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: ${{ secrets.DOCKER_TOKEN }}
-
+    
       - name: Build and push by digest
         id: build
         uses: docker/build-push-action@v5
@@ -65,17 +65,17 @@ jobs:
             NEXT_PUBLIC_POSTHOG_KEY=${{ secrets.POSTHOG_KEY }}
             NEXT_PUBLIC_POSTHOG_HOST=${{ secrets.POSTHOG_HOST }}
             NEXT_PUBLIC_SENTRY_DSN=${{ secrets.SENTRY_DSN }}
-          # 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:
@@ -95,42 +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

@@ -210,18 +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-helm-chart-testing.yml.disabled.txt

@@ -1,20 +1,24 @@
+# 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 ]
-  workflow_dispatch:  # Allows manual triggering
-  
+
 jobs:
-  helm-chart-check:
+  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@v4
+      uses: actions/checkout@v3
       with:
         fetch-depth: 0
         
@@ -24,7 +28,7 @@ jobs:
         version: v3.14.4
       
     - name: Set up Python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v4
       with:
         python-version: '3.11'
         cache: 'pip'
@@ -41,31 +45,24 @@ jobs:
     - 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: $changed"
+        changed=$(ct list-changed --target-branch ${{ github.event.repository.default_branch }})
         if [[ -n "$changed" ]]; then
           echo "changed=true" >> "$GITHUB_OUTPUT"
         fi
 
-    # 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 }}
+#       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'
+#       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 }}
+#       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

@@ -18,11 +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: ${{ 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 }}
 
 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 }}"]
 

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>
@@ -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/aryn-ai/sycamore/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
@@ -77,6 +87,7 @@ RUN apt-get update && \
 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/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/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/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/danswer/auth/users.py

@@ -48,11 +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.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
@@ -75,7 +75,6 @@ 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
@@ -84,27 +83,24 @@ from danswer.db.auth import SQLAlchemyUserAdminDB
 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.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()
 
 
-class BasicAuthenticationError(HTTPException):
-    def __init__(self, detail: str):
-        super().__init__(status_code=status.HTTP_403_FORBIDDEN, detail=detail)
-
-
 def is_user_admin(user: User | None) -> bool:
     if AUTH_TYPE == AuthType.DISABLED:
         return True
@@ -194,6 +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,
@@ -228,13 +238,19 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
         safe: bool = False,
         request: Optional[Request] = None,
     ) -> User:
-        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,
-        )
+        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")
+
+        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)
@@ -255,7 +271,7 @@ 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:
@@ -276,9 +292,7 @@ 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(
@@ -294,18 +308,19 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
         associate_by_email: bool = False,
         is_verified_by_default: bool = False,
     ) -> models.UOAP:
-        tenant_id = await fetch_ee_implementation_or_noop(
-            "danswer.server.tenants.provisioning",
-            "get_or_create_tenant_id",
-            async_return_default_schema,
-        )(
-            email=account_email,
-        )
+        # 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)
@@ -356,9 +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:
@@ -438,13 +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)
@@ -468,7 +477,8 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
             has_web_login = attributes.get_attribute(user, "has_web_login")
 
             if not has_web_login:
-                raise BasicAuthenticationError(
+                raise HTTPException(
+                    status_code=status.HTTP_403_FORBIDDEN,
                     detail="NO_WEB_LOGIN_AND_HAS_NO_PASSWORD",
                 )
 
@@ -500,30 +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,
@@ -625,12 +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.",
         )
 
@@ -639,7 +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.",
         )
 
@@ -665,13 +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.",
         )
 
@@ -683,7 +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.",
         )
 
@@ -876,22 +881,3 @@ def get_oauth_router(
         return redirect_response
 
     return router
-
-
-def api_key_dep(
-    request: Request, db_session: Session = Depends(get_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 = fetch_user_for_api_key(hashed_api_key, 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
@@ -12,22 +11,18 @@ from celery.states import READY_STATES
 from celery.utils.log import get_task_logger
 from celery.worker import strategy  # type: ignore
 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_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
@@ -113,27 +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)
+            rcp = RedisConnectorPruning(int(cc_pair_id))
+            r.srem(rcp.taskset_key, task_id)
         return
 
 
@@ -143,154 +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)
@@ -298,7 +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
 
 
@@ -310,20 +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 = sender.primary_worker_lock
-    try:
-        if lock.owned():
-            try:
-                lock.release()
-                sender.primary_worker_lock = None
-            except Exception as e:
-                logger.error(f"Failed to release primary worker lock: {e}")
-    except Exception as e:
-        logger.error(f"Failed to check if primary worker lock is owned: {e}")
+    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)
 
 

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()
@@ -62,13 +60,7 @@ def on_worker_init(sender: Any, **kwargs: Any) -> None:
     SqlEngine.set_app_name(POSTGRES_CELERY_WORKER_INDEXING_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)
     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)
 
 
@@ -91,6 +85,5 @@ celery_app.autodiscover_tasks(
     [
         "danswer.background.celery.tasks.shared",
         "danswer.background.celery.tasks.vespa",
-        "danswer.background.celery.tasks.connector_deletion",
     ]
 )

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

@@ -13,21 +13,21 @@ from celery.signals import worker_shutdown
 
 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.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_all_tenant_ids
 from danswer.db.engine import SqlEngine
-from danswer.redis.redis_connector_credential_pair import RedisConnectorCredentialPair
-from danswer.redis.redis_connector_delete import RedisConnectorDelete
-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()
@@ -75,64 +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)
 
-    # 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)
+        # 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)
 
-    # 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,
-    )
+        # 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,
+        )
 
-    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!")
+        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!")
 
-    # tacking on our own user data to the sender
-    sender.primary_worker_lock = lock
+        # tacking on our own user data to the sender
+        sender.primary_worker_locks[tenant_id] = lock
 
-    # 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)
+        # 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)
 
-    r.delete(RedisConnectorCredentialPair.get_taskset_key())
-    r.delete(RedisConnectorCredentialPair.get_fence_key())
+        r.delete(RedisConnectorCredentialPair.get_taskset_key())
+        r.delete(RedisConnectorCredentialPair.get_fence_key())
 
-    RedisDocumentSet.reset_all(r)
+        for key in r.scan_iter(RedisDocumentSet.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    RedisUserGroup.reset_all(r)
+        for key in r.scan_iter(RedisDocumentSet.FENCE_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorDelete.reset_all(r)
+        for key in r.scan_iter(RedisUserGroup.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorPrune.reset_all(r)
+        for key in r.scan_iter(RedisUserGroup.FENCE_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorIndex.reset_all(r)
+        for key in r.scan_iter(RedisConnectorDeletion.TASKSET_PREFIX + "*"):
+            r.delete(key)
 
-    RedisConnectorStop.reset_all(r)
+        for key in r.scan_iter(RedisConnectorDeletion.FENCE_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorPruning.TASKSET_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorPruning.GENERATOR_COMPLETE_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorPruning.GENERATOR_PROGRESS_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorPruning.FENCE_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorIndexing.TASKSET_PREFIX + "*"):
+            r.delete(key)
+
+        for key in r.scan_iter(RedisConnectorIndexing.GENERATOR_COMPLETE_PREFIX + "*"):
+            r.delete(key)
+
+        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
@@ -185,36 +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 = 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.")

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 +4,7 @@ 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 (
@@ -17,7 +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.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
     )
 
 

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

@@ -1,48 +0,0 @@
-from datetime import timedelta
-from typing import Any
-
-from danswer.configs.constants import DanswerCeleryPriority
-
-
-tasks_to_schedule = [
-    {
-        "name": "check-for-vespa-sync",
-        "task": "check_for_vespa_sync_task",
-        "schedule": timedelta(seconds=20),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-connector-deletion",
-        "task": "check_for_connector_deletion_task",
-        "schedule": timedelta(seconds=20),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-indexing",
-        "task": "check_for_indexing",
-        "schedule": timedelta(seconds=15),
-        "options": {"priority": DanswerCeleryPriority.HIGH},
-    },
-    {
-        "name": "check-for-prune",
-        "task": "check_for_pruning",
-        "schedule": timedelta(seconds=15),
-        "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},
-    },
-]
-
-
-def get_tasks_to_schedule() -> list[dict[str, Any]]:
-    return tasks_to_schedule

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

@@ -10,6 +10,13 @@ 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 DanswerRedisLocks
@@ -18,8 +25,6 @@ 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 RedisConnectorDeletionFenceData
 from danswer.redis.redis_pool import get_redis_client
 
 
@@ -57,7 +62,7 @@ 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, r, lock_beat, tenant_id
@@ -66,10 +71,10 @@ def check_for_connector_deletion_task(self: Task, *, tenant_id: str | None) -> N
                     # 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(
@@ -101,10 +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
@@ -118,49 +123,47 @@ def try_generate_document_cc_pair_cleanup_tasks(
         return None
 
     # set a basic fence to start
-    fence_payload = RedisConnectorDeletionFenceData(
+    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}"
             )
 
         # 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.
@@ -175,7 +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/indexing/tasks.py

@@ -2,9 +2,10 @@ 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
@@ -13,6 +14,12 @@ 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 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
@@ -43,15 +50,12 @@ from danswer.db.search_settings import get_secondary_search_settings
 from danswer.db.swap_index import check_index_swap
 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 RedisConnectorIndexingFenceData
 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()
 
@@ -101,22 +105,19 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
             return None
 
         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,
-                    )
-
-                    # only warm up if search settings were changed
-                    warm_up_bi_encoder(
-                        embedding_model=embedding_model,
-                    )
+                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,
+                )
 
         cc_pair_ids: list[int] = []
         with get_session_with_tenant(tenant_id) as db_session:
@@ -125,7 +126,6 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
                 cc_pair_ids.append(cc_pair_entry.id)
 
         for cc_pair_id in cc_pair_ids:
-            redis_connector = RedisConnector(tenant_id, cc_pair_id)
             with get_session_with_tenant(tenant_id) as db_session:
                 # Get the primary search settings
                 primary_search_settings = get_current_search_settings(db_session)
@@ -138,10 +138,10 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
                     search_settings.append(secondary_search_settings)
 
                 for search_settings_instance in search_settings:
-                    redis_connector_index = redis_connector.new_index(
-                        search_settings_instance.id
+                    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(
@@ -175,9 +175,7 @@ def check_for_indexing(self: Task, *, tenant_id: str | None) -> int | None:
                     )
                     if attempt_id:
                         task_logger.info(
-                            f"Indexing queued: 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
     except SoftTimeLimitExceeded:
@@ -306,15 +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)
@@ -322,17 +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 = RedisConnectorIndexingFenceData(
+        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
@@ -345,8 +345,6 @@ def try_creating_indexing_task(
             db_session=db_session,
         )
 
-        custom_task_id = redis_connector_index.generate_generator_task_id()
-
         result = celery_app.send_task(
             "connector_indexing_proxy_task",
             kwargs=dict(
@@ -363,12 +361,11 @@ 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:
-        redis_connector_index.set_fence(payload)
+        r.delete(rci.fence_key)
         task_logger.exception(
             f"Unexpected exception: "
             f"tenant={tenant_id} "
@@ -391,12 +388,7 @@ def connector_indexing_proxy_task(
     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 proxy - starting: attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
+
     client = SimpleJobClient()
 
     job = client.submit(
@@ -410,56 +402,29 @@ def connector_indexing_proxy_task(
     )
 
     if not job:
-        task_logger.info(
-            f"Indexing proxy - 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 proxy - spawn succeeded: attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
-
     while True:
         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
+            )
 
-        # do nothing for ongoing jobs that haven't been stopped
-        if not job.done():
-            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
-                )
-
+            # do nothing for ongoing jobs that haven't been stopped
+            if not job.done():
                 if not index_attempt:
                     continue
 
                 if not index_attempt.is_finished():
                     continue
 
-        if job.status == "error":
-            task_logger.error(
-                f"Indexing proxy - 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()}"
-            )
+            if job.status == "error":
+                logger.error(job.exception())
 
-        job.release()
-        break
+            job.release()
+            break
 
-    task_logger.info(
-        f"Indexing proxy - finished: attempt={index_attempt_id} "
-        f"tenant={tenant_id} "
-        f"cc_pair={cc_pair_id} "
-        f"search_settings={search_settings_id}"
-    )
     return
 
 
@@ -481,97 +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: 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"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"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:
-        # wait for the fence to come up
-        if not redis_connector_index.fenced:
+        # 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
-        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
 
     lock = r.lock(
-        redis_connector_index.generator_lock_key,
+        rci.generator_lock_key,
         timeout=CELERY_INDEXING_LOCK_TIMEOUT,
     )
 
     acquired = lock.acquire(blocking=False)
     if not acquired:
-        logger.warning(
+        task_logger.warning(
             f"Indexing task already running, exiting...: "
             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:
@@ -580,7 +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,
@@ -600,52 +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 = RunIndexingCallback(
-            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/pruning/tasks.py

@@ -11,6 +11,9 @@ 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 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 RunIndexingCallback
 from danswer.configs.app_configs import ALLOW_SIMULTANEOUS_PRUNING
@@ -30,7 +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
@@ -145,11 +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
@@ -166,10 +165,15 @@ def try_creating_prune_generator_task(
         return None
 
     try:
-        if redis_connector.prune.fenced:  # skip pruning if already pruning
+        rcp = RedisConnectorPruning(cc_pair.id)
+
+        # skip pruning if already pruning
+        if r.exists(rcp.fence_key):
             return None
 
-        if redis_connector.delete.fenced:  # skip pruning if the cc_pair is deleting
+        # skip pruning if the cc_pair is deleting
+        rcd = RedisConnectorDeletion(cc_pair.id)
+        if r.exists(rcd.fence_key):
             return None
 
         db_session.refresh(cc_pair)
@@ -177,10 +181,10 @@ 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(
             "connector_pruning_generator_task",
@@ -196,7 +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
@@ -231,12 +235,12 @@ def connector_pruning_generator_task(
     pruning_ctx_dict["request_id"] = self.request.id
     pruning_ctx.set(pruning_ctx_dict)
 
-    redis_connector = RedisConnector(tenant_id, cc_pair_id)
+    rcp = RedisConnectorPruning(cc_pair_id)
 
     r = get_redis_client(tenant_id=tenant_id)
 
     lock = r.lock(
-        DanswerRedisLocks.PRUNING_LOCK_PREFIX + f"_{redis_connector.id}",
+        DanswerRedisLocks.PRUNING_LOCK_PREFIX + f"_{rcp._id}",
         timeout=CELERY_PRUNING_LOCK_TIMEOUT,
     )
 
@@ -269,11 +273,10 @@ def connector_pruning_generator_task(
                 cc_pair.credential,
             )
 
+            rcs = RedisConnectorStop(cc_pair_id)
+
             callback = RunIndexingCallback(
-                redis_connector.stop.fence_key,
-                redis_connector.prune.generator_progress_key,
-                lock,
-                r,
+                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(
@@ -300,29 +303,31 @@ def connector_pruning_generator_task(
                 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.generator_clear()
-        redis_connector.prune.taskset_clear()
-        redis_connector.prune.set_fence(False)
+        r.delete(rcp.generator_progress_key)
+        r.delete(rcp.taskset_key)
+        r.delete(rcp.fence_key)
         raise e
     finally:
         if lock.owned():

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/vespa/tasks.py

@@ -19,6 +19,18 @@ 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
@@ -55,14 +67,7 @@ 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_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 (
@@ -187,7 +192,7 @@ def try_generate_stale_document_sync_tasks(
     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 = RedisConnectorCredentialPair(cc_pair.id)
         tasks_generated = rc.generate_tasks(
             celery_app, db_session, r, lock_beat, tenant_id
         )
@@ -223,10 +228,10 @@ def try_generate_document_set_sync_tasks(
 ) -> 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
@@ -264,7 +269,7 @@ def try_generate_document_set_sync_tasks(
     )
 
     # set this only after all tasks have been added
-    rds.set_fence(tasks_generated)
+    r.set(rds.fence_key, tasks_generated)
     return tasks_generated
 
 
@@ -278,9 +283,10 @@ def try_generate_user_group_sync_tasks(
 ) -> 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!
@@ -320,7 +326,7 @@ def try_generate_user_group_sync_tasks(
     )
 
     # set this only after all tasks have been added
-    rug.set_fence(tasks_generated)
+    r.set(rug.fence_key, tasks_generated)
     return tasks_generated
 
 
@@ -346,7 +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)
@@ -356,12 +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))
@@ -389,38 +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:
@@ -504,15 +524,15 @@ def monitor_connector_deletion_taskset(
         f"docs_deleted={fence_data.num_tasks}"
     )
 
-    redis_connector.delete.taskset_clear()
-    redis_connector.delete.set_fence(None)
+    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}"
@@ -521,37 +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)
+    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}"
@@ -566,37 +595,53 @@ 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_id={cc_pair_id} "
-            f"search_settings_id={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
 
-    status_int = redis_connector_index.get_completion()
-    if status_int is None:
+    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
@@ -607,18 +652,30 @@ def monitor_ccpair_indexing_taskset(
                 f"elapsed_submitted={elapsed_submitted.total_seconds():.2f}"
             )
 
-            index_attempt = get_index_attempt(db_session, payload.index_attempt_id)
+            index_attempt = get_index_attempt(db_session, fence_data.index_attempt_id)
             if index_attempt:
                 mark_attempt_failed(
-                    index_attempt_id=payload.index_attempt_id,
+                    index_attempt=index_attempt,
                     db_session=db_session,
                     failure_reason="Connector indexing aborted or exceptioned.",
                 )
 
-            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_id={cc_pair_id} "
@@ -627,7 +684,11 @@ def monitor_ccpair_indexing_taskset(
         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="monitor_vespa_sync", soft_time_limit=300, bind=True)
@@ -639,7 +700,7 @@ 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)
 
@@ -690,33 +751,27 @@ def monitor_vespa_sync(self: Task, tenant_id: str | None) -> bool:
 
             for a in attempts:
                 # if attempts exist in the db but we don't detect them in redis, mark them as failed
-                fence_key = RedisConnectorIndex.fence_key_with_ids(
+                rci = RedisConnectorIndexing(
                     a.connector_credential_pair_id, a.search_settings_id
                 )
-                if not r.exists(fence_key):
-                    failure_reason = (
-                        f"Unknown index attempt. Might be left over from a process restart: "
-                        f"index_attempt={a.id} "
-                        f"cc_pair={a.connector_credential_pair_id} "
-                        f"search_settings={a.search_settings_id}"
-                    )
-                    task_logger.warning(failure_reason)
-                    mark_attempt_failed(a.id, db_session, failure_reason=failure_reason)
+                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 + "*"):
@@ -727,19 +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)
+                monitor_ccpair_indexing_taskset(key_bytes, r, db_session)
 
         # uncomment for debugging if needed
         # r_celery = celery_app.broker_connection().channel().client

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

@@ -1,6 +1,8 @@
 """Factory stub for running celery worker / celery beat."""
-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_app
+app = fetch_versioned_implementation(
+    "danswer.background.celery.apps.beat", "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

@@ -118,13 +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
@@ -337,7 +331,7 @@ def _run_indexing(
                 or index_attempt.status != IndexingStatus.IN_PROGRESS
             ):
                 mark_attempt_failed(
-                    index_attempt.id,
+                    index_attempt,
                     db_session,
                     failure_reason=str(e),
                     full_exception_trace=traceback.format_exc(),
@@ -372,7 +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.",
         )

backend/danswer/background/task_name_builders.py

@@ -1,4 +0,0 @@
-def name_sync_external_doc_permissions_task(
-    cc_pair_id: int, tenant_id: str | None = None
-) -> str:
-    return f"sync_external_doc_permissions_task__{cc_pair_id}"

backend/danswer/chat/models.py

@@ -10,7 +10,7 @@ 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.tool_implementations.custom.base_tool_types import ToolResultType
+from danswer.tools.custom.base_tool_types import ToolResultType
 
 
 class LlmDoc(BaseModel):
@@ -156,7 +156,7 @@ class QAResponse(SearchResponse, DanswerAnswer):
     error_msg: str | None = None
 
 
-class FileChatDisplay(BaseModel):
+class ImageGenerationDisplay(BaseModel):
     file_ids: list[str]
 
 
@@ -170,7 +170,7 @@ AnswerQuestionPossibleReturn = (
     | DanswerQuotes
     | CitationInfo
     | DanswerContexts
-    | FileChatDisplay
+    | ImageGenerationDisplay
     | CustomToolResponse
     | StreamingError
     | StreamStopInfo

backend/danswer/chat/personas.yaml

@@ -42,14 +42,18 @@ personas:
     display_priority: 1
     is_visible: true
     starter_messages:
-      - name: "Give me an overview of what's here"
-        message: "Sample some documents and tell me what you find."
-      - name: "Use AI to solve a work related problem"
-        message: "Ask me what problem I would like to solve, then search the knowledge base to help me find a solution."
-      - name: "Find updates on a topic of interest"
-        message: "Once I provide a topic, retrieve related documents and tell me when there was last activity on the topic if available."
-      - name: "Surface contradictions"
-        message: "Have me choose a subject. Once I have provided it, check against the knowledge base and point out any inconsistencies. For all your following responses, focus on identifying contradictions."
+      - name: "General Information"
+        description: "Ask about available information"
+        message: "Hello! I'm interested in learning more about the information available here. Could you give me an overview of the types of data or documents that might be accessible?"
+      - name: "Specific Topic Search"
+        description: "Search for specific information"
+        message: "Hi! I'd like to learn more about a specific topic. Could you help me find relevant documents and information?"
+      - name: "Recent Updates"
+        description: "Inquire about latest additions"
+        message: "Hello! I'm curious about any recent updates or additions to the knowledge base. Can you tell me what new information has been added lately?"
+      - name: "Cross-referencing Information"
+        description: "Connect information from different sources"
+        message: "Hi! I'm working on a project that requires connecting information from multiple sources. How can I effectively cross-reference data across different documents or categories?"
 
   - id: 1
     name: "General"
@@ -67,14 +71,18 @@ personas:
     display_priority: 0
     is_visible: true
     starter_messages:
-      - name: "Summarize a document"
-        message: "If I have provided a document please summarize it for me. If not, please ask me to upload a document either by dragging it into the input bar or clicking the +file icon."
-      - name: "Help me with coding"
-        message: 'Write me a "Hello World" script in 5 random languages to show off the functionality.'
-      - name: "Draft a professional email"
-        message: "Help me craft a professional email. Let's establish the context and the anticipated outcomes of the email before proposing a draft."
-      - name: "Learn something new"
-        message: "What is the difference between a Gantt chart, a Burndown chart and a Kanban board?"
+      - name: "Open Discussion"
+        description: "Start an open-ended conversation"
+        message: "Hi! Can you help me write a professional email?"
+      - name: "Problem Solving"
+        description: "Get help with a challenge"
+        message: "Hello! I need help managing my daily tasks better. Do you have any simple tips?"
+      - name: "Learn Something New"
+        description: "Explore a new topic"
+        message: "Hi! Could you explain what project management is in simple terms?"
+      - name: "Creative Brainstorming"
+        description: "Generate creative ideas"
+        message: "Hello! I need to brainstorm some team building activities. Do you have any fun suggestions?"
 
   - id: 2
     name: "Paraphrase"
@@ -93,12 +101,16 @@ personas:
     is_visible: false
     starter_messages:
       - name: "Document Search"
+        description: "Find exact information"
         message: "Hi! Could you help me find information about our team structure and reporting lines from our internal documents?"
       - name: "Process Verification"
+        description: "Find exact quotes"
         message: "Hello! I need to understand our project approval process. Could you find the exact steps from our documentation?"
       - name: "Technical Documentation"
+        description: "Search technical details"
         message: "Hi there! I'm looking for information about our deployment procedures. Can you find the specific steps from our technical guides?"
       - name: "Policy Reference"
+        description: "Check official policies"
         message: "Hello! Could you help me find our official guidelines about client communication? I need the exact wording from our documentation."
 
   - id: 3
@@ -118,11 +130,15 @@ personas:
     display_priority: 3
     is_visible: true
     starter_messages:
-      - name: "Create visuals for a presentation"
-        message: "Generate someone presenting a graph which clearly demonstrates an upwards trajectory."
-      - name: "Find inspiration for a marketing campaign"
-        message: "Generate an image of two happy individuals sipping on a soda drink in a glass bottle."
-      - name: "Visualize a product design"
-        message: "I want to add a search bar to my Iphone app. Generate me generic examples of how other apps implement this."
-      - name: "Generate a humorous image response"
-        message: "My teammate just made a silly mistake and I want to respond with a facepalm. Can you generate me one?"
+      - name: "Landscape"
+        description: "Generate a landscape image"
+        message: "Create an image of a serene mountain lake at sunset, with snow-capped peaks reflected in the calm water and a small wooden cabin on the shore."
+      - name: "Character"
+        description: "Generate a character image"
+        message: "Generate an image of a futuristic robot with glowing blue eyes, sleek metallic body, and intricate circuitry visible through transparent panels on its chest and arms."
+      - name: "Abstract"
+        description: "Create an abstract image"
+        message: "Create an abstract image representing the concept of time, using swirling clock hands, fragmented hourglasses, and streaks of light to convey the passage of moments and eras."
+      - name: "Urban Scene"
+        description: "Generate an urban landscape"
+        message: "Generate an image of a bustling futuristic cityscape at night, with towering skyscrapers, flying vehicles, holographic advertisements, and a mix of neon and bioluminescent lighting."

backend/danswer/chat/process_message.py

@@ -11,18 +11,23 @@ from danswer.chat.models import AllCitations
 from danswer.chat.models import CitationInfo
 from danswer.chat.models import CustomToolResponse
 from danswer.chat.models import DanswerAnswerPiece
-from danswer.chat.models import FileChatDisplay
 from danswer.chat.models import FinalUsedContextDocsResponse
+from danswer.chat.models import ImageGenerationDisplay
 from danswer.chat.models import LLMRelevanceFilterResponse
 from danswer.chat.models import MessageResponseIDInfo
 from danswer.chat.models import MessageSpecificCitations
 from danswer.chat.models import QADocsResponse
 from danswer.chat.models import StreamingError
-from danswer.chat.models import StreamStopInfo
+from danswer.configs.app_configs import AZURE_DALLE_API_BASE
+from danswer.configs.app_configs import AZURE_DALLE_API_KEY
+from danswer.configs.app_configs import AZURE_DALLE_API_VERSION
+from danswer.configs.app_configs import AZURE_DALLE_DEPLOYMENT_NAME
+from danswer.configs.chat_configs import BING_API_KEY
 from danswer.configs.chat_configs import CHAT_TARGET_CHUNK_PERCENTAGE
 from danswer.configs.chat_configs import DISABLE_LLM_CHOOSE_SEARCH
 from danswer.configs.chat_configs import MAX_CHUNKS_FED_TO_CHAT
 from danswer.configs.constants import MessageType
+from danswer.configs.model_configs import GEN_AI_TEMPERATURE
 from danswer.db.chat import attach_files_to_chat_message
 from danswer.db.chat import create_db_search_doc
 from danswer.db.chat import create_new_chat_message
@@ -35,6 +40,7 @@ from danswer.db.chat import reserve_message_id
 from danswer.db.chat import translate_db_message_to_chat_message_detail
 from danswer.db.chat import translate_db_search_doc_to_server_search_doc
 from danswer.db.engine import get_session_context_manager
+from danswer.db.llm import fetch_existing_llm_providers
 from danswer.db.models import SearchDoc as DbSearchDoc
 from danswer.db.models import ToolCall
 from danswer.db.models import User
@@ -54,13 +60,14 @@ from danswer.llm.answering.models import PromptConfig
 from danswer.llm.exceptions import GenAIDisabledException
 from danswer.llm.factory import get_llms_for_persona
 from danswer.llm.factory import get_main_llm_from_tuple
+from danswer.llm.interfaces import LLMConfig
 from danswer.llm.utils import litellm_exception_to_error_msg
 from danswer.natural_language_processing.utils import get_tokenizer
+from danswer.search.enums import LLMEvaluationType
 from danswer.search.enums import OptionalSearchSetting
 from danswer.search.enums import QueryFlow
 from danswer.search.enums import SearchType
 from danswer.search.models import InferenceSection
-from danswer.search.models import RetrievalDetails
 from danswer.search.retrieval.search_runner import inference_sections_from_ids
 from danswer.search.utils import chunks_or_sections_to_search_docs
 from danswer.search.utils import dedupe_documents
@@ -69,48 +76,36 @@ from danswer.search.utils import relevant_sections_to_indices
 from danswer.server.query_and_chat.models import ChatMessageDetail
 from danswer.server.query_and_chat.models import CreateChatMessageRequest
 from danswer.server.utils import get_json_line
+from danswer.tools.built_in_tools import get_built_in_tool_by_id
+from danswer.tools.custom.custom_tool import (
+    build_custom_tools_from_openapi_schema_and_headers,
+)
+from danswer.tools.custom.custom_tool import CUSTOM_TOOL_RESPONSE_ID
+from danswer.tools.custom.custom_tool import CustomToolCallSummary
 from danswer.tools.force import ForceUseTool
-from danswer.tools.models import ToolResponse
-from danswer.tools.tool import Tool
-from danswer.tools.tool_constructor import construct_tools
-from danswer.tools.tool_constructor import CustomToolConfig
-from danswer.tools.tool_constructor import ImageGenerationToolConfig
-from danswer.tools.tool_constructor import InternetSearchToolConfig
-from danswer.tools.tool_constructor import SearchToolConfig
-from danswer.tools.tool_implementations.custom.custom_tool import (
-    CUSTOM_TOOL_RESPONSE_ID,
-)
-from danswer.tools.tool_implementations.custom.custom_tool import CustomToolCallSummary
-from danswer.tools.tool_implementations.images.image_generation_tool import (
-    IMAGE_GENERATION_RESPONSE_ID,
-)
-from danswer.tools.tool_implementations.images.image_generation_tool import (
-    ImageGenerationResponse,
-)
-from danswer.tools.tool_implementations.internet_search.internet_search_tool import (
+from danswer.tools.images.image_generation_tool import IMAGE_GENERATION_RESPONSE_ID
+from danswer.tools.images.image_generation_tool import ImageGenerationResponse
+from danswer.tools.images.image_generation_tool import ImageGenerationTool
+from danswer.tools.internet_search.internet_search_tool import (
     INTERNET_SEARCH_RESPONSE_ID,
 )
-from danswer.tools.tool_implementations.internet_search.internet_search_tool import (
+from danswer.tools.internet_search.internet_search_tool import (
     internet_search_response_to_search_docs,
 )
-from danswer.tools.tool_implementations.internet_search.internet_search_tool import (
-    InternetSearchResponse,
-)
-from danswer.tools.tool_implementations.internet_search.internet_search_tool import (
-    InternetSearchTool,
-)
-from danswer.tools.tool_implementations.search.search_tool import (
-    FINAL_CONTEXT_DOCUMENTS_ID,
-)
-from danswer.tools.tool_implementations.search.search_tool import (
-    SEARCH_RESPONSE_SUMMARY_ID,
-)
-from danswer.tools.tool_implementations.search.search_tool import SearchResponseSummary
-from danswer.tools.tool_implementations.search.search_tool import SearchTool
-from danswer.tools.tool_implementations.search.search_tool import (
-    SECTION_RELEVANCE_LIST_ID,
-)
+from danswer.tools.internet_search.internet_search_tool import InternetSearchResponse
+from danswer.tools.internet_search.internet_search_tool import InternetSearchTool
+from danswer.tools.models import DynamicSchemaInfo
+from danswer.tools.search.search_tool import FINAL_CONTEXT_DOCUMENTS_ID
+from danswer.tools.search.search_tool import SEARCH_RESPONSE_SUMMARY_ID
+from danswer.tools.search.search_tool import SearchResponseSummary
+from danswer.tools.search.search_tool import SearchTool
+from danswer.tools.search.search_tool import SECTION_RELEVANCE_LIST_ID
+from danswer.tools.tool import Tool
+from danswer.tools.tool import ToolResponse
 from danswer.tools.tool_runner import ToolCallFinalResult
+from danswer.tools.utils import compute_all_tool_tokens
+from danswer.tools.utils import explicit_tool_calling_supported
+from danswer.utils.headers import header_dict_to_header_list
 from danswer.utils.logger import setup_logger
 from danswer.utils.timing import log_generator_function_time
 
@@ -261,11 +256,10 @@ ChatPacket = (
     | DanswerAnswerPiece
     | AllCitations
     | CitationInfo
-    | FileChatDisplay
+    | ImageGenerationDisplay
     | CustomToolResponse
     | MessageSpecificCitations
     | MessageResponseIDInfo
-    | StreamStopInfo
 )
 ChatPacketStream = Iterator[ChatPacket]
 
@@ -281,6 +275,7 @@ def stream_chat_message_objects(
     max_document_percentage: float = CHAT_TARGET_CHUNK_PERCENTAGE,
     # if specified, uses the last user message and does not create a new user message based
     # on the `new_msg_req.message`. Currently, requires a state where the last message is a
+    use_existing_user_message: bool = False,
     litellm_additional_headers: dict[str, str] | None = None,
     custom_tool_additional_headers: dict[str, str] | None = None,
     is_connected: Callable[[], bool] | None = None,
@@ -292,9 +287,6 @@ def stream_chat_message_objects(
     3. [always] A set of streamed LLM tokens or an error anywhere along the line if something fails
     4. [always] Details on the final AI response message that is created
     """
-    use_existing_user_message = new_msg_req.use_existing_user_message
-    existing_assistant_message_id = new_msg_req.existing_assistant_message_id
-
     # Currently surrounding context is not supported for chat
     # Chat is already token heavy and harder for the model to process plus it would roll history over much faster
     new_msg_req.chunks_above = 0
@@ -416,20 +408,12 @@ def stream_chat_message_objects(
             final_msg, history_msgs = create_chat_chain(
                 chat_session_id=chat_session_id, db_session=db_session
             )
-            if existing_assistant_message_id is None:
-                if final_msg.message_type != MessageType.USER:
-                    raise RuntimeError(
-                        "The last message was not a user message. Cannot call "
-                        "`stream_chat_message_objects` with `is_regenerate=True` "
-                        "when the last message is not a user message."
-                    )
-            else:
-                if final_msg.id != existing_assistant_message_id:
-                    raise RuntimeError(
-                        "The last message was not the existing assistant message. "
-                        f"Final message id: {final_msg.id}, "
-                        f"existing assistant message id: {existing_assistant_message_id}"
-                    )
+            if final_msg.message_type != MessageType.USER:
+                raise RuntimeError(
+                    "The last message was not a user message. Cannot call "
+                    "`stream_chat_message_objects` with `is_regenerate=True` "
+                    "when the last message is not a user message."
+                )
 
         # Disable Query Rephrasing for the first message
         # This leads to a better first response since the LLM rephrasing the question
@@ -500,19 +484,13 @@ def stream_chat_message_objects(
                 ),
                 max_window_percentage=max_document_percentage,
             )
-
-        # we don't need to reserve a message id if we're using an existing assistant message
-        reserved_message_id = (
-            final_msg.id
-            if existing_assistant_message_id is not None
-            else reserve_message_id(
-                db_session=db_session,
-                chat_session_id=chat_session_id,
-                parent_message=user_message.id
-                if user_message is not None
-                else parent_message.id,
-                message_type=MessageType.ASSISTANT,
-            )
+        reserved_message_id = reserve_message_id(
+            db_session=db_session,
+            chat_session_id=chat_session_id,
+            parent_message=user_message.id
+            if user_message is not None
+            else parent_message.id,
+            message_type=MessageType.ASSISTANT,
         )
         yield MessageResponseIDInfo(
             user_message_id=user_message.id if user_message else None,
@@ -527,13 +505,7 @@ def stream_chat_message_objects(
         partial_response = partial(
             create_new_chat_message,
             chat_session_id=chat_session_id,
-            # if we're using an existing assistant message, then this will just be an
-            # update operation, in which case the parent should be the parent of
-            # the latest. If we're creating a new assistant message, then the parent
-            # should be the latest message (latest user message)
-            parent_message=(
-                final_msg if existing_assistant_message_id is None else parent_message
-            ),
+            parent_message=final_msg,
             prompt_id=prompt_id,
             overridden_model=overridden_model,
             # message=,
@@ -545,7 +517,6 @@ def stream_chat_message_objects(
             # reference_docs=,
             db_session=db_session,
             commit=False,
-            reserved_message_id=reserved_message_id,
         )
 
         if not final_msg.prompt:
@@ -561,53 +532,148 @@ def stream_chat_message_objects(
             if not persona
             else PromptConfig.from_model(persona.prompts[0])
         )
-        answer_style_config = AnswerStyleConfig(
-            citation_config=CitationConfig(
-                all_docs_useful=selected_db_search_docs is not None
-            ),
-            document_pruning_config=document_pruning_config,
-            structured_response_format=new_msg_req.structured_response_format,
-        )
 
