remove endpoint

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

@@ -3,61 +3,61 @@ name: Build and Push Backend Image on Tag
 on:
   push:
     tags:
-      - "*"
+      - '*'
 
 env:
-  REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'danswer/danswer-backend-cloud' || 'danswer/danswer-backend' }}
+  REGISTRY_IMAGE: danswer/danswer-backend
   LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
-
+  
 jobs:
   build-and-push:
-    # TODO: investigate a matrix build like the web container
+    # TODO: investigate a matrix build like the web container 
     # See https://runs-on.com/runners/linux/
-    runs-on: [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}"]
+    runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]
 
     steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
+    - name: Checkout code
+      uses: actions/checkout@v4
 
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+    - 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 }}
+    - name: Login to Docker Hub
+      uses: docker/login-action@v3
+      with:
+        username: ${{ secrets.DOCKER_USERNAME }}
+        password: ${{ secrets.DOCKER_TOKEN }}
 
-      - name: Install build-essential
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y build-essential
+    - name: Install build-essential
+      run: |
+        sudo apt-get update
+        sudo apt-get install -y build-essential
+          
+    - name: Backend Image Docker Build and Push
+      uses: docker/build-push-action@v5
+      with:
+        context: ./backend
+        file: ./backend/Dockerfile
+        platforms: linux/amd64,linux/arm64
+        push: true
+        tags: |
+          ${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
+          ${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
+        build-args: |
+          DANSWER_VERSION=${{ github.ref_name }}
 
-      - name: Backend Image Docker Build and Push
-        uses: docker/build-push-action@v5
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile
-          platforms: linux/amd64,linux/arm64
-          push: true
-          tags: |
-            ${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-            ${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
-          build-args: |
-            DANSWER_VERSION=${{ github.ref_name }}
-
-      # trivy has their own rate limiting issues causing this action to flake
-      # we worked around it by hardcoding to different db repos in env
-      # can re-enable when they figure it out
-      # 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"
-        with:
-          # To run locally: trivy image --severity HIGH,CRITICAL danswer/danswer-backend
-          image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-          severity: "CRITICAL,HIGH"
-          trivyignores: ./backend/.trivyignore
+    # trivy has their own rate limiting issues causing this action to flake
+    # we worked around it by hardcoding to different db repos in env
+    # can re-enable when they figure it out
+    # 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'
+      with:
+        # To run locally: trivy image --severity HIGH,CRITICAL danswer/danswer-backend
+        image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
+        severity: 'CRITICAL,HIGH'
+        trivyignores: ./backend/.trivyignore

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

@@ -4,12 +4,12 @@ name: Build and Push Cloud Web Image on Tag
 on:
   push:
     tags:
-      - "*"
+      - '*'
 
 env:
-  REGISTRY_IMAGE: danswer/danswer-web-server-cloud
+  REGISTRY_IMAGE: danswer/danswer-cloud-web-server
   LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
-
+  
 jobs:
   build:
     runs-on:
@@ -28,11 +28,11 @@ jobs:
       - name: Prepare
         run: |
           platform=${{ matrix.platform }}
-          echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV
-
+          echo "PLATFORM_PAIR=${platform//\//-}" >> $GITHUB_ENV          
+      
       - name: Checkout
         uses: actions/checkout@v4
-
+      
       - name: Docker meta
         id: meta
         uses: docker/metadata-action@v5
@@ -41,16 +41,16 @@ jobs:
           tags: |
             type=raw,value=${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
             type=raw,value=${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
-
+      
       - 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: ${{ secrets.DOCKER_TOKEN }}
-
+    
       - name: Build and push by digest
         id: build
         uses: docker/build-push-action@v5
@@ -65,18 +65,17 @@ jobs:
             NEXT_PUBLIC_POSTHOG_KEY=${{ secrets.POSTHOG_KEY }}
             NEXT_PUBLIC_POSTHOG_HOST=${{ secrets.POSTHOG_HOST }}
             NEXT_PUBLIC_SENTRY_DSN=${{ secrets.SENTRY_DSN }}
-            NEXT_PUBLIC_GTM_ENABLED=true
-          # needed due to weird interactions with the builds for different platforms
+          # needed due to weird interactions with the builds for different platforms  
           no-cache: true
           labels: ${{ steps.meta.outputs.labels }}
           outputs: type=image,name=${{ env.REGISTRY_IMAGE }},push-by-digest=true,name-canonical=true,push=true
-
+      
       - name: Export digest
         run: |
           mkdir -p /tmp/digests
           digest="${{ steps.build.outputs.digest }}"
-          touch "/tmp/digests/${digest#sha256:}"
-
+          touch "/tmp/digests/${digest#sha256:}"          
+      
       - name: Upload digest
         uses: actions/upload-artifact@v4
         with:
@@ -96,42 +95,42 @@ jobs:
           path: /tmp/digests
           pattern: digests-*
           merge-multiple: true
-
+      
       - name: Set up Docker Buildx
         uses: docker/setup-buildx-action@v3
-
+      
       - name: Docker meta
         id: meta
         uses: docker/metadata-action@v5
         with:
           images: ${{ env.REGISTRY_IMAGE }}
-
+      
       - name: Login to Docker Hub
         uses: docker/login-action@v3
         with:
           username: ${{ secrets.DOCKER_USERNAME }}
           password: ${{ secrets.DOCKER_TOKEN }}
-
+      
       - name: Create manifest list and push
         working-directory: /tmp/digests
         run: |
           docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
-            $(printf '${{ env.REGISTRY_IMAGE }}@sha256:%s ' *)
-
+            $(printf '${{ env.REGISTRY_IMAGE }}@sha256:%s ' *)          
+      
       - name: Inspect image
         run: |
           docker buildx imagetools inspect ${{ env.REGISTRY_IMAGE }}:${{ steps.meta.outputs.version }}
 
-      # trivy has their own rate limiting issues causing this action to flake
-      # we worked around it by hardcoding to different db repos in env
-      # can re-enable when they figure it out
-      # https://github.com/aquasecurity/trivy/discussions/7538
-      # https://github.com/aquasecurity/trivy-action/issues/389
+    # trivy has their own rate limiting issues causing this action to flake
+    # we worked around it by hardcoding to different db repos in env
+    # can re-enable when they figure it out
+    # 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_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
+          TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
         with:
           image-ref: docker.io/${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-          severity: "CRITICAL,HIGH"
+          severity: 'CRITICAL,HIGH'

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

@@ -3,53 +3,53 @@ name: Build and Push Model Server Image on Tag
 on:
   push:
     tags:
-      - "*"
+      - '*'
 
 env:
-  REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'danswer/danswer-model-server-cloud' || 'danswer/danswer-model-server' }}
+  REGISTRY_IMAGE: danswer/danswer-model-server
   LATEST_TAG: ${{ contains(github.ref_name, 'latest') }}
-
+  
 jobs:
   build-and-push:
     # See https://runs-on.com/runners/linux/
-    runs-on: [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}"]
+    runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]
 
     steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
+    - name: Checkout code
+      uses: actions/checkout@v4
 
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
+    - 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 }}
+    - name: Login to Docker Hub
+      uses: docker/login-action@v3
+      with:
+        username: ${{ secrets.DOCKER_USERNAME }}
+        password: ${{ secrets.DOCKER_TOKEN }}
 
-      - name: Model Server Image Docker Build and Push
-        uses: docker/build-push-action@v5
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile.model_server
-          platforms: linux/amd64,linux/arm64
-          push: true
-          tags: |
-            ${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
-            ${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
-          build-args: |
-            DANSWER_VERSION=${{ github.ref_name }}
+    - name: Model Server Image Docker Build and Push
+      uses: docker/build-push-action@v5
+      with:
+        context: ./backend
+        file: ./backend/Dockerfile.model_server
+        platforms: linux/amd64,linux/arm64
+        push: true
+        tags: |
+          ${{ env.REGISTRY_IMAGE }}:${{ github.ref_name }}
+          ${{ env.LATEST_TAG == 'true' && format('{0}:latest', env.REGISTRY_IMAGE) || '' }}
+        build-args: |
+          DANSWER_VERSION=${{ github.ref_name }}
 
-      # trivy has their own rate limiting issues causing this action to flake
-      # we worked around it by hardcoding to different db repos in env
-      # can re-enable when they figure it out
-      # 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"
-        with:
-          image-ref: docker.io/danswer/danswer-model-server:${{ github.ref_name }}
-          severity: "CRITICAL,HIGH"
+    # trivy has their own rate limiting issues causing this action to flake
+    # we worked around it by hardcoding to different db repos in env
+    # can re-enable when they figure it out
+    # https://github.com/aquasecurity/trivy/discussions/7538
+    # https://github.com/aquasecurity/trivy-action/issues/389
+    - name: Run Trivy vulnerability scanner
+      uses: aquasecurity/trivy-action@master
+      env:
+        TRIVY_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-db:2'
+        TRIVY_JAVA_DB_REPOSITORY: 'public.ecr.aws/aquasecurity/trivy-java-db:1'
+      with:
+        image-ref: docker.io/danswer/danswer-model-server:${{ github.ref_name }}
+        severity: 'CRITICAL,HIGH'

.github/workflows/nightly-scan-licenses.yml

@@ -1,76 +0,0 @@
-# Scan for problematic software licenses
-
-# trivy has their own rate limiting issues causing this action to flake
-# we worked around it by hardcoding to different db repos in env
-# can re-enable when they figure it out
-# https://github.com/aquasecurity/trivy/discussions/7538
-# https://github.com/aquasecurity/trivy-action/issues/389
-
-name: 'Nightly - Scan licenses'
-on:
-#   schedule:
-#     - cron: '0 14 * * *'  # Runs every day at 6 AM PST / 7 AM PDT / 2 PM UTC
-  workflow_dispatch:  # Allows manual triggering
-
-permissions:
-  actions: read
-  contents: read
-  security-events: write
-  
-jobs:
-  scan-licenses:
-    # See https://runs-on.com/runners/linux/
-    runs-on: [runs-on,runner=2cpu-linux-x64,"run-id=${{ github.run_id }}"]
-
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.11'
-          cache: 'pip'
-          cache-dependency-path: |
-            backend/requirements/default.txt
-            backend/requirements/dev.txt
-            backend/requirements/model_server.txt
-      
-      - name: Get explicit and transitive 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/model_server.txt
-          pip freeze > requirements-all.txt
-                    
-      - name: Check python
-        id: license_check_report
-        uses: pilosus/action-pip-license-checker@v2
-        with:
-          requirements: 'requirements-all.txt'
-          fail: 'Copyleft'
-          exclude: '(?i)^(pylint|aio[-_]*).*'
-          
-      - name: Print report
-        if: ${{ always() }}
-        run: echo "${{ steps.license_check_report.outputs.report }}"
-      
-      - name: Install npm dependencies
-        working-directory: ./web
-        run: npm ci
-        
-      - name: Run Trivy vulnerability scanner in repo mode
-        uses: aquasecurity/trivy-action@0.28.0
-        with:
-          scan-type: fs
-          scanners: license
-          format: table
-#           format: sarif
-#           output: trivy-results.sarif
-          severity: HIGH,CRITICAL
-
-#       - name: Upload Trivy scan results to GitHub Security tab
-#         uses: github/codeql-action/upload-sarif@v3
-#         with:
-#           sarif_file: trivy-results.sarif

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

@@ -13,10 +13,7 @@ on:
 env:
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
   SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
-  CONFLUENCE_TEST_SPACE_URL: ${{ secrets.CONFLUENCE_TEST_SPACE_URL }}
-  CONFLUENCE_USER_NAME: ${{ secrets.CONFLUENCE_USER_NAME }}
-  CONFLUENCE_ACCESS_TOKEN: ${{ secrets.CONFLUENCE_ACCESS_TOKEN }}
-  
+
 jobs:
   integration-tests:
     # See https://runs-on.com/runners/linux/
@@ -198,13 +195,9 @@ jobs:
             -e API_SERVER_HOST=api_server \
             -e OPENAI_API_KEY=${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 TEST_WEB_HOSTNAME=test-runner \
             danswer/danswer-integration:test \
-            /app/tests/integration/tests \
-            /app/tests/integration/connector_job_tests
+            /app/tests/integration/tests
         continue-on-error: true
         id: run_tests
 
@@ -217,18 +210,17 @@ jobs:
             echo "All integration tests passed successfully."
           fi
 
-      # save before stopping the containers so the logs can be captured
+      - name: Stop Docker containers
+        run: |
+          cd deployment/docker_compose
+          docker compose -f docker-compose.dev.yml -p danswer-stack down -v
+
       - name: Save Docker logs
         if: success() || failure()
         run: |
           cd deployment/docker_compose
           docker compose -f docker-compose.dev.yml -p danswer-stack logs > docker-compose.log
           mv docker-compose.log ${{ github.workspace }}/docker-compose.log
-
-      - name: Stop Docker containers
-        run: |
-          cd deployment/docker_compose
-          docker compose -f docker-compose.dev.yml -p danswer-stack down -v
       
       - name: Upload logs
         if: success() || failure()

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

@@ -1,225 +0,0 @@
-name: Run Chromatic Tests
-concurrency:
-  group: Run-Chromatic-Tests-${{ github.workflow }}-${{ github.head_ref || github.event.workflow_run.head_branch || github.run_id }}
-  cancel-in-progress: true
-
-on: push
-
-env:
-  OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-  SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
-
-jobs:
-  playwright-tests:
-    name: Playwright Tests
-
-    # See https://runs-on.com/runners/linux/
-    runs-on: [runs-on,runner=8cpu-linux-x64,ram=16,"run-id=${{ github.run_id }}"]
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        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
-        
-      - name: Setup node
-        uses: actions/setup-node@v4
-        with:
-          node-version: 22
-
-      - name: Install node dependencies
-        working-directory: ./web
-        run: npm ci
-
-      - name: Install playwright browsers
-        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: ${{ secrets.DOCKER_TOKEN }}
-
-      # tag every docker image with "test" so that we can spin up the correct set
-      # of images during testing
-      
-      # we use the runs-on cache for docker builds
-      # in conjunction with runs-on runners, it has better speed and unlimited caching
-      # https://runs-on.com/caching/s3-cache-for-github-actions/
-      # https://runs-on.com/caching/docker/
-      # https://github.com/moby/buildkit#s3-cache-experimental
-      
-      # images are built and run locally for testing purposes. Not pushed.
-
-      - name: Build Web Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./web
-          file: ./web/Dockerfile
-          platforms: linux/amd64
-          tags: danswer/danswer-web-server:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ 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=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build Backend Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile
-          platforms: linux/amd64
-          tags: danswer/danswer-backend:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ 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=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Build Model Server Docker image
-        uses: ./.github/actions/custom-build-and-push
-        with:
-          context: ./backend
-          file: ./backend/Dockerfile.model_server
-          platforms: linux/amd64
-          tags: danswer/danswer-model-server:test
-          push: false
-          load: true
-          cache-from: type=s3,prefix=cache/${{ 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=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
-
-      - name: Start Docker containers
-        run: |
-          cd deployment/docker_compose
-          ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
-          AUTH_TYPE=basic \
-          REQUIRE_EMAIL_VERIFICATION=false \
-          DISABLE_TELEMETRY=true \
-          IMAGE_TAG=test \
-          docker compose -f docker-compose.dev.yml -p danswer-stack up -d
-        id: start_docker
-
-      - name: Wait for service to be ready
-        run: |
-          echo "Starting wait-for-service script..."
-          
-          docker logs -f danswer-stack-api_server-1 &
-
-          start_time=$(date +%s)
-          timeout=300  # 5 minutes in seconds
-          
-          while true; do
-            current_time=$(date +%s)
-            elapsed_time=$((current_time - start_time))
-            
-            if [ $elapsed_time -ge $timeout ]; then
-              echo "Timeout reached. Service did not become ready in 5 minutes."
-              exit 1
-            fi
-            
-            # Use curl with error handling to ignore specific exit code 56
-            response=$(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, possibly exit code 56. Continuing to retry..."
-            else
-              echo "Service not ready yet (HTTP status $response). Retrying in 5 seconds..."
-            fi
-            
-            sleep 5
-          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
-
-      - uses: actions/upload-artifact@v4
-        if: always()
-        with:
-          # Chromatic automatically defaults to the test-results directory.
-          # Replace with the path to your custom directory and adjust the CHROMATIC_ARCHIVE_LOCATION environment variable accordingly.
-          name: test-results
-          path: ./web/test-results
-          retention-days: 30
-                    
-      # save before stopping the containers so the logs can be captured
-      - name: Save Docker logs
-        if: success() || failure()
-        run: |
-          cd deployment/docker_compose
-          docker compose -f docker-compose.dev.yml -p danswer-stack logs > docker-compose.log
-          mv docker-compose.log ${{ github.workspace }}/docker-compose.log
-      
-      - name: Upload logs
-        if: success() || failure()
-        uses: actions/upload-artifact@v4
-        with:
-          name: docker-logs
-          path: ${{ github.workspace }}/docker-compose.log
-
-      - name: Stop Docker containers
-        run: |
-          cd deployment/docker_compose
-          docker compose -f docker-compose.dev.yml -p danswer-stack down -v
-
-  chromatic-tests:
-    name: Chromatic Tests
-    
-    needs: playwright-tests
-    runs-on: [runs-on,runner=8cpu-linux-x64,ram=16,"run-id=${{ github.run_id }}"]
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          
-      - name: Setup node
-        uses: actions/setup-node@v4
-        with:
-          node-version: 22
-          
-      - name: Install node dependencies
-        working-directory: ./web
-        run: npm ci
-        
-      - name: Download Playwright test results
-        uses: actions/download-artifact@v4
-        with:
-          name: test-results
-          path: ./web/test-results
-          
-      - name: Run Chromatic
-        uses: chromaui/action@latest
-        with:
-          playwright: true
-          projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
-          workingDir: ./web
-        env: 
-          CHROMATIC_ARCHIVE_LOCATION: ./test-results

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

@@ -1,72 +0,0 @@
-name: Helm - Lint and Test Charts
-
-on:
-  merge_group:
-  pull_request:
-    branches: [ main ]
-  workflow_dispatch:  # Allows manual triggering
-  
-jobs:
-  helm-chart-check:
-    # See https://runs-on.com/runners/linux/
-    runs-on: [runs-on,runner=8cpu-linux-x64,hdd=256,"run-id=${{ github.run_id }}"]
-
-    # fetch-depth 0 is required for helm/chart-testing-action
-    steps:
-    - name: Checkout code
-      uses: actions/checkout@v4
-      with:
-        fetch-depth: 0
-        
-    - name: Set up Helm
-      uses: azure/setup-helm@v4.2.0
-      with:
-        version: v3.14.4
-      
-    - name: Set up chart-testing
-      uses: helm/chart-testing-action@v2.6.1
-
-    # even though we specify chart-dirs in ct.yaml, it isn't used by ct for the list-changed command...
-    - name: Run chart-testing (list-changed)
-      id: list-changed
-      run: |
-        echo "default_branch: ${{ github.event.repository.default_branch }}"
-        changed=$(ct list-changed --remote origin --target-branch ${{ github.event.repository.default_branch }} --chart-dirs deployment/helm/charts)
-        echo "list-changed output: $changed"
-        if [[ -n "$changed" ]]; then
-          echo "changed=true" >> "$GITHUB_OUTPUT"
-        fi
-
-#     rkuo: I don't think we need python?
-#     - name: Set up Python
-#       uses: actions/setup-python@v5
-#       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
-
-    # lint all charts if any changes were detected
-    - name: Run chart-testing (lint)
-      if: steps.list-changed.outputs.changed == 'true'
-      run: ct lint --config ct.yaml --all
-      # the following would lint only changed charts, but linting isn't expensive
-      # run: ct lint --config ct.yaml --target-branch ${{ github.event.repository.default_branch }}
-
-    - name: Create kind cluster
-      if: steps.list-changed.outputs.changed == 'true'
-      uses: helm/kind-action@v1.10.0
-
-    - name: Run chart-testing (install)
-      if: steps.list-changed.outputs.changed == 'true'
-      run: ct install --all --helm-extra-set-args="--set=nginx.enabled=false" --debug --config ct.yaml
-      # 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-helm-chart-testing.yml.disabled.txt

@@ -0,0 +1,68 @@
+# This workflow is intentionally disabled while we're still working on it
+# It's close to ready, but a race condition needs to be fixed with
+# API server and Vespa startup, and it needs to have a way to build/test against
+# local containers
+
+name: Helm - Lint and Test Charts
+
+on:
+  merge_group:
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  lint-test:
+    # See https://runs-on.com/runners/linux/
+    runs-on: [runs-on,runner=8cpu-linux-x64,hdd=256,"run-id=${{ github.run_id }}"]
+
+    # fetch-depth 0 is required for helm/chart-testing-action
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v3
+      with:
+        fetch-depth: 0
+        
+    - name: Set up Helm
+      uses: azure/setup-helm@v4.2.0
+      with:
+        version: v3.14.4
+      
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.11'
+        cache: 'pip'
+        cache-dependency-path: |
+          backend/requirements/default.txt
+          backend/requirements/dev.txt
+          backend/requirements/model_server.txt
+    - run: |
+        python -m pip install --upgrade pip
+        pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
+        pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
+        pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
+
+    - name: Set up chart-testing
+      uses: helm/chart-testing-action@v2.6.1
+
+    - name: Run chart-testing (list-changed)
+      id: list-changed
+      run: |
+        changed=$(ct list-changed --target-branch ${{ github.event.repository.default_branch }})
+        if [[ -n "$changed" ]]; then
+          echo "changed=true" >> "$GITHUB_OUTPUT"
+        fi
+
+    - name: Run chart-testing (lint)
+#       if: steps.list-changed.outputs.changed == 'true'
+      run: ct lint --all --config ct.yaml --target-branch ${{ github.event.repository.default_branch }}
+
+    - name: Create kind cluster
+#       if: steps.list-changed.outputs.changed == 'true'
+      uses: helm/kind-action@v1.10.0
+
+    - name: Run chart-testing (install)
+#       if: steps.list-changed.outputs.changed == 'true'
+      run: ct install --all --config ct.yaml
+#       run: ct install --target-branch ${{ github.event.repository.default_branch }}
+      

.github/workflows/pr-python-connector-tests.yml

@@ -18,14 +18,6 @@ env:
   # Jira
   JIRA_USER_EMAIL: ${{ secrets.JIRA_USER_EMAIL }}
   JIRA_API_TOKEN: ${{ secrets.JIRA_API_TOKEN }}
-  # Google
-  GOOGLE_DRIVE_SERVICE_ACCOUNT_JSON_STR: ${{ secrets.GOOGLE_DRIVE_SERVICE_ACCOUNT_JSON_STR }}
-  GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR_TEST_USER_1: ${{ secrets.GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR_TEST_USER_1 }}
-  GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR: ${{ secrets.GOOGLE_DRIVE_OAUTH_CREDENTIALS_JSON_STR }}
-  GOOGLE_GMAIL_SERVICE_ACCOUNT_JSON_STR: ${{ secrets.GOOGLE_GMAIL_SERVICE_ACCOUNT_JSON_STR }}
-  GOOGLE_GMAIL_OAUTH_CREDENTIALS_JSON_STR: ${{ secrets.GOOGLE_GMAIL_OAUTH_CREDENTIALS_JSON_STR }}
-  # Slab
-  SLAB_BOT_TOKEN: ${{ secrets.SLAB_BOT_TOKEN }}
 
 jobs:
   connectors-check:

.github/workflows/pr-python-model-tests.yml

@@ -15,7 +15,7 @@ env:
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
 
 jobs:
-  model-check:
+  connectors-check:
     # See https://runs-on.com/runners/linux/
     runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]
 

.gitignore

@@ -7,4 +7,3 @@
 .vscode/
 *.sw?
 /backend/tests/regression/answer_quality/search_test_config.yaml
-/web/test-results/

.vscode/launch.template.jsonc

@@ -203,7 +203,7 @@
                 "--loglevel=INFO",
                 "--hostname=light@%n",
                 "-Q",
-                "vespa_metadata_sync,connector_deletion,doc_permissions_upsert",
+                "vespa_metadata_sync,connector_deletion",
             ],
             "presentation": {
 				 "group": "2",
@@ -232,7 +232,7 @@
                 "--loglevel=INFO",
                 "--hostname=heavy@%n",
                 "-Q",
-                "connector_pruning,connector_doc_permissions_sync,connector_external_group_sync",
+                "connector_pruning",
             ],
             "presentation": {
 				 "group": "2",

CONTRIBUTING.md

@@ -32,7 +32,7 @@ To contribute to this project, please follow the
 When opening a pull request, mention related issues and feel free to tag relevant maintainers.
 
 Before creating a pull request please make sure that the new changes conform to the formatting and linting requirements.
-See the [Formatting and Linting](#formatting-and-linting) section for how to run these checks locally.
+See the [Formatting and Linting](#-formatting-and-linting) section for how to run these checks locally.
 
 
 ### Getting Help 🙋

README.md

@@ -1,5 +1,4 @@
 <!-- DANSWER_METADATA={"link": "https://github.com/danswer-ai/danswer/blob/main/README.md"} -->
-<a name="readme-top"></a>
 
 <h2 align="center">
 <a href="https://www.danswer.ai/"> <img width="50%" src="https://github.com/danswer-owners/danswer/blob/1fabd9372d66cd54238847197c33f091a724803b/DanswerWithName.png?raw=true)" /></a>
@@ -12,7 +11,7 @@
 <a href="https://docs.danswer.dev/" target="_blank">
     <img src="https://img.shields.io/badge/docs-view-blue" alt="Documentation">
 </a>
-<a href="https://join.slack.com/t/danswer/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA" target="_blank">
+<a href="https://join.slack.com/t/danswer/shared_invite/zt-2lcmqw703-071hBuZBfNEOGUsLa5PXvQ" target="_blank">
     <img src="https://img.shields.io/badge/slack-join-blue.svg?logo=slack" alt="Slack">
 </a>
 <a href="https://discord.gg/TDJ59cGV2X" target="_blank">
@@ -128,19 +127,3 @@ To try the Danswer Enterprise Edition:
 
 ## 💡 Contributing
 Looking to contribute? Please check out the [Contribution Guide](CONTRIBUTING.md) for more details.
-
-## ⭐Star History
-
-[![Star History Chart](https://api.star-history.com/svg?repos=danswer-ai/danswer&type=Date)](https://star-history.com/#danswer-ai/danswer&Date)
-
-## ✨Contributors
-
-<a href="https://github.com/danswer-ai/danswer/graphs/contributors">
-  <img alt="contributors" src="https://contrib.rocks/image?repo=danswer-ai/danswer"/>
-</a>
-
-<p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
-    <a href="#readme-top" style="text-decoration: none; color: #007bff; font-weight: bold;">
-        ↑ Back to Top ↑
-    </a>
-</p>

backend/Dockerfile

@@ -12,6 +12,7 @@ ARG DANSWER_VERSION=0.8-dev
 ENV DANSWER_VERSION=${DANSWER_VERSION} \
     DANSWER_RUNNING_IN_DOCKER="true"
 
+ARG CA_CERT_CONTENT=""
 
 RUN echo "DANSWER_VERSION: ${DANSWER_VERSION}"
 # Install system dependencies
@@ -38,6 +39,15 @@ RUN apt-get update && \
     apt-get clean
 
 
+# Conditionally write the CA certificate and update certificates
+RUN if [ -n "$CA_CERT_CONTENT" ]; then \
+    echo "Adding custom CA certificate"; \
+    echo "$CA_CERT_CONTENT" > /usr/local/share/ca-certificates/my-ca.crt && \
+    chmod 644 /usr/local/share/ca-certificates/my-ca.crt && \
+    update-ca-certificates; \
+else \
+    echo "No custom CA certificate provided"; \
+fi
 
 # Install Python dependencies
 # Remove py which is pulled in by retry, py is not needed and is a CVE
@@ -73,11 +83,11 @@ RUN apt-get update && \
     rm -rf /var/lib/apt/lists/* && \
     rm -f /usr/local/lib/python3.11/site-packages/tornado/test/test.key
 
-
 # Pre-downloading models for setups with limited egress
 RUN python -c "from tokenizers import Tokenizer; \
 Tokenizer.from_pretrained('nomic-ai/nomic-embed-text-v1')"
 
+
 # Pre-downloading NLTK for setups with limited egress
 RUN python -c "import nltk; \
 nltk.download('stopwords', quiet=True); \

backend/alembic/env.py

@@ -1,5 +1,5 @@
 from sqlalchemy.engine.base import Connection
-from typing import Literal
+from typing import Any
 import asyncio
 from logging.config import fileConfig
 import logging
@@ -8,7 +8,6 @@ from alembic import context
 from sqlalchemy import pool
 from sqlalchemy.ext.asyncio import create_async_engine
 from sqlalchemy.sql import text
-from sqlalchemy.sql.schema import SchemaItem
 
 from shared_configs.configs import MULTI_TENANT
 from danswer.db.engine import build_connection_string
@@ -36,18 +35,7 @@ logger = logging.getLogger(__name__)
 
 
 def include_object(
-    object: SchemaItem,
-    name: str | None,
-    type_: Literal[
-        "schema",
-        "table",
-        "column",
-        "index",
-        "unique_constraint",
-        "foreign_key_constraint",
-    ],
-    reflected: bool,
-    compare_to: SchemaItem | None,
+    object: Any, name: str, type_: str, reflected: bool, compare_to: Any
 ) -> bool:
     """
     Determines whether a database object should be included in migrations.

backend/alembic/versions/177de57c21c9_display_custom_llm_models.py

@@ -1,59 +0,0 @@
-"""display custom llm models
-
-Revision ID: 177de57c21c9
-Revises: 4ee1287bd26a
-Create Date: 2024-11-21 11:49:04.488677
-
-"""
-from alembic import op
-import sqlalchemy as sa
-from sqlalchemy.dialects import postgresql
-from sqlalchemy import and_
-
-revision = "177de57c21c9"
-down_revision = "4ee1287bd26a"
-branch_labels = None
-depends_on = None
-depends_on = None
-
-
-def upgrade() -> None:
-    conn = op.get_bind()
-    llm_provider = sa.table(
-        "llm_provider",
-        sa.column("id", sa.Integer),
-        sa.column("provider", sa.String),
-        sa.column("model_names", postgresql.ARRAY(sa.String)),
-        sa.column("display_model_names", postgresql.ARRAY(sa.String)),
-    )
-
-    excluded_providers = ["openai", "bedrock", "anthropic", "azure"]
-
-    providers_to_update = sa.select(
-        llm_provider.c.id,
-        llm_provider.c.model_names,
-        llm_provider.c.display_model_names,
-    ).where(
-        and_(
-            ~llm_provider.c.provider.in_(excluded_providers),
-            llm_provider.c.model_names.isnot(None),
-        )
-    )
-
-    results = conn.execute(providers_to_update).fetchall()
-
-    for provider_id, model_names, display_model_names in results:
-        if display_model_names is None:
-            display_model_names = []
-
-        combined_model_names = list(set(display_model_names + model_names))
-        update_stmt = (
-            llm_provider.update()
-            .where(llm_provider.c.id == provider_id)
-            .values(display_model_names=combined_model_names)
-        )
-        conn.execute(update_stmt)
-
-
-def downgrade() -> None:
-    pass

backend/alembic/versions/26b931506ecb_default_chosen_assistants_to_none.py

@@ -1,68 +0,0 @@
-"""default chosen assistants to none
-
-Revision ID: 26b931506ecb
-Revises: 2daa494a0851
-Create Date: 2024-11-12 13:23:29.858995
-
-"""
-from alembic import op
-import sqlalchemy as sa
-from sqlalchemy.dialects import postgresql
-
-# revision identifiers, used by Alembic.
-revision = "26b931506ecb"
-down_revision = "2daa494a0851"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "user", sa.Column("chosen_assistants_new", postgresql.JSONB(), nullable=True)
-    )
-
-    op.execute(
-        """
-    UPDATE "user"
-    SET chosen_assistants_new =
-        CASE
-            WHEN chosen_assistants = '[-2, -1, 0]' THEN NULL
-            ELSE chosen_assistants
-        END
-    """
-    )
-
-    op.drop_column("user", "chosen_assistants")
-
-    op.alter_column(
-        "user", "chosen_assistants_new", new_column_name="chosen_assistants"
-    )
-
-
-def downgrade() -> None:
-    op.add_column(
-        "user",
-        sa.Column(
-            "chosen_assistants_old",
-            postgresql.JSONB(),
-            nullable=False,
-            server_default="[-2, -1, 0]",
-        ),
-    )
-
-    op.execute(
-        """
-    UPDATE "user"
-    SET chosen_assistants_old =
-        CASE
-            WHEN chosen_assistants IS NULL THEN '[-2, -1, 0]'::jsonb
-            ELSE chosen_assistants
-        END
-    """
-    )
-
-    op.drop_column("user", "chosen_assistants")
-
-    op.alter_column(
-        "user", "chosen_assistants_old", new_column_name="chosen_assistants"
-    )

backend/alembic/versions/2daa494a0851_add_group_sync_time.py

@@ -1,30 +0,0 @@
-"""add-group-sync-time
-
-Revision ID: 2daa494a0851
-Revises: c0fd6e4da83a
-Create Date: 2024-11-11 10:57:22.991157
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-# revision identifiers, used by Alembic.
-revision = "2daa494a0851"
-down_revision = "c0fd6e4da83a"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "connector_credential_pair",
-        sa.Column(
-            "last_time_external_group_sync",
-            sa.DateTime(timezone=True),
-            nullable=True,
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("connector_credential_pair", "last_time_external_group_sync")

backend/alembic/versions/33cb72ea4d80_single_tool_call_per_message.py

@@ -1,50 +0,0 @@
-"""single tool call per message
-
-Revision ID: 33cb72ea4d80
-Revises: 5b29123cd710
-Create Date: 2024-11-01 12:51:01.535003
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "33cb72ea4d80"
-down_revision = "5b29123cd710"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Step 1: Delete extraneous ToolCall entries
-    # Keep only the ToolCall with the smallest 'id' for each 'message_id'
-    op.execute(
-        sa.text(
-            """
-            DELETE FROM tool_call
-            WHERE id NOT IN (
-                SELECT MIN(id)
-                FROM tool_call
-                WHERE message_id IS NOT NULL
-                GROUP BY message_id
-            );
-        """
-        )
-    )
-
-    # Step 2: Add a unique constraint on message_id
-    op.create_unique_constraint(
-        constraint_name="uq_tool_call_message_id",
-        table_name="tool_call",
-        columns=["message_id"],
-    )
-
-
-def downgrade() -> None:
-    # Step 1: Drop the unique constraint on message_id
-    op.drop_constraint(
-        constraint_name="uq_tool_call_message_id",
-        table_name="tool_call",
-        type_="unique",
-    )

backend/alembic/versions/47e5bef3a1d7_add_persona_categories.py

@@ -1,45 +0,0 @@
-"""add persona categories
-
-Revision ID: 47e5bef3a1d7
-Revises: dfbe9e93d3c7
-Create Date: 2024-11-05 18:55:02.221064
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "47e5bef3a1d7"
-down_revision = "dfbe9e93d3c7"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Create the persona_category table
-    op.create_table(
-        "persona_category",
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("name", sa.String(), nullable=False),
-        sa.Column("description", sa.String(), nullable=True),
-        sa.PrimaryKeyConstraint("id"),
-        sa.UniqueConstraint("name"),
-    )
-
-    # Add category_id to persona table
-    op.add_column("persona", sa.Column("category_id", sa.Integer(), nullable=True))
-    op.create_foreign_key(
-        "fk_persona_category",
-        "persona",
-        "persona_category",
-        ["category_id"],
-        ["id"],
-        ondelete="SET NULL",
-    )
-
-
-def downgrade() -> None:
-    op.drop_constraint("fk_persona_category", "persona", type_="foreignkey")
-    op.drop_column("persona", "category_id")
-    op.drop_table("persona_category")

backend/alembic/versions/4ee1287bd26a_add_multiple_slack_bot_support.py

@@ -1,280 +0,0 @@
-"""add_multiple_slack_bot_support
-
-Revision ID: 4ee1287bd26a
-Revises: 47e5bef3a1d7
-Create Date: 2024-11-06 13:15:53.302644
-
-"""
-import logging
-from typing import cast
-from alembic import op
-import sqlalchemy as sa
-from sqlalchemy.orm import Session
-from danswer.key_value_store.factory import get_kv_store
-from danswer.db.models import SlackBot
-from sqlalchemy.dialects import postgresql
-
-# revision identifiers, used by Alembic.
-revision = "4ee1287bd26a"
-down_revision = "47e5bef3a1d7"
-branch_labels: None = None
-depends_on: None = None
-
-# Configure logging
-logger = logging.getLogger("alembic.runtime.migration")
-logger.setLevel(logging.INFO)
-
-
-def upgrade() -> None:
-    logger.info(f"{revision}: create_table: slack_bot")
-    # Create new slack_bot table
-    op.create_table(
-        "slack_bot",
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("name", sa.String(), nullable=False),
-        sa.Column("enabled", sa.Boolean(), nullable=False, server_default="true"),
-        sa.Column("bot_token", sa.LargeBinary(), nullable=False),
-        sa.Column("app_token", sa.LargeBinary(), nullable=False),
-        sa.PrimaryKeyConstraint("id"),
-        sa.UniqueConstraint("bot_token"),
-        sa.UniqueConstraint("app_token"),
-    )
-
-    # # Create new slack_channel_config table
-    op.create_table(
-        "slack_channel_config",
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("slack_bot_id", sa.Integer(), nullable=True),
-        sa.Column("persona_id", sa.Integer(), nullable=True),
-        sa.Column("channel_config", postgresql.JSONB(), nullable=False),
-        sa.Column("response_type", sa.String(), nullable=False),
-        sa.Column(
-            "enable_auto_filters", sa.Boolean(), nullable=False, server_default="false"
-        ),
-        sa.ForeignKeyConstraint(
-            ["slack_bot_id"],
-            ["slack_bot.id"],
-        ),
-        sa.ForeignKeyConstraint(
-            ["persona_id"],
-            ["persona.id"],
-        ),
-        sa.PrimaryKeyConstraint("id"),
-    )
-
-    # Handle existing Slack bot tokens first
-    logger.info(f"{revision}: Checking for existing Slack bot.")
-    bot_token = None
-    app_token = None
-    first_row_id = None
-
-    try:
-        tokens = cast(dict, get_kv_store().load("slack_bot_tokens_config_key"))
-    except Exception:
-        logger.warning("No existing Slack bot tokens found.")
-        tokens = {}
-
-    bot_token = tokens.get("bot_token")
-    app_token = tokens.get("app_token")
-
-    if bot_token and app_token:
-        logger.info(f"{revision}: Found bot and app tokens.")
-
-        session = Session(bind=op.get_bind())
-        new_slack_bot = SlackBot(
-            name="Slack Bot (Migrated)",
-            enabled=True,
-            bot_token=bot_token,
-            app_token=app_token,
-        )
-        session.add(new_slack_bot)
-        session.commit()
-        first_row_id = new_slack_bot.id
-
-    # Create a default bot if none exists
-    # This is in case there are no slack tokens but there are channels configured
-    op.execute(
-        sa.text(
-            """
-            INSERT INTO slack_bot (name, enabled, bot_token, app_token)
-            SELECT 'Default Bot', true, '', ''
-            WHERE NOT EXISTS (SELECT 1 FROM slack_bot)
-            RETURNING id;
-            """
-        )
-    )
-
-    # Get the bot ID to use (either from existing migration or newly created)
-    bot_id_query = sa.text(
-        """
-        SELECT COALESCE(
-            :first_row_id,
-            (SELECT id FROM slack_bot ORDER BY id ASC LIMIT 1)
-        ) as bot_id;
-        """
-    )
-    result = op.get_bind().execute(bot_id_query, {"first_row_id": first_row_id})
-    bot_id = result.scalar()
-
-    # CTE (Common Table Expression) that transforms the old slack_bot_config table data
-    # This splits up the channel_names into their own rows
-    channel_names_cte = """
-        WITH channel_names AS (
-            SELECT
-                sbc.id as config_id,
-                sbc.persona_id,
-                sbc.response_type,
-                sbc.enable_auto_filters,
-                jsonb_array_elements_text(sbc.channel_config->'channel_names') as channel_name,
-                sbc.channel_config->>'respond_tag_only' as respond_tag_only,
-                sbc.channel_config->>'respond_to_bots' as respond_to_bots,
-                sbc.channel_config->'respond_member_group_list' as respond_member_group_list,
-                sbc.channel_config->'answer_filters' as answer_filters,
-                sbc.channel_config->'follow_up_tags' as follow_up_tags
-            FROM slack_bot_config sbc
-        )
-    """
-
-    # Insert the channel names into the new slack_channel_config table
-    insert_statement = """
-        INSERT INTO slack_channel_config (
-            slack_bot_id,
-            persona_id,
-            channel_config,
-            response_type,
-            enable_auto_filters
-        )
-        SELECT
-            :bot_id,
-            channel_name.persona_id,
-            jsonb_build_object(
-                'channel_name', channel_name.channel_name,
-                'respond_tag_only',
-                COALESCE((channel_name.respond_tag_only)::boolean, false),
-                'respond_to_bots',
-                COALESCE((channel_name.respond_to_bots)::boolean, false),
-                'respond_member_group_list',
-                COALESCE(channel_name.respond_member_group_list, '[]'::jsonb),
-                'answer_filters',
-                COALESCE(channel_name.answer_filters, '[]'::jsonb),
-                'follow_up_tags',
-                COALESCE(channel_name.follow_up_tags, '[]'::jsonb)
-            ),
-            channel_name.response_type,
-            channel_name.enable_auto_filters
-        FROM channel_names channel_name;
-    """
-
-    op.execute(sa.text(channel_names_cte + insert_statement).bindparams(bot_id=bot_id))
-
-    # Clean up old tokens if they existed
-    try:
-        if bot_token and app_token:
-            logger.info(f"{revision}: Removing old bot and app tokens.")
-            get_kv_store().delete("slack_bot_tokens_config_key")
-    except Exception:
-        logger.warning("tried to delete tokens in dynamic config but failed")
-    # Rename the table
-    op.rename_table(
-        "slack_bot_config__standard_answer_category",
-        "slack_channel_config__standard_answer_category",
-    )
-
-    # Rename the column
-    op.alter_column(
-        "slack_channel_config__standard_answer_category",
-        "slack_bot_config_id",
-        new_column_name="slack_channel_config_id",
-    )
-
-    # Drop the table with CASCADE to handle dependent objects
-    op.execute("DROP TABLE slack_bot_config CASCADE")
-
-    logger.info(f"{revision}: Migration complete.")
-
-
-def downgrade() -> None:
-    # Recreate the old slack_bot_config table
-    op.create_table(
-        "slack_bot_config",
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("persona_id", sa.Integer(), nullable=True),
-        sa.Column("channel_config", postgresql.JSONB(), nullable=False),
-        sa.Column("response_type", sa.String(), nullable=False),
-        sa.Column("enable_auto_filters", sa.Boolean(), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["persona_id"],
-            ["persona.id"],
-        ),
-        sa.PrimaryKeyConstraint("id"),
-    )
-
-    # Migrate data back to the old format
-    # Group by persona_id to combine channel names back into arrays
-    op.execute(
-        sa.text(
-            """
-            INSERT INTO slack_bot_config (
-                persona_id,
-                channel_config,
-                response_type,
-                enable_auto_filters
-            )
-            SELECT DISTINCT ON (persona_id)
-                persona_id,
-                jsonb_build_object(
-                    'channel_names', (
-                        SELECT jsonb_agg(c.channel_config->>'channel_name')
-                        FROM slack_channel_config c
-                        WHERE c.persona_id = scc.persona_id
-                    ),
-                    'respond_tag_only', (channel_config->>'respond_tag_only')::boolean,
-                    'respond_to_bots', (channel_config->>'respond_to_bots')::boolean,
-                    'respond_member_group_list', channel_config->'respond_member_group_list',
-                    'answer_filters', channel_config->'answer_filters',
-                    'follow_up_tags', channel_config->'follow_up_tags'
-                ),
-                response_type,
-                enable_auto_filters
-            FROM slack_channel_config scc
-            WHERE persona_id IS NOT NULL;
-            """
-        )
-    )
-
-    # Rename the table back
-    op.rename_table(
-        "slack_channel_config__standard_answer_category",
-        "slack_bot_config__standard_answer_category",
-    )
-
-    # Rename the column back
-    op.alter_column(
-        "slack_bot_config__standard_answer_category",
-        "slack_channel_config_id",
-        new_column_name="slack_bot_config_id",
-    )
-
-    # Try to save the first bot's tokens back to KV store
-    try:
-        first_bot = (
-            op.get_bind()
-            .execute(
-                sa.text(
-                    "SELECT bot_token, app_token FROM slack_bot ORDER BY id LIMIT 1"
-                )
-            )
-            .first()
-        )
-        if first_bot and first_bot.bot_token and first_bot.app_token:
-            tokens = {
-                "bot_token": first_bot.bot_token,
-                "app_token": first_bot.app_token,
-            }
-            get_kv_store().store("slack_bot_tokens_config_key", tokens)
-    except Exception:
-        logger.warning("Failed to save tokens back to KV store")
-
-    # Drop the new tables in reverse order
-    op.drop_table("slack_channel_config")
-    op.drop_table("slack_bot")

