona Config")
 
-    prompt = None
-    if query_request.prompt_id is not None:
-        prompt = get_prompt_by_id(
-            prompt_id=query_request.prompt_id,
-            user=user,
-            db_session=db_session,
-        )
-
     persona_info: Persona | PersonaOverrideConfig | None = None
     if query_request.persona_override_config is not None:
         persona_info = query_request.persona_override_config
@@ -192,7 +185,6 @@ def get_answer_stream(
         user=user,
         persona_id=query_request.persona_id,
         persona_override_config=query_request.persona_override_config,
-        prompt=prompt,
         message_ts_to_respond_to=None,
         retrieval_details=query_request.retrieval_options,
         rerank_settings=query_request.rerank_settings,
@@ -205,7 +197,6 @@ def get_answer_stream(
         new_msg_req=request,
         user=user,
         db_session=db_session,
-        include_contexts=query_request.return_contexts,
     )
 
     return packets
@@ -219,12 +210,28 @@ def get_answer_with_citation(
 ) -> OneShotQAResponse:
     try:
         packets = get_answer_stream(request, user, db_session)
-        answer = gather_stream_for_answer_api(packets)
+        answer = gather_stream(packets)
 
         if answer.error_msg:
             raise RuntimeError(answer.error_msg)
 
-        return answer
+        return OneShotQAResponse(
+            answer=answer.answer,
+            chat_message_id=answer.message_id,
+            error_msg=answer.error_msg,
+            citations=[
+                CitationInfo(citation_num=i, document_id=doc_id)
+                for i, doc_id in answer.cited_documents.items()
+            ],
+            docs=QADocsResponse(
+                top_documents=answer.top_documents,
+                predicted_flow=None,
+                predicted_search=None,
+                applied_source_filters=None,
+                applied_time_cutoff=None,
+                recency_bias_multiplier=0.0,
+            ),
+        )
     except Exception as e:
         logger.error(f"Error in get_answer_with_citation: {str(e)}", exc_info=True)
         raise HTTPException(status_code=500, detail="An internal server error occurred")

backend/ee/onyx/server/reporting/usage_export_api.py

@@ -12,11 +12,13 @@ from sqlalchemy.orm import Session
 from ee.onyx.db.usage_export import get_all_usage_reports
 from ee.onyx.db.usage_export import get_usage_report_data
 from ee.onyx.db.usage_export import UsageReportMetadata
-from ee.onyx.server.reporting.usage_export_generation import create_new_usage_report
 from onyx.auth.users import current_admin_user
+from onyx.background.celery.versioned_apps.client import app as client_app
+from onyx.configs.constants import OnyxCeleryTask
 from onyx.db.engine.sql_engine import get_session
 from onyx.db.models import User
 from onyx.file_store.constants import STANDARD_CHUNK_SIZE
+from shared_configs.contextvars import get_current_tenant_id
 
 router = APIRouter()
 
@@ -26,24 +28,31 @@ class GenerateUsageReportParams(BaseModel):
     period_to: str | None = None
 
 
-@router.post("/admin/generate-usage-report")
+@router.post("/admin/usage-report", status_code=204)
 def generate_report(
     params: GenerateUsageReportParams,
     user: User = Depends(current_admin_user),
-    db_session: Session = Depends(get_session),
-) -> UsageReportMetadata:
-    period = None
+) -> None:
+    # Validate period parameters
     if params.period_from and params.period_to:
         try:
-            period = (
-                datetime.fromisoformat(params.period_from),
-                datetime.fromisoformat(params.period_to),
-            )
+            datetime.fromisoformat(params.period_from)
+            datetime.fromisoformat(params.period_to)
         except ValueError as e:
             raise HTTPException(status_code=400, detail=str(e))
 
-    new_report = create_new_usage_report(db_session, user.id if user else None, period)
-    return new_report
+    tenant_id = get_current_tenant_id()
+    client_app.send_task(
+        OnyxCeleryTask.GENERATE_USAGE_REPORT_TASK,
+        kwargs={
+            "tenant_id": tenant_id,
+            "user_id": str(user.id) if user else None,
+            "period_from": params.period_from,
+            "period_to": params.period_to,
+        },
+    )
+
+    return None
 
 
 @router.get("/admin/usage-report/{report_name}")
@@ -54,7 +63,7 @@ def read_usage_report(
 ) -> Response:
     try:
         file = get_usage_report_data(report_name)
-    except ValueError as e:
+    except (ValueError, RuntimeError) as e:
         raise HTTPException(status_code=404, detail=str(e))
 
     def iterfile() -> Generator[bytes, None, None]:

backend/ee/onyx/server/reporting/usage_export_generation.py

@@ -67,7 +67,7 @@ def generate_chat_messages_report(
         file_id = file_store.save_file(
             content=temp_file,
             display_name=file_name,
-            file_origin=FileOrigin.OTHER,
+            file_origin=FileOrigin.GENERATED_REPORT,
             file_type="text/csv",
         )
 
@@ -99,7 +99,7 @@ def generate_user_report(
         file_id = file_store.save_file(
             content=temp_file,
             display_name=file_name,
-            file_origin=FileOrigin.OTHER,
+            file_origin=FileOrigin.GENERATED_REPORT,
             file_type="text/csv",
         )
 

backend/ee/onyx/server/seeding.py

@@ -131,32 +131,35 @@ def _seed_llms(
 def _seed_personas(db_session: Session, personas: list[PersonaUpsertRequest]) -> None:
     if personas:
         logger.notice("Seeding Personas")
-        for persona in personas:
-            if not persona.prompt_ids:
-                raise ValueError(
-                    f"Invalid Persona with name {persona.name}; no prompts exist"
+        try:
+            for persona in personas:
+                upsert_persona(
+                    user=None,  # Seeding is done as admin
+                    name=persona.name,
+                    description=persona.description,
+                    num_chunks=(
+                        persona.num_chunks if persona.num_chunks is not None else 0.0
+                    ),
+                    llm_relevance_filter=persona.llm_relevance_filter,
+                    llm_filter_extraction=persona.llm_filter_extraction,
+                    recency_bias=RecencyBiasSetting.AUTO,
+                    document_set_ids=persona.document_set_ids,
+                    llm_model_provider_override=persona.llm_model_provider_override,
+                    llm_model_version_override=persona.llm_model_version_override,
+                    starter_messages=persona.starter_messages,
+                    is_public=persona.is_public,
+                    db_session=db_session,
+                    tool_ids=persona.tool_ids,
+                    display_priority=persona.display_priority,
+                    system_prompt=persona.system_prompt,
+                    task_prompt=persona.task_prompt,
+                    datetime_aware=persona.datetime_aware,
+                    commit=False,
                 )
-
-            upsert_persona(
-                user=None,  # Seeding is done as admin
-                name=persona.name,
-                description=persona.description,
-                num_chunks=(
-                    persona.num_chunks if persona.num_chunks is not None else 0.0
-                ),
-                llm_relevance_filter=persona.llm_relevance_filter,
-                llm_filter_extraction=persona.llm_filter_extraction,
-                recency_bias=RecencyBiasSetting.AUTO,
-                prompt_ids=persona.prompt_ids,
-                document_set_ids=persona.document_set_ids,
-                llm_model_provider_override=persona.llm_model_provider_override,
-                llm_model_version_override=persona.llm_model_version_override,
-                starter_messages=persona.starter_messages,
-                is_public=persona.is_public,
-                db_session=db_session,
-                tool_ids=persona.tool_ids,
-                display_priority=persona.display_priority,
-            )
+            db_session.commit()
+        except Exception:
+            logger.exception("Failed to seed personas.")
+            raise
 
 
 def _seed_settings(settings: Settings) -> None:

backend/model_server/constants.py

@@ -1,34 +1,5 @@
-from shared_configs.enums import EmbeddingProvider
-from shared_configs.enums import EmbedTextType
-
-
 MODEL_WARM_UP_STRING = "hi " * 512
 INFORMATION_CONTENT_MODEL_WARM_UP_STRING = "hi " * 16
-DEFAULT_OPENAI_MODEL = "text-embedding-3-small"
-DEFAULT_COHERE_MODEL = "embed-english-light-v3.0"
-DEFAULT_VOYAGE_MODEL = "voyage-large-2-instruct"
-DEFAULT_VERTEX_MODEL = "text-embedding-005"
-
-
-class EmbeddingModelTextType:
-    PROVIDER_TEXT_TYPE_MAP = {
-        EmbeddingProvider.COHERE: {
-            EmbedTextType.QUERY: "search_query",
-            EmbedTextType.PASSAGE: "search_document",
-        },
-        EmbeddingProvider.VOYAGE: {
-            EmbedTextType.QUERY: "query",
-            EmbedTextType.PASSAGE: "document",
-        },
-        EmbeddingProvider.GOOGLE: {
-            EmbedTextType.QUERY: "RETRIEVAL_QUERY",
-            EmbedTextType.PASSAGE: "RETRIEVAL_DOCUMENT",
-        },
-    }
-
-    @staticmethod
-    def get_type(provider: EmbeddingProvider, text_type: EmbedTextType) -> str:
-        return EmbeddingModelTextType.PROVIDER_TEXT_TYPE_MAP[provider][text_type]
 
 
 class GPUStatus:

backend/model_server/encoders.py

@@ -1,55 +1,30 @@
 import asyncio
-import json
 import time
-from types import TracebackType
-from typing import cast
+from typing import Any
 from typing import Optional
 
-import aioboto3  # type: ignore
-import httpx
-import openai
-import vertexai  # type: ignore
-import voyageai  # type: ignore
-from cohere import AsyncClient as CohereAsyncClient
 from fastapi import APIRouter
 from fastapi import HTTPException
 from fastapi import Request
-from google.oauth2 import service_account  # type: ignore
-from litellm import aembedding
 from litellm.exceptions import RateLimitError
-from retry import retry
 from sentence_transformers import CrossEncoder  # type: ignore
 from sentence_transformers import SentenceTransformer  # type: ignore
-from vertexai.language_models import TextEmbeddingInput  # type: ignore
-from vertexai.language_models import TextEmbeddingModel  # type: ignore
 
-from model_server.constants import DEFAULT_COHERE_MODEL
-from model_server.constants import DEFAULT_OPENAI_MODEL
-from model_server.constants import DEFAULT_VERTEX_MODEL
-from model_server.constants import DEFAULT_VOYAGE_MODEL
-from model_server.constants import EmbeddingModelTextType
-from model_server.constants import EmbeddingProvider
-from model_server.utils import pass_aws_key
 from model_server.utils import simple_log_function_time
 from onyx.utils.logger import setup_logger
-from shared_configs.configs import API_BASED_EMBEDDING_TIMEOUT
 from shared_configs.configs import INDEXING_ONLY
-from shared_configs.configs import OPENAI_EMBEDDING_TIMEOUT
-from shared_configs.configs import VERTEXAI_EMBEDDING_LOCAL_BATCH_SIZE
 from shared_configs.enums import EmbedTextType
-from shared_configs.enums import RerankerProvider
 from shared_configs.model_server_models import Embedding
 from shared_configs.model_server_models import EmbedRequest
 from shared_configs.model_server_models import EmbedResponse
 from shared_configs.model_server_models import RerankRequest
 from shared_configs.model_server_models import RerankResponse
-from shared_configs.utils import batch_list
-
 
 logger = setup_logger()
 
 router = APIRouter(prefix="/encoder")
 