-        tool_dict = construct_tools(
-            persona=persona,
-            prompt_config=prompt_config,
-            db_session=db_session,
-            user=user,
-            llm=llm,
-            fast_llm=fast_llm,
-            search_tool_config=SearchToolConfig(
-                answer_style_config=answer_style_config,
-                document_pruning_config=document_pruning_config,
-                retrieval_options=retrieval_options or RetrievalDetails(),
-                selected_sections=selected_sections,
-                chunks_above=new_msg_req.chunks_above,
-                chunks_below=new_msg_req.chunks_below,
-                full_doc=new_msg_req.full_doc,
-                latest_query_files=latest_query_files,
-            ),
-            internet_search_tool_config=InternetSearchToolConfig(
-                answer_style_config=answer_style_config,
-            ),
-            image_generation_tool_config=ImageGenerationToolConfig(
-                additional_headers=litellm_additional_headers,
-            ),
-            custom_tool_config=CustomToolConfig(
-                chat_session_id=chat_session_id,
-                message_id=user_message.id if user_message else None,
-                additional_headers=custom_tool_additional_headers,
-            ),
-        )
+        # find out what tools to use
+        search_tool: SearchTool | None = None
+        tool_dict: dict[int, list[Tool]] = {}  # tool_id to tool
+        for db_tool_model in persona.tools:
+            # handle in-code tools specially
+            if db_tool_model.in_code_tool_id:
+                tool_cls = get_built_in_tool_by_id(db_tool_model.id, db_session)
+                if tool_cls.__name__ == SearchTool.__name__ and not latest_query_files:
+                    search_tool = SearchTool(
+                        db_session=db_session,
+                        user=user,
+                        persona=persona,
+                        retrieval_options=retrieval_options,
+                        prompt_config=prompt_config,
+                        llm=llm,
+                        fast_llm=fast_llm,
+                        pruning_config=document_pruning_config,
+                        selected_sections=selected_sections,
+                        chunks_above=new_msg_req.chunks_above,
+                        chunks_below=new_msg_req.chunks_below,
+                        full_doc=new_msg_req.full_doc,
+                        evaluation_type=LLMEvaluationType.BASIC
+                        if persona.llm_relevance_filter
+                        else LLMEvaluationType.SKIP,
+                    )
+                    tool_dict[db_tool_model.id] = [search_tool]
+                elif tool_cls.__name__ == ImageGenerationTool.__name__:
+                    img_generation_llm_config: LLMConfig | None = None
+                    if (
+                        llm
+                        and llm.config.api_key
+                        and llm.config.model_provider == "openai"
+                    ):
+                        img_generation_llm_config = LLMConfig(
+                            model_provider=llm.config.model_provider,
+                            model_name="dall-e-3",
+                            temperature=GEN_AI_TEMPERATURE,
+                            api_key=llm.config.api_key,
+                            api_base=llm.config.api_base,
+                            api_version=llm.config.api_version,
+                        )
+                    elif (
+                        llm.config.model_provider == "azure"
+                        and AZURE_DALLE_API_KEY is not None
+                    ):
+                        img_generation_llm_config = LLMConfig(
+                            model_provider="azure",
+                            model_name=f"azure/{AZURE_DALLE_DEPLOYMENT_NAME}",
+                            temperature=GEN_AI_TEMPERATURE,
+                            api_key=AZURE_DALLE_API_KEY,
+                            api_base=AZURE_DALLE_API_BASE,
+                            api_version=AZURE_DALLE_API_VERSION,
+                        )
+                    else:
+                        llm_providers = fetch_existing_llm_providers(db_session)
+                        openai_provider = next(
+                            iter(
+                                [
+                                    llm_provider
+                                    for llm_provider in llm_providers
+                                    if llm_provider.provider == "openai"
+                                ]
+                            ),
+                            None,
+                        )
+                        if not openai_provider or not openai_provider.api_key:
+                            raise ValueError(
+                                "Image generation tool requires an OpenAI API key"
+                            )
+                        img_generation_llm_config = LLMConfig(
+                            model_provider=openai_provider.provider,
+                            model_name="dall-e-3",
+                            temperature=GEN_AI_TEMPERATURE,
+                            api_key=openai_provider.api_key,
+                            api_base=openai_provider.api_base,
+                            api_version=openai_provider.api_version,
+                        )
+                    tool_dict[db_tool_model.id] = [
+                        ImageGenerationTool(
+                            api_key=cast(str, img_generation_llm_config.api_key),
+                            api_base=img_generation_llm_config.api_base,
+                            api_version=img_generation_llm_config.api_version,
+                            additional_headers=litellm_additional_headers,
+                            model=img_generation_llm_config.model_name,
+                        )
+                    ]
+                elif tool_cls.__name__ == InternetSearchTool.__name__:
+                    bing_api_key = BING_API_KEY
+                    if not bing_api_key:
+                        raise ValueError(
+                            "Internet search tool requires a Bing API key, please contact your Danswer admin to get it added!"
+                        )
+                    tool_dict[db_tool_model.id] = [
+                        InternetSearchTool(api_key=bing_api_key)
+                    ]
+
+                continue
+
+            # handle all custom tools
+            if db_tool_model.openapi_schema:
+                tool_dict[db_tool_model.id] = cast(
+                    list[Tool],
+                    build_custom_tools_from_openapi_schema_and_headers(
+                        db_tool_model.openapi_schema,
+                        dynamic_schema_info=DynamicSchemaInfo(
+                            chat_session_id=chat_session_id,
+                            message_id=user_message.id if user_message else None,
+                        ),
+                        custom_headers=(db_tool_model.custom_headers or [])
+                        + (
+                            header_dict_to_header_list(
+                                custom_tool_additional_headers or {}
+                            )
+                        ),
+                    ),
+                )
+
         tools: list[Tool] = []
         for tool_list in tool_dict.values():
             tools.extend(tool_list)
 
+        # factor in tool definition size when pruning
+        document_pruning_config.tool_num_tokens = compute_all_tool_tokens(
+            tools, llm_tokenizer
+        )
+        document_pruning_config.using_tool_message = explicit_tool_calling_supported(
+            llm_provider, llm_model_name
+        )
+
         # LLM prompt building, response capturing, etc.
         answer = Answer(
             is_connected=is_connected,
             question=final_msg.message,
             latest_query_files=latest_query_files,
-            answer_style_config=answer_style_config,
+            answer_style_config=AnswerStyleConfig(
+                citation_config=CitationConfig(
+                    all_docs_useful=selected_db_search_docs is not None
+                ),
+                document_pruning_config=document_pruning_config,
+                structured_response_format=new_msg_req.structured_response_format,
+            ),
             prompt_config=prompt_config,
             llm=(
                 llm
@@ -675,6 +741,7 @@ def stream_chat_message_objects(
                         yield LLMRelevanceFilterResponse(
                             llm_selected_doc_indices=llm_indices
                         )
+
                 elif packet.id == FINAL_CONTEXT_DOCUMENTS_ID:
                     yield FinalUsedContextDocsResponse(
                         final_context_docs=packet.response
@@ -692,7 +759,7 @@ def stream_chat_message_objects(
                         FileDescriptor(id=str(file_id), type=ChatFileType.IMAGE)
                         for file_id in file_ids
                     ]
-                    yield FileChatDisplay(
+                    yield ImageGenerationDisplay(
                         file_ids=[str(file_id) for file_id in file_ids]
                     )
                 elif packet.id == INTERNET_SEARCH_RESPONSE_ID:
@@ -706,32 +773,11 @@ def stream_chat_message_objects(
                     yield qa_docs_response
                 elif packet.id == CUSTOM_TOOL_RESPONSE_ID:
                     custom_tool_response = cast(CustomToolCallSummary, packet.response)
+                    yield CustomToolResponse(
+                        response=custom_tool_response.tool_result,
+                        tool_name=custom_tool_response.tool_name,
+                    )
 
-                    if (
-                        custom_tool_response.response_type == "image"
-                        or custom_tool_response.response_type == "csv"
-                    ):
-                        file_ids = custom_tool_response.tool_result.file_ids
-                        ai_message_files = [
-                            FileDescriptor(
-                                id=str(file_id),
-                                type=ChatFileType.IMAGE
-                                if custom_tool_response.response_type == "image"
-                                else ChatFileType.CSV,
-                            )
-                            for file_id in file_ids
-                        ]
-                        yield FileChatDisplay(
-                            file_ids=[str(file_id) for file_id in file_ids]
-                        )
-                    else:
-                        yield CustomToolResponse(
-                            response=custom_tool_response.tool_result,
-                            tool_name=custom_tool_response.tool_name,
-                        )
-
-            elif isinstance(packet, StreamStopInfo):
-                pass
             else:
                 if isinstance(packet, ToolCallFinalResult):
                     tool_result = packet
@@ -761,7 +807,6 @@ def stream_chat_message_objects(
 
     # Post-LLM answer processing
     try:
-        logger.debug("Post-LLM answer processing")
         message_specific_citations: MessageSpecificCitations | None = None
         if reference_db_search_docs:
             message_specific_citations = _translate_citations(
@@ -777,6 +822,7 @@ def stream_chat_message_objects(
                 tool_name_to_tool_id[tool.name] = tool_id
 
         gen_ai_response_message = partial_response(
+            reserved_message_id=reserved_message_id,
             message=answer.llm_answer,
             rephrased_query=(
                 qa_docs_response.rephrased_query if qa_docs_response else None
@@ -784,21 +830,21 @@ def stream_chat_message_objects(
             reference_docs=reference_db_search_docs,
             files=ai_message_files,
             token_count=len(llm_tokenizer_encode_func(answer.llm_answer)),
-            citations=(
-                message_specific_citations.citation_map
-                if message_specific_citations
-                else None
-            ),
+            citations=message_specific_citations.citation_map
+            if message_specific_citations
+            else None,
             error=None,
-            tool_call=(
-                ToolCall(
-                    tool_id=tool_name_to_tool_id[tool_result.tool_name],
-                    tool_name=tool_result.tool_name,
-                    tool_arguments=tool_result.tool_args,
-                    tool_result=tool_result.tool_result,
-                )
+            tool_calls=(
+                [
+                    ToolCall(
+                        tool_id=tool_name_to_tool_id[tool_result.tool_name],
+                        tool_name=tool_result.tool_name,
+                        tool_arguments=tool_result.tool_args,
+                        tool_result=tool_result.tool_result,
+                    )
+                ]
                 if tool_result
-                else None
+                else []
             ),
         )
 
@@ -822,6 +868,7 @@ def stream_chat_message_objects(
 def stream_chat_message(
     new_msg_req: CreateChatMessageRequest,
     user: User | None,
+    use_existing_user_message: bool = False,
     litellm_additional_headers: dict[str, str] | None = None,
     custom_tool_additional_headers: dict[str, str] | None = None,
     is_connected: Callable[[], bool] | None = None,
@@ -831,6 +878,7 @@ def stream_chat_message(
             new_msg_req=new_msg_req,
             user=user,
             db_session=db_session,
+            use_existing_user_message=use_existing_user_message,
             litellm_additional_headers=litellm_additional_headers,
             custom_tool_additional_headers=custom_tool_additional_headers,
             is_connected=is_connected,

backend/danswer/chat/prompts.yaml

@@ -9,19 +9,19 @@ prompts:
     system: >
       You are a question answering system that is constantly learning and improving.
       The current date is DANSWER_DATETIME_REPLACEMENT.
-
+      
       You can process and comprehend vast amounts of text and utilize this knowledge to provide
       grounded, accurate, and concise answers to diverse queries.
-
+      
       You always clearly communicate ANY UNCERTAINTY in your answer.
     # Task Prompt (as shown in UI)
     task: >
       Answer my query based on the documents provided.
       The documents may not all be relevant, ignore any documents that are not directly relevant
       to the most recent user query.
-
+      
       I have not read or seen any of the documents and do not want to read them.
-
+      
       If there are no relevant documents, refer to the chat history and your internal knowledge.
     # Inject a statement at the end of system prompt to inform the LLM of the current date/time
     # If the DANSWER_DATETIME_REPLACEMENT is set, the date/time is inserted there instead
@@ -30,21 +30,21 @@ prompts:
     # Prompts the LLM to include citations in the for [1], [2] etc.
     # which get parsed to match the passed in sources
     include_citations: true
-
+  
   - name: "ImageGeneration"
-    description: "Generates images from user descriptions!"
+    description: "Generates images based on user prompts!"
     system: >
-      You are an AI image generation assistant. Your role is to create high-quality images based on user descriptions.
-
-      For appropriate requests, you will generate an image that matches the user's requirements.
-      For inappropriate or unsafe requests, you will politely decline and explain why the request cannot be fulfilled.
-
-      You aim to be helpful while maintaining appropriate content standards.
+      You are an advanced image generation system capable of creating diverse and detailed images.
+      
+      You can interpret user prompts and generate high-quality, creative images that match their descriptions.
+      
+      You always strive to create safe and appropriate content, avoiding any harmful or offensive imagery.
     task: >
-      Based on the user's description, create a high-quality image that accurately reflects their request. 
-      Pay close attention to the specified details, styles, and desired elements.
-
-      If the request is not appropriate or cannot be fulfilled, explain why and suggest alternatives.
+      Generate an image based on the user's description.
+      
+      Provide a detailed description of the generated image, including key elements, colors, and composition.
+      
+      If the request is not possible or appropriate, explain why and suggest alternatives.
     datetime_aware: true
     include_citations: false
 
@@ -64,13 +64,14 @@ prompts:
     datetime_aware: true
     include_citations: true
 
+
   - name: "Summarize"
     description: "Summarize relevant information from retrieved context!"
     system: >
       You are a text summarizing assistant that highlights the most important knowledge from the
       context provided, prioritizing the information that relates to the user query.
       The current date is DANSWER_DATETIME_REPLACEMENT.
-
+      
       You ARE NOT creative and always stick to the provided documents.
       If there are no documents, refer to the conversation history.
 
@@ -83,6 +84,7 @@ prompts:
     datetime_aware: true
     include_citations: true
 
+
   - name: "Paraphrase"
     description: "Recites information from retrieved context! Least creative but most safe!"
     system: >
@@ -90,10 +92,10 @@ prompts:
       The current date is DANSWER_DATETIME_REPLACEMENT.
 
       You only provide quotes that are EXACT substrings from provided documents!
-
+      
       If there are no documents provided,
       simply tell the user that there are no documents to reference.
-
+      
       You NEVER generate new text or phrases outside of the citation.
       DO NOT explain your responses, only provide the quotes and NOTHING ELSE.
     task: >

backend/danswer/configs/app_configs.py

@@ -163,17 +163,6 @@ try:
 except ValueError:
     POSTGRES_POOL_RECYCLE = POSTGRES_POOL_RECYCLE_DEFAULT
 
-# Experimental setting to control idle transactions
-POSTGRES_IDLE_SESSIONS_TIMEOUT_DEFAULT = 0  # milliseconds
-try:
-    POSTGRES_IDLE_SESSIONS_TIMEOUT = int(
-        os.environ.get(
-            "POSTGRES_IDLE_SESSIONS_TIMEOUT", POSTGRES_IDLE_SESSIONS_TIMEOUT_DEFAULT
-        )
-    )
-except ValueError:
-    POSTGRES_IDLE_SESSIONS_TIMEOUT = POSTGRES_IDLE_SESSIONS_TIMEOUT_DEFAULT
-
 REDIS_SSL = os.getenv("REDIS_SSL", "").lower() == "true"
 REDIS_HOST = os.environ.get("REDIS_HOST") or "localhost"
 REDIS_PORT = int(os.environ.get("REDIS_PORT", 6379))
@@ -262,6 +251,9 @@ ENABLED_CONNECTOR_TYPES = os.environ.get("ENABLED_CONNECTOR_TYPES") or ""
 # for some connectors
 ENABLE_EXPENSIVE_EXPERT_CALLS = False
 
+GOOGLE_DRIVE_INCLUDE_SHARED = False
+GOOGLE_DRIVE_FOLLOW_SHORTCUTS = False
+GOOGLE_DRIVE_ONLY_ORG_PUBLIC = False
 
 # TODO these should be available for frontend configuration, via advanced options expandable
 WEB_CONNECTOR_IGNORED_CLASSES = os.environ.get(
@@ -489,17 +481,3 @@ CONTROL_PLANE_API_BASE_URL = os.environ.get(
 
 # JWT configuration
 JWT_ALGORITHM = "HS256"
-
-# Super Users
-SUPER_USERS = json.loads(os.environ.get("SUPER_USERS", '["pablo@danswer.ai"]'))
-SUPER_CLOUD_API_KEY = os.environ.get("SUPER_CLOUD_API_KEY", "api_key")
-
-
-#####
-# API Key Configs
-#####
-# refers to the rounds described here: https://passlib.readthedocs.io/en/stable/lib/passlib.hash.sha256_crypt.html
-_API_KEY_HASH_ROUNDS_RAW = os.environ.get("API_KEY_HASH_ROUNDS")
-API_KEY_HASH_ROUNDS = (
-    int(_API_KEY_HASH_ROUNDS_RAW) if _API_KEY_HASH_ROUNDS_RAW else None
-)

backend/danswer/configs/constants.py

@@ -125,8 +125,6 @@ class DocumentSource(str, Enum):
     OCI_STORAGE = "oci_storage"
     XENFORO = "xenforo"
     NOT_APPLICABLE = "not_applicable"
-    FRESHDESK = "freshdesk"
-    FIREFLIES = "fireflies"
 
 
 DocumentSourceRequiringTenantContext: list[DocumentSource] = [DocumentSource.FILE]
@@ -226,9 +224,6 @@ class DanswerRedisLocks:
     PRUNING_LOCK_PREFIX = "da_lock:pruning"
     INDEXING_METADATA_PREFIX = "da_metadata:indexing"
 
-    SLACK_BOT_LOCK = "da_lock:slack_bot"
-    SLACK_BOT_HEARTBEAT_PREFIX = "da_heartbeat:slack_bot"
-
 
 class DanswerCeleryPriority(int, Enum):
     HIGHEST = 0

backend/danswer/connectors/confluence/connector.py

@@ -17,7 +17,6 @@ from danswer.connectors.interfaces import GenerateDocumentsOutput
 from danswer.connectors.interfaces import GenerateSlimDocumentOutput
 from danswer.connectors.interfaces import LoadConnector
 from danswer.connectors.interfaces import PollConnector
-from danswer.connectors.interfaces import SecondsSinceUnixEpoch
 from danswer.connectors.interfaces import SlimConnector
 from danswer.connectors.models import BasicExpertInfo
 from danswer.connectors.models import ConnectorMissingCredentialError
@@ -250,11 +249,7 @@ class ConfluenceConnector(LoadConnector, PollConnector, SlimConnector):
         self.cql_time_filter += f" and lastmodified <= '{formatted_end_time}'"
         return self._fetch_document_batches()
 
-    def retrieve_all_slim_documents(
-        self,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
+    def retrieve_all_slim_documents(self) -> GenerateSlimDocumentOutput:
         if self.confluence_client is None:
             raise ConnectorMissingCredentialError("Confluence")
 

backend/danswer/connectors/cross_connector_utils/miscellaneous_utils.py

@@ -23,16 +23,7 @@ def datetime_to_utc(dt: datetime) -> datetime:
 
 
 def time_str_to_utc(datetime_str: str) -> datetime:
-    try:
-        dt = parse(datetime_str)
-    except ValueError:
-        # Handle malformed timezone by attempting to fix common format issues
-        if "0000" in datetime_str:
-            # Convert "0000" to "+0000" for proper timezone parsing
-            fixed_dt_str = datetime_str.replace(" 0000", " +0000")
-            dt = parse(fixed_dt_str)
-        else:
-            raise
+    dt = parse(datetime_str)
     return datetime_to_utc(dt)
 
 

backend/danswer/connectors/factory.py

@@ -16,8 +16,6 @@ from danswer.connectors.discourse.connector import DiscourseConnector
 from danswer.connectors.document360.connector import Document360Connector
 from danswer.connectors.dropbox.connector import DropboxConnector
 from danswer.connectors.file.connector import LocalFileConnector
-from danswer.connectors.fireflies.connector import FirefliesConnector
-from danswer.connectors.freshdesk.connector import FreshdeskConnector
 from danswer.connectors.github.connector import GithubConnector
 from danswer.connectors.gitlab.connector import GitlabConnector
 from danswer.connectors.gmail.connector import GmailConnector
@@ -101,8 +99,6 @@ def identify_connector_class(
         DocumentSource.GOOGLE_CLOUD_STORAGE: BlobStorageConnector,
         DocumentSource.OCI_STORAGE: BlobStorageConnector,
         DocumentSource.XENFORO: XenforoConnector,
-        DocumentSource.FRESHDESK: FreshdeskConnector,
-        DocumentSource.FIREFLIES: FirefliesConnector,
     }
     connector_by_source = connector_map.get(source, {})
 

backend/danswer/connectors/file/connector.py

@@ -27,8 +27,8 @@ from danswer.file_processing.extract_file_text import read_pdf_file
 from danswer.file_processing.extract_file_text import read_text_file
 from danswer.file_store.file_store import get_default_file_store
 from danswer.utils.logger import setup_logger
+from shared_configs.configs import CURRENT_TENANT_ID_CONTEXTVAR
 from shared_configs.configs import POSTGRES_DEFAULT_SCHEMA
-from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
 
 logger = setup_logger()
 
@@ -123,13 +123,9 @@ def _process_file(
             "filename",
             "file_display_name",
             "title",
-            "connector_type",
         ]
     }
 
-    source_type_str = all_metadata.get("connector_type")
-    source_type = DocumentSource(source_type_str) if source_type_str else None
-
     p_owner_names = all_metadata.get("primary_owners")
     s_owner_names = all_metadata.get("secondary_owners")
     p_owners = (
@@ -149,7 +145,7 @@ def _process_file(
             sections=[
                 Section(link=all_metadata.get("link"), text=file_content_raw.strip())
             ],
-            source=source_type or DocumentSource.FILE,
+            source=DocumentSource.FILE,
             semantic_identifier=file_display_name,
             title=title,
             doc_updated_at=final_time_updated,

backend/danswer/connectors/fireflies/connector.py

@@ -1,182 +0,0 @@
-from collections.abc import Iterator
-from datetime import datetime
-from datetime import timezone
-from typing import List
-
-import requests
-
-from danswer.configs.app_configs import INDEX_BATCH_SIZE
-from danswer.configs.constants import DocumentSource
-from danswer.connectors.interfaces import GenerateDocumentsOutput
-from danswer.connectors.interfaces import LoadConnector
-from danswer.connectors.interfaces import PollConnector
-from danswer.connectors.interfaces import SecondsSinceUnixEpoch
-from danswer.connectors.models import BasicExpertInfo
-from danswer.connectors.models import ConnectorMissingCredentialError
-from danswer.connectors.models import Document
-from danswer.connectors.models import Section
-from danswer.utils.logger import setup_logger
-
-logger = setup_logger()
-
-_FIREFLIES_ID_PREFIX = "FIREFLIES_"
-
-_FIREFLIES_API_URL = "https://api.fireflies.ai/graphql"
-
-_FIREFLIES_TRANSCRIPT_QUERY_SIZE = 50  # Max page size is 50
-
-_FIREFLIES_API_QUERY = """
-    query Transcripts($fromDate: DateTime, $toDate: DateTime, $limit: Int!, $skip: Int!) {
-        transcripts(fromDate: $fromDate, toDate: $toDate, limit: $limit, skip: $skip) {
-            id
-            title
-            host_email
-            participants
-            date
-            transcript_url
-            sentences {
-                text
-                speaker_name
-            }
-        }
-    }
-"""
-
-
-def _create_doc_from_transcript(transcript: dict) -> Document | None:
-    meeting_text = ""
-    sentences = transcript.get("sentences", [])
-    if sentences:
-        for sentence in sentences:
-            meeting_text += sentence.get("speaker_name") or "Unknown Speaker"
-            meeting_text += ": " + sentence.get("text", "") + "\n\n"
-    else:
-        return None
-
-    meeting_link = transcript["transcript_url"]
-
-    fireflies_id = _FIREFLIES_ID_PREFIX + transcript["id"]
-
-    meeting_title = transcript["title"] or "No Title"
-
-    meeting_date_unix = transcript["date"]
-    meeting_date = datetime.fromtimestamp(meeting_date_unix / 1000, tz=timezone.utc)
-
-    meeting_host_email = transcript["host_email"]
-    host_email_user_info = [BasicExpertInfo(email=meeting_host_email)]
-
-    meeting_participants_email_list = []
-    for participant in transcript.get("participants", []):
-        if participant != meeting_host_email and participant:
-            meeting_participants_email_list.append(BasicExpertInfo(email=participant))
-
-    return Document(
-        id=fireflies_id,
-        sections=[
-            Section(
-                link=meeting_link,
-                text=meeting_text,
-            )
-        ],
-        source=DocumentSource.FIREFLIES,
-        semantic_identifier=meeting_title,
-        metadata={},
-        doc_updated_at=meeting_date,
-        primary_owners=host_email_user_info,
-        secondary_owners=meeting_participants_email_list,
-    )
-
-
-class FirefliesConnector(PollConnector, LoadConnector):
-    def __init__(self, batch_size: int = INDEX_BATCH_SIZE) -> None:
-        self.batch_size = batch_size
-
-    def load_credentials(self, credentials: dict[str, str]) -> None:
-        api_key = credentials.get("fireflies_api_key")
-
-        if not isinstance(api_key, str):
-            raise ConnectorMissingCredentialError(
-                "The Fireflies API key must be a string"
-            )
-
-        self.api_key = api_key
-
-        return None
-
-    def _fetch_transcripts(
-        self, start_datetime: str | None = None, end_datetime: str | None = None
-    ) -> Iterator[List[dict]]:
-        if self.api_key is None:
-            raise ConnectorMissingCredentialError("Missing API key")
-
-        headers = {
-            "Content-Type": "application/json",
-            "Authorization": "Bearer " + self.api_key,
-        }
-
-        skip = 0
-        variables: dict[str, int | str] = {
-            "limit": _FIREFLIES_TRANSCRIPT_QUERY_SIZE,
-        }
-
-        if start_datetime:
-            variables["fromDate"] = start_datetime
-        if end_datetime:
-            variables["toDate"] = end_datetime
-
-        while True:
-            variables["skip"] = skip
-            response = requests.post(
-                _FIREFLIES_API_URL,
-                headers=headers,
-                json={"query": _FIREFLIES_API_QUERY, "variables": variables},
-            )
-
-            response.raise_for_status()
-
-            if response.status_code == 204:
-                break
-
-            recieved_transcripts = response.json()
-            parsed_transcripts = recieved_transcripts.get("data", {}).get(
-                "transcripts", []
-            )
-
-            yield parsed_transcripts
-
-            if len(parsed_transcripts) < _FIREFLIES_TRANSCRIPT_QUERY_SIZE:
-                break
-
-            skip += _FIREFLIES_TRANSCRIPT_QUERY_SIZE
-
-    def _process_transcripts(
-        self, start: str | None = None, end: str | None = None
-    ) -> GenerateDocumentsOutput:
-        doc_batch: List[Document] = []
-
-        for transcript_batch in self._fetch_transcripts(start, end):
-            for transcript in transcript_batch:
-                if doc := _create_doc_from_transcript(transcript):
-                    doc_batch.append(doc)
-
-                if len(doc_batch) >= self.batch_size:
-                    yield doc_batch
-                    doc_batch = []
-
-        if doc_batch:
-            yield doc_batch
-
-    def load_from_state(self) -> GenerateDocumentsOutput:
-        return self._process_transcripts()
-
-    def poll_source(
-        self, start_unixtime: SecondsSinceUnixEpoch, end_unixtime: SecondsSinceUnixEpoch
-    ) -> GenerateDocumentsOutput:
-        start_datetime = datetime.fromtimestamp(
-            start_unixtime, tz=timezone.utc
-        ).strftime("%Y-%m-%dT%H:%M:%S.000Z")
-        end_datetime = datetime.fromtimestamp(end_unixtime, tz=timezone.utc).strftime(
-            "%Y-%m-%dT%H:%M:%S.000Z"
-        )
-
-        yield from self._process_transcripts(start_datetime, end_datetime)

backend/danswer/connectors/freshdesk/connector.py

@@ -1,239 +0,0 @@
-import json
-from collections.abc import Iterator
-from datetime import datetime
-from datetime import timezone
-from typing import List
-
-import requests
-
-from danswer.configs.app_configs import INDEX_BATCH_SIZE
-from danswer.configs.constants import DocumentSource
-from danswer.connectors.interfaces import GenerateDocumentsOutput
-from danswer.connectors.interfaces import LoadConnector
-from danswer.connectors.interfaces import PollConnector
-from danswer.connectors.interfaces import SecondsSinceUnixEpoch
-from danswer.connectors.models import ConnectorMissingCredentialError
-from danswer.connectors.models import Document
-from danswer.connectors.models import Section
-from danswer.file_processing.html_utils import parse_html_page_basic
-from danswer.utils.logger import setup_logger
-
-logger = setup_logger()
-
-_FRESHDESK_ID_PREFIX = "FRESHDESK_"
-
-
-_TICKET_FIELDS_TO_INCLUDE = {
-    "fr_escalated",
-    "spam",
-    "priority",
-    "source",
-    "status",
-    "type",
-    "is_escalated",
-    "tags",
-    "nr_due_by",
-    "nr_escalated",
-    "cc_emails",
-    "fwd_emails",
-    "reply_cc_emails",
-    "ticket_cc_emails",
-    "support_email",
-    "to_emails",
-}
-
-_SOURCE_NUMBER_TYPE_MAP: dict[int, str] = {
-    1: "Email",
-    2: "Portal",
-    3: "Phone",
-    7: "Chat",
-    9: "Feedback Widget",
-    10: "Outbound Email",
-}
-
-_PRIORITY_NUMBER_TYPE_MAP: dict[int, str] = {
-    1: "low",
-    2: "medium",
-    3: "high",
-    4: "urgent",
-}
-
-_STATUS_NUMBER_TYPE_MAP: dict[int, str] = {
-    2: "open",
-    3: "pending",
-    4: "resolved",
-    5: "closed",
-}
-
-
-def _create_metadata_from_ticket(ticket: dict) -> dict:
-    metadata: dict[str, str | list[str]] = {}
-    # Combine all emails into a list so there are no repeated emails
-    email_data: set[str] = set()
-
-    for key, value in ticket.items():
-        # Skip fields that aren't useful for embedding
-        if key not in _TICKET_FIELDS_TO_INCLUDE:
-            continue
-
-        # Skip empty fields
-        if not value or value == "[]":
-            continue
-
-        # Convert strings or lists to strings
-        stringified_value: str | list[str]
-        if isinstance(value, list):
-            stringified_value = [str(item) for item in value]
-        else:
-            stringified_value = str(value)
-
-        if "email" in key:
-            if isinstance(stringified_value, list):
-                email_data.update(stringified_value)
-            else:
-                email_data.add(stringified_value)
-        else:
-            metadata[key] = stringified_value
-
-    if email_data:
-        metadata["emails"] = list(email_data)
-
-    # Convert source numbers to human-parsable string
-    if source_number := ticket.get("source"):
-        metadata["source"] = _SOURCE_NUMBER_TYPE_MAP.get(
-            source_number, "Unknown Source Type"
-        )
-
-    # Convert priority numbers to human-parsable string
-    if priority_number := ticket.get("priority"):
-        metadata["priority"] = _PRIORITY_NUMBER_TYPE_MAP.get(
-            priority_number, "Unknown Priority"
-        )
-
-    # Convert status to human-parsable string
-    if status_number := ticket.get("status"):
-        metadata["status"] = _STATUS_NUMBER_TYPE_MAP.get(
-            status_number, "Unknown Status"
-        )
-
-    due_by = datetime.fromisoformat(ticket["due_by"].replace("Z", "+00:00"))
-    metadata["overdue"] = str(datetime.now(timezone.utc) > due_by)
-
-    return metadata
-
-
-def _create_doc_from_ticket(ticket: dict, domain: str) -> Document:
-    # Use the ticket description as the text
-    text = f"Ticket description: {parse_html_page_basic(ticket.get('description_text', ''))}"
-    metadata = _create_metadata_from_ticket(ticket)
-
-    # This is also used in the ID because it is more unique than the just the ticket ID
-    link = f"https://{domain}.freshdesk.com/helpdesk/tickets/{ticket['id']}"
-
-    return Document(
-        id=_FRESHDESK_ID_PREFIX + link,
-        sections=[
-            Section(
-                link=link,
-                text=text,
-            )
-        ],
-        source=DocumentSource.FRESHDESK,
-        semantic_identifier=ticket["subject"],
-        metadata=metadata,
-        doc_updated_at=datetime.fromisoformat(
-            ticket["updated_at"].replace("Z", "+00:00")
-        ),
-    )
-
-
-class FreshdeskConnector(PollConnector, LoadConnector):
-    def __init__(self, batch_size: int = INDEX_BATCH_SIZE) -> None:
-        self.batch_size = batch_size
-
-    def load_credentials(self, credentials: dict[str, str | int]) -> None:
-        api_key = credentials.get("freshdesk_api_key")
-        domain = credentials.get("freshdesk_domain")
-        password = credentials.get("freshdesk_password")
-
-        if not all(isinstance(cred, str) for cred in [domain, api_key, password]):
-            raise ConnectorMissingCredentialError(
-                "All Freshdesk credentials must be strings"
-            )
-
-        self.api_key = str(api_key)
-        self.domain = str(domain)
-        self.password = str(password)
-
-    def _fetch_tickets(
-        self, start: datetime | None = None, end: datetime | None = None
-    ) -> Iterator[List[dict]]:
-        """
-        'end' is not currently used, so we may double fetch tickets created after the indexing
-        starts but before the actual call is made.
-
-        To use 'end' would require us to use the search endpoint but it has limitations,
-        namely having to fetch all IDs and then individually fetch each ticket because there is no
-        'include' field available for this endpoint:
-        https://developers.freshdesk.com/api/#filter_tickets
-        """
-        if self.api_key is None or self.domain is None or self.password is None:
-            raise ConnectorMissingCredentialError("freshdesk")
-
-        base_url = f"https://{self.domain}.freshdesk.com/api/v2/tickets"
-        params: dict[str, int | str] = {
-            "include": "description",
-            "per_page": 50,
-            "page": 1,
-        }
-
-        if start:
-            params["updated_since"] = start.isoformat()
-
-        while True:
-            response = requests.get(
-                base_url, auth=(self.api_key, self.password), params=params
-            )
-            response.raise_for_status()
-
-            if response.status_code == 204:
-                break
-
-            tickets = json.loads(response.content)
-            logger.info(
-                f"Fetched {len(tickets)} tickets from Freshdesk API (Page {params['page']})"
-            )
-
-            yield tickets
-
-            if len(tickets) < int(params["per_page"]):
-                break
-
-            params["page"] = int(params["page"]) + 1
-
-    def _process_tickets(
-        self, start: datetime | None = None, end: datetime | None = None
-    ) -> GenerateDocumentsOutput:
-        doc_batch: List[Document] = []
-
-        for ticket_batch in self._fetch_tickets(start, end):
-            for ticket in ticket_batch:
-                doc_batch.append(_create_doc_from_ticket(ticket, self.domain))
-
-                if len(doc_batch) >= self.batch_size:
-                    yield doc_batch
-                    doc_batch = []
-
-        if doc_batch:
-            yield doc_batch
-
-    def load_from_state(self) -> GenerateDocumentsOutput:
-        return self._process_tickets()
-
-    def poll_source(
-        self, start: SecondsSinceUnixEpoch, end: SecondsSinceUnixEpoch
-    ) -> GenerateDocumentsOutput:
-        start_datetime = datetime.fromtimestamp(start, tz=timezone.utc)
-        end_datetime = datetime.fromtimestamp(end, tz=timezone.utc)
-
-        yield from self._process_tickets(start_datetime, end_datetime)

backend/danswer/connectors/gmail/connector.py

@@ -1,360 +1,221 @@
 from base64 import urlsafe_b64decode
 from typing import Any
+from typing import cast
 from typing import Dict
 
 from google.oauth2.credentials import Credentials as OAuthCredentials  # type: ignore
 from google.oauth2.service_account import Credentials as ServiceAccountCredentials  # type: ignore
+from googleapiclient import discovery  # type: ignore
 
 from danswer.configs.app_configs import INDEX_BATCH_SIZE
 from danswer.configs.constants import DocumentSource
 from danswer.connectors.cross_connector_utils.miscellaneous_utils import time_str_to_utc
-from danswer.connectors.google_utils.google_auth import get_google_creds
-from danswer.connectors.google_utils.google_utils import execute_paginated_retrieval
-from danswer.connectors.google_utils.resources import get_admin_service
-from danswer.connectors.google_utils.resources import get_gmail_service
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_PRIMARY_ADMIN_KEY,
+from danswer.connectors.gmail.connector_auth import (
+    get_gmail_creds_for_authorized_user,
+)
+from danswer.connectors.gmail.connector_auth import (
+    get_gmail_creds_for_service_account,
+)
+from danswer.connectors.gmail.constants import (
+    DB_CREDENTIALS_DICT_DELEGATED_USER_KEY,
+)
+from danswer.connectors.gmail.constants import DB_CREDENTIALS_DICT_TOKEN_KEY
+from danswer.connectors.gmail.constants import (
+    GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
 )
-from danswer.connectors.google_utils.shared_constants import MISSING_SCOPES_ERROR_STR
-from danswer.connectors.google_utils.shared_constants import ONYX_SCOPE_INSTRUCTIONS
-from danswer.connectors.google_utils.shared_constants import SLIM_BATCH_SIZE
-from danswer.connectors.google_utils.shared_constants import USER_FIELDS
 from danswer.connectors.interfaces import GenerateDocumentsOutput
-from danswer.connectors.interfaces import GenerateSlimDocumentOutput
 from danswer.connectors.interfaces import LoadConnector
 from danswer.connectors.interfaces import PollConnector
 from danswer.connectors.interfaces import SecondsSinceUnixEpoch
-from danswer.connectors.interfaces import SlimConnector
-from danswer.connectors.models import BasicExpertInfo
 from danswer.connectors.models import Document
 from danswer.connectors.models import Section
-from danswer.connectors.models import SlimDocument
 from danswer.utils.logger import setup_logger
-from danswer.utils.retry_wrapper import retry_builder
-
 
 logger = setup_logger()
 