backend/alembic/versions/5b29123cd710_nullable_search_settings_for_historic_.py

@@ -1,70 +0,0 @@
-"""nullable search settings for historic index attempts
-
-Revision ID: 5b29123cd710
-Revises: 949b4a92a401
-Create Date: 2024-10-30 19:37:59.630704
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "5b29123cd710"
-down_revision = "949b4a92a401"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Drop the existing foreign key constraint
-    op.drop_constraint(
-        "fk_index_attempt_search_settings", "index_attempt", type_="foreignkey"
-    )
-
-    # Modify the column to be nullable
-    op.alter_column(
-        "index_attempt", "search_settings_id", existing_type=sa.INTEGER(), nullable=True
-    )
-
-    # Add back the foreign key with ON DELETE SET NULL
-    op.create_foreign_key(
-        "fk_index_attempt_search_settings",
-        "index_attempt",
-        "search_settings",
-        ["search_settings_id"],
-        ["id"],
-        ondelete="SET NULL",
-    )
-
-
-def downgrade() -> None:
-    # Warning: This will delete all index attempts that don't have search settings
-    op.execute(
-        """
-        DELETE FROM index_attempt
-        WHERE search_settings_id IS NULL
-    """
-    )
-
-    # Drop foreign key constraint
-    op.drop_constraint(
-        "fk_index_attempt_search_settings", "index_attempt", type_="foreignkey"
-    )
-
-    # Modify the column to be not nullable
-    op.alter_column(
-        "index_attempt",
-        "search_settings_id",
-        existing_type=sa.INTEGER(),
-        nullable=False,
-    )
-
-    # Add back the foreign key without ON DELETE SET NULL
-    op.create_foreign_key(
-        "fk_index_attempt_search_settings",
-        "index_attempt",
-        "search_settings",
-        ["search_settings_id"],
-        ["id"],
-    )

backend/alembic/versions/6d562f86c78b_remove_default_bot.py

@@ -1,45 +0,0 @@
-"""remove default bot
-
-Revision ID: 6d562f86c78b
-Revises: 177de57c21c9
-Create Date: 2024-11-22 11:51:29.331336
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-# revision identifiers, used by Alembic.
-revision = "6d562f86c78b"
-down_revision = "177de57c21c9"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.execute(
-        sa.text(
-            """
-            DELETE FROM slack_bot
-            WHERE name = 'Default Bot'
-            AND bot_token = ''
-            AND app_token = ''
-            AND NOT EXISTS (
-                SELECT 1 FROM slack_channel_config
-                WHERE slack_channel_config.slack_bot_id = slack_bot.id
-            )
-            """
-        )
-    )
-
-
-def downgrade() -> None:
-    op.execute(
-        sa.text(
-            """
-            INSERT INTO slack_bot (name, enabled, bot_token, app_token)
-            SELECT 'Default Bot', true, '', ''
-            WHERE NOT EXISTS (SELECT 1 FROM slack_bot)
-            RETURNING id;
-            """
-        )
-    )

backend/alembic/versions/776b3bbe9092_remove_remaining_enums.py

@@ -9,8 +9,8 @@ from alembic import op
 import sqlalchemy as sa
 
 from danswer.db.models import IndexModelStatus
-from danswer.context.search.enums import RecencyBiasSetting
-from danswer.context.search.enums import SearchType
+from danswer.search.enums import RecencyBiasSetting
+from danswer.search.enums import SearchType
 
 # revision identifiers, used by Alembic.
 revision = "776b3bbe9092"

backend/alembic/versions/93560ba1b118_add_web_ui_option_to_slack_config.py

@@ -1,35 +0,0 @@
-"""add web ui option to slack config
-
-Revision ID: 93560ba1b118
-Revises: 6d562f86c78b
-Create Date: 2024-11-24 06:36:17.490612
-
-"""
-from alembic import op
-
-# revision identifiers, used by Alembic.
-revision = "93560ba1b118"
-down_revision = "6d562f86c78b"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Add show_continue_in_web_ui with default False to all existing channel_configs
-    op.execute(
-        """
-        UPDATE slack_channel_config
-        SET channel_config = channel_config || '{"show_continue_in_web_ui": false}'::jsonb
-        WHERE NOT channel_config ? 'show_continue_in_web_ui'
-        """
-    )
-
-
-def downgrade() -> None:
-    # Remove show_continue_in_web_ui from all channel_configs
-    op.execute(
-        """
-        UPDATE slack_channel_config
-        SET channel_config = channel_config - 'show_continue_in_web_ui'
-        """
-    )

backend/alembic/versions/949b4a92a401_remove_rt.py

@@ -7,7 +7,6 @@ Create Date: 2024-10-26 13:06:06.937969
 """
 from alembic import op
 from sqlalchemy.orm import Session
-from sqlalchemy import text
 
 # Import your models and constants
 from danswer.db.models import (
@@ -16,6 +15,7 @@ from danswer.db.models import (
     Credential,
     IndexAttempt,
 )
+from danswer.configs.constants import DocumentSource
 
 
 # revision identifiers, used by Alembic.
@@ -30,11 +30,13 @@ def upgrade() -> None:
     bind = op.get_bind()
     session = Session(bind=bind)
 
-    # Get connectors using raw SQL
-    result = bind.execute(
-        text("SELECT id FROM connector WHERE source = 'requesttracker'")
+    connectors_to_delete = (
+        session.query(Connector)
+        .filter(Connector.source == DocumentSource.REQUESTTRACKER)
+        .all()
     )
-    connector_ids = [row[0] for row in result]
+
+    connector_ids = [connector.id for connector in connectors_to_delete]
 
     if connector_ids:
         cc_pairs_to_delete = (

backend/alembic/versions/9cf5c00f72fe_add_creator_to_cc_pair.py

@@ -1,30 +0,0 @@
-"""add creator to cc pair
-
-Revision ID: 9cf5c00f72fe
-Revises: 26b931506ecb
-Create Date: 2024-11-12 15:16:42.682902
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-# revision identifiers, used by Alembic.
-revision = "9cf5c00f72fe"
-down_revision = "26b931506ecb"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "connector_credential_pair",
-        sa.Column(
-            "creator_id",
-            sa.UUID(as_uuid=True),
-            nullable=True,
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("connector_credential_pair", "creator_id")

backend/alembic/versions/9f696734098f_combine_search_and_chat.py

@@ -1,36 +0,0 @@
-"""Combine Search and Chat
-
-Revision ID: 9f696734098f
-Revises: a8c2065484e6
-Create Date: 2024-11-27 15:32:19.694972
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-# revision identifiers, used by Alembic.
-revision = "9f696734098f"
-down_revision = "a8c2065484e6"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.alter_column("chat_session", "description", nullable=True)
-    op.drop_column("chat_session", "one_shot")
-    op.drop_column("slack_channel_config", "response_type")
-
-
-def downgrade() -> None:
-    op.execute("UPDATE chat_session SET description = '' WHERE description IS NULL")
-    op.alter_column("chat_session", "description", nullable=False)
-    op.add_column(
-        "chat_session",
-        sa.Column("one_shot", sa.Boolean(), nullable=False, server_default=sa.false()),
-    )
-    op.add_column(
-        "slack_channel_config",
-        sa.Column(
-            "response_type", sa.String(), nullable=False, server_default="citations"
-        ),
-    )

backend/alembic/versions/a8c2065484e6_add_auto_scroll_to_user_model.py

@@ -1,27 +0,0 @@
-"""add auto scroll to user model
-
-Revision ID: a8c2065484e6
-Revises: abe7378b8217
-Create Date: 2024-11-22 17:34:09.690295
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "a8c2065484e6"
-down_revision = "abe7378b8217"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "user",
-        sa.Column("auto_scroll", sa.Boolean(), nullable=True, server_default=None),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("user", "auto_scroll")

backend/alembic/versions/abe7378b8217_add_indexing_trigger_to_cc_pair.py

@@ -1,30 +0,0 @@
-"""add indexing trigger to cc_pair
-
-Revision ID: abe7378b8217
-Revises: 6d562f86c78b
-Create Date: 2024-11-26 19:09:53.481171
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-# revision identifiers, used by Alembic.
-revision = "abe7378b8217"
-down_revision = "93560ba1b118"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "connector_credential_pair",
-        sa.Column(
-            "indexing_trigger",
-            sa.Enum("UPDATE", "REINDEX", name="indexingmode", native_enum=False),
-            nullable=True,
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("connector_credential_pair", "indexing_trigger")

backend/alembic/versions/b156fa702355_chat_reworked.py

@@ -288,15 +288,6 @@ def upgrade() -> None:
 
 
 def downgrade() -> None:
-    # NOTE: you will lose all chat history. This is to satisfy the non-nullable constraints
-    # below
-    op.execute("DELETE FROM chat_feedback")
-    op.execute("DELETE FROM chat_message__search_doc")
-    op.execute("DELETE FROM document_retrieval_feedback")
-    op.execute("DELETE FROM document_retrieval_feedback")
-    op.execute("DELETE FROM chat_message")
-    op.execute("DELETE FROM chat_session")
-
     op.drop_constraint(
         "chat_feedback__chat_message_fk", "chat_feedback", type_="foreignkey"
     )

backend/alembic/versions/b72ed7a5db0e_remove_description_from_starter_messages.py

@@ -1,48 +0,0 @@
-"""remove description from starter messages
-
-Revision ID: b72ed7a5db0e
-Revises: 33cb72ea4d80
-Create Date: 2024-11-03 15:55:28.944408
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "b72ed7a5db0e"
-down_revision = "33cb72ea4d80"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.execute(
-        sa.text(
-            """
-            UPDATE persona
-            SET starter_messages = (
-                SELECT jsonb_agg(elem - 'description')
-                FROM jsonb_array_elements(starter_messages) elem
-            )
-            WHERE starter_messages IS NOT NULL
-              AND jsonb_typeof(starter_messages) = 'array'
-            """
-        )
-    )
-
-
-def downgrade() -> None:
-    op.execute(
-        sa.text(
-            """
-            UPDATE persona
-            SET starter_messages = (
-                SELECT jsonb_agg(elem || '{"description": ""}')
-                FROM jsonb_array_elements(starter_messages) elem
-            )
-            WHERE starter_messages IS NOT NULL
-              AND jsonb_typeof(starter_messages) = 'array'
-            """
-        )
-    )

backend/alembic/versions/c0fd6e4da83a_add_recent_assistants.py

@@ -1,29 +0,0 @@
-"""add recent assistants
-
-Revision ID: c0fd6e4da83a
-Revises: b72ed7a5db0e
-Create Date: 2024-11-03 17:28:54.916618
-
-"""
-from alembic import op
-import sqlalchemy as sa
-from sqlalchemy.dialects import postgresql
-
-# revision identifiers, used by Alembic.
-revision = "c0fd6e4da83a"
-down_revision = "b72ed7a5db0e"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "user",
-        sa.Column(
-            "recent_assistants", postgresql.JSONB(), server_default="[]", nullable=False
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("user", "recent_assistants")

backend/alembic/versions/c99d76fcd298_add_nullable_to_persona_id_in_chat_.py

@@ -23,56 +23,6 @@ def upgrade() -> None:
 
 
 def downgrade() -> None:
-    # Delete chat messages and feedback first since they reference chat sessions
-    # Get chat messages from sessions with null persona_id
-    chat_messages_query = """
-        SELECT id
-        FROM chat_message
-        WHERE chat_session_id IN (
-            SELECT id
-            FROM chat_session
-            WHERE persona_id IS NULL
-        )
-    """
-
-    # Delete dependent records first
-    op.execute(
-        f"""
-        DELETE FROM document_retrieval_feedback
-        WHERE chat_message_id IN (
-            {chat_messages_query}
-        )
-    """
-    )
-    op.execute(
-        f"""
-        DELETE FROM chat_message__search_doc
-        WHERE chat_message_id IN (
-            {chat_messages_query}
-        )
-    """
-    )
-
-    # Delete chat messages
-    op.execute(
-        """
-        DELETE FROM chat_message
-        WHERE chat_session_id IN (
-            SELECT id
-            FROM chat_session
-            WHERE persona_id IS NULL
-        )
-    """
-    )
-
-    # Now we can safely delete the chat sessions
-    op.execute(
-        """
-        DELETE FROM chat_session
-        WHERE persona_id IS NULL
-    """
-    )
-
     op.alter_column(
         "chat_session",
         "persona_id",

backend/alembic/versions/dfbe9e93d3c7_extended_role_for_non_web.py

@@ -1,42 +0,0 @@
-"""extended_role_for_non_web
-
-Revision ID: dfbe9e93d3c7
-Revises: 9cf5c00f72fe
-Create Date: 2024-11-16 07:54:18.727906
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-# revision identifiers, used by Alembic.
-revision = "dfbe9e93d3c7"
-down_revision = "9cf5c00f72fe"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.execute(
-        """
-        UPDATE "user"
-        SET role = 'EXT_PERM_USER'
-        WHERE has_web_login = false
-    """
-    )
-    op.drop_column("user", "has_web_login")
-
-
-def downgrade() -> None:
-    op.add_column(
-        "user",
-        sa.Column("has_web_login", sa.Boolean(), nullable=False, server_default="true"),
-    )
-
-    op.execute(
-        """
-        UPDATE "user"
-        SET has_web_login = false,
-            role = 'BASIC'
-        WHERE role IN ('SLACK_USER', 'EXT_PERM_USER')
-    """
-    )

backend/alembic_tenants/env.py

@@ -1,6 +1,5 @@
 import asyncio
 from logging.config import fileConfig
-from typing import Literal
 
 from sqlalchemy import pool
 from sqlalchemy.engine import Connection
@@ -38,15 +37,8 @@ EXCLUDE_TABLES = {"kombu_queue", "kombu_message"}
 
 def include_object(
     object: SchemaItem,
-    name: str | None,
-    type_: Literal[
-        "schema",
-        "table",
-        "column",
-        "index",
-        "unique_constraint",
-        "foreign_key_constraint",
-    ],
+    name: str,
+    type_: str,
     reflected: bool,
     compare_to: SchemaItem | None,
 ) -> bool:

backend/danswer/access/models.py

@@ -16,46 +16,6 @@ class ExternalAccess:
     is_public: bool
 
 
-@dataclass(frozen=True)
-class DocExternalAccess:
-    """
-    This is just a class to wrap the external access and the document ID
-    together. It's used for syncing document permissions to Redis.
-    """
-
-    external_access: ExternalAccess
-    # The document ID
-    doc_id: str
-
-    def to_dict(self) -> dict:
-        return {
-            "external_access": {
-                "external_user_emails": list(self.external_access.external_user_emails),
-                "external_user_group_ids": list(
-                    self.external_access.external_user_group_ids
-                ),
-                "is_public": self.external_access.is_public,
-            },
-            "doc_id": self.doc_id,
-        }
-
-    @classmethod
-    def from_dict(cls, data: dict) -> "DocExternalAccess":
-        external_access = ExternalAccess(
-            external_user_emails=set(
-                data["external_access"].get("external_user_emails", [])
-            ),
-            external_user_group_ids=set(
-                data["external_access"].get("external_user_group_ids", [])
-            ),
-            is_public=data["external_access"]["is_public"],
-        )
-        return cls(
-            external_access=external_access,
-            doc_id=data["doc_id"],
-        )
-
-
 @dataclass(frozen=True)
 class DocumentAccess(ExternalAccess):
     # User emails for Danswer users, None indicates admin

backend/danswer/agent_search/answer_query/graph_builder.py

@@ -1,100 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from danswer.agent_search.answer_query.nodes.answer_check import answer_check
-from danswer.agent_search.answer_query.nodes.answer_generation import answer_generation
-from danswer.agent_search.answer_query.nodes.format_answer import format_answer
-from danswer.agent_search.answer_query.states import AnswerQueryInput
-from danswer.agent_search.answer_query.states import AnswerQueryOutput
-from danswer.agent_search.answer_query.states import AnswerQueryState
-from danswer.agent_search.expanded_retrieval.graph_builder import (
-    expanded_retrieval_graph_builder,
-)
-
-
-def answer_query_graph_builder() -> StateGraph:
-    graph = StateGraph(
-        state_schema=AnswerQueryState,
-        input=AnswerQueryInput,
-        output=AnswerQueryOutput,
-    )
-
-    ### Add nodes ###
-
-    expanded_retrieval = expanded_retrieval_graph_builder().compile()
-    graph.add_node(
-        node="expanded_retrieval_for_initial_decomp",
-        action=expanded_retrieval,
-    )
-    graph.add_node(
-        node="answer_check",
-        action=answer_check,
-    )
-    graph.add_node(
-        node="answer_generation",
-        action=answer_generation,
-    )
-    graph.add_node(
-        node="format_answer",
-        action=format_answer,
-    )
-
-    ### Add edges ###
-
-    graph.add_edge(
-        start_key=START,
-        end_key="expanded_retrieval_for_initial_decomp",
-    )
-    graph.add_edge(
-        start_key="expanded_retrieval_for_initial_decomp",
-        end_key="answer_generation",
-    )
-    graph.add_edge(
-        start_key="answer_generation",
-        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 danswer.db.engine import get_session_context_manager
-    from danswer.llm.factory import get_default_llms
-    from danswer.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="Who made Excel and what other products did they make?",
-    )
-    with get_session_context_manager() as db_session:
-        inputs = AnswerQueryInput(
-            search_request=search_request,
-            primary_llm=primary_llm,
-            fast_llm=fast_llm,
-            db_session=db_session,
-            query_to_answer="Who made Excel?",
-        )
-        output = compiled_graph.invoke(
-            input=inputs,
-            # debug=True,
-            # subgraphs=True,
-        )
-        print(output)
-        # for namespace, chunk in compiled_graph.stream(
-        #     input=inputs,
-        #     # debug=True,
-        #     subgraphs=True,
-        # ):
-        #     print(namespace)
-        #     print(chunk)

backend/danswer/agent_search/answer_query/nodes/answer_check.py

@@ -1,30 +0,0 @@
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_message_runs
-
-from danswer.agent_search.answer_query.states import AnswerQueryState
-from danswer.agent_search.answer_query.states import QACheckOutput
-from danswer.agent_search.shared_graph_utils.prompts import BASE_CHECK_PROMPT
-
-
-def answer_check(state: AnswerQueryState) -> QACheckOutput:
-    msg = [
-        HumanMessage(
-            content=BASE_CHECK_PROMPT.format(
-                question=state["search_request"].query,
-                base_answer=state["answer"],
-            )
-        )
-    ]
-
-    fast_llm = state["fast_llm"]
-    response = list(
-        fast_llm.stream(
-            prompt=msg,
-        )
-    )
-
-    response_str = merge_message_runs(response, chunk_separator="")[0].content
-
-    return QACheckOutput(
-        answer_quality=response_str,
-    )

backend/danswer/agent_search/answer_query/nodes/answer_generation.py

@@ -1,32 +0,0 @@
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_message_runs
-
-from danswer.agent_search.answer_query.states import AnswerQueryState
-from danswer.agent_search.answer_query.states import QAGenerationOutput
-from danswer.agent_search.shared_graph_utils.prompts import BASE_RAG_PROMPT
-from danswer.agent_search.shared_graph_utils.utils import format_docs
-
-
-def answer_generation(state: AnswerQueryState) -> QAGenerationOutput:
-    query = state["query_to_answer"]
-    docs = state["reordered_documents"]
-
-    print(f"Number of verified retrieval docs: {len(docs)}")
-
-    msg = [
-        HumanMessage(
-            content=BASE_RAG_PROMPT.format(question=query, context=format_docs(docs))
-        )
-    ]
-
-    fast_llm = state["fast_llm"]
-    response = list(
-        fast_llm.stream(
-            prompt=msg,
-        )
-    )
-
-    answer_str = merge_message_runs(response, chunk_separator="")[0].content
-    return QAGenerationOutput(
-        answer=answer_str,
-    )

backend/danswer/agent_search/answer_query/nodes/format_answer.py

@@ -1,16 +0,0 @@
-from danswer.agent_search.answer_query.states import AnswerQueryOutput
-from danswer.agent_search.answer_query.states import AnswerQueryState
-from danswer.agent_search.answer_query.states import SearchAnswerResults
-
-
-def format_answer(state: AnswerQueryState) -> AnswerQueryOutput:
-    return AnswerQueryOutput(
-        decomp_answer_results=[
-            SearchAnswerResults(
-                query=state["query_to_answer"],
-                quality=state["answer_quality"],
-                answer=state["answer"],
-                documents=state["reordered_documents"],
-            )
-        ],
-    )

backend/danswer/agent_search/answer_query/states.py

@@ -1,45 +0,0 @@
-from typing import Annotated
-from typing import TypedDict
-
-from pydantic import BaseModel
-
-from danswer.agent_search.core_state import PrimaryState
-from danswer.agent_search.shared_graph_utils.operators import dedup_inference_sections
-from danswer.context.search.models import InferenceSection
-
-
-class SearchAnswerResults(BaseModel):
-    query: str
-    answer: str
-    quality: str
-    documents: Annotated[list[InferenceSection], dedup_inference_sections]
-
-
-class QACheckOutput(TypedDict, total=False):
-    answer_quality: str
-
-
-class QAGenerationOutput(TypedDict, total=False):
-    answer: str
-
-
-class ExpandedRetrievalOutput(TypedDict):
-    reordered_documents: Annotated[list[InferenceSection], dedup_inference_sections]
-
-
-class AnswerQueryState(
-    PrimaryState,
-    QACheckOutput,
-    QAGenerationOutput,
-    ExpandedRetrievalOutput,
-    total=True,
-):
-    query_to_answer: str
-
-
-class AnswerQueryInput(PrimaryState, total=True):
-    query_to_answer: str
-
-
-class AnswerQueryOutput(TypedDict):
-    decomp_answer_results: list[SearchAnswerResults]

backend/danswer/agent_search/core_state.py

@@ -1,15 +0,0 @@
-from typing import TypedDict
-
-from sqlalchemy.orm import Session
-
-from danswer.context.search.models import SearchRequest
-from danswer.llm.interfaces import LLM
-
-
-class PrimaryState(TypedDict, total=False):
-    search_request: SearchRequest
-    primary_llm: LLM
-    fast_llm: LLM
-    # a single session for the entire agent search
-    # is fine if we are only reading
-    db_session: Session

backend/danswer/agent_search/deep_answer/nodes/answer_generation.py

@@ -1,114 +0,0 @@
-from typing import Any
-
-from langchain_core.messages import HumanMessage
-
-from danswer.agent_search.main.states import MainState
-from danswer.agent_search.shared_graph_utils.prompts import COMBINED_CONTEXT
-from danswer.agent_search.shared_graph_utils.prompts import MODIFIED_RAG_PROMPT
-from danswer.agent_search.shared_graph_utils.utils import format_docs
-from danswer.agent_search.shared_graph_utils.utils import normalize_whitespace
-
-
-# aggregate sub questions and answers
-def deep_answer_generation(state: MainState) -> dict[str, Any]:
-    """
-    Generate answer
-
-    Args:
-        state (messages): The current state
-
-    Returns:
-         dict: The updated state with re-phrased question
-    """
-    print("---DEEP GENERATE---")
-
-    question = state["original_question"]
-    docs = state["deduped_retrieval_docs"]
-
-    deep_answer_context = state["core_answer_dynamic_context"]
-
-    print(f"Number of verified retrieval docs - deep: {len(docs)}")
-
-    combined_context = normalize_whitespace(
-        COMBINED_CONTEXT.format(
-            deep_answer_context=deep_answer_context, formated_docs=format_docs(docs)
-        )
-    )
-
-    msg = [
-        HumanMessage(
-            content=MODIFIED_RAG_PROMPT.format(
-                question=question, combined_context=combined_context
-            )
-        )
-    ]
-
-    # Grader
-    model = state["fast_llm"]
-    response = model.invoke(msg)
-
-    return {
-        "deep_answer": response.content,
-    }
-
-
-def final_stuff(state: MainState) -> dict[str, Any]:
-    """
-    Invokes the agent model to generate a response based on the current state. Given
-    the question, it will decide to retrieve using the retriever tool, or simply end.
-
-    Args:
-        state (messages): The current state
-
-    Returns:
-        dict: The updated state with the agent response appended to messages
-    """
-    print("---FINAL---")
-
-    messages = state["log_messages"]
-    time_ordered_messages = [x.pretty_repr() for x in messages]
-    time_ordered_messages.sort()
-
-    print("Message Log:")
-    print("\n".join(time_ordered_messages))
-
-    initial_sub_qas = state["initial_sub_qas"]
-    initial_sub_qa_list = []
-    for initial_sub_qa in initial_sub_qas:
-        if initial_sub_qa["sub_answer_check"] == "yes":
-            initial_sub_qa_list.append(
-                f'  Question:\n  {initial_sub_qa["sub_question"]}\n  --\n  Answer:\n  {initial_sub_qa["sub_answer"]}\n  -----'
-            )
-
-    initial_sub_qa_context = "\n".join(initial_sub_qa_list)
-
-    base_answer = state["base_answer"]
-
-    print(f"Final Base Answer:\n{base_answer}")
-    print("--------------------------------")
-    print(f"Initial Answered Sub Questions:\n{initial_sub_qa_context}")
-    print("--------------------------------")
-
-    if not state.get("deep_answer"):
-        print("No Deep Answer was required")
-        return {}
-
-    deep_answer = state["deep_answer"]
-    sub_qas = state["sub_qas"]
-    sub_qa_list = []
-    for sub_qa in sub_qas:
-        if sub_qa["sub_answer_check"] == "yes":
-            sub_qa_list.append(
-                f'  Question:\n  {sub_qa["sub_question"]}\n  --\n  Answer:\n  {sub_qa["sub_answer"]}\n  -----'
-            )
-
-    sub_qa_context = "\n".join(sub_qa_list)
-
-    print(f"Final Base Answer:\n{base_answer}")
-    print("--------------------------------")
-    print(f"Final Deep Answer:\n{deep_answer}")
-    print("--------------------------------")
-    print("Sub Questions and Answers:")
-    print(sub_qa_context)
-
-    return {}

backend/danswer/agent_search/deep_answer/nodes/deep_decomp.py

@@ -1,78 +0,0 @@
-import json
-import re
-from datetime import datetime
-from typing import Any
-
-from langchain_core.messages import HumanMessage
-
-from danswer.agent_search.main.states import MainState
-from danswer.agent_search.shared_graph_utils.prompts import DEEP_DECOMPOSE_PROMPT
-from danswer.agent_search.shared_graph_utils.utils import format_entity_term_extraction
-from danswer.agent_search.shared_graph_utils.utils import generate_log_message
-
-
-def decompose(state: MainState) -> dict[str, Any]:
-    """ """
-
-    node_start_time = datetime.now()
-
-    question = state["original_question"]
-    base_answer = state["base_answer"]
-
-    # get the entity term extraction dict and properly format it
-    entity_term_extraction_dict = state["retrieved_entities_relationships"][
-        "retrieved_entities_relationships"
-    ]
-
-    entity_term_extraction_str = format_entity_term_extraction(
-        entity_term_extraction_dict
-    )
-
-    initial_question_answers = state["initial_sub_qas"]
-
-    addressed_question_list = [
-        x["sub_question"]
-        for x in initial_question_answers
-        if x["sub_answer_check"] == "yes"
-    ]
-    failed_question_list = [
-        x["sub_question"]
-        for x in initial_question_answers
-        if x["sub_answer_check"] == "no"
-    ]
-
-    msg = [
-        HumanMessage(
-            content=DEEP_DECOMPOSE_PROMPT.format(
-                question=question,
-                entity_term_extraction_str=entity_term_extraction_str,
-                base_answer=base_answer,
-                answered_sub_questions="\n - ".join(addressed_question_list),
-                failed_sub_questions="\n - ".join(failed_question_list),
-            ),
-        )
-    ]
-
-    # Grader
-    model = state["fast_llm"]
-    response = model.invoke(msg)
-
-    cleaned_response = re.sub(r"```json\n|\n```", "", response.pretty_repr())
-    parsed_response = json.loads(cleaned_response)
-
-    sub_questions_dict = {}
-    for sub_question_nr, sub_question_dict in enumerate(
-        parsed_response["sub_questions"]
-    ):
-        sub_question_dict["answered"] = False
-        sub_question_dict["verified"] = False
-        sub_questions_dict[sub_question_nr] = sub_question_dict
-
-    return {
-        "decomposed_sub_questions_dict": sub_questions_dict,
-        "log_messages": generate_log_message(
-            message="deep - decompose",
-            node_start_time=node_start_time,
-            graph_start_time=state["graph_start_time"],
-        ),
-    }

backend/danswer/agent_search/deep_answer/nodes/entity_term_extraction.py

@@ -1,40 +0,0 @@
-import json
-import re
-from typing import Any
-
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_message_runs
-
-from danswer.agent_search.main.states import MainState
-from danswer.agent_search.shared_graph_utils.prompts import ENTITY_TERM_PROMPT
-from danswer.agent_search.shared_graph_utils.utils import format_docs
-
-
-def entity_term_extraction(state: MainState) -> dict[str, Any]:
-    """Extract entities and terms from the question and context"""
-
-    question = state["original_question"]
-    docs = state["deduped_retrieval_docs"]
-
-    doc_context = format_docs(docs)
-
-    msg = [
-        HumanMessage(
-            content=ENTITY_TERM_PROMPT.format(question=question, context=doc_context),
-        )
-    ]
-    fast_llm = state["fast_llm"]
-    # Grader
-    llm_response_list = list(
-        fast_llm.stream(
-            prompt=msg,
-        )
-    )
-    llm_response = merge_message_runs(llm_response_list, chunk_separator="")[0].content
-
-    cleaned_response = re.sub(r"```json\n|\n```", "", llm_response)
-    parsed_response = json.loads(cleaned_response)
-
-    return {
-        "retrieved_entities_relationships": parsed_response,
-    }

backend/danswer/agent_search/deep_answer/nodes/sub_qa_level_aggregator.py

@@ -1,30 +0,0 @@
-from typing import Any
-
-from danswer.agent_search.main.states import MainState
-
-
-# aggregate sub questions and answers
-def sub_qa_level_aggregator(state: MainState) -> dict[str, Any]:
-    sub_qas = state["sub_qas"]
-
-    dynamic_context_list = [
-        "Below you will find useful information to answer the original question:"
-    ]
-    checked_sub_qas = []
-
-    for core_answer_sub_qa in sub_qas:
-        question = core_answer_sub_qa["sub_question"]
-        answer = core_answer_sub_qa["sub_answer"]
-        verified = core_answer_sub_qa["sub_answer_check"]
-
-        if verified == "yes":
-            dynamic_context_list.append(
-                f"Question:\n{question}\n\nAnswer:\n{answer}\n\n---\n\n"
-            )
-            checked_sub_qas.append({"sub_question": question, "sub_answer": answer})
-    dynamic_context = "\n".join(dynamic_context_list)
-
-    return {
-        "core_answer_dynamic_context": dynamic_context,
-        "checked_sub_qas": checked_sub_qas,
-    }

backend/danswer/agent_search/deep_answer/nodes/sub_qa_manager.py

@@ -1,19 +0,0 @@
-from typing import Any
-
-from danswer.agent_search.main.states import MainState
-
-
-def sub_qa_manager(state: MainState) -> dict[str, Any]:
-    """ """
-
-    sub_questions_dict = state["decomposed_sub_questions_dict"]
-
-    sub_questions = {}
-
-    for sub_question_nr, sub_question_dict in sub_questions_dict.items():
-        sub_questions[sub_question_nr] = sub_question_dict["sub_question"]
-
-    return {
-        "sub_questions": sub_questions,
-        "num_new_question_iterations": 0,
-    }

backend/danswer/agent_search/expanded_retrieval/edges.py

@@ -1,44 +0,0 @@
-from collections.abc import Hashable
-
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_message_runs
-from langgraph.types import Send
-
-from danswer.agent_search.expanded_retrieval.nodes.doc_retrieval import RetrieveInput
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalInput
-from danswer.agent_search.shared_graph_utils.prompts import REWRITE_PROMPT_MULTI
-from danswer.llm.interfaces import LLM
-
-
-def parallel_retrieval_edge(state: ExpandedRetrievalInput) -> list[Send | Hashable]:
-    print(f"parallel_retrieval_edge state: {state.keys()}")
-
-    # This should be better...
-    question = state.get("query_to_answer") or state["search_request"].query
-    llm: LLM = state["fast_llm"]
-
-    msg = [
-        HumanMessage(
-            content=REWRITE_PROMPT_MULTI.format(question=question),
-        )
-    ]
-    llm_response_list = list(
-        llm.stream(
-            prompt=msg,
-        )
-    )
-    llm_response = merge_message_runs(llm_response_list, chunk_separator="")[0].content
-
-    print(f"llm_response: {llm_response}")
-
-    rewritten_queries = llm_response.split("\n")
-
-    print(f"rewritten_queries: {rewritten_queries}")
-
-    return [
-        Send(
-            "doc_retrieval",
-            RetrieveInput(query_to_retrieve=query, **state),
-        )
-        for query in rewritten_queries
-    ]

backend/danswer/agent_search/expanded_retrieval/graph_builder.py

@@ -1,88 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from danswer.agent_search.expanded_retrieval.edges import parallel_retrieval_edge
-from danswer.agent_search.expanded_retrieval.nodes.doc_reranking import doc_reranking
-from danswer.agent_search.expanded_retrieval.nodes.doc_retrieval import doc_retrieval
-from danswer.agent_search.expanded_retrieval.nodes.doc_verification import (
-    doc_verification,
-)
-from danswer.agent_search.expanded_retrieval.nodes.verification_kickoff import (
-    verification_kickoff,
-)
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalInput
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalOutput
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
-
-
-def expanded_retrieval_graph_builder() -> StateGraph:
-    graph = StateGraph(
-        state_schema=ExpandedRetrievalState,
-        input=ExpandedRetrievalInput,
-        output=ExpandedRetrievalOutput,
-    )
-
-    ### Add nodes ###
-
-    graph.add_node(
-        node="doc_retrieval",
-        action=doc_retrieval,
-    )
-    graph.add_node(
-        node="verification_kickoff",
-        action=verification_kickoff,
-    )
-    graph.add_node(
-        node="doc_verification",
-        action=doc_verification,
-    )
-    graph.add_node(
-        node="doc_reranking",
-        action=doc_reranking,
-    )
-
-    ### Add edges ###
-
-    graph.add_conditional_edges(
-        source=START,
-        path=parallel_retrieval_edge,
-        path_map=["doc_retrieval"],
-    )
-    graph.add_edge(
-        start_key="doc_retrieval",
-        end_key="verification_kickoff",
-    )
-    graph.add_edge(
-        start_key="doc_verification",
-        end_key="doc_reranking",
-    )
-    graph.add_edge(
-        start_key="doc_reranking",
-        end_key=END,
-    )
-
-    return graph
-
-
-if __name__ == "__main__":
-    from danswer.db.engine import get_session_context_manager
-    from danswer.llm.factory import get_default_llms
-    from danswer.context.search.models import SearchRequest
-
-    graph = expanded_retrieval_graph_builder()
-    compiled_graph = graph.compile()
-    primary_llm, fast_llm = get_default_llms()
-    search_request = SearchRequest(
-        query="Who made Excel and what other products did they make?",
-    )
-    with get_session_context_manager() as db_session:
-        inputs = ExpandedRetrievalInput(
-            search_request=search_request,
-            primary_llm=primary_llm,
-            fast_llm=fast_llm,
-            db_session=db_session,
-            query_to_answer="Who made Excel?",
-        )
-        for thing in compiled_graph.stream(inputs, debug=True):
-            print(thing)

backend/danswer/agent_search/expanded_retrieval/nodes/doc_reranking.py

@@ -1,11 +0,0 @@
-from danswer.agent_search.expanded_retrieval.states import DocRerankingOutput
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
-
-
-def doc_reranking(state: ExpandedRetrievalState) -> DocRerankingOutput:
-    print(f"doc_reranking state: {state.keys()}")
-
-    verified_documents = state["verified_documents"]
-    reranked_documents = verified_documents
-
-    return DocRerankingOutput(reranked_documents=reranked_documents)

backend/danswer/agent_search/expanded_retrieval/nodes/doc_retrieval.py

@@ -1,47 +0,0 @@
-from danswer.agent_search.expanded_retrieval.states import DocRetrievalOutput
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
-from danswer.context.search.models import InferenceSection
-from danswer.context.search.models import SearchRequest
-from danswer.context.search.pipeline import SearchPipeline
-from danswer.db.engine import get_session_context_manager
-
-
-class RetrieveInput(ExpandedRetrievalState):
-    query_to_retrieve: str
-
-
-def doc_retrieval(state: RetrieveInput) -> DocRetrievalOutput:
-    # def doc_retrieval(state: RetrieveInput) -> Command[Literal["doc_verification"]]:
-    """
-    Retrieve documents
-
-    Args:
-        state (dict): The current graph state
-
-    Returns:
-        state (dict): New key added to state, documents, that contains retrieved documents
-    """
-    print(f"doc_retrieval state: {state.keys()}")
-
-    state["query_to_retrieve"]
-
-    documents: list[InferenceSection] = []
-    llm = state["primary_llm"]
-    fast_llm = state["fast_llm"]
-    # db_session = state["db_session"]
-    query_to_retrieve = state["search_request"].query
-    with get_session_context_manager() as db_session1:
-        documents = SearchPipeline(
-            search_request=SearchRequest(
-                query=query_to_retrieve,
-            ),
-            user=None,
-            llm=llm,
-            fast_llm=fast_llm,
-            db_session=db_session1,
-        ).reranked_sections
-
-    print(f"retrieved documents: {len(documents)}")
-    return DocRetrievalOutput(
-        retrieved_documents=documents,
-    )