+
 _GLOBAL_MODELS_DICT: dict[str, "SentenceTransformer"] = {}
 _RERANK_MODEL: Optional["CrossEncoder"] = None
 
@@ -57,338 +32,56 @@ _RERANK_MODEL: Optional["CrossEncoder"] = None
 _RETRY_DELAY = 10 if INDEXING_ONLY else 0.1
 _RETRY_TRIES = 10 if INDEXING_ONLY else 2
 
-# OpenAI only allows 2048 embeddings to be computed at once
-_OPENAI_MAX_INPUT_LEN = 2048
-# Cohere allows up to 96 embeddings in a single embedding calling
-_COHERE_MAX_INPUT_LEN = 96
-
-# Authentication error string constants
-_AUTH_ERROR_401 = "401"
-_AUTH_ERROR_UNAUTHORIZED = "unauthorized"
-_AUTH_ERROR_INVALID_API_KEY = "invalid api key"
-_AUTH_ERROR_PERMISSION = "permission"
-
-
-def is_authentication_error(error: Exception) -> bool:
-    """Check if an exception is related to authentication issues.
-
-    Args:
-        error: The exception to check
-
-    Returns:
-        bool: True if the error appears to be authentication-related
-    """
-    error_str = str(error).lower()
-    return (
-        _AUTH_ERROR_401 in error_str
-        or _AUTH_ERROR_UNAUTHORIZED in error_str
-        or _AUTH_ERROR_INVALID_API_KEY in error_str
-        or _AUTH_ERROR_PERMISSION in error_str
-    )
-
-
-def format_embedding_error(
-    error: Exception,
-    service_name: str,
-    model: str | None,
-    provider: EmbeddingProvider,
-    sanitized_api_key: str | None = None,
-    status_code: int | None = None,
-) -> str:
-    """
-    Format a standardized error string for embedding errors.
-    """
-    detail = f"Status {status_code}" if status_code else f"{type(error)}"
-
-    return (
-        f"{'HTTP error' if status_code else 'Exception'} embedding text with {service_name} - {detail}: "
-        f"Model: {model} "
-        f"Provider: {provider} "
-        f"API Key: {sanitized_api_key} "
-        f"Exception: {error}"
-    )
-
-
-# Custom exception for authentication errors
-class AuthenticationError(Exception):
-    """Raised when authentication fails with a provider."""
-
-    def __init__(self, provider: str, message: str = "API key is invalid or expired"):
-        self.provider = provider
-        self.message = message
-        super().__init__(f"{provider} authentication failed: {message}")
-
-
-class CloudEmbedding:
-    def __init__(
-        self,
-        api_key: str,
-        provider: EmbeddingProvider,
-        api_url: str | None = None,
-        api_version: str | None = None,
-        timeout: int = API_BASED_EMBEDDING_TIMEOUT,
-    ) -> None:
-        self.provider = provider
-        self.api_key = api_key
-        self.api_url = api_url
-        self.api_version = api_version
-        self.timeout = timeout
-        self.http_client = httpx.AsyncClient(timeout=timeout)
-        self._closed = False
-        self.sanitized_api_key = api_key[:4] + "********" + api_key[-4:]
-
-    async def _embed_openai(
-        self, texts: list[str], model: str | None, reduced_dimension: int | None
-    ) -> list[Embedding]:
-        if not model:
-            model = DEFAULT_OPENAI_MODEL
-
-        # Use the OpenAI specific timeout for this one
-        client = openai.AsyncOpenAI(
-            api_key=self.api_key, timeout=OPENAI_EMBEDDING_TIMEOUT
-        )
-
-        final_embeddings: list[Embedding] = []
-
-        for text_batch in batch_list(texts, _OPENAI_MAX_INPUT_LEN):
-            response = await client.embeddings.create(
-                input=text_batch,
-                model=model,
-                dimensions=reduced_dimension or openai.NOT_GIVEN,
-            )
-            final_embeddings.extend(
-                [embedding.embedding for embedding in response.data]
-            )
-        return final_embeddings
-
-    async def _embed_cohere(
-        self, texts: list[str], model: str | None, embedding_type: str
-    ) -> list[Embedding]:
-        if not model:
-            model = DEFAULT_COHERE_MODEL
-
-        client = CohereAsyncClient(api_key=self.api_key)
-
-        final_embeddings: list[Embedding] = []
-        for text_batch in batch_list(texts, _COHERE_MAX_INPUT_LEN):
-            # Does not use the same tokenizer as the Onyx API server but it's approximately the same
-            # empirically it's only off by a very few tokens so it's not a big deal
-            response = await client.embed(
-                texts=text_batch,
-                model=model,
-                input_type=embedding_type,
-                truncate="END",
-            )
-            final_embeddings.extend(cast(list[Embedding], response.embeddings))
-        return final_embeddings
-
-    async def _embed_voyage(
-        self, texts: list[str], model: str | None, embedding_type: str
-    ) -> list[Embedding]:
-        if not model:
-            model = DEFAULT_VOYAGE_MODEL
-
-        client = voyageai.AsyncClient(
-            api_key=self.api_key, timeout=API_BASED_EMBEDDING_TIMEOUT
-        )
-
-        response = await client.embed(
-            texts=texts,
-            model=model,
-            input_type=embedding_type,
-            truncation=True,
-        )
-        return response.embeddings
-
-    async def _embed_azure(
-        self, texts: list[str], model: str | None
-    ) -> list[Embedding]:
-        response = await aembedding(
-            model=model,
-            input=texts,
-            timeout=API_BASED_EMBEDDING_TIMEOUT,
-            api_key=self.api_key,
-            api_base=self.api_url,
-            api_version=self.api_version,
-        )
-        embeddings = [embedding["embedding"] for embedding in response.data]
-        return embeddings
-
-    async def _embed_vertex(
-        self, texts: list[str], model: str | None, embedding_type: str
-    ) -> list[Embedding]:
-        if not model:
-            model = DEFAULT_VERTEX_MODEL
-
-        credentials = service_account.Credentials.from_service_account_info(
-            json.loads(self.api_key)
-        )
-        project_id = json.loads(self.api_key)["project_id"]
-        vertexai.init(project=project_id, credentials=credentials)
-        client = TextEmbeddingModel.from_pretrained(model)
-
-        inputs = [TextEmbeddingInput(text, embedding_type) for text in texts]
-
-        # Split into batches of 25 texts
-        max_texts_per_batch = VERTEXAI_EMBEDDING_LOCAL_BATCH_SIZE
-        batches = [
-            inputs[i : i + max_texts_per_batch]
-            for i in range(0, len(inputs), max_texts_per_batch)
-        ]
-
-        # Dispatch all embedding calls asynchronously at once
-        tasks = [
-            client.get_embeddings_async(batch, auto_truncate=True) for batch in batches
-        ]
-
-        # Wait for all tasks to complete in parallel
-        results = await asyncio.gather(*tasks)
-
-        return [embedding.values for batch in results for embedding in batch]
-
-    async def _embed_litellm_proxy(
-        self, texts: list[str], model_name: str | None
-    ) -> list[Embedding]:
-        if not model_name:
-            raise ValueError("Model name is required for LiteLLM proxy embedding.")
-
-        if not self.api_url:
-            raise ValueError("API URL is required for LiteLLM proxy embedding.")
-
-        headers = (
-            {} if not self.api_key else {"Authorization": f"Bearer {self.api_key}"}
-        )
-
-        response = await self.http_client.post(
-            self.api_url,
-            json={
-                "model": model_name,
-                "input": texts,
-            },
-            headers=headers,
-        )
-        response.raise_for_status()
-        result = response.json()
-        return [embedding["embedding"] for embedding in result["data"]]
-
-    @retry(tries=_RETRY_TRIES, delay=_RETRY_DELAY)
-    async def embed(
-        self,
-        *,
-        texts: list[str],
-        text_type: EmbedTextType,
-        model_name: str | None = None,
-        deployment_name: str | None = None,
-        reduced_dimension: int | None = None,
-    ) -> list[Embedding]:
-        try:
-            if self.provider == EmbeddingProvider.OPENAI:
-                return await self._embed_openai(texts, model_name, reduced_dimension)
-            elif self.provider == EmbeddingProvider.AZURE:
-                return await self._embed_azure(texts, f"azure/{deployment_name}")
-            elif self.provider == EmbeddingProvider.LITELLM:
-                return await self._embed_litellm_proxy(texts, model_name)
-
-            embedding_type = EmbeddingModelTextType.get_type(self.provider, text_type)
-            if self.provider == EmbeddingProvider.COHERE:
-                return await self._embed_cohere(texts, model_name, embedding_type)
-            elif self.provider == EmbeddingProvider.VOYAGE:
-                return await self._embed_voyage(texts, model_name, embedding_type)
-            elif self.provider == EmbeddingProvider.GOOGLE:
-                return await self._embed_vertex(texts, model_name, embedding_type)
-            else:
-                raise ValueError(f"Unsupported provider: {self.provider}")
-        except openai.AuthenticationError:
-            raise AuthenticationError(provider="OpenAI")
-        except httpx.HTTPStatusError as e:
-            if e.response.status_code == 401:
-                raise AuthenticationError(provider=str(self.provider))
-
-            error_string = format_embedding_error(
-                e,
-                str(self.provider),
-                model_name or deployment_name,
-                self.provider,
-                sanitized_api_key=self.sanitized_api_key,
-                status_code=e.response.status_code,
-            )
-            logger.error(error_string)
-            logger.debug(f"Exception texts: {texts}")
-
-            raise RuntimeError(error_string)
-        except Exception as e:
-            if is_authentication_error(e):
-                raise AuthenticationError(provider=str(self.provider))
-
-            error_string = format_embedding_error(
-                e,
-                str(self.provider),
-                model_name or deployment_name,
-                self.provider,
-                sanitized_api_key=self.sanitized_api_key,
-            )
-            logger.error(error_string)
-            logger.debug(f"Exception texts: {texts}")
-
-            raise RuntimeError(error_string)
-
-    @staticmethod
-    def create(
-        api_key: str,
-        provider: EmbeddingProvider,
-        api_url: str | None = None,
-        api_version: str | None = None,
-    ) -> "CloudEmbedding":
-        logger.debug(f"Creating Embedding instance for provider: {provider}")
-        return CloudEmbedding(api_key, provider, api_url, api_version)
-
-    async def aclose(self) -> None:
-        """Explicitly close the client."""
-        if not self._closed:
-            await self.http_client.aclose()
-            self._closed = True
-
-    async def __aenter__(self) -> "CloudEmbedding":
-        return self
-
-    async def __aexit__(
-        self,
-        exc_type: type[BaseException] | None,
-        exc_val: BaseException | None,
-        exc_tb: TracebackType | None,
-    ) -> None:
-        await self.aclose()
-
-    def __del__(self) -> None:
-        """Finalizer to warn about unclosed clients."""
-        if not self._closed:
-            logger.warning(
-                "CloudEmbedding was not properly closed. Use 'async with' or call aclose()"
-            )
-
 
 def get_embedding_model(
     model_name: str,
     max_context_length: int,
 ) -> "SentenceTransformer":
+    """
+    Loads or returns a cached SentenceTransformer, sets max_seq_length, pins device,
+    pre-warms rotary caches once, and wraps encode() with a lock to avoid cache races.
+    """
     from sentence_transformers import SentenceTransformer  # type: ignore
 