-# This is for the initial list call to get the thread ids
-THREAD_LIST_FIELDS = "nextPageToken, threads(id)"
 
-# These are the fields to retrieve using the ID from the initial list call
-PARTS_FIELDS = "parts(body(data), mimeType)"
-PAYLOAD_FIELDS = f"payload(headers, {PARTS_FIELDS})"
-MESSAGES_FIELDS = f"messages(id, {PAYLOAD_FIELDS})"
-THREADS_FIELDS = f"threads(id, {MESSAGES_FIELDS})"
-THREAD_FIELDS = f"id, {MESSAGES_FIELDS}"
-
-EMAIL_FIELDS = [
-    "cc",
-    "bcc",
-    "from",
-    "to",
-]
-
-add_retries = retry_builder(tries=50, max_delay=30)
-
-
-def _build_time_range_query(
-    time_range_start: SecondsSinceUnixEpoch | None = None,
-    time_range_end: SecondsSinceUnixEpoch | None = None,
-) -> str | None:
-    query = ""
-    if time_range_start is not None and time_range_start != 0:
-        query += f"after:{int(time_range_start)}"
-    if time_range_end is not None and time_range_end != 0:
-        query += f" before:{int(time_range_end)}"
-    query = query.strip()
-
-    if len(query) == 0:
-        return None
-
-    return query
-
-
-def _clean_email_and_extract_name(email: str) -> tuple[str, str | None]:
-    email = email.strip()
-    if "<" in email and ">" in email:
-        # Handle format: "Display Name <email@domain.com>"
-        display_name = email[: email.find("<")].strip()
-        email_address = email[email.find("<") + 1 : email.find(">")].strip()
-        return email_address, display_name if display_name else None
-    else:
-        # Handle plain email address
-        return email.strip(), None
-
-
-def _get_owners_from_emails(emails: dict[str, str | None]) -> list[BasicExpertInfo]:
-    owners = []
-    for email, names in emails.items():
-        if names:
-            name_parts = names.split(" ")
-            first_name = " ".join(name_parts[:-1])
-            last_name = name_parts[-1]
-        else:
-            first_name = None
-            last_name = None
-        owners.append(
-            BasicExpertInfo(email=email, first_name=first_name, last_name=last_name)
-        )
-    return owners
-
-
-def _get_message_body(payload: dict[str, Any]) -> str:
-    parts = payload.get("parts", [])
-    message_body = ""
-    for part in parts:
-        mime_type = part.get("mimeType")
-        body = part.get("body")
-        if mime_type == "text/plain" and body:
-            data = body.get("data", "")
-            text = urlsafe_b64decode(data).decode()
-            message_body += text
-    return message_body
-
-
-def message_to_section(message: Dict[str, Any]) -> tuple[Section, dict[str, str]]:
-    link = f"https://mail.google.com/mail/u/0/#inbox/{message['id']}"
-
-    payload = message.get("payload", {})
-    headers = payload.get("headers", [])
-    metadata: dict[str, Any] = {}
-    for header in headers:
-        name = header.get("name").lower()
-        value = header.get("value")
-        if name in EMAIL_FIELDS:
-            metadata[name] = value
-        if name == "subject":
-            metadata["subject"] = value
-        if name == "date":
-            metadata["updated_at"] = value
-
-    if labels := message.get("labelIds"):
-        metadata["labels"] = labels
-
-    message_data = ""
-    for name, value in metadata.items():
-        # updated at isnt super useful for the llm
-        if name != "updated_at":
-            message_data += f"{name}: {value}\n"
-
-    message_body_text: str = _get_message_body(payload)
-
-    return Section(link=link, text=message_body_text + message_data), metadata
-
-
-def thread_to_document(full_thread: Dict[str, Any]) -> Document | None:
-    all_messages = full_thread.get("messages", [])
-    if not all_messages:
-        return None
-
-    sections = []
-    semantic_identifier = ""
-    updated_at = None
-    from_emails: dict[str, str | None] = {}
-    other_emails: dict[str, str | None] = {}
-    for message in all_messages:
-        section, message_metadata = message_to_section(message)
-        sections.append(section)
-
-        for name, value in message_metadata.items():
-            if name in EMAIL_FIELDS:
-                email, display_name = _clean_email_and_extract_name(value)
-                if name == "from":
-                    from_emails[email] = (
-                        display_name if not from_emails.get(email) else None
-                    )
-                else:
-                    other_emails[email] = (
-                        display_name if not other_emails.get(email) else None
-                    )
-
-        # If we haven't set the semantic identifier yet, set it to the subject of the first message
-        if not semantic_identifier:
-            semantic_identifier = message_metadata.get("subject", "")
-
-        if message_metadata.get("updated_at"):
-            updated_at = message_metadata.get("updated_at")
-
-    updated_at_datetime = None
-    if updated_at:
-        updated_at_datetime = time_str_to_utc(updated_at)
-
-    id = full_thread.get("id")
-    if not id:
-        raise ValueError("Thread ID is required")
-
-    primary_owners = _get_owners_from_emails(from_emails)
-    secondary_owners = _get_owners_from_emails(other_emails)
-
-    return Document(
-        id=id,
-        semantic_identifier=semantic_identifier,
-        sections=sections,
-        source=DocumentSource.GMAIL,
-        # This is used to perform permission sync
-        primary_owners=primary_owners,
-        secondary_owners=secondary_owners,
-        doc_updated_at=updated_at_datetime,
-        # Not adding emails to metadata because it's already in the sections
-        metadata={},
-    )
-
-
-class GmailConnector(LoadConnector, PollConnector, SlimConnector):
+class GmailConnector(LoadConnector, PollConnector):
     def __init__(self, batch_size: int = INDEX_BATCH_SIZE) -> None:
         self.batch_size = batch_size
-
-        self._creds: OAuthCredentials | ServiceAccountCredentials | None = None
-        self._primary_admin_email: str | None = None
-
-    @property
-    def primary_admin_email(self) -> str:
-        if self._primary_admin_email is None:
-            raise RuntimeError(
-                "Primary admin email missing, "
-                "should not call this property "
-                "before calling load_credentials"
-            )
-        return self._primary_admin_email
-
-    @property
-    def google_domain(self) -> str:
-        if self._primary_admin_email is None:
-            raise RuntimeError(
-                "Primary admin email missing, "
-                "should not call this property "
-                "before calling load_credentials"
-            )
-        return self._primary_admin_email.split("@")[-1]
-
-    @property
-    def creds(self) -> OAuthCredentials | ServiceAccountCredentials:
-        if self._creds is None:
-            raise RuntimeError(
-                "Creds missing, "
-                "should not call this property "
-                "before calling load_credentials"
-            )
-        return self._creds
+        self.creds: OAuthCredentials | ServiceAccountCredentials | None = None
 
     def load_credentials(self, credentials: dict[str, Any]) -> dict[str, str] | None:
-        primary_admin_email = credentials[DB_CREDENTIALS_PRIMARY_ADMIN_KEY]
-        self._primary_admin_email = primary_admin_email
+        """Checks for two different types of credentials.
+        (1) A credential which holds a token acquired via a user going thorugh
+        the Google OAuth flow.
+        (2) A credential which holds a service account key JSON file, which
+        can then be used to impersonate any user in the workspace.
+        """
+        creds: OAuthCredentials | ServiceAccountCredentials | None = None
+        new_creds_dict = None
+        if DB_CREDENTIALS_DICT_TOKEN_KEY in credentials:
+            access_token_json_str = cast(
+                str, credentials[DB_CREDENTIALS_DICT_TOKEN_KEY]
+            )
+            creds = get_gmail_creds_for_authorized_user(
+                token_json_str=access_token_json_str
+            )
 
-        self._creds, new_creds_dict = get_google_creds(
-            credentials=credentials,
-            source=DocumentSource.GMAIL,
-        )
+            # tell caller to update token stored in DB if it has changed
+            # (e.g. the token has been refreshed)
+            new_creds_json_str = creds.to_json() if creds else ""
+            if new_creds_json_str != access_token_json_str:
+                new_creds_dict = {DB_CREDENTIALS_DICT_TOKEN_KEY: new_creds_json_str}
+
+        if GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY in credentials:
+            service_account_key_json_str = credentials[
+                GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY
+            ]
+            creds = get_gmail_creds_for_service_account(
+                service_account_key_json_str=service_account_key_json_str
+            )
+
+            # "Impersonate" a user if one is specified
+            delegated_user_email = cast(
+                str | None, credentials.get(DB_CREDENTIALS_DICT_DELEGATED_USER_KEY)
+            )
+            if delegated_user_email:
+                creds = creds.with_subject(delegated_user_email) if creds else None  # type: ignore
+
+        if creds is None:
+            raise PermissionError(
+                "Unable to access Gmail - unknown credential structure."
+            )
+
+        self.creds = creds
         return new_creds_dict
 
-    def _get_all_user_emails(self) -> list[str]:
-        admin_service = get_admin_service(self.creds, self.primary_admin_email)
-        emails = []
-        for user in execute_paginated_retrieval(
-            retrieval_function=admin_service.users().list,
-            list_key="users",
-            fields=USER_FIELDS,
-            domain=self.google_domain,
-        ):
-            if email := user.get("primaryEmail"):
-                emails.append(email)
-        return emails
+    def _get_email_body(self, payload: dict[str, Any]) -> str:
+        parts = payload.get("parts", [])
+        email_body = ""
+        for part in parts:
+            mime_type = part.get("mimeType")
+            body = part.get("body")
+            if mime_type == "text/plain":
+                data = body.get("data", "")
+                text = urlsafe_b64decode(data).decode()
+                email_body += text
+        return email_body
 
-    def _fetch_threads(
+    def _email_to_document(self, full_email: Dict[str, Any]) -> Document:
+        email_id = full_email["id"]
+        payload = full_email["payload"]
+        headers = payload.get("headers")
+        labels = full_email.get("labelIds", [])
+        metadata = {}
+        if headers:
+            for header in headers:
+                name = header.get("name").lower()
+                value = header.get("value")
+                if name in ["from", "to", "subject", "date", "cc", "bcc"]:
+                    metadata[name] = value
+        email_data = ""
+        for name, value in metadata.items():
+            email_data += f"{name}: {value}\n"
+        metadata["labels"] = labels
+        logger.debug(f"{email_data}")
+        email_body_text: str = self._get_email_body(payload)
+        date_str = metadata.get("date")
+        email_updated_at = time_str_to_utc(date_str) if date_str else None
+        link = f"https://mail.google.com/mail/u/0/#inbox/{email_id}"
+        return Document(
+            id=email_id,
+            sections=[Section(link=link, text=email_data + email_body_text)],
+            source=DocumentSource.GMAIL,
+            title=metadata.get("subject"),
+            semantic_identifier=metadata.get("subject", "Untitled Email"),
+            doc_updated_at=email_updated_at,
+            metadata=metadata,
+        )
+
+    @staticmethod
+    def _build_time_range_query(
+        time_range_start: SecondsSinceUnixEpoch | None = None,
+        time_range_end: SecondsSinceUnixEpoch | None = None,
+    ) -> str | None:
+        query = ""
+        if time_range_start is not None and time_range_start != 0:
+            query += f"after:{int(time_range_start)}"
+        if time_range_end is not None and time_range_end != 0:
+            query += f" before:{int(time_range_end)}"
+        query = query.strip()
+
+        if len(query) == 0:
+            return None
+
+        return query
+
+    def _fetch_mails_from_gmail(
         self,
         time_range_start: SecondsSinceUnixEpoch | None = None,
         time_range_end: SecondsSinceUnixEpoch | None = None,
     ) -> GenerateDocumentsOutput:
-        query = _build_time_range_query(time_range_start, time_range_end)
-        doc_batch = []
-        for user_email in self._get_all_user_emails():
-            gmail_service = get_gmail_service(self.creds, user_email)
-            for thread in execute_paginated_retrieval(
-                retrieval_function=gmail_service.users().threads().list,
-                list_key="threads",
-                userId=user_email,
-                fields=THREAD_LIST_FIELDS,
-                q=query,
-            ):
-                full_threads = execute_paginated_retrieval(
-                    retrieval_function=gmail_service.users().threads().get,
-                    list_key=None,
-                    userId=user_email,
-                    fields=THREAD_FIELDS,
-                    id=thread["id"],
+        if self.creds is None:
+            raise PermissionError("Not logged into Gmail")
+        page_token = ""
+        query = GmailConnector._build_time_range_query(time_range_start, time_range_end)
+        service = discovery.build("gmail", "v1", credentials=self.creds)
+        while page_token is not None:
+            result = (
+                service.users()
+                .messages()
+                .list(
+                    userId="me",
+                    pageToken=page_token,
+                    q=query,
+                    maxResults=self.batch_size,
                 )
-                # full_threads is an iterator containing a single thread
-                # so we need to convert it to a list and grab the first element
-                full_thread = list(full_threads)[0]
-                doc = thread_to_document(full_thread)
-                if doc is None:
-                    continue
+                .execute()
+            )
+            page_token = result.get("nextPageToken")
+            messages = result.get("messages", [])
+            doc_batch = []
+            for message in messages:
+                message_id = message["id"]
+                msg = (
+                    service.users()
+                    .messages()
+                    .get(userId="me", id=message_id, format="full")
+                    .execute()
+                )
+                doc = self._email_to_document(msg)
                 doc_batch.append(doc)
-                if len(doc_batch) > self.batch_size:
-                    yield doc_batch
-                    doc_batch = []
-        if doc_batch:
-            yield doc_batch
-
-    def _fetch_slim_threads(
-        self,
-        time_range_start: SecondsSinceUnixEpoch | None = None,
-        time_range_end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
-        query = _build_time_range_query(time_range_start, time_range_end)
-        doc_batch = []
-        for user_email in self._get_all_user_emails():
-            gmail_service = get_gmail_service(self.creds, user_email)
-            for thread in execute_paginated_retrieval(
-                retrieval_function=gmail_service.users().threads().list,
-                list_key="threads",
-                userId=user_email,
-                fields=THREAD_LIST_FIELDS,
-                q=query,
-            ):
-                doc_batch.append(
-                    SlimDocument(
-                        id=thread["id"],
-                        perm_sync_data={"user_email": user_email},
-                    )
-                )
-                if len(doc_batch) > SLIM_BATCH_SIZE:
-                    yield doc_batch
-                    doc_batch = []
-        if doc_batch:
-            yield doc_batch
+            if len(doc_batch) > 0:
+                yield doc_batch
 
     def load_from_state(self) -> GenerateDocumentsOutput:
-        try:
-            yield from self._fetch_threads()
-        except Exception as e:
-            if MISSING_SCOPES_ERROR_STR in str(e):
-                raise PermissionError(ONYX_SCOPE_INSTRUCTIONS) from e
-            raise e
+        yield from self._fetch_mails_from_gmail()
 
     def poll_source(
         self, start: SecondsSinceUnixEpoch, end: SecondsSinceUnixEpoch
     ) -> GenerateDocumentsOutput:
-        try:
-            yield from self._fetch_threads(start, end)
-        except Exception as e:
-            if MISSING_SCOPES_ERROR_STR in str(e):
-                raise PermissionError(ONYX_SCOPE_INSTRUCTIONS) from e
-            raise e
-
-    def retrieve_all_slim_documents(
-        self,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
-        try:
-            yield from self._fetch_slim_threads(start, end)
-        except Exception as e:
-            if MISSING_SCOPES_ERROR_STR in str(e):
-                raise PermissionError(ONYX_SCOPE_INSTRUCTIONS) from e
-            raise e
+        yield from self._fetch_mails_from_gmail(start, end)
 
 
 if __name__ == "__main__":
-    pass
+    import json
+    import os
+
+    service_account_json_path = os.environ.get("GOOGLE_SERVICE_ACCOUNT_KEY_JSON_PATH")
+    if not service_account_json_path:
+        raise ValueError(
+            "Please set GOOGLE_SERVICE_ACCOUNT_KEY_JSON_PATH environment variable"
+        )
+    with open(service_account_json_path) as f:
+        creds = json.load(f)
+
+    credentials_dict = {
+        DB_CREDENTIALS_DICT_TOKEN_KEY: json.dumps(creds),
+    }
+    delegated_user = os.environ.get("GMAIL_DELEGATED_USER")
+    if delegated_user:
+        credentials_dict[DB_CREDENTIALS_DICT_DELEGATED_USER_KEY] = delegated_user
+
+    connector = GmailConnector()
+    connector.load_credentials(
+        json.loads(credentials_dict[DB_CREDENTIALS_DICT_TOKEN_KEY])
+    )
+    document_batch_generator = connector.load_from_state()
+    for document_batch in document_batch_generator:
+        print(document_batch)
+        break

backend/danswer/connectors/gmail/connector_auth.py

@@ -0,0 +1,197 @@
+import json
+from typing import cast
+from urllib.parse import parse_qs
+from urllib.parse import ParseResult
+from urllib.parse import urlparse
+
+from google.auth.transport.requests import Request  # type: ignore
+from google.oauth2.credentials import Credentials as OAuthCredentials  # type: ignore
+from google.oauth2.service_account import Credentials as ServiceAccountCredentials  # type: ignore
+from google_auth_oauthlib.flow import InstalledAppFlow  # type: ignore
+from sqlalchemy.orm import Session
+
+from danswer.configs.app_configs import WEB_DOMAIN
+from danswer.configs.constants import DocumentSource
+from danswer.configs.constants import KV_CRED_KEY
+from danswer.configs.constants import KV_GMAIL_CRED_KEY
+from danswer.configs.constants import KV_GMAIL_SERVICE_ACCOUNT_KEY
+from danswer.connectors.gmail.constants import (
+    DB_CREDENTIALS_DICT_DELEGATED_USER_KEY,
+)
+from danswer.connectors.gmail.constants import DB_CREDENTIALS_DICT_TOKEN_KEY
+from danswer.connectors.gmail.constants import (
+    GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
+)
+from danswer.connectors.gmail.constants import SCOPES
+from danswer.db.credentials import update_credential_json
+from danswer.db.models import User
+from danswer.key_value_store.factory import get_kv_store
+from danswer.server.documents.models import CredentialBase
+from danswer.server.documents.models import GoogleAppCredentials
+from danswer.server.documents.models import GoogleServiceAccountKey
+from danswer.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+def _build_frontend_gmail_redirect() -> str:
+    return f"{WEB_DOMAIN}/admin/connectors/gmail/auth/callback"
+
+
+def get_gmail_creds_for_authorized_user(
+    token_json_str: str,
+) -> OAuthCredentials | None:
+    creds_json = json.loads(token_json_str)
+    creds = OAuthCredentials.from_authorized_user_info(creds_json, SCOPES)
+    if creds.valid:
+        return creds
+
+    if creds.expired and creds.refresh_token:
+        try:
+            creds.refresh(Request())
+            if creds.valid:
+                logger.notice("Refreshed Gmail tokens.")
+                return creds
+        except Exception as e:
+            logger.exception(f"Failed to refresh gmail access token due to: {e}")
+            return None
+
+    return None
+
+
+def get_gmail_creds_for_service_account(
+    service_account_key_json_str: str,
+) -> ServiceAccountCredentials | None:
+    service_account_key = json.loads(service_account_key_json_str)
+    creds = ServiceAccountCredentials.from_service_account_info(
+        service_account_key, scopes=SCOPES
+    )
+    if not creds.valid or not creds.expired:
+        creds.refresh(Request())
+    return creds if creds.valid else None
+
+
+def verify_csrf(credential_id: int, state: str) -> None:
+    csrf = get_kv_store().load(KV_CRED_KEY.format(str(credential_id)))
+    if csrf != state:
+        raise PermissionError(
+            "State from Gmail Connector callback does not match expected"
+        )
+
+
+def get_gmail_auth_url(credential_id: int) -> str:
+    creds_str = str(get_kv_store().load(KV_GMAIL_CRED_KEY))
+    credential_json = json.loads(creds_str)
+    flow = InstalledAppFlow.from_client_config(
+        credential_json,
+        scopes=SCOPES,
+        redirect_uri=_build_frontend_gmail_redirect(),
+    )
+    auth_url, _ = flow.authorization_url(prompt="consent")
+
+    parsed_url = cast(ParseResult, urlparse(auth_url))
+    params = parse_qs(parsed_url.query)
+
+    get_kv_store().store(
+        KV_CRED_KEY.format(credential_id), params.get("state", [None])[0], encrypt=True
+    )  # type: ignore
+    return str(auth_url)
+
+
+def get_auth_url(credential_id: int) -> str:
+    creds_str = str(get_kv_store().load(KV_GMAIL_CRED_KEY))
+    credential_json = json.loads(creds_str)
+    flow = InstalledAppFlow.from_client_config(
+        credential_json,
+        scopes=SCOPES,
+        redirect_uri=_build_frontend_gmail_redirect(),
+    )
+    auth_url, _ = flow.authorization_url(prompt="consent")
+
+    parsed_url = cast(ParseResult, urlparse(auth_url))
+    params = parse_qs(parsed_url.query)
+
+    get_kv_store().store(
+        KV_CRED_KEY.format(credential_id), params.get("state", [None])[0], encrypt=True
+    )  # type: ignore
+    return str(auth_url)
+
+
+def update_gmail_credential_access_tokens(
+    auth_code: str,
+    credential_id: int,
+    user: User,
+    db_session: Session,
+) -> OAuthCredentials | None:
+    app_credentials = get_google_app_gmail_cred()
+    flow = InstalledAppFlow.from_client_config(
+        app_credentials.model_dump(),
+        scopes=SCOPES,
+        redirect_uri=_build_frontend_gmail_redirect(),
+    )
+    flow.fetch_token(code=auth_code)
+    creds = flow.credentials
+    token_json_str = creds.to_json()
+    new_creds_dict = {DB_CREDENTIALS_DICT_TOKEN_KEY: token_json_str}
+
+    if not update_credential_json(credential_id, new_creds_dict, user, db_session):
+        return None
+    return creds
+
+
+def build_service_account_creds(
+    delegated_user_email: str | None = None,
+) -> CredentialBase:
+    service_account_key = get_gmail_service_account_key()
+
+    credential_dict = {
+        GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY: service_account_key.json(),
+    }
+    if delegated_user_email:
+        credential_dict[DB_CREDENTIALS_DICT_DELEGATED_USER_KEY] = delegated_user_email
+
+    return CredentialBase(
+        source=DocumentSource.GMAIL,
+        credential_json=credential_dict,
+        admin_public=True,
+    )
+
+
+def get_google_app_gmail_cred() -> GoogleAppCredentials:
+    creds_str = str(get_kv_store().load(KV_GMAIL_CRED_KEY))
+    return GoogleAppCredentials(**json.loads(creds_str))
+
+
+def upsert_google_app_gmail_cred(app_credentials: GoogleAppCredentials) -> None:
+    get_kv_store().store(KV_GMAIL_CRED_KEY, app_credentials.json(), encrypt=True)
+
+
+def delete_google_app_gmail_cred() -> None:
+    get_kv_store().delete(KV_GMAIL_CRED_KEY)
+
+
+def get_gmail_service_account_key() -> GoogleServiceAccountKey:
+    creds_str = str(get_kv_store().load(KV_GMAIL_SERVICE_ACCOUNT_KEY))
+    return GoogleServiceAccountKey(**json.loads(creds_str))
+
+
+def upsert_gmail_service_account_key(
+    service_account_key: GoogleServiceAccountKey,
+) -> None:
+    get_kv_store().store(
+        KV_GMAIL_SERVICE_ACCOUNT_KEY, service_account_key.json(), encrypt=True
+    )
+
+
+def upsert_service_account_key(service_account_key: GoogleServiceAccountKey) -> None:
+    get_kv_store().store(
+        KV_GMAIL_SERVICE_ACCOUNT_KEY, service_account_key.json(), encrypt=True
+    )
+
+
+def delete_gmail_service_account_key() -> None:
+    get_kv_store().delete(KV_GMAIL_SERVICE_ACCOUNT_KEY)
+
+
+def delete_service_account_key() -> None:
+    get_kv_store().delete(KV_GMAIL_SERVICE_ACCOUNT_KEY)

backend/danswer/connectors/gmail/constants.py

@@ -0,0 +1,4 @@
+DB_CREDENTIALS_DICT_TOKEN_KEY = "gmail_tokens"
+GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY = "gmail_service_account_key"
+DB_CREDENTIALS_DICT_DELEGATED_USER_KEY = "gmail_delegated_user"
+SCOPES = ["https://www.googleapis.com/auth/gmail.readonly"]

backend/danswer/connectors/google_drive/connector.py

@@ -1,400 +1,556 @@
-from collections.abc import Callable
+import io
 from collections.abc import Iterator
-from concurrent.futures import as_completed
-from concurrent.futures import ThreadPoolExecutor
-from functools import partial
+from collections.abc import Sequence
+from datetime import datetime
+from datetime import timezone
+from enum import Enum
+from itertools import chain
 from typing import Any
 
 from google.oauth2.credentials import Credentials as OAuthCredentials  # type: ignore
 from google.oauth2.service_account import Credentials as ServiceAccountCredentials  # type: ignore
+from googleapiclient import discovery  # type: ignore
+from googleapiclient.errors import HttpError  # type: ignore
 
+from danswer.configs.app_configs import CONTINUE_ON_CONNECTOR_FAILURE
+from danswer.configs.app_configs import GOOGLE_DRIVE_FOLLOW_SHORTCUTS
+from danswer.configs.app_configs import GOOGLE_DRIVE_INCLUDE_SHARED
+from danswer.configs.app_configs import GOOGLE_DRIVE_ONLY_ORG_PUBLIC
 from danswer.configs.app_configs import INDEX_BATCH_SIZE
 from danswer.configs.constants import DocumentSource
-from danswer.connectors.google_drive.doc_conversion import build_slim_document
-from danswer.connectors.google_drive.doc_conversion import (
-    convert_drive_item_to_document,
+from danswer.configs.constants import IGNORE_FOR_QA
+from danswer.connectors.google_drive.connector_auth import get_google_drive_creds
+from danswer.connectors.google_drive.constants import (
+    DB_CREDENTIALS_DICT_DELEGATED_USER_KEY,
 )
-from danswer.connectors.google_drive.file_retrieval import crawl_folders_for_files
-from danswer.connectors.google_drive.file_retrieval import get_all_files_in_my_drive
-from danswer.connectors.google_drive.file_retrieval import get_files_in_shared_drive
-from danswer.connectors.google_drive.models import GoogleDriveFileType
-from danswer.connectors.google_utils.google_auth import get_google_creds
-from danswer.connectors.google_utils.google_utils import execute_paginated_retrieval
-from danswer.connectors.google_utils.resources import get_admin_service
-from danswer.connectors.google_utils.resources import get_drive_service
-from danswer.connectors.google_utils.resources import get_google_docs_service
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_PRIMARY_ADMIN_KEY,
+from danswer.connectors.google_drive.constants import (
+    DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
 )
-from danswer.connectors.google_utils.shared_constants import MISSING_SCOPES_ERROR_STR
-from danswer.connectors.google_utils.shared_constants import ONYX_SCOPE_INSTRUCTIONS
-from danswer.connectors.google_utils.shared_constants import SCOPE_DOC_URL
-from danswer.connectors.google_utils.shared_constants import SLIM_BATCH_SIZE
-from danswer.connectors.google_utils.shared_constants import USER_FIELDS
 from danswer.connectors.interfaces import GenerateDocumentsOutput
-from danswer.connectors.interfaces import GenerateSlimDocumentOutput
 from danswer.connectors.interfaces import LoadConnector
 from danswer.connectors.interfaces import PollConnector
 from danswer.connectors.interfaces import SecondsSinceUnixEpoch
-from danswer.connectors.interfaces import SlimConnector
+from danswer.connectors.models import Document
+from danswer.connectors.models import Section
+from danswer.file_processing.extract_file_text import docx_to_text
+from danswer.file_processing.extract_file_text import pptx_to_text
+from danswer.file_processing.extract_file_text import read_pdf_file
+from danswer.file_processing.unstructured import get_unstructured_api_key
+from danswer.file_processing.unstructured import unstructured_to_text
+from danswer.utils.batching import batch_generator
 from danswer.utils.logger import setup_logger
+from danswer.utils.retry_wrapper import retry_builder
 
 logger = setup_logger()
-# TODO: Improve this by using the batch utility: https://googleapis.github.io/google-api-python-client/docs/batch.html
-# All file retrievals could be batched and made at once
+
+DRIVE_FOLDER_TYPE = "application/vnd.google-apps.folder"
+DRIVE_SHORTCUT_TYPE = "application/vnd.google-apps.shortcut"
+UNSUPPORTED_FILE_TYPE_CONTENT = ""  # keep empty for now
 
 
-def _extract_str_list_from_comma_str(string: str | None) -> list[str]:
-    if not string:
-        return []
-    return [s.strip() for s in string.split(",") if s.strip()]
+class GDriveMimeType(str, Enum):
+    DOC = "application/vnd.google-apps.document"
+    SPREADSHEET = "application/vnd.google-apps.spreadsheet"
+    PDF = "application/pdf"
+    WORD_DOC = "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+    PPT = "application/vnd.google-apps.presentation"
+    POWERPOINT = (
+        "application/vnd.openxmlformats-officedocument.presentationml.presentation"
+    )
+    PLAIN_TEXT = "text/plain"
+    MARKDOWN = "text/markdown"
 
 
-def _extract_ids_from_urls(urls: list[str]) -> list[str]:
-    return [url.split("/")[-1] for url in urls]
+GoogleDriveFileType = dict[str, Any]
+
+# Google Drive APIs are quite flakey and may 500 for an
+# extended period of time. Trying to combat here by adding a very
+# long retry period (~20 minutes of trying every minute)
+add_retries = retry_builder(tries=50, max_delay=30)
 
 
-def _convert_single_file(
-    creds: Any, primary_admin_email: str, file: dict[str, Any]
-) -> Any:
-    user_email = file.get("owners", [{}])[0].get("emailAddress") or primary_admin_email
-    user_drive_service = get_drive_service(creds, user_email=user_email)
-    docs_service = get_google_docs_service(creds, user_email=user_email)
-    return convert_drive_item_to_document(
-        file=file,
-        drive_service=user_drive_service,
-        docs_service=docs_service,
+def _run_drive_file_query(
+    service: discovery.Resource,
+    query: str,
+    continue_on_failure: bool,
+    include_shared: bool = GOOGLE_DRIVE_INCLUDE_SHARED,
+    follow_shortcuts: bool = GOOGLE_DRIVE_FOLLOW_SHORTCUTS,
+    batch_size: int = INDEX_BATCH_SIZE,
+) -> Iterator[GoogleDriveFileType]:
+    next_page_token = ""
+    while next_page_token is not None:
+        logger.debug(f"Running Google Drive fetch with query: {query}")
+        results = add_retries(
+            lambda: (
+                service.files()
+                .list(
+                    corpora="allDrives"
+                    if include_shared
+                    else "user",  # needed to search through shared drives
+                    pageSize=batch_size,
+                    supportsAllDrives=include_shared,
+                    includeItemsFromAllDrives=include_shared,
+                    fields=(
+                        "nextPageToken, files(mimeType, id, name, permissions, "
+                        "modifiedTime, webViewLink, shortcutDetails)"
+                    ),
+                    pageToken=next_page_token,
+                    q=query,
+                )
+                .execute()
+            )
+        )()
+        next_page_token = results.get("nextPageToken")
+        files = results["files"]
+        for file in files:
+            if follow_shortcuts and "shortcutDetails" in file:
+                try:
+                    file_shortcut_points_to = add_retries(
+                        lambda: (
+                            service.files()
+                            .get(
+                                fileId=file["shortcutDetails"]["targetId"],
+                                supportsAllDrives=include_shared,
+                                fields="mimeType, id, name, modifiedTime, webViewLink, permissions, shortcutDetails",
+                            )
+                            .execute()
+                        )
+                    )()
+                    yield file_shortcut_points_to
+                except HttpError:
+                    logger.error(
+                        f"Failed to follow shortcut with details: {file['shortcutDetails']}"
+                    )
+                    if continue_on_failure:
+                        continue
+                    raise
+            else:
+                yield file
+
+
+def _get_folder_id(
+    service: discovery.Resource,
+    parent_id: str,
+    folder_name: str,
+    include_shared: bool,
+    follow_shortcuts: bool,
+) -> str | None:
+    """
+    Get the ID of a folder given its name and the ID of its parent folder.
+    """
+    query = f"'{parent_id}' in parents and name='{folder_name}' and "
+    if follow_shortcuts:
+        query += f"(mimeType='{DRIVE_FOLDER_TYPE}' or mimeType='{DRIVE_SHORTCUT_TYPE}')"
+    else:
+        query += f"mimeType='{DRIVE_FOLDER_TYPE}'"
+
+    # TODO: support specifying folder path in shared drive rather than just `My Drive`
+    results = add_retries(
+        lambda: (
+            service.files()
+            .list(
+                q=query,
+                spaces="drive",
+                fields="nextPageToken, files(id, name, shortcutDetails)",
+                supportsAllDrives=include_shared,
+                includeItemsFromAllDrives=include_shared,
+            )
+            .execute()
+        )
+    )()
+    items = results.get("files", [])
+
+    folder_id = None
+    if items:
+        if follow_shortcuts and "shortcutDetails" in items[0]:
+            folder_id = items[0]["shortcutDetails"]["targetId"]
+        else:
+            folder_id = items[0]["id"]
+    return folder_id
+
+
+def _get_folders(
+    service: discovery.Resource,
+    continue_on_failure: bool,
+    folder_id: str | None = None,  # if specified, only fetches files within this folder
+    include_shared: bool = GOOGLE_DRIVE_INCLUDE_SHARED,
+    follow_shortcuts: bool = GOOGLE_DRIVE_FOLLOW_SHORTCUTS,
+    batch_size: int = INDEX_BATCH_SIZE,
+) -> Iterator[GoogleDriveFileType]:
+    query = f"mimeType = '{DRIVE_FOLDER_TYPE}' "
+    if follow_shortcuts:
+        query = "(" + query + f" or mimeType = '{DRIVE_SHORTCUT_TYPE}'" + ") "
+
+    if folder_id:
+        query += f"and '{folder_id}' in parents "
+    query = query.rstrip()  # remove the trailing space(s)
+
+    for file in _run_drive_file_query(
+        service=service,
+        query=query,
+        continue_on_failure=continue_on_failure,
+        include_shared=include_shared,
+        follow_shortcuts=follow_shortcuts,
+        batch_size=batch_size,
+    ):
+        # Need to check this since file may have been a target of a shortcut
+        # and not necessarily a folder
+        if file["mimeType"] == DRIVE_FOLDER_TYPE:
+            yield file
+        else:
+            pass
+
+
+def _get_files(
+    service: discovery.Resource,
+    continue_on_failure: bool,
+    time_range_start: SecondsSinceUnixEpoch | None = None,
+    time_range_end: SecondsSinceUnixEpoch | None = None,
+    folder_id: str | None = None,  # if specified, only fetches files within this folder
+    include_shared: bool = GOOGLE_DRIVE_INCLUDE_SHARED,
+    follow_shortcuts: bool = GOOGLE_DRIVE_FOLLOW_SHORTCUTS,
+    batch_size: int = INDEX_BATCH_SIZE,
+) -> Iterator[GoogleDriveFileType]:
+    query = f"mimeType != '{DRIVE_FOLDER_TYPE}' "
+    if time_range_start is not None:
+        time_start = datetime.utcfromtimestamp(time_range_start).isoformat() + "Z"
+        query += f"and modifiedTime >= '{time_start}' "
+    if time_range_end is not None:
+        time_stop = datetime.utcfromtimestamp(time_range_end).isoformat() + "Z"
+        query += f"and modifiedTime <= '{time_stop}' "
+    if folder_id:
+        query += f"and '{folder_id}' in parents "
+    query = query.rstrip()  # remove the trailing space(s)
+
+    files = _run_drive_file_query(
+        service=service,
+        query=query,
+        continue_on_failure=continue_on_failure,
+        include_shared=include_shared,
+        follow_shortcuts=follow_shortcuts,
+        batch_size=batch_size,
     )
 
-
-def _process_files_batch(
-    files: list[GoogleDriveFileType], convert_func: Callable, batch_size: int
-) -> GenerateDocumentsOutput:
-    doc_batch = []
-    with ThreadPoolExecutor(max_workers=min(16, len(files))) as executor:
-        for doc in executor.map(convert_func, files):
-            if doc:
-                doc_batch.append(doc)
-                if len(doc_batch) >= batch_size:
-                    yield doc_batch
-                    doc_batch = []
-    if doc_batch:
-        yield doc_batch
+    return files
 