backend/danswer/agent_search/expanded_retrieval/nodes/doc_verification.py

@@ -1,60 +0,0 @@
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_message_runs
-
-from danswer.agent_search.expanded_retrieval.states import DocVerificationOutput
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
-from danswer.agent_search.shared_graph_utils.models import BinaryDecision
-from danswer.agent_search.shared_graph_utils.prompts import VERIFIER_PROMPT
-from danswer.context.search.models import InferenceSection
-
-
-class DocVerificationInput(ExpandedRetrievalState, total=True):
-    doc_to_verify: InferenceSection
-
-
-def doc_verification(state: DocVerificationInput) -> DocVerificationOutput:
-    """
-    Check whether the document is relevant for the original user question
-
-    Args:
-        state (VerifierState): The current state
-
-    Returns:
-        dict: ict: The updated state with the final decision
-    """
-
-    print(f"doc_verification state: {state.keys()}")
-
-    original_query = state["search_request"].query
-    doc_to_verify = state["doc_to_verify"]
-    document_content = doc_to_verify.combined_content
-
-    msg = [
-        HumanMessage(
-            content=VERIFIER_PROMPT.format(
-                question=original_query, document_content=document_content
-            )
-        )
-    ]
-
-    fast_llm = state["fast_llm"]
-    response = list(
-        fast_llm.stream(
-            prompt=msg,
-        )
-    )
-
-    response_string = merge_message_runs(response, chunk_separator="")[0].content
-    # Convert string response to proper dictionary format
-    decision_dict = {"decision": response_string.lower()}
-    formatted_response = BinaryDecision.model_validate(decision_dict)
-
-    print(f"Verdict: {formatted_response.decision}")
-
-    verified_documents = []
-    if formatted_response.decision == "yes":
-        verified_documents.append(doc_to_verify)
-
-    return DocVerificationOutput(
-        verified_documents=verified_documents,
-    )

backend/danswer/agent_search/expanded_retrieval/nodes/verification_kickoff.py

@@ -1,27 +0,0 @@
-from typing import Literal
-
-from langgraph.types import Command
-from langgraph.types import Send
-
-from danswer.agent_search.expanded_retrieval.nodes.doc_verification import (
-    DocVerificationInput,
-)
-from danswer.agent_search.expanded_retrieval.states import ExpandedRetrievalState
-
-
-def verification_kickoff(
-    state: ExpandedRetrievalState,
-) -> Command[Literal["doc_verification"]]:
-    print(f"verification_kickoff state: {state.keys()}")
-
-    documents = state["retrieved_documents"]
-    return Command(
-        update={},
-        goto=[
-            Send(
-                node="doc_verification",
-                arg=DocVerificationInput(doc_to_verify=doc, **state),
-            )
-            for doc in documents
-        ],
-    )

backend/danswer/agent_search/expanded_retrieval/states.py

@@ -1,36 +0,0 @@
-from typing import Annotated
-from typing import TypedDict
-
-from danswer.agent_search.core_state import PrimaryState
-from danswer.agent_search.shared_graph_utils.operators import dedup_inference_sections
-from danswer.context.search.models import InferenceSection
-
-
-class DocRetrievalOutput(TypedDict, total=False):
-    retrieved_documents: Annotated[list[InferenceSection], dedup_inference_sections]
-
-
-class DocVerificationOutput(TypedDict, total=False):
-    verified_documents: Annotated[list[InferenceSection], dedup_inference_sections]
-
-
-class DocRerankingOutput(TypedDict, total=False):
-    reranked_documents: Annotated[list[InferenceSection], dedup_inference_sections]
-
-
-class ExpandedRetrievalState(
-    PrimaryState,
-    DocRetrievalOutput,
-    DocVerificationOutput,
-    DocRerankingOutput,
-    total=True,
-):
-    query_to_answer: str
-
-
-class ExpandedRetrievalInput(PrimaryState, total=True):
-    query_to_answer: str
-
-
-class ExpandedRetrievalOutput(TypedDict):
-    reordered_documents: Annotated[list[InferenceSection], dedup_inference_sections]

backend/danswer/agent_search/main/edges.py

@@ -1,61 +0,0 @@
-from collections.abc import Hashable
-
-from langgraph.types import Send
-
-from danswer.agent_search.answer_query.states import AnswerQueryInput
-from danswer.agent_search.main.states import MainState
-
-
-def parallelize_decompozed_answer_queries(state: MainState) -> list[Send | Hashable]:
-    return [
-        Send(
-            "answer_query",
-            AnswerQueryInput(
-                **state,
-                query_to_answer=query,
-            ),
-        )
-        for query in state["initial_decomp_queries"]
-    ]
-
-
-# def continue_to_answer_sub_questions(state: QAState) -> Union[Hashable, list[Hashable]]:
-#     # Routes re-written queries to the (parallel) retrieval steps
-#     # Notice the 'Send()' API that takes care of the parallelization
-#     return [
-#         Send(
-#             "sub_answers_graph",
-#             ResearchQAState(
-#                 sub_question=sub_question["sub_question_str"],
-#                 sub_question_nr=sub_question["sub_question_nr"],
-#                 graph_start_time=state["graph_start_time"],
-#                 primary_llm=state["primary_llm"],
-#                 fast_llm=state["fast_llm"],
-#             ),
-#         )
-#         for sub_question in state["sub_questions"]
-#     ]
-
-
-# def continue_to_deep_answer(state: QAState) -> Union[Hashable, list[Hashable]]:
-#     print("---GO TO DEEP ANSWER OR END---")
-
-#     base_answer = state["base_answer"]
-
-#     question = state["original_question"]
-
-#     BASE_CHECK_MESSAGE = [
-#         HumanMessage(
-#             content=BASE_CHECK_PROMPT.format(question=question, base_answer=base_answer)
-#         )
-#     ]
-
-#     model = state["fast_llm"]
-#     response = model.invoke(BASE_CHECK_MESSAGE)
-
-#     print(f"CAN WE CONTINUE W/O GENERATING A DEEP ANSWER? - {response.pretty_repr()}")
-
-#     if response.pretty_repr() == "no":
-#         return "decompose"
-#     else:
-#         return "end"

backend/danswer/agent_search/main/graph_builder.py

@@ -1,98 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from danswer.agent_search.answer_query.graph_builder import answer_query_graph_builder
-from danswer.agent_search.expanded_retrieval.graph_builder import (
-    expanded_retrieval_graph_builder,
-)
-from danswer.agent_search.main.edges import parallelize_decompozed_answer_queries
-from danswer.agent_search.main.nodes.base_decomp import main_decomp_base
-from danswer.agent_search.main.nodes.generate_initial_answer import (
-    generate_initial_answer,
-)
-from danswer.agent_search.main.states import MainInput
-from danswer.agent_search.main.states import MainState
-
-
-def main_graph_builder() -> StateGraph:
-    graph = StateGraph(
-        state_schema=MainState,
-        input=MainInput,
-    )
-
-    ### Add nodes ###
-
-    graph.add_node(
-        node="base_decomp",
-        action=main_decomp_base,
-    )
-    answer_query_subgraph = answer_query_graph_builder().compile()
-    graph.add_node(
-        node="answer_query",
-        action=answer_query_subgraph,
-    )
-    expanded_retrieval_subgraph = expanded_retrieval_graph_builder().compile()
-    graph.add_node(
-        node="expanded_retrieval",
-        action=expanded_retrieval_subgraph,
-    )
-    graph.add_node(
-        node="generate_initial_answer",
-        action=generate_initial_answer,
-    )
-
-    ### Add edges ###
-    graph.add_edge(
-        start_key=START,
-        end_key="expanded_retrieval",
-    )
-
-    graph.add_edge(
-        start_key=START,
-        end_key="base_decomp",
-    )
-    graph.add_conditional_edges(
-        source="base_decomp",
-        path=parallelize_decompozed_answer_queries,
-        path_map=["answer_query"],
-    )
-    graph.add_edge(
-        start_key=["answer_query", "expanded_retrieval"],
-        end_key="generate_initial_answer",
-    )
-    graph.add_edge(
-        start_key="generate_initial_answer",
-        end_key=END,
-    )
-
-    return graph
-
-
-if __name__ == "__main__":
-    from danswer.db.engine import get_session_context_manager
-    from danswer.llm.factory import get_default_llms
-    from danswer.context.search.models import SearchRequest
-
-    graph = main_graph_builder()
-    compiled_graph = graph.compile()
-    primary_llm, fast_llm = get_default_llms()
-    search_request = SearchRequest(
-        query="If i am familiar with the function that I need, how can I type it into a cell?",
-    )
-    with get_session_context_manager() as db_session:
-        inputs = MainInput(
-            search_request=search_request,
-            primary_llm=primary_llm,
-            fast_llm=fast_llm,
-            db_session=db_session,
-        )
-        for thing in compiled_graph.stream(
-            input=inputs,
-            # stream_mode="debug",
-            # debug=True,
-            subgraphs=True,
-        ):
-            # print(thing)
-            print()
-            print()

backend/danswer/agent_search/main/nodes/base_decomp.py

@@ -1,31 +0,0 @@
-from langchain_core.messages import HumanMessage
-
-from danswer.agent_search.main.states import BaseDecompOutput
-from danswer.agent_search.main.states import MainState
-from danswer.agent_search.shared_graph_utils.prompts import INITIAL_DECOMPOSITION_PROMPT
-from danswer.agent_search.shared_graph_utils.utils import clean_and_parse_list_string
-
-
-def main_decomp_base(state: MainState) -> BaseDecompOutput:
-    question = state["search_request"].query
-
-    msg = [
-        HumanMessage(
-            content=INITIAL_DECOMPOSITION_PROMPT.format(question=question),
-        )
-    ]
-
-    # Get the rewritten queries in a defined format
-    model = state["fast_llm"]
-    response = model.invoke(msg)
-
-    content = response.pretty_repr()
-    list_of_subquestions = clean_and_parse_list_string(content)
-
-    decomp_list: list[str] = [
-        sub_question["sub_question"].strip() for sub_question in list_of_subquestions
-    ]
-
-    return BaseDecompOutput(
-        initial_decomp_queries=decomp_list,
-    )

backend/danswer/agent_search/main/nodes/generate_initial_answer.py

@@ -1,53 +0,0 @@
-from langchain_core.messages import HumanMessage
-
-from danswer.agent_search.main.states import InitialAnswerOutput
-from danswer.agent_search.main.states import MainState
-from danswer.agent_search.shared_graph_utils.prompts import INITIAL_RAG_PROMPT
-from danswer.agent_search.shared_graph_utils.utils import format_docs
-
-
-def generate_initial_answer(state: MainState) -> InitialAnswerOutput:
-    print("---GENERATE INITIAL---")
-
-    question = state["search_request"].query
-    docs = state["documents"]
-
-    decomp_answer_results = state["decomp_answer_results"]
-
-    good_qa_list: list[str] = []
-
-    _SUB_QUESTION_ANSWER_TEMPLATE = """
-    Sub-Question:\n  - {sub_question}\n  --\nAnswer:\n  - {sub_answer}\n\n
-    """
-    for decomp_answer_result in decomp_answer_results:
-        if (
-            decomp_answer_result.quality.lower() == "yes"
-            and len(decomp_answer_result.answer) > 0
-            and decomp_answer_result.answer != "I don't know"
-        ):
-            good_qa_list.append(
-                _SUB_QUESTION_ANSWER_TEMPLATE.format(
-                    sub_question=decomp_answer_result.query,
-                    sub_answer=decomp_answer_result.answer,
-                )
-            )
-
-    sub_question_answer_str = "\n\n------\n\n".join(good_qa_list)
-
-    msg = [
-        HumanMessage(
-            content=INITIAL_RAG_PROMPT.format(
-                question=question,
-                context=format_docs(docs),
-                answered_sub_questions=sub_question_answer_str,
-            )
-        )
-    ]
-
-    # Grader
-    model = state["fast_llm"]
-    response = model.invoke(msg)
-    answer = response.pretty_repr()
-
-    print(answer)
-    return InitialAnswerOutput(initial_answer=answer)

backend/danswer/agent_search/main/states.py

@@ -1,37 +0,0 @@
-from operator import add
-from typing import Annotated
-from typing import TypedDict
-
-from danswer.agent_search.answer_query.states import SearchAnswerResults
-from danswer.agent_search.core_state import PrimaryState
-from danswer.agent_search.shared_graph_utils.operators import dedup_inference_sections
-from danswer.context.search.models import InferenceSection
-
-
-class BaseDecompOutput(TypedDict, total=False):
-    initial_decomp_queries: list[str]
-
-
-class InitialAnswerOutput(TypedDict, total=False):
-    initial_answer: str
-
-
-class MainState(
-    PrimaryState,
-    BaseDecompOutput,
-    InitialAnswerOutput,
-    total=True,
-):
-    documents: Annotated[list[InferenceSection], dedup_inference_sections]
-    decomp_answer_results: Annotated[list[SearchAnswerResults], add]
-
-
-class MainInput(PrimaryState, total=True):
-    pass
-
-
-class MainOutput(TypedDict):
-    """
-    This is not used because defining the output only matters for filtering the output of
-      a .invoke() call but we are streaming so we just yield the entire state.
-    """

backend/danswer/agent_search/run_graph.py

@@ -1,27 +0,0 @@
-from danswer.agent_search.primary_graph.graph_builder import build_core_graph
-from danswer.llm.answering.answer import AnswerStream
-from danswer.llm.interfaces import LLM
-from danswer.tools.tool import Tool
-
-
-def run_graph(
-    query: str,
-    llm: LLM,
-    tools: list[Tool],
-) -> AnswerStream:
-    graph = build_core_graph()
-
-    inputs = {
-        "original_query": query,
-        "messages": [],
-        "tools": tools,
-        "llm": llm,
-    }
-    compiled_graph = graph.compile()
-    output = compiled_graph.invoke(input=inputs)
-    yield from output
-
-
-if __name__ == "__main__":
-    pass
-    # run_graph("What is the capital of France?", llm, [])

backend/danswer/agent_search/shared_graph_utils/models.py

@@ -1,12 +0,0 @@
-from typing import Literal
-
-from pydantic import BaseModel
-
-
-# Pydantic models for structured outputs
-class RewrittenQueries(BaseModel):
-    rewritten_queries: list[str]
-
-
-class BinaryDecision(BaseModel):
-    decision: Literal["yes", "no"]

backend/danswer/agent_search/shared_graph_utils/operators.py

@@ -1,9 +0,0 @@
-from danswer.context.search.models import InferenceSection
-from danswer.llm.answering.prune_and_merge import _merge_sections
-
-
-def dedup_inference_sections(
-    list1: list[InferenceSection], list2: list[InferenceSection]
-) -> list[InferenceSection]:
-    deduped = _merge_sections(list1 + list2)
-    return deduped

backend/danswer/agent_search/shared_graph_utils/prompts.py

@@ -1,427 +0,0 @@
-REWRITE_PROMPT_MULTI_ORIGINAL = """ \n
-    Please convert an initial user question into a 2-3 more appropriate short and pointed search queries for retrievel from a
-    document store. Particularly, try to think about resolving ambiguities and make the search queries more specific,
-    enabling the system to search more broadly.
-    Also, try to make the search queries not redundant, i.e. not too similar! \n\n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-    Formulate the queries separated by '--' (Do not say 'Query 1: ...', just write the querytext): """
-
-REWRITE_PROMPT_MULTI = """ \n
-    Please create a list of 2-3 sample documents that could answer an original question. Each document
-    should be about as long as the original question. \n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-    Formulate the sample documents separated by '--' (Do not say 'Document 1: ...', just write the text): """
-
-BASE_RAG_PROMPT = """ \n
-    You are an assistant for question-answering tasks. Use the context provided below - and only the
-    provided context - to answer the question. If you don't know the answer or if the provided context is
-    empty, just say "I don't know". Do not use your internal knowledge!
-
-    Again, only use the provided context and do not use your internal knowledge! If you cannot answer the
-    question based on the context, say "I don't know". It is a matter of life and death that you do NOT
-    use your internal knowledge, just the provided information!
-
-    Use three sentences maximum and keep the answer concise.
-    answer concise.\nQuestion:\n {question} \nContext:\n {context} \n\n
-    \n\n
-    Answer:"""
-
-BASE_CHECK_PROMPT = """ \n
-    Please check whether 1) the suggested answer seems to fully address the original question AND 2)the
-    original question requests a simple, factual answer, and there are no ambiguities, judgements,
-    aggregations, or any other complications that may require extra context. (I.e., if the question is
-    somewhat addressed, but the answer would benefit from more context, then answer with 'no'.)
-
-    Please only answer with 'yes' or 'no' \n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-    Here is the proposed answer:
-    \n ------- \n
-    {base_answer}
-    \n ------- \n
-    Please answer with yes or no:"""
-
-VERIFIER_PROMPT = """ \n
-    Please check whether the document seems to be relevant for the answer of the question. Please
-    only answer with 'yes' or 'no' \n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-    Here is the document text:
-    \n ------- \n
-    {document_content}
-    \n ------- \n
-    Please answer with yes or no:"""
-
-INITIAL_DECOMPOSITION_PROMPT_BASIC = """ \n
-    Please decompose an initial user question into not more than 4 appropriate sub-questions that help to
-    answer the original question. The purpose for this decomposition is to isolate individulal entities
-    (i.e., 'compare sales of company A and company B' -> 'what are sales for company A' + 'what are sales
-    for company B'), split ambiguous terms (i.e., 'what is our success with company A' -> 'what are our
-    sales with company A' + 'what is our market share with company A' + 'is company A a reference customer
-    for us'), etc. Each sub-question should be realistically be answerable by a good RAG system. \n
-
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-
-    Please formulate your answer as a list of subquestions:
-
-    Answer:
-    """
-
-REWRITE_PROMPT_SINGLE = """ \n
-    Please convert an initial user question into a more appropriate search query for retrievel from a
-    document store. \n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-
-    Formulate the query: """
-
-MODIFIED_RAG_PROMPT = """You are an assistant for question-answering tasks. Use the context provided below
-    - and only this context - to answer the question. If you don't know the answer, just say "I don't know".
-    Use three sentences maximum and keep the answer concise.
-    Pay also particular attention to the sub-questions and their answers, at least it may enrich the answer.
-    Again, only use the provided context and do not use your internal knowledge! If you cannot answer the
-    question based on the context, say "I don't know". It is a matter of life and death that you do NOT
-    use your internal knowledge, just the provided information!
-
-    \nQuestion: {question}
-    \nContext: {combined_context} \n
-
-    Answer:"""
-
-ORIG_DEEP_DECOMPOSE_PROMPT = """ \n
-    An initial user question needs to be answered. An initial answer has been provided but it wasn't quite
-    good enough. Also, some sub-questions had been answered and this information has been used to provide
-    the initial answer. Some other subquestions may have been suggested based on little knowledge, but they
-    were not directly answerable. Also, some entities, relationships and terms are givenm to you so that
-    you have an idea of how the avaiolable data looks like.
-
-    Your role is to generate 3-5 new sub-questions that would help to answer the initial question,
-    considering:
-
-    1) The initial question
-    2) The initial answer that was found to be unsatisfactory
-    3) The sub-questions that were answered
-    4) The sub-questions that were suggested but not answered
-    5) The entities, relationships and terms that were extracted from the context
-
-    The individual questions should be answerable by a good RAG system.
-    So a good idea would be to use the sub-questions to resolve ambiguities and/or to separate the
-    question for different entities that may be involved in the original question, but in a way that does
-    not duplicate questions that were already tried.
-
-    Additional Guidelines:
-    - The sub-questions should be specific to the question and provide richer context for the question,
-    resolve ambiguities, or address shortcoming of the initial answer
-    - Each sub-question - when answered - should be relevant for the answer to the original question
-    - The sub-questions should be free from comparisions, ambiguities,judgements, aggregations, or any
-    other complications that may require extra context.
-    - The sub-questions MUST have the full context of the original question so that it can be executed by
-    a RAG system independently without the original question available
-      (Example:
-        - initial question: "What is the capital of France?"
-        - bad sub-question: "What is the name of the river there?"
-        - good sub-question: "What is the name of the river that flows through Paris?"
-    - For each sub-question, please provide a short explanation for why it is a good sub-question. So
-    generate a list of dictionaries with the following format:
-      [{{"sub_question": <sub-question>, "explanation": <explanation>, "search_term": <rewrite the
-      sub-question using as a search phrase for the document store>}}, ...]
-
-    \n\n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-
-    Here is the initial sub-optimal answer:
-    \n ------- \n
-    {base_answer}
-    \n ------- \n
-
-    Here are the sub-questions that were answered:
-    \n ------- \n
-    {answered_sub_questions}
-    \n ------- \n
-
-    Here are the sub-questions that were suggested but not answered:
-    \n ------- \n
-    {failed_sub_questions}
-    \n ------- \n
-
-    And here are the entities, relationships and terms extracted from the context:
-    \n ------- \n
-    {entity_term_extraction_str}
-    \n ------- \n
-
-   Please generate the list of good, fully contextualized sub-questions that would help to address the
-   main question. Again, please find questions that are NOT overlapping too much with the already answered
-   sub-questions or those that already were suggested and failed.
-   In other words - what can we try in addition to what has been tried so far?
-
-   Please think through it step by step and then generate the list of json dictionaries with the following
-   format:
-
-   {{"sub_questions": [{{"sub_question": <sub-question>,
-        "explanation": <explanation>,
-        "search_term": <rewrite the sub-question using as a search phrase for the document store>}},
-        ...]}} """
-
-DEEP_DECOMPOSE_PROMPT = """ \n
-    An initial user question needs to be answered. An initial answer has been provided but it wasn't quite
-    good enough. Also, some sub-questions had been answered and this information has been used to provide
-    the initial answer. Some other subquestions may have been suggested based on little knowledge, but they
-    were not directly answerable. Also, some entities, relationships and terms are givenm to you so that
-    you have an idea of how the avaiolable data looks like.
-
-    Your role is to generate 4-6 new sub-questions that would help to answer the initial question,
-    considering:
-
-    1) The initial question
-    2) The initial answer that was found to be unsatisfactory
-    3) The sub-questions that were answered
-    4) The sub-questions that were suggested but not answered
-    5) The entities, relationships and terms that were extracted from the context
-
-    The individual questions should be answerable by a good RAG system.
-    So a good idea would be to use the sub-questions to resolve ambiguities and/or to separate the
-    question for different entities that may be involved in the original question, but in a way that does
-    not duplicate questions that were already tried.
-
-    Additional Guidelines:
-    - The sub-questions should be specific to the question and provide richer context for the question,
-    resolve ambiguities, or address shortcoming of the initial answer
-    - Each sub-question - when answered - should be relevant for the answer to the original question
-    - The sub-questions should be free from comparisions, ambiguities,judgements, aggregations, or any
-    other complications that may require extra context.
-    - The sub-questions MUST have the full context of the original question so that it can be executed by
-    a RAG system independently without the original question available
-      (Example:
-        - initial question: "What is the capital of France?"
-        - bad sub-question: "What is the name of the river there?"
-        - good sub-question: "What is the name of the river that flows through Paris?"
-    - For each sub-question, please also provide a search term that can be used to retrieve relevant
-    documents from a document store.
-    \n\n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-
-    Here is the initial sub-optimal answer:
-    \n ------- \n
-    {base_answer}
-    \n ------- \n
-
-    Here are the sub-questions that were answered:
-    \n ------- \n
-    {answered_sub_questions}
-    \n ------- \n
-
-    Here are the sub-questions that were suggested but not answered:
-    \n ------- \n
-    {failed_sub_questions}
-    \n ------- \n
-
-    And here are the entities, relationships and terms extracted from the context:
-    \n ------- \n
-    {entity_term_extraction_str}
-    \n ------- \n
-
-   Please generate the list of good, fully contextualized sub-questions that would help to address the
-   main question. Again, please find questions that are NOT overlapping too much with the already answered
-   sub-questions or those that already were suggested and failed.
-   In other words - what can we try in addition to what has been tried so far?
-
-   Generate the list of json dictionaries with the following format:
-
-   {{"sub_questions": [{{"sub_question": <sub-question>,
-        "search_term": <rewrite the sub-question using as a search phrase for the document store>}},
-        ...]}} """
-
-DECOMPOSE_PROMPT = """ \n
-    For an initial user question, please generate at 5-10 individual sub-questions whose answers would help
-    \n to answer the initial question. The individual questions should be answerable by a good RAG system.
-    So a good idea would be to \n use the sub-questions to resolve ambiguities and/or to separate the
-    question for different entities that may be involved in the original question.
-
-    In order to arrive at meaningful sub-questions, please also consider the context retrieved from the
-    document store, expressed as entities, relationships and terms. You can also think about the types
-    mentioned in brackets
-
-    Guidelines:
-    - The sub-questions should be specific to the question and provide richer context for the question,
-    and or resolve ambiguities
-    - Each sub-question - when answered - should be relevant for the answer to the original question
-    - The sub-questions should be free from comparisions, ambiguities,judgements, aggregations, or any
-    other complications that may require extra context.
-    - The sub-questions MUST have the full context of the original question so that it can be executed by
-    a RAG system independently without the original question available
-      (Example:
-        - initial question: "What is the capital of France?"
-        - bad sub-question: "What is the name of the river there?"
-        - good sub-question: "What is the name of the river that flows through Paris?"
-    - For each sub-question, please provide a short explanation for why it is a good sub-question. So
-    generate a list of dictionaries with the following format:
-      [{{"sub_question": <sub-question>, "explanation": <explanation>, "search_term": <rewrite the
-      sub-question using as a search phrase for the document store>}}, ...]
-
-    \n\n
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-
-    And here are the entities, relationships and terms extracted from the context:
-    \n ------- \n
-    {entity_term_extraction_str}
-    \n ------- \n
-
-   Please generate the list of good, fully contextualized sub-questions that would help to address the
-   main question. Don't be too specific unless the original question is specific.
-   Please think through it step by step and then generate the list of json dictionaries with the following
-   format:
-   {{"sub_questions": [{{"sub_question": <sub-question>,
-        "explanation": <explanation>,
-        "search_term": <rewrite the sub-question using as a search phrase for the document store>}},
-        ...]}} """
-
-#### Consolidations
-COMBINED_CONTEXT = """-------
-    Below you will find useful information to answer the original question. First, you see a number of
-    sub-questions with their answers. This information should be considered to be more focussed and
-    somewhat more specific to the original question as it tries to contextualized facts.
-    After that will see the documents that were considered to be relevant to answer the original question.
-
-    Here are the sub-questions and their answers:
-    \n\n {deep_answer_context} \n\n
-    \n\n Here are the documents that were considered to be relevant to answer the original question:
-    \n\n {formated_docs} \n\n
-    ----------------
-    """
-
-SUB_QUESTION_EXPLANATION_RANKER_PROMPT = """-------
-    Below you will find a question that we ultimately want to answer (the original question) and a list of
-    motivations in arbitrary order for generated sub-questions that are supposed to help us answering the
-    original question. The motivations are formatted as <motivation number>:  <motivation explanation>.
-    (Again, the numbering is arbitrary and does not necessarily mean that 1 is the most relevant
-    motivation and 2 is less relevant.)
-
-    Please rank the motivations in order of relevance for answering the original question. Also, try to
-    ensure that the top questions do not duplicate too much, i.e. that they are not too similar.
-    Ultimately, create a list with the motivation numbers where the number of the most relevant
-    motivations comes first.
-
-    Here is the original question:
-    \n\n {original_question} \n\n
-    \n\n Here is the list of sub-question motivations:
-    \n\n {sub_question_explanations} \n\n
-    ----------------
-
-    Please think step by step and then generate the ranked list of motivations.
-
-    Please format your answer as a json object in the following format:
-    {{"reasonning": <explain your reasoning for the ranking>,
-      "ranked_motivations": <ranked list of motivation numbers>}}
-    """
-
-
-INITIAL_DECOMPOSITION_PROMPT = """ \n
-    Please decompose an initial user question into 2 or 3 appropriate sub-questions that help to
-    answer the original question. The purpose for this decomposition is to isolate individulal entities
-    (i.e., 'compare sales of company A and company B' -> 'what are sales for company A' + 'what are sales
-    for company B'), split ambiguous terms (i.e., 'what is our success with company A' -> 'what are our
-    sales with company A' + 'what is our market share with company A' + 'is company A a reference customer
-    for us'), etc. Each sub-question should be realistically be answerable by a good RAG system. \n
-
-    For each sub-question, please also create one search term that can be used to retrieve relevant
-    documents from a document store.
-
-    Here is the initial question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-
-    Please formulate your answer as a list of json objects with the following format:
-
-   [{{"sub_question": <sub-question>, "search_term": <search term>}}, ...]
-
-    Answer:
-    """
-
-INITIAL_RAG_PROMPT = """ \n
-    You are an assistant for question-answering tasks. Use the information provided below - and only the
-    provided information - to answer the provided question.
-
-    The information provided below consists of:
-     1) a number of answered sub-questions - these are very important(!) and definitely should be
-     considered to answer the question.
-     2) a number of documents that were also deemed relevant for the question.
-
-    If you don't know the answer or if the provided information is empty or insufficient, just say
-    "I don't know". Do not use your internal knowledge!
-
-    Again, only use the provided informationand do not use your internal knowledge! It is a matter of life
-    and death that you do NOT use your internal knowledge, just the provided information!
-
-    Try to keep your answer concise.
-
-    And here is the question and the provided information:
-    \n
-    \nQuestion:\n {question}
-
-    \nAnswered Sub-questions:\n {answered_sub_questions}
-
-    \nContext:\n {context} \n\n
-    \n\n
-
-    Answer:"""
-
-ENTITY_TERM_PROMPT = """ \n
-    Based on the original question and the context retieved from a dataset, please generate a list of
-    entities (e.g. companies, organizations, industries, products, locations, etc.), terms and concepts
-    (e.g. sales, revenue, etc.) that are relevant for the question, plus their relations to each other.
-
-    \n\n
-    Here is the original question:
-    \n ------- \n
-    {question}
-    \n ------- \n
-   And here is the context retrieved:
-    \n ------- \n
-    {context}
-    \n ------- \n
-
-    Please format your answer as a json object in the following format:
-
-    {{"retrieved_entities_relationships": {{
-        "entities": [{{
-            "entity_name": <assign a name for the entity>,
-            "entity_type": <specify a short type name for the entity, such as 'company', 'location',...>
-        }}],
-        "relationships": [{{
-            "name": <assign a name for the relationship>,
-            "type": <specify a short type name for the relationship, such as 'sales_to', 'is_location_of',...>,
-            "entities": [<related entity name 1>, <related entity name 2>]
-        }}],
-        "terms": [{{
-            "term_name": <assign a name for the term>,
-            "term_type": <specify a short type name for the term, such as 'revenue', 'market_share',...>,
-            "similar_to": <list terms that are similar to this term>
-        }}]
-    }}
-    }}
-   """

backend/danswer/agent_search/shared_graph_utils/utils.py

@@ -1,101 +0,0 @@
-import ast
-import json
-import re
-from collections.abc import Sequence
-from datetime import datetime
-from datetime import timedelta
-from typing import Any
-
-from danswer.context.search.models import InferenceSection
-
-
-def normalize_whitespace(text: str) -> str:
-    """Normalize whitespace in text to single spaces and strip leading/trailing whitespace."""
-    import re
-
-    return re.sub(r"\s+", " ", text.strip())
-
-
-# Post-processing
-def format_docs(docs: Sequence[InferenceSection]) -> str:
-    return "\n\n".join(doc.combined_content for doc in docs)
-
-
-def clean_and_parse_list_string(json_string: str) -> list[dict]:
-    # Remove any prefixes/labels before the actual JSON content
-    json_string = re.sub(r"^.*?(?=\[)", "", json_string, flags=re.DOTALL)
-
-    # Remove markdown code block markers and any newline prefixes
-    cleaned_string = re.sub(r"```json\n|\n```", "", json_string)
-    cleaned_string = cleaned_string.replace("\\n", " ").replace("\n", " ")
-    cleaned_string = " ".join(cleaned_string.split())
-
-    # Try parsing with json.loads first, fall back to ast.literal_eval
-    try:
-        return json.loads(cleaned_string)
-    except json.JSONDecodeError:
-        try:
-            return ast.literal_eval(cleaned_string)
-        except (ValueError, SyntaxError) as e:
-            raise ValueError(f"Failed to parse JSON string: {cleaned_string}") from e
-
-
-def clean_and_parse_json_string(json_string: str) -> dict[str, Any]:
-    # Remove markdown code block markers and any newline prefixes
-    cleaned_string = re.sub(r"```json\n|\n```", "", json_string)
-    cleaned_string = cleaned_string.replace("\\n", " ").replace("\n", " ")
-    cleaned_string = " ".join(cleaned_string.split())
-    # Parse the cleaned string into a Python dictionary
-    return json.loads(cleaned_string)
-
-
-def format_entity_term_extraction(entity_term_extraction_dict: dict[str, Any]) -> str:
-    entities = entity_term_extraction_dict["entities"]
-    terms = entity_term_extraction_dict["terms"]
-    relationships = entity_term_extraction_dict["relationships"]
-
-    entity_strs = ["\nEntities:\n"]
-    for entity in entities:
-        entity_str = f"{entity['entity_name']} ({entity['entity_type']})"
-        entity_strs.append(entity_str)
-
-    entity_str = "\n - ".join(entity_strs)
-
-    relationship_strs = ["\n\nRelationships:\n"]
-    for relationship in relationships:
-        relationship_str = f"{relationship['name']} ({relationship['type']}): {relationship['entities']}"
-        relationship_strs.append(relationship_str)
-
-    relationship_str = "\n - ".join(relationship_strs)
-
-    term_strs = ["\n\nTerms:\n"]
-    for term in terms:
-        term_str = f"{term['term_name']} ({term['term_type']}): similar to {term['similar_to']}"
-        term_strs.append(term_str)
-
-    term_str = "\n - ".join(term_strs)
-
-    return "\n".join(entity_strs + relationship_strs + term_strs)
-
-
-def _format_time_delta(time: timedelta) -> str:
-    seconds_from_start = f"{((time).seconds):03d}"
-    microseconds_from_start = f"{((time).microseconds):06d}"
-    return f"{seconds_from_start}.{microseconds_from_start}"
-
-
-def generate_log_message(
-    message: str,
-    node_start_time: datetime,
-    graph_start_time: datetime | None = None,
-) -> str:
-    current_time = datetime.now()
-
-    if graph_start_time is not None:
-        graph_time_str = _format_time_delta(current_time - graph_start_time)
-    else:
-        graph_time_str = "N/A"
-
-    node_time_str = _format_time_delta(current_time - node_start_time)
-
-    return f"{graph_time_str} ({node_time_str} s): {message}"

backend/danswer/auth/invited_users.py

@@ -2,8 +2,8 @@ from typing import cast
 
 from danswer.configs.constants import KV_USER_STORE_KEY
 from danswer.key_value_store.factory import get_kv_store
+from danswer.key_value_store.interface import JSON_ro
 from danswer.key_value_store.interface import KvKeyNotFoundError
-from danswer.utils.special_types import JSON_ro
 
 
 def get_invited_users() -> list[str]:

backend/danswer/auth/noauth_user.py

@@ -23,9 +23,7 @@ def load_no_auth_user_preferences(store: KeyValueStore) -> UserPreferences:
         )
         return UserPreferences(**preferences_data)
     except KvKeyNotFoundError:
-        return UserPreferences(
-            chosen_assistants=None, default_model=None, auto_scroll=True
-        )
+        return UserPreferences(chosen_assistants=None, default_model=None)
 
 
 def fetch_no_auth_user(store: KeyValueStore) -> UserInfo:

backend/danswer/auth/schemas.py

@@ -13,24 +13,12 @@ class UserRole(str, Enum):
         groups they are curators of
     - Global Curator can perform admin actions
         for all groups they are a member of
-    - Limited can access a limited set of basic api endpoints
-    - Slack are users that have used danswer via slack but dont have a web login
-    - External permissioned users that have been picked up during the external permissions sync process but don't have a web login
     """
 
-    LIMITED = "limited"
     BASIC = "basic"
     ADMIN = "admin"
     CURATOR = "curator"
     GLOBAL_CURATOR = "global_curator"
-    SLACK_USER = "slack_user"
-    EXT_PERM_USER = "ext_perm_user"
-
-    def is_web_login(self) -> bool:
-        return self not in [
-            UserRole.SLACK_USER,
-            UserRole.EXT_PERM_USER,
-        ]
 
 
 class UserStatus(str, Enum):
@@ -45,8 +33,10 @@ class UserRead(schemas.BaseUser[uuid.UUID]):
 
 class UserCreate(schemas.BaseUserCreate):
     role: UserRole = UserRole.BASIC
+    has_web_login: bool | None = True
     tenant_id: str | None = None
 
 
 class UserUpdate(schemas.BaseUserUpdate):
     role: UserRole
+    has_web_login: bool | None = True

backend/danswer/auth/users.py

@@ -48,10 +48,11 @@ from httpx_oauth.integrations.fastapi import OAuth2AuthorizeCallback
 from httpx_oauth.oauth2 import BaseOAuth2
 from httpx_oauth.oauth2 import OAuth2Token
 from pydantic import BaseModel
+from sqlalchemy import select
 from sqlalchemy import text
-from sqlalchemy.ext.asyncio import AsyncSession
+from sqlalchemy.orm import attributes
+from sqlalchemy.orm import Session
 
-from danswer.auth.api_key import get_hashed_api_key_from_request
 from danswer.auth.invited_users import get_invited_users
 from danswer.auth.schemas import UserCreate
 from danswer.auth.schemas import UserRole
@@ -74,28 +75,28 @@ from danswer.configs.constants import AuthType
 from danswer.configs.constants import DANSWER_API_KEY_DUMMY_EMAIL_DOMAIN
 from danswer.configs.constants import DANSWER_API_KEY_PREFIX
 from danswer.configs.constants import UNNAMED_KEY_PLACEHOLDER
-from danswer.db.api_key import fetch_user_for_api_key
 from danswer.db.auth import get_access_token_db
 from danswer.db.auth import get_default_admin_user_emails
 from danswer.db.auth import get_user_count
 from danswer.db.auth import get_user_db
 from danswer.db.auth import SQLAlchemyUserAdminDB
-from danswer.db.engine import get_async_session
 from danswer.db.engine import get_async_session_with_tenant
+from danswer.db.engine import get_session
 from danswer.db.engine import get_session_with_tenant
+from danswer.db.engine import get_sqlalchemy_engine
 from danswer.db.models import AccessToken
 from danswer.db.models import OAuthAccount
 from danswer.db.models import User
+from danswer.db.models import UserTenantMapping
 from danswer.db.users import get_user_by_email
-from danswer.server.utils import BasicAuthenticationError
 from danswer.utils.logger import setup_logger
 from danswer.utils.telemetry import optional_telemetry
 from danswer.utils.telemetry import RecordType
-from danswer.utils.variable_functionality import fetch_ee_implementation_or_noop
 from danswer.utils.variable_functionality import fetch_versioned_implementation
-from shared_configs.configs import async_return_default_schema
+from shared_configs.configs import CURRENT_TENANT_ID_CONTEXTVAR
 from shared_configs.configs import MULTI_TENANT
-from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
+from shared_configs.configs import POSTGRES_DEFAULT_SCHEMA
+
 
 logger = setup_logger()
 
@@ -189,6 +190,20 @@ def verify_email_domain(email: str) -> None:
             )
 
 
+def get_tenant_id_for_email(email: str) -> str:
+    if not MULTI_TENANT:
+        return POSTGRES_DEFAULT_SCHEMA
+    # Implement logic to get tenant_id from the mapping table
+    with Session(get_sqlalchemy_engine()) as db_session:
+        result = db_session.execute(
+            select(UserTenantMapping.tenant_id).where(UserTenantMapping.email == email)
+        )
+        tenant_id = result.scalar_one_or_none()
+    if tenant_id is None:
+        raise exceptions.UserNotExists()
+    return tenant_id
+
+
 def send_user_verification_email(
     user_email: str,
     token: str,
@@ -217,26 +232,25 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
     reset_password_token_secret = USER_AUTH_SECRET
     verification_token_secret = USER_AUTH_SECRET
 
-    user_db: SQLAlchemyUserDatabase[User, uuid.UUID]
-
     async def create(
         self,
         user_create: schemas.UC | UserCreate,
         safe: bool = False,
         request: Optional[Request] = None,
     ) -> User:
-        referral_source = None
-        if request is not None:
-            referral_source = request.cookies.get("referral_source", None)
+        try:
+            tenant_id = (
+                get_tenant_id_for_email(user_create.email)
+                if MULTI_TENANT
+                else POSTGRES_DEFAULT_SCHEMA
+            )
+        except exceptions.UserNotExists:
+            raise HTTPException(status_code=401, detail="User not found")
 