-    global _GLOBAL_MODELS_DICT  # A dictionary to store models
+    def _prewarm_rope(st_model: "SentenceTransformer", target_len: int) -> None:
+        """
+        Build RoPE cos/sin caches once on the final device/dtype so later forwards only read.
+        Works by calling the underlying HF model directly with dummy IDs/attention.
+        """
+        try:
+            # ensure > max seq after tokenization
+            # Ideally we would use the saved tokenizer, but whatever it's ok
+            # we'll make an assumption about tokenization here
+            long_text = "x " * (target_len * 2)
+            _ = st_model.encode(
+                [long_text],
+                batch_size=1,
+                convert_to_tensor=True,
+                show_progress_bar=False,
+                normalize_embeddings=False,
+            )
+            logger.info("RoPE pre-warm successful")
+        except Exception as e:
+            logger.warning(f"RoPE pre-warm skipped/failed: {e}")
+
+    global _GLOBAL_MODELS_DICT
 
     if model_name not in _GLOBAL_MODELS_DICT:
         logger.notice(f"Loading {model_name}")
-        # Some model architectures that aren't built into the Transformers or Sentence
-        # Transformer need to be downloaded to be loaded locally. This does not mean
-        # data is sent to remote servers for inference, however the remote code can
-        # be fairly arbitrary so only use trusted models
         model = SentenceTransformer(
             model_name_or_path=model_name,
             trust_remote_code=True,
         )
         model.max_seq_length = max_context_length
+        _prewarm_rope(model, max_context_length)
         _GLOBAL_MODELS_DICT[model_name] = model
-    elif max_context_length != _GLOBAL_MODELS_DICT[model_name].max_seq_length:
-        _GLOBAL_MODELS_DICT[model_name].max_seq_length = max_context_length
+    else:
+        model = _GLOBAL_MODELS_DICT[model_name]
+        if max_context_length != model.max_seq_length:
+            model.max_seq_length = max_context_length
+            prev = getattr(model, "_rope_prewarmed_to", 0)
+            if max_context_length > int(prev or 0):
+                _prewarm_rope(model, max_context_length)
 
     return _GLOBAL_MODELS_DICT[model_name]
 
@@ -404,20 +97,34 @@ def get_local_reranking_model(
     return _RERANK_MODEL
 
 
+ENCODING_RETRIES = 3
+ENCODING_RETRY_DELAY = 0.1
+
+
+def _concurrent_embedding(
+    texts: list[str], model: "SentenceTransformer", normalize_embeddings: bool
+) -> Any:
+    """Synchronous wrapper for concurrent_embedding to use with run_in_executor."""
+    for _ in range(ENCODING_RETRIES):
+        try:
+            return model.encode(texts, normalize_embeddings=normalize_embeddings)
+        except RuntimeError as e:
+            # There is a concurrency bug in the SentenceTransformer library that causes
+            # the model to fail to encode texts. It's pretty rare and we want to allow
+            # concurrent embedding, hence we retry (the specific error is
+            # "RuntimeError: Already borrowed" and occurs in the transformers library)
+            logger.error(f"Error encoding texts, retrying: {e}")
+            time.sleep(ENCODING_RETRY_DELAY)
+    return model.encode(texts, normalize_embeddings=normalize_embeddings)
+
+
 @simple_log_function_time()
 async def embed_text(
     texts: list[str],
-    text_type: EmbedTextType,
     model_name: str | None,
-    deployment_name: str | None,
     max_context_length: int,
     normalize_embeddings: bool,
-    api_key: str | None,
-    provider_type: EmbeddingProvider | None,
     prefix: str | None,
-    api_url: str | None,
-    api_version: str | None,
-    reduced_dimension: int | None,
     gpu_type: str = "UNKNOWN",
 ) -> list[Embedding]:
     if not all(texts):
@@ -434,52 +141,10 @@ async def embed_text(
     for text in texts:
         total_chars += len(text)
 
-    if provider_type is not None:
-        logger.info(
-            f"Embedding {len(texts)} texts with {total_chars} total characters with provider: {provider_type}"
-        )
+    # Only local models should call this function now
+    # API providers should go directly to API server
 
-        if api_key is None:
-            logger.error("API key not provided for cloud model")
-            raise RuntimeError("API key not provided for cloud model")
-
-        if prefix:
-            logger.warning("Prefix provided for cloud model, which is not supported")
-            raise ValueError(
-                "Prefix string is not valid for cloud models. "
-                "Cloud models take an explicit text type instead."
-            )
-
-        async with CloudEmbedding(
-            api_key=api_key,
-            provider=provider_type,
-            api_url=api_url,
-            api_version=api_version,
-        ) as cloud_model:
-            embeddings = await cloud_model.embed(
-                texts=texts,
-                model_name=model_name,
-                deployment_name=deployment_name,
-                text_type=text_type,
-                reduced_dimension=reduced_dimension,
-            )
-
-        if any(embedding is None for embedding in embeddings):
-            error_message = "Embeddings contain None values\n"
-            error_message += "Corresponding texts:\n"
-            error_message += "\n".join(texts)
-            logger.error(error_message)
-            raise ValueError(error_message)
-
-        elapsed = time.monotonic() - start
-        logger.info(
-            f"event=embedding_provider "
-            f"texts={len(texts)} "
-            f"chars={total_chars} "
-            f"provider={provider_type} "
-            f"elapsed={elapsed:.2f}"
-        )
-    elif model_name is not None:
+    if model_name is not None:
         logger.info(
             f"Embedding {len(texts)} texts with {total_chars} total characters with local model: {model_name}"
         )
@@ -492,8 +157,8 @@ async def embed_text(
         # Run CPU-bound embedding in a thread pool
         embeddings_vectors = await asyncio.get_event_loop().run_in_executor(
             None,
-            lambda: local_model.encode(
-                prefixed_texts, normalize_embeddings=normalize_embeddings
+            lambda: _concurrent_embedding(
+                prefixed_texts, local_model, normalize_embeddings
             ),
         )
         embeddings = [
@@ -515,10 +180,8 @@ async def embed_text(
             f"elapsed={elapsed:.2f}"
         )
     else:
-        logger.error("Neither model name nor provider specified for embedding")
-        raise ValueError(
-            "Either model name or provider must be provided to run embeddings."
-        )
+        logger.error("Model name not specified for embedding")
+        raise ValueError("Model name must be provided to run embeddings.")
 
     return embeddings
 
@@ -533,77 +196,6 @@ async def local_rerank(query: str, docs: list[str], model_name: str) -> list[flo
     )
 
 
-async def cohere_rerank_api(
-    query: str, docs: list[str], model_name: str, api_key: str
-) -> list[float]:
-    cohere_client = CohereAsyncClient(api_key=api_key)
-    response = await cohere_client.rerank(query=query, documents=docs, model=model_name)
-    results = response.results
-    sorted_results = sorted(results, key=lambda item: item.index)
-    return [result.relevance_score for result in sorted_results]
-
-
-async def cohere_rerank_aws(
-    query: str,
-    docs: list[str],
-    model_name: str,
-    region_name: str,
-    aws_access_key_id: str,
-    aws_secret_access_key: str,
-) -> list[float]:
-    session = aioboto3.Session(
-        aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key
-    )
-    async with session.client(
-        "bedrock-runtime", region_name=region_name
-    ) as bedrock_client:
-        body = json.dumps(
-            {
-                "query": query,
-                "documents": docs,
-                "api_version": 2,
-            }
-        )
-        # Invoke the Bedrock model asynchronously
-        response = await bedrock_client.invoke_model(
-            modelId=model_name,
-            accept="application/json",
-            contentType="application/json",
-            body=body,
-        )
-
-        # Read the response asynchronously
-        response_body = json.loads(await response["body"].read())
-
-        # Extract and sort the results
-        results = response_body.get("results", [])
-        sorted_results = sorted(results, key=lambda item: item["index"])
-
-        return [result["relevance_score"] for result in sorted_results]
-
-
-async def litellm_rerank(
-    query: str, docs: list[str], api_url: str, model_name: str, api_key: str | None
-) -> list[float]:
-    headers = {} if not api_key else {"Authorization": f"Bearer {api_key}"}
-    async with httpx.AsyncClient() as client:
-        response = await client.post(
-            api_url,
-            json={
-                "model": model_name,
-                "query": query,
-                "documents": docs,
-            },
-            headers=headers,
-        )
-        response.raise_for_status()
-        result = response.json()
-        return [
-            item["relevance_score"]
-            for item in sorted(result["results"], key=lambda x: x["index"])
-        ]
-
-
 @router.post("/bi-encoder-embed")
 async def route_bi_encoder_embed(
     request: Request,
@@ -615,6 +207,13 @@ async def route_bi_encoder_embed(
 async def process_embed_request(
     embed_request: EmbedRequest, gpu_type: str = "UNKNOWN"
 ) -> EmbedResponse:
+    # Only local models should use this endpoint - API providers should make direct API calls
+    if embed_request.provider_type is not None:
+        raise ValueError(
+            f"Model server embedding endpoint should only be used for local models. "
+            f"API provider '{embed_request.provider_type}' should make direct API calls instead."
+        )
+
     if not embed_request.texts:
         raise HTTPException(status_code=400, detail="No texts to be embedded")
 
@@ -632,26 +231,12 @@ async def process_embed_request(
         embeddings = await embed_text(
             texts=embed_request.texts,
             model_name=embed_request.model_name,
-            deployment_name=embed_request.deployment_name,
             max_context_length=embed_request.max_context_length,
             normalize_embeddings=embed_request.normalize_embeddings,
-            api_key=embed_request.api_key,
-            provider_type=embed_request.provider_type,
-            text_type=embed_request.text_type,
-            api_url=embed_request.api_url,
-            api_version=embed_request.api_version,
-            reduced_dimension=embed_request.reduced_dimension,
             prefix=prefix,
             gpu_type=gpu_type,
         )
         return EmbedResponse(embeddings=embeddings)
-    except AuthenticationError as e:
-        # Handle authentication errors consistently
-        logger.error(f"Authentication error: {e.provider}")
-        raise HTTPException(
-            status_code=401,
-            detail=f"Authentication failed: {e.message}",
-        )
     except RateLimitError as e:
         raise HTTPException(
             status_code=429,
@@ -669,6 +254,13 @@ async def process_embed_request(
 @router.post("/cross-encoder-scores")
 async def process_rerank_request(rerank_request: RerankRequest) -> RerankResponse:
     """Cross encoders can be purely black box from the app perspective"""
+    # Only local models should use this endpoint - API providers should make direct API calls
+    if rerank_request.provider_type is not None:
+        raise ValueError(
+            f"Model server reranking endpoint should only be used for local models. "
+            f"API provider '{rerank_request.provider_type}' should make direct API calls instead."
+        )
+
     if INDEXING_ONLY:
         raise RuntimeError("Indexing model server should not call intent endpoint")
 