 
-class GoogleDriveConnector(LoadConnector, PollConnector, SlimConnector):
+def get_all_files_batched(
+    service: discovery.Resource,
+    continue_on_failure: bool,
+    include_shared: bool = GOOGLE_DRIVE_INCLUDE_SHARED,
+    follow_shortcuts: bool = GOOGLE_DRIVE_FOLLOW_SHORTCUTS,
+    batch_size: int = INDEX_BATCH_SIZE,
+    time_range_start: SecondsSinceUnixEpoch | None = None,
+    time_range_end: SecondsSinceUnixEpoch | None = None,
+    folder_id: str | None = None,  # if specified, only fetches files within this folder
+    # if True, will fetch files in sub-folders of the specified folder ID.
+    # Only applies if folder_id is specified.
+    traverse_subfolders: bool = True,
+    folder_ids_traversed: list[str] | None = None,
+) -> Iterator[list[GoogleDriveFileType]]:
+    """Gets all files matching the criteria specified by the args from Google Drive
+    in batches of size `batch_size`.
+    """
+    found_files = _get_files(
+        service=service,
+        continue_on_failure=continue_on_failure,
+        time_range_start=time_range_start,
+        time_range_end=time_range_end,
+        folder_id=folder_id,
+        include_shared=include_shared,
+        follow_shortcuts=follow_shortcuts,
+        batch_size=batch_size,
+    )
+    yield from batch_generator(
+        items=found_files,
+        batch_size=batch_size,
+        pre_batch_yield=lambda batch_files: logger.debug(
+            f"Parseable Documents in batch: {[file['name'] for file in batch_files]}"
+        ),
+    )
+
+    if traverse_subfolders and folder_id is not None:
+        folder_ids_traversed = folder_ids_traversed or []
+        subfolders = _get_folders(
+            service=service,
+            folder_id=folder_id,
+            continue_on_failure=continue_on_failure,
+            include_shared=include_shared,
+            follow_shortcuts=follow_shortcuts,
+            batch_size=batch_size,
+        )
+        for subfolder in subfolders:
+            if subfolder["id"] not in folder_ids_traversed:
+                logger.info("Fetching all files in subfolder: " + subfolder["name"])
+                folder_ids_traversed.append(subfolder["id"])
+                yield from get_all_files_batched(
+                    service=service,
+                    continue_on_failure=continue_on_failure,
+                    include_shared=include_shared,
+                    follow_shortcuts=follow_shortcuts,
+                    batch_size=batch_size,
+                    time_range_start=time_range_start,
+                    time_range_end=time_range_end,
+                    folder_id=subfolder["id"],
+                    traverse_subfolders=traverse_subfolders,
+                    folder_ids_traversed=folder_ids_traversed,
+                )
+            else:
+                logger.debug(
+                    "Skipping subfolder since already traversed: " + subfolder["name"]
+                )
+
+
+def extract_text(file: dict[str, str], service: discovery.Resource) -> str:
+    mime_type = file["mimeType"]
+
+    if mime_type not in set(item.value for item in GDriveMimeType):
+        # Unsupported file types can still have a title, finding this way is still useful
+        return UNSUPPORTED_FILE_TYPE_CONTENT
+
+    if mime_type in [
+        GDriveMimeType.DOC.value,
+        GDriveMimeType.PPT.value,
+        GDriveMimeType.SPREADSHEET.value,
+    ]:
+        export_mime_type = (
+            "text/plain"
+            if mime_type != GDriveMimeType.SPREADSHEET.value
+            else "text/csv"
+        )
+        return (
+            service.files()
+            .export(fileId=file["id"], mimeType=export_mime_type)
+            .execute()
+            .decode("utf-8")
+        )
+    elif mime_type in [
+        GDriveMimeType.PLAIN_TEXT.value,
+        GDriveMimeType.MARKDOWN.value,
+    ]:
+        return service.files().get_media(fileId=file["id"]).execute().decode("utf-8")
+    if mime_type in [
+        GDriveMimeType.WORD_DOC.value,
+        GDriveMimeType.POWERPOINT.value,
+        GDriveMimeType.PDF.value,
+    ]:
+        response = service.files().get_media(fileId=file["id"]).execute()
+        if get_unstructured_api_key():
+            return unstructured_to_text(
+                file=io.BytesIO(response), file_name=file.get("name", file["id"])
+            )
+
+        if mime_type == GDriveMimeType.WORD_DOC.value:
+            return docx_to_text(file=io.BytesIO(response))
+        elif mime_type == GDriveMimeType.PDF.value:
+            text, _ = read_pdf_file(file=io.BytesIO(response))
+            return text
+        elif mime_type == GDriveMimeType.POWERPOINT.value:
+            return pptx_to_text(file=io.BytesIO(response))
+
+    return UNSUPPORTED_FILE_TYPE_CONTENT
+
+
+class GoogleDriveConnector(LoadConnector, PollConnector):
     def __init__(
         self,
-        include_shared_drives: bool = True,
-        shared_drive_urls: str | None = None,
-        include_my_drives: bool = True,
-        my_drive_emails: str | None = None,
-        shared_folder_urls: str | None = None,
-        batch_size: int = INDEX_BATCH_SIZE,
-        # OLD PARAMETERS
+        # optional list of folder paths e.g. "[My Folder/My Subfolder]"
+        # if specified, will only index files in these folders
         folder_paths: list[str] | None = None,
-        include_shared: bool | None = None,
-        follow_shortcuts: bool | None = None,
-        only_org_public: bool | None = None,
-        continue_on_failure: bool | None = None,
+        batch_size: int = INDEX_BATCH_SIZE,
+        include_shared: bool = GOOGLE_DRIVE_INCLUDE_SHARED,
+        follow_shortcuts: bool = GOOGLE_DRIVE_FOLLOW_SHORTCUTS,
+        only_org_public: bool = GOOGLE_DRIVE_ONLY_ORG_PUBLIC,
+        continue_on_failure: bool = CONTINUE_ON_CONNECTOR_FAILURE,
     ) -> None:
-        # Check for old input parameters
-        if (
-            folder_paths is not None
-            or include_shared is not None
-            or follow_shortcuts is not None
-            or only_org_public is not None
-            or continue_on_failure is not None
-        ):
-            logger.exception(
-                "Google Drive connector received old input parameters. "
-                "Please visit the docs for help with the new setup: "
-                f"{SCOPE_DOC_URL}"
-            )
-            raise ValueError(
-                "Google Drive connector received old input parameters. "
-                "Please visit the docs for help with the new setup: "
-                f"{SCOPE_DOC_URL}"
-            )
-
-        if (
-            not include_shared_drives
-            and not include_my_drives
-            and not shared_folder_urls
-        ):
-            raise ValueError(
-                "At least one of include_shared_drives, include_my_drives,"
-                " or shared_folder_urls must be true"
-            )
-
+        self.folder_paths = folder_paths or []
         self.batch_size = batch_size
+        self.include_shared = include_shared
+        self.follow_shortcuts = follow_shortcuts
+        self.only_org_public = only_org_public
+        self.continue_on_failure = continue_on_failure
+        self.creds: OAuthCredentials | ServiceAccountCredentials | None = None
 
-        self.include_shared_drives = include_shared_drives
-        shared_drive_url_list = _extract_str_list_from_comma_str(shared_drive_urls)
-        self._requested_shared_drive_ids = set(
-            _extract_ids_from_urls(shared_drive_url_list)
-        )
+    @staticmethod
+    def _process_folder_paths(
+        service: discovery.Resource,
+        folder_paths: list[str],
+        include_shared: bool,
+        follow_shortcuts: bool,
+    ) -> list[str]:
+        """['Folder/Sub Folder'] -> ['<FOLDER_ID>']"""
+        folder_ids: list[str] = []
+        for path in folder_paths:
+            folder_names = path.split("/")
+            parent_id = "root"
+            for folder_name in folder_names:
+                found_parent_id = _get_folder_id(
+                    service=service,
+                    parent_id=parent_id,
+                    folder_name=folder_name,
+                    include_shared=include_shared,
+                    follow_shortcuts=follow_shortcuts,
+                )
+                if found_parent_id is None:
+                    raise ValueError(
+                        (
+                            f"Folder '{folder_name}' in path '{path}' "
+                            "not found in Google Drive"
+                        )
+                    )
+                parent_id = found_parent_id
+            folder_ids.append(parent_id)
 
-        self.include_my_drives = include_my_drives
-        self._requested_my_drive_emails = set(
-            _extract_str_list_from_comma_str(my_drive_emails)
-        )
-
-        shared_folder_url_list = _extract_str_list_from_comma_str(shared_folder_urls)
-        self._requested_folder_ids = set(_extract_ids_from_urls(shared_folder_url_list))
-
-        self._primary_admin_email: str | None = None
-
-        self._creds: OAuthCredentials | ServiceAccountCredentials | None = None
-
-        self._retrieved_ids: set[str] = set()
-
-    @property
-    def primary_admin_email(self) -> str:
-        if self._primary_admin_email is None:
-            raise RuntimeError(
-                "Primary admin email missing, "
-                "should not call this property "
-                "before calling load_credentials"
-            )
-        return self._primary_admin_email
-
-    @property
-    def google_domain(self) -> str:
-        if self._primary_admin_email is None:
-            raise RuntimeError(
-                "Primary admin email missing, "
-                "should not call this property "
-                "before calling load_credentials"
-            )
-        return self._primary_admin_email.split("@")[-1]
-
-    @property
-    def creds(self) -> OAuthCredentials | ServiceAccountCredentials:
-        if self._creds is None:
-            raise RuntimeError(
-                "Creds missing, "
-                "should not call this property "
-                "before calling load_credentials"
-            )
-        return self._creds
+        return folder_ids
 
     def load_credentials(self, credentials: dict[str, Any]) -> dict[str, str] | None:
-        primary_admin_email = credentials[DB_CREDENTIALS_PRIMARY_ADMIN_KEY]
-        self._primary_admin_email = primary_admin_email
-
-        self._creds, new_creds_dict = get_google_creds(
-            credentials=credentials,
-            source=DocumentSource.GOOGLE_DRIVE,
-        )
+        """Checks for two different types of credentials.
+        (1) A credential which holds a token acquired via a user going thorough
+        the Google OAuth flow.
+        (2) A credential which holds a service account key JSON file, which
+        can then be used to impersonate any user in the workspace.
+        """
+        creds, new_creds_dict = get_google_drive_creds(credentials)
+        self.creds = creds
         return new_creds_dict
 
-    def _update_traversed_parent_ids(self, folder_id: str) -> None:
-        self._retrieved_ids.add(folder_id)
-
-    def _get_all_user_emails(self, admins_only: bool) -> list[str]:
-        admin_service = get_admin_service(
-            creds=self.creds,
-            user_email=self.primary_admin_email,
-        )
-        query = "isAdmin=true" if admins_only else "isAdmin=false"
-        emails = []
-        for user in execute_paginated_retrieval(
-            retrieval_function=admin_service.users().list,
-            list_key="users",
-            fields=USER_FIELDS,
-            domain=self.google_domain,
-            query=query,
-        ):
-            if email := user.get("primaryEmail"):
-                emails.append(email)
-        return emails
-
-    def _get_all_drive_ids(self) -> set[str]:
-        primary_drive_service = get_drive_service(
-            creds=self.creds,
-            user_email=self.primary_admin_email,
-        )
-        all_drive_ids = set()
-        for drive in execute_paginated_retrieval(
-            retrieval_function=primary_drive_service.drives().list,
-            list_key="drives",
-            useDomainAdminAccess=True,
-            fields="drives(id)",
-        ):
-            all_drive_ids.add(drive["id"])
-        return all_drive_ids
-
-    def _initialize_all_class_variables(self) -> None:
-        # Get all user emails
-        # Get admins first becuase they are more likely to have access to the most files
-        user_emails = [self.primary_admin_email]
-        for admins_only in [True, False]:
-            for email in self._get_all_user_emails(admins_only=admins_only):
-                if email not in user_emails:
-                    user_emails.append(email)
-        self._all_org_emails = user_emails
-
-        self._all_drive_ids: set[str] = self._get_all_drive_ids()
-
-        # remove drive ids from the folder ids because they are queried differently
-        self._requested_folder_ids -= self._all_drive_ids
-
-        # Remove drive_ids that are not in the all_drive_ids and check them as folders instead
-        invalid_drive_ids = self._requested_shared_drive_ids - self._all_drive_ids
-        if invalid_drive_ids:
-            logger.warning(
-                f"Some shared drive IDs were not found. IDs: {invalid_drive_ids}"
-            )
-            logger.warning("Checking for folder access instead...")
-            self._requested_folder_ids.update(invalid_drive_ids)
-
-        if not self.include_shared_drives:
-            self._requested_shared_drive_ids = set()
-        elif not self._requested_shared_drive_ids:
-            self._requested_shared_drive_ids = self._all_drive_ids
-
-    def _impersonate_user_for_retrieval(
-        self,
-        user_email: str,
-        is_slim: bool,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> Iterator[GoogleDriveFileType]:
-        drive_service = get_drive_service(self.creds, user_email)
-        if self.include_my_drives and (
-            not self._requested_my_drive_emails
-            or user_email in self._requested_my_drive_emails
-        ):
-            yield from get_all_files_in_my_drive(
-                service=drive_service,
-                update_traversed_ids_func=self._update_traversed_parent_ids,
-                is_slim=is_slim,
-                start=start,
-                end=end,
-            )
-
-        remaining_drive_ids = self._requested_shared_drive_ids - self._retrieved_ids
-        for drive_id in remaining_drive_ids:
-            yield from get_files_in_shared_drive(
-                service=drive_service,
-                drive_id=drive_id,
-                is_slim=is_slim,
-                update_traversed_ids_func=self._update_traversed_parent_ids,
-                start=start,
-                end=end,
-            )
-
-        remaining_folders = self._requested_folder_ids - self._retrieved_ids
-        for folder_id in remaining_folders:
-            yield from crawl_folders_for_files(
-                service=drive_service,
-                parent_id=folder_id,
-                traversed_parent_ids=self._retrieved_ids,
-                update_traversed_ids_func=self._update_traversed_parent_ids,
-                start=start,
-                end=end,
-            )
-
-    def _fetch_drive_items(
-        self,
-        is_slim: bool,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> Iterator[GoogleDriveFileType]:
-        self._initialize_all_class_variables()
-
-        # Process users in parallel using ThreadPoolExecutor
-        with ThreadPoolExecutor(max_workers=10) as executor:
-            future_to_email = {
-                executor.submit(
-                    self._impersonate_user_for_retrieval, email, is_slim, start, end
-                ): email
-                for email in self._all_org_emails
-            }
-
-            # Yield results as they complete
-            for future in as_completed(future_to_email):
-                yield from future.result()
-
-        remaining_folders = self._requested_folder_ids - self._retrieved_ids
-        if remaining_folders:
-            logger.warning(
-                f"Some folders/drives were not retrieved. IDs: {remaining_folders}"
-            )
-
-    def _extract_docs_from_google_drive(
+    def _fetch_docs_from_drive(
         self,
         start: SecondsSinceUnixEpoch | None = None,
         end: SecondsSinceUnixEpoch | None = None,
     ) -> GenerateDocumentsOutput:
-        # Create a larger process pool for file conversion
-        convert_func = partial(
-            _convert_single_file, self.creds, self.primary_admin_email
+        if self.creds is None:
+            raise PermissionError("Not logged into Google Drive")
+
+        service = discovery.build("drive", "v3", credentials=self.creds)
+        folder_ids: Sequence[str | None] = self._process_folder_paths(
+            service, self.folder_paths, self.include_shared, self.follow_shortcuts
         )
+        if not folder_ids:
+            folder_ids = [None]
 
-        # Process files in larger batches
-        LARGE_BATCH_SIZE = self.batch_size * 4
-        files_to_process = []
-        # Gather the files into batches to be processed in parallel
-        for file in self._fetch_drive_items(is_slim=False, start=start, end=end):
-            files_to_process.append(file)
-            if len(files_to_process) >= LARGE_BATCH_SIZE:
-                yield from _process_files_batch(
-                    files_to_process, convert_func, self.batch_size
+        file_batches = chain(
+            *[
+                get_all_files_batched(
+                    service=service,
+                    continue_on_failure=self.continue_on_failure,
+                    include_shared=self.include_shared,
+                    follow_shortcuts=self.follow_shortcuts,
+                    batch_size=self.batch_size,
+                    time_range_start=start,
+                    time_range_end=end,
+                    folder_id=folder_id,
+                    traverse_subfolders=True,
                 )
-                files_to_process = []
+                for folder_id in folder_ids
+            ]
+        )
+        for files_batch in file_batches:
+            doc_batch = []
+            for file in files_batch:
+                try:
+                    # Skip files that are shortcuts
+                    if file.get("mimeType") == DRIVE_SHORTCUT_TYPE:
+                        logger.info("Ignoring Drive Shortcut Filetype")
+                        continue
 
-        # Process any remaining files
-        if files_to_process:
-            yield from _process_files_batch(
-                files_to_process, convert_func, self.batch_size
-            )
+                    if self.only_org_public:
+                        if "permissions" not in file:
+                            continue
+                        if not any(
+                            permission["type"] == "domain"
+                            for permission in file["permissions"]
+                        ):
+                            continue
+                    try:
+                        text_contents = extract_text(file, service) or ""
+                    except HttpError as e:
+                        reason = (
+                            e.error_details[0]["reason"]
+                            if e.error_details
+                            else e.reason
+                        )
+                        message = (
+                            e.error_details[0]["message"]
+                            if e.error_details
+                            else e.reason
+                        )
+
+                        # these errors don't represent a failure in the connector, but simply files
+                        # that can't / shouldn't be indexed
+                        ERRORS_TO_CONTINUE_ON = [
+                            "cannotExportFile",
+                            "exportSizeLimitExceeded",
+                            "cannotDownloadFile",
+                        ]
+                        if e.status_code == 403 and reason in ERRORS_TO_CONTINUE_ON:
+                            logger.warning(
+                                f"Could not export file '{file['name']}' due to '{message}', skipping..."
+                            )
+                            continue
+
+                        raise
+
+                    doc_batch.append(
+                        Document(
+                            id=file["webViewLink"],
+                            sections=[
+                                Section(link=file["webViewLink"], text=text_contents)
+                            ],
+                            source=DocumentSource.GOOGLE_DRIVE,
+                            semantic_identifier=file["name"],
+                            doc_updated_at=datetime.fromisoformat(
+                                file["modifiedTime"]
+                            ).astimezone(timezone.utc),
+                            metadata={} if text_contents else {IGNORE_FOR_QA: "True"},
+                            additional_info=file.get("id"),
+                        )
+                    )
+                except Exception as e:
+                    if not self.continue_on_failure:
+                        raise e
+
+                    logger.exception(
+                        "Ran into exception when pulling a file from Google Drive"
+                    )
+
+            yield doc_batch
 
     def load_from_state(self) -> GenerateDocumentsOutput:
-        try:
-            yield from self._extract_docs_from_google_drive()
-        except Exception as e:
-            if MISSING_SCOPES_ERROR_STR in str(e):
-                raise PermissionError(ONYX_SCOPE_INSTRUCTIONS) from e
-            raise e
+        yield from self._fetch_docs_from_drive()
 
     def poll_source(
         self, start: SecondsSinceUnixEpoch, end: SecondsSinceUnixEpoch
     ) -> GenerateDocumentsOutput:
-        try:
-            yield from self._extract_docs_from_google_drive(start, end)
-        except Exception as e:
-            if MISSING_SCOPES_ERROR_STR in str(e):
-                raise PermissionError(ONYX_SCOPE_INSTRUCTIONS) from e
-            raise e
+        # need to subtract 10 minutes from start time to account for modifiedTime
+        # propogation if a document is modified, it takes some time for the API to
+        # reflect these changes if we do not have an offset, then we may "miss" the
+        # update when polling
+        yield from self._fetch_docs_from_drive(start, end)
 
-    def _extract_slim_docs_from_google_drive(
-        self,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
-        slim_batch = []
-        for file in self._fetch_drive_items(
-            is_slim=True,
-            start=start,
-            end=end,
-        ):
-            if doc := build_slim_document(file):
-                slim_batch.append(doc)
-            if len(slim_batch) >= SLIM_BATCH_SIZE:
-                yield slim_batch
-                slim_batch = []
-        yield slim_batch
 
-    def retrieve_all_slim_documents(
-        self,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
-        try:
-            yield from self._extract_slim_docs_from_google_drive(start, end)
-        except Exception as e:
-            if MISSING_SCOPES_ERROR_STR in str(e):
-                raise PermissionError(ONYX_SCOPE_INSTRUCTIONS) from e
-            raise e
+if __name__ == "__main__":
+    import json
+    import os
+
+    service_account_json_path = os.environ.get("GOOGLE_SERVICE_ACCOUNT_KEY_JSON_PATH")
+    if not service_account_json_path:
+        raise ValueError(
+            "Please set GOOGLE_SERVICE_ACCOUNT_KEY_JSON_PATH environment variable"
+        )
+    with open(service_account_json_path) as f:
+        creds = json.load(f)
+
+    credentials_dict = {
+        DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY: json.dumps(creds),
+    }
+    delegated_user = os.environ.get("GOOGLE_DRIVE_DELEGATED_USER")
+    if delegated_user:
+        credentials_dict[DB_CREDENTIALS_DICT_DELEGATED_USER_KEY] = delegated_user
+
+    connector = GoogleDriveConnector(include_shared=True, follow_shortcuts=True)
+    connector.load_credentials(credentials_dict)
+    document_batch_generator = connector.load_from_state()
+    for document_batch in document_batch_generator:
+        print(document_batch)
+        break

backend/danswer/connectors/google_drive/connector_auth.py

@@ -0,0 +1,229 @@
+import json
+from typing import cast
+from urllib.parse import parse_qs
+from urllib.parse import ParseResult
+from urllib.parse import urlparse
+
+from google.auth.transport.requests import Request  # type: ignore
+from google.oauth2.credentials import Credentials as OAuthCredentials  # type: ignore
+from google.oauth2.service_account import Credentials as ServiceAccountCredentials  # type: ignore
+from google_auth_oauthlib.flow import InstalledAppFlow  # type: ignore
+from sqlalchemy.orm import Session
+
+from danswer.configs.app_configs import ENTERPRISE_EDITION_ENABLED
+from danswer.configs.app_configs import WEB_DOMAIN
+from danswer.configs.constants import DocumentSource
+from danswer.configs.constants import KV_CRED_KEY
+from danswer.configs.constants import KV_GOOGLE_DRIVE_CRED_KEY
+from danswer.configs.constants import KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY
+from danswer.connectors.google_drive.constants import BASE_SCOPES
+from danswer.connectors.google_drive.constants import (
+    DB_CREDENTIALS_DICT_DELEGATED_USER_KEY,
+)
+from danswer.connectors.google_drive.constants import (
+    DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
+)
+from danswer.connectors.google_drive.constants import DB_CREDENTIALS_DICT_TOKEN_KEY
+from danswer.connectors.google_drive.constants import FETCH_GROUPS_SCOPES
+from danswer.connectors.google_drive.constants import FETCH_PERMISSIONS_SCOPES
+from danswer.db.credentials import update_credential_json
+from danswer.db.models import User
+from danswer.key_value_store.factory import get_kv_store
+from danswer.server.documents.models import CredentialBase
+from danswer.server.documents.models import GoogleAppCredentials
+from danswer.server.documents.models import GoogleServiceAccountKey
+from danswer.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+def build_gdrive_scopes() -> list[str]:
+    base_scopes: list[str] = BASE_SCOPES
+    permissions_scopes: list[str] = FETCH_PERMISSIONS_SCOPES
+    groups_scopes: list[str] = FETCH_GROUPS_SCOPES
+
+    if ENTERPRISE_EDITION_ENABLED:
+        return base_scopes + permissions_scopes + groups_scopes
+    return base_scopes + permissions_scopes
+
+
+def _build_frontend_google_drive_redirect() -> str:
+    return f"{WEB_DOMAIN}/admin/connectors/google-drive/auth/callback"
+
+
+def get_google_drive_creds_for_authorized_user(
+    token_json_str: str, scopes: list[str] = build_gdrive_scopes()
+) -> OAuthCredentials | None:
+    creds_json = json.loads(token_json_str)
+    creds = OAuthCredentials.from_authorized_user_info(creds_json, scopes)
+    if creds.valid:
+        return creds
+
+    if creds.expired and creds.refresh_token:
+        try:
+            creds.refresh(Request())
+            if creds.valid:
+                logger.notice("Refreshed Google Drive tokens.")
+                return creds
+        except Exception as e:
+            logger.exception(f"Failed to refresh google drive access token due to: {e}")
+            return None
+
+    return None
+
+
+def _get_google_drive_creds_for_service_account(
+    service_account_key_json_str: str, scopes: list[str] = build_gdrive_scopes()
+) -> ServiceAccountCredentials | None:
+    service_account_key = json.loads(service_account_key_json_str)
+    creds = ServiceAccountCredentials.from_service_account_info(
+        service_account_key, scopes=scopes
+    )
+    if not creds.valid or not creds.expired:
+        creds.refresh(Request())
+    return creds if creds.valid else None
+
+
+def get_google_drive_creds(
+    credentials: dict[str, str], scopes: list[str] = build_gdrive_scopes()
+) -> tuple[ServiceAccountCredentials | OAuthCredentials, dict[str, str] | None]:
+    oauth_creds = None
+    service_creds = None
+    new_creds_dict = None
+    if DB_CREDENTIALS_DICT_TOKEN_KEY in credentials:
+        access_token_json_str = cast(str, credentials[DB_CREDENTIALS_DICT_TOKEN_KEY])
+        oauth_creds = get_google_drive_creds_for_authorized_user(
+            token_json_str=access_token_json_str, scopes=scopes
+        )
+
+        # tell caller to update token stored in DB if it has changed
+        # (e.g. the token has been refreshed)
+        new_creds_json_str = oauth_creds.to_json() if oauth_creds else ""
+        if new_creds_json_str != access_token_json_str:
+            new_creds_dict = {DB_CREDENTIALS_DICT_TOKEN_KEY: new_creds_json_str}
+
+    elif DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY in credentials:
+        service_account_key_json_str = credentials[
+            DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY
+        ]
+        service_creds = _get_google_drive_creds_for_service_account(
+            service_account_key_json_str=service_account_key_json_str,
+            scopes=scopes,
+        )
+
+        # "Impersonate" a user if one is specified
+        delegated_user_email = cast(
+            str | None, credentials.get(DB_CREDENTIALS_DICT_DELEGATED_USER_KEY)
+        )
+        if delegated_user_email:
+            service_creds = (
+                service_creds.with_subject(delegated_user_email)
+                if service_creds
+                else None
+            )
+
+    creds: ServiceAccountCredentials | OAuthCredentials | None = (
+        oauth_creds or service_creds
+    )
+    if creds is None:
+        raise PermissionError(
+            "Unable to access Google Drive - unknown credential structure."
+        )
+
+    return creds, new_creds_dict
+
+
+def verify_csrf(credential_id: int, state: str) -> None:
+    csrf = get_kv_store().load(KV_CRED_KEY.format(str(credential_id)))
+    if csrf != state:
+        raise PermissionError(
+            "State from Google Drive Connector callback does not match expected"
+        )
+
+
+def get_auth_url(credential_id: int) -> str:
+    creds_str = str(get_kv_store().load(KV_GOOGLE_DRIVE_CRED_KEY))
+    credential_json = json.loads(creds_str)
+    flow = InstalledAppFlow.from_client_config(
+        credential_json,
+        scopes=build_gdrive_scopes(),
+        redirect_uri=_build_frontend_google_drive_redirect(),
+    )
+    auth_url, _ = flow.authorization_url(prompt="consent")
+
+    parsed_url = cast(ParseResult, urlparse(auth_url))
+    params = parse_qs(parsed_url.query)
+
+    get_kv_store().store(
+        KV_CRED_KEY.format(credential_id), params.get("state", [None])[0], encrypt=True
+    )  # type: ignore
+    return str(auth_url)
+
+
+def update_credential_access_tokens(
+    auth_code: str,
+    credential_id: int,
+    user: User,
+    db_session: Session,
+) -> OAuthCredentials | None:
+    app_credentials = get_google_app_cred()
+    flow = InstalledAppFlow.from_client_config(
+        app_credentials.model_dump(),
+        scopes=build_gdrive_scopes(),
+        redirect_uri=_build_frontend_google_drive_redirect(),
+    )
+    flow.fetch_token(code=auth_code)
+    creds = flow.credentials
+    token_json_str = creds.to_json()
+    new_creds_dict = {DB_CREDENTIALS_DICT_TOKEN_KEY: token_json_str}
+
+    if not update_credential_json(credential_id, new_creds_dict, user, db_session):
+        return None
+    return creds
+
+
+def build_service_account_creds(
+    source: DocumentSource,
+    delegated_user_email: str | None = None,
+) -> CredentialBase:
+    service_account_key = get_service_account_key()
+
+    credential_dict = {
+        DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY: service_account_key.json(),
+    }
+    if delegated_user_email:
+        credential_dict[DB_CREDENTIALS_DICT_DELEGATED_USER_KEY] = delegated_user_email
+
+    return CredentialBase(
+        credential_json=credential_dict,
+        admin_public=True,
+        source=DocumentSource.GOOGLE_DRIVE,
+    )
+
+
+def get_google_app_cred() -> GoogleAppCredentials:
+    creds_str = str(get_kv_store().load(KV_GOOGLE_DRIVE_CRED_KEY))
+    return GoogleAppCredentials(**json.loads(creds_str))
+
+
+def upsert_google_app_cred(app_credentials: GoogleAppCredentials) -> None:
+    get_kv_store().store(KV_GOOGLE_DRIVE_CRED_KEY, app_credentials.json(), encrypt=True)
+
+
+def delete_google_app_cred() -> None:
+    get_kv_store().delete(KV_GOOGLE_DRIVE_CRED_KEY)
+
+
+def get_service_account_key() -> GoogleServiceAccountKey:
+    creds_str = str(get_kv_store().load(KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY))
+    return GoogleServiceAccountKey(**json.loads(creds_str))
+
+
+def upsert_service_account_key(service_account_key: GoogleServiceAccountKey) -> None:
+    get_kv_store().store(
+        KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY, service_account_key.json(), encrypt=True
+    )
+
+
+def delete_service_account_key() -> None:
+    get_kv_store().delete(KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY)

backend/danswer/connectors/google_drive/constants.py

@@ -1,4 +1,7 @@
-UNSUPPORTED_FILE_TYPE_CONTENT = ""  # keep empty for now
-DRIVE_FOLDER_TYPE = "application/vnd.google-apps.folder"
-DRIVE_SHORTCUT_TYPE = "application/vnd.google-apps.shortcut"
-DRIVE_FILE_TYPE = "application/vnd.google-apps.file"
+DB_CREDENTIALS_DICT_TOKEN_KEY = "google_drive_tokens"
+DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY = "google_drive_service_account_key"
+DB_CREDENTIALS_DICT_DELEGATED_USER_KEY = "google_drive_delegated_user"
+
+BASE_SCOPES = ["https://www.googleapis.com/auth/drive.readonly"]
+FETCH_PERMISSIONS_SCOPES = ["https://www.googleapis.com/auth/drive.metadata.readonly"]
+FETCH_GROUPS_SCOPES = ["https://www.googleapis.com/auth/cloud-identity.groups.readonly"]

backend/danswer/connectors/google_drive/doc_conversion.py

@@ -1,197 +0,0 @@
-import io
-from datetime import datetime
-from datetime import timezone
-
-from googleapiclient.errors import HttpError  # type: ignore
-
-from danswer.configs.app_configs import CONTINUE_ON_CONNECTOR_FAILURE
-from danswer.configs.constants import DocumentSource
-from danswer.configs.constants import IGNORE_FOR_QA
-from danswer.connectors.google_drive.constants import DRIVE_FOLDER_TYPE
-from danswer.connectors.google_drive.constants import DRIVE_SHORTCUT_TYPE
-from danswer.connectors.google_drive.constants import UNSUPPORTED_FILE_TYPE_CONTENT
-from danswer.connectors.google_drive.models import GDriveMimeType
-from danswer.connectors.google_drive.models import GoogleDriveFileType
-from danswer.connectors.google_drive.section_extraction import get_document_sections
-from danswer.connectors.google_utils.resources import GoogleDocsService
-from danswer.connectors.google_utils.resources import GoogleDriveService
-from danswer.connectors.models import Document
-from danswer.connectors.models import Section
-from danswer.connectors.models import SlimDocument
-from danswer.file_processing.extract_file_text import docx_to_text
-from danswer.file_processing.extract_file_text import pptx_to_text
-from danswer.file_processing.extract_file_text import read_pdf_file
-from danswer.file_processing.unstructured import get_unstructured_api_key
-from danswer.file_processing.unstructured import unstructured_to_text
-from danswer.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-# these errors don't represent a failure in the connector, but simply files
-# that can't / shouldn't be indexed
-ERRORS_TO_CONTINUE_ON = [
-    "cannotExportFile",
-    "exportSizeLimitExceeded",
-    "cannotDownloadFile",
-]
-
-
-def _extract_sections_basic(
-    file: dict[str, str], service: GoogleDriveService
-) -> list[Section]:
-    mime_type = file["mimeType"]
-    link = file["webViewLink"]
-
-    if mime_type not in set(item.value for item in GDriveMimeType):
-        # Unsupported file types can still have a title, finding this way is still useful
-        return [Section(link=link, text=UNSUPPORTED_FILE_TYPE_CONTENT)]
-
-    try:
-        if mime_type in [
-            GDriveMimeType.DOC.value,
-            GDriveMimeType.PPT.value,
-            GDriveMimeType.SPREADSHEET.value,
-        ]:
-            export_mime_type = (
-                "text/plain"
-                if mime_type != GDriveMimeType.SPREADSHEET.value
-                else "text/csv"
-            )
-            text = (
-                service.files()
-                .export(fileId=file["id"], mimeType=export_mime_type)
-                .execute()
-                .decode("utf-8")
-            )
-            return [Section(link=link, text=text)]
-        elif mime_type in [
-            GDriveMimeType.PLAIN_TEXT.value,
-            GDriveMimeType.MARKDOWN.value,
-        ]:
-            return [
-                Section(
-                    link=link,
-                    text=service.files()
-                    .get_media(fileId=file["id"])
-                    .execute()
-                    .decode("utf-8"),
-                )
-            ]
-        if mime_type in [
-            GDriveMimeType.WORD_DOC.value,
-            GDriveMimeType.POWERPOINT.value,
-            GDriveMimeType.PDF.value,
-        ]:
-            response = service.files().get_media(fileId=file["id"]).execute()
-            if get_unstructured_api_key():
-                return [
-                    Section(
-                        link=link,
-                        text=unstructured_to_text(
-                            file=io.BytesIO(response),
-                            file_name=file.get("name", file["id"]),
-                        ),
-                    )
-                ]
-
-            if mime_type == GDriveMimeType.WORD_DOC.value:
-                return [
-                    Section(link=link, text=docx_to_text(file=io.BytesIO(response)))
-                ]
-            elif mime_type == GDriveMimeType.PDF.value:
-                text, _ = read_pdf_file(file=io.BytesIO(response))
-                return [Section(link=link, text=text)]
-            elif mime_type == GDriveMimeType.POWERPOINT.value:
-                return [
-                    Section(link=link, text=pptx_to_text(file=io.BytesIO(response)))
-                ]
-
-        return [Section(link=link, text=UNSUPPORTED_FILE_TYPE_CONTENT)]
-
-    except Exception:
-        return [Section(link=link, text=UNSUPPORTED_FILE_TYPE_CONTENT)]
-
-
-def convert_drive_item_to_document(
-    file: GoogleDriveFileType,
-    drive_service: GoogleDriveService,
-    docs_service: GoogleDocsService,
-) -> Document | None:
-    try:
-        # Skip files that are shortcuts
-        if file.get("mimeType") == DRIVE_SHORTCUT_TYPE:
-            logger.info("Ignoring Drive Shortcut Filetype")
-            return None
-        # Skip files that are folders
-        if file.get("mimeType") == DRIVE_FOLDER_TYPE:
-            logger.info("Ignoring Drive Folder Filetype")
-            return None
-
-        sections: list[Section] = []
-
-        # Special handling for Google Docs to preserve structure, link
-        # to headers
-        if file.get("mimeType") == GDriveMimeType.DOC.value:
-            try:
-                sections = get_document_sections(docs_service, file["id"])
-            except Exception as e:
-                logger.warning(
-                    f"Ran into exception '{e}' when pulling sections from Google Doc '{file['name']}'."
-                    " Falling back to basic extraction."
-                )
-        # NOTE: this will run for either (1) the above failed or (2) the file is not a Google Doc
-        if not sections:
-            try:
-                # For all other file types just extract the text
-                sections = _extract_sections_basic(file, drive_service)
-
-            except HttpError as e:
-                reason = e.error_details[0]["reason"] if e.error_details else e.reason
-                message = e.error_details[0]["message"] if e.error_details else e.reason
-                if e.status_code == 403 and reason in ERRORS_TO_CONTINUE_ON:
-                    logger.warning(
-                        f"Could not export file '{file['name']}' due to '{message}', skipping..."
-                    )
-                    return None
-
-                raise
-        if not sections:
-            return None
-
-        return Document(
-            id=file["webViewLink"],
-            sections=sections,
-            source=DocumentSource.GOOGLE_DRIVE,
-            semantic_identifier=file["name"],
-            doc_updated_at=datetime.fromisoformat(file["modifiedTime"]).astimezone(
-                timezone.utc
-            ),
-            metadata={}
-            if any(section.text for section in sections)
-            else {IGNORE_FOR_QA: "True"},
-            additional_info=file.get("id"),
-        )
-    except Exception as e:
-        if not CONTINUE_ON_CONNECTOR_FAILURE:
-            raise e
-
-        logger.exception("Ran into exception when pulling a file from Google Drive")
-    return None
-
-
-def build_slim_document(file: GoogleDriveFileType) -> SlimDocument | None:
-    # Skip files that are folders or shortcuts
-    if file.get("mimeType") in [DRIVE_FOLDER_TYPE, DRIVE_SHORTCUT_TYPE]:
-        return None
-
-    return SlimDocument(
-        id=file["webViewLink"],
-        perm_sync_data={
-            "doc_id": file.get("id"),
-            "permissions": file.get("permissions", []),
-            "permission_ids": file.get("permissionIds", []),
-            "name": file.get("name"),
-            "owner_email": file.get("owners", [{}])[0].get("emailAddress"),
-        },
-    )