-        tenant_id = await fetch_ee_implementation_or_noop(
-            "danswer.server.tenants.provisioning",
-            "get_or_create_tenant_id",
-            async_return_default_schema,
-        )(
-            email=user_create.email,
-            referral_source=referral_source,
-        )
+        if not tenant_id:
+            raise HTTPException(
+                status_code=401, detail="User does not belong to an organization"
+            )
 
         async with get_async_session_with_tenant(tenant_id) as db_session:
             token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
@@ -244,9 +258,7 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
             verify_email_is_invited(user_create.email)
             verify_email_domain(user_create.email)
             if MULTI_TENANT:
-                tenant_user_db = SQLAlchemyUserAdminDB[User, uuid.UUID](
-                    db_session, User, OAuthAccount
-                )
+                tenant_user_db = SQLAlchemyUserAdminDB(db_session, User, OAuthAccount)
                 self.user_db = tenant_user_db
                 self.database = tenant_user_db
 
@@ -259,15 +271,20 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
                     user_create.role = UserRole.ADMIN
                 else:
                     user_create.role = UserRole.BASIC
-
+            user = None
             try:
                 user = await super().create(user_create, safe=safe, request=request)  # type: ignore
             except exceptions.UserAlreadyExists:
                 user = await self.get_by_email(user_create.email)
                 # Handle case where user has used product outside of web and is now creating an account through web
-                if not user.role.is_web_login() and user_create.role.is_web_login():
+                if (
+                    not user.has_web_login
+                    and hasattr(user_create, "has_web_login")
+                    and user_create.has_web_login
+                ):
                     user_update = UserUpdate(
                         password=user_create.password,
+                        has_web_login=True,
                         role=user_create.role,
                         is_verified=user_create.is_verified,
                     )
@@ -275,13 +292,11 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
                 else:
                     raise exceptions.UserAlreadyExists()
 
-            finally:
-                CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
-
+            CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
             return user
 
     async def oauth_callback(
-        self,
+        self: "BaseUserManager[models.UOAP, models.ID]",
         oauth_name: str,
         access_token: str,
         account_id: str,
@@ -292,24 +307,20 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
         *,
         associate_by_email: bool = False,
         is_verified_by_default: bool = False,
-    ) -> User:
-        referral_source = None
-        if request:
-            referral_source = getattr(request.state, "referral_source", None)
-
-        tenant_id = await fetch_ee_implementation_or_noop(
-            "danswer.server.tenants.provisioning",
-            "get_or_create_tenant_id",
-            async_return_default_schema,
-        )(
-            email=account_email,
-            referral_source=referral_source,
-        )
+    ) -> models.UOAP:
+        # Get tenant_id from mapping table
+        try:
+            tenant_id = (
+                get_tenant_id_for_email(account_email)
+                if MULTI_TENANT
+                else POSTGRES_DEFAULT_SCHEMA
+            )
+        except exceptions.UserNotExists:
+            raise HTTPException(status_code=401, detail="User not found")
 
         if not tenant_id:
             raise HTTPException(status_code=401, detail="User not found")
 
-        # Proceed with the tenant context
         token = None
         async with get_async_session_with_tenant(tenant_id) as db_session:
             token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
@@ -318,11 +329,9 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
             verify_email_domain(account_email)
 
             if MULTI_TENANT:
-                tenant_user_db = SQLAlchemyUserAdminDB[User, uuid.UUID](
-                    db_session, User, OAuthAccount
-                )
+                tenant_user_db = SQLAlchemyUserAdminDB(db_session, User, OAuthAccount)
                 self.user_db = tenant_user_db
-                self.database = tenant_user_db
+                self.database = tenant_user_db  # type: ignore
 
             oauth_account_dict = {
                 "oauth_name": oauth_name,
@@ -362,9 +371,9 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
                     # Explicitly set the Postgres schema for this session to ensure
                     # OAuth account creation happens in the correct tenant schema
                     await db_session.execute(text(f'SET search_path = "{tenant_id}"'))
-
-                    # Add OAuth account
-                    await self.user_db.add_oauth_account(user, oauth_account_dict)
+                    user = await self.user_db.add_oauth_account(
+                        user, oauth_account_dict
+                    )
                     await self.on_after_register(user, request)
 
             else:
@@ -374,11 +383,7 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
                         and existing_oauth_account.oauth_name == oauth_name
                     ):
                         user = await self.user_db.update_oauth_account(
-                            user,
-                            # NOTE: OAuthAccount DOES implement the OAuthAccountProtocol
-                            # but the type checker doesn't know that :(
-                            existing_oauth_account,  # type: ignore
-                            oauth_account_dict,
+                            user, existing_oauth_account, oauth_account_dict
                         )
 
             # NOTE: Most IdPs have very short expiry times, and we don't want to force the user to
@@ -391,15 +396,16 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
                 )
 
             # Handle case where user has used product outside of web and is now creating an account through web
-            if not user.role.is_web_login():
+            if not user.has_web_login:  # type: ignore
                 await self.user_db.update(
                     user,
                     {
                         "is_verified": is_verified_by_default,
-                        "role": UserRole.BASIC,
+                        "has_web_login": True,
                     },
                 )
                 user.is_verified = is_verified_by_default
+                user.has_web_login = True  # type: ignore
 
             # this is needed if an organization goes from `TRACK_EXTERNAL_IDP_EXPIRY=true` to `false`
             # otherwise, the oidc expiry will always be old, and the user will never be able to login
@@ -447,13 +453,7 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
         email = credentials.username
 
         # Get tenant_id from mapping table
-        tenant_id = await fetch_ee_implementation_or_noop(
-            "danswer.server.tenants.provisioning",
-            "get_or_create_tenant_id",
-            async_return_default_schema,
-        )(
-            email=email,
-        )
+        tenant_id = get_tenant_id_for_email(email)
         if not tenant_id:
             # User not found in mapping
             self.password_helper.hash(credentials.password)
@@ -474,8 +474,11 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
                 self.password_helper.hash(credentials.password)
                 return None
 
-            if not user.role.is_web_login():
-                raise BasicAuthenticationError(
+            has_web_login = attributes.get_attribute(user, "has_web_login")
+
+            if not has_web_login:
+                raise HTTPException(
+                    status_code=status.HTTP_403_FORBIDDEN,
                     detail="NO_WEB_LOGIN_AND_HAS_NO_PASSWORD",
                 )
 
@@ -507,30 +510,19 @@ cookie_transport = CookieTransport(
 
 # This strategy is used to add tenant_id to the JWT token
 class TenantAwareJWTStrategy(JWTStrategy):
-    async def _create_token_data(self, user: User, impersonate: bool = False) -> dict:
-        tenant_id = await fetch_ee_implementation_or_noop(
-            "danswer.server.tenants.provisioning",
-            "get_or_create_tenant_id",
-            async_return_default_schema,
-        )(
-            email=user.email,
-        )
-
+    async def write_token(self, user: User) -> str:
+        tenant_id = get_tenant_id_for_email(user.email)
         data = {
             "sub": str(user.id),
             "aud": self.token_audience,
             "tenant_id": tenant_id,
         }
-        return data
-
-    async def write_token(self, user: User) -> str:
-        data = await self._create_token_data(user)
         return generate_jwt(
             data, self.encode_key, self.lifetime_seconds, algorithm=self.algorithm
         )
 
 
-def get_jwt_strategy() -> TenantAwareJWTStrategy:
+def get_jwt_strategy() -> JWTStrategy:
     return TenantAwareJWTStrategy(
         secret=USER_AUTH_SECRET,
         lifetime_seconds=SESSION_EXPIRE_TIME_SECONDS,
@@ -605,7 +597,7 @@ optional_fastapi_current_user = fastapi_users.current_user(active=True, optional
 async def optional_user_(
     request: Request,
     user: User | None,
-    async_db_session: AsyncSession,
+    db_session: Session,
 ) -> User | None:
     """NOTE: `request` and `db_session` are not used here, but are included
     for the EE version of this function."""
@@ -614,21 +606,13 @@ async def optional_user_(
 
 async def optional_user(
     request: Request,
-    async_db_session: AsyncSession = Depends(get_async_session),
+    db_session: Session = Depends(get_session),
     user: User | None = Depends(optional_fastapi_current_user),
 ) -> User | None:
     versioned_fetch_user = fetch_versioned_implementation(
         "danswer.auth.users", "optional_user_"
     )
-    user = await versioned_fetch_user(request, user, async_db_session)
-
-    # check if an API key is present
-    if user is None:
-        hashed_api_key = get_hashed_api_key_from_request(request)
-        if hashed_api_key:
-            user = await fetch_user_for_api_key(hashed_api_key, async_db_session)
-
-    return user
+    return await versioned_fetch_user(request, user, db_session)
 
 
 async def double_check_user(
@@ -640,12 +624,14 @@ async def double_check_user(
         return None
 
     if user is None:
-        raise BasicAuthenticationError(
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
             detail="Access denied. User is not authenticated.",
         )
 
     if user_needs_to_be_verified() and not user.is_verified:
-        raise BasicAuthenticationError(
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
             detail="Access denied. User is not verified.",
         )
 
@@ -654,7 +640,8 @@ async def double_check_user(
         and user.oidc_expiry < datetime.now(timezone.utc)
         and not include_expired
     ):
-        raise BasicAuthenticationError(
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
             detail="Access denied. User's OIDC token has expired.",
         )
 
@@ -667,24 +654,10 @@ async def current_user_with_expired_token(
     return await double_check_user(user, include_expired=True)
 
 
-async def current_limited_user(
-    user: User | None = Depends(optional_user),
-) -> User | None:
-    return await double_check_user(user)
-
-
 async def current_user(
     user: User | None = Depends(optional_user),
 ) -> User | None:
-    user = await double_check_user(user)
-    if not user:
-        return None
-
-    if user.role == UserRole.LIMITED:
-        raise BasicAuthenticationError(
-            detail="Access denied. User role is LIMITED. BASIC or higher permissions are required.",
-        )
-    return user
+    return await double_check_user(user)
 
 
 async def current_curator_or_admin_user(
@@ -694,13 +667,15 @@ async def current_curator_or_admin_user(
         return None
 
     if not user or not hasattr(user, "role"):
-        raise BasicAuthenticationError(
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
             detail="Access denied. User is not authenticated or lacks role information.",
         )
 
     allowed_roles = {UserRole.GLOBAL_CURATOR, UserRole.CURATOR, UserRole.ADMIN}
     if user.role not in allowed_roles:
-        raise BasicAuthenticationError(
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
             detail="Access denied. User is not a curator or admin.",
         )
 
@@ -712,7 +687,8 @@ async def current_admin_user(user: User | None = Depends(current_user)) -> User
         return None
 
     if not user or not hasattr(user, "role") or user.role != UserRole.ADMIN:
-        raise BasicAuthenticationError(
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
             detail="Access denied. User must be an admin to perform this action.",
         )
 
@@ -740,6 +716,8 @@ def generate_state_token(
 
 
 # refer to https://github.com/fastapi-users/fastapi-users/blob/42ddc241b965475390e2bce887b084152ae1a2cd/fastapi_users/fastapi_users.py#L91
+
+
 def create_danswer_oauth_router(
     oauth_client: BaseOAuth2,
     backend: AuthenticationBackend,
@@ -789,22 +767,15 @@ def get_oauth_router(
         response_model=OAuth2AuthorizeResponse,
     )
     async def authorize(
-        request: Request,
-        scopes: List[str] = Query(None),
+        request: Request, scopes: List[str] = Query(None)
     ) -> OAuth2AuthorizeResponse:
-        referral_source = request.cookies.get("referral_source", None)
-
         if redirect_url is not None:
             authorize_redirect_url = redirect_url
         else:
             authorize_redirect_url = str(request.url_for(callback_route_name))
 
         next_url = request.query_params.get("next", "/")
-
-        state_data: Dict[str, str] = {
-            "next_url": next_url,
-            "referral_source": referral_source or "default_referral",
-        }
+        state_data: Dict[str, str] = {"next_url": next_url}
         state = generate_state_token(state_data, state_secret)
         authorization_url = await oauth_client.get_authorization_url(
             authorize_redirect_url,
@@ -863,11 +834,8 @@ def get_oauth_router(
             raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST)
 
         next_url = state_data.get("next_url", "/")
-        referral_source = state_data.get("referral_source", None)
 
-        request.state.referral_source = referral_source
-
-        # Proceed to authenticate or create the user
+        # Authenticate user
         try:
             user = await user_manager.oauth_callback(
                 oauth_client.name,
@@ -909,25 +877,7 @@ def get_oauth_router(
             redirect_response.status_code = response.status_code
         if hasattr(response, "media_type"):
             redirect_response.media_type = response.media_type
+
         return redirect_response
 
     return router
-
-
-async def api_key_dep(
-    request: Request, async_db_session: AsyncSession = Depends(get_async_session)
-) -> User | None:
-    if AUTH_TYPE == AuthType.DISABLED:
-        return None
-
-    hashed_api_key = get_hashed_api_key_from_request(request)
-    if not hashed_api_key:
-        raise HTTPException(status_code=401, detail="Missing API key")
-
-    if hashed_api_key:
-        user = await fetch_user_for_api_key(hashed_api_key, async_db_session)
-
-    if user is None:
-        raise HTTPException(status_code=401, detail="Invalid API key")
-
-    return user

backend/danswer/background/celery/apps/app_base.py

@@ -3,7 +3,6 @@ import multiprocessing
 import time
 from typing import Any
 
-import requests
 import sentry_sdk
 from celery import Task
 from celery.app import trace
@@ -11,26 +10,19 @@ from celery.exceptions import WorkerShutdown
 from celery.states import READY_STATES
 from celery.utils.log import get_task_logger
 from celery.worker import strategy  # type: ignore
-from redis.lock import Lock as RedisLock
 from sentry_sdk.integrations.celery import CeleryIntegration
-from sqlalchemy import text
-from sqlalchemy.orm import Session
 
 from danswer.background.celery.apps.task_formatters import CeleryTaskColoredFormatter
 from danswer.background.celery.apps.task_formatters import CeleryTaskPlainFormatter
+from danswer.background.celery.celery_redis import RedisConnectorCredentialPair
+from danswer.background.celery.celery_redis import RedisConnectorDeletion
+from danswer.background.celery.celery_redis import RedisConnectorPruning
+from danswer.background.celery.celery_redis import RedisDocumentSet
+from danswer.background.celery.celery_redis import RedisUserGroup
 from danswer.background.celery.celery_utils import celery_is_worker_primary
 from danswer.configs.constants import DanswerRedisLocks
-from danswer.db.engine import get_sqlalchemy_engine
-from danswer.document_index.vespa_constants import VESPA_CONFIG_SERVER_URL
-from danswer.redis.redis_connector import RedisConnector
-from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
-from danswer.redis.redis_connector_delete import RedisConnectorDelete
-from danswer.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
-from danswer.redis.redis_connector_ext_group_sync import RedisConnectorExternalGroupSync
-from danswer.redis.redis_connector_prune import RedisConnectorPrune
-from danswer.redis.redis_document_set import RedisDocumentSet
+from danswer.db.engine import get_all_tenant_ids
 from danswer.redis.redis_pool import get_redis_client
-from danswer.redis.redis_usergroup import RedisUserGroup
 from danswer.utils.logger import ColoredFormatter
 from danswer.utils.logger import PlainFormatter
 from danswer.utils.logger import setup_logger
@@ -116,43 +108,29 @@ def on_task_postrun(
     if task_id.startswith(RedisDocumentSet.PREFIX):
         document_set_id = RedisDocumentSet.get_id_from_task_id(task_id)
         if document_set_id is not None:
-            rds = RedisDocumentSet(tenant_id, int(document_set_id))
+            rds = RedisDocumentSet(int(document_set_id))
             r.srem(rds.taskset_key, task_id)
         return
 
     if task_id.startswith(RedisUserGroup.PREFIX):
         usergroup_id = RedisUserGroup.get_id_from_task_id(task_id)
         if usergroup_id is not None:
-            rug = RedisUserGroup(tenant_id, int(usergroup_id))
+            rug = RedisUserGroup(int(usergroup_id))
             r.srem(rug.taskset_key, task_id)
         return
 
-    if task_id.startswith(RedisConnectorDelete.PREFIX):
-        cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
+    if task_id.startswith(RedisConnectorDeletion.PREFIX):
+        cc_pair_id = RedisConnectorDeletion.get_id_from_task_id(task_id)
         if cc_pair_id is not None:
-            RedisConnectorDelete.remove_from_taskset(int(cc_pair_id), task_id, r)
+            rcd = RedisConnectorDeletion(int(cc_pair_id))
+            r.srem(rcd.taskset_key, task_id)
         return
 
-    if task_id.startswith(RedisConnectorPrune.SUBTASK_PREFIX):
-        cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
+    if task_id.startswith(RedisConnectorPruning.SUBTASK_PREFIX):
+        cc_pair_id = RedisConnectorPruning.get_id_from_task_id(task_id)
         if cc_pair_id is not None:
-            RedisConnectorPrune.remove_from_taskset(int(cc_pair_id), task_id, r)
-        return
-
-    if task_id.startswith(RedisConnectorPermissionSync.SUBTASK_PREFIX):
-        cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
-        if cc_pair_id is not None:
-            RedisConnectorPermissionSync.remove_from_taskset(
-                int(cc_pair_id), task_id, r
-            )
-        return
-
-    if task_id.startswith(RedisConnectorExternalGroupSync.SUBTASK_PREFIX):
-        cc_pair_id = RedisConnector.get_id_from_task_id(task_id)
-        if cc_pair_id is not None:
-            RedisConnectorExternalGroupSync.remove_from_taskset(
-                int(cc_pair_id), task_id, r
-            )
+            rcp = RedisConnectorPruning(int(cc_pair_id))
+            r.srem(rcp.taskset_key, task_id)
         return
 
 
@@ -162,154 +140,27 @@ def on_celeryd_init(sender: Any = None, conf: Any = None, **kwargs: Any) -> None
 
 
 def wait_for_redis(sender: Any, **kwargs: Any) -> None:
-    """Waits for redis to become ready subject to a hardcoded timeout.
-    Will raise WorkerShutdown to kill the celery worker if the timeout is reached."""
-
     r = get_redis_client(tenant_id=None)
 
     WAIT_INTERVAL = 5
     WAIT_LIMIT = 60
 
-    ready = False
     time_start = time.monotonic()
-    logger.info("Redis: Readiness probe starting.")
+    logger.info("Redis: Readiness check starting.")
     while True:
         try:
             if r.ping():
-                ready = True
                 break
         except Exception:
             pass
 
         time_elapsed = time.monotonic() - time_start
-        if time_elapsed > WAIT_LIMIT:
-            break
-
         logger.info(
-            f"Redis: Readiness probe ongoing. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
-        )
-
-        time.sleep(WAIT_INTERVAL)
-
-    if not ready:
-        msg = (
-            f"Redis: Readiness probe did not succeed within the timeout "
-            f"({WAIT_LIMIT} seconds). Exiting..."
-        )
-        logger.error(msg)
-        raise WorkerShutdown(msg)
-
-    logger.info("Redis: Readiness probe succeeded. Continuing...")
-    return
-
-
-def wait_for_db(sender: Any, **kwargs: Any) -> None:
-    """Waits for the db to become ready subject to a hardcoded timeout.
-    Will raise WorkerShutdown to kill the celery worker if the timeout is reached."""
-
-    WAIT_INTERVAL = 5
-    WAIT_LIMIT = 60
-
-    ready = False
-    time_start = time.monotonic()
-    logger.info("Database: Readiness probe starting.")
-    while True:
-        try:
-            with Session(get_sqlalchemy_engine()) as db_session:
-                result = db_session.execute(text("SELECT NOW()")).scalar()
-                if result:
-                    ready = True
-                    break
-        except Exception:
-            pass
-
-        time_elapsed = time.monotonic() - time_start
-        if time_elapsed > WAIT_LIMIT:
-            break
-
-        logger.info(
-            f"Database: Readiness probe ongoing. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
-        )
-
-        time.sleep(WAIT_INTERVAL)
-
-    if not ready:
-        msg = (
-            f"Database: Readiness probe did not succeed within the timeout "
-            f"({WAIT_LIMIT} seconds). Exiting..."
-        )
-        logger.error(msg)
-        raise WorkerShutdown(msg)
-
-    logger.info("Database: Readiness probe succeeded. Continuing...")
-    return
-
-
-def wait_for_vespa(sender: Any, **kwargs: Any) -> None:
-    """Waits for Vespa to become ready subject to a hardcoded timeout.
-    Will raise WorkerShutdown to kill the celery worker if the timeout is reached."""
-
-    WAIT_INTERVAL = 5
-    WAIT_LIMIT = 60
-
-    ready = False
-    time_start = time.monotonic()
-    logger.info("Vespa: Readiness probe starting.")
-    while True:
-        try:
-            response = requests.get(f"{VESPA_CONFIG_SERVER_URL}/state/v1/health")
-            response.raise_for_status()
-
-            response_dict = response.json()
-            if response_dict["status"]["code"] == "up":
-                ready = True
-                break
-        except Exception:
-            pass
-
-        time_elapsed = time.monotonic() - time_start
-        if time_elapsed > WAIT_LIMIT:
-            break
-
-        logger.info(
-            f"Vespa: Readiness probe ongoing. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
-        )
-
-        time.sleep(WAIT_INTERVAL)
-
-    if not ready:
-        msg = (
-            f"Vespa: Readiness probe did not succeed within the timeout "
-            f"({WAIT_LIMIT} seconds). Exiting..."
-        )
-        logger.error(msg)
-        raise WorkerShutdown(msg)
-
-    logger.info("Vespa: Readiness probe succeeded. Continuing...")
-    return
-
-
-def on_secondary_worker_init(sender: Any, **kwargs: Any) -> None:
-    logger.info("Running as a secondary celery worker.")
-
-    # Set up variables for waiting on primary worker
-    WAIT_INTERVAL = 5
-    WAIT_LIMIT = 60
-    r = get_redis_client(tenant_id=None)
-    time_start = time.monotonic()
-
-    logger.info("Waiting for primary worker to be ready...")
-    while True:
-        if r.exists(DanswerRedisLocks.PRIMARY_WORKER):
-            break
-
-        time_elapsed = time.monotonic() - time_start
-        logger.info(
-            f"Primary worker is not ready yet. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
+            f"Redis: Ping failed. elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
         )
         if time_elapsed > WAIT_LIMIT:
             msg = (
-                f"Primary worker was not ready within the timeout. "
+                f"Redis: Readiness check did not succeed within the timeout "
                 f"({WAIT_LIMIT} seconds). Exiting..."
             )
             logger.error(msg)
@@ -317,7 +168,57 @@ def on_secondary_worker_init(sender: Any, **kwargs: Any) -> None:
 
         time.sleep(WAIT_INTERVAL)
 
-    logger.info("Wait for primary worker completed successfully. Continuing...")
+    logger.info("Redis: Readiness check succeeded. Continuing...")
+    return
+
+
+def on_secondary_worker_init(sender: Any, **kwargs: Any) -> None:
+    WAIT_INTERVAL = 5
+    WAIT_LIMIT = 60
+
+    logger.info("Running as a secondary celery worker.")
+    logger.info("Waiting for all tenant primary workers to be ready...")
+    time_start = time.monotonic()
+
+    while True:
+        tenant_ids = get_all_tenant_ids()
+        # Check if we have a primary worker lock for each tenant
+        all_tenants_ready = all(
+            get_redis_client(tenant_id=tenant_id).exists(
+                DanswerRedisLocks.PRIMARY_WORKER
+            )
+            for tenant_id in tenant_ids
+        )
+
+        if all_tenants_ready:
+            break
+
+        time_elapsed = time.monotonic() - time_start
+        ready_tenants = sum(
+            1
+            for tenant_id in tenant_ids
+            if get_redis_client(tenant_id=tenant_id).exists(
+                DanswerRedisLocks.PRIMARY_WORKER
+            )
+        )
+
+        logger.info(
+            f"Not all tenant primary workers are ready yet. "
+            f"Ready tenants: {ready_tenants}/{len(tenant_ids)} "
+            f"elapsed={time_elapsed:.1f} timeout={WAIT_LIMIT:.1f}"
+        )
+
+        if time_elapsed > WAIT_LIMIT:
+            msg = (
+                f"Not all tenant primary workers were ready within the timeout "
+                f"({WAIT_LIMIT} seconds). Exiting..."
+            )
+            logger.error(msg)
+            raise WorkerShutdown(msg)
+
+        time.sleep(WAIT_INTERVAL)
+
+    logger.info("All tenant primary workers are ready. Continuing...")
     return
 
 
@@ -329,20 +230,26 @@ def on_worker_shutdown(sender: Any, **kwargs: Any) -> None:
     if not celery_is_worker_primary(sender):
         return
 
-    if not sender.primary_worker_lock:
+    if not hasattr(sender, "primary_worker_locks"):
         return
 
-    logger.info("Releasing primary worker lock.")
-    lock: RedisLock = sender.primary_worker_lock
-    try:
-        if lock.owned():
-            try:
-                lock.release()
-                sender.primary_worker_lock = None
-            except Exception:
-                logger.exception("Failed to release primary worker lock")
-    except Exception:
-        logger.exception("Failed to check if primary worker lock is owned")
+    for tenant_id, lock in sender.primary_worker_locks.items():
+        try:
+            if lock and lock.owned():
+                logger.debug(f"Attempting to release lock for tenant {tenant_id}")
+                try:
+                    lock.release()
+                    logger.debug(f"Successfully released lock for tenant {tenant_id}")
+                except Exception as e:
+                    logger.error(
+                        f"Failed to release lock for tenant {tenant_id}. Error: {str(e)}"
+                    )
+                finally:
+                    sender.primary_worker_locks[tenant_id] = None
+        except Exception as e:
+            logger.error(
+                f"Error checking lock status for tenant {tenant_id}. Error: {str(e)}"
+            )
 
 
 def on_setup_logging(

backend/danswer/background/celery/apps/beat.py

@@ -3,162 +3,28 @@ from typing import Any
 
 from celery import Celery
 from celery import signals
-from celery.beat import PersistentScheduler  # type: ignore
 from celery.signals import beat_init
 
 import danswer.background.celery.apps.app_base as app_base
+from danswer.configs.constants import DanswerCeleryPriority
 from danswer.configs.constants import POSTGRES_CELERY_BEAT_APP_NAME
 from danswer.db.engine import get_all_tenant_ids
 from danswer.db.engine import SqlEngine
 from danswer.utils.logger import setup_logger
-from danswer.utils.variable_functionality import fetch_versioned_implementation
-from shared_configs.configs import IGNORED_SYNCING_TENANT_LIST
-from shared_configs.configs import MULTI_TENANT
 
-logger = setup_logger(__name__)
+logger = setup_logger()
 
 celery_app = Celery(__name__)
 celery_app.config_from_object("danswer.background.celery.configs.beat")
 
 
-class DynamicTenantScheduler(PersistentScheduler):
-    def __init__(self, *args: Any, **kwargs: Any) -> None:
-        logger.info("Initializing DynamicTenantScheduler")
-        super().__init__(*args, **kwargs)
-        self._reload_interval = timedelta(minutes=2)
-        self._last_reload = self.app.now() - self._reload_interval
-        # Let the parent class handle store initialization
-        self.setup_schedule()
-        self._update_tenant_tasks()
-        logger.info(f"Set reload interval to {self._reload_interval}")
-
-    def setup_schedule(self) -> None:
-        logger.info("Setting up initial schedule")
-        super().setup_schedule()
-        logger.info("Initial schedule setup complete")
-
-    def tick(self) -> float:
-        retval = super().tick()
-        now = self.app.now()
-        if (
-            self._last_reload is None
-            or (now - self._last_reload) > self._reload_interval
-        ):
-            logger.info("Reload interval reached, initiating tenant task update")
-            self._update_tenant_tasks()
-            self._last_reload = now
-            logger.info("Tenant task update completed, reset reload timer")
-        return retval
-
-    def _update_tenant_tasks(self) -> None:
-        logger.info("Starting tenant task update process")
-        try:
-            logger.info("Fetching all tenant IDs")
-            tenant_ids = get_all_tenant_ids()
-            logger.info(f"Found {len(tenant_ids)} tenants")
-
-            logger.info("Fetching tasks to schedule")
-            tasks_to_schedule = fetch_versioned_implementation(
-                "danswer.background.celery.tasks.beat_schedule", "get_tasks_to_schedule"
-            )
-
-            new_beat_schedule: dict[str, dict[str, Any]] = {}
-
-            current_schedule = self.schedule.items()
-
-            existing_tenants = set()
-            for task_name, _ in current_schedule:
-                if "-" in task_name:
-                    existing_tenants.add(task_name.split("-")[-1])
-            logger.info(f"Found {len(existing_tenants)} existing tenants in schedule")
-
-            for tenant_id in tenant_ids:
-                if (
-                    IGNORED_SYNCING_TENANT_LIST
-                    and tenant_id in IGNORED_SYNCING_TENANT_LIST
-                ):
-                    logger.info(
-                        f"Skipping tenant {tenant_id} as it is in the ignored syncing list"
-                    )
-                    continue
-
-                if tenant_id not in existing_tenants:
-                    logger.info(f"Processing new tenant: {tenant_id}")
-
-                for task in tasks_to_schedule():
-                    task_name = f"{task['name']}-{tenant_id}"
-                    logger.debug(f"Creating task configuration for {task_name}")
-                    new_task = {
-                        "task": task["task"],
-                        "schedule": task["schedule"],
-                        "kwargs": {"tenant_id": tenant_id},
-                    }
-                    if options := task.get("options"):
-                        logger.debug(f"Adding options to task {task_name}: {options}")
-                        new_task["options"] = options
-                    new_beat_schedule[task_name] = new_task
-
-            if self._should_update_schedule(current_schedule, new_beat_schedule):
-                logger.info(
-                    "Schedule update required",
-                    extra={
-                        "new_tasks": len(new_beat_schedule),
-                        "current_tasks": len(current_schedule),
-                    },
-                )
-
-                # Create schedule entries
-                entries = {}
-                for name, entry in new_beat_schedule.items():
-                    entries[name] = self.Entry(
-                        name=name,
-                        app=self.app,
-                        task=entry["task"],
-                        schedule=entry["schedule"],
-                        options=entry.get("options", {}),
-                        kwargs=entry.get("kwargs", {}),
-                    )
-
-                # Update the schedule using the scheduler's methods
-                self.schedule.clear()
-                self.schedule.update(entries)
-
-                # Ensure changes are persisted
-                self.sync()
-
-                logger.info("Schedule update completed successfully")
-            else:
-                logger.info("Schedule is up to date, no changes needed")
-
-        except (AttributeError, KeyError):
-            logger.exception("Failed to process task configuration")
-        except Exception:
-            logger.exception("Unexpected error updating tenant tasks")
-
-    def _should_update_schedule(
-        self, current_schedule: dict, new_schedule: dict
-    ) -> bool:
-        """Compare schedules to determine if an update is needed."""
-        logger.debug("Comparing current and new schedules")
-        current_tasks = set(name for name, _ in current_schedule)
-        new_tasks = set(new_schedule.keys())
-        needs_update = current_tasks != new_tasks
-        logger.debug(f"Schedule update needed: {needs_update}")
-        return needs_update
-
-
 @beat_init.connect
 def on_beat_init(sender: Any, **kwargs: Any) -> None:
     logger.info("beat_init signal received.")
 
-    # Celery beat shouldn't touch the db at all. But just setting a low minimum here.
+    # celery beat shouldn't touch the db at all. But just setting a low minimum here.
     SqlEngine.set_app_name(POSTGRES_CELERY_BEAT_APP_NAME)
     SqlEngine.init_engine(pool_size=2, max_overflow=0)
-
-    # Startup checks are not needed in multi-tenant case
-    if MULTI_TENANT:
-        return
-
     app_base.wait_for_redis(sender, **kwargs)
 
 
@@ -169,4 +35,68 @@ def on_setup_logging(
     app_base.on_setup_logging(loglevel, logfile, format, colorize, **kwargs)
 
 
-celery_app.conf.beat_scheduler = DynamicTenantScheduler
+#####
+# Celery Beat (Periodic Tasks) Settings
+#####
+
+tenant_ids = get_all_tenant_ids()
+
+tasks_to_schedule = [
+    {
+        "name": "check-for-vespa-sync",
+        "task": "check_for_vespa_sync_task",
+        "schedule": timedelta(seconds=5),
+        "options": {"priority": DanswerCeleryPriority.HIGH},
+    },
+    {
+        "name": "check-for-connector-deletion",
+        "task": "check_for_connector_deletion_task",
+        "schedule": timedelta(seconds=60),
+        "options": {"priority": DanswerCeleryPriority.HIGH},
+    },
+    {
+        "name": "check-for-indexing",
+        "task": "check_for_indexing",
+        "schedule": timedelta(seconds=10),
+        "options": {"priority": DanswerCeleryPriority.HIGH},
+    },
+    {
+        "name": "check-for-prune",
+        "task": "check_for_pruning",
+        "schedule": timedelta(seconds=10),
+        "options": {"priority": DanswerCeleryPriority.HIGH},
+    },
+    {
+        "name": "kombu-message-cleanup",
+        "task": "kombu_message_cleanup_task",
+        "schedule": timedelta(seconds=3600),
+        "options": {"priority": DanswerCeleryPriority.LOWEST},
+    },
+    {
+        "name": "monitor-vespa-sync",
+        "task": "monitor_vespa_sync",
+        "schedule": timedelta(seconds=5),
+        "options": {"priority": DanswerCeleryPriority.HIGH},
+    },
+]
+
+
+# Build the celery beat schedule dynamically
+beat_schedule = {}
+
+for tenant_id in tenant_ids:
+    for task in tasks_to_schedule:
+        task_name = f"{task['name']}-{tenant_id}"  # Unique name for each scheduled task
+        beat_schedule[task_name] = {
+            "task": task["task"],
+            "schedule": task["schedule"],
+            "options": task["options"],
+            "kwargs": {"tenant_id": tenant_id},  # Must pass tenant_id as an argument
+        }
+
+# Include any existing beat schedules
+existing_beat_schedule = celery_app.conf.beat_schedule or {}
+beat_schedule.update(existing_beat_schedule)
+
+# Update the Celery app configuration once
+celery_app.conf.beat_schedule = beat_schedule

backend/danswer/background/celery/apps/heavy.py

@@ -13,7 +13,6 @@ import danswer.background.celery.apps.app_base as app_base
 from danswer.configs.constants import POSTGRES_CELERY_WORKER_HEAVY_APP_NAME
 from danswer.db.engine import SqlEngine
 from danswer.utils.logger import setup_logger
-from shared_configs.configs import MULTI_TENANT
 
 
 logger = setup_logger()
@@ -61,13 +60,7 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
     SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_HEAVY_APP_NAME)
     SqlEngine.init_engine(pool_size=4, max_overflow=12)
 
-    # Startup checks are not needed in multi-tenant case
-    if MULTI_TENANT:
-        return
-
     app_base.wait_for_redis(sender, **kwargs)
-    app_base.wait_for_db(sender, **kwargs)
-    app_base.wait_for_vespa(sender, **kwargs)
     app_base.on_secondary_worker_init(sender, **kwargs)
 
 
@@ -91,7 +84,5 @@ def on_setup_logging(
 celery_app.autodiscover_tasks(
     [
         "danswer.background.celery.tasks.pruning",
-        "danswer.background.celery.tasks.doc_permission_syncing",
-        "danswer.background.celery.tasks.external_group_syncing",
     ]
 )

backend/danswer/background/celery/apps/indexing.py

@@ -6,7 +6,6 @@ from celery import signals
 from celery import Task
 from celery.signals import celeryd_init
 from celery.signals import worker_init
-from celery.signals import worker_process_init
 from celery.signals import worker_ready
 from celery.signals import worker_shutdown
 
@@ -14,7 +13,6 @@ import danswer.background.celery.apps.app_base as app_base
 from danswer.configs.constants import POSTGRES_CELERY_WORKER_INDEXING_APP_NAME
 from danswer.db.engine import SqlEngine
 from danswer.utils.logger import setup_logger
-from shared_configs.configs import MULTI_TENANT
 
 
 logger = setup_logger()
@@ -60,15 +58,9 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
     logger.info(f"Multiprocessing start method: {multiprocessing.get_start_method()}")
 
     SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_INDEXING_APP_NAME)
-    SqlEngine.init_engine(pool_size=sender.concurrency, max_overflow=sender.concurrency)
-
-    # Startup checks are not needed in multi-tenant case
-    if MULTI_TENANT:
-        return
+    SqlEngine.init_engine(pool_size=8, max_overflow=0)
 
     app_base.wait_for_redis(sender, **kwargs)
-    app_base.wait_for_db(sender, **kwargs)
-    app_base.wait_for_vespa(sender, **kwargs)
     app_base.on_secondary_worker_init(sender, **kwargs)
 
 
@@ -82,11 +74,6 @@ def on_worker_shutdown(sender: Any, **kwargs: Any) -> None:
     app_base.on_worker_shutdown(sender, **kwargs)
 
 
-@worker_process_init.connect
-def init_worker(**kwargs: Any) -> None:
-    SqlEngine.reset_engine()
-
-
 @signals.setup_logging.connect
 def on_setup_logging(
     loglevel: Any, logfile: Any, format: Any, colorize: Any, **kwargs: Any

backend/danswer/background/celery/apps/light.py

@@ -13,7 +13,6 @@ import danswer.background.celery.apps.app_base as app_base
 from danswer.configs.constants import POSTGRES_CELERY_WORKER_LIGHT_APP_NAME
 from danswer.db.engine import SqlEngine
 from danswer.utils.logger import setup_logger
-from shared_configs.configs import MULTI_TENANT
 
 
 logger = setup_logger()
@@ -60,13 +59,8 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
 
     SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_LIGHT_APP_NAME)
     SqlEngine.init_engine(pool_size=sender.concurrency, max_overflow=8)
-    # Startup checks are not needed in multi-tenant case
-    if MULTI_TENANT:
-        return
 
     app_base.wait_for_redis(sender, **kwargs)
-    app_base.wait_for_db(sender, **kwargs)
-    app_base.wait_for_vespa(sender, **kwargs)
     app_base.on_secondary_worker_init(sender, **kwargs)
 
 
@@ -91,7 +85,5 @@ celery_app.autodiscover_tasks(
     [
         "danswer.background.celery.tasks.shared",
         "danswer.background.celery.tasks.vespa",
-        "danswer.background.celery.tasks.connector_deletion",
-        "danswer.background.celery.tasks.doc_permission_syncing",
     ]
 )

backend/danswer/background/celery/apps/primary.py

@@ -1,6 +1,5 @@
 import multiprocessing
 from typing import Any
-from typing import cast
 
 from celery import bootsteps  # type: ignore
 from celery import Celery
@@ -11,33 +10,25 @@ from celery.signals import celeryd_init
 from celery.signals import worker_init
 from celery.signals import worker_ready
 from celery.signals import worker_shutdown
-from redis.lock import Lock as RedisLock
 
 import danswer.background.celery.apps.app_base as app_base
 from danswer.background.celery.apps.app_base import task_logger
+from danswer.background.celery.celery_redis import RedisConnectorCredentialPair
+from danswer.background.celery.celery_redis import RedisConnectorDeletion
+from danswer.background.celery.celery_redis import RedisConnectorIndexing
+from danswer.background.celery.celery_redis import RedisConnectorPruning
+from danswer.background.celery.celery_redis import RedisConnectorStop
+from danswer.background.celery.celery_redis import RedisDocumentSet
+from danswer.background.celery.celery_redis import RedisUserGroup
 from danswer.background.celery.celery_utils import celery_is_worker_primary
-from danswer.background.celery.tasks.indexing.tasks import (
-    get_unfenced_index_attempt_ids,
-)
 from danswer.configs.constants import CELERY_PRIMARY_WORKER_LOCK_TIMEOUT
 from danswer.configs.constants import DanswerRedisLocks
 from danswer.configs.constants import POSTGRES_CELERY_WORKER_PRIMARY_APP_NAME
-from danswer.db.engine import get_session_with_default_tenant
+from danswer.db.engine import get_all_tenant_ids
 from danswer.db.engine import SqlEngine
-from danswer.db.index_attempt import get_index_attempt
-from danswer.db.index_attempt import mark_attempt_canceled
-from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
-from danswer.redis.redis_connector_delete import RedisConnectorDelete
-from danswer.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
-from danswer.redis.redis_connector_ext_group_sync import RedisConnectorExternalGroupSync
-from danswer.redis.redis_connector_index import RedisConnectorIndex
-from danswer.redis.redis_connector_prune import RedisConnectorPrune
-from danswer.redis.redis_connector_stop import RedisConnectorStop
-from danswer.redis.redis_document_set import RedisDocumentSet
 from danswer.redis.redis_pool import get_redis_client
-from danswer.redis.redis_usergroup import RedisUserGroup
 from danswer.utils.logger import setup_logger
-from shared_configs.configs import MULTI_TENANT
+
 
 logger = setup_logger()
 
@@ -84,98 +75,95 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
     SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_PRIMARY_APP_NAME)
     SqlEngine.init_engine(pool_size=8, max_overflow=0)
 
-    # Startup checks are not needed in multi-tenant case
-    if MULTI_TENANT:
-        return
-
     app_base.wait_for_redis(sender, **kwargs)
-    app_base.wait_for_db(sender, **kwargs)
-    app_base.wait_for_vespa(sender, **kwargs)
 
     logger.info("Running as the primary celery worker.")
 