@@ -680,55 +272,13 @@ async def process_rerank_request(rerank_request: RerankRequest) -> RerankRespons
         raise ValueError("Empty documents cannot be reranked.")
 
     try:
-        if rerank_request.provider_type is None:
-            sim_scores = await local_rerank(
-                query=rerank_request.query,
-                docs=rerank_request.documents,
-                model_name=rerank_request.model_name,
-            )
-            return RerankResponse(scores=sim_scores)
-        elif rerank_request.provider_type == RerankerProvider.LITELLM:
-            if rerank_request.api_url is None:
-                raise ValueError("API URL is required for LiteLLM reranking.")
-
-            sim_scores = await litellm_rerank(
-                query=rerank_request.query,
-                docs=rerank_request.documents,
-                api_url=rerank_request.api_url,
-                model_name=rerank_request.model_name,
-                api_key=rerank_request.api_key,
-            )
-
-            return RerankResponse(scores=sim_scores)
-
-        elif rerank_request.provider_type == RerankerProvider.COHERE:
-            if rerank_request.api_key is None:
-                raise RuntimeError("Cohere Rerank Requires an API Key")
-            sim_scores = await cohere_rerank_api(
-                query=rerank_request.query,
-                docs=rerank_request.documents,
-                model_name=rerank_request.model_name,
-                api_key=rerank_request.api_key,
-            )
-            return RerankResponse(scores=sim_scores)
-
-        elif rerank_request.provider_type == RerankerProvider.BEDROCK:
-            if rerank_request.api_key is None:
-                raise RuntimeError("Bedrock Rerank Requires an API Key")
-            aws_access_key_id, aws_secret_access_key, aws_region = pass_aws_key(
-                rerank_request.api_key
-            )
-            sim_scores = await cohere_rerank_aws(
-                query=rerank_request.query,
-                docs=rerank_request.documents,
-                model_name=rerank_request.model_name,
-                region_name=aws_region,
-                aws_access_key_id=aws_access_key_id,
-                aws_secret_access_key=aws_secret_access_key,
-            )
-            return RerankResponse(scores=sim_scores)
-        else:
-            raise ValueError(f"Unsupported provider: {rerank_request.provider_type}")
+        # At this point, provider_type is None, so handle local reranking
+        sim_scores = await local_rerank(
+            query=rerank_request.query,
+            docs=rerank_request.documents,
+            model_name=rerank_request.model_name,
+        )
+        return RerankResponse(scores=sim_scores)
 
     except Exception as e:
         logger.exception(f"Error during reranking process:\n{str(e)}")

backend/model_server/main.py

@@ -34,8 +34,8 @@ from shared_configs.configs import SENTRY_DSN
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
 os.environ["HF_HUB_DISABLE_TELEMETRY"] = "1"
 
-HF_CACHE_PATH = Path(os.path.expanduser("~")) / ".cache/huggingface"
-TEMP_HF_CACHE_PATH = Path(os.path.expanduser("~")) / ".cache/temp_huggingface"
+HF_CACHE_PATH = Path(".cache/huggingface")
+TEMP_HF_CACHE_PATH = Path(".cache/temp_huggingface")
 
 transformer_logging.set_verbosity_error()
 

backend/model_server/utils.py

@@ -70,32 +70,3 @@ def get_gpu_type() -> str:
         return GPUStatus.MAC_MPS
 
     return GPUStatus.NONE
-
-
-def pass_aws_key(api_key: str) -> tuple[str, str, str]:
-    """Parse AWS API key string into components.
-
-    Args:
-        api_key: String in format 'aws_ACCESSKEY_SECRETKEY_REGION'
-
-    Returns:
-        Tuple of (access_key, secret_key, region)
-
-    Raises:
-        ValueError: If key format is invalid
-    """
-    if not api_key.startswith("aws"):
-        raise ValueError("API key must start with 'aws' prefix")
-
-    parts = api_key.split("_")
-    if len(parts) != 4:
-        raise ValueError(
-            f"API key must be in format 'aws_ACCESSKEY_SECRETKEY_REGION', got {len(parts) - 1} parts"
-            "this is an onyx specific format for formatting the aws secrets for bedrock"
-        )
-
-    try:
-        _, aws_access_key_id, aws_secret_access_key, aws_region = parts
-        return aws_access_key_id, aws_secret_access_key, aws_region
-    except Exception as e:
-        raise ValueError(f"Failed to parse AWS key components: {str(e)}")

backend/onyx/agents/agent_search/basic/graph_builder.py

@@ -1,97 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from onyx.agents.agent_search.basic.states import BasicInput
-from onyx.agents.agent_search.basic.states import BasicOutput
-from onyx.agents.agent_search.basic.states import BasicState
-from onyx.agents.agent_search.orchestration.nodes.call_tool import call_tool
-from onyx.agents.agent_search.orchestration.nodes.choose_tool import choose_tool
-from onyx.agents.agent_search.orchestration.nodes.prepare_tool_input import (
-    prepare_tool_input,
-)
-from onyx.agents.agent_search.orchestration.nodes.use_tool_response import (
-    basic_use_tool_response,
-)
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-def basic_graph_builder() -> StateGraph:
-    graph = StateGraph(
-        state_schema=BasicState,
-        input=BasicInput,
-        output=BasicOutput,
-    )
-
-    ### Add nodes ###
-
-    graph.add_node(
-        node="prepare_tool_input",
-        action=prepare_tool_input,
-    )
-
-    graph.add_node(
-        node="choose_tool",
-        action=choose_tool,
-    )
-
-    graph.add_node(
-        node="call_tool",
-        action=call_tool,
-    )
-
-    graph.add_node(
-        node="basic_use_tool_response",
-        action=basic_use_tool_response,
-    )
-
-    ### Add edges ###
-
-    graph.add_edge(start_key=START, end_key="prepare_tool_input")
-
-    graph.add_edge(start_key="prepare_tool_input", end_key="choose_tool")
-
-    graph.add_conditional_edges("choose_tool", should_continue, ["call_tool", END])
-
-    graph.add_edge(
-        start_key="call_tool",
-        end_key="basic_use_tool_response",
-    )
-
-    graph.add_edge(
-        start_key="basic_use_tool_response",
-        end_key=END,
-    )
-
-    return graph
-
-
-def should_continue(state: BasicState) -> str:
-    return (
-        # If there are no tool calls, basic graph already streamed the answer
-        END
-        if state.tool_choice is None
-        else "call_tool"
-    )
-
-
-if __name__ == "__main__":
-    from onyx.db.engine.sql_engine import get_session_with_current_tenant
-    from onyx.context.search.models import SearchRequest
-    from onyx.llm.factory import get_default_llms
-    from onyx.agents.agent_search.shared_graph_utils.utils import get_test_config
-
-    graph = basic_graph_builder()
-    compiled_graph = graph.compile()
-    input = BasicInput(unused=True)
-    primary_llm, fast_llm = get_default_llms()
-    with get_session_with_current_tenant() as db_session:
-        config, _ = get_test_config(
-            db_session=db_session,
-            primary_llm=primary_llm,
-            fast_llm=fast_llm,
-            search_request=SearchRequest(query="How does onyx use FastAPI?"),
-        )
-        compiled_graph.invoke(input, config={"metadata": {"config": config}})

backend/onyx/agents/agent_search/basic/states.py

@@ -1,35 +0,0 @@
-from typing import TypedDict
-
-from langchain_core.messages import AIMessageChunk
-from pydantic import BaseModel
-
-from onyx.agents.agent_search.orchestration.states import ToolCallUpdate
-from onyx.agents.agent_search.orchestration.states import ToolChoiceInput
-from onyx.agents.agent_search.orchestration.states import ToolChoiceUpdate
-
-# States contain values that change over the course of graph execution,
-# Config is for values that are set at the start and never change.
-# If you are using a value from the config and realize it needs to change,
-# you should add it to the state and use/update the version in the state.
-
-
-## Graph Input State
-class BasicInput(BaseModel):
-    # Langgraph needs a nonempty input, but we pass in all static
-    # data through a RunnableConfig.
-    unused: bool = True
-
-
-## Graph Output State
-class BasicOutput(TypedDict):
-    tool_call_chunk: AIMessageChunk
-
-
-## Graph State
-class BasicState(
-    BasicInput,
-    ToolChoiceInput,
-    ToolCallUpdate,
-    ToolChoiceUpdate,
-):
-    pass

backend/onyx/agents/agent_search/basic/utils.py

@@ -1,64 +0,0 @@
-from collections.abc import Iterator
-from typing import cast
-
-from langchain_core.messages import AIMessageChunk
-from langchain_core.messages import BaseMessage
-from langgraph.types import StreamWriter
-
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import LlmDoc
-from onyx.chat.stream_processing.answer_response_handler import AnswerResponseHandler
-from onyx.chat.stream_processing.answer_response_handler import CitationResponseHandler
-from onyx.chat.stream_processing.answer_response_handler import (
-    PassThroughAnswerResponseHandler,
-)
-from onyx.chat.stream_processing.utils import map_document_id_order
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-def process_llm_stream(
-    messages: Iterator[BaseMessage],
-    should_stream_answer: bool,
-    writer: StreamWriter,
-    final_search_results: list[LlmDoc] | None = None,
-    displayed_search_results: list[LlmDoc] | None = None,
-) -> AIMessageChunk:
-    tool_call_chunk = AIMessageChunk(content="")
-
-    if final_search_results and displayed_search_results:
-        answer_handler: AnswerResponseHandler = CitationResponseHandler(
-            context_docs=final_search_results,
-            final_doc_id_to_rank_map=map_document_id_order(final_search_results),
-            display_doc_id_to_rank_map=map_document_id_order(displayed_search_results),
-        )
-    else:
-        answer_handler = PassThroughAnswerResponseHandler()
-
-    full_answer = ""
-    # This stream will be the llm answer if no tool is chosen. When a tool is chosen,
-    # the stream will contain AIMessageChunks with tool call information.
-    for message in messages:
-
-        answer_piece = message.content
-        if not isinstance(answer_piece, str):
-            # this is only used for logging, so fine to
-            # just add the string representation
-            answer_piece = str(answer_piece)
-        full_answer += answer_piece
-
-        if isinstance(message, AIMessageChunk) and (
-            message.tool_call_chunks or message.tool_calls
-        ):
-            tool_call_chunk += message  # type: ignore
-        elif should_stream_answer:
-            for response_part in answer_handler.handle_response_part(message, []):
-                write_custom_event(
-                    "basic_response",
-                    response_part,
-                    writer,
-                )
-
-    logger.debug(f"Full answer: {full_answer}")
-    return cast(AIMessageChunk, tool_call_chunk)

backend/onyx/agents/agent_search/core_state.py

@@ -10,6 +10,7 @@ class CoreState(BaseModel):
     """
 
     log_messages: Annotated[list[str], add] = []
+    current_step_nr: int = 1
 
 
 class SubgraphCoreState(BaseModel):

backend/onyx/agents/agent_search/dc_search_analysis/nodes/a1_search_objects.py

@@ -14,8 +14,6 @@ from onyx.agents.agent_search.models import GraphConfig
 from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
     trim_prompt_piece,
 )
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import AgentAnswerPiece
 from onyx.configs.constants import DocumentSource
 from onyx.prompts.agents.dc_prompts import DC_OBJECT_NO_BASE_DATA_EXTRACTION_PROMPT
 from onyx.prompts.agents.dc_prompts import DC_OBJECT_SEPARATOR
@@ -41,7 +39,7 @@ def search_objects(
         raise ValueError("Search tool and persona must be provided for DivCon search")
 
     try:
-        instructions = graph_config.inputs.persona.prompts[0].system_prompt
+        instructions = graph_config.inputs.persona.system_prompt or ""
 
         agent_1_instructions = extract_section(
             instructions, "Agent Step 1:", "Agent Step 2:"
@@ -139,17 +137,6 @@ def search_objects(
     except Exception as e:
         raise ValueError(f"Error in search_objects: {e}")
 