backend/danswer/connectors/google_drive/file_retrieval.py

@@ -1,222 +0,0 @@
-from collections.abc import Callable
-from collections.abc import Iterator
-from datetime import datetime
-from typing import Any
-
-from googleapiclient.discovery import Resource  # type: ignore
-
-from danswer.connectors.google_drive.constants import DRIVE_FOLDER_TYPE
-from danswer.connectors.google_drive.constants import DRIVE_SHORTCUT_TYPE
-from danswer.connectors.google_drive.models import GoogleDriveFileType
-from danswer.connectors.google_utils.google_utils import execute_paginated_retrieval
-from danswer.connectors.interfaces import SecondsSinceUnixEpoch
-from danswer.utils.logger import setup_logger
-
-logger = setup_logger()
-
-FILE_FIELDS = (
-    "nextPageToken, files(mimeType, id, name, permissions, modifiedTime, webViewLink, "
-    "shortcutDetails, owners(emailAddress))"
-)
-SLIM_FILE_FIELDS = (
-    "nextPageToken, files(mimeType, id, name, permissions(emailAddress, type), "
-    "permissionIds, webViewLink, owners(emailAddress))"
-)
-FOLDER_FIELDS = "nextPageToken, files(id, name, permissions, modifiedTime, webViewLink, shortcutDetails)"
-
-
-def _generate_time_range_filter(
-    start: SecondsSinceUnixEpoch | None = None,
-    end: SecondsSinceUnixEpoch | None = None,
-) -> str:
-    time_range_filter = ""
-    if start is not None:
-        time_start = datetime.utcfromtimestamp(start).isoformat() + "Z"
-        time_range_filter += f" and modifiedTime >= '{time_start}'"
-    if end is not None:
-        time_stop = datetime.utcfromtimestamp(end).isoformat() + "Z"
-        time_range_filter += f" and modifiedTime <= '{time_stop}'"
-    return time_range_filter
-
-
-def _get_folders_in_parent(
-    service: Resource,
-    parent_id: str | None = None,
-) -> Iterator[GoogleDriveFileType]:
-    # Follow shortcuts to folders
-    query = f"(mimeType = '{DRIVE_FOLDER_TYPE}' or mimeType = '{DRIVE_SHORTCUT_TYPE}')"
-    query += " and trashed = false"
-
-    if parent_id:
-        query += f" and '{parent_id}' in parents"
-
-    for file in execute_paginated_retrieval(
-        retrieval_function=service.files().list,
-        list_key="files",
-        continue_on_404_or_403=True,
-        corpora="allDrives",
-        supportsAllDrives=True,
-        includeItemsFromAllDrives=True,
-        fields=FOLDER_FIELDS,
-        q=query,
-    ):
-        yield file
-
-
-def _get_files_in_parent(
-    service: Resource,
-    parent_id: str,
-    start: SecondsSinceUnixEpoch | None = None,
-    end: SecondsSinceUnixEpoch | None = None,
-    is_slim: bool = False,
-) -> Iterator[GoogleDriveFileType]:
-    query = f"mimeType != '{DRIVE_FOLDER_TYPE}' and '{parent_id}' in parents"
-    query += " and trashed = false"
-    query += _generate_time_range_filter(start, end)
-
-    for file in execute_paginated_retrieval(
-        retrieval_function=service.files().list,
-        list_key="files",
-        continue_on_404_or_403=True,
-        corpora="allDrives",
-        supportsAllDrives=True,
-        includeItemsFromAllDrives=True,
-        fields=SLIM_FILE_FIELDS if is_slim else FILE_FIELDS,
-        q=query,
-    ):
-        yield file
-
-
-def crawl_folders_for_files(
-    service: Resource,
-    parent_id: str,
-    traversed_parent_ids: set[str],
-    update_traversed_ids_func: Callable[[str], None],
-    start: SecondsSinceUnixEpoch | None = None,
-    end: SecondsSinceUnixEpoch | None = None,
-) -> Iterator[GoogleDriveFileType]:
-    """
-    This function starts crawling from any folder. It is slower though.
-    """
-    if parent_id in traversed_parent_ids:
-        logger.info(f"Skipping subfolder since already traversed: {parent_id}")
-        return
-
-    found_files = False
-    for file in _get_files_in_parent(
-        service=service,
-        start=start,
-        end=end,
-        parent_id=parent_id,
-    ):
-        found_files = True
-        yield file
-
-    if found_files:
-        update_traversed_ids_func(parent_id)
-
-    for subfolder in _get_folders_in_parent(
-        service=service,
-        parent_id=parent_id,
-    ):
-        logger.info("Fetching all files in subfolder: " + subfolder["name"])
-        yield from crawl_folders_for_files(
-            service=service,
-            parent_id=subfolder["id"],
-            traversed_parent_ids=traversed_parent_ids,
-            update_traversed_ids_func=update_traversed_ids_func,
-            start=start,
-            end=end,
-        )
-
-
-def get_files_in_shared_drive(
-    service: Resource,
-    drive_id: str,
-    is_slim: bool = False,
-    update_traversed_ids_func: Callable[[str], None] = lambda _: None,
-    start: SecondsSinceUnixEpoch | None = None,
-    end: SecondsSinceUnixEpoch | None = None,
-) -> Iterator[GoogleDriveFileType]:
-    # If we know we are going to folder crawl later, we can cache the folders here
-    # Get all folders being queried and add them to the traversed set
-    query = f"mimeType = '{DRIVE_FOLDER_TYPE}'"
-    query += " and trashed = false"
-    found_folders = False
-    for file in execute_paginated_retrieval(
-        retrieval_function=service.files().list,
-        list_key="files",
-        continue_on_404_or_403=True,
-        corpora="drive",
-        driveId=drive_id,
-        supportsAllDrives=True,
-        includeItemsFromAllDrives=True,
-        fields="nextPageToken, files(id)",
-        q=query,
-    ):
-        update_traversed_ids_func(file["id"])
-        found_folders = True
-    if found_folders:
-        update_traversed_ids_func(drive_id)
-
-    # Get all files in the shared drive
-    query = f"mimeType != '{DRIVE_FOLDER_TYPE}'"
-    query += " and trashed = false"
-    query += _generate_time_range_filter(start, end)
-    yield from execute_paginated_retrieval(
-        retrieval_function=service.files().list,
-        list_key="files",
-        continue_on_404_or_403=True,
-        corpora="drive",
-        driveId=drive_id,
-        supportsAllDrives=True,
-        includeItemsFromAllDrives=True,
-        fields=SLIM_FILE_FIELDS if is_slim else FILE_FIELDS,
-        q=query,
-    )
-
-
-def get_all_files_in_my_drive(
-    service: Any,
-    update_traversed_ids_func: Callable,
-    is_slim: bool = False,
-    start: SecondsSinceUnixEpoch | None = None,
-    end: SecondsSinceUnixEpoch | None = None,
-) -> Iterator[GoogleDriveFileType]:
-    # If we know we are going to folder crawl later, we can cache the folders here
-    # Get all folders being queried and add them to the traversed set
-    query = "trashed = false and 'me' in owners"
-    found_folders = False
-    for file in execute_paginated_retrieval(
-        retrieval_function=service.files().list,
-        list_key="files",
-        corpora="user",
-        fields=SLIM_FILE_FIELDS if is_slim else FILE_FIELDS,
-        q=query,
-    ):
-        update_traversed_ids_func(file["id"])
-        found_folders = True
-    if found_folders:
-        update_traversed_ids_func(get_root_folder_id(service))
-
-    # Then get the files
-    query = "trashed = false and 'me' in owners"
-    query += _generate_time_range_filter(start, end)
-    fields = "files(id, name, mimeType, webViewLink, modifiedTime, createdTime)"
-    if not is_slim:
-        fields += ", files(permissions, permissionIds, owners)"
-
-    yield from execute_paginated_retrieval(
-        retrieval_function=service.files().list,
-        list_key="files",
-        corpora="user",
-        fields=SLIM_FILE_FIELDS if is_slim else FILE_FIELDS,
-        q=query,
-    )
-
-
-# Just in case we need to get the root folder id
-def get_root_folder_id(service: Resource) -> str:
-    # we dont paginate here because there is only one root folder per user
-    # https://developers.google.com/drive/api/guides/v2-to-v3-reference
-    return service.files().get(fileId="root", fields="id").execute()["id"]

backend/danswer/connectors/google_drive/models.py

@@ -1,18 +0,0 @@
-from enum import Enum
-from typing import Any
-
-
-class GDriveMimeType(str, Enum):
-    DOC = "application/vnd.google-apps.document"
-    SPREADSHEET = "application/vnd.google-apps.spreadsheet"
-    PDF = "application/pdf"
-    WORD_DOC = "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
-    PPT = "application/vnd.google-apps.presentation"
-    POWERPOINT = (
-        "application/vnd.openxmlformats-officedocument.presentationml.presentation"
-    )
-    PLAIN_TEXT = "text/plain"
-    MARKDOWN = "text/markdown"
-
-
-GoogleDriveFileType = dict[str, Any]

backend/danswer/connectors/google_drive/section_extraction.py

@@ -1,105 +0,0 @@
-from typing import Any
-
-from pydantic import BaseModel
-
-from danswer.connectors.google_utils.resources import GoogleDocsService
-from danswer.connectors.models import Section
-
-
-class CurrentHeading(BaseModel):
-    id: str
-    text: str
-
-
-def _build_gdoc_section_link(doc_id: str, heading_id: str) -> str:
-    """Builds a Google Doc link that jumps to a specific heading"""
-    # NOTE: doesn't support docs with multiple tabs atm, if we need that ask
-    # @Chris
-    return (
-        f"https://docs.google.com/document/d/{doc_id}/edit?tab=t.0#heading={heading_id}"
-    )
-
-
-def _extract_id_from_heading(paragraph: dict[str, Any]) -> str:
-    """Extracts the id from a heading paragraph element"""
-    return paragraph["paragraphStyle"]["headingId"]
-
-
-def _extract_text_from_paragraph(paragraph: dict[str, Any]) -> str:
-    """Extracts the text content from a paragraph element"""
-    text_elements = []
-    for element in paragraph.get("elements", []):
-        if "textRun" in element:
-            text_elements.append(element["textRun"].get("content", ""))
-    return "".join(text_elements)
-
-
-def get_document_sections(
-    docs_service: GoogleDocsService,
-    doc_id: str,
-) -> list[Section]:
-    """Extracts sections from a Google Doc, including their headings and content"""
-    # Fetch the document structure
-    doc = docs_service.documents().get(documentId=doc_id).execute()
-
-    # Get the content
-    content = doc.get("body", {}).get("content", [])
-
-    sections: list[Section] = []
-    current_section: list[str] = []
-    current_heading: CurrentHeading | None = None
-
-    for element in content:
-        if "paragraph" not in element:
-            continue
-
-        paragraph = element["paragraph"]
-
-        # Check if this is a heading
-        if (
-            "paragraphStyle" in paragraph
-            and "namedStyleType" in paragraph["paragraphStyle"]
-        ):
-            style = paragraph["paragraphStyle"]["namedStyleType"]
-            is_heading = style.startswith("HEADING_")
-            is_title = style.startswith("TITLE")
-
-            if is_heading or is_title:
-                # If we were building a previous section, add it to sections list
-                if current_heading is not None and current_section:
-                    heading_text = current_heading.text
-                    section_text = f"{heading_text}\n" + "\n".join(current_section)
-                    sections.append(
-                        Section(
-                            text=section_text.strip(),
-                            link=_build_gdoc_section_link(doc_id, current_heading.id),
-                        )
-                    )
-                    current_section = []
-
-                # Start new heading
-                heading_id = _extract_id_from_heading(paragraph)
-                heading_text = _extract_text_from_paragraph(paragraph)
-                current_heading = CurrentHeading(
-                    id=heading_id,
-                    text=heading_text,
-                )
-                continue
-
-        # Add content to current section
-        if current_heading is not None:
-            text = _extract_text_from_paragraph(paragraph)
-            if text.strip():
-                current_section.append(text)
-
-    # Don't forget to add the last section
-    if current_heading is not None and current_section:
-        section_text = f"{current_heading.text}\n" + "\n".join(current_section)
-        sections.append(
-            Section(
-                text=section_text.strip(),
-                link=_build_gdoc_section_link(doc_id, current_heading.id),
-            )
-        )
-
-    return sections

backend/danswer/connectors/google_utils/google_auth.py

@@ -1,107 +0,0 @@
-import json
-from typing import cast
-
-from google.auth.transport.requests import Request  # type: ignore
-from google.oauth2.credentials import Credentials as OAuthCredentials  # type: ignore
-from google.oauth2.service_account import Credentials as ServiceAccountCredentials  # type: ignore
-
-from danswer.configs.constants import DocumentSource
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_DICT_TOKEN_KEY,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_PRIMARY_ADMIN_KEY,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    GOOGLE_SCOPES,
-)
-from danswer.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-def get_google_oauth_creds(
-    token_json_str: str, source: DocumentSource
-) -> OAuthCredentials | None:
-    creds_json = json.loads(token_json_str)
-    creds = OAuthCredentials.from_authorized_user_info(
-        info=creds_json,
-        scopes=GOOGLE_SCOPES[source],
-    )
-    if creds.valid:
-        return creds
-
-    if creds.expired and creds.refresh_token:
-        try:
-            creds.refresh(Request())
-            if creds.valid:
-                logger.notice("Refreshed Google Drive tokens.")
-                return creds
-        except Exception:
-            logger.exception("Failed to refresh google drive access token due to:")
-            return None
-
-    return None
-
-
-def get_google_creds(
-    credentials: dict[str, str],
-    source: DocumentSource,
-) -> tuple[ServiceAccountCredentials | OAuthCredentials, dict[str, str] | None]:
-    """Checks for two different types of credentials.
-    (1) A credential which holds a token acquired via a user going thorough
-    the Google OAuth flow.
-    (2) A credential which holds a service account key JSON file, which
-    can then be used to impersonate any user in the workspace.
-    """
-    oauth_creds = None
-    service_creds = None
-    new_creds_dict = None
-    if DB_CREDENTIALS_DICT_TOKEN_KEY in credentials:
-        # OAUTH
-        access_token_json_str = cast(str, credentials[DB_CREDENTIALS_DICT_TOKEN_KEY])
-        oauth_creds = get_google_oauth_creds(
-            token_json_str=access_token_json_str, source=source
-        )
-
-        # tell caller to update token stored in DB if it has changed
-        # (e.g. the token has been refreshed)
-        new_creds_json_str = oauth_creds.to_json() if oauth_creds else ""
-        if new_creds_json_str != access_token_json_str:
-            new_creds_dict = {
-                DB_CREDENTIALS_DICT_TOKEN_KEY: new_creds_json_str,
-                DB_CREDENTIALS_PRIMARY_ADMIN_KEY: credentials[
-                    DB_CREDENTIALS_PRIMARY_ADMIN_KEY
-                ],
-            }
-    elif DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY in credentials:
-        # SERVICE ACCOUNT
-        service_account_key_json_str = credentials[
-            DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY
-        ]
-        service_account_key = json.loads(service_account_key_json_str)
-
-        service_creds = ServiceAccountCredentials.from_service_account_info(
-            service_account_key, scopes=GOOGLE_SCOPES[source]
-        )
-
-        if not service_creds.valid or not service_creds.expired:
-            service_creds.refresh(Request())
-
-        if not service_creds.valid:
-            raise PermissionError(
-                f"Unable to access {source} - service account credentials are invalid."
-            )
-
-    creds: ServiceAccountCredentials | OAuthCredentials | None = (
-        oauth_creds or service_creds
-    )
-    if creds is None:
-        raise PermissionError(
-            f"Unable to access {source} - unknown credential structure."
-        )
-
-    return creds, new_creds_dict

backend/danswer/connectors/google_utils/google_kv.py

@@ -1,237 +0,0 @@
-import json
-from typing import cast
-from urllib.parse import parse_qs
-from urllib.parse import ParseResult
-from urllib.parse import urlparse
-
-from google.oauth2.credentials import Credentials as OAuthCredentials  # type: ignore
-from google_auth_oauthlib.flow import InstalledAppFlow  # type: ignore
-from sqlalchemy.orm import Session
-
-from danswer.configs.app_configs import WEB_DOMAIN
-from danswer.configs.constants import DocumentSource
-from danswer.configs.constants import KV_CRED_KEY
-from danswer.configs.constants import KV_GMAIL_CRED_KEY
-from danswer.configs.constants import KV_GMAIL_SERVICE_ACCOUNT_KEY
-from danswer.configs.constants import KV_GOOGLE_DRIVE_CRED_KEY
-from danswer.configs.constants import KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY
-from danswer.connectors.google_utils.resources import get_drive_service
-from danswer.connectors.google_utils.resources import get_gmail_service
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_DICT_TOKEN_KEY,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_PRIMARY_ADMIN_KEY,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    GOOGLE_SCOPES,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    MISSING_SCOPES_ERROR_STR,
-)
-from danswer.connectors.google_utils.shared_constants import (
-    ONYX_SCOPE_INSTRUCTIONS,
-)
-from danswer.db.credentials import update_credential_json
-from danswer.db.models import User
-from danswer.key_value_store.factory import get_kv_store
-from danswer.server.documents.models import CredentialBase
-from danswer.server.documents.models import GoogleAppCredentials
-from danswer.server.documents.models import GoogleServiceAccountKey
-from danswer.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-def _build_frontend_google_drive_redirect(source: DocumentSource) -> str:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        return f"{WEB_DOMAIN}/admin/connectors/google-drive/auth/callback"
-    elif source == DocumentSource.GMAIL:
-        return f"{WEB_DOMAIN}/admin/connectors/gmail/auth/callback"
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-
-
-def _get_current_oauth_user(creds: OAuthCredentials, source: DocumentSource) -> str:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        drive_service = get_drive_service(creds)
-        user_info = (
-            drive_service.about()
-            .get(
-                fields="user(emailAddress)",
-            )
-            .execute()
-        )
-        email = user_info.get("user", {}).get("emailAddress")
-    elif source == DocumentSource.GMAIL:
-        gmail_service = get_gmail_service(creds)
-        user_info = (
-            gmail_service.users()
-            .getProfile(
-                userId="me",
-                fields="emailAddress",
-            )
-            .execute()
-        )
-        email = user_info.get("emailAddress")
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-    return email
-
-
-def verify_csrf(credential_id: int, state: str) -> None:
-    csrf = get_kv_store().load(KV_CRED_KEY.format(str(credential_id)))
-    if csrf != state:
-        raise PermissionError(
-            "State from Google Drive Connector callback does not match expected"
-        )
-
-
-def update_credential_access_tokens(
-    auth_code: str,
-    credential_id: int,
-    user: User,
-    db_session: Session,
-    source: DocumentSource,
-) -> OAuthCredentials | None:
-    app_credentials = get_google_app_cred(source)
-    flow = InstalledAppFlow.from_client_config(
-        app_credentials.model_dump(),
-        scopes=GOOGLE_SCOPES[source],
-        redirect_uri=_build_frontend_google_drive_redirect(source),
-    )
-    flow.fetch_token(code=auth_code)
-    creds = flow.credentials
-    token_json_str = creds.to_json()
-
-    # Get user email from Google API so we know who
-    # the primary admin is for this connector
-    try:
-        email = _get_current_oauth_user(creds, source)
-    except Exception as e:
-        if MISSING_SCOPES_ERROR_STR in str(e):
-            raise PermissionError(ONYX_SCOPE_INSTRUCTIONS) from e
-        raise e
-
-    new_creds_dict = {
-        DB_CREDENTIALS_DICT_TOKEN_KEY: token_json_str,
-        DB_CREDENTIALS_PRIMARY_ADMIN_KEY: email,
-    }
-
-    if not update_credential_json(credential_id, new_creds_dict, user, db_session):
-        return None
-    return creds
-
-
-def build_service_account_creds(
-    source: DocumentSource,
-    primary_admin_email: str | None = None,
-) -> CredentialBase:
-    service_account_key = get_service_account_key(source=source)
-
-    credential_dict = {
-        DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY: service_account_key.json(),
-    }
-    if primary_admin_email:
-        credential_dict[DB_CREDENTIALS_PRIMARY_ADMIN_KEY] = primary_admin_email
-
-    return CredentialBase(
-        credential_json=credential_dict,
-        admin_public=True,
-        source=source,
-    )
-
-
-def get_auth_url(credential_id: int, source: DocumentSource) -> str:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        creds_str = str(get_kv_store().load(KV_GOOGLE_DRIVE_CRED_KEY))
-    elif source == DocumentSource.GMAIL:
-        creds_str = str(get_kv_store().load(KV_GMAIL_CRED_KEY))
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-    credential_json = json.loads(creds_str)
-    flow = InstalledAppFlow.from_client_config(
-        credential_json,
-        scopes=GOOGLE_SCOPES[source],
-        redirect_uri=_build_frontend_google_drive_redirect(source),
-    )
-    auth_url, _ = flow.authorization_url(prompt="consent")
-
-    parsed_url = cast(ParseResult, urlparse(auth_url))
-    params = parse_qs(parsed_url.query)
-
-    get_kv_store().store(
-        KV_CRED_KEY.format(credential_id), params.get("state", [None])[0], encrypt=True
-    )  # type: ignore
-    return str(auth_url)
-
-
-def get_google_app_cred(source: DocumentSource) -> GoogleAppCredentials:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        creds_str = str(get_kv_store().load(KV_GOOGLE_DRIVE_CRED_KEY))
-    elif source == DocumentSource.GMAIL:
-        creds_str = str(get_kv_store().load(KV_GMAIL_CRED_KEY))
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-    return GoogleAppCredentials(**json.loads(creds_str))
-
-
-def upsert_google_app_cred(
-    app_credentials: GoogleAppCredentials, source: DocumentSource
-) -> None:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        get_kv_store().store(
-            KV_GOOGLE_DRIVE_CRED_KEY, app_credentials.json(), encrypt=True
-        )
-    elif source == DocumentSource.GMAIL:
-        get_kv_store().store(KV_GMAIL_CRED_KEY, app_credentials.json(), encrypt=True)
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-
-
-def delete_google_app_cred(source: DocumentSource) -> None:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        get_kv_store().delete(KV_GOOGLE_DRIVE_CRED_KEY)
-    elif source == DocumentSource.GMAIL:
-        get_kv_store().delete(KV_GMAIL_CRED_KEY)
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-
-
-def get_service_account_key(source: DocumentSource) -> GoogleServiceAccountKey:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        creds_str = str(get_kv_store().load(KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY))
-    elif source == DocumentSource.GMAIL:
-        creds_str = str(get_kv_store().load(KV_GMAIL_SERVICE_ACCOUNT_KEY))
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-    return GoogleServiceAccountKey(**json.loads(creds_str))
-
-
-def upsert_service_account_key(
-    service_account_key: GoogleServiceAccountKey, source: DocumentSource
-) -> None:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        get_kv_store().store(
-            KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY,
-            service_account_key.json(),
-            encrypt=True,
-        )
-    elif source == DocumentSource.GMAIL:
-        get_kv_store().store(
-            KV_GMAIL_SERVICE_ACCOUNT_KEY, service_account_key.json(), encrypt=True
-        )
-    else:
-        raise ValueError(f"Unsupported source: {source}")
-
-
-def delete_service_account_key(source: DocumentSource) -> None:
-    if source == DocumentSource.GOOGLE_DRIVE:
-        get_kv_store().delete(KV_GOOGLE_DRIVE_SERVICE_ACCOUNT_KEY)
-    elif source == DocumentSource.GMAIL:
-        get_kv_store().delete(KV_GMAIL_SERVICE_ACCOUNT_KEY)
-    else:
-        raise ValueError(f"Unsupported source: {source}")

backend/danswer/connectors/google_utils/google_utils.py

@@ -1,125 +0,0 @@
-import re
-import time
-from collections.abc import Callable
-from collections.abc import Iterator
-from datetime import datetime
-from datetime import timezone
-from typing import Any
-
-from googleapiclient.errors import HttpError  # type: ignore
-
-from danswer.connectors.google_drive.models import GoogleDriveFileType
-from danswer.utils.logger import setup_logger
-from danswer.utils.retry_wrapper import retry_builder
-
-logger = setup_logger()
-
-
-# Google Drive APIs are quite flakey and may 500 for an
-# extended period of time. Trying to combat here by adding a very
-# long retry period (~20 minutes of trying every minute)
-add_retries = retry_builder(tries=50, max_delay=30)
-
-
-def _execute_with_retry(request: Any) -> Any:
-    max_attempts = 10
-    attempt = 1
-
-    while attempt < max_attempts:
-        # Note for reasons unknown, the Google API will sometimes return a 429
-        # and even after waiting the retry period, it will return another 429.
-        # It could be due to a few possibilities:
-        # 1. Other things are also requesting from the Gmail API with the same key
-        # 2. It's a rolling rate limit so the moment we get some amount of requests cleared, we hit it again very quickly
-        # 3. The retry-after has a maximum and we've already hit the limit for the day
-        # or it's something else...
-        try:
-            return request.execute()
-        except HttpError as error:
-            attempt += 1
-
-            if error.resp.status == 429:
-                # Attempt to get 'Retry-After' from headers
-                retry_after = error.resp.get("Retry-After")
-                if retry_after:
-                    sleep_time = int(retry_after)
-                else:
-                    # Extract 'Retry after' timestamp from error message
-                    match = re.search(
-                        r"Retry after (\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\.\d+Z)",
-                        str(error),
-                    )
-                    if match:
-                        retry_after_timestamp = match.group(1)
-                        retry_after_dt = datetime.strptime(
-                            retry_after_timestamp, "%Y-%m-%dT%H:%M:%S.%fZ"
-                        ).replace(tzinfo=timezone.utc)
-                        current_time = datetime.now(timezone.utc)
-                        sleep_time = max(
-                            int((retry_after_dt - current_time).total_seconds()),
-                            0,
-                        )
-                    else:
-                        logger.error(
-                            f"No Retry-After header or timestamp found in error message: {error}"
-                        )
-                        sleep_time = 60
-
-                sleep_time += 3  # Add a buffer to be safe
-
-                logger.info(
-                    f"Rate limit exceeded. Attempt {attempt}/{max_attempts}. Sleeping for {sleep_time} seconds."
-                )
-                time.sleep(sleep_time)
-
-            else:
-                raise
-
-    # If we've exhausted all attempts
-    raise Exception(f"Failed to execute request after {max_attempts} attempts")
-
-
-def execute_paginated_retrieval(
-    retrieval_function: Callable,
-    list_key: str | None = None,
-    continue_on_404_or_403: bool = False,
-    **kwargs: Any,
-) -> Iterator[GoogleDriveFileType]:
-    """Execute a paginated retrieval from Google Drive API
-    Args:
-        retrieval_function: The specific list function to call (e.g., service.files().list)
-        **kwargs: Arguments to pass to the list function
-    """
-    next_page_token = ""
-    while next_page_token is not None:
-        request_kwargs = kwargs.copy()
-        if next_page_token:
-            request_kwargs["pageToken"] = next_page_token
-
-        try:
-            results = retrieval_function(**request_kwargs).execute()
-        except HttpError as e:
-            if e.resp.status >= 500:
-                results = add_retries(
-                    lambda: retrieval_function(**request_kwargs).execute()
-                )()
-            elif e.resp.status == 404 or e.resp.status == 403:
-                if continue_on_404_or_403:
-                    logger.warning(f"Error executing request: {e}")
-                    results = {}
-                else:
-                    raise e
-            elif e.resp.status == 429:
-                results = _execute_with_retry(
-                    lambda: retrieval_function(**request_kwargs).execute()
-                )
-            else:
-                logger.exception("Error executing request:")
-                raise e
-
-        next_page_token = results.get("nextPageToken")
-        if list_key:
-            for item in results.get(list_key, []):
-                yield item
-        else:
-            yield results

backend/danswer/connectors/google_utils/resources.py

@@ -1,63 +0,0 @@
-from google.oauth2.credentials import Credentials as OAuthCredentials  # type: ignore
-from google.oauth2.service_account import Credentials as ServiceAccountCredentials  # type: ignore
-from googleapiclient.discovery import build  # type: ignore
-from googleapiclient.discovery import Resource  # type: ignore
-
-
-class GoogleDriveService(Resource):
-    pass
-
-
-class GoogleDocsService(Resource):
-    pass
-
-
-class AdminService(Resource):
-    pass
-
-
-class GmailService(Resource):
-    pass
-
-
-def _get_google_service(
-    service_name: str,
-    service_version: str,
-    creds: ServiceAccountCredentials | OAuthCredentials,
-    user_email: str | None = None,
-) -> GoogleDriveService | GoogleDocsService | AdminService | GmailService:
-    if isinstance(creds, ServiceAccountCredentials):
-        creds = creds.with_subject(user_email)
-        service = build(service_name, service_version, credentials=creds)
-    elif isinstance(creds, OAuthCredentials):
-        service = build(service_name, service_version, credentials=creds)
-
-    return service
-
-
-def get_google_docs_service(
-    creds: ServiceAccountCredentials | OAuthCredentials,
-    user_email: str | None = None,
-) -> GoogleDocsService:
-    return _get_google_service("docs", "v1", creds, user_email)
-
-
-def get_drive_service(
-    creds: ServiceAccountCredentials | OAuthCredentials,
-    user_email: str | None = None,
-) -> GoogleDriveService:
-    return _get_google_service("drive", "v3", creds, user_email)
-
-
-def get_admin_service(
-    creds: ServiceAccountCredentials | OAuthCredentials,
-    user_email: str | None = None,
-) -> AdminService:
-    return _get_google_service("admin", "directory_v1", creds, user_email)
-
-
-def get_gmail_service(
-    creds: ServiceAccountCredentials | OAuthCredentials,
-    user_email: str | None = None,
-) -> GmailService:
-    return _get_google_service("gmail", "v1", creds, user_email)

backend/danswer/connectors/google_utils/shared_constants.py

@@ -1,40 +0,0 @@
-from danswer.configs.constants import DocumentSource
-
-# NOTE: do not need https://www.googleapis.com/auth/documents.readonly
-# this is counted under `/auth/drive.readonly`
-GOOGLE_SCOPES = {
-    DocumentSource.GOOGLE_DRIVE: [
-        "https://www.googleapis.com/auth/drive.readonly",
-        "https://www.googleapis.com/auth/drive.metadata.readonly",
-        "https://www.googleapis.com/auth/admin.directory.group.readonly",
-        "https://www.googleapis.com/auth/admin.directory.user.readonly",
-    ],
-    DocumentSource.GMAIL: [
-        "https://www.googleapis.com/auth/gmail.readonly",
-        "https://www.googleapis.com/auth/admin.directory.user.readonly",
-        "https://www.googleapis.com/auth/admin.directory.group.readonly",
-    ],
-}
-
-# This is the Oauth token
-DB_CREDENTIALS_DICT_TOKEN_KEY = "google_tokens"
-# This is the service account key
-DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY = "google_service_account_key"
-# The email saved for both auth types
-DB_CREDENTIALS_PRIMARY_ADMIN_KEY = "google_primary_admin"
-
-USER_FIELDS = "nextPageToken, users(primaryEmail)"
-
-# Error message substrings
-MISSING_SCOPES_ERROR_STR = "client not authorized for any of the scopes requested"
-
-# Documentation and error messages
-SCOPE_DOC_URL = "https://docs.danswer.dev/connectors/google_drive/overview"
-ONYX_SCOPE_INSTRUCTIONS = (
-    "You have upgraded Danswer without updating the Google Auth scopes. "
-    f"Please refer to the documentation to learn how to update the scopes: {SCOPE_DOC_URL}"
-)
-
-
-# This is the maximum number of threads that can be retrieved at once
-SLIM_BATCH_SIZE = 500

backend/danswer/connectors/interfaces.py

@@ -56,11 +56,7 @@ class PollConnector(BaseConnector):
 
 class SlimConnector(BaseConnector):
     @abc.abstractmethod
-    def retrieve_all_slim_documents(
-        self,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
+    def retrieve_all_slim_documents(self) -> GenerateSlimDocumentOutput:
         raise NotImplementedError
 
 

backend/danswer/connectors/mediawiki/family.py

@@ -3,7 +3,6 @@ from __future__ import annotations
 import builtins
 import functools
 import itertools
-import tempfile
 from typing import Any
 from unittest import mock
 from urllib.parse import urlparse
@@ -19,8 +18,6 @@ from danswer.utils.logger import setup_logger
 
 logger = setup_logger()
 
-pywikibot.config.base_dir = tempfile.TemporaryDirectory().name
-
 
 @mock.patch.object(
     builtins, "print", lambda *args: logger.info("\t".join(map(str, args)))

backend/danswer/connectors/mediawiki/wiki.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 
 import datetime
 import itertools
-import tempfile
 from collections.abc import Generator
 from collections.abc import Iterator
 from typing import Any
@@ -26,8 +25,6 @@ from danswer.utils.logger import setup_logger
 
 logger = setup_logger()
 
-pywikibot.config.base_dir = tempfile.TemporaryDirectory().name
-
 
 def pywikibot_timestamp_to_utc_datetime(
     timestamp: pywikibot.time.Timestamp,
@@ -124,6 +121,7 @@ class MediaWikiConnector(LoadConnector, PollConnector):
         self.batch_size = batch_size
 
         # short names can only have ascii letters and digits
+
         self.family = family_class_dispatch(hostname, "WikipediaConnector")()
         self.site = pywikibot.Site(fam=self.family, code=language_code)
         self.categories = [

backend/danswer/connectors/salesforce/connector.py

@@ -251,11 +251,7 @@ class SalesforceConnector(LoadConnector, PollConnector, SlimConnector):
         end_datetime = datetime.utcfromtimestamp(end)
         return self._fetch_from_salesforce(start=start_datetime, end=end_datetime)
 
-    def retrieve_all_slim_documents(
-        self,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
+    def retrieve_all_slim_documents(self) -> GenerateSlimDocumentOutput:
         if self.sf_client is None:
             raise ConnectorMissingCredentialError("Salesforce")
         doc_metadata_list: list[SlimDocument] = []

backend/danswer/connectors/slack/connector.py

@@ -391,11 +391,7 @@ class SlackPollConnector(PollConnector, SlimConnector):
         self.client = WebClient(token=bot_token)
         return None
 
-    def retrieve_all_slim_documents(
-        self,
-        start: SecondsSinceUnixEpoch | None = None,
-        end: SecondsSinceUnixEpoch | None = None,
-    ) -> GenerateSlimDocumentOutput:
+    def retrieve_all_slim_documents(self) -> GenerateSlimDocumentOutput:
         if self.client is None:
             raise ConnectorMissingCredentialError("Slack")
 

backend/danswer/connectors/zendesk/connector.py

@@ -1,7 +1,10 @@
-from collections.abc import Iterator
 from typing import Any
 
 import requests
+from retry import retry
+from zenpy import Zenpy  # type: ignore
+from zenpy.lib.api_objects import Ticket  # type: ignore
+from zenpy.lib.api_objects.help_centre_objects import Article  # type: ignore
 
 from danswer.configs.app_configs import INDEX_BATCH_SIZE
 from danswer.configs.app_configs import ZENDESK_CONNECTOR_SKIP_ARTICLE_LABELS
@@ -17,244 +20,43 @@ from danswer.connectors.models import BasicExpertInfo
 from danswer.connectors.models import Document
 from danswer.connectors.models import Section
 from danswer.file_processing.html_utils import parse_html_page_basic
-from danswer.utils.retry_wrapper import retry_builder
 
 
-MAX_PAGE_SIZE = 30  # Zendesk API maximum
-
-
-class ZendeskCredentialsNotSetUpError(PermissionError):
-    def __init__(self) -> None:
-        super().__init__(
-            "Zendesk Credentials are not set up, was load_credentials called?"
-        )
-
-
-class ZendeskClient:
-    def __init__(self, subdomain: str, email: str, token: str):
-        self.base_url = f"https://{subdomain}.zendesk.com/api/v2"
-        self.auth = (f"{email}/token", token)
-
-    @retry_builder()
-    def make_request(self, endpoint: str, params: dict[str, Any]) -> dict[str, Any]:
-        response = requests.get(
-            f"{self.base_url}/{endpoint}", auth=self.auth, params=params
-        )
-        response.raise_for_status()
-        return response.json()
-
-
-def _get_content_tag_mapping(client: ZendeskClient) -> dict[str, str]:
-    content_tags: dict[str, str] = {}
-    params = {"page[size]": MAX_PAGE_SIZE}
-
-    try:
-        while True:
-            data = client.make_request("guide/content_tags", params)
-
-            for tag in data.get("records", []):
-                content_tags[tag["id"]] = tag["name"]
-
-            # Check if there are more pages
-            if data.get("meta", {}).get("has_more", False):
-                params["page[after]"] = data["meta"]["after_cursor"]
-            else:
-                break
-
-        return content_tags
-    except Exception as e:
-        raise Exception(f"Error fetching content tags: {str(e)}")
-
-
-def _get_articles(
-    client: ZendeskClient, start_time: int | None = None, page_size: int = MAX_PAGE_SIZE
-) -> Iterator[dict[str, Any]]:
-    params = (
-        {"start_time": start_time, "page[size]": page_size}
-        if start_time
-        else {"page[size]": page_size}
+def _article_to_document(article: Article, content_tags: dict[str, str]) -> Document:
+    author = BasicExpertInfo(
+        display_name=article.author.name, email=article.author.email
     )
+    update_time = time_str_to_utc(article.updated_at)
 