+    sender.primary_worker_locks = {}
+
     # This is singleton work that should be done on startup exactly once
-    # by the primary worker. This is unnecessary in the multi tenant scenario
-    r = get_redis_client(tenant_id=None)
+    # by the primary worker
+    tenant_ids = get_all_tenant_ids()
+    for tenant_id in tenant_ids:
+        r = get_redis_client(tenant_id=tenant_id)
 
-    # Log the role and slave count - being connected to a slave or slave count > 0 could be problematic
-    info: dict[str, Any] = cast(dict, r.info("replication"))
-    role: str = cast(str, info.get("role"))
-    connected_slaves: int = info.get("connected_slaves", 0)
+        # For the moment, we're assuming that we are the only primary worker
+        # that should be running.
+        # TODO: maybe check for or clean up another zombie primary worker if we detect it
+        r.delete(DanswerRedisLocks.PRIMARY_WORKER)
 
-    logger.info(
-        f"Redis INFO REPLICATION: role={role} connected_slaves={connected_slaves}"
-    )
+        # this process wide lock is taken to help other workers start up in order.
+        # it is planned to use this lock to enforce singleton behavior on the primary
+        # worker, since the primary worker does redis cleanup on startup, but this isn't
+        # implemented yet.
+        lock = r.lock(
+            DanswerRedisLocks.PRIMARY_WORKER,
+            timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
+        )
 
-    # For the moment, we're assuming that we are the only primary worker
-    # that should be running.
-    # TODO: maybe check for or clean up another zombie primary worker if we detect it
-    r.delete(DanswerRedisLocks.PRIMARY_WORKER)
+        logger.info("Primary worker lock: Acquire starting.")
+        acquired = lock.acquire(blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2)
+        if acquired:
+            logger.info("Primary worker lock: Acquire succeeded.")
+        else:
+            logger.error("Primary worker lock: Acquire failed!")
+            raise WorkerShutdown("Primary worker lock could not be acquired!")
 
-    # this process wide lock is taken to help other workers start up in order.
-    # it is planned to use this lock to enforce singleton behavior on the primary
-    # worker, since the primary worker does redis cleanup on startup, but this isn't
-    # implemented yet.
+        # tacking on our own user data to the sender
+        sender.primary_worker_locks[tenant_id] = lock
 
-    # set thread_local=False since we don't control what thread the periodic task might
-    # reacquire the lock with
-    lock: RedisLock = r.lock(
-        DanswerRedisLocks.PRIMARY_WORKER,
-        timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
-        thread_local=False,
-    )
+        # As currently designed, when this worker starts as "primary", we reinitialize redis
+        # to a clean state (for our purposes, anyway)
+        r.delete(DanswerRedisLocks.CHECK_VESPA_SYNC_BEAT_LOCK)
+        r.delete(DanswerRedisLocks.MONITOR_VESPA_SYNC_BEAT_LOCK)
 
-    logger.info("Primary worker lock: Acquire starting.")
-    acquired = lock.acquire(blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2)
-    if acquired:
-        logger.info("Primary worker lock: Acquire succeeded.")
-    else:
-        logger.error("Primary worker lock: Acquire failed!")
-        raise WorkerShutdown("Primary worker lock could not be acquired!")
+        r.delete(RedisConnectorCredentialPair.get_taskset_key())
+        r.delete(RedisConnectorCredentialPair.get_fence_key())
 
-    # tacking on our own user data to the sender
-    sender.primary_worker_lock = lock
+        for key in r.scan_iter(RedisDocumentSet.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    # As currently designed, when this worker starts as "primary", we reinitialize redis
-    # to a clean state (for our purposes, anyway)
-    r.delete(DanswerRedisLocks.CHECK_VESPA_SYNC_BEAT_LOCK)
-    r.delete(DanswerRedisLocks.MONITOR_VESPA_SYNC_BEAT_LOCK)
+        for key in r.scan_iter(RedisDocumentSet.FENCE_PREFIX + "*"):
+            r.delete(key)
 
-    r.delete(RedisConnectorCredentialPair.get_taskset_key())
-    r.delete(RedisConnectorCredentialPair.get_fence_key())
+        for key in r.scan_iter(RedisUserGroup.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    RedisDocumentSet.reset_all(r)
+        for key in r.scan_iter(RedisUserGroup.FENCE_PREFIX + "*"):
+            r.delete(key)
 
-    RedisUserGroup.reset_all(r)
+        for key in r.scan_iter(RedisConnectorDeletion.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorDelete.reset_all(r)
+        for key in r.scan_iter(RedisConnectorDeletion.FENCE_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorPrune.reset_all(r)
+        for key in r.scan_iter(RedisConnectorPruning.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorIndex.reset_all(r)
+        for key in r.scan_iter(RedisConnectorPruning.GENERATOR_COMPLETE_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorStop.reset_all(r)
+        for key in r.scan_iter(RedisConnectorPruning.GENERATOR_PROGRESS_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorPermissionSync.reset_all(r)
+        for key in r.scan_iter(RedisConnectorPruning.FENCE_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorExternalGroupSync.reset_all(r)
+        for key in r.scan_iter(RedisConnectorIndexing.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    # mark orphaned index attempts as failed
-    with get_session_with_default_tenant() as db_session:
-        unfenced_attempt_ids = get_unfenced_index_attempt_ids(db_session, r)
-        for attempt_id in unfenced_attempt_ids:
-            attempt = get_index_attempt(db_session, attempt_id)
-            if not attempt:
-                continue
+        for key in r.scan_iter(RedisConnectorIndexing.GENERATOR_COMPLETE_PREFIX + "*"):
+            r.delete(key)
 
-            failure_reason = (
-                f"Canceling leftover index attempt found on startup: "
-                f"index_attempt={attempt.id} "
-                f"cc_pair={attempt.connector_credential_pair_id} "
-                f"search_settings={attempt.search_settings_id}"
-            )
-            logger.warning(failure_reason)
-            mark_attempt_canceled(attempt.id, db_session, failure_reason)
+        for key in r.scan_iter(RedisConnectorIndexing.GENERATOR_PROGRESS_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorIndexing.FENCE_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorStop.FENCE_PREFIX + "*"):
+            r.delete(key)
 
 
 @worker_ready.connect
@@ -228,36 +216,52 @@ class HubPeriodicTask(bootsteps.StartStopStep):
             if not celery_is_worker_primary(worker):
                 return
 
-            if not hasattr(worker, "primary_worker_lock"):
+            if not hasattr(worker, "primary_worker_locks"):
                 return
 
-            lock: RedisLock = worker.primary_worker_lock
+            # Retrieve all tenant IDs
+            tenant_ids = get_all_tenant_ids()
 
-            r = get_redis_client(tenant_id=None)
+            for tenant_id in tenant_ids:
+                lock = worker.primary_worker_locks.get(tenant_id)
+                if not lock:
+                    continue  # Skip if no lock for this tenant
 
-            if lock.owned():
-                task_logger.debug("Reacquiring primary worker lock.")
-                lock.reacquire()
-            else:
-                task_logger.warning(
-                    "Full acquisition of primary worker lock. "
-                    "Reasons could be worker restart or lock expiration."
-                )
-                lock = r.lock(
-                    DanswerRedisLocks.PRIMARY_WORKER,
-                    timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
-                )
+                r = get_redis_client(tenant_id=tenant_id)
 
-                task_logger.info("Primary worker lock: Acquire starting.")
-                acquired = lock.acquire(
-                    blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2
-                )
-                if acquired:
-                    task_logger.info("Primary worker lock: Acquire succeeded.")
-                    worker.primary_worker_lock = lock
+                if lock.owned():
+                    task_logger.debug(
+                        f"Reacquiring primary worker lock for tenant {tenant_id}."
+                    )
+                    lock.reacquire()
                 else:
-                    task_logger.error("Primary worker lock: Acquire failed!")
-                    raise TimeoutError("Primary worker lock could not be acquired!")
+                    task_logger.warning(
+                        f"Full acquisition of primary worker lock for tenant {tenant_id}. "
+                        "Reasons could be worker restart or lock expiration."
+                    )
+                    lock = r.lock(
+                        DanswerRedisLocks.PRIMARY_WORKER,
+                        timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT,
+                    )
+
+                    task_logger.info(
+                        f"Primary worker lock for tenant {tenant_id}: Acquire starting."
+                    )
+                    acquired = lock.acquire(
+                        blocking_timeout=CELERY_PRIMARY_WORKER_LOCK_TIMEOUT / 2
+                    )
+                    if acquired:
+                        task_logger.info(
+                            f"Primary worker lock for tenant {tenant_id}: Acquire succeeded."
+                        )
+                        worker.primary_worker_locks[tenant_id] = lock
+                    else:
+                        task_logger.error(
+                            f"Primary worker lock for tenant {tenant_id}: Acquire failed!"
+                        )
+                        raise TimeoutError(
+                            f"Primary worker lock for tenant {tenant_id} could not be acquired!"
+                        )
 
         except Exception:
             task_logger.exception("Periodic task failed.")
@@ -276,8 +280,6 @@ celery_app.autodiscover_tasks(
         "danswer.background.celery.tasks.connector_deletion",
         "danswer.background.celery.tasks.indexing",
         "danswer.background.celery.tasks.periodic",
-        "danswer.background.celery.tasks.doc_permission_syncing",
-        "danswer.background.celery.tasks.external_group_syncing",
         "danswer.background.celery.tasks.pruning",
         "danswer.background.celery.tasks.shared",
         "danswer.background.celery.tasks.vespa",

backend/danswer/background/celery/celery_redis.py

@@ -1,10 +1,568 @@
 # These are helper objects for tracking the keys we need to write in redis
+import time
+from abc import ABC
+from abc import abstractmethod
 from typing import cast
+from uuid import uuid4
 
+import redis
+from celery import Celery
 from redis import Redis
+from sqlalchemy.orm import Session
 
 from danswer.background.celery.configs.base import CELERY_SEPARATOR
+from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
 from danswer.configs.constants import DanswerCeleryPriority
+from danswer.configs.constants import DanswerCeleryQueues
+from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
+from danswer.db.document import construct_document_select_for_connector_credential_pair
+from danswer.db.document import (
+    construct_document_select_for_connector_credential_pair_by_needs_sync,
+)
+from danswer.db.document_set import construct_document_select_by_docset
+from danswer.utils.variable_functionality import fetch_versioned_implementation
+from danswer.utils.variable_functionality import global_version
+
+
+class RedisObjectHelper(ABC):
+    PREFIX = "base"
+    FENCE_PREFIX = PREFIX + "_fence"
+    TASKSET_PREFIX = PREFIX + "_taskset"
+
+    def __init__(self, id: str):
+        self._id: str = id
+
+    @property
+    def task_id_prefix(self) -> str:
+        return f"{self.PREFIX}_{self._id}"
+
+    @property
+    def fence_key(self) -> str:
+        # example: documentset_fence_1
+        return f"{self.FENCE_PREFIX}_{self._id}"
+
+    @property
+    def taskset_key(self) -> str:
+        # example: documentset_taskset_1
+        return f"{self.TASKSET_PREFIX}_{self._id}"
+
+    @staticmethod
+    def get_id_from_fence_key(key: str) -> str | None:
+        """
+        Extracts the object ID from a fence key in the format `PREFIX_fence_X`.
+
+        Args:
+            key (str): The fence key string.
+
+        Returns:
+            Optional[int]: The extracted ID if the key is in the correct format, otherwise None.
+        """
+        parts = key.split("_")
+        if len(parts) != 3:
+            return None
+
+        object_id = parts[2]
+        return object_id
+
+    @staticmethod
+    def get_id_from_task_id(task_id: str) -> str | None:
+        """
+        Extracts the object ID from a task ID string.
+
+        This method assumes the task ID is formatted as `prefix_objectid_suffix`, where:
+        - `prefix` is an arbitrary string (e.g., the name of the task or entity),
+        - `objectid` is the ID you want to extract,
+        - `suffix` is another arbitrary string (e.g., a UUID).
+
+        Example:
+            If the input `task_id` is `documentset_1_cbfdc96a-80ca-4312-a242-0bb68da3c1dc`,
+            this method will return the string `"1"`.
+
+        Args:
+            task_id (str): The task ID string from which to extract the object ID.
+
+        Returns:
+            str | None: The extracted object ID if the task ID is in the correct format, otherwise None.
+        """
+        # example: task_id=documentset_1_cbfdc96a-80ca-4312-a242-0bb68da3c1dc
+        parts = task_id.split("_")
+        if len(parts) != 3:
+            return None
+
+        object_id = parts[1]
+        return object_id
+
+    @abstractmethod
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock,
+        tenant_id: str | None,
+    ) -> int | None:
+        pass
+
+
+class RedisDocumentSet(RedisObjectHelper):
+    PREFIX = "documentset"
+    FENCE_PREFIX = PREFIX + "_fence"
+    TASKSET_PREFIX = PREFIX + "_taskset"
+
+    def __init__(self, id: int) -> None:
+        super().__init__(str(id))
+
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock,
+        tenant_id: str | None,
+    ) -> int | None:
+        last_lock_time = time.monotonic()
+
+        async_results = []
+        stmt = construct_document_select_by_docset(int(self._id), current_only=False)
+        for doc in db_session.scalars(stmt).yield_per(1):
+            current_time = time.monotonic()
+            if current_time - last_lock_time >= (
+                CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
+            ):
+                lock.reacquire()
+                last_lock_time = current_time
+
+            # celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # the key for the result is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # we prefix the task id so it's easier to keep track of who created the task
+            # aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
+
+            # add to the set BEFORE creating the task.
+            redis_client.sadd(self.taskset_key, custom_task_id)
+
+            result = celery_app.send_task(
+                "vespa_metadata_sync_task",
+                kwargs=dict(document_id=doc.id, tenant_id=tenant_id),
+                queue=DanswerCeleryQueues.VESPA_METADATA_SYNC,
+                task_id=custom_task_id,
+                priority=DanswerCeleryPriority.LOW,
+            )
+
+            async_results.append(result)
+
+        return len(async_results)
+
+
+class RedisUserGroup(RedisObjectHelper):
+    PREFIX = "usergroup"
+    FENCE_PREFIX = PREFIX + "_fence"
+    TASKSET_PREFIX = PREFIX + "_taskset"
+
+    def __init__(self, id: int) -> None:
+        super().__init__(str(id))
+
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock,
+        tenant_id: str | None,
+    ) -> int | None:
+        last_lock_time = time.monotonic()
+
+        async_results = []
+
+        if not global_version.is_ee_version():
+            return 0
+
+        try:
+            construct_document_select_by_usergroup = fetch_versioned_implementation(
+                "danswer.db.user_group",
+                "construct_document_select_by_usergroup",
+            )
+        except ModuleNotFoundError:
+            return 0
+
+        stmt = construct_document_select_by_usergroup(int(self._id))
+        for doc in db_session.scalars(stmt).yield_per(1):
+            current_time = time.monotonic()
+            if current_time - last_lock_time >= (
+                CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
+            ):
+                lock.reacquire()
+                last_lock_time = current_time
+
+            # celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # the key for the result is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # we prefix the task id so it's easier to keep track of who created the task
+            # aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
+
+            # add to the set BEFORE creating the task.
+            redis_client.sadd(self.taskset_key, custom_task_id)
+
+            result = celery_app.send_task(
+                "vespa_metadata_sync_task",
+                kwargs=dict(document_id=doc.id, tenant_id=tenant_id),
+                queue=DanswerCeleryQueues.VESPA_METADATA_SYNC,
+                task_id=custom_task_id,
+                priority=DanswerCeleryPriority.LOW,
+            )
+
+            async_results.append(result)
+
+        return len(async_results)
+
+
+class RedisConnectorCredentialPair(RedisObjectHelper):
+    """This class is used to scan documents by cc_pair in the db and collect them into
+    a unified set for syncing.
+
+    It differs from the other redis helpers in that the taskset used spans
+    all connectors and is not per connector."""
+
+    PREFIX = "connectorsync"
+    FENCE_PREFIX = PREFIX + "_fence"
+    TASKSET_PREFIX = PREFIX + "_taskset"
+
+    def __init__(self, id: int) -> None:
+        super().__init__(str(id))
+
+    @classmethod
+    def get_fence_key(cls) -> str:
+        return RedisConnectorCredentialPair.FENCE_PREFIX
+
+    @classmethod
+    def get_taskset_key(cls) -> str:
+        return RedisConnectorCredentialPair.TASKSET_PREFIX
+
+    @property
+    def taskset_key(self) -> str:
+        """Notice that this is intentionally reusing the same taskset for all
+        connector syncs"""
+        # example: connector_taskset
+        return f"{self.TASKSET_PREFIX}"
+
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock,
+        tenant_id: str | None,
+    ) -> int | None:
+        last_lock_time = time.monotonic()
+
+        async_results = []
+        cc_pair = get_connector_credential_pair_from_id(int(self._id), db_session)
+        if not cc_pair:
+            return None
+
+        stmt = construct_document_select_for_connector_credential_pair_by_needs_sync(
+            cc_pair.connector_id, cc_pair.credential_id
+        )
+        for doc in db_session.scalars(stmt).yield_per(1):
+            current_time = time.monotonic()
+            if current_time - last_lock_time >= (
+                CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
+            ):
+                lock.reacquire()
+                last_lock_time = current_time
+
+            # celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # the key for the result is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # we prefix the task id so it's easier to keep track of who created the task
+            # aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
+
+            # add to the tracking taskset in redis BEFORE creating the celery task.
+            # note that for the moment we are using a single taskset key, not differentiated by cc_pair id
+            redis_client.sadd(
+                RedisConnectorCredentialPair.get_taskset_key(), custom_task_id
+            )
+
+            # Priority on sync's triggered by new indexing should be medium
+            result = celery_app.send_task(
+                "vespa_metadata_sync_task",
+                kwargs=dict(document_id=doc.id, tenant_id=tenant_id),
+                queue=DanswerCeleryQueues.VESPA_METADATA_SYNC,
+                task_id=custom_task_id,
+                priority=DanswerCeleryPriority.MEDIUM,
+            )
+
+            async_results.append(result)
+
+        return len(async_results)
+
+
+class RedisConnectorDeletion(RedisObjectHelper):
+    PREFIX = "connectordeletion"
+    FENCE_PREFIX = PREFIX + "_fence"
+    TASKSET_PREFIX = PREFIX + "_taskset"
+
+    def __init__(self, id: int) -> None:
+        super().__init__(str(id))
+
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock,
+        tenant_id: str | None,
+    ) -> int | None:
+        """Returns None if the cc_pair doesn't exist.
+        Otherwise, returns an int with the number of generated tasks."""
+        last_lock_time = time.monotonic()
+
+        async_results = []
+        cc_pair = get_connector_credential_pair_from_id(int(self._id), db_session)
+        if not cc_pair:
+            return None
+
+        stmt = construct_document_select_for_connector_credential_pair(
+            cc_pair.connector_id, cc_pair.credential_id
+        )
+        for doc in db_session.scalars(stmt).yield_per(1):
+            current_time = time.monotonic()
+            if current_time - last_lock_time >= (
+                CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
+            ):
+                lock.reacquire()
+                last_lock_time = current_time
+
+            # celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # the actual redis key is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # we prefix the task id so it's easier to keep track of who created the task
+            # aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            custom_task_id = f"{self.task_id_prefix}_{uuid4()}"
+
+            # add to the tracking taskset in redis BEFORE creating the celery task.
+            # note that for the moment we are using a single taskset key, not differentiated by cc_pair id
+            redis_client.sadd(self.taskset_key, custom_task_id)
+
+            # Priority on sync's triggered by new indexing should be medium
+            result = celery_app.send_task(
+                "document_by_cc_pair_cleanup_task",
+                kwargs=dict(
+                    document_id=doc.id,
+                    connector_id=cc_pair.connector_id,
+                    credential_id=cc_pair.credential_id,
+                    tenant_id=tenant_id,
+                ),
+                queue=DanswerCeleryQueues.CONNECTOR_DELETION,
+                task_id=custom_task_id,
+                priority=DanswerCeleryPriority.MEDIUM,
+            )
+
+            async_results.append(result)
+
+        return len(async_results)
+
+
+class RedisConnectorPruning(RedisObjectHelper):
+    """Celery will kick off a long running generator task to crawl the connector and
+    find any missing docs, which will each then get a new cleanup task. The progress of
+    those tasks will then be monitored to completion.
+
+    Example rough happy path order:
+    Check connectorpruning_fence_1
+    Send generator task with id connectorpruning+generator_1_{uuid}
+
+    generator runs connector with callbacks that increment connectorpruning_generator_progress_1
+    generator creates many subtasks with id connectorpruning+sub_1_{uuid}
+      in taskset connectorpruning_taskset_1
+    on completion, generator sets connectorpruning_generator_complete_1
+
+    celery postrun removes subtasks from taskset
+    monitor beat task cleans up when taskset reaches 0 items
+    """
+
+    PREFIX = "connectorpruning"
+    FENCE_PREFIX = PREFIX + "_fence"  # a fence for the entire pruning process
+    GENERATOR_TASK_PREFIX = PREFIX + "+generator"
+
+    TASKSET_PREFIX = PREFIX + "_taskset"  # stores a list of prune tasks id's
+    SUBTASK_PREFIX = PREFIX + "+sub"
+
+    GENERATOR_PROGRESS_PREFIX = (
+        PREFIX + "_generator_progress"
+    )  # a signal that contains generator progress
+    GENERATOR_COMPLETE_PREFIX = (
+        PREFIX + "_generator_complete"
+    )  # a signal that the generator has finished
+
+    def __init__(self, id: int) -> None:
+        super().__init__(str(id))
+        self.documents_to_prune: set[str] = set()
+
+    @property
+    def generator_task_id_prefix(self) -> str:
+        return f"{self.GENERATOR_TASK_PREFIX}_{self._id}"
+
+    @property
+    def generator_progress_key(self) -> str:
+        # example: connectorpruning_generator_progress_1
+        return f"{self.GENERATOR_PROGRESS_PREFIX}_{self._id}"
+
+    @property
+    def generator_complete_key(self) -> str:
+        # example: connectorpruning_generator_complete_1
+        return f"{self.GENERATOR_COMPLETE_PREFIX}_{self._id}"
+
+    @property
+    def subtask_id_prefix(self) -> str:
+        return f"{self.SUBTASK_PREFIX}_{self._id}"
+
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock | None,
+        tenant_id: str | None,
+    ) -> int | None:
+        last_lock_time = time.monotonic()
+
+        async_results = []
+        cc_pair = get_connector_credential_pair_from_id(int(self._id), db_session)
+        if not cc_pair:
+            return None
+
+        for doc_id in self.documents_to_prune:
+            current_time = time.monotonic()
+            if lock and current_time - last_lock_time >= (
+                CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT / 4
+            ):
+                lock.reacquire()
+                last_lock_time = current_time
+
+            # celery's default task id format is "dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # the actual redis key is "celery-task-meta-dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            # we prefix the task id so it's easier to keep track of who created the task
+            # aka "documentset_1_6dd32ded3-00aa-4884-8b21-42f8332e7fac"
+            custom_task_id = f"{self.subtask_id_prefix}_{uuid4()}"
+
+            # add to the tracking taskset in redis BEFORE creating the celery task.
+            # note that for the moment we are using a single taskset key, not differentiated by cc_pair id
+            redis_client.sadd(self.taskset_key, custom_task_id)
+
+            # Priority on sync's triggered by new indexing should be medium
+            result = celery_app.send_task(
+                "document_by_cc_pair_cleanup_task",
+                kwargs=dict(
+                    document_id=doc_id,
+                    connector_id=cc_pair.connector_id,
+                    credential_id=cc_pair.credential_id,
+                    tenant_id=tenant_id,
+                ),
+                queue=DanswerCeleryQueues.CONNECTOR_DELETION,
+                task_id=custom_task_id,
+                priority=DanswerCeleryPriority.MEDIUM,
+            )
+
+            async_results.append(result)
+
+        return len(async_results)
+
+    def is_pruning(self, redis_client: Redis) -> bool:
+        """A single example of a helper method being refactored into the redis helper"""
+        if redis_client.exists(self.fence_key):
+            return True
+
+        return False
+
+
+class RedisConnectorIndexing(RedisObjectHelper):
+    """Celery will kick off a long running indexing task to crawl the connector and
+    find any new or updated docs docs, which will each then get a new sync task or be
+    indexed inline.
+
+    ID should be a concatenation of cc_pair_id and search_setting_id, delimited by "/".
+    e.g. "2/5"
+    """
+
+    PREFIX = "connectorindexing"
+    FENCE_PREFIX = PREFIX + "_fence"  # a fence for the entire indexing process
+    GENERATOR_TASK_PREFIX = PREFIX + "+generator"
+
+    TASKSET_PREFIX = PREFIX + "_taskset"  # stores a list of prune tasks id's
+    SUBTASK_PREFIX = PREFIX + "+sub"
+
+    GENERATOR_LOCK_PREFIX = "da_lock:indexing"
+    GENERATOR_PROGRESS_PREFIX = (
+        PREFIX + "_generator_progress"
+    )  # a signal that contains generator progress
+    GENERATOR_COMPLETE_PREFIX = (
+        PREFIX + "_generator_complete"
+    )  # a signal that the generator has finished
+
+    def __init__(self, cc_pair_id: int, search_settings_id: int) -> None:
+        super().__init__(f"{cc_pair_id}/{search_settings_id}")
+
+    @property
+    def generator_lock_key(self) -> str:
+        return f"{self.GENERATOR_LOCK_PREFIX}_{self._id}"
+
+    @property
+    def generator_task_id_prefix(self) -> str:
+        return f"{self.GENERATOR_TASK_PREFIX}_{self._id}"
+
+    @property
+    def generator_progress_key(self) -> str:
+        # example: connectorpruning_generator_progress_1
+        return f"{self.GENERATOR_PROGRESS_PREFIX}_{self._id}"
+
+    @property
+    def generator_complete_key(self) -> str:
+        # example: connectorpruning_generator_complete_1
+        return f"{self.GENERATOR_COMPLETE_PREFIX}_{self._id}"
+
+    @property
+    def subtask_id_prefix(self) -> str:
+        return f"{self.SUBTASK_PREFIX}_{self._id}"
+
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock | None,
+        tenant_id: str | None,
+    ) -> int | None:
+        return None
+
+    def is_indexing(self, redis_client: Redis) -> bool:
+        """A single example of a helper method being refactored into the redis helper"""
+        if redis_client.exists(self.fence_key):
+            return True
+
+        return False
+
+
+class RedisConnectorStop(RedisObjectHelper):
+    """Used to signal any running tasks for a connector to stop. We should refactor
+    connector related redis helpers into a single class.
+    """
+
+    PREFIX = "connectorstop"
+    FENCE_PREFIX = PREFIX + "_fence"  # a fence for the entire indexing process
+    TASKSET_PREFIX = PREFIX + "_taskset"  # stores a list of prune tasks id's
+
+    def __init__(self, id: int) -> None:
+        super().__init__(str(id))
+
+    def generate_tasks(
+        self,
+        celery_app: Celery,
+        db_session: Session,
+        redis_client: Redis,
+        lock: redis.lock.Lock | None,
+        tenant_id: str | None,
+    ) -> int | None:
+        return None
 
 
 def celery_get_queue_length(queue: str, r: Redis) -> int:

backend/danswer/background/celery/celery_utils.py

@@ -4,6 +4,8 @@ from typing import Any
 
 from sqlalchemy.orm import Session
 
+from danswer.background.celery.celery_redis import RedisConnectorDeletion
+from danswer.background.indexing.run_indexing import RunIndexingCallbackInterface
 from danswer.configs.app_configs import MAX_PRUNING_DOCUMENT_RETRIEVAL_PER_MINUTE
 from danswer.connectors.cross_connector_utils.rate_limit_wrapper import (
     rate_limit_builder,
@@ -16,8 +18,7 @@ from danswer.connectors.models import Document
 from danswer.db.connector_credential_pair import get_connector_credential_pair
 from danswer.db.enums import TaskStatus
 from danswer.db.models import TaskQueueState
-from danswer.indexing.indexing_heartbeat import IndexingHeartbeatInterface
-from danswer.redis.redis_connector import RedisConnector
+from danswer.redis.redis_pool import get_redis_client
 from danswer.server.documents.models import DeletionAttemptSnapshot
 from danswer.utils.logger import setup_logger
 
@@ -40,14 +41,14 @@ def _get_deletion_status(
     if not cc_pair:
         return None
 
-    redis_connector = RedisConnector(tenant_id, cc_pair.id)
-    if not redis_connector.delete.fenced:
+    rcd = RedisConnectorDeletion(cc_pair.id)
+
+    r = get_redis_client(tenant_id=tenant_id)
+    if not r.exists(rcd.fence_key):
         return None
 
     return TaskQueueState(
-        task_id="",
-        task_name=redis_connector.delete.fence_key,
-        status=TaskStatus.STARTED,
+        task_id="", task_name=rcd.fence_key, status=TaskStatus.STARTED
     )
 
 
@@ -78,10 +79,10 @@ def document_batch_to_ids(
 
 def extract_ids_from_runnable_connector(
     runnable_connector: BaseConnector,
-    callback: IndexingHeartbeatInterface | None = None,
+    callback: RunIndexingCallbackInterface | None = None,
 ) -> set[str]:
     """
-    If the SlimConnector hasnt been implemented for the given connector, just pull
+    If the PruneConnector hasnt been implemented for the given connector, just pull
     all docs using the load_from_state and grab out the IDs.
 
     Optionally, a callback can be passed to handle the length of each document batch.
@@ -111,15 +112,10 @@ def extract_ids_from_runnable_connector(
     for doc_batch in doc_batch_generator:
         if callback:
             if callback.should_stop():
-                raise RuntimeError(
-                    "extract_ids_from_runnable_connector: Stop signal detected"
-                )
-
+                raise RuntimeError("Stop signal received")
+            callback.progress(len(doc_batch))
         all_connector_doc_ids.update(doc_batch_processing_func(doc_batch))
 
-        if callback:
-            callback.progress("extract_ids_from_runnable_connector", len(doc_batch))
-
     return all_connector_doc_ids
 
 

backend/danswer/background/celery/tasks/beat_schedule.py

@@ -1,61 +0,0 @@
-from datetime import timedelta
-from typing import Any
-
-from danswer.configs.constants import DanswerCeleryPriority
-from danswer.configs.constants import DanswerCeleryTask
-
-
-tasks_to_schedule = [
-    {
-        "name": "check-for-vespa-sync",
-        "task": DanswerCeleryTask.CHECK_FOR_VESPA_SYNC_TASK,
-        "schedule": timedelta(seconds=20),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-connector-deletion",
-        "task": DanswerCeleryTask.CHECK_FOR_CONNECTOR_DELETION,
-        "schedule": timedelta(seconds=20),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-indexing",
-        "task": DanswerCeleryTask.CHECK_FOR_INDEXING,
-        "schedule": timedelta(seconds=15),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-prune",
-        "task": DanswerCeleryTask.CHECK_FOR_PRUNING,
-        "schedule": timedelta(seconds=15),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "kombu-message-cleanup",
-        "task": DanswerCeleryTask.KOMBU_MESSAGE_CLEANUP_TASK,
-        "schedule": timedelta(seconds=3600),
-        "options": {"priority": DanswerCeleryPriority.LOWEST},
-    },
-    {
-        "name": "monitor-vespa-sync",
-        "task": DanswerCeleryTask.MONITOR_VESPA_SYNC,
-        "schedule": timedelta(seconds=5),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-doc-permissions-sync",
-        "task": DanswerCeleryTask.CHECK_FOR_DOC_PERMISSIONS_SYNC,
-        "schedule": timedelta(seconds=30),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-external-group-sync",
-        "task": DanswerCeleryTask.CHECK_FOR_EXTERNAL_GROUP_SYNC,
-        "schedule": timedelta(seconds=20),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-]
-
-
-def get_tasks_to_schedule() -> list[dict[str, Any]]:
-    return tasks_to_schedule

backend/danswer/background/celery/tasks/connector_deletion/tasks.py

@@ -1,25 +1,30 @@
 from datetime import datetime
 from datetime import timezone
 
+import redis
 from celery import Celery
 from celery import shared_task
 from celery import Task
 from celery.exceptions import SoftTimeLimitExceeded
-from redis.lock import Lock as RedisLock
+from redis import Redis
 from sqlalchemy.orm import Session
 
 from danswer.background.celery.apps.app_base import task_logger
+from danswer.background.celery.celery_redis import RedisConnectorDeletion
+from danswer.background.celery.celery_redis import RedisConnectorIndexing
+from danswer.background.celery.celery_redis import RedisConnectorPruning
+from danswer.background.celery.celery_redis import RedisConnectorStop
+from danswer.background.celery.tasks.shared.RedisConnectorDeletionFenceData import (
+    RedisConnectorDeletionFenceData,
+)
 from danswer.configs.app_configs import JOB_TIMEOUT
 from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
-from danswer.configs.constants import DanswerCeleryTask
 from danswer.configs.constants import DanswerRedisLocks
 from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
 from danswer.db.connector_credential_pair import get_connector_credential_pairs
 from danswer.db.engine import get_session_with_tenant
 from danswer.db.enums import ConnectorCredentialPairStatus
 from danswer.db.search_settings import get_all_search_settings
-from danswer.redis.redis_connector import RedisConnector
-from danswer.redis.redis_connector_delete import RedisConnectorDeletePayload
 from danswer.redis.redis_pool import get_redis_client
 
 
@@ -29,7 +34,7 @@ class TaskDependencyError(RuntimeError):
 
 
 @shared_task(
-    name=DanswerCeleryTask.CHECK_FOR_CONNECTOR_DELETION,
+    name="check_for_connector_deletion_task",
     soft_time_limit=JOB_TIMEOUT,
     trail=False,
     bind=True,
@@ -37,7 +42,7 @@ class TaskDependencyError(RuntimeError):
 def check_for_connector_deletion_task(self: Task, *, tenant_id: str | None) -> None:
     r = get_redis_client(tenant_id=tenant_id)
 
-    lock_beat: RedisLock = r.lock(
+    lock_beat = r.lock(
         DanswerRedisLocks.CHECK_CONNECTOR_DELETION_BEAT_LOCK,
         timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
     )
@@ -57,19 +62,19 @@ def check_for_connector_deletion_task(self: Task, *, tenant_id: str | None) -> N
         # try running cleanup on the cc_pair_ids
         for cc_pair_id in cc_pair_ids:
             with get_session_with_tenant(tenant_id) as db_session:
-                redis_connector = RedisConnector(tenant_id, cc_pair_id)
+                rcs = RedisConnectorStop(cc_pair_id)
                 try:
                     try_generate_document_cc_pair_cleanup_tasks(
-                        self.app, cc_pair_id, db_session, lock_beat, tenant_id
+                        self.app, cc_pair_id, db_session, r, lock_beat, tenant_id
                     )
                 except TaskDependencyError as e:
                     # this means we wanted to start deleting but dependent tasks were running
                     # Leave a stop signal to clear indexing and pruning tasks more quickly
                     task_logger.info(str(e))
-                    redis_connector.stop.set_fence(True)
+                    r.set(rcs.fence_key, cc_pair_id)
                 else:
                     # clear the stop signal if it exists ... no longer needed
-                    redis_connector.stop.set_fence(False)
+                    r.delete(rcs.fence_key)
 
     except SoftTimeLimitExceeded:
         task_logger.info(
@@ -86,7 +91,8 @@ def try_generate_document_cc_pair_cleanup_tasks(
     app: Celery,
     cc_pair_id: int,
     db_session: Session,
-    lock_beat: RedisLock,
+    r: Redis,
+    lock_beat: redis.lock.Lock,
     tenant_id: str | None,
 ) -> int | None:
     """Returns an int if syncing is needed. The int represents the number of sync tasks generated.
@@ -100,10 +106,10 @@ def try_generate_document_cc_pair_cleanup_tasks(
 
     lock_beat.reacquire()
 
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
+    rcd = RedisConnectorDeletion(cc_pair_id)
 
     # don't generate sync tasks if tasks are still pending
-    if redis_connector.delete.fenced:
+    if r.exists(rcd.fence_key):
         return None
 
     # we need to load the state of the object inside the fence
@@ -117,55 +123,47 @@ def try_generate_document_cc_pair_cleanup_tasks(
         return None
 
     # set a basic fence to start
-    fence_payload = RedisConnectorDeletePayload(
+    fence_value = RedisConnectorDeletionFenceData(
         num_tasks=None,
         submitted=datetime.now(timezone.utc),
     )
-
-    redis_connector.delete.set_fence(fence_payload)
+    r.set(rcd.fence_key, fence_value.model_dump_json())
 
     try:
         # do not proceed if connector indexing or connector pruning are running
         search_settings_list = get_all_search_settings(db_session)
         for search_settings in search_settings_list:
-            redis_connector_index = redis_connector.new_index(search_settings.id)
-            if redis_connector_index.fenced:
+            rci = RedisConnectorIndexing(cc_pair_id, search_settings.id)
+            if r.get(rci.fence_key):
                 raise TaskDependencyError(
                     f"Connector deletion - Delayed (indexing in progress): "
                     f"cc_pair={cc_pair_id} "
                     f"search_settings={search_settings.id}"
                 )
 
-        if redis_connector.prune.fenced:
+        rcp = RedisConnectorPruning(cc_pair_id)
+        if r.get(rcp.fence_key):
             raise TaskDependencyError(
                 f"Connector deletion - Delayed (pruning in progress): "
                 f"cc_pair={cc_pair_id}"
             )
 
-        if redis_connector.permissions.fenced:
-            raise TaskDependencyError(
-                f"Connector deletion - Delayed (permissions in progress): "
-                f"cc_pair={cc_pair_id}"
-            )
-
         # add tasks to celery and build up the task set to monitor in redis
-        redis_connector.delete.taskset_clear()
+        r.delete(rcd.taskset_key)
 
         # Add all documents that need to be updated into the queue
         task_logger.info(
             f"RedisConnectorDeletion.generate_tasks starting. cc_pair={cc_pair_id}"
         )
-        tasks_generated = redis_connector.delete.generate_tasks(
-            app, db_session, lock_beat
-        )
+        tasks_generated = rcd.generate_tasks(app, db_session, r, lock_beat, tenant_id)
         if tasks_generated is None:
             raise ValueError("RedisConnectorDeletion.generate_tasks returned None")
     except TaskDependencyError:
-        redis_connector.delete.set_fence(None)
+        r.delete(rcd.fence_key)
         raise
     except Exception:
         task_logger.exception("Unexpected exception")
-        redis_connector.delete.set_fence(None)
+        r.delete(rcd.fence_key)
         return None
     else:
         # Currently we are allowing the sync to proceed with 0 tasks.
@@ -180,7 +178,7 @@ def try_generate_document_cc_pair_cleanup_tasks(
         )
 