-    write_custom_event(
-        "initial_agent_answer",
-        AgentAnswerPiece(
-            answer_piece=" Researching the individual objects for each source type... ",
-            level=0,
-            level_question_num=0,
-            answer_type="agent_level_answer",
-        ),
-        writer,
-    )
-
     return SearchSourcesObjectsUpdate(
         analysis_objects=object_list,
         analysis_sources=document_sources,

backend/onyx/agents/agent_search/dc_search_analysis/nodes/a2_research_object_source.py

@@ -43,7 +43,7 @@ def research_object_source(
         raise ValueError("Search tool and persona must be provided for DivCon search")
 
     try:
-        instructions = graph_config.inputs.persona.prompts[0].system_prompt
+        instructions = graph_config.inputs.persona.system_prompt or ""
 
         agent_2_instructions = extract_section(
             instructions, "Agent Step 2:", "Agent Step 3:"

backend/onyx/agents/agent_search/dc_search_analysis/nodes/a3_structure_research_by_object.py

@@ -9,8 +9,6 @@ from onyx.agents.agent_search.dc_search_analysis.states import MainState
 from onyx.agents.agent_search.dc_search_analysis.states import (
     ObjectResearchInformationUpdate,
 )
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import AgentAnswerPiece
 from onyx.utils.logger import setup_logger
 
 logger = setup_logger()
@@ -23,17 +21,6 @@ def structure_research_by_object(
     LangGraph node to start the agentic search process.
     """
 
-    write_custom_event(
-        "initial_agent_answer",
-        AgentAnswerPiece(
-            answer_piece=" consolidating the information across source types for each object...",
-            level=0,
-            level_question_num=0,
-            answer_type="agent_level_answer",
-        ),
-        writer,
-    )
-
     object_source_research_results = state.object_source_research_results
 
     object_research_information_results: List[Dict[str, str]] = []

backend/onyx/agents/agent_search/dc_search_analysis/nodes/a4_consolidate_object_research.py

@@ -33,7 +33,7 @@ def consolidate_object_research(
     if search_tool is None or graph_config.inputs.persona is None:
         raise ValueError("Search tool and persona must be provided for DivCon search")
 
-    instructions = graph_config.inputs.persona.prompts[0].system_prompt
+    instructions = graph_config.inputs.persona.system_prompt or ""
 
     agent_4_instructions = extract_section(
         instructions, "Agent Step 4:", "Agent Step 5:"

backend/onyx/agents/agent_search/dc_search_analysis/nodes/a5_consolidate_research.py

@@ -12,8 +12,6 @@ from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
     trim_prompt_piece,
 )
 from onyx.agents.agent_search.shared_graph_utils.llm import stream_llm_answer
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import AgentAnswerPiece
 from onyx.prompts.agents.dc_prompts import DC_FORMATTING_NO_BASE_DATA_PROMPT
 from onyx.prompts.agents.dc_prompts import DC_FORMATTING_WITH_BASE_DATA_PROMPT
 from onyx.utils.logger import setup_logger
@@ -33,22 +31,11 @@ def consolidate_research(
 
     search_tool = graph_config.tooling.search_tool
 
-    write_custom_event(
-        "initial_agent_answer",
-        AgentAnswerPiece(
-            answer_piece=" generating the answer\n\n\n",
-            level=0,
-            level_question_num=0,
-            answer_type="agent_level_answer",
-        ),
-        writer,
-    )
-
     if search_tool is None or graph_config.inputs.persona is None:
         raise ValueError("Search tool and persona must be provided for DivCon search")
 
     # Populate prompt
-    instructions = graph_config.inputs.persona.prompts[0].system_prompt
+    instructions = graph_config.inputs.persona.system_prompt or ""
 
     try:
         agent_5_instructions = extract_section(

backend/onyx/agents/agent_search/deep_search/initial/generate_individual_sub_answer/edges.py

@@ -1,31 +0,0 @@
-from collections.abc import Hashable
-from datetime import datetime
-
-from langgraph.types import Send
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnsweringInput,
-)
-from onyx.agents.agent_search.deep_search.shared.expanded_retrieval.states import (
-    ExpandedRetrievalInput,
-)
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-def send_to_expanded_retrieval(state: SubQuestionAnsweringInput) -> Send | Hashable:
-    """
-    LangGraph edge to send a sub-question to the expanded retrieval.
-    """
-    edge_start_time = datetime.now()
-
-    return Send(
-        "initial_sub_question_expanded_retrieval",
-        ExpandedRetrievalInput(
-            question=state.question,
-            base_search=False,
-            sub_question_id=state.question_id,
-            log_messages=[f"{edge_start_time} -- Sending to expanded retrieval"],
-        ),
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_individual_sub_answer/graph_builder.py

@@ -1,137 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.edges import (
-    send_to_expanded_retrieval,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.nodes.check_sub_answer import (
-    check_sub_answer,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.nodes.format_sub_answer import (
-    format_sub_answer,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.nodes.generate_sub_answer import (
-    generate_sub_answer,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.nodes.ingest_retrieved_documents import (
-    ingest_retrieved_documents,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionOutput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionState,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnsweringInput,
-)
-from onyx.agents.agent_search.deep_search.shared.expanded_retrieval.graph_builder import (
-    expanded_retrieval_graph_builder,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import get_test_config
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-def answer_query_graph_builder() -> StateGraph:
-    """
-    LangGraph sub-graph builder for the initial individual sub-answer generation.
-    """
-    graph = StateGraph(
-        state_schema=AnswerQuestionState,
-        input=SubQuestionAnsweringInput,
-        output=AnswerQuestionOutput,
-    )
-
-    ### Add nodes ###
-
-    # The sub-graph that executes the expanded retrieval process for a sub-question
-    expanded_retrieval = expanded_retrieval_graph_builder().compile()
-    graph.add_node(
-        node="initial_sub_question_expanded_retrieval",
-        action=expanded_retrieval,
-    )
-
-    # The node that ingests the retrieved documents and puts them into the proper
-    # state keys.
-    graph.add_node(
-        node="ingest_retrieval",
-        action=ingest_retrieved_documents,
-    )
-
-    # The node that generates the sub-answer
-    graph.add_node(
-        node="generate_sub_answer",
-        action=generate_sub_answer,
-    )
-
-    # The node that checks the sub-answer
-    graph.add_node(
-        node="answer_check",
-        action=check_sub_answer,
-    )
-
-    # The node that formats the sub-answer for the following initial answer generation
-    graph.add_node(
-        node="format_answer",
-        action=format_sub_answer,
-    )
-
-    ### Add edges ###
-
-    graph.add_conditional_edges(
-        source=START,
-        path=send_to_expanded_retrieval,
-        path_map=["initial_sub_question_expanded_retrieval"],
-    )
-    graph.add_edge(
-        start_key="initial_sub_question_expanded_retrieval",
-        end_key="ingest_retrieval",
-    )
-    graph.add_edge(
-        start_key="ingest_retrieval",
-        end_key="generate_sub_answer",
-    )
-    graph.add_edge(
-        start_key="generate_sub_answer",
-        end_key="answer_check",
-    )
-    graph.add_edge(
-        start_key="answer_check",
-        end_key="format_answer",
-    )
-    graph.add_edge(
-        start_key="format_answer",
-        end_key=END,
-    )
-
-    return graph
-
-
-if __name__ == "__main__":
-    from onyx.db.engine.sql_engine import get_session_with_current_tenant
-    from onyx.llm.factory import get_default_llms
-    from onyx.context.search.models import SearchRequest
-
-    graph = answer_query_graph_builder()
-    compiled_graph = graph.compile()
-    primary_llm, fast_llm = get_default_llms()
-    search_request = SearchRequest(
-        query="what can you do with onyx or danswer?",
-    )
-    with get_session_with_current_tenant() as db_session:
-        graph_config, search_tool = get_test_config(
-            db_session, primary_llm, fast_llm, search_request
-        )
-        inputs = SubQuestionAnsweringInput(
-            question="what can you do with onyx?",
-            question_id="0_0",
-            log_messages=[],
-        )
-        for thing in compiled_graph.stream(
-            input=inputs,
-            config={"configurable": {"config": graph_config}},
-        ):
-            logger.debug(thing)

backend/onyx/agents/agent_search/deep_search/initial/generate_individual_sub_answer/nodes/check_sub_answer.py