-    while True:
-        data = client.make_request("help_center/articles", params)
-        for article in data["articles"]:
-            yield article
-
-        if not data.get("meta", {}).get("has_more"):
-            break
-        params["page[after]"] = data["meta"]["after_cursor"]
-
-
-def _get_tickets(
-    client: ZendeskClient, start_time: int | None = None
-) -> Iterator[dict[str, Any]]:
-    params = {"start_time": start_time} if start_time else {"start_time": 0}
-
-    while True:
-        data = client.make_request("incremental/tickets.json", params)
-        for ticket in data["tickets"]:
-            yield ticket
-
-        if not data.get("end_of_stream", False):
-            params["start_time"] = data["end_time"]
-        else:
-            break
-
-
-def _fetch_author(client: ZendeskClient, author_id: str) -> BasicExpertInfo | None:
-    author_data = client.make_request(f"users/{author_id}", {})
-    user = author_data.get("user")
-    return (
-        BasicExpertInfo(display_name=user.get("name"), email=user.get("email"))
-        if user and user.get("name") and user.get("email")
-        else None
-    )
-
-
-def _article_to_document(
-    article: dict[str, Any],
-    content_tags: dict[str, str],
-    author_map: dict[str, BasicExpertInfo],
-    client: ZendeskClient,
-) -> tuple[dict[str, BasicExpertInfo] | None, Document]:
-    author_id = article.get("author_id")
-    if not author_id:
-        author = None
-    else:
-        author = (
-            author_map.get(author_id)
-            if author_id in author_map
-            else _fetch_author(client, author_id)
-        )
-
-    new_author_mapping = {author_id: author} if author_id and author else None
-
-    updated_at = article.get("updated_at")
-    update_time = time_str_to_utc(updated_at) if updated_at else None
-
-    # Build metadata
+    # build metadata
     metadata: dict[str, str | list[str]] = {
-        "labels": [str(label) for label in article.get("label_names", []) if label],
+        "labels": [str(label) for label in article.label_names if label],
         "content_tags": [
             content_tags[tag_id]
-            for tag_id in article.get("content_tag_ids", [])
+            for tag_id in article.content_tag_ids
             if tag_id in content_tags
         ],
     }
 
-    # Remove empty values
+    # remove empty values
     metadata = {k: v for k, v in metadata.items() if v}
 
-    return new_author_mapping, Document(
-        id=f"article:{article['id']}",
+    return Document(
+        id=f"article:{article.id}",
         sections=[
-            Section(
-                link=article.get("html_url"),
-                text=parse_html_page_basic(article["body"]),
-            )
+            Section(link=article.html_url, text=parse_html_page_basic(article.body))
         ],
         source=DocumentSource.ZENDESK,
-        semantic_identifier=article["title"],
+        semantic_identifier=article.title,
         doc_updated_at=update_time,
-        primary_owners=[author] if author else None,
+        primary_owners=[author],
         metadata=metadata,
     )
 
 
-def _get_comment_text(
-    comment: dict[str, Any],
-    author_map: dict[str, BasicExpertInfo],
-    client: ZendeskClient,
-) -> tuple[dict[str, BasicExpertInfo] | None, str]:
-    author_id = comment.get("author_id")
-    if not author_id:
-        author = None
-    else:
-        author = (
-            author_map.get(author_id)
-            if author_id in author_map
-            else _fetch_author(client, author_id)
-        )
-
-    new_author_mapping = {author_id: author} if author_id and author else None
-
-    comment_text = f"Comment{' by ' + author.display_name if author and author.display_name else ''}"
-    comment_text += f"{' at ' + comment['created_at'] if comment.get('created_at') else ''}:\n{comment['body']}"
-
-    return new_author_mapping, comment_text
-
-
-def _ticket_to_document(
-    ticket: dict[str, Any],
-    author_map: dict[str, BasicExpertInfo],
-    client: ZendeskClient,
-    default_subdomain: str,
-) -> tuple[dict[str, BasicExpertInfo] | None, Document]:
-    submitter_id = ticket.get("submitter")
-    if not submitter_id:
-        submitter = None
-    else:
-        submitter = (
-            author_map.get(submitter_id)
-            if submitter_id in author_map
-            else _fetch_author(client, submitter_id)
-        )
-
-    new_author_mapping = (
-        {submitter_id: submitter} if submitter_id and submitter else None
-    )
-
-    updated_at = ticket.get("updated_at")
-    update_time = time_str_to_utc(updated_at) if updated_at else None
-
-    metadata: dict[str, str | list[str]] = {}
-    if status := ticket.get("status"):
-        metadata["status"] = status
-    if priority := ticket.get("priority"):
-        metadata["priority"] = priority
-    if tags := ticket.get("tags"):
-        metadata["tags"] = tags
-    if ticket_type := ticket.get("type"):
-        metadata["ticket_type"] = ticket_type
-
-    # Fetch comments for the ticket
-    comments_data = client.make_request(f"tickets/{ticket.get('id')}/comments", {})
-    comments = comments_data.get("comments", [])
-
-    comment_texts = []
-    for comment in comments:
-        new_author_mapping, comment_text = _get_comment_text(
-            comment, author_map, client
-        )
-        if new_author_mapping:
-            author_map.update(new_author_mapping)
-        comment_texts.append(comment_text)
-
-    comments_text = "\n\n".join(comment_texts)
-
-    subject = ticket.get("subject")
-    full_text = f"Ticket Subject:\n{subject}\n\nComments:\n{comments_text}"
-
-    ticket_url = ticket.get("url")
-    subdomain = (
-        ticket_url.split("//")[1].split(".zendesk.com")[0]
-        if ticket_url
-        else default_subdomain
-    )
-
-    ticket_display_url = (
-        f"https://{subdomain}.zendesk.com/agent/tickets/{ticket.get('id')}"
-    )
-
-    return new_author_mapping, Document(
-        id=f"zendesk_ticket_{ticket['id']}",
-        sections=[Section(link=ticket_display_url, text=full_text)],
-        source=DocumentSource.ZENDESK,
-        semantic_identifier=f"Ticket #{ticket['id']}: {subject or 'No Subject'}",
-        doc_updated_at=update_time,
-        primary_owners=[submitter] if submitter else None,
-        metadata=metadata,
-    )
+class ZendeskClientNotSetUpError(PermissionError):
+    def __init__(self) -> None:
+        super().__init__("Zendesk Client is not set up, was load_credentials called?")
 
 
 class ZendeskConnector(LoadConnector, PollConnector):
@@ -264,10 +66,44 @@ class ZendeskConnector(LoadConnector, PollConnector):
         content_type: str = "articles",
     ) -> None:
         self.batch_size = batch_size
-        self.content_type = content_type
-        self.subdomain = ""
-        # Fetch all tags ahead of time
+        self.zendesk_client: Zenpy | None = None
         self.content_tags: dict[str, str] = {}
+        self.content_type = content_type
+
+    @retry(tries=3, delay=2, backoff=2)
+    def _set_content_tags(
+        self, subdomain: str, email: str, token: str, page_size: int = 30
+    ) -> None:
+        # Construct the base URL
+        base_url = f"https://{subdomain}.zendesk.com/api/v2/guide/content_tags"
+
+        # Set up authentication
+        auth = (f"{email}/token", token)
+
+        # Set up pagination parameters
+        params = {"page[size]": page_size}
+
+        try:
+            while True:
+                # Make the GET request
+                response = requests.get(base_url, auth=auth, params=params)
+
+                # Check if the request was successful
+                if response.status_code == 200:
+                    data = response.json()
+                    content_tag_list = data.get("records", [])
+                    for tag in content_tag_list:
+                        self.content_tags[tag["id"]] = tag["name"]
+
+                    # Check if there are more pages
+                    if data.get("meta", {}).get("has_more", False):
+                        params["page[after]"] = data["meta"]["after_cursor"]
+                    else:
+                        break
+                else:
+                    raise Exception(f"Error: {response.status_code}\n{response.text}")
+        except Exception as e:
+            raise Exception(f"Error fetching content tags: {str(e)}")
 
     def load_credentials(self, credentials: dict[str, Any]) -> dict[str, Any] | None:
         # Subdomain is actually the whole URL
@@ -276,23 +112,87 @@ class ZendeskConnector(LoadConnector, PollConnector):
             .replace("https://", "")
             .split(".zendesk.com")[0]
         )
-        self.subdomain = subdomain
 
-        self.client = ZendeskClient(
-            subdomain, credentials["zendesk_email"], credentials["zendesk_token"]
+        self.zendesk_client = Zenpy(
+            subdomain=subdomain,
+            email=credentials["zendesk_email"],
+            token=credentials["zendesk_token"],
+        )
+        self._set_content_tags(
+            subdomain,
+            credentials["zendesk_email"],
+            credentials["zendesk_token"],
         )
         return None
 
     def load_from_state(self) -> GenerateDocumentsOutput:
         return self.poll_source(None, None)
 
+    def _ticket_to_document(self, ticket: Ticket) -> Document:
+        if self.zendesk_client is None:
+            raise ZendeskClientNotSetUpError()
+
+        owner = None
+        if ticket.requester and ticket.requester.name and ticket.requester.email:
+            owner = [
+                BasicExpertInfo(
+                    display_name=ticket.requester.name, email=ticket.requester.email
+                )
+            ]
+        update_time = time_str_to_utc(ticket.updated_at) if ticket.updated_at else None
+
+        metadata: dict[str, str | list[str]] = {}
+        if ticket.status is not None:
+            metadata["status"] = ticket.status
+        if ticket.priority is not None:
+            metadata["priority"] = ticket.priority
+        if ticket.tags:
+            metadata["tags"] = ticket.tags
+        if ticket.type is not None:
+            metadata["ticket_type"] = ticket.type
+
+        # Fetch comments for the ticket
+        comments = self.zendesk_client.tickets.comments(ticket=ticket)
+
+        # Combine all comments into a single text
+        comments_text = "\n\n".join(
+            [
+                f"Comment{f' by {comment.author.name}' if comment.author and comment.author.name else ''}"
+                f"{f' at {comment.created_at}' if comment.created_at else ''}:\n{comment.body}"
+                for comment in comments
+                if comment.body
+            ]
+        )
+
+        # Combine ticket description and comments
+        description = (
+            ticket.description
+            if hasattr(ticket, "description") and ticket.description
+            else ""
+        )
+        full_text = f"Ticket Description:\n{description}\n\nComments:\n{comments_text}"
+
+        # Extract subdomain from ticket.url
+        subdomain = ticket.url.split("//")[1].split(".zendesk.com")[0]
+
+        # Build the html url for the ticket
+        ticket_url = f"https://{subdomain}.zendesk.com/agent/tickets/{ticket.id}"
+
+        return Document(
+            id=f"zendesk_ticket_{ticket.id}",
+            sections=[Section(link=ticket_url, text=full_text)],
+            source=DocumentSource.ZENDESK,
+            semantic_identifier=f"Ticket #{ticket.id}: {ticket.subject or 'No Subject'}",
+            doc_updated_at=update_time,
+            primary_owners=owner,
+            metadata=metadata,
+        )
+
     def poll_source(
         self, start: SecondsSinceUnixEpoch | None, end: SecondsSinceUnixEpoch | None
     ) -> GenerateDocumentsOutput:
-        if self.client is None:
-            raise ZendeskCredentialsNotSetUpError()
-
-        self.content_tags = _get_content_tag_mapping(self.client)
+        if self.zendesk_client is None:
+            raise ZendeskClientNotSetUpError()
 
         if self.content_type == "articles":
             yield from self._poll_articles(start)
@@ -304,30 +204,26 @@ class ZendeskConnector(LoadConnector, PollConnector):
     def _poll_articles(
         self, start: SecondsSinceUnixEpoch | None
     ) -> GenerateDocumentsOutput:
-        articles = _get_articles(self.client, start_time=int(start) if start else None)
-
-        # This one is built on the fly as there may be more many more authors than tags
-        author_map: dict[str, BasicExpertInfo] = {}
-
+        articles = (
+            self.zendesk_client.help_center.articles(cursor_pagination=True)  # type: ignore
+            if start is None
+            else self.zendesk_client.help_center.articles.incremental(  # type: ignore
+                start_time=int(start)
+            )
+        )
         doc_batch = []
         for article in articles:
             if (
-                article.get("body") is None
-                or article.get("draft")
+                article.body is None
+                or article.draft
                 or any(
                     label in ZENDESK_CONNECTOR_SKIP_ARTICLE_LABELS
-                    for label in article.get("label_names", [])
+                    for label in article.label_names
                 )
             ):
                 continue
 
-            new_author_map, documents = _article_to_document(
-                article, self.content_tags, author_map, self.client
-            )
-            if new_author_map:
-                author_map.update(new_author_map)
-
-            doc_batch.append(documents)
+            doc_batch.append(_article_to_document(article, self.content_tags))
             if len(doc_batch) >= self.batch_size:
                 yield doc_batch
                 doc_batch.clear()
@@ -338,14 +234,10 @@ class ZendeskConnector(LoadConnector, PollConnector):
     def _poll_tickets(
         self, start: SecondsSinceUnixEpoch | None
     ) -> GenerateDocumentsOutput:
-        if self.client is None:
-            raise ZendeskCredentialsNotSetUpError()
+        if self.zendesk_client is None:
+            raise ZendeskClientNotSetUpError()
 
-        author_map: dict[str, BasicExpertInfo] = {}
-
-        ticket_generator = _get_tickets(
-            self.client, start_time=int(start) if start else None
-        )
+        ticket_generator = self.zendesk_client.tickets.incremental(start_time=start)
 
         while True:
             doc_batch = []
@@ -354,20 +246,10 @@ class ZendeskConnector(LoadConnector, PollConnector):
                     ticket = next(ticket_generator)
 
                     # Check if the ticket status is deleted and skip it if so
-                    if ticket.get("status") == "deleted":
+                    if ticket.status == "deleted":
                         continue
 
-                    new_author_map, documents = _ticket_to_document(
-                        ticket=ticket,
-                        author_map=author_map,
-                        client=self.client,
-                        default_subdomain=self.subdomain,
-                    )
-
-                    if new_author_map:
-                        author_map.update(new_author_map)
-
-                    doc_batch.append(documents)
+                    doc_batch.append(self._ticket_to_document(ticket))
 
                     if len(doc_batch) >= self.batch_size:
                         yield doc_batch
@@ -385,6 +267,7 @@ class ZendeskConnector(LoadConnector, PollConnector):
 
 if __name__ == "__main__":
     import os
+
     import time
 
     connector = ZendeskConnector()

backend/danswer/danswerbot/slack/config.py

@@ -1,5 +1,3 @@
-import os
-
 from sqlalchemy.orm import Session
 
 from danswer.db.models import SlackBotConfig
@@ -50,16 +48,3 @@ def validate_channel_names(
                 )
 
     return cleaned_channel_names
-
-
-# Scaling configurations for multi-tenant Slack bot handling
-TENANT_LOCK_EXPIRATION = 1800  # How long a pod can hold exclusive access to a tenant before other pods can acquire it
-TENANT_HEARTBEAT_INTERVAL = (
-    15  # How often pods send heartbeats to indicate they are still processing a tenant
-)
-TENANT_HEARTBEAT_EXPIRATION = (
-    30  # How long before a tenant's heartbeat expires, allowing other pods to take over
-)
-TENANT_ACQUISITION_INTERVAL = 60  # How often pods attempt to acquire unprocessed tenants and checks for new tokens
-
-MAX_TENANTS_PER_POD = int(os.getenv("MAX_TENANTS_PER_POD", 50))

backend/danswer/danswerbot/slack/listener.py

@@ -1,34 +1,18 @@
-import asyncio
-import os
-import signal
-import sys
-import threading
 import time
 from threading import Event
-from types import FrameType
 from typing import Any
 from typing import cast
-from typing import Dict
-from typing import Set
 
-from prometheus_client import Gauge
-from prometheus_client import start_http_server
 from slack_sdk import WebClient
 from slack_sdk.socket_mode.request import SocketModeRequest
 from slack_sdk.socket_mode.response import SocketModeResponse
 
-from danswer.configs.constants import DanswerRedisLocks
 from danswer.configs.constants import MessageType
 from danswer.configs.danswerbot_configs import DANSWER_BOT_REPHRASE_MESSAGE
 from danswer.configs.danswerbot_configs import DANSWER_BOT_RESPOND_EVERY_CHANNEL
 from danswer.configs.danswerbot_configs import NOTIFY_SLACKBOT_NO_ANSWER
 from danswer.connectors.slack.utils import expert_info_from_slack_id
 from danswer.danswerbot.slack.config import get_slack_bot_config_for_channel
-from danswer.danswerbot.slack.config import MAX_TENANTS_PER_POD
-from danswer.danswerbot.slack.config import TENANT_ACQUISITION_INTERVAL
-from danswer.danswerbot.slack.config import TENANT_HEARTBEAT_EXPIRATION
-from danswer.danswerbot.slack.config import TENANT_HEARTBEAT_INTERVAL
-from danswer.danswerbot.slack.config import TENANT_LOCK_EXPIRATION
 from danswer.danswerbot.slack.constants import DISLIKE_BLOCK_ACTION_ID
 from danswer.danswerbot.slack.constants import FEEDBACK_DOC_BUTTON_BLOCK_ACTION_ID
 from danswer.danswerbot.slack.constants import FOLLOWUP_BUTTON_ACTION_ID
@@ -62,7 +46,6 @@ from danswer.danswerbot.slack.utils import remove_danswer_bot_tag
 from danswer.danswerbot.slack.utils import rephrase_slack_message
 from danswer.danswerbot.slack.utils import respond_in_thread
 from danswer.danswerbot.slack.utils import TenantSocketModeClient
-from danswer.db.engine import CURRENT_TENANT_ID_CONTEXTVAR
 from danswer.db.engine import get_all_tenant_ids
 from danswer.db.engine import get_session_with_tenant
 from danswer.db.search_settings import get_current_search_settings
@@ -70,24 +53,17 @@ from danswer.key_value_store.interface import KvKeyNotFoundError
 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.one_shot_answer.models import ThreadMessage
-from danswer.redis.redis_pool import get_redis_client
 from danswer.search.retrieval.search_runner import download_nltk_data
 from danswer.server.manage.models import SlackBotTokens
 from danswer.utils.logger import setup_logger
 from danswer.utils.variable_functionality import set_is_ee_based_on_env_variable
-from shared_configs.configs import DISALLOWED_SLACK_BOT_TENANT_LIST
+from shared_configs.configs import CURRENT_TENANT_ID_CONTEXTVAR
 from shared_configs.configs import MODEL_SERVER_HOST
 from shared_configs.configs import MODEL_SERVER_PORT
-from shared_configs.configs import POSTGRES_DEFAULT_SCHEMA
 from shared_configs.configs import SLACK_CHANNEL_ID
 
 logger = setup_logger()
 
-# Prometheus metric for HPA
-active_tenants_gauge = Gauge(
-    "active_tenants", "Number of active tenants handled by this pod"
-)
-
 # In rare cases, some users have been experiencing a massive amount of trivial messages coming through
 # to the Slack Bot with trivial messages. Adding this to avoid exploding LLM costs while we track down
 # the cause.
@@ -101,232 +77,10 @@ _SLACK_GREETINGS_TO_IGNORE = {
     ":wave:",
 }
 
-# This is always (currently) the user id of Slack's official slackbot
+# this is always (currently) the user id of Slack's official slackbot
 _OFFICIAL_SLACKBOT_USER_ID = "USLACKBOT"
 
 
-class SlackbotHandler:
-    def __init__(self) -> None:
-        logger.info("Initializing SlackbotHandler")
-        self.tenant_ids: Set[str | None] = set()
-        self.socket_clients: Dict[str | None, TenantSocketModeClient] = {}
-        self.slack_bot_tokens: Dict[str | None, SlackBotTokens] = {}
-        self.running = True
-        self.pod_id = self.get_pod_id()
-        self._shutdown_event = Event()
-        logger.info(f"Pod ID: {self.pod_id}")
-
-        # Set up signal handlers for graceful shutdown
-        signal.signal(signal.SIGTERM, self.shutdown)
-        signal.signal(signal.SIGINT, self.shutdown)
-        logger.info("Signal handlers registered")
-
-        # Start the Prometheus metrics server
-        logger.info("Starting Prometheus metrics server")
-        start_http_server(8000)
-        logger.info("Prometheus metrics server started")
-
-        # Start background threads
-        logger.info("Starting background threads")
-        self.acquire_thread = threading.Thread(
-            target=self.acquire_tenants_loop, daemon=True
-        )
-        self.heartbeat_thread = threading.Thread(
-            target=self.heartbeat_loop, daemon=True
-        )
-
-        self.acquire_thread.start()
-        self.heartbeat_thread.start()
-        logger.info("Background threads started")
-
-    def get_pod_id(self) -> str:
-        pod_id = os.environ.get("HOSTNAME", "unknown_pod")
-        logger.info(f"Retrieved pod ID: {pod_id}")
-        return pod_id
-
-    def acquire_tenants_loop(self) -> None:
-        while not self._shutdown_event.is_set():
-            try:
-                self.acquire_tenants()
-                active_tenants_gauge.set(len(self.tenant_ids))
-                logger.debug(f"Current active tenants: {len(self.tenant_ids)}")
-            except Exception as e:
-                logger.exception(f"Error in Slack acquisition: {e}")
-            self._shutdown_event.wait(timeout=TENANT_ACQUISITION_INTERVAL)
-
-    def heartbeat_loop(self) -> None:
-        while not self._shutdown_event.is_set():
-            try:
-                self.send_heartbeats()
-                logger.debug(f"Sent heartbeats for {len(self.tenant_ids)} tenants")
-            except Exception as e:
-                logger.exception(f"Error in heartbeat loop: {e}")
-            self._shutdown_event.wait(timeout=TENANT_HEARTBEAT_INTERVAL)
-
-    def acquire_tenants(self) -> None:
-        tenant_ids = get_all_tenant_ids()
-
-        for tenant_id in tenant_ids:
-            if (
-                DISALLOWED_SLACK_BOT_TENANT_LIST is not None
-                and tenant_id in DISALLOWED_SLACK_BOT_TENANT_LIST
-            ):
-                logger.debug(f"Tenant {tenant_id} is in the disallowed list, skipping")
-                continue
-
-            if tenant_id in self.tenant_ids:
-                logger.debug(f"Tenant {tenant_id} already in self.tenant_ids")
-                continue
-
-            if len(self.tenant_ids) >= MAX_TENANTS_PER_POD:
-                logger.info(
-                    f"Max tenants per pod reached ({MAX_TENANTS_PER_POD}) Not acquiring any more tenants"
-                )
-                break
-
-            redis_client = get_redis_client(tenant_id=tenant_id)
-            pod_id = self.pod_id
-            acquired = redis_client.set(
-                DanswerRedisLocks.SLACK_BOT_LOCK,
-                pod_id,
-                nx=True,
-                ex=TENANT_LOCK_EXPIRATION,
-            )
-            if not acquired:
-                logger.debug(f"Another pod holds the lock for tenant {tenant_id}")
-                continue
-
-            logger.debug(f"Acquired lock for tenant {tenant_id}")
-            self.tenant_ids.add(tenant_id)
-
-        for tenant_id in self.tenant_ids:
-            token = CURRENT_TENANT_ID_CONTEXTVAR.set(
-                tenant_id or POSTGRES_DEFAULT_SCHEMA
-            )
-            try:
-                with get_session_with_tenant(tenant_id) as db_session:
-                    try:
-                        logger.debug(
-                            f"Setting tenant ID context variable for tenant {tenant_id}"
-                        )
-                        slack_bot_tokens = fetch_tokens()
-                        logger.debug(f"Fetched Slack bot tokens for tenant {tenant_id}")
-                        logger.debug(
-                            f"Reset tenant ID context variable for tenant {tenant_id}"
-                        )
-
-                        if not slack_bot_tokens:
-                            logger.debug(
-                                f"No Slack bot token found for tenant {tenant_id}"
-                            )
-                            if tenant_id in self.socket_clients:
-                                asyncio.run(self.socket_clients[tenant_id].close())
-                                del self.socket_clients[tenant_id]
-                                del self.slack_bot_tokens[tenant_id]
-                            continue
-
-                        if (
-                            tenant_id not in self.slack_bot_tokens
-                            or slack_bot_tokens != self.slack_bot_tokens[tenant_id]
-                        ):
-                            if tenant_id in self.slack_bot_tokens:
-                                logger.info(
-                                    f"Slack Bot tokens have changed for tenant {tenant_id} - reconnecting"
-                                )
-                            else:
-                                search_settings = get_current_search_settings(
-                                    db_session
-                                )
-                                embedding_model = EmbeddingModel.from_db_model(
-                                    search_settings=search_settings,
-                                    server_host=MODEL_SERVER_HOST,
-                                    server_port=MODEL_SERVER_PORT,
-                                )
-                                warm_up_bi_encoder(embedding_model=embedding_model)
-
-                            self.slack_bot_tokens[tenant_id] = slack_bot_tokens
-
-                            if self.socket_clients.get(tenant_id):
-                                asyncio.run(self.socket_clients[tenant_id].close())
-
-                            self.start_socket_client(tenant_id, slack_bot_tokens)
-
-                    except KvKeyNotFoundError:
-                        logger.debug(f"Missing Slack Bot tokens for tenant {tenant_id}")
-                        if self.socket_clients.get(tenant_id):
-                            asyncio.run(self.socket_clients[tenant_id].close())
-                            del self.socket_clients[tenant_id]
-                            del self.slack_bot_tokens[tenant_id]
-                    except Exception as e:
-                        logger.exception(f"Error handling tenant {tenant_id}: {e}")
-            finally:
-                CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
-
-    def send_heartbeats(self) -> None:
-        current_time = int(time.time())
-        logger.debug(f"Sending heartbeats for {len(self.tenant_ids)} tenants")
-        for tenant_id in self.tenant_ids:
-            redis_client = get_redis_client(tenant_id=tenant_id)
-            heartbeat_key = (
-                f"{DanswerRedisLocks.SLACK_BOT_HEARTBEAT_PREFIX}:{self.pod_id}"
-            )
-            redis_client.set(
-                heartbeat_key, current_time, ex=TENANT_HEARTBEAT_EXPIRATION
-            )
-
-    def start_socket_client(
-        self, tenant_id: str | None, slack_bot_tokens: SlackBotTokens
-    ) -> None:
-        logger.info(f"Starting socket client for tenant {tenant_id}")
-        socket_client = _get_socket_client(slack_bot_tokens, tenant_id)
-
-        # Append the event handler
-        socket_client.socket_mode_request_listeners.append(process_slack_event)  # type: ignore
-
-        # Establish a WebSocket connection to the Socket Mode servers
-        logger.info(f"Connecting socket client for tenant {tenant_id}")
-        socket_client.connect()
-        self.socket_clients[tenant_id] = socket_client
-        logger.info(f"Started SocketModeClient for tenant {tenant_id}")
-
-    def stop_socket_clients(self) -> None:
-        logger.info(f"Stopping {len(self.socket_clients)} socket clients")
-        for tenant_id, client in self.socket_clients.items():
-            if client:
-                asyncio.run(client.close())
-                logger.info(f"Stopped SocketModeClient for tenant {tenant_id}")
-
-    def shutdown(self, signum: int | None, frame: FrameType | None) -> None:
-        if not self.running:
-            return
-
-        logger.info("Shutting down gracefully")
-        self.running = False
-        self._shutdown_event.set()
-
-        # Stop all socket clients
-        logger.info(f"Stopping {len(self.socket_clients)} socket clients")
-        self.stop_socket_clients()
-
-        # Release locks for all tenants
-        logger.info(f"Releasing locks for {len(self.tenant_ids)} tenants")
-        for tenant_id in self.tenant_ids:
-            try:
-                redis_client = get_redis_client(tenant_id=tenant_id)
-                redis_client.delete(DanswerRedisLocks.SLACK_BOT_LOCK)
-                logger.info(f"Released lock for tenant {tenant_id}")
-            except Exception as e:
-                logger.error(f"Error releasing lock for tenant {tenant_id}: {e}")
-
-        # Wait for background threads to finish (with timeout)
-        logger.info("Waiting for background threads to finish...")
-        self.acquire_thread.join(timeout=5)
-        self.heartbeat_thread.join(timeout=5)
-
-        logger.info("Shutdown complete")
-        sys.exit(0)
-
-
 def prefilter_requests(req: SocketModeRequest, client: TenantSocketModeClient) -> bool:
     """True to keep going, False to ignore this Slack request"""
     if req.type == "events_api":
@@ -418,7 +172,7 @@ def prefilter_requests(req: SocketModeRequest, client: TenantSocketModeClient) -
         message_subtype = event.get("subtype")
         if message_subtype not in [None, "file_share"]:
             channel_specific_logger.info(
-                f"Ignoring message with subtype '{message_subtype}' since it is a special message type"
+                f"Ignoring message with subtype '{message_subtype}' since is is a special message type"
             )
             return False
 
@@ -493,7 +247,7 @@ def process_feedback(req: SocketModeRequest, client: TenantSocketModeClient) ->
     )
 
     query_event_id, _, _ = decompose_action_id(feedback_id)
-    logger.info(f"Successfully handled QA feedback for event: {query_event_id}")
+    logger.notice(f"Successfully handled QA feedback for event: {query_event_id}")
 
 
 def build_request_details(
@@ -515,14 +269,14 @@ def build_request_details(
         msg = remove_danswer_bot_tag(msg, client=client.web_client)
 
         if DANSWER_BOT_REPHRASE_MESSAGE:
-            logger.info(f"Rephrasing Slack message. Original message: {msg}")
+            logger.notice(f"Rephrasing Slack message. Original message: {msg}")
             try:
                 msg = rephrase_slack_message(msg)
-                logger.info(f"Rephrased message: {msg}")
+                logger.notice(f"Rephrased message: {msg}")
             except Exception as e:
                 logger.error(f"Error while trying to rephrase the Slack message: {e}")
         else:
-            logger.info(f"Received Slack message: {msg}")
+            logger.notice(f"Received Slack message: {msg}")
 
         if tagged:
             logger.debug("User tagged DanswerBot")
@@ -723,21 +477,94 @@ def _get_socket_client(
     )
 
 
+def _initialize_socket_client(socket_client: TenantSocketModeClient) -> None:
+    socket_client.socket_mode_request_listeners.append(process_slack_event)  # type: ignore
+
+    # Establish a WebSocket connection to the Socket Mode servers
+    logger.notice(f"Listening for messages from Slack {socket_client.tenant_id }...")
+    socket_client.connect()
+
+
+# Follow the guide (https://docs.danswer.dev/slack_bot_setup) to set up
+# the slack bot in your workspace, and then add the bot to any channels you want to
+# try and answer questions for. Running this file will setup Danswer to listen to all
+# messages in those channels and attempt to answer them. As of now, it will only respond
+# to messages sent directly in the channel - it will not respond to messages sent within a
+# thread.
+#
+# NOTE: we are using Web Sockets so that you can run this from within a firewalled VPC
+# without issue.
 if __name__ == "__main__":
-    # Initialize the tenant handler which will manage tenant connections
-    logger.info("Starting SlackbotHandler")
-    tenant_handler = SlackbotHandler()
+    slack_bot_tokens: dict[str | None, SlackBotTokens] = {}
+    socket_clients: dict[str | None, TenantSocketModeClient] = {}
 
     set_is_ee_based_on_env_variable()
 
-    logger.info("Verifying query preprocessing (NLTK) data is downloaded")
+    logger.notice("Verifying query preprocessing (NLTK) data is downloaded")
     download_nltk_data()
 
-    try:
-        # Keep the main thread alive
-        while tenant_handler.running:
-            time.sleep(1)
+    while True:
+        try:
+            tenant_ids = get_all_tenant_ids()  # Function to retrieve all tenant IDs
 
-    except Exception:
-        logger.exception("Fatal error in main thread")
-        tenant_handler.shutdown(None, None)
+            for tenant_id in tenant_ids:
+                with get_session_with_tenant(tenant_id) as db_session:
+                    try:
+                        token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id or "public")
+                        latest_slack_bot_tokens = fetch_tokens()
+                        CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
+
+                        if (
+                            tenant_id not in slack_bot_tokens
+                            or latest_slack_bot_tokens != slack_bot_tokens[tenant_id]
+                        ):
+                            if tenant_id in slack_bot_tokens:
+                                logger.notice(
+                                    f"Slack Bot tokens have changed for tenant {tenant_id} - reconnecting"
+                                )
+                            else:
+                                # Initial setup for this tenant
+                                search_settings = get_current_search_settings(
+                                    db_session
+                                )
+                                embedding_model = EmbeddingModel.from_db_model(
+                                    search_settings=search_settings,
+                                    server_host=MODEL_SERVER_HOST,
+                                    server_port=MODEL_SERVER_PORT,
+                                )
+                                warm_up_bi_encoder(embedding_model=embedding_model)
+
+                            slack_bot_tokens[tenant_id] = latest_slack_bot_tokens
+
+                            # potentially may cause a message to be dropped, but it is complicated
+                            # to avoid + (1) if the user is changing tokens, they are likely okay with some
+                            # "migration downtime" and (2) if a single message is lost it is okay
+                            # as this should be a very rare occurrence
+                            if tenant_id in socket_clients:
+                                socket_clients[tenant_id].close()
+
+                            socket_client = _get_socket_client(
+                                latest_slack_bot_tokens, tenant_id
+                            )
+
+                            # Initialize socket client for this tenant. Each tenant has its own
+                            # socket client, allowing for multiple concurrent connections (one
+                            # per tenant) with the tenant ID wrapped in the socket model client.
+                            # Each `connect` stores websocket connection in a separate thread.
+                            _initialize_socket_client(socket_client)
+
+                            socket_clients[tenant_id] = socket_client
+
+                    except KvKeyNotFoundError:
+                        logger.debug(f"Missing Slack Bot tokens for tenant {tenant_id}")
+                        if tenant_id in socket_clients:
+                            socket_clients[tenant_id].disconnect()
+                            del socket_clients[tenant_id]
+                            del slack_bot_tokens[tenant_id]
+
+            # Wait before checking for updates
+            Event().wait(timeout=60)
+
+        except Exception:
+            logger.exception("An error occurred outside of main event loop")
+            time.sleep(60)

backend/danswer/db/auth.py

@@ -14,7 +14,6 @@ from sqlalchemy.orm import Session
 
 from danswer.auth.invited_users import get_invited_users
 from danswer.auth.schemas import UserRole
-from danswer.db.api_key import get_api_key_email_pattern
 from danswer.db.engine import get_async_session
 from danswer.db.engine import get_async_session_with_tenant
 from danswer.db.models import AccessToken
@@ -36,16 +35,12 @@ def get_default_admin_user_emails() -> list[str]:
     return get_default_admin_user_emails_fn()
 
 
-def get_total_users_count(db_session: Session) -> int:
+def get_total_users(db_session: Session) -> int:
     """
     Returns the total number of users in the system.
     This is the sum of users and invited users.
     """
-    user_count = (
-        db_session.query(User)
-        .filter(~User.email.endswith(get_api_key_email_pattern()))  # type: ignore
-        .count()
-    )
+    user_count = db_session.query(User).count()
     invited_users = len(get_invited_users())
     return user_count + invited_users
 

backend/danswer/db/chat.py

@@ -388,7 +388,7 @@ def get_chat_messages_by_session(
     )
 
     if prefetch_tool_calls:
-        stmt = stmt.options(joinedload(ChatMessage.tool_call))
+        stmt = stmt.options(joinedload(ChatMessage.tool_calls))
         result = db_session.scalars(stmt).unique().all()
     else:
         result = db_session.scalars(stmt).all()
@@ -474,7 +474,7 @@ def create_new_chat_message(
     alternate_assistant_id: int | None = None,
     # Maps the citation number [n] to the DB SearchDoc
     citations: dict[int, int] | None = None,
-    tool_call: ToolCall | None = None,
+    tool_calls: list[ToolCall] | None = None,
     commit: bool = True,
     reserved_message_id: int | None = None,
     overridden_model: str | None = None,
@@ -494,7 +494,7 @@ def create_new_chat_message(
         existing_message.message_type = message_type
         existing_message.citations = citations
         existing_message.files = files
-        existing_message.tool_call = tool_call
+        existing_message.tool_calls = tool_calls if tool_calls else []
         existing_message.error = error
         existing_message.alternate_assistant_id = alternate_assistant_id
         existing_message.overridden_model = overridden_model
@@ -513,7 +513,7 @@ def create_new_chat_message(
             message_type=message_type,
             citations=citations,
             files=files,
-            tool_call=tool_call,
+            tool_calls=tool_calls if tool_calls else [],
             error=error,
             alternate_assistant_id=alternate_assistant_id,
             overridden_model=overridden_model,
@@ -749,13 +749,14 @@ def translate_db_message_to_chat_message_detail(
         time_sent=chat_message.time_sent,
         citations=chat_message.citations,
         files=chat_message.files or [],
-        tool_call=ToolCallFinalResult(
-            tool_name=chat_message.tool_call.tool_name,
-            tool_args=chat_message.tool_call.tool_arguments,
-            tool_result=chat_message.tool_call.tool_result,
-        )
-        if chat_message.tool_call
-        else None,
+        tool_calls=[
+            ToolCallFinalResult(
+                tool_name=tool_call.tool_name,
+                tool_args=tool_call.tool_arguments,
+                tool_result=tool_call.tool_result,
+            )
+            for tool_call in chat_message.tool_calls
+        ],
         alternate_assistant_id=chat_message.alternate_assistant_id,
         overridden_model=chat_message.overridden_model,
     )

backend/danswer/db/connector_credential_pair.py

@@ -25,8 +25,8 @@ from danswer.db.models import UserGroup__ConnectorCredentialPair
 from danswer.db.models import UserRole
 from danswer.server.models import StatusResponse
 from danswer.utils.logger import setup_logger
-from danswer.utils.variable_functionality import fetch_ee_implementation_or_noop
-
+from ee.danswer.db.external_perm import delete_user__ext_group_for_cc_pair__no_commit
+from ee.danswer.external_permissions.sync_params import check_if_valid_sync_source
 
 logger = setup_logger()
 