         # set this only after all tasks have been added
-        fence_payload.num_tasks = tasks_generated
-        redis_connector.delete.set_fence(fence_payload)
+        fence_value.num_tasks = tasks_generated
+        r.set(rcd.fence_key, fence_value.model_dump_json())
 
     return tasks_generated

backend/danswer/background/celery/tasks/doc_permission_syncing/tasks.py

@@ -1,345 +0,0 @@
-from datetime import datetime
-from datetime import timedelta
-from datetime import timezone
-from uuid import uuid4
-
-from celery import Celery
-from celery import shared_task
-from celery import Task
-from celery.exceptions import SoftTimeLimitExceeded
-from redis import Redis
-from redis.lock import Lock as RedisLock
-
-from danswer.access.models import DocExternalAccess
-from danswer.background.celery.apps.app_base import task_logger
-from danswer.configs.app_configs import JOB_TIMEOUT
-from danswer.configs.constants import CELERY_PERMISSIONS_SYNC_LOCK_TIMEOUT
-from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
-from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
-from danswer.configs.constants import DanswerCeleryPriority
-from danswer.configs.constants import DanswerCeleryQueues
-from danswer.configs.constants import DanswerCeleryTask
-from danswer.configs.constants import DanswerRedisLocks
-from danswer.configs.constants import DocumentSource
-from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
-from danswer.db.document import upsert_document_by_connector_credential_pair
-from danswer.db.engine import get_session_with_tenant
-from danswer.db.enums import AccessType
-from danswer.db.enums import ConnectorCredentialPairStatus
-from danswer.db.models import ConnectorCredentialPair
-from danswer.db.users import batch_add_ext_perm_user_if_not_exists
-from danswer.redis.redis_connector import RedisConnector
-from danswer.redis.redis_connector_doc_perm_sync import (
-    RedisConnectorPermissionSyncPayload,
-)
-from danswer.redis.redis_pool import get_redis_client
-from danswer.utils.logger import doc_permission_sync_ctx
-from danswer.utils.logger import setup_logger
-from ee.danswer.db.connector_credential_pair import get_all_auto_sync_cc_pairs
-from ee.danswer.db.document import upsert_document_external_perms
-from ee.danswer.external_permissions.sync_params import DOC_PERMISSION_SYNC_PERIODS
-from ee.danswer.external_permissions.sync_params import DOC_PERMISSIONS_FUNC_MAP
-
-logger = setup_logger()
-
-
-DOCUMENT_PERMISSIONS_UPDATE_MAX_RETRIES = 3
-
-
-# 5 seconds more than RetryDocumentIndex STOP_AFTER+MAX_WAIT
-LIGHT_SOFT_TIME_LIMIT = 105
-LIGHT_TIME_LIMIT = LIGHT_SOFT_TIME_LIMIT + 15
-
-
-def _is_external_doc_permissions_sync_due(cc_pair: ConnectorCredentialPair) -> bool:
-    """Returns boolean indicating if external doc permissions sync is due."""
-
-    if cc_pair.access_type != AccessType.SYNC:
-        return False
-
-    # skip doc permissions sync if not active
-    if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
-        return False
-
-    if cc_pair.status == ConnectorCredentialPairStatus.DELETING:
-        return False
-
-    # If the last sync is None, it has never been run so we run the sync
-    last_perm_sync = cc_pair.last_time_perm_sync
-    if last_perm_sync is None:
-        return True
-
-    source_sync_period = DOC_PERMISSION_SYNC_PERIODS.get(cc_pair.connector.source)
-
-    # If RESTRICTED_FETCH_PERIOD[source] is None, we always run the sync.
-    if not source_sync_period:
-        return True
-
-    # If the last sync is greater than the full fetch period, we run the sync
-    next_sync = last_perm_sync + timedelta(seconds=source_sync_period)
-    if datetime.now(timezone.utc) >= next_sync:
-        return True
-
-    return False
-
-
-@shared_task(
-    name=DanswerCeleryTask.CHECK_FOR_DOC_PERMISSIONS_SYNC,
-    soft_time_limit=JOB_TIMEOUT,
-    bind=True,
-)
-def check_for_doc_permissions_sync(self: Task, *, tenant_id: str | None) -> None:
-    r = get_redis_client(tenant_id=tenant_id)
-
-    lock_beat = r.lock(
-        DanswerRedisLocks.CHECK_CONNECTOR_DOC_PERMISSIONS_SYNC_BEAT_LOCK,
-        timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
-    )
-
-    try:
-        # these tasks should never overlap
-        if not lock_beat.acquire(blocking=False):
-            return
-
-        # get all cc pairs that need to be synced
-        cc_pair_ids_to_sync: list[int] = []
-        with get_session_with_tenant(tenant_id) as db_session:
-            cc_pairs = get_all_auto_sync_cc_pairs(db_session)
-
-            for cc_pair in cc_pairs:
-                if _is_external_doc_permissions_sync_due(cc_pair):
-                    cc_pair_ids_to_sync.append(cc_pair.id)
-
-        for cc_pair_id in cc_pair_ids_to_sync:
-            tasks_created = try_creating_permissions_sync_task(
-                self.app, cc_pair_id, r, tenant_id
-            )
-            if not tasks_created:
-                continue
-
-            task_logger.info(f"Doc permissions sync queued: cc_pair={cc_pair_id}")
-    except SoftTimeLimitExceeded:
-        task_logger.info(
-            "Soft time limit exceeded, task is being terminated gracefully."
-        )
-    except Exception:
-        task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
-    finally:
-        if lock_beat.owned():
-            lock_beat.release()
-
-
-def try_creating_permissions_sync_task(
-    app: Celery,
-    cc_pair_id: int,
-    r: Redis,
-    tenant_id: str | None,
-) -> int | None:
-    """Returns an int if syncing is needed. The int represents the number of sync tasks generated.
-    Returns None if no syncing is required."""
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-
-    LOCK_TIMEOUT = 30
-
-    lock: RedisLock = r.lock(
-        DANSWER_REDIS_FUNCTION_LOCK_PREFIX + "try_generate_permissions_sync_tasks",
-        timeout=LOCK_TIMEOUT,
-    )
-
-    acquired = lock.acquire(blocking_timeout=LOCK_TIMEOUT / 2)
-    if not acquired:
-        return None
-
-    try:
-        if redis_connector.permissions.fenced:
-            return None
-
-        if redis_connector.delete.fenced:
-            return None
-
-        if redis_connector.prune.fenced:
-            return None
-
-        redis_connector.permissions.generator_clear()
-        redis_connector.permissions.taskset_clear()
-
-        custom_task_id = f"{redis_connector.permissions.generator_task_key}_{uuid4()}"
-
-        result = app.send_task(
-            DanswerCeleryTask.CONNECTOR_PERMISSION_SYNC_GENERATOR_TASK,
-            kwargs=dict(
-                cc_pair_id=cc_pair_id,
-                tenant_id=tenant_id,
-            ),
-            queue=DanswerCeleryQueues.CONNECTOR_DOC_PERMISSIONS_SYNC,
-            task_id=custom_task_id,
-            priority=DanswerCeleryPriority.HIGH,
-        )
-
-        # set a basic fence to start
-        payload = RedisConnectorPermissionSyncPayload(
-            started=None, celery_task_id=result.id
-        )
-
-        redis_connector.permissions.set_fence(payload)
-    except Exception:
-        task_logger.exception(f"Unexpected exception: cc_pair={cc_pair_id}")
-        return None
-    finally:
-        if lock.owned():
-            lock.release()
-
-    return 1
-
-
-@shared_task(
-    name=DanswerCeleryTask.CONNECTOR_PERMISSION_SYNC_GENERATOR_TASK,
-    acks_late=False,
-    soft_time_limit=JOB_TIMEOUT,
-    track_started=True,
-    trail=False,
-    bind=True,
-)
-def connector_permission_sync_generator_task(
-    self: Task,
-    cc_pair_id: int,
-    tenant_id: str | None,
-) -> None:
-    """
-    Permission sync task that handles document permission syncing for a given connector credential pair
-    This task assumes that the task has already been properly fenced
-    """
-
-    doc_permission_sync_ctx_dict = doc_permission_sync_ctx.get()
-    doc_permission_sync_ctx_dict["cc_pair_id"] = cc_pair_id
-    doc_permission_sync_ctx_dict["request_id"] = self.request.id
-    doc_permission_sync_ctx.set(doc_permission_sync_ctx_dict)
-
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-
-    r = get_redis_client(tenant_id=tenant_id)
-
-    lock = r.lock(
-        DanswerRedisLocks.CONNECTOR_DOC_PERMISSIONS_SYNC_LOCK_PREFIX
-        + f"_{redis_connector.id}",
-        timeout=CELERY_PERMISSIONS_SYNC_LOCK_TIMEOUT,
-    )
-
-    acquired = lock.acquire(blocking=False)
-    if not acquired:
-        task_logger.warning(
-            f"Permission sync task already running, exiting...: cc_pair={cc_pair_id}"
-        )
-        return None
-
-    try:
-        with get_session_with_tenant(tenant_id) as db_session:
-            cc_pair = get_connector_credential_pair_from_id(cc_pair_id, db_session)
-            if cc_pair is None:
-                raise ValueError(
-                    f"No connector credential pair found for id: {cc_pair_id}"
-                )
-
-            source_type = cc_pair.connector.source
-
-            doc_sync_func = DOC_PERMISSIONS_FUNC_MAP.get(source_type)
-            if doc_sync_func is None:
-                raise ValueError(
-                    f"No doc sync func found for {source_type} with cc_pair={cc_pair_id}"
-                )
-
-            logger.info(f"Syncing docs for {source_type} with cc_pair={cc_pair_id}")
-
-            payload = redis_connector.permissions.payload
-            if not payload:
-                raise ValueError(f"No fence payload found: cc_pair={cc_pair_id}")
-
-            payload.started = datetime.now(timezone.utc)
-            redis_connector.permissions.set_fence(payload)
-
-            document_external_accesses: list[DocExternalAccess] = doc_sync_func(cc_pair)
-
-            task_logger.info(
-                f"RedisConnector.permissions.generate_tasks starting. cc_pair={cc_pair_id}"
-            )
-            tasks_generated = redis_connector.permissions.generate_tasks(
-                celery_app=self.app,
-                lock=lock,
-                new_permissions=document_external_accesses,
-                source_string=source_type,
-                connector_id=cc_pair.connector.id,
-                credential_id=cc_pair.credential.id,
-            )
-            if tasks_generated is None:
-                return None
-
-            task_logger.info(
-                f"RedisConnector.permissions.generate_tasks finished. "
-                f"cc_pair={cc_pair_id} tasks_generated={tasks_generated}"
-            )
-
-            redis_connector.permissions.generator_complete = tasks_generated
-
-    except Exception as e:
-        task_logger.exception(f"Failed to run permission sync: cc_pair={cc_pair_id}")
-
-        redis_connector.permissions.generator_clear()
-        redis_connector.permissions.taskset_clear()
-        redis_connector.permissions.set_fence(None)
-        raise e
-    finally:
-        if lock.owned():
-            lock.release()
-
-
-@shared_task(
-    name=DanswerCeleryTask.UPDATE_EXTERNAL_DOCUMENT_PERMISSIONS_TASK,
-    soft_time_limit=LIGHT_SOFT_TIME_LIMIT,
-    time_limit=LIGHT_TIME_LIMIT,
-    max_retries=DOCUMENT_PERMISSIONS_UPDATE_MAX_RETRIES,
-    bind=True,
-)
-def update_external_document_permissions_task(
-    self: Task,
-    tenant_id: str | None,
-    serialized_doc_external_access: dict,
-    source_string: str,
-    connector_id: int,
-    credential_id: int,
-) -> bool:
-    document_external_access = DocExternalAccess.from_dict(
-        serialized_doc_external_access
-    )
-    doc_id = document_external_access.doc_id
-    external_access = document_external_access.external_access
-    try:
-        with get_session_with_tenant(tenant_id) as db_session:
-            # Add the users to the DB if they don't exist
-            batch_add_ext_perm_user_if_not_exists(
-                db_session=db_session,
-                emails=list(external_access.external_user_emails),
-            )
-            # Then we upsert the document's external permissions in postgres
-            created_new_doc = upsert_document_external_perms(
-                db_session=db_session,
-                doc_id=doc_id,
-                external_access=external_access,
-                source_type=DocumentSource(source_string),
-            )
-
-            if created_new_doc:
-                # If a new document was created, we associate it with the cc_pair
-                upsert_document_by_connector_credential_pair(
-                    db_session=db_session,
-                    connector_id=connector_id,
-                    credential_id=credential_id,
-                    document_ids=[doc_id],
-                )
-
-            logger.debug(
-                f"Successfully synced postgres document permissions for {doc_id}"
-            )
-        return True
-    except Exception:
-        logger.exception("Error Syncing Document Permissions")
-        return False

backend/danswer/background/celery/tasks/external_group_syncing/tasks.py

@@ -1,298 +0,0 @@
-from datetime import datetime
-from datetime import timedelta
-from datetime import timezone
-from uuid import uuid4
-
-from celery import Celery
-from celery import shared_task
-from celery import Task
-from celery.exceptions import SoftTimeLimitExceeded
-from redis import Redis
-from redis.lock import Lock as RedisLock
-
-from danswer.background.celery.apps.app_base import task_logger
-from danswer.configs.app_configs import JOB_TIMEOUT
-from danswer.configs.constants import CELERY_EXTERNAL_GROUP_SYNC_LOCK_TIMEOUT
-from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
-from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
-from danswer.configs.constants import DanswerCeleryPriority
-from danswer.configs.constants import DanswerCeleryQueues
-from danswer.configs.constants import DanswerCeleryTask
-from danswer.configs.constants import DanswerRedisLocks
-from danswer.db.connector import mark_cc_pair_as_external_group_synced
-from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
-from danswer.db.engine import get_session_with_tenant
-from danswer.db.enums import AccessType
-from danswer.db.enums import ConnectorCredentialPairStatus
-from danswer.db.models import ConnectorCredentialPair
-from danswer.redis.redis_connector import RedisConnector
-from danswer.redis.redis_connector_ext_group_sync import (
-    RedisConnectorExternalGroupSyncPayload,
-)
-from danswer.redis.redis_pool import get_redis_client
-from danswer.utils.logger import setup_logger
-from ee.danswer.db.connector_credential_pair import get_all_auto_sync_cc_pairs
-from ee.danswer.db.connector_credential_pair import get_cc_pairs_by_source
-from ee.danswer.db.external_perm import ExternalUserGroup
-from ee.danswer.db.external_perm import replace_user__ext_group_for_cc_pair
-from ee.danswer.external_permissions.sync_params import EXTERNAL_GROUP_SYNC_PERIODS
-from ee.danswer.external_permissions.sync_params import GROUP_PERMISSIONS_FUNC_MAP
-from ee.danswer.external_permissions.sync_params import (
-    GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC,
-)
-
-logger = setup_logger()
-
-
-EXTERNAL_GROUPS_UPDATE_MAX_RETRIES = 3
-
-
-# 5 seconds more than RetryDocumentIndex STOP_AFTER+MAX_WAIT
-LIGHT_SOFT_TIME_LIMIT = 105
-LIGHT_TIME_LIMIT = LIGHT_SOFT_TIME_LIMIT + 15
-
-
-def _is_external_group_sync_due(cc_pair: ConnectorCredentialPair) -> bool:
-    """Returns boolean indicating if external group sync is due."""
-
-    if cc_pair.access_type != AccessType.SYNC:
-        return False
-
-    # skip external group sync if not active
-    if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
-        return False
-
-    if cc_pair.status == ConnectorCredentialPairStatus.DELETING:
-        return False
-
-    # If there is not group sync function for the connector, we don't run the sync
-    # This is fine because all sources dont necessarily have a concept of groups
-    if not GROUP_PERMISSIONS_FUNC_MAP.get(cc_pair.connector.source):
-        return False
-
-    # If the last sync is None, it has never been run so we run the sync
-    last_ext_group_sync = cc_pair.last_time_external_group_sync
-    if last_ext_group_sync is None:
-        return True
-
-    source_sync_period = EXTERNAL_GROUP_SYNC_PERIODS.get(cc_pair.connector.source)
-
-    # If EXTERNAL_GROUP_SYNC_PERIODS is None, we always run the sync.
-    if not source_sync_period:
-        return True
-
-    # If the last sync is greater than the full fetch period, we run the sync
-    next_sync = last_ext_group_sync + timedelta(seconds=source_sync_period)
-    if datetime.now(timezone.utc) >= next_sync:
-        return True
-
-    return False
-
-
-@shared_task(
-    name=DanswerCeleryTask.CHECK_FOR_EXTERNAL_GROUP_SYNC,
-    soft_time_limit=JOB_TIMEOUT,
-    bind=True,
-)
-def check_for_external_group_sync(self: Task, *, tenant_id: str | None) -> None:
-    r = get_redis_client(tenant_id=tenant_id)
-
-    lock_beat = r.lock(
-        DanswerRedisLocks.CHECK_CONNECTOR_EXTERNAL_GROUP_SYNC_BEAT_LOCK,
-        timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
-    )
-
-    try:
-        # these tasks should never overlap
-        if not lock_beat.acquire(blocking=False):
-            return
-
-        cc_pair_ids_to_sync: list[int] = []
-        with get_session_with_tenant(tenant_id) as db_session:
-            cc_pairs = get_all_auto_sync_cc_pairs(db_session)
-
-            # We only want to sync one cc_pair per source type in
-            # GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC
-            for source in GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC:
-                # These are ordered by cc_pair id so the first one is the one we want
-                cc_pairs_to_dedupe = get_cc_pairs_by_source(
-                    db_session, source, only_sync=True
-                )
-                # We only want to sync one cc_pair per source type
-                # in GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC so we dedupe here
-                for cc_pair_to_remove in cc_pairs_to_dedupe[1:]:
-                    cc_pairs = [
-                        cc_pair
-                        for cc_pair in cc_pairs
-                        if cc_pair.id != cc_pair_to_remove.id
-                    ]
-
-            for cc_pair in cc_pairs:
-                if _is_external_group_sync_due(cc_pair):
-                    cc_pair_ids_to_sync.append(cc_pair.id)
-
-        for cc_pair_id in cc_pair_ids_to_sync:
-            tasks_created = try_creating_external_group_sync_task(
-                self.app, cc_pair_id, r, tenant_id
-            )
-            if not tasks_created:
-                continue
-
-            task_logger.info(f"External group sync queued: cc_pair={cc_pair_id}")
-    except SoftTimeLimitExceeded:
-        task_logger.info(
-            "Soft time limit exceeded, task is being terminated gracefully."
-        )
-    except Exception:
-        task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
-    finally:
-        if lock_beat.owned():
-            lock_beat.release()
-
-
-def try_creating_external_group_sync_task(
-    app: Celery,
-    cc_pair_id: int,
-    r: Redis,
-    tenant_id: str | None,
-) -> int | None:
-    """Returns an int if syncing is needed. The int represents the number of sync tasks generated.
-    Returns None if no syncing is required."""
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-
-    LOCK_TIMEOUT = 30
-
-    lock = r.lock(
-        DANSWER_REDIS_FUNCTION_LOCK_PREFIX + "try_generate_external_group_sync_tasks",
-        timeout=LOCK_TIMEOUT,
-    )
-
-    acquired = lock.acquire(blocking_timeout=LOCK_TIMEOUT / 2)
-    if not acquired:
-        return None
-
-    try:
-        # Dont kick off a new sync if the previous one is still running
-        if redis_connector.external_group_sync.fenced:
-            return None
-
-        redis_connector.external_group_sync.generator_clear()
-        redis_connector.external_group_sync.taskset_clear()
-
-        custom_task_id = f"{redis_connector.external_group_sync.taskset_key}_{uuid4()}"
-
-        result = app.send_task(
-            DanswerCeleryTask.CONNECTOR_EXTERNAL_GROUP_SYNC_GENERATOR_TASK,
-            kwargs=dict(
-                cc_pair_id=cc_pair_id,
-                tenant_id=tenant_id,
-            ),
-            queue=DanswerCeleryQueues.CONNECTOR_EXTERNAL_GROUP_SYNC,
-            task_id=custom_task_id,
-            priority=DanswerCeleryPriority.HIGH,
-        )
-
-        payload = RedisConnectorExternalGroupSyncPayload(
-            started=datetime.now(timezone.utc),
-            celery_task_id=result.id,
-        )
-
-        redis_connector.external_group_sync.set_fence(payload)
-
-    except Exception:
-        task_logger.exception(
-            f"Unexpected exception while trying to create external group sync task: cc_pair={cc_pair_id}"
-        )
-        return None
-    finally:
-        if lock.owned():
-            lock.release()
-
-    return 1
-
-
-@shared_task(
-    name=DanswerCeleryTask.CONNECTOR_EXTERNAL_GROUP_SYNC_GENERATOR_TASK,
-    acks_late=False,
-    soft_time_limit=JOB_TIMEOUT,
-    track_started=True,
-    trail=False,
-    bind=True,
-)
-def connector_external_group_sync_generator_task(
-    self: Task,
-    cc_pair_id: int,
-    tenant_id: str | None,
-) -> None:
-    """
-    Permission sync task that handles external group syncing for a given connector credential pair
-    This task assumes that the task has already been properly fenced
-    """
-
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-
-    r = get_redis_client(tenant_id=tenant_id)
-
-    lock: RedisLock = r.lock(
-        DanswerRedisLocks.CONNECTOR_EXTERNAL_GROUP_SYNC_LOCK_PREFIX
-        + f"_{redis_connector.id}",
-        timeout=CELERY_EXTERNAL_GROUP_SYNC_LOCK_TIMEOUT,
-    )
-
-    try:
-        acquired = lock.acquire(blocking=False)
-        if not acquired:
-            task_logger.warning(
-                f"External group sync task already running, exiting...: cc_pair={cc_pair_id}"
-            )
-            return None
-
-        with get_session_with_tenant(tenant_id) as db_session:
-            cc_pair = get_connector_credential_pair_from_id(cc_pair_id, db_session)
-            if cc_pair is None:
-                raise ValueError(
-                    f"No connector credential pair found for id: {cc_pair_id}"
-                )
-
-            source_type = cc_pair.connector.source
-
-            ext_group_sync_func = GROUP_PERMISSIONS_FUNC_MAP.get(source_type)
-            if ext_group_sync_func is None:
-                raise ValueError(
-                    f"No external group sync func found for {source_type} for cc_pair: {cc_pair_id}"
-                )
-
-            logger.info(
-                f"Syncing external groups for {source_type} for cc_pair: {cc_pair_id}"
-            )
-
-            external_user_groups: list[ExternalUserGroup] = ext_group_sync_func(cc_pair)
-
-            logger.info(
-                f"Syncing {len(external_user_groups)} external user groups for {source_type}"
-            )
-
-            replace_user__ext_group_for_cc_pair(
-                db_session=db_session,
-                cc_pair_id=cc_pair.id,
-                group_defs=external_user_groups,
-                source=cc_pair.connector.source,
-            )
-            logger.info(
-                f"Synced {len(external_user_groups)} external user groups for {source_type}"
-            )
-
-            mark_cc_pair_as_external_group_synced(db_session, cc_pair.id)
-    except Exception as e:
-        task_logger.exception(
-            f"Failed to run external group sync: cc_pair={cc_pair_id}"
-        )
-
-        redis_connector.external_group_sync.generator_clear()
-        redis_connector.external_group_sync.taskset_clear()
-        raise e
-    finally:
-        # we always want to clear the fence after the task is done or failed so it doesn't get stuck
-        redis_connector.external_group_sync.set_fence(None)
-        if lock.owned():
-            lock.release()

backend/danswer/background/celery/tasks/indexing/tasks.py

@@ -2,171 +2,99 @@ from datetime import datetime
 from datetime import timezone
 from http import HTTPStatus
 from time import sleep
+from typing import cast
+from uuid import uuid4
 
 import redis
-import sentry_sdk
 from celery import Celery
 from celery import shared_task
 from celery import Task
 from celery.exceptions import SoftTimeLimitExceeded
 from redis import Redis
-from redis.exceptions import LockError
-from redis.lock import Lock as RedisLock
 from sqlalchemy.orm import Session
 
 from danswer.background.celery.apps.app_base import task_logger
+from danswer.background.celery.celery_redis import RedisConnectorDeletion
+from danswer.background.celery.celery_redis import RedisConnectorIndexing
+from danswer.background.celery.celery_redis import RedisConnectorStop
+from danswer.background.celery.tasks.shared.RedisConnectorIndexingFenceData import (
+    RedisConnectorIndexingFenceData,
+)
 from danswer.background.indexing.job_client import SimpleJobClient
 from danswer.background.indexing.run_indexing import run_indexing_entrypoint
+from danswer.background.indexing.run_indexing import RunIndexingCallbackInterface
 from danswer.configs.app_configs import DISABLE_INDEX_UPDATE_ON_SWAP
 from danswer.configs.constants import CELERY_INDEXING_LOCK_TIMEOUT
 from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
 from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
 from danswer.configs.constants import DanswerCeleryPriority
 from danswer.configs.constants import DanswerCeleryQueues
-from danswer.configs.constants import DanswerCeleryTask
 from danswer.configs.constants import DanswerRedisLocks
 from danswer.configs.constants import DocumentSource
-from danswer.db.connector import mark_ccpair_with_indexing_trigger
 from danswer.db.connector_credential_pair import fetch_connector_credential_pairs
 from danswer.db.connector_credential_pair import get_connector_credential_pair_from_id
 from danswer.db.engine import get_db_current_time
 from danswer.db.engine import get_session_with_tenant
 from danswer.db.enums import ConnectorCredentialPairStatus
-from danswer.db.enums import IndexingMode
 from danswer.db.enums import IndexingStatus
 from danswer.db.enums import IndexModelStatus
 from danswer.db.index_attempt import create_index_attempt
-from danswer.db.index_attempt import delete_index_attempt
-from danswer.db.index_attempt import get_all_index_attempts_by_status
 from danswer.db.index_attempt import get_index_attempt
 from danswer.db.index_attempt import get_last_attempt_for_cc_pair
-from danswer.db.index_attempt import mark_attempt_canceled
 from danswer.db.index_attempt import mark_attempt_failed
 from danswer.db.models import ConnectorCredentialPair
 from danswer.db.models import IndexAttempt
 from danswer.db.models import SearchSettings
-from danswer.db.search_settings import get_active_search_settings
 from danswer.db.search_settings import get_current_search_settings
+from danswer.db.search_settings import get_secondary_search_settings
 from danswer.db.swap_index import check_index_swap
-from danswer.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from danswer.natural_language_processing.search_nlp_models import EmbeddingModel
 from danswer.natural_language_processing.search_nlp_models import warm_up_bi_encoder
-from danswer.redis.redis_connector import RedisConnector
-from danswer.redis.redis_connector_index import RedisConnectorIndex
-from danswer.redis.redis_connector_index import RedisConnectorIndexPayload
 from danswer.redis.redis_pool import get_redis_client
 from danswer.utils.logger import setup_logger
 from danswer.utils.variable_functionality import global_version
 from shared_configs.configs import INDEXING_MODEL_SERVER_HOST
 from shared_configs.configs import INDEXING_MODEL_SERVER_PORT
 from shared_configs.configs import MULTI_TENANT
-from shared_configs.configs import SENTRY_DSN
 
 logger = setup_logger()
 
 
-class IndexingCallback(IndexingHeartbeatInterface):
+class RunIndexingCallback(RunIndexingCallbackInterface):
     def __init__(
         self,
         stop_key: str,
         generator_progress_key: str,
-        redis_lock: RedisLock,
+        redis_lock: redis.lock.Lock,
         redis_client: Redis,
     ):
         super().__init__()
-        self.redis_lock: RedisLock = redis_lock
+        self.redis_lock: redis.lock.Lock = redis_lock
         self.stop_key: str = stop_key
         self.generator_progress_key: str = generator_progress_key
         self.redis_client = redis_client
-        self.started: datetime = datetime.now(timezone.utc)
-        self.redis_lock.reacquire()
-
-        self.last_tag: str = "IndexingCallback.__init__"
-        self.last_lock_reacquire: datetime = datetime.now(timezone.utc)
 
     def should_stop(self) -> bool:
         if self.redis_client.exists(self.stop_key):
             return True
         return False
 
-    def progress(self, tag: str, amount: int) -> None:
-        try:
-            self.redis_lock.reacquire()
-            self.last_tag = tag
-            self.last_lock_reacquire = datetime.now(timezone.utc)
-        except LockError:
-            logger.exception(
-                f"IndexingCallback - lock.reacquire exceptioned. "
-                f"lock_timeout={self.redis_lock.timeout} "
-                f"start={self.started} "
-                f"last_tag={self.last_tag} "
-                f"last_reacquired={self.last_lock_reacquire} "
-                f"now={datetime.now(timezone.utc)}"
-            )
-            raise
-
+    def progress(self, amount: int) -> None:
+        self.redis_lock.reacquire()
         self.redis_client.incrby(self.generator_progress_key, amount)
 
 
-def get_unfenced_index_attempt_ids(db_session: Session, r: redis.Redis) -> list[int]:
-    """Gets a list of unfenced index attempts. Should not be possible, so we'd typically
-    want to clean them up.
-
-    Unfenced = attempt not in terminal state and fence does not exist.
-    """
-    unfenced_attempts: list[int] = []
-
-    # inner/outer/inner double check pattern to avoid race conditions when checking for
-    # bad state
-    # inner = index_attempt in non terminal state
-    # outer = r.fence_key down
-
-    # check the db for index attempts in a non terminal state
-    attempts: list[IndexAttempt] = []
-    attempts.extend(
-        get_all_index_attempts_by_status(IndexingStatus.NOT_STARTED, db_session)
-    )
-    attempts.extend(
-        get_all_index_attempts_by_status(IndexingStatus.IN_PROGRESS, db_session)
-    )
-
-    for attempt in attempts:
-        fence_key = RedisConnectorIndex.fence_key_with_ids(
-            attempt.connector_credential_pair_id, attempt.search_settings_id
-        )
-
-        # if the fence is down / doesn't exist, possible error but not confirmed
-        if r.exists(fence_key):
-            continue
-
-        # Between the time the attempts are first looked up and the time we see the fence down,
-        # the attempt may have completed and taken down the fence normally.
-
-        # We need to double check that the index attempt is still in a non terminal state
-        # and matches the original state, which confirms we are really in a bad state.
-        attempt_2 = get_index_attempt(db_session, attempt.id)
-        if not attempt_2:
-            continue
-
-        if attempt.status != attempt_2.status:
-            continue
-
-        unfenced_attempts.append(attempt.id)
-
-    return unfenced_attempts
-
-
 @shared_task(
-    name=DanswerCeleryTask.CHECK_FOR_INDEXING,
+    name="check_for_indexing",
     soft_time_limit=300,
     bind=True,
 )
 def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
     tasks_created = 0
-    locked = False
+
     r = get_redis_client(tenant_id=tenant_id)
 
-    lock_beat: RedisLock = r.lock(
+    lock_beat = r.lock(
         DanswerRedisLocks.CHECK_INDEXING_BEAT_LOCK,
         timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
     )
@@ -176,49 +104,44 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
         if not lock_beat.acquire(blocking=False):
             return None
 
-        locked = True
-
-        # check for search settings swap
         with get_session_with_tenant(tenant_id=tenant_id) as db_session:
-            old_search_settings = check_index_swap(db_session=db_session)
+            check_index_swap(db_session=db_session)
             current_search_settings = get_current_search_settings(db_session)
             # So that the first time users aren't surprised by really slow speed of first
             # batch of documents indexed
             if current_search_settings.provider_type is None and not MULTI_TENANT:
-                if old_search_settings:
-                    embedding_model = EmbeddingModel.from_db_model(
-                        search_settings=current_search_settings,
-                        server_host=INDEXING_MODEL_SERVER_HOST,
-                        server_port=INDEXING_MODEL_SERVER_PORT,
-                    )
+                embedding_model = EmbeddingModel.from_db_model(
+                    search_settings=current_search_settings,
+                    server_host=INDEXING_MODEL_SERVER_HOST,
+                    server_port=INDEXING_MODEL_SERVER_PORT,
+                )
+                warm_up_bi_encoder(
+                    embedding_model=embedding_model,
+                )
 
-                    # only warm up if search settings were changed
-                    warm_up_bi_encoder(
-                        embedding_model=embedding_model,
-                    )
-
-        # gather cc_pair_ids
         cc_pair_ids: list[int] = []
         with get_session_with_tenant(tenant_id) as db_session:
-            lock_beat.reacquire()
             cc_pairs = fetch_connector_credential_pairs(db_session)
             for cc_pair_entry in cc_pairs:
                 cc_pair_ids.append(cc_pair_entry.id)
 
-        # kick off index attempts
         for cc_pair_id in cc_pair_ids:
-            lock_beat.reacquire()
-
-            redis_connector = RedisConnector(tenant_id, cc_pair_id)
             with get_session_with_tenant(tenant_id) as db_session:
-                search_settings_list: list[SearchSettings] = get_active_search_settings(
-                    db_session
-                )
-                for search_settings_instance in search_settings_list:
-                    redis_connector_index = redis_connector.new_index(
-                        search_settings_instance.id
+                # Get the primary search settings
+                primary_search_settings = get_current_search_settings(db_session)
+                search_settings = [primary_search_settings]
+
+                # Check for secondary search settings
+                secondary_search_settings = get_secondary_search_settings(db_session)
+                if secondary_search_settings is not None:
+                    # If secondary settings exist, add them to the list
+                    search_settings.append(secondary_search_settings)
+
+                for search_settings_instance in search_settings:
+                    rci = RedisConnectorIndexing(
+                        cc_pair_id, search_settings_instance.id
                     )
-                    if redis_connector_index.fenced:
+                    if r.exists(rci.fence_key):
                         continue
 
                     cc_pair = get_connector_credential_pair_from_id(
@@ -230,80 +153,31 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
                     last_attempt = get_last_attempt_for_cc_pair(
                         cc_pair.id, search_settings_instance.id, db_session
                     )
-
-                    search_settings_primary = False
-                    if search_settings_instance.id == search_settings_list[0].id:
-                        search_settings_primary = True
-
                     if not _should_index(
                         cc_pair=cc_pair,
                         last_index=last_attempt,
                         search_settings_instance=search_settings_instance,
-                        search_settings_primary=search_settings_primary,
-                        secondary_index_building=len(search_settings_list) > 1,
+                        secondary_index_building=len(search_settings) > 1,
                         db_session=db_session,
                     ):
                         continue
 
-                    reindex = False
-                    if search_settings_instance.id == search_settings_list[0].id:
-                        # the indexing trigger is only checked and cleared with the primary search settings
-                        if cc_pair.indexing_trigger is not None:
-                            if cc_pair.indexing_trigger == IndexingMode.REINDEX:
-                                reindex = True
-
-                            task_logger.info(
-                                f"Connector indexing manual trigger detected: "
-                                f"cc_pair={cc_pair.id} "
-                                f"search_settings={search_settings_instance.id} "
-                                f"indexing_mode={cc_pair.indexing_trigger}"
-                            )
-
-                            mark_ccpair_with_indexing_trigger(
-                                cc_pair.id, None, db_session
-                            )
-
                     # using a task queue and only allowing one task per cc_pair/search_setting
                     # prevents us from starving out certain attempts
                     attempt_id = try_creating_indexing_task(
                         self.app,
                         cc_pair,
                         search_settings_instance,
-                        reindex,
+                        False,
                         db_session,
                         r,
                         tenant_id,
                     )
                     if attempt_id:
                         task_logger.info(
-                            f"Connector indexing queued: "
-                            f"index_attempt={attempt_id} "
-                            f"cc_pair={cc_pair.id} "
-                            f"search_settings={search_settings_instance.id}"
+                            f"Indexing queued: cc_pair={cc_pair.id} index_attempt={attempt_id}"
                         )
                         tasks_created += 1
-
-        # Fail any index attempts in the DB that don't have fences
-        # This shouldn't ever happen!
-        with get_session_with_tenant(tenant_id) as db_session:
-            unfenced_attempt_ids = get_unfenced_index_attempt_ids(db_session, r)
-            for attempt_id in unfenced_attempt_ids:
-                lock_beat.reacquire()
-
-                attempt = get_index_attempt(db_session, attempt_id)
-                if not attempt:
-                    continue
-
-                failure_reason = (
-                    f"Unfenced index attempt found in DB: "
-                    f"index_attempt={attempt.id} "
-                    f"cc_pair={attempt.connector_credential_pair_id} "
-                    f"search_settings={attempt.search_settings_id}"
-                )
-                task_logger.error(failure_reason)
-                mark_attempt_failed(
-                    attempt.id, db_session, failure_reason=failure_reason
-                )
     except SoftTimeLimitExceeded:
         task_logger.info(
             "Soft time limit exceeded, task is being terminated gracefully."
@@ -311,14 +185,8 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
     except Exception:
         task_logger.exception(f"Unexpected exception: tenant={tenant_id}")
     finally:
-        if locked:
-            if lock_beat.owned():
-                lock_beat.release()
-            else:
-                task_logger.error(
-                    "check_for_indexing - Lock not owned on completion: "
-                    f"tenant={tenant_id}"
-                )
+        if lock_beat.owned():
+            lock_beat.release()
 
     return tasks_created
 
@@ -327,7 +195,6 @@ def _should_index(
     cc_pair: ConnectorCredentialPair,
     last_index: IndexAttempt | None,
     search_settings_instance: SearchSettings,
-    search_settings_primary: bool,
     secondary_index_building: bool,
     db_session: Session,
 ) -> bool:
@@ -392,11 +259,6 @@ def _should_index(
     ):
         return False
 
-    if search_settings_primary:
-        if cc_pair.indexing_trigger is not None:
-            # if a manual indexing trigger is on the cc pair, honor it for primary search settings
-            return True
-
     # if no attempt has ever occurred, we should index regardless of refresh_freq
     if not last_index:
         return True
@@ -429,11 +291,10 @@ def try_creating_indexing_task(
     """
 
     LOCK_TIMEOUT = 30
-    index_attempt_id: int | None = None
 
     # we need to serialize any attempt to trigger indexing since it can be triggered
     # either via celery beat or manually (API call)
-    lock: RedisLock = r.lock(
+    lock = r.lock(
         DANSWER_REDIS_FUNCTION_LOCK_PREFIX + "try_creating_indexing_task",
         timeout=LOCK_TIMEOUT,
     )
@@ -443,15 +304,15 @@ def try_creating_indexing_task(
         return None
 
     try:
-        redis_connector = RedisConnector(tenant_id, cc_pair.id)
-        redis_connector_index = redis_connector.new_index(search_settings.id)
+        rci = RedisConnectorIndexing(cc_pair.id, search_settings.id)
 
         # skip if already indexing
-        if redis_connector_index.fenced:
+        if r.exists(rci.fence_key):
             return None
 
         # skip indexing if the cc_pair is deleting
-        if redis_connector.delete.fenced:
+        rcd = RedisConnectorDeletion(cc_pair.id)
+        if r.exists(rcd.fence_key):
             return None
 
         db_session.refresh(cc_pair)
@@ -459,17 +320,19 @@ def try_creating_indexing_task(
             return None
 
         # add a long running generator task to the queue
-        redis_connector_index.generator_clear()
+        r.delete(rci.generator_complete_key)
+        r.delete(rci.taskset_key)
+
+        custom_task_id = f"{rci.generator_task_id_prefix}_{uuid4()}"
 
         # set a basic fence to start
-        payload = RedisConnectorIndexPayload(
+        fence_value = RedisConnectorIndexingFenceData(
             index_attempt_id=None,
             started=None,
             submitted=datetime.now(timezone.utc),
             celery_task_id=None,
         )
-
-        redis_connector_index.set_fence(payload)
+        r.set(rci.fence_key, fence_value.model_dump_json())
 
         # create the index attempt for tracking purposes
         # code elsewhere checks for index attempts without an associated redis key
@@ -482,12 +345,8 @@ def try_creating_indexing_task(
             db_session=db_session,
         )
 
-        custom_task_id = redis_connector_index.generate_generator_task_id()
-
-        # when the task is sent, we have yet to finish setting up the fence
-        # therefore, the task must contain code that blocks until the fence is ready
         result = celery_app.send_task(
-            DanswerCeleryTask.CONNECTOR_INDEXING_PROXY_TASK,
+            "connector_indexing_proxy_task",
             kwargs=dict(
                 index_attempt_id=index_attempt_id,
                 cc_pair_id=cc_pair.id,
@@ -502,20 +361,17 @@ def try_creating_indexing_task(
             raise RuntimeError("send_task for connector_indexing_proxy_task failed.")
 