@@ -1,136 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import BaseMessage
-from langchain_core.messages import HumanMessage
-from langchain_core.runnables.config import RunnableConfig
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionState,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnswerCheckUpdate,
-)
-from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    binary_string_test,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_RATELIMIT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_TIMEOUT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_POSITIVE_VALUE_STR,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import AgentLLMErrorType
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import parse_question_id
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_VALIDATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_CHECK
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_SUBANSWER_CHECK
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
-from onyx.prompts.agent_search import SUB_ANSWER_CHECK_PROMPT
-from onyx.prompts.agent_search import UNKNOWN_ANSWER
-from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-logger = setup_logger()
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. The sub-answer will be treated as 'relevant'",
-    rate_limit="LLM Rate Limit Error. The sub-answer will be treated as 'relevant'",
-    general_error="General LLM Error. The sub-answer will be treated as 'relevant'",
-)
-
-
-@log_function_time(print_only=True)
-def check_sub_answer(
-    state: AnswerQuestionState, config: RunnableConfig
-) -> SubQuestionAnswerCheckUpdate:
-    """
-    LangGraph node to check the quality of the sub-answer. The answer
-    is represented as a boolean value.
-    """
-    node_start_time = datetime.now()
-
-    level, question_num = parse_question_id(state.question_id)
-    if state.answer == UNKNOWN_ANSWER:
-        return SubQuestionAnswerCheckUpdate(
-            answer_quality=False,
-            log_messages=[
-                get_langgraph_node_log_string(
-                    graph_component="initial  - generate individual sub answer",
-                    node_name="check sub answer",
-                    node_start_time=node_start_time,
-                    result="unknown answer",
-                )
-            ],
-        )
-    msg = [
-        HumanMessage(
-            content=SUB_ANSWER_CHECK_PROMPT.format(
-                question=state.question,
-                base_answer=state.answer,
-            )
-        )
-    ]
-
-    graph_config = cast(GraphConfig, config["metadata"]["config"])
-    fast_llm = graph_config.tooling.fast_llm
-    agent_error: AgentErrorLog | None = None
-    response: BaseMessage | None = None
-    try:
-        response = run_with_timeout(
-            AGENT_TIMEOUT_LLM_SUBANSWER_CHECK,
-            fast_llm.invoke,
-            prompt=msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_CHECK,
-            max_tokens=AGENT_MAX_TOKENS_VALIDATION,
-        )
-
-        quality_str: str = cast(str, response.content)
-        answer_quality = binary_string_test(
-            text=quality_str, positive_value=AGENT_POSITIVE_VALUE_STR
-        )
-        log_result = f"Answer quality: {quality_str}"
-
-    except (LLMTimeoutError, TimeoutError):
-        agent_error = AgentErrorLog(
-            error_type=AgentLLMErrorType.TIMEOUT,
-            error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-            error_result=_llm_node_error_strings.timeout,
-        )
-        answer_quality = True
-        log_result = agent_error.error_result
-        logger.error("LLM Timeout Error - check sub answer")
-
-    except LLMRateLimitError:
-        agent_error = AgentErrorLog(
-            error_type=AgentLLMErrorType.RATE_LIMIT,
-            error_message=AGENT_LLM_RATELIMIT_MESSAGE,
-            error_result=_llm_node_error_strings.rate_limit,
-        )
-
-        answer_quality = True
-        log_result = agent_error.error_result
-        logger.error("LLM Rate Limit Error - check sub answer")
-
-    return SubQuestionAnswerCheckUpdate(
-        answer_quality=answer_quality,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial  - generate individual sub answer",
-                node_name="check sub answer",
-                node_start_time=node_start_time,
-                result=log_result,
-            )
-        ],
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_individual_sub_answer/nodes/format_sub_answer.py

@@ -1,30 +0,0 @@
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionOutput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionState,
-)
-from onyx.agents.agent_search.shared_graph_utils.models import (
-    SubQuestionAnswerResults,
-)
-
-
-def format_sub_answer(state: AnswerQuestionState) -> AnswerQuestionOutput:
-    """
-    LangGraph node to generate the sub-answer format.
-    """
-    return AnswerQuestionOutput(
-        answer_results=[
-            SubQuestionAnswerResults(
-                question=state.question,
-                question_id=state.question_id,
-                verified_high_quality=state.answer_quality,
-                answer=state.answer,
-                sub_query_retrieval_results=state.expanded_retrieval_results,
-                verified_reranked_documents=state.verified_reranked_documents,
-                context_documents=state.context_documents,
-                cited_documents=state.cited_documents,
-                sub_question_retrieval_stats=state.sub_question_retrieval_stats,
-            )
-        ],
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_individual_sub_answer/nodes/generate_sub_answer.py

@@ -1,185 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import merge_message_runs
-from langchain_core.runnables.config import RunnableConfig
-from langgraph.types import StreamWriter
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionState,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnswerGenerationUpdate,
-)
-from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    build_sub_question_answer_prompt,
-)
-from onyx.agents.agent_search.shared_graph_utils.calculations import (
-    dedup_sort_inference_section_list,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_RATELIMIT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_TIMEOUT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AgentLLMErrorType,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    LLM_ANSWER_ERROR_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.llm import stream_llm_answer
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
-from onyx.agents.agent_search.shared_graph_utils.utils import get_answer_citation_ids
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_persona_agent_prompt_expressions,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import parse_question_id
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import AgentAnswerPiece
-from onyx.chat.models import StreamStopInfo
-from onyx.chat.models import StreamStopReason
-from onyx.chat.models import StreamType
-from onyx.configs.agent_configs import AGENT_MAX_ANSWER_CONTEXT_DOCS
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_SUBANSWER_GENERATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_GENERATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_SUBANSWER_GENERATION
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
-from onyx.prompts.agent_search import NO_RECOVERED_DOCS
-from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-logger = setup_logger()
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-    rate_limit="LLM Rate Limit Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-    general_error="General LLM Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-)
-
-
-@log_function_time(print_only=True)
-def generate_sub_answer(
-    state: AnswerQuestionState,
-    config: RunnableConfig,
-    writer: StreamWriter = lambda _: None,
-) -> SubQuestionAnswerGenerationUpdate:
-    """
-    LangGraph node to generate a sub-answer.
-    """
-    node_start_time = datetime.now()
-
-    graph_config = cast(GraphConfig, config["metadata"]["config"])
-    question = state.question
-    state.verified_reranked_documents
-    level, question_num = parse_question_id(state.question_id)
-    context_docs = state.context_documents[:AGENT_MAX_ANSWER_CONTEXT_DOCS]
-
-    context_docs = dedup_sort_inference_section_list(context_docs)
-
-    persona_contextualized_prompt = get_persona_agent_prompt_expressions(
-        graph_config.inputs.persona
-    ).contextualized_prompt
-
-    if len(context_docs) == 0:
-        answer_str = NO_RECOVERED_DOCS
-        cited_documents: list = []
-        log_results = "No documents retrieved"
-        write_custom_event(
-            "sub_answers",
-            AgentAnswerPiece(
-                answer_piece=answer_str,
-                level=level,
-                level_question_num=question_num,
-                answer_type="agent_sub_answer",
-            ),
-            writer,
-        )
-    else:
-        fast_llm = graph_config.tooling.fast_llm
-        msg = build_sub_question_answer_prompt(
-            question=question,
-            original_question=graph_config.inputs.prompt_builder.raw_user_query,
-            docs=context_docs,
-            persona_specification=persona_contextualized_prompt,
-            config=fast_llm.config,
-        )
-
-        agent_error: AgentErrorLog | None = None
-        response: list[str] = []
-
-        try:
-            response, _ = run_with_timeout(
-                AGENT_TIMEOUT_LLM_SUBANSWER_GENERATION,
-                lambda: stream_llm_answer(
-                    llm=fast_llm,
-                    prompt=msg,
-                    event_name="sub_answers",
-                    writer=writer,
-                    agent_answer_level=level,
-                    agent_answer_question_num=question_num,
-                    agent_answer_type="agent_sub_answer",
-                    timeout_override=AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_GENERATION,
-                    max_tokens=AGENT_MAX_TOKENS_SUBANSWER_GENERATION,
-                ),
-            )
-
-        except (LLMTimeoutError, TimeoutError):
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.TIMEOUT,
-                error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-                error_result=_llm_node_error_strings.timeout,
-            )
-            logger.error("LLM Timeout Error - generate sub answer")
-        except LLMRateLimitError:
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.RATE_LIMIT,
-                error_message=AGENT_LLM_RATELIMIT_MESSAGE,
-                error_result=_llm_node_error_strings.rate_limit,
-            )
-            logger.error("LLM Rate Limit Error - generate sub answer")
-
-        if agent_error:
-            answer_str = LLM_ANSWER_ERROR_MESSAGE
-            cited_documents = []
-            log_results = (
-                agent_error.error_result
-                or "Sub-answer generation failed due to LLM error"
-            )
-
-        else:
-            answer_str = merge_message_runs(response, chunk_separator="")[0].content
-            answer_citation_ids = get_answer_citation_ids(answer_str)
-            cited_documents = [
-                context_docs[id] for id in answer_citation_ids if id < len(context_docs)
-            ]
-            log_results = None
-
-    stop_event = StreamStopInfo(
-        stop_reason=StreamStopReason.FINISHED,
-        stream_type=StreamType.SUB_ANSWER,
-        level=level,
-        level_question_num=question_num,
-    )
-    write_custom_event("stream_finished", stop_event, writer)
-
-    return SubQuestionAnswerGenerationUpdate(
-        answer=answer_str,
-        cited_documents=cited_documents,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial - generate individual sub answer",
-                node_name="generate sub answer",
-                node_start_time=node_start_time,
-                result=log_results or "",
-            )
-        ],
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_individual_sub_answer/nodes/ingest_retrieved_documents.py

@@ -1,25 +0,0 @@
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionRetrievalIngestionUpdate,
-)
-from onyx.agents.agent_search.deep_search.shared.expanded_retrieval.states import (
-    ExpandedRetrievalOutput,
-)
-from onyx.agents.agent_search.shared_graph_utils.models import AgentChunkRetrievalStats
-
-
-def ingest_retrieved_documents(
-    state: ExpandedRetrievalOutput,
-) -> SubQuestionRetrievalIngestionUpdate:
-    """
-    LangGraph node to ingest the retrieved documents to format it for the sub-answer.
-    """
-    sub_question_retrieval_stats = state.expanded_retrieval_result.retrieval_stats
-    if sub_question_retrieval_stats is None:
-        sub_question_retrieval_stats = [AgentChunkRetrievalStats()]
-
-    return SubQuestionRetrievalIngestionUpdate(
-        expanded_retrieval_results=state.expanded_retrieval_result.expanded_query_results,
-        verified_reranked_documents=state.expanded_retrieval_result.verified_reranked_documents,
-        context_documents=state.expanded_retrieval_result.context_documents,
-        sub_question_retrieval_stats=sub_question_retrieval_stats,
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_individual_sub_answer/states.py

@@ -1,73 +0,0 @@
-from operator import add
-from typing import Annotated
-
-from pydantic import BaseModel
-
-from onyx.agents.agent_search.core_state import SubgraphCoreState
-from onyx.agents.agent_search.deep_search.main.states import LoggerUpdate
-from onyx.agents.agent_search.shared_graph_utils.models import AgentChunkRetrievalStats
-from onyx.agents.agent_search.shared_graph_utils.models import QueryRetrievalResult
-from onyx.agents.agent_search.shared_graph_utils.models import (
-    SubQuestionAnswerResults,
-)
-from onyx.agents.agent_search.shared_graph_utils.operators import (
-    dedup_inference_sections,
-)
-from onyx.context.search.models import InferenceSection
-
-
-## Update States
-class SubQuestionAnswerCheckUpdate(LoggerUpdate, BaseModel):
-    answer_quality: bool = False
-    log_messages: list[str] = []
-
-
-class SubQuestionAnswerGenerationUpdate(LoggerUpdate, BaseModel):
-    answer: str = ""
-    log_messages: list[str] = []
-    cited_documents: Annotated[list[InferenceSection], dedup_inference_sections] = []
-    # answer_stat: AnswerStats
-
-
-class SubQuestionRetrievalIngestionUpdate(LoggerUpdate, BaseModel):
-    expanded_retrieval_results: list[QueryRetrievalResult] = []
-    verified_reranked_documents: Annotated[
-        list[InferenceSection], dedup_inference_sections
-    ] = []
-    context_documents: Annotated[list[InferenceSection], dedup_inference_sections] = []
-    sub_question_retrieval_stats: AgentChunkRetrievalStats = AgentChunkRetrievalStats()
-
-
-## Graph Input State
-
-
-class SubQuestionAnsweringInput(SubgraphCoreState):
-    question: str
-    question_id: str
-    # level 0 is original question and first decomposition, level 1 is follow up, etc
-    # question_num is a unique number per original question per level.
-
-
-## Graph State
-
-
-class AnswerQuestionState(
-    SubQuestionAnsweringInput,
-    SubQuestionAnswerGenerationUpdate,
-    SubQuestionAnswerCheckUpdate,
-    SubQuestionRetrievalIngestionUpdate,
-):
-    pass
-
-
-## Graph Output State
-
-
-class AnswerQuestionOutput(LoggerUpdate, BaseModel):
-    """
-    This is a list of results even though each call of this subgraph only returns one result.
-    This is because if we parallelize the answer query subgraph, there will be multiple
-      results in a list so the add operator is used to add them together.
-    """
-
-    answer_results: Annotated[list[SubQuestionAnswerResults], add] = []

backend/onyx/agents/agent_search/deep_search/initial/generate_initial_answer/edges.py