@@ -351,11 +351,7 @@ def add_credential_to_connector(
         raise HTTPException(status_code=404, detail="Connector does not exist")
 
     if access_type == AccessType.SYNC:
-        if not fetch_ee_implementation_or_noop(
-            "danswer.external_permissions.sync_params",
-            "check_if_valid_sync_source",
-            noop_return_value=True,
-        )(connector.source):
+        if not check_if_valid_sync_source(connector.source):
             raise HTTPException(
                 status_code=400,
                 detail=f"Connector of type {connector.source} does not support SYNC access type",
@@ -442,10 +438,7 @@ def remove_credential_from_connector(
     )
 
     if association is not None:
-        fetch_ee_implementation_or_noop(
-            "danswer.db.external_perm",
-            "delete_user__ext_group_for_cc_pair__no_commit",
-        )(
+        delete_user__ext_group_for_cc_pair__no_commit(
             db_session=db_session,
             cc_pair_id=association.id,
         )

backend/danswer/db/credentials.py

@@ -10,7 +10,10 @@ from sqlalchemy.sql.expression import or_
 
 from danswer.auth.schemas import UserRole
 from danswer.configs.constants import DocumentSource
-from danswer.connectors.google_utils.shared_constants import (
+from danswer.connectors.gmail.constants import (
+    GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
+)
+from danswer.connectors.google_drive.constants import (
     DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY,
 )
 from danswer.db.models import ConnectorCredentialPair
@@ -421,15 +424,25 @@ def cleanup_google_drive_credentials(db_session: Session) -> None:
     db_session.commit()
 
 
-def delete_service_account_credentials(
-    user: User | None, db_session: Session, source: DocumentSource
+def delete_gmail_service_account_credentials(
+    user: User | None, db_session: Session
 ) -> None:
     credentials = fetch_credentials(db_session=db_session, user=user)
     for credential in credentials:
-        if (
-            credential.credential_json.get(DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY)
-            and credential.source == source
+        if credential.credential_json.get(
+            GMAIL_DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY
         ):
             db_session.delete(credential)
 
     db_session.commit()
+
+
+def delete_google_drive_service_account_credentials(
+    user: User | None, db_session: Session
+) -> None:
+    credentials = fetch_credentials(db_session=db_session, user=user)
+    for credential in credentials:
+        if credential.credential_json.get(DB_CREDENTIALS_DICT_SERVICE_ACCOUNT_KEY):
+            db_session.delete(credential)
+
+    db_session.commit()

backend/danswer/db/engine.py

@@ -29,7 +29,6 @@ from danswer.configs.app_configs import POSTGRES_API_SERVER_POOL_OVERFLOW
 from danswer.configs.app_configs import POSTGRES_API_SERVER_POOL_SIZE
 from danswer.configs.app_configs import POSTGRES_DB
 from danswer.configs.app_configs import POSTGRES_HOST
-from danswer.configs.app_configs import POSTGRES_IDLE_SESSIONS_TIMEOUT
 from danswer.configs.app_configs import POSTGRES_PASSWORD
 from danswer.configs.app_configs import POSTGRES_POOL_PRE_PING
 from danswer.configs.app_configs import POSTGRES_POOL_RECYCLE
@@ -38,10 +37,10 @@ from danswer.configs.app_configs import POSTGRES_USER
 from danswer.configs.app_configs import USER_AUTH_SECRET
 from danswer.configs.constants import POSTGRES_UNKNOWN_APP_NAME
 from danswer.utils.logger import setup_logger
+from shared_configs.configs import CURRENT_TENANT_ID_CONTEXTVAR
 from shared_configs.configs import MULTI_TENANT
 from shared_configs.configs import POSTGRES_DEFAULT_SCHEMA
 from shared_configs.configs import TENANT_ID_PREFIX
-from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
 
 logger = setup_logger()
 
@@ -310,12 +309,8 @@ async def get_async_session_with_tenant(
         try:
             # Set the search_path to the tenant's schema
             await session.execute(text(f'SET search_path = "{tenant_id}"'))
-            if POSTGRES_IDLE_SESSIONS_TIMEOUT:
-                await session.execute(
-                    f"SET SESSION idle_in_transaction_session_timeout = {POSTGRES_IDLE_SESSIONS_TIMEOUT}"
-                )
-        except Exception:
-            logger.exception("Error setting search_path.")
+        except Exception as e:
+            logger.error(f"Error setting search_path: {str(e)}")
             # You can choose to re-raise the exception or handle it
             # Here, we'll re-raise to prevent proceeding with an incorrect session
             raise
@@ -323,77 +318,47 @@ async def get_async_session_with_tenant(
             yield session
 
 
-@contextmanager
-def get_session_with_default_tenant() -> Generator[Session, None, None]:
-    """
-    Get a database session using the current tenant ID from the context variable.
-    """
-    tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get()
-    with get_session_with_tenant(tenant_id) as session:
-        yield session
-
-
 @contextmanager
 def get_session_with_tenant(
     tenant_id: str | None = None,
 ) -> Generator[Session, None, None]:
-    """
-    Generate a database session for a specific tenant.
-
-    This function:
-    1. Sets the database schema to the specified tenant's schema.
-    2. Preserves the tenant ID across the session.
-    3. Reverts to the previous tenant ID after the session is closed.
-    4. Uses the default schema if no tenant ID is provided.
-    """
+    """Generate a database session bound to a connection with the appropriate tenant schema set."""
     engine = get_sqlalchemy_engine()
 
-    # Store the previous tenant ID
-    previous_tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get() or POSTGRES_DEFAULT_SCHEMA
-
     if tenant_id is None:
-        tenant_id = POSTGRES_DEFAULT_SCHEMA
-
-    CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
+        tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get()
+    else:
+        CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
 
     event.listen(engine, "checkout", set_search_path_on_checkout)
 
     if not is_valid_schema_name(tenant_id):
         raise HTTPException(status_code=400, detail="Invalid tenant ID")
 
-    try:
-        # Establish a raw connection
-        with engine.connect() as connection:
-            # Access the raw DBAPI connection and set the search_path
-            dbapi_connection = connection.connection
+    # Establish a raw connection
+    with engine.connect() as connection:
+        # Access the raw DBAPI connection and set the search_path
+        dbapi_connection = connection.connection
 
-            # Set the search_path outside of any transaction
-            cursor = dbapi_connection.cursor()
+        # Set the search_path outside of any transaction
+        cursor = dbapi_connection.cursor()
+        try:
+            cursor.execute(f'SET search_path = "{tenant_id}"')
+        finally:
+            cursor.close()
+
+        # Bind the session to the connection
+        with Session(bind=connection, expire_on_commit=False) as session:
             try:
-                cursor.execute(f'SET search_path = "{tenant_id}"')
-                if POSTGRES_IDLE_SESSIONS_TIMEOUT:
-                    cursor.execute(
-                        f"SET SESSION idle_in_transaction_session_timeout = {POSTGRES_IDLE_SESSIONS_TIMEOUT}"
-                    )
+                yield session
             finally:
-                cursor.close()
-
-            # Bind the session to the connection
-            with Session(bind=connection, expire_on_commit=False) as session:
-                try:
-                    yield session
-                finally:
-                    # Reset search_path to default after the session is used
-                    if MULTI_TENANT:
-                        cursor = dbapi_connection.cursor()
-                        try:
-                            cursor.execute('SET search_path TO "$user", public')
-                        finally:
-                            cursor.close()
-
-    finally:
-        # Restore the previous tenant ID
-        CURRENT_TENANT_ID_CONTEXTVAR.set(previous_tenant_id)
+                # Reset search_path to default after the session is used
+                if MULTI_TENANT:
+                    cursor = dbapi_connection.cursor()
+                    try:
+                        cursor.execute('SET search_path TO "$user", public')
+                    finally:
+                        cursor.close()
 
 
 def set_search_path_on_checkout(

backend/danswer/db/index_attempt.py

@@ -219,7 +219,7 @@ def mark_attempt_partially_succeeded(
 
 
 def mark_attempt_failed(
-    index_attempt_id: int,
+    index_attempt: IndexAttempt,
     db_session: Session,
     failure_reason: str = "Unknown",
     full_exception_trace: str | None = None,
@@ -227,7 +227,7 @@ def mark_attempt_failed(
     try:
         attempt = db_session.execute(
             select(IndexAttempt)
-            .where(IndexAttempt.id == index_attempt_id)
+            .where(IndexAttempt.id == index_attempt.id)
             .with_for_update()
         ).scalar_one()
 

backend/danswer/db/models.py

@@ -135,9 +135,6 @@ class User(SQLAlchemyBaseUserTableUUID, Base):
     hidden_assistants: Mapped[list[int]] = mapped_column(
         postgresql.JSONB(), nullable=False, default=[]
     )
-    recent_assistants: Mapped[list[dict]] = mapped_column(
-        postgresql.JSONB(), nullable=False, default=list, server_default="[]"
-    )
 
     oidc_expiry: Mapped[datetime.datetime] = mapped_column(
         TIMESTAMPAware(timezone=True), nullable=True
@@ -737,10 +734,9 @@ class IndexAttempt(Base):
     full_exception_trace: Mapped[str | None] = mapped_column(Text, default=None)
     # Nullable because in the past, we didn't allow swapping out embedding models live
     search_settings_id: Mapped[int] = mapped_column(
-        ForeignKey("search_settings.id", ondelete="SET NULL"),
-        nullable=True,
+        ForeignKey("search_settings.id"),
+        nullable=False,
     )
-
     time_created: Mapped[datetime.datetime] = mapped_column(
         DateTime(timezone=True),
         server_default=func.now(),
@@ -760,7 +756,7 @@ class IndexAttempt(Base):
         "ConnectorCredentialPair", back_populates="index_attempts"
     )
 
-    search_settings: Mapped[SearchSettings | None] = relationship(
+    search_settings: Mapped[SearchSettings] = relationship(
         "SearchSettings", back_populates="index_attempts"
     )
 
@@ -921,15 +917,10 @@ class ToolCall(Base):
     tool_arguments: Mapped[dict[str, JSON_ro]] = mapped_column(postgresql.JSONB())
     tool_result: Mapped[JSON_ro] = mapped_column(postgresql.JSONB())
 
-    message_id: Mapped[int | None] = mapped_column(
-        ForeignKey("chat_message.id"), nullable=False
-    )
+    message_id: Mapped[int] = mapped_column(ForeignKey("chat_message.id"))
 
-    # Update the relationship
     message: Mapped["ChatMessage"] = relationship(
-        "ChatMessage",
-        back_populates="tool_call",
-        uselist=False,
+        "ChatMessage", back_populates="tool_calls"
     )
 
 
@@ -1060,13 +1051,12 @@ class ChatMessage(Base):
         secondary=ChatMessage__SearchDoc.__table__,
         back_populates="chat_messages",
     )
-
-    tool_call: Mapped["ToolCall"] = relationship(
+    # NOTE: Should always be attached to the `assistant` message.
+    # represents the tool calls used to generate this message
+    tool_calls: Mapped[list["ToolCall"]] = relationship(
         "ToolCall",
         back_populates="message",
-        uselist=False,
     )
-
     standard_answers: Mapped[list["StandardAnswer"]] = relationship(
         "StandardAnswer",
         secondary=ChatMessage__StandardAnswer.__table__,
@@ -1324,6 +1314,7 @@ class StarterMessage(TypedDict):
     in Postgres"""
 
     name: str
+    description: str
     message: str
 
 

backend/danswer/db/search_settings.py

@@ -12,7 +12,7 @@ from danswer.configs.model_configs import NORMALIZE_EMBEDDINGS
 from danswer.configs.model_configs import OLD_DEFAULT_DOCUMENT_ENCODER_MODEL
 from danswer.configs.model_configs import OLD_DEFAULT_MODEL_DOC_EMBEDDING_DIM
 from danswer.configs.model_configs import OLD_DEFAULT_MODEL_NORMALIZE_EMBEDDINGS
-from danswer.db.engine import get_session_with_default_tenant
+from danswer.db.engine import get_session_with_tenant
 from danswer.db.llm import fetch_embedding_provider
 from danswer.db.models import CloudEmbeddingProvider
 from danswer.db.models import IndexAttempt
@@ -152,7 +152,7 @@ def get_all_search_settings(db_session: Session) -> list[SearchSettings]:
 
 def get_multilingual_expansion(db_session: Session | None = None) -> list[str]:
     if db_session is None:
-        with get_session_with_default_tenant() as db_session:
+        with get_session_with_tenant() as db_session:
             search_settings = get_current_search_settings(db_session)
     else:
         search_settings = get_current_search_settings(db_session)

backend/danswer/db/swap_index.py

@@ -14,6 +14,7 @@ from danswer.db.search_settings import get_secondary_search_settings
 from danswer.db.search_settings import update_search_settings_status
 from danswer.key_value_store.factory import get_kv_store
 from danswer.utils.logger import setup_logger
+from shared_configs.configs import MULTI_TENANT
 
 
 logger = setup_logger()
@@ -22,14 +23,7 @@ logger = setup_logger()
 def check_index_swap(db_session: Session) -> SearchSettings | None:
     """Get count of cc-pairs and count of successful index_attempts for the
     new model grouped by connector + credential, if it's the same, then assume
-    new index is done building. If so, swap the indices and expire the old one.
-
-    Returns None if search settings did not change, or the old search settings if they
-    did change.
-    """
-
-    old_search_settings = None
-
+    new index is done building. If so, swap the indices and expire the old one."""
     # Default CC-pair created for Ingestion API unused here
     all_cc_pairs = get_connector_credential_pairs(db_session)
     cc_pair_count = max(len(all_cc_pairs) - 1, 0)
@@ -49,9 +43,9 @@ def check_index_swap(db_session: Session) -> SearchSettings | None:
 
     if cc_pair_count == 0 or cc_pair_count == unique_cc_indexings:
         # Swap indices
-        current_search_settings = get_current_search_settings(db_session)
+        now_old_search_settings = get_current_search_settings(db_session)
         update_search_settings_status(
-            search_settings=current_search_settings,
+            search_settings=now_old_search_settings,
             new_status=IndexModelStatus.PAST,
             db_session=db_session,
         )
@@ -73,6 +67,6 @@ def check_index_swap(db_session: Session) -> SearchSettings | None:
             for cc_pair in all_cc_pairs:
                 resync_cc_pair(cc_pair, db_session=db_session)
 
-            old_search_settings = current_search_settings
-
-    return old_search_settings
+            if MULTI_TENANT:
+                return now_old_search_settings
+    return None

backend/danswer/db/token_limit.py

@@ -1,111 +0,0 @@
-from collections.abc import Sequence
-
-from sqlalchemy import select
-from sqlalchemy.orm import Session
-
-from danswer.configs.constants import TokenRateLimitScope
-from danswer.db.models import TokenRateLimit
-from danswer.db.models import TokenRateLimit__UserGroup
-from danswer.server.token_rate_limits.models import TokenRateLimitArgs
-
-
-def fetch_all_user_token_rate_limits(
-    db_session: Session,
-    enabled_only: bool = False,
-    ordered: bool = True,
-) -> Sequence[TokenRateLimit]:
-    query = select(TokenRateLimit).where(
-        TokenRateLimit.scope == TokenRateLimitScope.USER
-    )
-
-    if enabled_only:
-        query = query.where(TokenRateLimit.enabled.is_(True))
-
-    if ordered:
-        query = query.order_by(TokenRateLimit.created_at.desc())
-
-    return db_session.scalars(query).all()
-
-
-def fetch_all_global_token_rate_limits(
-    db_session: Session,
-    enabled_only: bool = False,
-    ordered: bool = True,
-) -> Sequence[TokenRateLimit]:
-    query = select(TokenRateLimit).where(
-        TokenRateLimit.scope == TokenRateLimitScope.GLOBAL
-    )
-
-    if enabled_only:
-        query = query.where(TokenRateLimit.enabled.is_(True))
-
-    if ordered:
-        query = query.order_by(TokenRateLimit.created_at.desc())
-
-    token_rate_limits = db_session.scalars(query).all()
-    return token_rate_limits
-
-
-def insert_user_token_rate_limit(
-    db_session: Session,
-    token_rate_limit_settings: TokenRateLimitArgs,
-) -> TokenRateLimit:
-    token_limit = TokenRateLimit(
-        enabled=token_rate_limit_settings.enabled,
-        token_budget=token_rate_limit_settings.token_budget,
-        period_hours=token_rate_limit_settings.period_hours,
-        scope=TokenRateLimitScope.USER,
-    )
-    db_session.add(token_limit)
-    db_session.commit()
-
-    return token_limit
-
-
-def insert_global_token_rate_limit(
-    db_session: Session,
-    token_rate_limit_settings: TokenRateLimitArgs,
-) -> TokenRateLimit:
-    token_limit = TokenRateLimit(
-        enabled=token_rate_limit_settings.enabled,
-        token_budget=token_rate_limit_settings.token_budget,
-        period_hours=token_rate_limit_settings.period_hours,
-        scope=TokenRateLimitScope.GLOBAL,
-    )
-    db_session.add(token_limit)
-    db_session.commit()
-
-    return token_limit
-
-
-def update_token_rate_limit(
-    db_session: Session,
-    token_rate_limit_id: int,
-    token_rate_limit_settings: TokenRateLimitArgs,
-) -> TokenRateLimit:
-    token_limit = db_session.get(TokenRateLimit, token_rate_limit_id)
-    if token_limit is None:
-        raise ValueError(f"TokenRateLimit with id '{token_rate_limit_id}' not found")
-
-    token_limit.enabled = token_rate_limit_settings.enabled
-    token_limit.token_budget = token_rate_limit_settings.token_budget
-    token_limit.period_hours = token_rate_limit_settings.period_hours
-    db_session.commit()
-
-    return token_limit
-
-
-def delete_token_rate_limit(
-    db_session: Session,
-    token_rate_limit_id: int,
-) -> None:
-    token_limit = db_session.get(TokenRateLimit, token_rate_limit_id)
-    if token_limit is None:
-        raise ValueError(f"TokenRateLimit with id '{token_rate_limit_id}' not found")
-
-    db_session.query(TokenRateLimit__UserGroup).filter(
-        TokenRateLimit__UserGroup.rate_limit_id == token_rate_limit_id
-    ).delete()
-
-    db_session.delete(token_limit)
-    db_session.commit()

backend/danswer/db/tools.py

@@ -24,13 +24,6 @@ def get_tool_by_id(tool_id: int, db_session: Session) -> Tool:
     return tool
 
 
-def get_tool_by_name(tool_name: str, db_session: Session) -> Tool:
-    tool = db_session.scalar(select(Tool).where(Tool.name == tool_name))
-    if not tool:
-        raise ValueError("Tool by specified name does not exist")
-    return tool
-
-
 def create_tool(
     name: str,
     description: str | None,
@@ -44,7 +37,7 @@ def create_tool(
         description=description,
         in_code_tool_id=None,
         openapi_schema=openapi_schema,
-        custom_headers=[header.model_dump() for header in custom_headers]
+        custom_headers=[header.dict() for header in custom_headers]
         if custom_headers
         else [],
         user_id=user_id,

backend/danswer/document_index/vespa/index.py

@@ -147,7 +147,7 @@ class VespaIndex(DocumentIndex):
             return None
 
         deploy_url = f"{VESPA_APPLICATION_ENDPOINT}/tenant/default/prepareandactivate"
-        logger.notice(f"Deploying Vespa application package to {deploy_url}")
+        logger.info(f"Deploying Vespa application package to {deploy_url}")
 
         vespa_schema_path = os.path.join(
             os.getcwd(), "danswer", "document_index", "vespa", "app_config"

backend/danswer/file_store/models.py

@@ -13,7 +13,6 @@ class ChatFileType(str, Enum):
     DOC = "document"
     # Plain text only contain the text
     PLAIN_TEXT = "plain_text"
-    CSV = "csv"
 
 
 class FileDescriptor(TypedDict):

backend/danswer/file_store/utils.py

@@ -8,13 +8,12 @@ import requests
 from sqlalchemy.orm import Session
 
 from danswer.configs.constants import FileOrigin
-from danswer.db.engine import get_session_with_tenant
+from danswer.db.engine import get_session_context_manager
 from danswer.db.models import ChatMessage
 from danswer.file_store.file_store import get_default_file_store
 from danswer.file_store.models import FileDescriptor
 from danswer.file_store.models import InMemoryChatFile
 from danswer.utils.threadpool_concurrency import run_functions_tuples_in_parallel
-from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
 
 
 def load_chat_file(
@@ -53,11 +52,11 @@ def load_all_chat_files(
     return files
 
 
-def save_file_from_url(url: str, tenant_id: str) -> str:
+def save_file_from_url(url: str) -> str:
     """NOTE: using multiple sessions here, since this is often called
     using multithreading. In practice, sharing a session has resulted in
     weird errors."""
-    with get_session_with_tenant(tenant_id) as db_session:
+    with get_session_context_manager() as db_session:
         response = requests.get(url)
         response.raise_for_status()
 
@@ -76,10 +75,7 @@ def save_file_from_url(url: str, tenant_id: str) -> str:
 
 
 def save_files_from_urls(urls: list[str]) -> list[str]:
-    tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get()
-
     funcs: list[tuple[Callable[..., Any], tuple[Any, ...]]] = [
-        (save_file_from_url, (url, tenant_id)) for url in urls
+        (save_file_from_url, (url,)) for url in urls
     ]
-    # Must pass in tenant_id here, since this is called by multithreading
     return run_functions_tuples_in_parallel(funcs)

backend/danswer/key_value_store/store.py

@@ -16,9 +16,9 @@ from danswer.key_value_store.interface import KeyValueStore
 from danswer.key_value_store.interface import KvKeyNotFoundError
 from danswer.redis.redis_pool import get_redis_client
 from danswer.utils.logger import setup_logger
+from shared_configs.configs import CURRENT_TENANT_ID_CONTEXTVAR
 from shared_configs.configs import MULTI_TENANT
 from shared_configs.configs import POSTGRES_DEFAULT_SCHEMA
-from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
 
 logger = setup_logger()
 

backend/danswer/llm/answering/answer.py

@@ -1,44 +1,72 @@
+import itertools
 from collections.abc import Callable
 from collections.abc import Iterator
+from typing import Any
+from typing import cast
 from uuid import uuid4
 
 from langchain.schema.messages import BaseMessage
 from langchain_core.messages import AIMessageChunk
-from langchain_core.messages import ToolCall
+from langchain_core.messages import HumanMessage
 
+from danswer.chat.chat_utils import llm_doc_from_inference_section
 from danswer.chat.models import AnswerQuestionPossibleReturn
 from danswer.chat.models import CitationInfo
 from danswer.chat.models import DanswerAnswerPiece
+from danswer.chat.models import LlmDoc
+from danswer.chat.models import StreamStopInfo
+from danswer.chat.models import StreamStopReason
+from danswer.configs.chat_configs import QA_PROMPT_OVERRIDE
 from danswer.file_store.utils import InMemoryChatFile
-from danswer.llm.answering.llm_response_handler import LLMCall
-from danswer.llm.answering.llm_response_handler import LLMResponseHandlerManager
 from danswer.llm.answering.models import AnswerStyleConfig
 from danswer.llm.answering.models import PreviousMessage
 from danswer.llm.answering.models import PromptConfig
+from danswer.llm.answering.models import StreamProcessor
 from danswer.llm.answering.prompts.build import AnswerPromptBuilder
 from danswer.llm.answering.prompts.build import default_build_system_message
 from danswer.llm.answering.prompts.build import default_build_user_message
-from danswer.llm.answering.stream_processing.answer_response_handler import (
-    AnswerResponseHandler,
+from danswer.llm.answering.prompts.citations_prompt import (
+    build_citations_system_message,
 )
-from danswer.llm.answering.stream_processing.answer_response_handler import (
-    CitationResponseHandler,
+from danswer.llm.answering.prompts.citations_prompt import build_citations_user_message
+from danswer.llm.answering.prompts.quotes_prompt import build_quotes_user_message
+from danswer.llm.answering.stream_processing.citation_processing import (
+    build_citation_processor,
 )
-from danswer.llm.answering.stream_processing.answer_response_handler import (
-    DummyAnswerResponseHandler,
-)
-from danswer.llm.answering.stream_processing.answer_response_handler import (
-    QuotesResponseHandler,
+from danswer.llm.answering.stream_processing.quotes_processing import (
+    build_quotes_processor,
 )
+from danswer.llm.answering.stream_processing.utils import DocumentIdOrderMapping
 from danswer.llm.answering.stream_processing.utils import map_document_id_order
-from danswer.llm.answering.tool.tool_response_handler import ToolResponseHandler
 from danswer.llm.interfaces import LLM
+from danswer.llm.interfaces import ToolChoiceOptions
 from danswer.natural_language_processing.utils import get_tokenizer
+from danswer.tools.custom.custom_tool_prompt_builder import (
+    build_user_message_for_custom_tool_for_non_tool_calling_llm,
+)
+from danswer.tools.force import filter_tools_for_force_tool_use
 from danswer.tools.force import ForceUseTool
-from danswer.tools.models import ToolResponse
+from danswer.tools.images.image_generation_tool import IMAGE_GENERATION_RESPONSE_ID
+from danswer.tools.images.image_generation_tool import ImageGenerationResponse
+from danswer.tools.images.image_generation_tool import ImageGenerationTool
+from danswer.tools.images.prompt import build_image_generation_user_prompt
+from danswer.tools.internet_search.internet_search_tool import InternetSearchTool
+from danswer.tools.message import build_tool_message
+from danswer.tools.message import ToolCallSummary
+from danswer.tools.search.search_tool import FINAL_CONTEXT_DOCUMENTS_ID
+from danswer.tools.search.search_tool import SEARCH_DOC_CONTENT_ID
+from danswer.tools.search.search_tool import SEARCH_RESPONSE_SUMMARY_ID
+from danswer.tools.search.search_tool import SearchResponseSummary
+from danswer.tools.search.search_tool import SearchTool
 from danswer.tools.tool import Tool
-from danswer.tools.tool_implementations.search.search_tool import SearchTool
+from danswer.tools.tool import ToolResponse
+from danswer.tools.tool_runner import (
+    check_which_tools_should_run_for_non_tool_calling_llm,
+)
+from danswer.tools.tool_runner import ToolCallFinalResult
 from danswer.tools.tool_runner import ToolCallKickoff
+from danswer.tools.tool_runner import ToolRunner
+from danswer.tools.tool_selection import select_single_tool_for_non_tool_calling_llm
 from danswer.tools.utils import explicit_tool_calling_supported
 from danswer.utils.logger import setup_logger
 
@@ -46,9 +74,29 @@ from danswer.utils.logger import setup_logger
 logger = setup_logger()
 
 
+def _get_answer_stream_processor(
+    context_docs: list[LlmDoc],
+    doc_id_to_rank_map: DocumentIdOrderMapping,
+    answer_style_configs: AnswerStyleConfig,
+) -> StreamProcessor:
+    if answer_style_configs.citation_config:
+        return build_citation_processor(
+            context_docs=context_docs, doc_id_to_rank_map=doc_id_to_rank_map
+        )
+    if answer_style_configs.quotes_config:
+        return build_quotes_processor(
+            context_docs=context_docs, is_json_prompt=not (QA_PROMPT_OVERRIDE == "weak")
+        )
+
+    raise RuntimeError("Not implemented yet")
+
+
 AnswerStream = Iterator[AnswerQuestionPossibleReturn | ToolCallKickoff | ToolResponse]
 
 
+logger = setup_logger()
+
+
 class Answer:
     def __init__(
         self,
@@ -88,6 +136,8 @@ class Answer:
         self.tools = tools or []
         self.force_use_tool = force_use_tool
 
+        self.skip_explicit_tool_calling = skip_explicit_tool_calling
+
         self.message_history = message_history or []
         # used for QA flow where we only want to send a single message
         self.single_message_history = single_message_history
@@ -112,141 +162,335 @@ class Answer:
         self.skip_gen_ai_answer_generation = skip_gen_ai_answer_generation
         self._is_cancelled = False
 
-        self.using_tool_calling_llm = (
-            explicit_tool_calling_supported(
-                self.llm.config.model_provider, self.llm.config.model_name
+    def _update_prompt_builder_for_search_tool(
+        self, prompt_builder: AnswerPromptBuilder, final_context_documents: list[LlmDoc]
+    ) -> None:
+        if self.answer_style_config.citation_config:
+            prompt_builder.update_system_prompt(
+                build_citations_system_message(self.prompt_config)
             )
-            and not skip_explicit_tool_calling
-        )
-
-    def _get_tools_list(self) -> list[Tool]:
-        if not self.force_use_tool.force_use:
-            return self.tools
-
-        tool = next(
-            (t for t in self.tools if t.name == self.force_use_tool.tool_name), None
-        )
-        if tool is None:
-            raise RuntimeError(f"Tool '{self.force_use_tool.tool_name}' not found")
-
-        logger.info(
-            f"Forcefully using tool='{tool.name}'"
-            + (
-                f" with args='{self.force_use_tool.args}'"
-                if self.force_use_tool.args is not None
-                else ""
-            )
-        )
-        return [tool]
-
-    def _handle_specified_tool_call(
-        self, llm_calls: list[LLMCall], tool: Tool, tool_args: dict
-    ) -> AnswerStream:
-        current_llm_call = llm_calls[-1]
-
-        # make a dummy tool handler
-        tool_handler = ToolResponseHandler([tool])
-
-        dummy_tool_call_chunk = AIMessageChunk(content="")
-        dummy_tool_call_chunk.tool_calls = [
-            ToolCall(name=tool.name, args=tool_args, id=str(uuid4()))
-        ]
-
-        response_handler_manager = LLMResponseHandlerManager(
-            tool_handler, DummyAnswerResponseHandler(), self.is_cancelled
-        )
-        yield from response_handler_manager.handle_llm_response(
-            iter([dummy_tool_call_chunk])
-        )
-
-        new_llm_call = response_handler_manager.next_llm_call(current_llm_call)
-        if new_llm_call:
-            yield from self._get_response(llm_calls + [new_llm_call])
-        else:
-            raise RuntimeError("Tool call handler did not return a new LLM call")
-
-    def _get_response(self, llm_calls: list[LLMCall]) -> AnswerStream:
-        current_llm_call = llm_calls[-1]
-
-        # handle the case where no decision has to be made; we simply run the tool
-        if (
-            current_llm_call.force_use_tool.force_use
-            and current_llm_call.force_use_tool.args is not None
-        ):
-            tool_name, tool_args = (
-                current_llm_call.force_use_tool.tool_name,
-                current_llm_call.force_use_tool.args,
-            )
-            tool = next(
-                (t for t in current_llm_call.tools if t.name == tool_name), None
-            )
-            if not tool:
-                raise RuntimeError(f"Tool '{tool_name}' not found")
-
-            yield from self._handle_specified_tool_call(llm_calls, tool, tool_args)
-            return
-
-        # special pre-logic for non-tool calling LLM case
-        if not self.using_tool_calling_llm and current_llm_call.tools:
-            chosen_tool_and_args = (
-                ToolResponseHandler.get_tool_call_for_non_tool_calling_llm(
-                    current_llm_call, self.llm
+            prompt_builder.update_user_prompt(
+                build_citations_user_message(
+                    question=self.question,
+                    prompt_config=self.prompt_config,
+                    context_docs=final_context_documents,
+                    files=self.latest_query_files,
+                    all_doc_useful=(
+                        self.answer_style_config.citation_config.all_docs_useful
+                        if self.answer_style_config.citation_config
+                        else False
+                    ),
+                    history_message=self.single_message_history or "",
+                )
+            )
+        elif self.answer_style_config.quotes_config:
+            prompt_builder.update_user_prompt(
+                build_quotes_user_message(
+                    question=self.question,
+                    context_docs=final_context_documents,
+                    history_str=self.single_message_history or "",
+                    prompt=self.prompt_config,
                 )
             )
-            if chosen_tool_and_args:
-                tool, tool_args = chosen_tool_and_args
-                yield from self._handle_specified_tool_call(llm_calls, tool, tool_args)
-                return
 
-        # if we're skipping gen ai answer generation, we should break
-        # out unless we're forcing a tool call. If we don't, we might generate an
-        # answer, which is a no-no!
-        if (
-            self.skip_gen_ai_answer_generation
-            and not current_llm_call.force_use_tool.force_use
-        ):
+    def _raw_output_for_explicit_tool_calling_llms(
+        self,
+    ) -> Iterator[
+        str | StreamStopInfo | ToolCallKickoff | ToolResponse | ToolCallFinalResult
+    ]:
+        prompt_builder = AnswerPromptBuilder(self.message_history, self.llm.config)
+
+        tool_call_chunk: AIMessageChunk | None = None
+        if self.force_use_tool.force_use and self.force_use_tool.args is not None:
+            # if we are forcing a tool WITH args specified, we don't need to check which tools to run
+            # / need to generate the args
+            tool_call_chunk = AIMessageChunk(
+                content="",
+            )
+            tool_call_chunk.tool_calls = [
+                {
+                    "name": self.force_use_tool.tool_name,
+                    "args": self.force_use_tool.args,
+                    "id": str(uuid4()),
+                }
+            ]
+        else:
+            # if tool calling is supported, first try the raw message
+            # to see if we don't need to use any tools
+            prompt_builder.update_system_prompt(
+                default_build_system_message(self.prompt_config)
+            )
+            prompt_builder.update_user_prompt(
+                default_build_user_message(
+                    self.question, self.prompt_config, self.latest_query_files
+                )
+            )
+            prompt = prompt_builder.build()
+            final_tool_definitions = [
+                tool.tool_definition()
+                for tool in filter_tools_for_force_tool_use(
+                    self.tools, self.force_use_tool
+                )
+            ]
+
+            for message in self.llm.stream(
+                prompt=prompt,
+                tools=final_tool_definitions if final_tool_definitions else None,
+                tool_choice="required" if self.force_use_tool.force_use else None,
+                structured_response_format=self.answer_style_config.structured_response_format,
+            ):
+                if isinstance(message, AIMessageChunk) and (
+                    message.tool_call_chunks or message.tool_calls
+                ):
+                    if tool_call_chunk is None:
+                        tool_call_chunk = message
+                    else:
+                        tool_call_chunk += message  # type: ignore
+                else:
+                    if message.content:
+                        if self.is_cancelled:
+                            return
+                        yield cast(str, message.content)
+                    if (
+                        message.additional_kwargs.get("usage_metadata", {}).get("stop")
+                        == "length"
+                    ):
+                        yield StreamStopInfo(
+                            stop_reason=StreamStopReason.CONTEXT_LENGTH
+                        )
+
+            if not tool_call_chunk:
+                return  # no tool call needed
+
+        # if we have a tool call, we need to call the tool
+        tool_call_requests = tool_call_chunk.tool_calls
+        for tool_call_request in tool_call_requests:
+            known_tools_by_name = [
+                tool for tool in self.tools if tool.name == tool_call_request["name"]
+            ]
+
+            if not known_tools_by_name:
+                logger.error(
+                    "Tool call requested with unknown name field. \n"
+                    f"self.tools: {self.tools}"
+                    f"tool_call_request: {tool_call_request}"
+                )
+                if self.tools:
+                    tool = self.tools[0]
+                else:
+                    continue
+            else:
+                tool = known_tools_by_name[0]
+            tool_args = (
+                self.force_use_tool.args
+                if self.force_use_tool.tool_name == tool.name
+                and self.force_use_tool.args
+                else tool_call_request["args"]
+            )
+
+            tool_runner = ToolRunner(tool, tool_args)
+            yield tool_runner.kickoff()
+            yield from tool_runner.tool_responses()
+
+            tool_call_summary = ToolCallSummary(
+                tool_call_request=tool_call_chunk,
+                tool_call_result=build_tool_message(
+                    tool_call_request, tool_runner.tool_message_content()
+                ),
+            )
+
+            if tool.name in {SearchTool._NAME, InternetSearchTool._NAME}:
+                self._update_prompt_builder_for_search_tool(prompt_builder, [])
+            elif tool.name == ImageGenerationTool._NAME:
+                img_urls = [
+                    img_generation_result["url"]
+                    for img_generation_result in tool_runner.tool_final_result().tool_result
+                ]
+                prompt_builder.update_user_prompt(
+                    build_image_generation_user_prompt(
+                        query=self.question, img_urls=img_urls
+                    )
+                )
+            yield tool_runner.tool_final_result()
+            if not self.skip_gen_ai_answer_generation:
+                prompt = prompt_builder.build(tool_call_summary=tool_call_summary)
+
+                yield from self._process_llm_stream(
+                    prompt=prompt,
+                    # as of now, we don't support multiple tool calls in sequence, which is why
+                    # we don't need to pass this in here
+                    # tools=[tool.tool_definition() for tool in self.tools],
+                )
+
             return
 