         # now fill out the fence with the rest of the data
-        payload.index_attempt_id = index_attempt_id
-        payload.celery_task_id = result.id
-        redis_connector_index.set_fence(payload)
+        fence_value.index_attempt_id = index_attempt_id
+        fence_value.celery_task_id = result.id
+        r.set(rci.fence_key, fence_value.model_dump_json())
     except Exception:
+        r.delete(rci.fence_key)
         task_logger.exception(
-            f"try_creating_indexing_task - Unexpected exception: "
+            f"Unexpected exception: "
             f"tenant={tenant_id} "
             f"cc_pair={cc_pair.id} "
             f"search_settings={search_settings.id}"
         )
-
-        if index_attempt_id is not None:
-            delete_index_attempt(db_session, index_attempt_id)
-        redis_connector_index.set_fence(None)
         return None
     finally:
         if lock.owned():
@@ -524,34 +380,19 @@ def try_creating_indexing_task(
     return index_attempt_id
 
 
-@shared_task(
-    name=DanswerCeleryTask.CONNECTOR_INDEXING_PROXY_TASK,
-    bind=True,
-    acks_late=False,
-    track_started=True,
-)
+@shared_task(name="connector_indexing_proxy_task", acks_late=False, track_started=True)
 def connector_indexing_proxy_task(
-    self: Task,
     index_attempt_id: int,
     cc_pair_id: int,
     search_settings_id: int,
     tenant_id: str | None,
 ) -> None:
     """celery tasks are forked, but forking is unstable.  This proxies work to a spawned task."""
-    task_logger.info(
-        f"Indexing watchdog - starting: attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
-
-    if not self.request.id:
-        task_logger.error("self.request.id is None!")
 
     client = SimpleJobClient()
 
     job = client.submit(
-        connector_indexing_task_wrapper,
+        connector_indexing_task,
         index_attempt_id,
         cc_pair_id,
         search_settings_id,
@@ -561,138 +402,32 @@ def connector_indexing_proxy_task(
     )
 
     if not job:
-        task_logger.info(
-            f"Indexing watchdog - spawn failed: attempt={index_attempt_id} "
-            f"tenant={tenant_id} "
-            f"cc_pair={cc_pair_id} "
-            f"search_settings={search_settings_id}"
-        )
         return
 
-    task_logger.info(
-        f"Indexing watchdog - spawn succeeded: attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
-
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-    redis_connector_index = redis_connector.new_index(search_settings_id)
-
     while True:
-        sleep(5)
-
-        if self.request.id and redis_connector_index.terminating(self.request.id):
-            task_logger.warning(
-                "Indexing watchdog - termination signal detected: "
-                f"attempt={index_attempt_id} "
-                f"tenant={tenant_id} "
-                f"cc_pair={cc_pair_id} "
-                f"search_settings={search_settings_id}"
+        sleep(10)
+        with get_session_with_tenant(tenant_id) as db_session:
+            index_attempt = get_index_attempt(
+                db_session=db_session, index_attempt_id=index_attempt_id
             )
 
-            try:
-                with get_session_with_tenant(tenant_id) as db_session:
-                    mark_attempt_canceled(
-                        index_attempt_id,
-                        db_session,
-                        "Connector termination signal detected",
-                    )
-            finally:
-                # if the DB exceptions, we'll just get an unfriendly failure message
-                # in the UI instead of the cancellation message
-                logger.exception(
-                    "Indexing watchdog - transient exception marking index attempt as canceled: "
-                    f"attempt={index_attempt_id} "
-                    f"tenant={tenant_id} "
-                    f"cc_pair={cc_pair_id} "
-                    f"search_settings={search_settings_id}"
-                )
+            # do nothing for ongoing jobs that haven't been stopped
+            if not job.done():
+                if not index_attempt:
+                    continue
 
-                job.cancel()
+                if not index_attempt.is_finished():
+                    continue
 
+            if job.status == "error":
+                logger.error(job.exception())
+
+            job.release()
             break
 
-        if not job.done():
-            # if the spawned task is still running, restart the check once again
-            # if the index attempt is not in a finished status
-            try:
-                with get_session_with_tenant(tenant_id) as db_session:
-                    index_attempt = get_index_attempt(
-                        db_session=db_session, index_attempt_id=index_attempt_id
-                    )
-
-                    if not index_attempt:
-                        continue
-
-                    if not index_attempt.is_finished():
-                        continue
-            except Exception:
-                # if the DB exceptioned, just restart the check.
-                # polling the index attempt status doesn't need to be strongly consistent
-                logger.exception(
-                    "Indexing watchdog - transient exception looking up index attempt: "
-                    f"attempt={index_attempt_id} "
-                    f"tenant={tenant_id} "
-                    f"cc_pair={cc_pair_id} "
-                    f"search_settings={search_settings_id}"
-                )
-                continue
-
-        if job.status == "error":
-            task_logger.error(
-                "Indexing watchdog - spawned task exceptioned: "
-                f"attempt={index_attempt_id} "
-                f"tenant={tenant_id} "
-                f"cc_pair={cc_pair_id} "
-                f"search_settings={search_settings_id} "
-                f"error={job.exception()}"
-            )
-
-        job.release()
-        break
-
-    task_logger.info(
-        f"Indexing watchdog - finished: attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
     return
 
 
-def connector_indexing_task_wrapper(
-    index_attempt_id: int,
-    cc_pair_id: int,
-    search_settings_id: int,
-    tenant_id: str | None,
-    is_ee: bool,
-) -> int | None:
-    """Just wraps connector_indexing_task so we can log any exceptions before
-    re-raising it."""
-    result: int | None = None
-
-    try:
-        result = connector_indexing_task(
-            index_attempt_id,
-            cc_pair_id,
-            search_settings_id,
-            tenant_id,
-            is_ee,
-        )
-    except:
-        logger.exception(
-            f"connector_indexing_task exceptioned: "
-            f"tenant={tenant_id} "
-            f"index_attempt={index_attempt_id} "
-            f"cc_pair={cc_pair_id} "
-            f"search_settings={search_settings_id}"
-        )
-        raise
-
-    return result
-
-
 def connector_indexing_task(
     index_attempt_id: int,
     cc_pair_id: int,
@@ -711,102 +446,78 @@ def connector_indexing_task(
 
     Returns None if the task did not run (possibly due to a conflict).
     Otherwise, returns an int >= 0 representing the number of indexed docs.
-
-    NOTE: if an exception is raised out of this task, the primary worker will detect
-    that the task transitioned to a "READY" state but the generator_complete_key doesn't exist.
-    This will cause the primary worker to abort the indexing attempt and clean up.
     """
 
-    # Since connector_indexing_proxy_task spawns a new process using this function as
-    # the entrypoint, we init Sentry here.
-    if SENTRY_DSN:
-        sentry_sdk.init(
-            dsn=SENTRY_DSN,
-            traces_sample_rate=0.1,
-        )
-        logger.info("Sentry initialized")
-    else:
-        logger.debug("Sentry DSN not provided, skipping Sentry initialization")
-
-    logger.info(
-        f"Indexing spawned task starting: "
-        f"attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
-
-    attempt_found = False
-    n_final_progress: int | None = None
-
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-    redis_connector_index = redis_connector.new_index(search_settings_id)
+    attempt = None
+    n_final_progress = 0
 
     r = get_redis_client(tenant_id=tenant_id)
 
-    if redis_connector.delete.fenced:
+    rcd = RedisConnectorDeletion(cc_pair_id)
+    if r.exists(rcd.fence_key):
         raise RuntimeError(
             f"Indexing will not start because connector deletion is in progress: "
-            f"attempt={index_attempt_id} "
             f"cc_pair={cc_pair_id} "
-            f"fence={redis_connector.delete.fence_key}"
+            f"fence={rcd.fence_key}"
         )
 
-    if redis_connector.stop.fenced:
+    rcs = RedisConnectorStop(cc_pair_id)
+    if r.exists(rcs.fence_key):
         raise RuntimeError(
             f"Indexing will not start because a connector stop signal was detected: "
-            f"attempt={index_attempt_id} "
             f"cc_pair={cc_pair_id} "
-            f"fence={redis_connector.stop.fence_key}"
+            f"fence={rcs.fence_key}"
         )
 
+    rci = RedisConnectorIndexing(cc_pair_id, search_settings_id)
+
     while True:
-        if not redis_connector_index.fenced:  # The fence must exist
+        # read related data and evaluate/print task progress
+        fence_value = cast(bytes, r.get(rci.fence_key))
+        if fence_value is None:
             raise ValueError(
-                f"connector_indexing_task - fence not found: fence={redis_connector_index.fence_key}"
+                f"connector_indexing_task: fence_value not found: fence={rci.fence_key}"
             )
 
-        payload = redis_connector_index.payload  # The payload must exist
-        if not payload:
-            raise ValueError("connector_indexing_task: payload invalid or not found")
+        try:
+            fence_json = fence_value.decode("utf-8")
+            fence_data = RedisConnectorIndexingFenceData.model_validate_json(
+                cast(str, fence_json)
+            )
+        except ValueError:
+            task_logger.exception(
+                f"connector_indexing_task: fence_data not decodeable: fence={rci.fence_key}"
+            )
+            raise
 
-        if payload.index_attempt_id is None or payload.celery_task_id is None:
-            logger.info(
-                f"connector_indexing_task - Waiting for fence: fence={redis_connector_index.fence_key}"
+        if fence_data.index_attempt_id is None or fence_data.celery_task_id is None:
+            task_logger.info(
+                f"connector_indexing_task - Waiting for fence: fence={rci.fence_key}"
             )
             sleep(1)
             continue
 
-        if payload.index_attempt_id != index_attempt_id:
-            raise ValueError(
-                f"connector_indexing_task - id mismatch. Task may be left over from previous run.: "
-                f"task_index_attempt={index_attempt_id} "
-                f"payload_index_attempt={payload.index_attempt_id}"
-            )
-
-        logger.info(
-            f"connector_indexing_task - Fence found, continuing...: fence={redis_connector_index.fence_key}"
+        task_logger.info(
+            f"connector_indexing_task - Fence found, continuing...: fence={rci.fence_key}"
         )
         break
 
-    # set thread_local=False since we don't control what thread the indexing/pruning
-    # might run our callback with
-    lock: RedisLock = r.lock(
-        redis_connector_index.generator_lock_key,
+    lock = r.lock(
+        rci.generator_lock_key,
         timeout=CELERY_INDEXING_LOCK_TIMEOUT,
-        thread_local=False,
     )
 
     acquired = lock.acquire(blocking=False)
     if not acquired:
-        logger.warning(
+        task_logger.warning(
             f"Indexing task already running, exiting...: "
-            f"index_attempt={index_attempt_id} cc_pair={cc_pair_id} search_settings={search_settings_id}"
+            f"cc_pair={cc_pair_id} search_settings={search_settings_id}"
         )
+        # r.set(rci.generator_complete_key, HTTPStatus.CONFLICT.value)
         return None
 
-    payload.started = datetime.now(timezone.utc)
-    redis_connector_index.set_fence(payload)
+    fence_data.started = datetime.now(timezone.utc)
+    r.set(rci.fence_key, fence_data.model_dump_json())
 
     try:
         with get_session_with_tenant(tenant_id) as db_session:
@@ -815,7 +526,6 @@ def connector_indexing_task(
                 raise ValueError(
                     f"Index attempt not found: index_attempt={index_attempt_id}"
                 )
-            attempt_found = True
 
             cc_pair = get_connector_credential_pair_from_id(
                 cc_pair_id=cc_pair_id,
@@ -835,52 +545,43 @@ def connector_indexing_task(
                     f"Credential not found: cc_pair={cc_pair_id} credential={cc_pair.credential_id}"
                 )
 
-        # define a callback class
-        callback = IndexingCallback(
-            redis_connector.stop.fence_key,
-            redis_connector_index.generator_progress_key,
-            lock,
-            r,
-        )
+            rci = RedisConnectorIndexing(cc_pair_id, search_settings_id)
 
-        logger.info(
-            f"Indexing spawned task running entrypoint: attempt={index_attempt_id} "
-            f"tenant={tenant_id} "
-            f"cc_pair={cc_pair_id} "
-            f"search_settings={search_settings_id}"
-        )
+            # define a callback class
+            callback = RunIndexingCallback(
+                rcs.fence_key, rci.generator_progress_key, lock, r
+            )
 
-        run_indexing_entrypoint(
-            index_attempt_id,
-            tenant_id,
-            cc_pair_id,
-            is_ee,
-            callback=callback,
-        )
+            run_indexing_entrypoint(
+                index_attempt_id,
+                tenant_id,
+                cc_pair_id,
+                is_ee,
+                callback=callback,
+            )
 
-        # get back the total number of indexed docs and return it
-        n_final_progress = redis_connector_index.get_progress()
-        redis_connector_index.set_generator_complete(HTTPStatus.OK.value)
+            # get back the total number of indexed docs and return it
+            generator_progress_value = r.get(rci.generator_progress_key)
+            if generator_progress_value is not None:
+                try:
+                    n_final_progress = int(cast(int, generator_progress_value))
+                except ValueError:
+                    pass
+
+            r.set(rci.generator_complete_key, HTTPStatus.OK.value)
     except Exception as e:
-        logger.exception(
-            f"Indexing spawned task failed: attempt={index_attempt_id} "
-            f"tenant={tenant_id} "
-            f"cc_pair={cc_pair_id} "
-            f"search_settings={search_settings_id}"
-        )
-        if attempt_found:
+        task_logger.exception(f"Indexing failed: cc_pair={cc_pair_id}")
+        if attempt:
             with get_session_with_tenant(tenant_id) as db_session:
-                mark_attempt_failed(index_attempt_id, db_session, failure_reason=str(e))
+                mark_attempt_failed(attempt, db_session, failure_reason=str(e))
 
+        r.delete(rci.generator_lock_key)
+        r.delete(rci.generator_progress_key)
+        r.delete(rci.taskset_key)
+        r.delete(rci.fence_key)
         raise e
     finally:
         if lock.owned():
             lock.release()
 
-    logger.info(
-        f"Indexing spawned task finished: attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
     return n_final_progress

backend/danswer/background/celery/tasks/periodic/tasks.py

@@ -13,13 +13,12 @@ from sqlalchemy.orm import Session
 
 from danswer.background.celery.apps.app_base import task_logger
 from danswer.configs.app_configs import JOB_TIMEOUT
-from danswer.configs.constants import DanswerCeleryTask
 from danswer.configs.constants import PostgresAdvisoryLocks
 from danswer.db.engine import get_session_with_tenant
 
 
 @shared_task(
-    name=DanswerCeleryTask.KOMBU_MESSAGE_CLEANUP_TASK,
+    name="kombu_message_cleanup_task",
     soft_time_limit=JOB_TIMEOUT,
     bind=True,
     base=AbortableTask,

backend/danswer/background/celery/tasks/pruning/tasks.py

@@ -8,12 +8,14 @@ from celery import shared_task
 from celery import Task
 from celery.exceptions import SoftTimeLimitExceeded
 from redis import Redis
-from redis.lock import Lock as RedisLock
 from sqlalchemy.orm import Session
 
 from danswer.background.celery.apps.app_base import task_logger
+from danswer.background.celery.celery_redis import RedisConnectorDeletion
+from danswer.background.celery.celery_redis import RedisConnectorPruning
+from danswer.background.celery.celery_redis import RedisConnectorStop
 from danswer.background.celery.celery_utils import extract_ids_from_runnable_connector
-from danswer.background.celery.tasks.indexing.tasks import IndexingCallback
+from danswer.background.celery.tasks.indexing.tasks import RunIndexingCallback
 from danswer.configs.app_configs import ALLOW_SIMULTANEOUS_PRUNING
 from danswer.configs.app_configs import JOB_TIMEOUT
 from danswer.configs.constants import CELERY_PRUNING_LOCK_TIMEOUT
@@ -21,7 +23,6 @@ from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
 from danswer.configs.constants import DANSWER_REDIS_FUNCTION_LOCK_PREFIX
 from danswer.configs.constants import DanswerCeleryPriority
 from danswer.configs.constants import DanswerCeleryQueues
-from danswer.configs.constants import DanswerCeleryTask
 from danswer.configs.constants import DanswerRedisLocks
 from danswer.connectors.factory import instantiate_connector
 from danswer.connectors.models import InputType
@@ -32,7 +33,6 @@ from danswer.db.document import get_documents_for_connector_credential_pair
 from danswer.db.engine import get_session_with_tenant
 from danswer.db.enums import ConnectorCredentialPairStatus
 from danswer.db.models import ConnectorCredentialPair
-from danswer.redis.redis_connector import RedisConnector
 from danswer.redis.redis_pool import get_redis_client
 from danswer.utils.logger import pruning_ctx
 from danswer.utils.logger import setup_logger
@@ -40,44 +40,8 @@ from danswer.utils.logger import setup_logger
 logger = setup_logger()
 
 
-def _is_pruning_due(cc_pair: ConnectorCredentialPair) -> bool:
-    """Returns boolean indicating if pruning is due.
-
-    Next pruning time is calculated as a delta from the last successful prune, or the
-    last successful indexing if pruning has never succeeded.
-
-    TODO(rkuo): consider whether we should allow pruning to be immediately rescheduled
-    if pruning fails (which is what it does now). A backoff could be reasonable.
-    """
-
-    # skip pruning if no prune frequency is set
-    # pruning can still be forced via the API which will run a pruning task directly
-    if not cc_pair.connector.prune_freq:
-        return False
-
-    # skip pruning if not active
-    if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
-        return False
-
-    # skip pruning if the next scheduled prune time hasn't been reached yet
-    last_pruned = cc_pair.last_pruned
-    if not last_pruned:
-        if not cc_pair.last_successful_index_time:
-            # if we've never indexed, we can't prune
-            return False
-
-        # if never pruned, use the last time the connector indexed successfully
-        last_pruned = cc_pair.last_successful_index_time
-
-    next_prune = last_pruned + timedelta(seconds=cc_pair.connector.prune_freq)
-    if datetime.now(timezone.utc) < next_prune:
-        return False
-
-    return True
-
-
 @shared_task(
-    name=DanswerCeleryTask.CHECK_FOR_PRUNING,
+    name="check_for_pruning",
     soft_time_limit=JOB_TIMEOUT,
     bind=True,
 )
@@ -107,7 +71,7 @@ def check_for_pruning(self: Task, *, tenant_id: str | None) -> None:
                 if not cc_pair:
                     continue
 
-                if not _is_pruning_due(cc_pair):
+                if not is_pruning_due(cc_pair, db_session, r):
                     continue
 
                 tasks_created = try_creating_prune_generator_task(
@@ -128,6 +92,47 @@ def check_for_pruning(self: Task, *, tenant_id: str | None) -> None:
             lock_beat.release()
 
 
+def is_pruning_due(
+    cc_pair: ConnectorCredentialPair,
+    db_session: Session,
+    r: Redis,
+) -> bool:
+    """Returns an int if pruning is triggered.
+    The int represents the number of prune tasks generated (in this case, only one
+    because the task is a long running generator task.)
+    Returns None if no pruning is triggered (due to not being needed or
+    other reasons such as simultaneous pruning restrictions.
+
+    Checks for scheduling related conditions, then delegates the rest of the checks to
+    try_creating_prune_generator_task.
+    """
+
+    # skip pruning if no prune frequency is set
+    # pruning can still be forced via the API which will run a pruning task directly
+    if not cc_pair.connector.prune_freq:
+        return False
+
+    # skip pruning if not active
+    if cc_pair.status != ConnectorCredentialPairStatus.ACTIVE:
+        return False
+
+    # skip pruning if the next scheduled prune time hasn't been reached yet
+    last_pruned = cc_pair.last_pruned
+    if not last_pruned:
+        if not cc_pair.last_successful_index_time:
+            # if we've never indexed, we can't prune
+            return False
+
+        # if never pruned, use the last time the connector indexed successfully
+        last_pruned = cc_pair.last_successful_index_time
+
+    next_prune = last_pruned + timedelta(seconds=cc_pair.connector.prune_freq)
+    if datetime.now(timezone.utc) < next_prune:
+        return False
+
+    return True
+
+
 def try_creating_prune_generator_task(
     celery_app: Celery,
     cc_pair: ConnectorCredentialPair,
@@ -142,11 +147,8 @@ def try_creating_prune_generator_task(
     is used to trigger prunes immediately, e.g. via the web ui.
     """
 
-    redis_connector = RedisConnector(tenant_id, cc_pair.id)
-
     if not ALLOW_SIMULTANEOUS_PRUNING:
-        count = redis_connector.prune.get_active_task_count()
-        if count > 0:
+        for key in r.scan_iter(RedisConnectorPruning.FENCE_PREFIX + "*"):
             return None
 
     LOCK_TIMEOUT = 30
@@ -163,16 +165,15 @@ def try_creating_prune_generator_task(
         return None
 
     try:
+        rcp = RedisConnectorPruning(cc_pair.id)
+
         # skip pruning if already pruning
-        if redis_connector.prune.fenced:
+        if r.exists(rcp.fence_key):
             return None
 
         # skip pruning if the cc_pair is deleting
-        if redis_connector.delete.fenced:
-            return None
-
-        # skip pruning if doc permissions sync is running
-        if redis_connector.permissions.fenced:
+        rcd = RedisConnectorDeletion(cc_pair.id)
+        if r.exists(rcd.fence_key):
             return None
 
         db_session.refresh(cc_pair)
@@ -180,13 +181,13 @@ def try_creating_prune_generator_task(
             return None
 
         # add a long running generator task to the queue
-        redis_connector.prune.generator_clear()
-        redis_connector.prune.taskset_clear()
+        r.delete(rcp.generator_complete_key)
+        r.delete(rcp.taskset_key)
 
-        custom_task_id = f"{redis_connector.prune.generator_task_key}_{uuid4()}"
+        custom_task_id = f"{rcp.generator_task_id_prefix}_{uuid4()}"
 
         celery_app.send_task(
-            DanswerCeleryTask.CONNECTOR_PRUNING_GENERATOR_TASK,
+            "connector_pruning_generator_task",
             kwargs=dict(
                 cc_pair_id=cc_pair.id,
                 connector_id=cc_pair.connector_id,
@@ -199,7 +200,7 @@ def try_creating_prune_generator_task(
         )
 
         # set this only after all tasks have been added
-        redis_connector.prune.set_fence(True)
+        r.set(rcp.fence_key, 1)
     except Exception:
         task_logger.exception(f"Unexpected exception: cc_pair={cc_pair.id}")
         return None
@@ -211,7 +212,7 @@ def try_creating_prune_generator_task(
 
 
 @shared_task(
-    name=DanswerCeleryTask.CONNECTOR_PRUNING_GENERATOR_TASK,
+    name="connector_pruning_generator_task",
     acks_late=False,
     soft_time_limit=JOB_TIMEOUT,
     track_started=True,
@@ -234,18 +235,13 @@ def connector_pruning_generator_task(
     pruning_ctx_dict["request_id"] = self.request.id
     pruning_ctx.set(pruning_ctx_dict)
 
-    task_logger.info(f"Pruning generator starting: cc_pair={cc_pair_id}")
-
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
+    rcp = RedisConnectorPruning(cc_pair_id)
 
     r = get_redis_client(tenant_id=tenant_id)
 
-    # set thread_local=False since we don't control what thread the indexing/pruning
-    # might run our callback with
-    lock: RedisLock = r.lock(
-        DanswerRedisLocks.PRUNING_LOCK_PREFIX + f"_{redis_connector.id}",
+    lock = r.lock(
+        DanswerRedisLocks.PRUNING_LOCK_PREFIX + f"_{rcp._id}",
         timeout=CELERY_PRUNING_LOCK_TIMEOUT,
-        thread_local=False,
     )
 
     acquired = lock.acquire(blocking=False)
@@ -269,11 +265,6 @@ def connector_pruning_generator_task(
                 )
                 return
 
-            task_logger.info(
-                f"Pruning generator running connector: "
-                f"cc_pair={cc_pair_id} "
-                f"connector_source={cc_pair.connector.source}"
-            )
             runnable_connector = instantiate_connector(
                 db_session,
                 cc_pair.connector.source,
@@ -282,13 +273,11 @@ def connector_pruning_generator_task(
                 cc_pair.credential,
             )
 
-            callback = IndexingCallback(
-                redis_connector.stop.fence_key,
-                redis_connector.prune.generator_progress_key,
-                lock,
-                r,
-            )
+            rcs = RedisConnectorStop(cc_pair_id)
 
+            callback = RunIndexingCallback(
+                rcs.fence_key, rcp.generator_progress_key, lock, r
+            )
             # a list of docs in the source
             all_connector_doc_ids: set[str] = extract_ids_from_runnable_connector(
                 runnable_connector, callback
@@ -310,34 +299,36 @@ def connector_pruning_generator_task(
             task_logger.info(
                 f"Pruning set collected: "
                 f"cc_pair={cc_pair_id} "
-                f"connector_source={cc_pair.connector.source} "
-                f"docs_to_remove={len(doc_ids_to_remove)}"
+                f"docs_to_remove={len(doc_ids_to_remove)} "
+                f"doc_source={cc_pair.connector.source}"
             )
 
+            rcp.documents_to_prune = set(doc_ids_to_remove)
+
             task_logger.info(
-                f"RedisConnector.prune.generate_tasks starting. cc_pair={cc_pair_id}"
+                f"RedisConnectorPruning.generate_tasks starting. cc_pair={cc_pair.id}"
             )
-            tasks_generated = redis_connector.prune.generate_tasks(
-                set(doc_ids_to_remove), self.app, db_session, None
+            tasks_generated = rcp.generate_tasks(
+                self.app, db_session, r, None, tenant_id
             )
             if tasks_generated is None:
                 return None
 
             task_logger.info(
-                f"RedisConnector.prune.generate_tasks finished. "
-                f"cc_pair={cc_pair_id} tasks_generated={tasks_generated}"
+                f"RedisConnectorPruning.generate_tasks finished. "
+                f"cc_pair={cc_pair.id} tasks_generated={tasks_generated}"
             )
 
-            redis_connector.prune.generator_complete = tasks_generated
+            r.set(rcp.generator_complete_key, tasks_generated)
     except Exception as e:
         task_logger.exception(
             f"Failed to run pruning: cc_pair={cc_pair_id} connector={connector_id}"
         )
 
-        redis_connector.prune.reset()
+        r.delete(rcp.generator_progress_key)
+        r.delete(rcp.taskset_key)
+        r.delete(rcp.fence_key)
         raise e
     finally:
         if lock.owned():
             lock.release()
-
-        task_logger.info(f"Pruning generator finished: cc_pair={cc_pair_id}")

backend/danswer/background/celery/tasks/shared/RedisConnectorDeletionFenceData.py

@@ -0,0 +1,8 @@
+from datetime import datetime
+
+from pydantic import BaseModel
+
+
+class RedisConnectorDeletionFenceData(BaseModel):
+    num_tasks: int | None
+    submitted: datetime

backend/danswer/background/celery/tasks/shared/RedisConnectorIndexingFenceData.py

@@ -0,0 +1,10 @@
+from datetime import datetime
+
+from pydantic import BaseModel
+
+
+class RedisConnectorIndexingFenceData(BaseModel):
+    index_attempt_id: int | None
+    started: datetime | None
+    submitted: datetime
+    celery_task_id: str | None

backend/danswer/background/celery/tasks/shared/tasks.py

@@ -9,7 +9,6 @@ from tenacity import RetryError
 from danswer.access.access import get_access_for_document
 from danswer.background.celery.apps.app_base import task_logger
 from danswer.background.celery.tasks.shared.RetryDocumentIndex import RetryDocumentIndex
-from danswer.configs.constants import DanswerCeleryTask
 from danswer.db.document import delete_document_by_connector_credential_pair__no_commit
 from danswer.db.document import delete_documents_complete__no_commit
 from danswer.db.document import get_document
@@ -32,7 +31,7 @@ LIGHT_TIME_LIMIT = LIGHT_SOFT_TIME_LIMIT + 15
 
 
 @shared_task(
-    name=DanswerCeleryTask.DOCUMENT_BY_CC_PAIR_CLEANUP_TASK,
+    name="document_by_cc_pair_cleanup_task",
     soft_time_limit=LIGHT_SOFT_TIME_LIMIT,
     time_limit=LIGHT_TIME_LIMIT,
     max_retries=DOCUMENT_BY_CC_PAIR_CLEANUP_MAX_RETRIES,
@@ -60,7 +59,7 @@ def document_by_cc_pair_cleanup_task(
     connector / credential pair from the access list
     (6) delete all relevant entries from postgres
     """
-    task_logger.debug(f"Task start: tenant={tenant_id} doc={document_id}")
+    task_logger.info(f"tenant={tenant_id} doc={document_id}")
 
     try:
         with get_session_with_tenant(tenant_id) as db_session:
@@ -142,9 +141,7 @@ def document_by_cc_pair_cleanup_task(
         return False
     except Exception as ex:
         if isinstance(ex, RetryError):
-            task_logger.warning(
-                f"Tenacity retry failed: num_attempts={ex.last_attempt.attempt_number}"
-            )
+            task_logger.info(f"Retry failed: {ex.last_attempt.attempt_number}")
 
             # only set the inner exception if it is of type Exception
             e_temp = ex.last_attempt.exception()
@@ -174,21 +171,11 @@ def document_by_cc_pair_cleanup_task(
         else:
             # This is the last attempt! mark the document as dirty in the db so that it
             # eventually gets fixed out of band via stale document reconciliation
-            task_logger.warning(
-                f"Max celery task retries reached. Marking doc as dirty for reconciliation: "
+            task_logger.info(
+                f"Max retries reached. Marking doc as dirty for reconciliation: "
                 f"tenant={tenant_id} doc={document_id}"
             )
-            with get_session_with_tenant(tenant_id) as db_session:
-                # delete the cc pair relationship now and let reconciliation clean it up
-                # in vespa
-                delete_document_by_connector_credential_pair__no_commit(
-                    db_session=db_session,
-                    document_id=document_id,
-                    connector_credential_pair_identifier=ConnectorCredentialPairIdentifier(
-                        connector_id=connector_id,
-                        credential_id=credential_id,
-                    ),
-                )
+            with get_session_with_tenant(tenant_id):
                 mark_document_as_modified(document_id, db_session)
         return False
 

backend/danswer/background/celery/tasks/vespa/tasks.py

@@ -5,6 +5,7 @@ from http import HTTPStatus
 from typing import cast
 
 import httpx
+import redis
 from celery import Celery
 from celery import shared_task
 from celery import Task
@@ -12,23 +13,32 @@ from celery.exceptions import SoftTimeLimitExceeded
 from celery.result import AsyncResult
 from celery.states import READY_STATES
 from redis import Redis
-from redis.lock import Lock as RedisLock
 from sqlalchemy.orm import Session
 from tenacity import RetryError
 
 from danswer.access.access import get_access_for_document
 from danswer.background.celery.apps.app_base import task_logger
 from danswer.background.celery.celery_redis import celery_get_queue_length
+from danswer.background.celery.celery_redis import RedisConnectorCredentialPair
+from danswer.background.celery.celery_redis import RedisConnectorDeletion
+from danswer.background.celery.celery_redis import RedisConnectorIndexing
+from danswer.background.celery.celery_redis import RedisConnectorPruning
+from danswer.background.celery.celery_redis import RedisDocumentSet
+from danswer.background.celery.celery_redis import RedisUserGroup
+from danswer.background.celery.tasks.shared.RedisConnectorDeletionFenceData import (
+    RedisConnectorDeletionFenceData,
+)
+from danswer.background.celery.tasks.shared.RedisConnectorIndexingFenceData import (
+    RedisConnectorIndexingFenceData,
+)
 from danswer.background.celery.tasks.shared.RetryDocumentIndex import RetryDocumentIndex
 from danswer.background.celery.tasks.shared.tasks import LIGHT_SOFT_TIME_LIMIT
 from danswer.background.celery.tasks.shared.tasks import LIGHT_TIME_LIMIT
 from danswer.configs.app_configs import JOB_TIMEOUT
 from danswer.configs.constants import CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT
 from danswer.configs.constants import DanswerCeleryQueues
-from danswer.configs.constants import DanswerCeleryTask
 from danswer.configs.constants import DanswerRedisLocks
 from danswer.db.connector import fetch_connector_by_id
-from danswer.db.connector import mark_cc_pair_as_permissions_synced
 from danswer.db.connector import mark_ccpair_as_pruned
 from danswer.db.connector_credential_pair import add_deletion_failure_message
 from danswer.db.connector_credential_pair import (
@@ -49,24 +59,15 @@ from danswer.db.document_set import mark_document_set_as_synced
 from danswer.db.engine import get_session_with_tenant
 from danswer.db.enums import IndexingStatus
 from danswer.db.index_attempt import delete_index_attempts
+from danswer.db.index_attempt import get_all_index_attempts_by_status
 from danswer.db.index_attempt import get_index_attempt
 from danswer.db.index_attempt import mark_attempt_failed
 from danswer.db.models import DocumentSet
+from danswer.db.models import IndexAttempt
 from danswer.document_index.document_index_utils import get_both_index_names
 from danswer.document_index.factory import get_default_document_index
 from danswer.document_index.interfaces import VespaDocumentFields
-from danswer.redis.redis_connector import RedisConnector
-from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
-from danswer.redis.redis_connector_delete import RedisConnectorDelete
-from danswer.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSync
-from danswer.redis.redis_connector_doc_perm_sync import (
-    RedisConnectorPermissionSyncPayload,
-)
-from danswer.redis.redis_connector_index import RedisConnectorIndex
-from danswer.redis.redis_connector_prune import RedisConnectorPrune
-from danswer.redis.redis_document_set import RedisDocumentSet
 from danswer.redis.redis_pool import get_redis_client
-from danswer.redis.redis_usergroup import RedisUserGroup
 from danswer.utils.logger import setup_logger
 from danswer.utils.variable_functionality import fetch_versioned_implementation
 from danswer.utils.variable_functionality import (
@@ -81,7 +82,7 @@ logger = setup_logger()
 # celery auto associates tasks created inside another task,
 # which bloats the result metadata considerably. trail=False prevents this.
 @shared_task(
-    name=DanswerCeleryTask.CHECK_FOR_VESPA_SYNC_TASK,
+    name="check_for_vespa_sync_task",
     soft_time_limit=JOB_TIMEOUT,
     trail=False,
     bind=True,
@@ -166,7 +167,7 @@ def try_generate_stale_document_sync_tasks(
     celery_app: Celery,
     db_session: Session,
     r: Redis,
-    lock_beat: RedisLock,
+    lock_beat: redis.lock.Lock,
     tenant_id: str | None,
 ) -> int | None:
     # the fence is up, do nothing
@@ -184,34 +185,30 @@ def try_generate_stale_document_sync_tasks(
         f"Stale documents found (at least {stale_doc_count}). Generating sync tasks by cc pair."
     )
 
-    task_logger.info(
-        "RedisConnector.generate_tasks starting by cc_pair. "
-        "Documents spanning multiple cc_pairs will only be synced once."
-    )
-
-    docs_to_skip: set[str] = set()
+    task_logger.info("RedisConnector.generate_tasks starting by cc_pair.")
 
     # rkuo: we could technically sync all stale docs in one big pass.
     # but I feel it's more understandable to group the docs by cc_pair
     total_tasks_generated = 0
     cc_pairs = get_connector_credential_pairs(db_session)
     for cc_pair in cc_pairs:
-        rc = RedisConnectorCredentialPair(tenant_id, cc_pair.id)
-        rc.set_skip_docs(docs_to_skip)
-        result = rc.generate_tasks(celery_app, db_session, r, lock_beat, tenant_id)
+        rc = RedisConnectorCredentialPair(cc_pair.id)
+        tasks_generated = rc.generate_tasks(
+            celery_app, db_session, r, lock_beat, tenant_id
+        )
 
-        if result is None:
+        if tasks_generated is None:
             continue
 
-        if result[1] == 0:
+        if tasks_generated == 0:
             continue
 
         task_logger.info(
             f"RedisConnector.generate_tasks finished for single cc_pair. "
-            f"cc_pair={cc_pair.id} tasks_generated={result[0]} tasks_possible={result[1]}"
+            f"cc_pair_id={cc_pair.id} tasks_generated={tasks_generated}"
         )
 
-        total_tasks_generated += result[0]
+        total_tasks_generated += tasks_generated
 
     task_logger.info(
         f"RedisConnector.generate_tasks finished for all cc_pairs. total_tasks_generated={total_tasks_generated}"
@@ -226,15 +223,15 @@ def try_generate_document_set_sync_tasks(
     document_set_id: int,
     db_session: Session,
     r: Redis,
-    lock_beat: RedisLock,
+    lock_beat: redis.lock.Lock,
     tenant_id: str | None,
 ) -> int | None:
     lock_beat.reacquire()
 
-    rds = RedisDocumentSet(tenant_id, document_set_id)
+    rds = RedisDocumentSet(document_set_id)
 
     # don't generate document set sync tasks if tasks are still pending
-    if rds.fenced:
+    if r.exists(rds.fence_key):
         return None
 
     # don't generate sync tasks if we're up to date
@@ -254,11 +251,12 @@ def try_generate_document_set_sync_tasks(
     )
 
     # Add all documents that need to be updated into the queue
-    result = rds.generate_tasks(celery_app, db_session, r, lock_beat, tenant_id)
-    if result is None:
+    tasks_generated = rds.generate_tasks(
+        celery_app, db_session, r, lock_beat, tenant_id
+    )
+    if tasks_generated is None:
         return None
 
-    tasks_generated = result[0]
     # Currently we are allowing the sync to proceed with 0 tasks.
     # It's possible for sets/groups to be generated initially with no entries
     # and they still need to be marked as up to date.
@@ -267,11 +265,11 @@ def try_generate_document_set_sync_tasks(
 
     task_logger.info(
         f"RedisDocumentSet.generate_tasks finished. "
-        f"document_set={document_set.id} tasks_generated={tasks_generated}"
+        f"document_set_id={document_set.id} tasks_generated={tasks_generated}"
     )
 
     # set this only after all tasks have been added
-    rds.set_fence(tasks_generated)
+    r.set(rds.fence_key, tasks_generated)
     return tasks_generated
 
 
@@ -280,14 +278,15 @@ def try_generate_user_group_sync_tasks(
     usergroup_id: int,
     db_session: Session,
     r: Redis,
-    lock_beat: RedisLock,
+    lock_beat: redis.lock.Lock,
     tenant_id: str | None,
 ) -> int | None:
     lock_beat.reacquire()
 
-    rug = RedisUserGroup(tenant_id, usergroup_id)
-    if rug.fenced:
-        # don't generate sync tasks if tasks are still pending
+    rug = RedisUserGroup(usergroup_id)
+
+    # don't generate sync tasks if tasks are still pending
+    if r.exists(rug.fence_key):
         return None
 
     # race condition with the monitor/cleanup function if we use a cached result!
@@ -309,11 +308,12 @@ def try_generate_user_group_sync_tasks(
     task_logger.info(
         f"RedisUserGroup.generate_tasks starting. usergroup_id={usergroup.id}"
     )
-    result = rug.generate_tasks(celery_app, db_session, r, lock_beat, tenant_id)
-    if result is None:
+    tasks_generated = rug.generate_tasks(
+        celery_app, db_session, r, lock_beat, tenant_id
+    )
+    if tasks_generated is None:
         return None
 
-    tasks_generated = result[0]
     # Currently we are allowing the sync to proceed with 0 tasks.
     # It's possible for sets/groups to be generated initially with no entries
     # and they still need to be marked as up to date.
@@ -322,11 +322,11 @@ def try_generate_user_group_sync_tasks(
 
     task_logger.info(
         f"RedisUserGroup.generate_tasks finished. "
-        f"usergroup={usergroup.id} tasks_generated={tasks_generated}"
+        f"usergroup_id={usergroup.id} tasks_generated={tasks_generated}"
     )
 
     # set this only after all tasks have been added
-    rug.set_fence(tasks_generated)
+    r.set(rug.fence_key, tasks_generated)
     return tasks_generated
 
 
@@ -352,7 +352,7 @@ def monitor_connector_taskset(r: Redis) -> None:
 
 
 def monitor_document_set_taskset(
-    tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
+    key_bytes: bytes, r: Redis, db_session: Session
 ) -> None:
     fence_key = key_bytes.decode("utf-8")
     document_set_id_str = RedisDocumentSet.get_id_from_fence_key(fence_key)
@@ -362,12 +362,16 @@ def monitor_document_set_taskset(
 
     document_set_id = int(document_set_id_str)
 
-    rds = RedisDocumentSet(tenant_id, document_set_id)
-    if not rds.fenced:
+    rds = RedisDocumentSet(document_set_id)
+
+    fence_value = r.get(rds.fence_key)
+    if fence_value is None:
         return
 
-    initial_count = rds.payload
-    if initial_count is None:
+    try:
+        initial_count = int(cast(int, fence_value))
+    except ValueError:
+        task_logger.error("The value is not an integer.")
         return
 
     count = cast(int, r.scard(rds.taskset_key))
@@ -395,38 +399,48 @@ def monitor_document_set_taskset(
                 f"Successfully synced document set: document_set={document_set_id}"
             )
 
-    rds.reset()
+    r.delete(rds.taskset_key)
+    r.delete(rds.fence_key)
 
 
 def monitor_connector_deletion_taskset(
-    tenant_id: str | None, key_bytes: bytes, r: Redis
+    key_bytes: bytes, r: Redis, tenant_id: str | None
 ) -> None:
     fence_key = key_bytes.decode("utf-8")
-    cc_pair_id_str = RedisConnector.get_id_from_fence_key(fence_key)
+    cc_pair_id_str = RedisConnectorDeletion.get_id_from_fence_key(fence_key)
     if cc_pair_id_str is None:
         task_logger.warning(f"could not parse cc_pair_id from {fence_key}")
         return
 
     cc_pair_id = int(cc_pair_id_str)
 
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
+    rcd = RedisConnectorDeletion(cc_pair_id)
 
-    fence_data = redis_connector.delete.payload
-    if not fence_data:
-        task_logger.warning(
-            f"Connector deletion - fence payload invalid: cc_pair={cc_pair_id}"
+    # read related data and evaluate/print task progress
+    fence_value = cast(bytes, r.get(rcd.fence_key))
+    if fence_value is None:
+        return
+
+    try:
+        fence_json = fence_value.decode("utf-8")
+        fence_data = RedisConnectorDeletionFenceData.model_validate_json(
+            cast(str, fence_json)
         )
-        return
+    except ValueError:
+        task_logger.exception(
+            "monitor_ccpair_indexing_taskset: fence_data not decodeable."
+        )
+        raise
 
+    # the fence is setting up but isn't ready yet
     if fence_data.num_tasks is None:
-        # the fence is setting up but isn't ready yet
         return
 
-    remaining = redis_connector.delete.get_remaining()
+    count = cast(int, r.scard(rcd.taskset_key))
     task_logger.info(
-        f"Connector deletion progress: cc_pair={cc_pair_id} remaining={remaining} initial={fence_data.num_tasks}"
+        f"Connector deletion progress: cc_pair={cc_pair_id} remaining={count} initial={fence_data.num_tasks}"
     )
-    if remaining > 0:
+    if count > 0:
         return
 
     with get_session_with_tenant(tenant_id) as db_session:
@@ -442,22 +456,11 @@ def monitor_connector_deletion_taskset(
                 db_session, cc_pair.connector_id, cc_pair.credential_id
             )
             if len(doc_ids) > 0:
-                # NOTE(rkuo): if this happens, documents somehow got added while
-                # deletion was in progress. Likely a bug gating off pruning and indexing
-                # work before deletion starts.
+                # if this happens, documents somehow got added while deletion was in progress. Likely a bug
+                # gating off pruning and indexing work before deletion starts
                 task_logger.warning(
-                    "Connector deletion - documents still found after taskset completion. "
-                    "Clearing the current deletion attempt and allowing deletion to restart: "
-                    f"cc_pair={cc_pair_id} "
-                    f"docs_deleted={fence_data.num_tasks} "
-                    f"docs_remaining={len(doc_ids)}"
-                )
-
-                # We don't want to waive off why we get into this state, but resetting
-                # our attempt and letting the deletion restart is a good way to recover
-                redis_connector.delete.reset()
-                raise RuntimeError(
-                    "Connector deletion - documents still found after taskset completion"
+                    f"Connector deletion - documents still found after taskset completion: "
+                    f"cc_pair={cc_pair_id} num={len(doc_ids)}"
                 )
 