@@ -1,50 +0,0 @@
-from collections.abc import Hashable
-from datetime import datetime
-
-from langgraph.types import Send
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionOutput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnsweringInput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalState,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import make_question_id
-
-
-def parallelize_initial_sub_question_answering(
-    state: SubQuestionRetrievalState,
-) -> list[Send | Hashable]:
-    """
-    LangGraph edge to parallelize the initial sub-question answering. If there are no sub-questions,
-    we send empty answers to the initial answer generation, and that answer would be generated
-    solely based on the documents retrieved for the original question.
-    """
-    edge_start_time = datetime.now()
-    if len(state.initial_sub_questions) > 0:
-        return [
-            Send(
-                "answer_query_subgraph",
-                SubQuestionAnsweringInput(
-                    question=question,
-                    question_id=make_question_id(0, question_num + 1),
-                    log_messages=[
-                        f"{edge_start_time} -- Main Edge - Parallelize Initial Sub-question Answering"
-                    ],
-                ),
-            )
-            for question_num, question in enumerate(state.initial_sub_questions)
-        ]
-
-    else:
-        return [
-            Send(
-                "ingest_answers",
-                AnswerQuestionOutput(
-                    answer_results=[],
-                ),
-            )
-        ]

backend/onyx/agents/agent_search/deep_search/initial/generate_initial_answer/graph_builder.py

@@ -1,96 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.nodes.generate_initial_answer import (
-    generate_initial_answer,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.nodes.validate_initial_answer import (
-    validate_initial_answer,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalInput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalState,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_sub_answers.graph_builder import (
-    generate_sub_answers_graph_builder,
-)
-from onyx.agents.agent_search.deep_search.initial.retrieve_orig_question_docs.graph_builder import (
-    retrieve_orig_question_docs_graph_builder,
-)
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-def generate_initial_answer_graph_builder(test_mode: bool = False) -> StateGraph:
-    """
-    LangGraph graph builder for the initial answer generation.
-    """
-    graph = StateGraph(
-        state_schema=SubQuestionRetrievalState,
-        input=SubQuestionRetrievalInput,
-    )
-
-    # The sub-graph that generates the initial sub-answers
-    generate_sub_answers = generate_sub_answers_graph_builder().compile()
-    graph.add_node(
-        node="generate_sub_answers_subgraph",
-        action=generate_sub_answers,
-    )
-
-    # The sub-graph that retrieves the original question documents. This is run
-    # in parallel with the sub-answer generation process
-    retrieve_orig_question_docs = retrieve_orig_question_docs_graph_builder().compile()
-    graph.add_node(
-        node="retrieve_orig_question_docs_subgraph_wrapper",
-        action=retrieve_orig_question_docs,
-    )
-
-    # Node that generates the initial answer using the results of the previous
-    # two sub-graphs
-    graph.add_node(
-        node="generate_initial_answer",
-        action=generate_initial_answer,
-    )
-
-    # Node that validates the initial answer
-    graph.add_node(
-        node="validate_initial_answer",
-        action=validate_initial_answer,
-    )
-
-    ### Add edges ###
-
-    graph.add_edge(
-        start_key=START,
-        end_key="retrieve_orig_question_docs_subgraph_wrapper",
-    )
-
-    graph.add_edge(
-        start_key=START,
-        end_key="generate_sub_answers_subgraph",
-    )
-
-    # Wait for both, the original question docs and the sub-answers to be generated before proceeding
-    graph.add_edge(
-        start_key=[
-            "retrieve_orig_question_docs_subgraph_wrapper",
-            "generate_sub_answers_subgraph",
-        ],
-        end_key="generate_initial_answer",
-    )
-
-    graph.add_edge(
-        start_key="generate_initial_answer",
-        end_key="validate_initial_answer",
-    )
-
-    graph.add_edge(
-        start_key="validate_initial_answer",
-        end_key=END,
-    )
-
-    return graph

backend/onyx/agents/agent_search/deep_search/initial/generate_initial_answer/nodes/generate_initial_answer.py