             # clean up the rest of the related Postgres entities
@@ -521,14 +524,15 @@ def monitor_connector_deletion_taskset(
         f"docs_deleted={fence_data.num_tasks}"
     )
 
-    redis_connector.delete.reset()
+    r.delete(rcd.taskset_key)
+    r.delete(rcd.fence_key)
 
 
 def monitor_ccpair_pruning_taskset(
-    tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
+    key_bytes: bytes, r: Redis, db_session: Session
 ) -> None:
     fence_key = key_bytes.decode("utf-8")
-    cc_pair_id_str = RedisConnector.get_id_from_fence_key(fence_key)
+    cc_pair_id_str = RedisConnectorPruning.get_id_from_fence_key(fence_key)
     if cc_pair_id_str is None:
         task_logger.warning(
             f"monitor_ccpair_pruning_taskset: could not parse cc_pair_id from {fence_key}"
@@ -537,76 +541,46 @@ def monitor_ccpair_pruning_taskset(
 
     cc_pair_id = int(cc_pair_id_str)
 
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-    if not redis_connector.prune.fenced:
+    rcp = RedisConnectorPruning(cc_pair_id)
+
+    fence_value = r.get(rcp.fence_key)
+    if fence_value is None:
         return
 
-    initial = redis_connector.prune.generator_complete
-    if initial is None:
+    generator_value = r.get(rcp.generator_complete_key)
+    if generator_value is None:
         return
 
-    remaining = redis_connector.prune.get_remaining()
+    try:
+        initial_count = int(cast(int, generator_value))
+    except ValueError:
+        task_logger.error("The value is not an integer.")
+        return
+
+    count = cast(int, r.scard(rcp.taskset_key))
     task_logger.info(
-        f"Connector pruning progress: cc_pair={cc_pair_id} remaining={remaining} initial={initial}"
+        f"Connector pruning progress: cc_pair_id={cc_pair_id} remaining={count} initial={initial_count}"
     )
-    if remaining > 0:
+    if count > 0:
         return
 
     mark_ccpair_as_pruned(int(cc_pair_id), db_session)
     task_logger.info(
-        f"Successfully pruned connector credential pair. cc_pair={cc_pair_id}"
+        f"Successfully pruned connector credential pair. cc_pair_id={cc_pair_id}"
     )
 
-    redis_connector.prune.taskset_clear()
-    redis_connector.prune.generator_clear()
-    redis_connector.prune.set_fence(False)
-
-
-def monitor_ccpair_permissions_taskset(
-    tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
-) -> None:
-    fence_key = key_bytes.decode("utf-8")
-    cc_pair_id_str = RedisConnector.get_id_from_fence_key(fence_key)
-    if cc_pair_id_str is None:
-        task_logger.warning(
-            f"monitor_ccpair_permissions_taskset: could not parse cc_pair_id from {fence_key}"
-        )
-        return
-
-    cc_pair_id = int(cc_pair_id_str)
-
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-    if not redis_connector.permissions.fenced:
-        return
-
-    initial = redis_connector.permissions.generator_complete
-    if initial is None:
-        return
-
-    remaining = redis_connector.permissions.get_remaining()
-    task_logger.info(
-        f"Permissions sync progress: cc_pair={cc_pair_id} remaining={remaining} initial={initial}"
-    )
-    if remaining > 0:
-        return
-
-    payload: RedisConnectorPermissionSyncPayload | None = (
-        redis_connector.permissions.payload
-    )
-    start_time: datetime | None = payload.started if payload else None
-
-    mark_cc_pair_as_permissions_synced(db_session, int(cc_pair_id), start_time)
-    task_logger.info(f"Successfully synced permissions for cc_pair={cc_pair_id}")
-
-    redis_connector.permissions.reset()
+    r.delete(rcp.taskset_key)
+    r.delete(rcp.generator_progress_key)
+    r.delete(rcp.generator_complete_key)
+    r.delete(rcp.fence_key)
 
 
 def monitor_ccpair_indexing_taskset(
-    tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
+    key_bytes: bytes, r: Redis, db_session: Session
 ) -> None:
     # if the fence doesn't exist, there's nothing to do
     fence_key = key_bytes.decode("utf-8")
-    composite_id = RedisConnector.get_id_from_fence_key(fence_key)
+    composite_id = RedisConnectorIndexing.get_id_from_fence_key(fence_key)
     if composite_id is None:
         task_logger.warning(
             f"monitor_ccpair_indexing_taskset: could not parse composite_id from {fence_key}"
@@ -621,94 +595,103 @@ def monitor_ccpair_indexing_taskset(
     cc_pair_id = int(parts[0])
     search_settings_id = int(parts[1])
 
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
-    redis_connector_index = redis_connector.new_index(search_settings_id)
-    if not redis_connector_index.fenced:
+    rci = RedisConnectorIndexing(cc_pair_id, search_settings_id)
+
+    # read related data and evaluate/print task progress
+    fence_value = cast(bytes, r.get(rci.fence_key))
+    if fence_value is None:
         return
 
-    payload = redis_connector_index.payload
-    if not payload:
-        return
-
-    elapsed_submitted = datetime.now(timezone.utc) - payload.submitted
-
-    progress = redis_connector_index.get_progress()
-    if progress is not None:
-        task_logger.info(
-            f"Connector indexing progress: cc_pair={cc_pair_id} "
-            f"search_settings={search_settings_id} "
-            f"progress={progress} "
-            f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
+    try:
+        fence_json = fence_value.decode("utf-8")
+        fence_data = RedisConnectorIndexingFenceData.model_validate_json(
+            cast(str, fence_json)
         )
+    except ValueError:
+        task_logger.exception(
+            "monitor_ccpair_indexing_taskset: fence_data not decodeable."
+        )
+        raise
 
-    if payload.index_attempt_id is None or payload.celery_task_id is None:
+    elapsed_submitted = datetime.now(timezone.utc) - fence_data.submitted
+
+    generator_progress_value = r.get(rci.generator_progress_key)
+    if generator_progress_value is not None:
+        try:
+            progress_count = int(cast(int, generator_progress_value))
+
+            task_logger.info(
+                f"Connector indexing progress: cc_pair_id={cc_pair_id} "
+                f"search_settings_id={search_settings_id} "
+                f"progress={progress_count} "
+                f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
+            )
+        except ValueError:
+            task_logger.error(
+                "monitor_ccpair_indexing_taskset: generator_progress_value is not an integer."
+            )
+
+    if fence_data.index_attempt_id is None or fence_data.celery_task_id is None:
         # the task is still setting up
         return
 
+    # Read result state BEFORE generator_complete_key to avoid a race condition
     # never use any blocking methods on the result from inside a task!
-    result: AsyncResult = AsyncResult(payload.celery_task_id)
+    result: AsyncResult = AsyncResult(fence_data.celery_task_id)
+    result_state = result.state
 
-    # inner/outer/inner double check pattern to avoid race conditions when checking for
-    # bad state
+    generator_complete_value = r.get(rci.generator_complete_key)
+    if generator_complete_value is None:
+        if result_state in READY_STATES:
+            # IF the task state is READY, THEN generator_complete should be set
+            # if it isn't, then the worker crashed
+            task_logger.info(
+                f"Connector indexing aborted: "
+                f"cc_pair_id={cc_pair_id} "
+                f"search_settings_id={search_settings_id} "
+                f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
+            )
 
-    # inner = get_completion / generator_complete not signaled
-    # outer = result.state in READY state
-    status_int = redis_connector_index.get_completion()
-    if status_int is None:  # inner signal not set ... possible error
-        task_state = result.state
-        if (
-            task_state in READY_STATES
-        ):  # outer signal in terminal state ... possible error
-            # Now double check!
-            if redis_connector_index.get_completion() is None:
-                # inner signal still not set (and cannot change when outer result_state is READY)
-                # Task is finished but generator complete isn't set.
-                # We have a problem! Worker may have crashed.
-                task_result = str(result.result)
-                task_traceback = str(result.traceback)
-
-                msg = (
-                    f"Connector indexing aborted or exceptioned: "
-                    f"attempt={payload.index_attempt_id} "
-                    f"celery_task={payload.celery_task_id} "
-                    f"cc_pair={cc_pair_id} "
-                    f"search_settings={search_settings_id} "
-                    f"elapsed_submitted={elapsed_submitted.total_seconds():.2f} "
-                    f"result.state={task_state} "
-                    f"result.result={task_result} "
-                    f"result.traceback={task_traceback}"
+            index_attempt = get_index_attempt(db_session, fence_data.index_attempt_id)
+            if index_attempt:
+                mark_attempt_failed(
+                    index_attempt=index_attempt,
+                    db_session=db_session,
+                    failure_reason="Connector indexing aborted or exceptioned.",
                 )
-                task_logger.warning(msg)
 
-                index_attempt = get_index_attempt(db_session, payload.index_attempt_id)
-                if index_attempt:
-                    if (
-                        index_attempt.status != IndexingStatus.CANCELED
-                        and index_attempt.status != IndexingStatus.FAILED
-                    ):
-                        mark_attempt_failed(
-                            index_attempt_id=payload.index_attempt_id,
-                            db_session=db_session,
-                            failure_reason=msg,
-                        )
-
-                redis_connector_index.reset()
+            r.delete(rci.generator_lock_key)
+            r.delete(rci.taskset_key)
+            r.delete(rci.generator_progress_key)
+            r.delete(rci.generator_complete_key)
+            r.delete(rci.fence_key)
         return
 
-    status_enum = HTTPStatus(status_int)
+    status_enum = HTTPStatus.INTERNAL_SERVER_ERROR
+    try:
+        status_value = int(cast(int, generator_complete_value))
+        status_enum = HTTPStatus(status_value)
+    except ValueError:
+        task_logger.error(
+            f"monitor_ccpair_indexing_taskset: "
+            f"generator_complete_value=f{generator_complete_value} could not be parsed."
+        )
 
     task_logger.info(
-        f"Connector indexing finished: cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id} "
-        f"progress={progress} "
+        f"Connector indexing finished: cc_pair_id={cc_pair_id} "
+        f"search_settings_id={search_settings_id} "
         f"status={status_enum.name} "
         f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
     )
 
-    redis_connector_index.reset()
+    r.delete(rci.generator_lock_key)
+    r.delete(rci.taskset_key)
+    r.delete(rci.generator_progress_key)
+    r.delete(rci.generator_complete_key)
+    r.delete(rci.fence_key)
 
 
-@shared_task(name=DanswerCeleryTask.MONITOR_VESPA_SYNC, soft_time_limit=300, bind=True)
+@shared_task(name="monitor_vespa_sync", soft_time_limit=300, bind=True)
 def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
     """This is a celery beat task that monitors and finalizes metadata sync tasksets.
     It scans for fence values and then gets the counts of any associated tasksets.
@@ -717,11 +700,11 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
     This task lock timeout is CELERY_METADATA_SYNC_BEAT_LOCK_TIMEOUT seconds, so don't
     do anything too expensive in this function!
 
-    Returns True if the task actually did work, False if it exited early to prevent overlap
+    Returns True if the task actually did work, False
     """
     r = get_redis_client(tenant_id=tenant_id)
 
-    lock_beat: RedisLock = r.lock(
+    lock_beat: redis.lock.Lock = r.lock(
         DanswerRedisLocks.MONITOR_VESPA_SYNC_BEAT_LOCK,
         timeout=CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT,
     )
@@ -733,7 +716,7 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
 
         # print current queue lengths
         r_celery = self.app.broker_connection().channel().client  # type: ignore
-        n_celery = celery_get_queue_length("celery", r_celery)
+        n_celery = celery_get_queue_length("celery", r)
         n_indexing = celery_get_queue_length(
             DanswerCeleryQueues.CONNECTOR_INDEXING, r_celery
         )
@@ -746,33 +729,49 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
         n_pruning = celery_get_queue_length(
             DanswerCeleryQueues.CONNECTOR_PRUNING, r_celery
         )
-        n_permissions_sync = celery_get_queue_length(
-            DanswerCeleryQueues.CONNECTOR_DOC_PERMISSIONS_SYNC, r_celery
-        )
 
         task_logger.info(
             f"Queue lengths: celery={n_celery} "
             f"indexing={n_indexing} "
             f"sync={n_sync} "
             f"deletion={n_deletion} "
-            f"pruning={n_pruning} "
-            f"permissions_sync={n_permissions_sync} "
+            f"pruning={n_pruning}"
         )
 
+        # do some cleanup before clearing fences
+        # check the db for any outstanding index attempts
+        with get_session_with_tenant(tenant_id) as db_session:
+            attempts: list[IndexAttempt] = []
+            attempts.extend(
+                get_all_index_attempts_by_status(IndexingStatus.NOT_STARTED, db_session)
+            )
+            attempts.extend(
+                get_all_index_attempts_by_status(IndexingStatus.IN_PROGRESS, db_session)
+            )
+
+            for a in attempts:
+                # if attempts exist in the db but we don't detect them in redis, mark them as failed
+                rci = RedisConnectorIndexing(
+                    a.connector_credential_pair_id, a.search_settings_id
+                )
+                failure_reason = f"Unknown index attempt {a.id}. Might be left over from a process restart."
+                if not r.exists(rci.fence_key):
+                    mark_attempt_failed(a, db_session, failure_reason=failure_reason)
+
         lock_beat.reacquire()
         if r.exists(RedisConnectorCredentialPair.get_fence_key()):
             monitor_connector_taskset(r)
 
         lock_beat.reacquire()
-        for key_bytes in r.scan_iter(RedisConnectorDelete.FENCE_PREFIX + "*"):
+        for key_bytes in r.scan_iter(RedisConnectorDeletion.FENCE_PREFIX + "*"):
             lock_beat.reacquire()
-            monitor_connector_deletion_taskset(tenant_id, key_bytes, r)
+            monitor_connector_deletion_taskset(key_bytes, r, tenant_id)
 
         lock_beat.reacquire()
         for key_bytes in r.scan_iter(RedisDocumentSet.FENCE_PREFIX + "*"):
             lock_beat.reacquire()
             with get_session_with_tenant(tenant_id) as db_session:
-                monitor_document_set_taskset(tenant_id, key_bytes, r, db_session)
+                monitor_document_set_taskset(key_bytes, r, db_session)
 
         lock_beat.reacquire()
         for key_bytes in r.scan_iter(RedisUserGroup.FENCE_PREFIX + "*"):
@@ -783,25 +782,19 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
                 noop_fallback,
             )
             with get_session_with_tenant(tenant_id) as db_session:
-                monitor_usergroup_taskset(tenant_id, key_bytes, r, db_session)
+                monitor_usergroup_taskset(key_bytes, r, db_session)
 
         lock_beat.reacquire()
-        for key_bytes in r.scan_iter(RedisConnectorPrune.FENCE_PREFIX + "*"):
+        for key_bytes in r.scan_iter(RedisConnectorPruning.FENCE_PREFIX + "*"):
             lock_beat.reacquire()
             with get_session_with_tenant(tenant_id) as db_session:
-                monitor_ccpair_pruning_taskset(tenant_id, key_bytes, r, db_session)
+                monitor_ccpair_pruning_taskset(key_bytes, r, db_session)
 
         lock_beat.reacquire()
-        for key_bytes in r.scan_iter(RedisConnectorIndex.FENCE_PREFIX + "*"):
+        for key_bytes in r.scan_iter(RedisConnectorIndexing.FENCE_PREFIX + "*"):
             lock_beat.reacquire()
             with get_session_with_tenant(tenant_id) as db_session:
-                monitor_ccpair_indexing_taskset(tenant_id, key_bytes, r, db_session)
-
-        lock_beat.reacquire()
-        for key_bytes in r.scan_iter(RedisConnectorPermissionSync.FENCE_PREFIX + "*"):
-            lock_beat.reacquire()
-            with get_session_with_tenant(tenant_id) as db_session:
-                monitor_ccpair_permissions_taskset(tenant_id, key_bytes, r, db_session)
+                monitor_ccpair_indexing_taskset(key_bytes, r, db_session)
 
         # uncomment for debugging if needed
         # r_celery = celery_app.broker_connection().channel().client
@@ -819,7 +812,7 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
 
 
 @shared_task(
-    name=DanswerCeleryTask.VESPA_METADATA_SYNC_TASK,
+    name="vespa_metadata_sync_task",
     bind=True,
     soft_time_limit=LIGHT_SOFT_TIME_LIMIT,
     time_limit=LIGHT_TIME_LIMIT,
@@ -873,9 +866,7 @@ def vespa_metadata_sync_task(
         )
     except Exception as ex:
         if isinstance(ex, RetryError):
-            task_logger.warning(
-                f"Tenacity retry failed: num_attempts={ex.last_attempt.attempt_number}"
-            )
+            task_logger.warning(f"Retry failed: {ex.last_attempt.attempt_number}")
 
             # only set the inner exception if it is of type Exception
             e_temp = ex.last_attempt.exception()

backend/danswer/background/celery/versioned_apps/beat.py

@@ -1,8 +1,8 @@
 """Factory stub for running celery worker / celery beat."""
-from celery import Celery
-
-from danswer.background.celery.apps.beat import celery_app
+from danswer.utils.variable_functionality import fetch_versioned_implementation
 from danswer.utils.variable_functionality import set_is_ee_based_on_env_variable
 
 set_is_ee_based_on_env_variable()
-app: Celery = celery_app
+app = fetch_versioned_implementation(
+    "danswer.background.celery.apps.beat", "celery_app"
+)

backend/danswer/background/celery/versioned_apps/primary.py

@@ -1,10 +1,8 @@
 """Factory stub for running celery worker / celery beat."""
-from celery import Celery
-
 from danswer.utils.variable_functionality import fetch_versioned_implementation
 from danswer.utils.variable_functionality import set_is_ee_based_on_env_variable
 
 set_is_ee_based_on_env_variable()
-app: Celery = fetch_versioned_implementation(
+app = fetch_versioned_implementation(
     "danswer.background.celery.apps.primary", "celery_app"
 )

backend/danswer/background/indexing/job_client.py

@@ -29,26 +29,18 @@ JobStatusType = (
 def _initializer(
     func: Callable, args: list | tuple, kwargs: dict[str, Any] | None = None
 ) -> Any:
-    """Initialize the child process with a fresh SQLAlchemy Engine.
+    """Ensure the parent proc's database connections are not touched
+    in the new connection pool
 
-    Based on SQLAlchemy's recommendations to handle multiprocessing:
+    Based on the recommended approach in the SQLAlchemy docs found:
     https://docs.sqlalchemy.org/en/20/core/pooling.html#using-connection-pools-with-multiprocessing-or-os-fork
     """
     if kwargs is None:
         kwargs = {}
 
     logger.info("Initializing spawned worker child process.")
-
-    # Reset the engine in the child process
-    SqlEngine.reset_engine()
-
-    # Optionally set a custom app name for database logging purposes
     SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_INDEXING_CHILD_APP_NAME)
-
-    # Initialize a new engine with desired parameters
     SqlEngine.init_engine(pool_size=4, max_overflow=12, pool_recycle=60)
-
-    # Proceed with executing the target function
     return func(*args, **kwargs)
 
 

backend/danswer/background/indexing/run_indexing.py

@@ -1,5 +1,7 @@
 import time
 import traceback
+from abc import ABC
+from abc import abstractmethod
 from datetime import datetime
 from datetime import timedelta
 from datetime import timezone
@@ -19,7 +21,6 @@ from danswer.db.connector_credential_pair import get_last_successful_attempt_tim
 from danswer.db.connector_credential_pair import update_connector_credential_pair
 from danswer.db.engine import get_session_with_tenant
 from danswer.db.enums import ConnectorCredentialPairStatus
-from danswer.db.index_attempt import mark_attempt_canceled
 from danswer.db.index_attempt import mark_attempt_failed
 from danswer.db.index_attempt import mark_attempt_partially_succeeded
 from danswer.db.index_attempt import mark_attempt_succeeded
@@ -30,10 +31,10 @@ from danswer.db.models import IndexingStatus
 from danswer.db.models import IndexModelStatus
 from danswer.document_index.factory import get_default_document_index
 from danswer.indexing.embedder import DefaultIndexingEmbedder
-from danswer.indexing.indexing_heartbeat import IndexingHeartbeatInterface
+from danswer.indexing.indexing_heartbeat import IndexingHeartbeat
 from danswer.indexing.indexing_pipeline import build_indexing_pipeline
+from danswer.utils.logger import IndexAttemptSingleton
 from danswer.utils.logger import setup_logger
-from danswer.utils.logger import TaskAttemptSingleton
 from danswer.utils.variable_functionality import global_version
 
 logger = setup_logger()
@@ -41,6 +42,19 @@ logger = setup_logger()
 INDEXING_TRACER_NUM_PRINT_ENTRIES = 5
 
 
+class RunIndexingCallbackInterface(ABC):
+    """Defines a callback interface to be passed to
+    to run_indexing_entrypoint."""
+
+    @abstractmethod
+    def should_stop(self) -> bool:
+        """Signal to stop the looping function in flight."""
+
+    @abstractmethod
+    def progress(self, amount: int) -> None:
+        """Send progress updates to the caller."""
+
+
 def _get_connector_runner(
     db_session: Session,
     attempt: IndexAttempt,
@@ -88,15 +102,11 @@ def _get_connector_runner(
     )
 
 
-class ConnectorStopSignal(Exception):
-    """A custom exception used to signal a stop in processing."""
-
-
 def _run_indexing(
     db_session: Session,
     index_attempt: IndexAttempt,
     tenant_id: str | None,
-    callback: IndexingHeartbeatInterface | None = None,
+    callback: RunIndexingCallbackInterface | None = None,
 ) -> None:
     """
     1. Get documents which are either new or updated from specified application
@@ -108,13 +118,7 @@ def _run_indexing(
     """
     start_time = time.time()
 
-    if index_attempt.search_settings is None:
-        raise ValueError(
-            "Search settings must be set for indexing. This should not be possible."
-        )
-
     search_settings = index_attempt.search_settings
-
     index_name = search_settings.index_name
 
     # Only update cc-pair status for primary index jobs
@@ -128,7 +132,13 @@ def _run_indexing(
 
     embedding_model = DefaultIndexingEmbedder.from_db_search_settings(
         search_settings=search_settings,
-        callback=callback,
+        heartbeat=IndexingHeartbeat(
+            index_attempt_id=index_attempt.id,
+            db_session=db_session,
+            # let the world know we're still making progress after
+            # every 10 batches
+            freq=10,
+        ),
     )
 
     indexing_pipeline = build_indexing_pipeline(
@@ -141,7 +151,6 @@ def _run_indexing(
         ),
         db_session=db_session,
         tenant_id=tenant_id,
-        callback=callback,
     )
 
     db_cc_pair = index_attempt.connector_credential_pair
@@ -213,7 +222,7 @@ def _run_indexing(
                 # contents still need to be initially pulled.
                 if callback:
                     if callback.should_stop():
-                        raise ConnectorStopSignal("Connector stop signal detected")
+                        raise RuntimeError("Connector stop signal detected")
 
                 # TODO: should we move this into the above callback instead?
                 db_session.refresh(db_cc_pair)
@@ -274,7 +283,7 @@ def _run_indexing(
                 db_session.commit()
 
                 if callback:
-                    callback.progress("_run_indexing", len(doc_batch))
+                    callback.progress(len(doc_batch))
 
                 # This new value is updated every batch, so UI can refresh per batch update
                 update_docs_indexed(
@@ -307,16 +316,26 @@ def _run_indexing(
                 )
         except Exception as e:
             logger.exception(
-                f"Connector run exceptioned after elapsed time: {time.time() - start_time} seconds"
+                f"Connector run ran into exception after elapsed time: {time.time() - start_time} seconds"
             )
-
-            if isinstance(e, ConnectorStopSignal):
-                mark_attempt_canceled(
-                    index_attempt.id,
+            # Only mark the attempt as a complete failure if this is the first indexing window.
+            # Otherwise, some progress was made - the next run will not start from the beginning.
+            # In this case, it is not accurate to mark it as a failure. When the next run begins,
+            # if that fails immediately, it will be marked as a failure.
+            #
+            # NOTE: if the connector is manually disabled, we should mark it as a failure regardless
+            # to give better clarity in the UI, as the next run will never happen.
+            if (
+                ind == 0
+                or not db_cc_pair.status.is_active()
+                or index_attempt.status != IndexingStatus.IN_PROGRESS
+            ):
+                mark_attempt_failed(
+                    index_attempt,
                     db_session,
-                    reason=str(e),
+                    failure_reason=str(e),
+                    full_exception_trace=traceback.format_exc(),
                 )
-
                 if is_primary:
                     update_connector_credential_pair(
                         db_session=db_session,
@@ -328,37 +347,6 @@ def _run_indexing(
                 if INDEXING_TRACER_INTERVAL > 0:
                     tracer.stop()
                 raise e
-            else:
-                # Only mark the attempt as a complete failure if this is the first indexing window.
-                # Otherwise, some progress was made - the next run will not start from the beginning.
-                # In this case, it is not accurate to mark it as a failure. When the next run begins,
-                # if that fails immediately, it will be marked as a failure.
-                #
-                # NOTE: if the connector is manually disabled, we should mark it as a failure regardless
-                # to give better clarity in the UI, as the next run will never happen.
-                if (
-                    ind == 0
-                    or not db_cc_pair.status.is_active()
-                    or index_attempt.status != IndexingStatus.IN_PROGRESS
-                ):
-                    mark_attempt_failed(
-                        index_attempt.id,
-                        db_session,
-                        failure_reason=str(e),
-                        full_exception_trace=traceback.format_exc(),
-                    )
-
-                    if is_primary:
-                        update_connector_credential_pair(
-                            db_session=db_session,
-                            connector_id=db_connector.id,
-                            credential_id=db_credential.id,
-                            net_docs=net_doc_change,
-                        )
-
-                    if INDEXING_TRACER_INTERVAL > 0:
-                        tracer.stop()
-                    raise e
 
             # break => similar to success case. As mentioned above, if the next run fails for the same
             # reason it will then be marked as a failure
@@ -378,7 +366,7 @@ def _run_indexing(
         and index_attempt_md.num_exceptions >= batch_num
     ):
         mark_attempt_failed(
-            index_attempt.id,
+            index_attempt,
             db_session,
             failure_reason="All batches exceptioned.",
         )
@@ -425,7 +413,7 @@ def run_indexing_entrypoint(
     tenant_id: str | None,
     connector_credential_pair_id: int,
     is_ee: bool = False,
-    callback: IndexingHeartbeatInterface | None = None,
+    callback: RunIndexingCallbackInterface | None = None,
 ) -> None:
     try:
         if is_ee:
@@ -433,19 +421,17 @@ def run_indexing_entrypoint(
 
         # set the indexing attempt ID so that all log messages from this process
         # will have it added as a prefix
-        TaskAttemptSingleton.set_cc_and_index_id(
+        IndexAttemptSingleton.set_cc_and_index_id(
             index_attempt_id, connector_credential_pair_id
         )
         with get_session_with_tenant(tenant_id) as db_session:
             attempt = transition_attempt_to_in_progress(index_attempt_id, db_session)
 
-            tenant_str = ""
-            if tenant_id is not None:
-                tenant_str = f" for tenant {tenant_id}"
-
             logger.info(
-                f"Indexing starting{tenant_str}: "
-                f"connector='{attempt.connector_credential_pair.connector.name}' "
+                f"Indexing starting for tenant {tenant_id}: "
+                if tenant_id is not None
+                else ""
+                + f"connector='{attempt.connector_credential_pair.connector.name}' "
                 f"config='{attempt.connector_credential_pair.connector.connector_specific_config}' "
                 f"credentials='{attempt.connector_credential_pair.connector_id}'"
             )
@@ -453,8 +439,10 @@ def run_indexing_entrypoint(
             _run_indexing(db_session, attempt, tenant_id, callback)
 
             logger.info(
-                f"Indexing finished{tenant_str}: "
-                f"connector='{attempt.connector_credential_pair.connector.name}' "
+                f"Indexing finished for tenant {tenant_id}: "
+                if tenant_id is not None
+                else ""
+                + f"connector='{attempt.connector_credential_pair.connector.name}' "
                 f"config='{attempt.connector_credential_pair.connector.connector_specific_config}' "
                 f"credentials='{attempt.connector_credential_pair.connector_id}'"
             )

backend/danswer/background/task_utils.py

@@ -14,6 +14,15 @@ from danswer.db.tasks import mark_task_start
 from danswer.db.tasks import register_task
 
 
+def name_cc_prune_task(
+    connector_id: int | None = None, credential_id: int | None = None
+) -> str:
+    task_name = f"prune_connector_credential_pair_{connector_id}_{credential_id}"
+    if not connector_id or not credential_id:
+        task_name = "prune_connector_credential_pair"
+    return task_name
+
+
 T = TypeVar("T", bound=Callable)
 
 

backend/danswer/chat/chat_utils.py

@@ -2,79 +2,20 @@ import re
 from typing import cast
 from uuid import UUID
 
-from fastapi import HTTPException
 from fastapi.datastructures import Headers
 from sqlalchemy.orm import Session
 
-from danswer.auth.users import is_user_admin
 from danswer.chat.models import CitationInfo
 from danswer.chat.models import LlmDoc
-from danswer.chat.models import PersonaOverrideConfig
-from danswer.chat.models import ThreadMessage
-from danswer.configs.constants import DEFAULT_PERSONA_ID
-from danswer.configs.constants import MessageType
-from danswer.context.search.models import InferenceSection
-from danswer.context.search.models import RerankingDetails
-from danswer.context.search.models import RetrievalDetails
-from danswer.db.chat import create_chat_session
 from danswer.db.chat import get_chat_messages_by_session
-from danswer.db.llm import fetch_existing_doc_sets
-from danswer.db.llm import fetch_existing_tools
 from danswer.db.models import ChatMessage
-from danswer.db.models import Persona
-from danswer.db.models import Prompt
-from danswer.db.models import Tool
-from danswer.db.models import User
-from danswer.db.persona import get_prompts_by_ids
 from danswer.llm.answering.models import PreviousMessage
-from danswer.natural_language_processing.utils import BaseTokenizer
-from danswer.server.query_and_chat.models import CreateChatMessageRequest
-from danswer.tools.tool_implementations.custom.custom_tool import (
-    build_custom_tools_from_openapi_schema_and_headers,
-)
+from danswer.search.models import InferenceSection
 from danswer.utils.logger import setup_logger
 
 logger = setup_logger()
 
 
-def prepare_chat_message_request(
-    message_text: str,
-    user: User | None,
-    persona_id: int | None,
-    # Does the question need to have a persona override
-    persona_override_config: PersonaOverrideConfig | None,
-    prompt: Prompt | None,
-    message_ts_to_respond_to: str | None,
-    retrieval_details: RetrievalDetails | None,
-    rerank_settings: RerankingDetails | None,
-    db_session: Session,
-) -> CreateChatMessageRequest:
-    # Typically used for one shot flows like SlackBot or non-chat API endpoint use cases
-    new_chat_session = create_chat_session(
-        db_session=db_session,
-        description=None,
-        user_id=user.id if user else None,
-        # If using an override, this id will be ignored later on
-        persona_id=persona_id or DEFAULT_PERSONA_ID,
-        danswerbot_flow=True,
-        slack_thread_id=message_ts_to_respond_to,
-    )
-
-    return CreateChatMessageRequest(
-        chat_session_id=new_chat_session.id,
-        parent_message_id=None,  # It's a standalone chat session each time
-        message=message_text,
-        file_descriptors=[],  # Currently SlackBot/answer api do not support files in the context
-        prompt_id=prompt.id if prompt else None,
-        # Can always override the persona for the single query, if it's a normal persona
-        # then it will be treated the same
-        persona_override_config=persona_override_config,
-        search_doc_ids=None,
-        retrieval_options=retrieval_details,
-        rerank_settings=rerank_settings,
-    )
-
-
 def llm_doc_from_inference_section(inference_section: InferenceSection) -> LlmDoc:
     return LlmDoc(
         document_id=inference_section.center_chunk.document_id,
@@ -90,49 +31,9 @@ def llm_doc_from_inference_section(inference_section: InferenceSection) -> LlmDo
         if inference_section.center_chunk.source_links
         else None,
         source_links=inference_section.center_chunk.source_links,
-        match_highlights=inference_section.center_chunk.match_highlights,
     )
 
 
-def combine_message_thread(
-    messages: list[ThreadMessage],
-    max_tokens: int | None,
-    llm_tokenizer: BaseTokenizer,
-) -> str:
-    """Used to create a single combined message context from threads"""
-    if not messages:
-        return ""
-
-    message_strs: list[str] = []
-    total_token_count = 0
-
-    for message in reversed(messages):
-        if message.role == MessageType.USER:
-            role_str = message.role.value.upper()
-            if message.sender:
-                role_str += " " + message.sender
-            else:
-                # Since other messages might have the user identifying information
-                # better to use Unknown for symmetry
-                role_str += " Unknown"
-        else:
-            role_str = message.role.value.upper()
-
-        msg_str = f"{role_str}:\n{message.message}"
-        message_token_count = len(llm_tokenizer.encode(msg_str))
-
-        if (
-            max_tokens is not None
-            and total_token_count + message_token_count > max_tokens
-        ):
-            break
-
-        message_strs.insert(0, msg_str)
-        total_token_count += message_token_count
-
-    return "\n\n".join(message_strs)
-
-
 def create_chat_chain(
     chat_session_id: UUID,
     db_session: Session,
@@ -295,71 +196,3 @@ def extract_headers(
             if lowercase_key in headers:
                 extracted_headers[lowercase_key] = headers[lowercase_key]
     return extracted_headers
-
-
-def create_temporary_persona(
-    persona_config: PersonaOverrideConfig, db_session: Session, user: User | None = None
-) -> Persona:
-    if not is_user_admin(user):
-        raise HTTPException(
-            status_code=403,
-            detail="User is not authorized to create a persona in one shot queries",
-        )
-
-    """Create a temporary Persona object from the provided configuration."""
-    persona = Persona(
-        name=persona_config.name,
-        description=persona_config.description,
-        num_chunks=persona_config.num_chunks,
-        llm_relevance_filter=persona_config.llm_relevance_filter,
-        llm_filter_extraction=persona_config.llm_filter_extraction,
-        recency_bias=persona_config.recency_bias,
-        llm_model_provider_override=persona_config.llm_model_provider_override,
-        llm_model_version_override=persona_config.llm_model_version_override,
-    )
-
-    if persona_config.prompts:
-        persona.prompts = [
-            Prompt(
-                name=p.name,
-                description=p.description,
-                system_prompt=p.system_prompt,
-                task_prompt=p.task_prompt,
-                include_citations=p.include_citations,
-                datetime_aware=p.datetime_aware,
-            )
-            for p in persona_config.prompts
-        ]
-    elif persona_config.prompt_ids:
-        persona.prompts = get_prompts_by_ids(
-            db_session=db_session, prompt_ids=persona_config.prompt_ids
-        )
-
-    persona.tools = []
-    if persona_config.custom_tools_openapi:
-        for schema in persona_config.custom_tools_openapi:
-            tools = cast(
-                list[Tool],
-                build_custom_tools_from_openapi_schema_and_headers(schema),
-            )
-            persona.tools.extend(tools)
-
-    if persona_config.tools:
-        tool_ids = [tool.id for tool in persona_config.tools]
-        persona.tools.extend(
-            fetch_existing_tools(db_session=db_session, tool_ids=tool_ids)
-        )
-
-    if persona_config.tool_ids:
-        persona.tools.extend(
-            fetch_existing_tools(
-                db_session=db_session, tool_ids=persona_config.tool_ids
-            )
-        )
-
-    fetched_docs = fetch_existing_doc_sets(
-        db_session=db_session, doc_ids=persona_config.document_set_ids
-    )
-    persona.document_sets = fetched_docs
-
-    return persona

backend/danswer/chat/load_yamls.py

@@ -5,7 +5,6 @@ from danswer.configs.chat_configs import INPUT_PROMPT_YAML
 from danswer.configs.chat_configs import MAX_CHUNKS_FED_TO_CHAT
 from danswer.configs.chat_configs import PERSONAS_YAML
 from danswer.configs.chat_configs import PROMPTS_YAML
-from danswer.context.search.enums import RecencyBiasSetting
 from danswer.db.document_set import get_or_create_document_set_by_name
 from danswer.db.input_prompt import insert_input_prompt_if_not_exists
 from danswer.db.models import DocumentSet as DocumentSetDBModel
@@ -15,6 +14,7 @@ from danswer.db.models import Tool as ToolDBModel
 from danswer.db.persona import get_prompt_by_name
 from danswer.db.persona import upsert_persona
 from danswer.db.persona import upsert_prompt
+from danswer.search.enums import RecencyBiasSetting
 
 
 def load_prompts_from_yaml(
@@ -81,7 +81,6 @@ def load_personas_from_yaml(
 
         p_id = persona.get("id")
         tool_ids = []
-
         if persona.get("image_generation"):
             image_gen_tool = (
                 db_session.query(ToolDBModel)

backend/danswer/chat/models.py

@@ -4,15 +4,13 @@ from enum import Enum
 from typing import Any
 
 from pydantic import BaseModel
-from pydantic import Field
 
 from danswer.configs.constants import DocumentSource
-from danswer.configs.constants import MessageType
-from danswer.context.search.enums import QueryFlow
-from danswer.context.search.enums import RecencyBiasSetting
-from danswer.context.search.enums import SearchType
-from danswer.context.search.models import RetrievalDocs
-from danswer.tools.tool_implementations.custom.base_tool_types import ToolResultType
+from danswer.search.enums import QueryFlow
+from danswer.search.enums import SearchType
+from danswer.search.models import RetrievalDocs
+from danswer.search.models import SearchResponse
+from danswer.tools.custom.base_tool_types import ToolResultType
 
 
 class LlmDoc(BaseModel):
@@ -27,7 +25,6 @@ class LlmDoc(BaseModel):
     updated_at: datetime | None
     link: str | None
     source_links: dict[int, str] | None
-    match_highlights: list[str] | None
 
 
 # First chunk of info for streaming QA
@@ -120,6 +117,20 @@ class StreamingError(BaseModel):
     stack_trace: str | None = None
 
 
+class DanswerQuote(BaseModel):
+    # This is during inference so everything is a string by this point
+    quote: str
+    document_id: str
+    link: str | None
+    source_type: str
+    semantic_identifier: str
+    blurb: str
+
+
+class DanswerQuotes(BaseModel):
+    quotes: list[DanswerQuote]
+
+
 class DanswerContext(BaseModel):
     content: str
     document_id: str
@@ -135,23 +146,17 @@ class DanswerAnswer(BaseModel):
     answer: str | None
 
 
-class ThreadMessage(BaseModel):
-    message: str
-    sender: str | None = None
-    role: MessageType = MessageType.USER
-
-
-class ChatDanswerBotResponse(BaseModel):
-    answer: str | None = None
-    citations: list[CitationInfo] | None = None
-    docs: QADocsResponse | None = None
+class QAResponse(SearchResponse, DanswerAnswer):
+    quotes: list[DanswerQuote] | None
+    contexts: list[DanswerContexts] | None
+    predicted_flow: QueryFlow
+    predicted_search: SearchType
+    eval_res_valid: bool | None = None
     llm_selected_doc_indices: list[int] | None = None
     error_msg: str | None = None
-    chat_message_id: int | None = None
-    answer_valid: bool = True  # Reflexion result, default True if Reflexion not run
 
 
-class FileChatDisplay(BaseModel):
+class ImageGenerationDisplay(BaseModel):
     file_ids: list[str]
 
 
@@ -160,44 +165,12 @@ class CustomToolResponse(BaseModel):
     tool_name: str
 
 
-class ToolConfig(BaseModel):
-    id: int
-
-
-class PromptOverrideConfig(BaseModel):
-    name: str
-    description: str = ""
-    system_prompt: str
-    task_prompt: str = ""
-    include_citations: bool = True
-    datetime_aware: bool = True
-
-
-class PersonaOverrideConfig(BaseModel):
-    name: str
-    description: str
-    search_type: SearchType = SearchType.SEMANTIC
-    num_chunks: float | None = None
-    llm_relevance_filter: bool = False
-    llm_filter_extraction: bool = False
-    recency_bias: RecencyBiasSetting = RecencyBiasSetting.AUTO
-    llm_model_provider_override: str | None = None
-    llm_model_version_override: str | None = None
-
-    prompts: list[PromptOverrideConfig] = Field(default_factory=list)
-    prompt_ids: list[int] = Field(default_factory=list)
-
-    document_set_ids: list[int] = Field(default_factory=list)
-    tools: list[ToolConfig] = Field(default_factory=list)
-    tool_ids: list[int] = Field(default_factory=list)
-    custom_tools_openapi: list[dict[str, Any]] = Field(default_factory=list)
-
-
 AnswerQuestionPossibleReturn = (
     DanswerAnswerPiece
+    | DanswerQuotes
     | CitationInfo
     | DanswerContexts
-    | FileChatDisplay
+    | ImageGenerationDisplay
     | CustomToolResponse
     | StreamingError
     | StreamStopInfo