@@ -1,405 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_content
-from langchain_core.runnables import RunnableConfig
-from langgraph.types import StreamWriter
-
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalState,
-)
-from onyx.agents.agent_search.deep_search.main.models import AgentBaseMetrics
-from onyx.agents.agent_search.deep_search.main.operations import (
-    calculate_initial_agent_stats,
-)
-from onyx.agents.agent_search.deep_search.main.operations import get_query_info
-from onyx.agents.agent_search.deep_search.main.operations import logger
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialAnswerUpdate,
-)
-from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    get_prompt_enrichment_components,
-)
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    trim_prompt_piece,
-)
-from onyx.agents.agent_search.shared_graph_utils.calculations import (
-    get_answer_generation_documents,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_RATELIMIT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_TIMEOUT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AgentLLMErrorType,
-)
-from onyx.agents.agent_search.shared_graph_utils.llm import stream_llm_answer
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
-from onyx.agents.agent_search.shared_graph_utils.models import InitialAgentResultStats
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
-from onyx.agents.agent_search.shared_graph_utils.operators import (
-    dedup_inference_section_list,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import _should_restrict_tokens
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    dispatch_main_answer_stop_info,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_deduplicated_structured_subquestion_documents,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import relevance_from_docs
-from onyx.agents.agent_search.shared_graph_utils.utils import remove_document_citations
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import AgentAnswerPiece
-from onyx.chat.models import ExtendedToolResponse
-from onyx.chat.models import StreamingError
-from onyx.configs.agent_configs import AGENT_ANSWER_GENERATION_BY_FAST_LLM
-from onyx.configs.agent_configs import AGENT_MAX_ANSWER_CONTEXT_DOCS
-from onyx.configs.agent_configs import AGENT_MAX_STREAMED_DOCS_FOR_INITIAL_ANSWER
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_ANSWER_GENERATION
-from onyx.configs.agent_configs import AGENT_MIN_ORIG_QUESTION_DOCS
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_INITIAL_ANSWER_GENERATION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_LLM_INITIAL_ANSWER_GENERATION,
-)
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
-from onyx.prompts.agent_search import INITIAL_ANSWER_PROMPT_W_SUB_QUESTIONS
-from onyx.prompts.agent_search import (
-    INITIAL_ANSWER_PROMPT_WO_SUB_QUESTIONS,
-)
-from onyx.prompts.agent_search import (
-    SUB_QUESTION_ANSWER_TEMPLATE,
-)
-from onyx.prompts.agent_search import UNKNOWN_ANSWER
-from onyx.tools.tool_implementations.search.search_tool import yield_search_responses
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. The initial answer could not be generated.",
-    rate_limit="LLM Rate Limit Error. The initial answer could not be generated.",
-    general_error="General LLM Error. The initial answer could not be generated.",
-)
-
-
-@log_function_time(print_only=True)
-def generate_initial_answer(
-    state: SubQuestionRetrievalState,
-    config: RunnableConfig,
-    writer: StreamWriter = lambda _: None,
-) -> InitialAnswerUpdate:
-    """
-    LangGraph node to generate the initial answer, using the initial sub-questions/sub-answers and the
-    documents retrieved for the original question.
-    """
-    node_start_time = datetime.now()
-
-    graph_config = cast(GraphConfig, config["metadata"]["config"])
-    question = graph_config.inputs.prompt_builder.raw_user_query
-    prompt_enrichment_components = get_prompt_enrichment_components(graph_config)
-
-    # get all documents cited in sub-questions
-    structured_subquestion_docs = get_deduplicated_structured_subquestion_documents(
-        state.sub_question_results
-    )
-
-    orig_question_retrieval_documents = state.orig_question_retrieved_documents
-
-    consolidated_context_docs = structured_subquestion_docs.cited_documents
-    counter = 0
-    for original_doc in orig_question_retrieval_documents:
-        if original_doc in structured_subquestion_docs.cited_documents:
-            continue
-
-        if (
-            counter <= AGENT_MIN_ORIG_QUESTION_DOCS
-            or len(consolidated_context_docs) < AGENT_MAX_ANSWER_CONTEXT_DOCS
-        ):
-            consolidated_context_docs.append(original_doc)
-            counter += 1
-
-    # sort docs by their scores - though the scores refer to different questions
-    relevant_docs = dedup_inference_section_list(consolidated_context_docs)
-
-    sub_questions: list[str] = []
-
-    # Create the list of documents to stream out. Start with the
-    # ones that wil be in the context (or, if len == 0, use docs
-    # that were retrieved for the original question)
-    answer_generation_documents = get_answer_generation_documents(
-        relevant_docs=relevant_docs,
-        context_documents=structured_subquestion_docs.context_documents,
-        original_question_docs=orig_question_retrieval_documents,
-        max_docs=AGENT_MAX_STREAMED_DOCS_FOR_INITIAL_ANSWER,
-    )
-
-    # Use the query info from the base document retrieval
-    query_info = get_query_info(state.orig_question_sub_query_retrieval_results)
-
-    assert (
-        graph_config.tooling.search_tool
-    ), "search_tool must be provided for agentic search"
-
-    relevance_list = relevance_from_docs(
-        answer_generation_documents.streaming_documents
-    )
-    for tool_response in yield_search_responses(
-        query=question,
-        get_retrieved_sections=lambda: answer_generation_documents.context_documents,
-        get_final_context_sections=lambda: answer_generation_documents.context_documents,
-        search_query_info=query_info,
-        get_section_relevance=lambda: relevance_list,
-        search_tool=graph_config.tooling.search_tool,
-    ):
-        write_custom_event(
-            "tool_response",
-            ExtendedToolResponse(
-                id=tool_response.id,
-                response=tool_response.response,
-                level=0,
-                level_question_num=0,  # 0, 0 is the base question
-            ),
-            writer,
-        )
-
-    if len(answer_generation_documents.context_documents) == 0:
-        write_custom_event(
-            "initial_agent_answer",
-            AgentAnswerPiece(
-                answer_piece=UNKNOWN_ANSWER,
-                level=0,
-                level_question_num=0,
-                answer_type="agent_level_answer",
-            ),
-            writer,
-        )
-        dispatch_main_answer_stop_info(0, writer)
-
-        answer = UNKNOWN_ANSWER
-        initial_agent_stats = InitialAgentResultStats(
-            sub_questions={},
-            original_question={},
-            agent_effectiveness={},
-        )
-
-    else:
-        sub_question_answer_results = state.sub_question_results
-
-        # Collect the sub-questions and sub-answers and construct an appropriate
-        # prompt string.
-        # Consider replacing by a function.
-        answered_sub_questions: list[str] = []
-        all_sub_questions: list[str] = []  # Separate list for tracking all questions
-
-        for idx, sub_question_answer_result in enumerate(
-            sub_question_answer_results, start=1
-        ):
-            all_sub_questions.append(sub_question_answer_result.question)
-
-            is_valid_answer = (
-                sub_question_answer_result.verified_high_quality
-                and sub_question_answer_result.answer
-                and sub_question_answer_result.answer != UNKNOWN_ANSWER
-            )
-
-            if is_valid_answer:
-                answered_sub_questions.append(
-                    SUB_QUESTION_ANSWER_TEMPLATE.format(
-                        sub_question=sub_question_answer_result.question,
-                        sub_answer=sub_question_answer_result.answer,
-                        sub_question_num=idx,
-                    )
-                )
-
-        sub_question_answer_str = (
-            "\n\n------\n\n".join(answered_sub_questions)
-            if answered_sub_questions
-            else ""
-        )
-
-        # Use the appropriate prompt based on whether there are sub-questions.
-        base_prompt = (
-            INITIAL_ANSWER_PROMPT_W_SUB_QUESTIONS
-            if answered_sub_questions
-            else INITIAL_ANSWER_PROMPT_WO_SUB_QUESTIONS
-        )
-
-        sub_questions = all_sub_questions  # Replace the original assignment
-
-        model = (
-            graph_config.tooling.fast_llm
-            if AGENT_ANSWER_GENERATION_BY_FAST_LLM
-            else graph_config.tooling.primary_llm
-        )
-
-        doc_context = format_docs(answer_generation_documents.context_documents)
-        doc_context = trim_prompt_piece(
-            config=model.config,
-            prompt_piece=doc_context,
-            reserved_str=(
-                base_prompt
-                + sub_question_answer_str
-                + prompt_enrichment_components.persona_prompts.contextualized_prompt
-                + prompt_enrichment_components.history
-                + prompt_enrichment_components.date_str
-            ),
-        )
-
-        msg = [
-            HumanMessage(
-                content=base_prompt.format(
-                    question=question,
-                    answered_sub_questions=remove_document_citations(
-                        sub_question_answer_str
-                    ),
-                    relevant_docs=doc_context,
-                    persona_specification=prompt_enrichment_components.persona_prompts.contextualized_prompt,
-                    history=prompt_enrichment_components.history,
-                    date_prompt=prompt_enrichment_components.date_str,
-                )
-            )
-        ]
-
-        streamed_tokens: list[str] = [""]
-        dispatch_timings: list[float] = []
-
-        agent_error: AgentErrorLog | None = None
-
-        try:
-            streamed_tokens, dispatch_timings = run_with_timeout(
-                AGENT_TIMEOUT_LLM_INITIAL_ANSWER_GENERATION,
-                lambda: stream_llm_answer(
-                    llm=model,
-                    prompt=msg,
-                    event_name="initial_agent_answer",
-                    writer=writer,
-                    agent_answer_level=0,
-                    agent_answer_question_num=0,
-                    agent_answer_type="agent_level_answer",
-                    timeout_override=AGENT_TIMEOUT_CONNECT_LLM_INITIAL_ANSWER_GENERATION,
-                    max_tokens=(
-                        AGENT_MAX_TOKENS_ANSWER_GENERATION
-                        if _should_restrict_tokens(model.config)
-                        else None
-                    ),
-                ),
-            )
-
-        except (LLMTimeoutError, TimeoutError):
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.TIMEOUT,
-                error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-                error_result=_llm_node_error_strings.timeout,
-            )
-            logger.error("LLM Timeout Error - generate initial answer")
-
-        except LLMRateLimitError:
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.RATE_LIMIT,
-                error_message=AGENT_LLM_RATELIMIT_MESSAGE,
-                error_result=_llm_node_error_strings.rate_limit,
-            )
-            logger.error("LLM Rate Limit Error - generate initial answer")
-
-        if agent_error:
-            write_custom_event(
-                "initial_agent_answer",
-                StreamingError(
-                    error=AGENT_LLM_TIMEOUT_MESSAGE,
-                ),
-                writer,
-            )
-            return InitialAnswerUpdate(
-                initial_answer=None,
-                answer_error=AgentErrorLog(
-                    error_message=agent_error.error_message or "An LLM error occurred",
-                    error_type=agent_error.error_type,
-                    error_result=agent_error.error_result,
-                ),
-                initial_agent_stats=None,
-                generated_sub_questions=sub_questions,
-                agent_base_end_time=None,
-                agent_base_metrics=None,
-                log_messages=[
-                    get_langgraph_node_log_string(
-                        graph_component="initial - generate initial answer",
-                        node_name="generate initial answer",
-                        node_start_time=node_start_time,
-                        result=agent_error.error_result or "An LLM error occurred",
-                    )
-                ],
-            )
-
-        logger.debug(
-            f"Average dispatch time for initial answer: {sum(dispatch_timings) / len(dispatch_timings)}"
-        )
-
-        dispatch_main_answer_stop_info(0, writer)
-        response = merge_content(*streamed_tokens)
-        answer = cast(str, response)
-
-        initial_agent_stats = calculate_initial_agent_stats(
-            state.sub_question_results, state.orig_question_retrieval_stats
-        )
-
-        logger.debug(
-            f"\n\nYYYYY--Sub-Questions:\n\n{sub_question_answer_str}\n\nStats:\n\n"
-        )
-
-        if initial_agent_stats:
-            logger.debug(initial_agent_stats.original_question)
-            logger.debug(initial_agent_stats.sub_questions)
-            logger.debug(initial_agent_stats.agent_effectiveness)
-
-    agent_base_end_time = datetime.now()
-
-    if agent_base_end_time and state.agent_start_time:
-        duration_s = (agent_base_end_time - state.agent_start_time).total_seconds()
-    else:
-        duration_s = None
-
-    agent_base_metrics = AgentBaseMetrics(
-        num_verified_documents_total=len(relevant_docs),
-        num_verified_documents_core=state.orig_question_retrieval_stats.verified_count,
-        verified_avg_score_core=state.orig_question_retrieval_stats.verified_avg_scores,
-        num_verified_documents_base=initial_agent_stats.sub_questions.get(
-            "num_verified_documents"
-        ),
-        verified_avg_score_base=initial_agent_stats.sub_questions.get(
-            "verified_avg_score"
-        ),
-        base_doc_boost_factor=initial_agent_stats.agent_effectiveness.get(
-            "utilized_chunk_ratio"
-        ),
-        support_boost_factor=initial_agent_stats.agent_effectiveness.get(
-            "support_ratio"
-        ),
-        duration_s=duration_s,
-    )
-
-    return InitialAnswerUpdate(
-        initial_answer=answer,
-        initial_agent_stats=initial_agent_stats,
-        generated_sub_questions=sub_questions,
-        agent_base_end_time=agent_base_end_time,
-        agent_base_metrics=agent_base_metrics,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial - generate initial answer",
-                node_name="generate initial answer",
-                node_start_time=node_start_time,
-                result="",
-            )
-        ],
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_initial_answer/nodes/validate_initial_answer.py

@@ -1,42 +0,0 @@
-from datetime import datetime
-
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalState,
-)
-from onyx.agents.agent_search.deep_search.main.operations import logger
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialAnswerQualityUpdate,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.utils.timing import log_function_time
-
-
-@log_function_time(print_only=True)
-def validate_initial_answer(
-    state: SubQuestionRetrievalState,
-) -> InitialAnswerQualityUpdate:
-    """
-    Check whether the initial answer sufficiently addresses the original user question.
-    """
-
-    node_start_time = datetime.now()
-
-    logger.debug(
-        f"--------{node_start_time}--------Checking for base answer validity - for not set True/False manually"
-    )
-
-    verdict = True  # not actually required as already streamed out. Refinement will do similar
-
-    return InitialAnswerQualityUpdate(
-        initial_answer_quality_eval=verdict,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial - generate initial answer",
-                node_name="validate initial answer",
-                node_start_time=node_start_time,
-                result="",
-            )
-        ],
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_initial_answer/states.py

@@ -1,51 +0,0 @@
-from operator import add
-from typing import Annotated
-from typing import TypedDict
-
-from onyx.agents.agent_search.core_state import CoreState
-from onyx.agents.agent_search.deep_search.main.states import (
-    ExploratorySearchUpdate,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialAnswerQualityUpdate,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialAnswerUpdate,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialQuestionDecompositionUpdate,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    OrigQuestionRetrievalUpdate,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    SubQuestionResultsUpdate,
-)
-from onyx.agents.agent_search.deep_search.shared.expanded_retrieval.models import (
-    QuestionRetrievalResult,
-)
-from onyx.context.search.models import InferenceSection
-
-
-### States ###
-class SubQuestionRetrievalInput(CoreState):
-    exploratory_search_results: list[InferenceSection]
-
-
-## Graph State
-class SubQuestionRetrievalState(
-    # This includes the core state
-    SubQuestionRetrievalInput,
-    InitialQuestionDecompositionUpdate,
-    InitialAnswerUpdate,
-    SubQuestionResultsUpdate,
-    OrigQuestionRetrievalUpdate,
-    InitialAnswerQualityUpdate,
-    ExploratorySearchUpdate,
-):
-    base_raw_search_result: Annotated[list[QuestionRetrievalResult], add]
-
-
-## Graph Output State
-class SubQuestionRetrievalOutput(TypedDict):
-    log_messages: list[str]

backend/onyx/agents/agent_search/deep_search/initial/generate_sub_answers/edges.py

@@ -1,48 +0,0 @@
-from collections.abc import Hashable
-from datetime import datetime
-
-from langgraph.types import Send
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionOutput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnsweringInput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalState,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import make_question_id
-
-
-def parallelize_initial_sub_question_answering(
-    state: SubQuestionRetrievalState,
-) -> list[Send | Hashable]:
-    """
-    LangGraph edge to parallelize the initial sub-question answering.
-    """
-    edge_start_time = datetime.now()
-    if len(state.initial_sub_questions) > 0:
-        return [
-            Send(
-                "answer_sub_question_subgraphs",
-                SubQuestionAnsweringInput(
-                    question=question,
-                    question_id=make_question_id(0, question_num + 1),
-                    log_messages=[
-                        f"{edge_start_time} -- Main Edge - Parallelize Initial Sub-question Answering"
-                    ],
-                ),
-            )
-            for question_num, question in enumerate(state.initial_sub_questions)
-        ]
-
-    else:
-        return [
-            Send(
-                "ingest_answers",
-                AnswerQuestionOutput(
-                    answer_results=[],
-                ),
-            )
-        ]