-        # set up "handlers" to listen to the LLM response stream and
-        # feed back the processed results + handle tool call requests
-        # + figure out what the next LLM call should be
-        tool_call_handler = ToolResponseHandler(current_llm_call.tools)
+    # This method processes the LLM stream and yields the content or stop information
+    def _process_llm_stream(
+        self,
+        prompt: Any,
+        tools: list[dict] | None = None,
+        tool_choice: ToolChoiceOptions | None = None,
+    ) -> Iterator[str | StreamStopInfo]:
+        for message in self.llm.stream(
+            prompt=prompt,
+            tools=tools,
+            tool_choice=tool_choice,
+            structured_response_format=self.answer_style_config.structured_response_format,
+        ):
+            if isinstance(message, AIMessageChunk):
+                if message.content:
+                    if self.is_cancelled:
+                        return StreamStopInfo(stop_reason=StreamStopReason.CANCELLED)
+                    yield cast(str, message.content)
 
-        search_result = SearchTool.get_search_result(current_llm_call) or []
+            if (
+                message.additional_kwargs.get("usage_metadata", {}).get("stop")
+                == "length"
+            ):
+                yield StreamStopInfo(stop_reason=StreamStopReason.CONTEXT_LENGTH)
 
-        answer_handler: AnswerResponseHandler
-        if self.answer_style_config.citation_config:
-            answer_handler = CitationResponseHandler(
-                context_docs=search_result,
-                doc_id_to_rank_map=map_document_id_order(search_result),
+    def _raw_output_for_non_explicit_tool_calling_llms(
+        self,
+    ) -> Iterator[
+        str | StreamStopInfo | ToolCallKickoff | ToolResponse | ToolCallFinalResult
+    ]:
+        prompt_builder = AnswerPromptBuilder(self.message_history, self.llm.config)
+        chosen_tool_and_args: tuple[Tool, dict] | None = None
+
+        if self.force_use_tool.force_use:
+            # if we are forcing a tool, we don't need to check which tools to run
+            tool = next(
+                iter(
+                    [
+                        tool
+                        for tool in self.tools
+                        if tool.name == self.force_use_tool.tool_name
+                    ]
+                ),
+                None,
             )
-        elif self.answer_style_config.quotes_config:
-            answer_handler = QuotesResponseHandler(
-                context_docs=search_result,
+            if not tool:
+                raise RuntimeError(f"Tool '{self.force_use_tool.tool_name}' not found")
+
+            tool_args = (
+                self.force_use_tool.args
+                if self.force_use_tool.args is not None
+                else tool.get_args_for_non_tool_calling_llm(
+                    query=self.question,
+                    history=self.message_history,
+                    llm=self.llm,
+                    force_run=True,
+                )
+            )
+
+            if tool_args is None:
+                raise RuntimeError(f"Tool '{tool.name}' did not return args")
+
+            chosen_tool_and_args = (tool, tool_args)
+        else:
+            tool_options = check_which_tools_should_run_for_non_tool_calling_llm(
+                tools=self.tools,
+                query=self.question,
+                history=self.message_history,
+                llm=self.llm,
+            )
+
+            available_tools_and_args = [
+                (self.tools[ind], args)
+                for ind, args in enumerate(tool_options)
+                if args is not None
+            ]
+
+            logger.info(
+                f"Selecting single tool from tools: {[(tool.name, args) for tool, args in available_tools_and_args]}"
+            )
+
+            chosen_tool_and_args = (
+                select_single_tool_for_non_tool_calling_llm(
+                    tools_and_args=available_tools_and_args,
+                    history=self.message_history,
+                    query=self.question,
+                    llm=self.llm,
+                )
+                if available_tools_and_args
+                else None
+            )
+
+            logger.notice(f"Chosen tool: {chosen_tool_and_args}")
+
+        if not chosen_tool_and_args:
+            if self.skip_gen_ai_answer_generation:
+                raise ValueError(
+                    "skip_gen_ai_answer_generation is True, but no tool was chosen; no answer will be generated"
+                )
+            prompt_builder.update_system_prompt(
+                default_build_system_message(self.prompt_config)
+            )
+            prompt_builder.update_user_prompt(
+                default_build_user_message(
+                    self.question, self.prompt_config, self.latest_query_files
+                )
+            )
+            prompt = prompt_builder.build()
+            yield from self._process_llm_stream(
+                prompt=prompt,
+                tools=None,
+            )
+            return
+
+        tool, tool_args = chosen_tool_and_args
+        tool_runner = ToolRunner(tool, tool_args)
+        yield tool_runner.kickoff()
+
+        if tool.name in {SearchTool._NAME, InternetSearchTool._NAME}:
+            final_context_documents = None
+            for response in tool_runner.tool_responses():
+                if response.id == FINAL_CONTEXT_DOCUMENTS_ID:
+                    final_context_documents = cast(list[LlmDoc], response.response)
+                yield response
+
+            if final_context_documents is None:
+                raise RuntimeError(
+                    f"{tool.name} did not return final context documents"
+                )
+
+            self._update_prompt_builder_for_search_tool(
+                prompt_builder, final_context_documents
+            )
+        elif tool.name == ImageGenerationTool._NAME:
+            img_urls = []
+            for response in tool_runner.tool_responses():
+                if response.id == IMAGE_GENERATION_RESPONSE_ID:
+                    img_generation_response = cast(
+                        list[ImageGenerationResponse], response.response
+                    )
+                    img_urls = [img.url for img in img_generation_response]
+
+                yield response
+
+            prompt_builder.update_user_prompt(
+                build_image_generation_user_prompt(
+                    query=self.question,
+                    img_urls=img_urls,
+                )
             )
         else:
-            raise ValueError("No answer style config provided")
+            prompt_builder.update_user_prompt(
+                HumanMessage(
+                    content=build_user_message_for_custom_tool_for_non_tool_calling_llm(
+                        self.question,
+                        tool.name,
+                        *tool_runner.tool_responses(),
+                    )
+                )
+            )
+        final = tool_runner.tool_final_result()
 
-        response_handler_manager = LLMResponseHandlerManager(
-            tool_call_handler, answer_handler, self.is_cancelled
-        )
+        yield final
+        if not self.skip_gen_ai_answer_generation:
+            prompt = prompt_builder.build()
 
-        # DEBUG: good breakpoint
-        stream = self.llm.stream(
-            prompt=current_llm_call.prompt_builder.build(),
-            tools=[tool.tool_definition() for tool in current_llm_call.tools] or None,
-            tool_choice=(
-                "required"
-                if current_llm_call.tools and current_llm_call.force_use_tool.force_use
-                else None
-            ),
-            structured_response_format=self.answer_style_config.structured_response_format,
-        )
-        yield from response_handler_manager.handle_llm_response(stream)
-
-        new_llm_call = response_handler_manager.next_llm_call(current_llm_call)
-        if new_llm_call:
-            yield from self._get_response(llm_calls + [new_llm_call])
+            yield from self._process_llm_stream(prompt=prompt, tools=None)
 
     @property
     def processed_streamed_output(self) -> AnswerStream:
@@ -254,30 +498,94 @@ class Answer:
             yield from self._processed_stream
             return
 
-        prompt_builder = AnswerPromptBuilder(
-            user_message=default_build_user_message(
-                user_query=self.question,
-                prompt_config=self.prompt_config,
-                files=self.latest_query_files,
-            ),
-            message_history=self.message_history,
-            llm_config=self.llm.config,
-            single_message_history=self.single_message_history,
-        )
-        prompt_builder.update_system_prompt(
-            default_build_system_message(self.prompt_config)
-        )
-        llm_call = LLMCall(
-            prompt_builder=prompt_builder,
-            tools=self._get_tools_list(),
-            force_use_tool=self.force_use_tool,
-            files=self.latest_query_files,
-            tool_call_info=[],
-            using_tool_calling_llm=self.using_tool_calling_llm,
+        output_generator = (
+            self._raw_output_for_explicit_tool_calling_llms()
+            if explicit_tool_calling_supported(
+                self.llm.config.model_provider, self.llm.config.model_name
+            )
+            and not self.skip_explicit_tool_calling
+            else self._raw_output_for_non_explicit_tool_calling_llms()
         )
 
+        def _process_stream(
+            stream: Iterator[ToolCallKickoff | ToolResponse | str | StreamStopInfo],
+        ) -> AnswerStream:
+            message = None
+
+            # special things we need to keep track of for the SearchTool
+            # raw results that will be displayed to the user
+            search_results: list[LlmDoc] | None = None
+            # processed docs to feed into the LLM
+            final_context_docs: list[LlmDoc] | None = None
+
+            for message in stream:
+                if isinstance(message, ToolCallKickoff) or isinstance(
+                    message, ToolCallFinalResult
+                ):
+                    yield message
+                elif isinstance(message, ToolResponse):
+                    if message.id == SEARCH_RESPONSE_SUMMARY_ID:
+                        # We don't need to run section merging in this flow, this variable is only used
+                        # below to specify the ordering of the documents for the purpose of matching
+                        # citations to the right search documents. The deduplication logic is more lightweight
+                        # there and we don't need to do it twice
+                        search_results = [
+                            llm_doc_from_inference_section(section)
+                            for section in cast(
+                                SearchResponseSummary, message.response
+                            ).top_sections
+                        ]
+                    elif message.id == FINAL_CONTEXT_DOCUMENTS_ID:
+                        final_context_docs = cast(list[LlmDoc], message.response)
+                        yield message
+
+                    elif (
+                        message.id == SEARCH_DOC_CONTENT_ID
+                        and not self._return_contexts
+                    ):
+                        continue
+
+                    yield message
+                else:
+                    # assumes all tool responses will come first, then the final answer
+                    break
+
+            if not self.skip_gen_ai_answer_generation:
+                process_answer_stream_fn = _get_answer_stream_processor(
+                    context_docs=final_context_docs or [],
+                    # if doc selection is enabled, then search_results will be None,
+                    # so we need to use the final_context_docs
+                    doc_id_to_rank_map=map_document_id_order(
+                        search_results or final_context_docs or []
+                    ),
+                    answer_style_configs=self.answer_style_config,
+                )
+
+                stream_stop_info = None
+
+                def _stream() -> Iterator[str]:
+                    nonlocal stream_stop_info
+                    for item in itertools.chain([message], stream):
+                        if isinstance(item, StreamStopInfo):
+                            stream_stop_info = item
+                            return
+
+                        # this should never happen, but we're seeing weird behavior here so handling for now
+                        if not isinstance(item, str):
+                            logger.error(
+                                f"Received non-string item in answer stream: {item}. Skipping."
+                            )
+                            continue
+
+                        yield item
+
+                yield from process_answer_stream_fn(_stream())
+
+                if stream_stop_info:
+                    yield stream_stop_info
+
         processed_stream = []
-        for processed_packet in self._get_response([llm_call]):
+        for processed_packet in _process_stream(output_generator):
             processed_stream.append(processed_packet)
             yield processed_packet
 
@@ -301,6 +609,7 @@ class Answer:
 
         return citations
 
+    @property
     def is_cancelled(self) -> bool:
         if self._is_cancelled:
             return True

backend/danswer/llm/answering/llm_response_handler.py

@@ -1,84 +0,0 @@
-from collections.abc import Callable
-from collections.abc import Generator
-from collections.abc import Iterator
-from typing import TYPE_CHECKING
-
-from langchain_core.messages import BaseMessage
-from pydantic.v1 import BaseModel as BaseModel__v1
-
-from danswer.chat.models import CitationInfo
-from danswer.chat.models import DanswerAnswerPiece
-from danswer.chat.models import DanswerQuotes
-from danswer.chat.models import StreamStopInfo
-from danswer.chat.models import StreamStopReason
-from danswer.file_store.models import InMemoryChatFile
-from danswer.llm.answering.prompts.build import AnswerPromptBuilder
-from danswer.tools.force import ForceUseTool
-from danswer.tools.models import ToolCallFinalResult
-from danswer.tools.models import ToolCallKickoff
-from danswer.tools.models import ToolResponse
-from danswer.tools.tool import Tool
-
-
-if TYPE_CHECKING:
-    from danswer.llm.answering.stream_processing.answer_response_handler import (
-        AnswerResponseHandler,
-    )
-    from danswer.llm.answering.tool.tool_response_handler import ToolResponseHandler
-
-
-ResponsePart = (
-    DanswerAnswerPiece
-    | CitationInfo
-    | DanswerQuotes
-    | ToolCallKickoff
-    | ToolResponse
-    | ToolCallFinalResult
-    | StreamStopInfo
-)
-
-
-class LLMCall(BaseModel__v1):
-    prompt_builder: AnswerPromptBuilder
-    tools: list[Tool]
-    force_use_tool: ForceUseTool
-    files: list[InMemoryChatFile]
-    tool_call_info: list[ToolCallKickoff | ToolResponse | ToolCallFinalResult]
-    using_tool_calling_llm: bool
-
-    class Config:
-        arbitrary_types_allowed = True
-
-
-class LLMResponseHandlerManager:
-    def __init__(
-        self,
-        tool_handler: "ToolResponseHandler",
-        answer_handler: "AnswerResponseHandler",
-        is_cancelled: Callable[[], bool],
-    ):
-        self.tool_handler = tool_handler
-        self.answer_handler = answer_handler
-        self.is_cancelled = is_cancelled
-
-    def handle_llm_response(
-        self,
-        stream: Iterator[BaseMessage],
-    ) -> Generator[ResponsePart, None, None]:
-        all_messages: list[BaseMessage] = []
-        for message in stream:
-            if self.is_cancelled():
-                yield StreamStopInfo(stop_reason=StreamStopReason.CANCELLED)
-                return
-            # tool handler doesn't do anything until the full message is received
-            # NOTE: still need to run list() to get this to run
-            list(self.tool_handler.handle_response_part(message, all_messages))
-            yield from self.answer_handler.handle_response_part(message, all_messages)
-            all_messages.append(message)
-
-        # potentially give back all info on the selected tool call + its result
-        yield from self.tool_handler.handle_response_part(None, all_messages)
-        yield from self.answer_handler.handle_response_part(None, all_messages)
-
-    def next_llm_call(self, llm_call: LLMCall) -> LLMCall | None:
-        return self.tool_handler.next_llm_call(llm_call)

backend/danswer/llm/answering/models.py

@@ -33,7 +33,7 @@ class PreviousMessage(BaseModel):
     token_count: int
     message_type: MessageType
     files: list[InMemoryChatFile]
-    tool_call: ToolCallFinalResult | None
+    tool_calls: list[ToolCallFinalResult]
 
     @classmethod
     def from_chat_message(
@@ -51,13 +51,14 @@ class PreviousMessage(BaseModel):
                 for file in available_files
                 if str(file.file_id) in message_file_ids
             ],
-            tool_call=ToolCallFinalResult(
-                tool_name=chat_message.tool_call.tool_name,
-                tool_args=chat_message.tool_call.tool_arguments,
-                tool_result=chat_message.tool_call.tool_result,
-            )
-            if chat_message.tool_call
-            else None,
+            tool_calls=[
+                ToolCallFinalResult(
+                    tool_name=tool_call.tool_name,
+                    tool_args=tool_call.tool_arguments,
+                    tool_result=tool_call.tool_result,
+                )
+                for tool_call in chat_message.tool_calls
+            ],
         )
 
     def to_langchain_msg(self) -> BaseMessage:

backend/danswer/llm/answering/prompts/build.py

@@ -12,12 +12,12 @@ from danswer.llm.answering.prompts.citations_prompt import compute_max_llm_input
 from danswer.llm.interfaces import LLMConfig
 from danswer.llm.utils import build_content_with_imgs
 from danswer.llm.utils import check_message_tokens
-from danswer.llm.utils import message_to_prompt_and_imgs
 from danswer.llm.utils import translate_history_to_basemessages
 from danswer.natural_language_processing.utils import get_tokenizer
 from danswer.prompts.chat_prompts import CHAT_USER_CONTEXT_FREE_PROMPT
 from danswer.prompts.prompt_utils import add_date_time_to_prompt
 from danswer.prompts.prompt_utils import drop_messages_history_overflow
+from danswer.tools.message import ToolCallSummary
 
 
 def default_build_system_message(
@@ -54,14 +54,18 @@ def default_build_user_message(
 
 class AnswerPromptBuilder:
     def __init__(
-        self,
-        user_message: HumanMessage,
-        message_history: list[PreviousMessage],
-        llm_config: LLMConfig,
-        single_message_history: str | None = None,
+        self, message_history: list[PreviousMessage], llm_config: LLMConfig
     ) -> None:
         self.max_tokens = compute_max_llm_input_tokens(llm_config)
 
+        (
+            self.message_history,
+            self.history_token_cnts,
+        ) = translate_history_to_basemessages(message_history)
+
+        self.system_message_and_token_cnt: tuple[SystemMessage, int] | None = None
+        self.user_message_and_token_cnt: tuple[HumanMessage, int] | None = None
+
         llm_tokenizer = get_tokenizer(
             provider_type=llm_config.model_provider,
             model_name=llm_config.model_name,
@@ -70,24 +74,6 @@ class AnswerPromptBuilder:
             Callable[[str], list[int]], llm_tokenizer.encode
         )
 
-        self.raw_message_history = message_history
-        (
-            self.message_history,
-            self.history_token_cnts,
-        ) = translate_history_to_basemessages(message_history)
-
-        # for cases where like the QA flow where we want to condense the chat history
-        # into a single message rather than a sequence of User / Assistant messages
-        self.single_message_history = single_message_history
-
-        self.system_message_and_token_cnt: tuple[SystemMessage, int] | None = None
-        self.user_message_and_token_cnt = (
-            user_message,
-            check_message_tokens(user_message, self.llm_tokenizer_encode_func),
-        )
-
-        self.new_messages_and_token_cnts: list[tuple[BaseMessage, int]] = []
-
     def update_system_prompt(self, system_message: SystemMessage | None) -> None:
         if not system_message:
             self.system_message_and_token_cnt = None
@@ -99,21 +85,18 @@ class AnswerPromptBuilder:
         )
 
     def update_user_prompt(self, user_message: HumanMessage) -> None:
+        if not user_message:
+            self.user_message_and_token_cnt = None
+            return
+
         self.user_message_and_token_cnt = (
             user_message,
             check_message_tokens(user_message, self.llm_tokenizer_encode_func),
         )
 
-    def append_message(self, message: BaseMessage) -> None:
-        """Append a new message to the message history."""
-        token_count = check_message_tokens(message, self.llm_tokenizer_encode_func)
-        self.new_messages_and_token_cnts.append((message, token_count))
-
-    def get_user_message_content(self) -> str:
-        query, _ = message_to_prompt_and_imgs(self.user_message_and_token_cnt[0])
-        return query
-
-    def build(self) -> list[BaseMessage]:
+    def build(
+        self, tool_call_summary: ToolCallSummary | None = None
+    ) -> list[BaseMessage]:
         if not self.user_message_and_token_cnt:
             raise ValueError("User message must be set before building prompt")
 
@@ -130,8 +113,25 @@ class AnswerPromptBuilder:
 
         final_messages_with_tokens.append(self.user_message_and_token_cnt)
 
-        if self.new_messages_and_token_cnts:
-            final_messages_with_tokens.extend(self.new_messages_and_token_cnts)
+        if tool_call_summary:
+            final_messages_with_tokens.append(
+                (
+                    tool_call_summary.tool_call_request,
+                    check_message_tokens(
+                        tool_call_summary.tool_call_request,
+                        self.llm_tokenizer_encode_func,
+                    ),
+                )
+            )
+            final_messages_with_tokens.append(
+                (
+                    tool_call_summary.tool_call_result,
+                    check_message_tokens(
+                        tool_call_summary.tool_call_result,
+                        self.llm_tokenizer_encode_func,
+                    ),
+                )
+            )
 
         return drop_messages_history_overflow(
             final_messages_with_tokens, self.max_tokens

backend/danswer/llm/answering/prompts/citations_prompt.py

@@ -6,6 +6,7 @@ from danswer.configs.model_configs import GEN_AI_SINGLE_USER_MESSAGE_EXPECTED_MA
 from danswer.db.models import Persona
 from danswer.db.persona import get_default_prompt__read_only
 from danswer.db.search_settings import get_multilingual_expansion
+from danswer.file_store.utils import InMemoryChatFile
 from danswer.llm.answering.models import PromptConfig
 from danswer.llm.factory import get_llms_for_persona
 from danswer.llm.factory import get_main_llm_from_tuple
@@ -13,7 +14,6 @@ from danswer.llm.interfaces import LLMConfig
 from danswer.llm.utils import build_content_with_imgs
 from danswer.llm.utils import check_number_of_tokens
 from danswer.llm.utils import get_max_input_tokens
-from danswer.llm.utils import message_to_prompt_and_imgs
 from danswer.prompts.chat_prompts import REQUIRE_CITATION_STATEMENT
 from danswer.prompts.constants import DEFAULT_IGNORE_STATEMENT
 from danswer.prompts.direct_qa_prompts import CITATIONS_PROMPT
@@ -132,9 +132,10 @@ def build_citations_system_message(
 
 
 def build_citations_user_message(
-    message: HumanMessage,
+    question: str,
     prompt_config: PromptConfig,
     context_docs: list[LlmDoc] | list[InferenceChunk],
+    files: list[InMemoryChatFile],
     all_doc_useful: bool,
     history_message: str = "",
 ) -> HumanMessage:
@@ -148,7 +149,6 @@ def build_citations_user_message(
         if history_message
         else ""
     )
-    query, img_urls = message_to_prompt_and_imgs(message)
 
     if context_docs:
         context_docs_str = build_complete_context_str(context_docs)
@@ -158,22 +158,20 @@ def build_citations_user_message(
             optional_ignore_statement=optional_ignore,
             context_docs_str=context_docs_str,
             task_prompt=task_prompt_with_reminder,
-            user_query=query,
+            user_query=question,
             history_block=history_block,
         )
     else:
         # if no context docs provided, assume we're in the tool calling flow
         user_prompt = CITATIONS_PROMPT_FOR_TOOL_CALLING.format(
             task_prompt=task_prompt_with_reminder,
-            user_query=query,
+            user_query=question,
             history_block=history_block,
         )
 
     user_prompt = user_prompt.strip()
     user_msg = HumanMessage(
-        content=build_content_with_imgs(user_prompt, img_urls=img_urls)
-        if img_urls
-        else user_prompt
+        content=build_content_with_imgs(user_prompt, files) if files else user_prompt
     )
 
     return user_msg

backend/danswer/llm/answering/prompts/quotes_prompt.py

@@ -5,7 +5,6 @@ from danswer.configs.chat_configs import LANGUAGE_HINT
 from danswer.configs.chat_configs import QA_PROMPT_OVERRIDE
 from danswer.db.search_settings import get_multilingual_expansion
 from danswer.llm.answering.models import PromptConfig
-from danswer.llm.utils import message_to_prompt_and_imgs
 from danswer.prompts.direct_qa_prompts import CONTEXT_BLOCK
 from danswer.prompts.direct_qa_prompts import HISTORY_BLOCK
 from danswer.prompts.direct_qa_prompts import JSON_PROMPT
@@ -76,7 +75,7 @@ def _build_strong_llm_quotes_prompt(
 
 
 def build_quotes_user_message(
-    message: HumanMessage,
+    question: str,
     context_docs: list[LlmDoc] | list[InferenceChunk],
     history_str: str,
     prompt: PromptConfig,
@@ -87,10 +86,28 @@ def build_quotes_user_message(
         else _build_strong_llm_quotes_prompt
     )
 
-    query, _ = message_to_prompt_and_imgs(message)
-
     return prompt_builder(
-        question=query,
+        question=question,
+        context_docs=context_docs,
+        history_str=history_str,
+        prompt=prompt,
+    )
+
+
+def build_quotes_prompt(
+    question: str,
+    context_docs: list[LlmDoc] | list[InferenceChunk],
+    history_str: str,
+    prompt: PromptConfig,
+) -> HumanMessage:
+    prompt_builder = (
+        _build_weak_llm_quotes_prompt
+        if QA_PROMPT_OVERRIDE == "weak"
+        else _build_strong_llm_quotes_prompt
+    )
+
+    return prompt_builder(
+        question=question,
         context_docs=context_docs,
         history_str=history_str,
         prompt=prompt,

backend/danswer/llm/answering/prune_and_merge.py

@@ -19,7 +19,7 @@ from danswer.natural_language_processing.utils import tokenizer_trim_content
 from danswer.prompts.prompt_utils import build_doc_context_str
 from danswer.search.models import InferenceChunk
 from danswer.search.models import InferenceSection
-from danswer.tools.tool_implementations.search.search_utils import section_to_dict
+from danswer.tools.search.search_utils import section_to_dict
 from danswer.utils.logger import setup_logger
 
 

backend/danswer/llm/answering/stream_processing/answer_response_handler.py

@@ -1,91 +0,0 @@
-import abc
-from collections.abc import Generator
-
-from langchain_core.messages import BaseMessage
-
-from danswer.chat.models import CitationInfo
-from danswer.chat.models import LlmDoc
-from danswer.llm.answering.llm_response_handler import ResponsePart
-from danswer.llm.answering.stream_processing.citation_processing import (
-    CitationProcessor,
-)
-from danswer.llm.answering.stream_processing.quotes_processing import (
-    QuotesProcessor,
-)
-from danswer.llm.answering.stream_processing.utils import DocumentIdOrderMapping
-
-
-class AnswerResponseHandler(abc.ABC):
-    @abc.abstractmethod
-    def handle_response_part(
-        self,
-        response_item: BaseMessage | None,
-        previous_response_items: list[BaseMessage],
-    ) -> Generator[ResponsePart, None, None]:
-        raise NotImplementedError
-
-
-class DummyAnswerResponseHandler(AnswerResponseHandler):
-    def handle_response_part(
-        self,
-        response_item: BaseMessage | None,
-        previous_response_items: list[BaseMessage],
-    ) -> Generator[ResponsePart, None, None]:
-        # This is a dummy handler that returns nothing
-        yield from []
-
-
-class CitationResponseHandler(AnswerResponseHandler):
-    def __init__(
-        self, context_docs: list[LlmDoc], doc_id_to_rank_map: DocumentIdOrderMapping
-    ):
-        self.context_docs = context_docs
-        self.doc_id_to_rank_map = doc_id_to_rank_map
-        self.citation_processor = CitationProcessor(
-            context_docs=self.context_docs,
-            doc_id_to_rank_map=self.doc_id_to_rank_map,
-        )
-        self.processed_text = ""
-        self.citations: list[CitationInfo] = []
-
-    def handle_response_part(
-        self,
-        response_item: BaseMessage | None,
-        previous_response_items: list[BaseMessage],
-    ) -> Generator[ResponsePart, None, None]:
-        if response_item is None:
-            return
-
-        content = (
-            response_item.content if isinstance(response_item.content, str) else ""
-        )
-
-        # Process the new content through the citation processor
-        yield from self.citation_processor.process_token(content)
-
-
-class QuotesResponseHandler(AnswerResponseHandler):
-    def __init__(
-        self,
-        context_docs: list[LlmDoc],
-        is_json_prompt: bool = True,
-    ):
-        self.quotes_processor = QuotesProcessor(
-            context_docs=context_docs,
-            is_json_prompt=is_json_prompt,
-        )
-
-    def handle_response_part(
-        self,
-        response_item: BaseMessage | None,
-        previous_response_items: list[BaseMessage],
-    ) -> Generator[ResponsePart, None, None]:
-        if response_item is None:
-            yield from self.quotes_processor.process_token(None)
-            return
-
-        content = (
-            response_item.content if isinstance(response_item.content, str) else ""
-        )
-
-        yield from self.quotes_processor.process_token(content)

backend/danswer/llm/answering/stream_processing/citation_processing.py

@@ -1,10 +1,12 @@
 import re
-from collections.abc import Generator
+from collections.abc import Iterator
 
+from danswer.chat.models import AnswerQuestionStreamReturn
 from danswer.chat.models import CitationInfo
 from danswer.chat.models import DanswerAnswerPiece
 from danswer.chat.models import LlmDoc
 from danswer.configs.chat_configs import STOP_STREAM_PAT
+from danswer.llm.answering.models import StreamProcessor
 from danswer.llm.answering.stream_processing.utils import DocumentIdOrderMapping
 from danswer.prompts.constants import TRIPLE_BACKTICK
 from danswer.utils.logger import setup_logger
@@ -17,104 +19,128 @@ def in_code_block(llm_text: str) -> bool:
     return count % 2 != 0
 
 
-class CitationProcessor:
-    def __init__(
-        self,
-        context_docs: list[LlmDoc],
-        doc_id_to_rank_map: DocumentIdOrderMapping,
-        stop_stream: str | None = STOP_STREAM_PAT,
-    ):
-        self.context_docs = context_docs
-        self.doc_id_to_rank_map = doc_id_to_rank_map
-        self.stop_stream = stop_stream
-        self.order_mapping = doc_id_to_rank_map.order_mapping
-        self.llm_out = ""
-        self.max_citation_num = len(context_docs)
-        self.citation_order: list[int] = []
-        self.curr_segment = ""
-        self.cited_inds: set[int] = set()
-        self.hold = ""
-        self.current_citations: list[int] = []
-        self.past_cite_count = 0
+def extract_citations_from_stream(
+    tokens: Iterator[str],
+    context_docs: list[LlmDoc],
+    doc_id_to_rank_map: DocumentIdOrderMapping,
+    stop_stream: str | None = STOP_STREAM_PAT,
+) -> Iterator[DanswerAnswerPiece | CitationInfo]:
+    """
+    Key aspects:
 
-    def process_token(
-        self, token: str | None
-    ) -> Generator[DanswerAnswerPiece | CitationInfo, None, None]:
-        # None -> end of stream
-        if token is None:
-            yield DanswerAnswerPiece(answer_piece=self.curr_segment)
-            return
+    1. Stream Processing:
+    - Processes tokens one by one, allowing for real-time handling of large texts.
 
-        if self.stop_stream:
-            next_hold = self.hold + token
-            if self.stop_stream in next_hold:
-                return
-            if next_hold == self.stop_stream[: len(next_hold)]:
-                self.hold = next_hold
-                return
+    2. Citation Detection:
+    - Uses regex to find citations in the format [number].
+    - Example: [1], [2], etc.
+
+    3. Citation Mapping:
+    - Maps detected citation numbers to actual document ranks using doc_id_to_rank_map.
+    - Example: [1] might become [3] if doc_id_to_rank_map maps it to 3.
+
+    4. Citation Formatting:
+    - Replaces citations with properly formatted versions.
+    - Adds links if available: [[1]](https://example.com)
+    - Handles cases where links are not available: [[1]]()
+
+    5. Duplicate Handling:
+    - Skips consecutive citations of the same document to avoid redundancy.
+
+    6. Output Generation:
+    - Yields DanswerAnswerPiece objects for regular text.
+    - Yields CitationInfo objects for each unique citation encountered.
+
+    7. Context Awareness:
+    - Uses context_docs to access document information for citations.
+
+    This function effectively processes a stream of text, identifies and reformats citations,
+    and provides both the processed text and citation information as output.
+    """
+    order_mapping = doc_id_to_rank_map.order_mapping
+    llm_out = ""
+    max_citation_num = len(context_docs)
+    citation_order = []
+    curr_segment = ""
+    cited_inds = set()
+    hold = ""
+
+    raw_out = ""
+    current_citations: list[int] = []
+    past_cite_count = 0
+    for raw_token in tokens:
+        raw_out += raw_token
+        if stop_stream:
+            next_hold = hold + raw_token
+            if stop_stream in next_hold:
+                break
+            if next_hold == stop_stream[: len(next_hold)]:
+                hold = next_hold
+                continue
             token = next_hold
-            self.hold = ""
+            hold = ""
+        else:
+            token = raw_token
 
-        self.curr_segment += token
-        self.llm_out += token
+        curr_segment += token
+        llm_out += token
 
         # Handle code blocks without language tags
-        if "`" in self.curr_segment:
-            if self.curr_segment.endswith("`"):
-                return
-            elif "```" in self.curr_segment:
-                piece_that_comes_after = self.curr_segment.split("```")[1][0]
-                if piece_that_comes_after == "\n" and in_code_block(self.llm_out):
-                    self.curr_segment = self.curr_segment.replace("```", "```plaintext")
+        if "`" in curr_segment:
+            if curr_segment.endswith("`"):
+                continue
+            elif "```" in curr_segment:
+                piece_that_comes_after = curr_segment.split("```")[1][0]
+                if piece_that_comes_after == "\n" and in_code_block(llm_out):
+                    curr_segment = curr_segment.replace("```", "```plaintext")
 
         citation_pattern = r"\[(\d+)\]"
-        citations_found = list(re.finditer(citation_pattern, self.curr_segment))
+
+        citations_found = list(re.finditer(citation_pattern, curr_segment))
         possible_citation_pattern = r"(\[\d*$)"  # [1, [, etc
-        possible_citation_found = re.search(
-            possible_citation_pattern, self.curr_segment
-        )
+        possible_citation_found = re.search(possible_citation_pattern, curr_segment)
 
-        if len(citations_found) == 0 and len(self.llm_out) - self.past_cite_count > 5:
-            self.current_citations = []
+        # `past_cite_count`: number of characters since past citation
+        # 5 to ensure a citation hasn't occured
+        if len(citations_found) == 0 and len(llm_out) - past_cite_count > 5:
+            current_citations = []
 
-        result = ""  # Initialize result here
-        if citations_found and not in_code_block(self.llm_out):
+        if citations_found and not in_code_block(llm_out):
             last_citation_end = 0
             length_to_add = 0
             while len(citations_found) > 0:
                 citation = citations_found.pop(0)
                 numerical_value = int(citation.group(1))
 
-                if 1 <= numerical_value <= self.max_citation_num:
-                    context_llm_doc = self.context_docs[numerical_value - 1]
-                    real_citation_num = self.order_mapping[context_llm_doc.document_id]
+                if 1 <= numerical_value <= max_citation_num:
+                    context_llm_doc = context_docs[numerical_value - 1]
+                    real_citation_num = order_mapping[context_llm_doc.document_id]
 
-                    if real_citation_num not in self.citation_order:
-                        self.citation_order.append(real_citation_num)
+                    if real_citation_num not in citation_order:
+                        citation_order.append(real_citation_num)
 
-                    target_citation_num = (
-                        self.citation_order.index(real_citation_num) + 1
-                    )
+                    target_citation_num = citation_order.index(real_citation_num) + 1
 
                     # Skip consecutive citations of the same work
-                    if target_citation_num in self.current_citations:
+                    if target_citation_num in current_citations:
                         start, end = citation.span()
                         real_start = length_to_add + start
                         diff = end - start
-                        self.curr_segment = (
-                            self.curr_segment[: length_to_add + start]
-                            + self.curr_segment[real_start + diff :]
+                        curr_segment = (
+                            curr_segment[: length_to_add + start]
+                            + curr_segment[real_start + diff :]
                         )
                         length_to_add -= diff
                         continue
 
                     # Handle edge case where LLM outputs citation itself
-                    if self.curr_segment.startswith("[["):
-                        match = re.match(r"\[\[(\d+)\]\]", self.curr_segment)
+                    # by allowing it to generate citations on its own.
+                    if curr_segment.startswith("[["):
+                        match = re.match(r"\[\[(\d+)\]\]", curr_segment)
                         if match:
                             try:
                                 doc_id = int(match.group(1))
-                                context_llm_doc = self.context_docs[doc_id - 1]
+                                context_llm_doc = context_docs[doc_id - 1]
                                 yield CitationInfo(
                                     citation_num=target_citation_num,
                                     document_id=context_llm_doc.document_id,
@@ -124,57 +150,75 @@ class CitationProcessor:
                                     f"Manual LLM citation didn't properly cite documents {e}"
                                 )
                         else:
+                            # Will continue attempt on next loops
                             logger.warning(
                                 "Manual LLM citation wasn't able to close brackets"
                             )
+
                         continue
 
                     link = context_llm_doc.link
 
                     # Replace the citation in the current segment
                     start, end = citation.span()
-                    self.curr_segment = (
-                        self.curr_segment[: start + length_to_add]
+                    curr_segment = (
+                        curr_segment[: start + length_to_add]
                         + f"[{target_citation_num}]"
-                        + self.curr_segment[end + length_to_add :]
+                        + curr_segment[end + length_to_add :]
                     )
 
-                    self.past_cite_count = len(self.llm_out)
-                    self.current_citations.append(target_citation_num)
+                    past_cite_count = len(llm_out)
+                    current_citations.append(target_citation_num)
 
-                    if target_citation_num not in self.cited_inds:
-                        self.cited_inds.add(target_citation_num)
+                    if target_citation_num not in cited_inds:
+                        cited_inds.add(target_citation_num)
                         yield CitationInfo(
                             citation_num=target_citation_num,
                             document_id=context_llm_doc.document_id,
                         )
 
                     if link:
-                        prev_length = len(self.curr_segment)
-                        self.curr_segment = (
-                            self.curr_segment[: start + length_to_add]
+                        prev_length = len(curr_segment)
+                        curr_segment = (
+                            curr_segment[: start + length_to_add]
                             + f"[[{target_citation_num}]]({link})"
-                            + self.curr_segment[end + length_to_add :]
+                            + curr_segment[end + length_to_add :]
                         )
-                        length_to_add += len(self.curr_segment) - prev_length
+                        length_to_add += len(curr_segment) - prev_length
+
                     else:
-                        prev_length = len(self.curr_segment)
-                        self.curr_segment = (
-                            self.curr_segment[: start + length_to_add]
+                        prev_length = len(curr_segment)
+                        curr_segment = (
+                            curr_segment[: start + length_to_add]
                             + f"[[{target_citation_num}]]()"
-                            + self.curr_segment[end + length_to_add :]
+                            + curr_segment[end + length_to_add :]
                         )
-                        length_to_add += len(self.curr_segment) - prev_length
+                        length_to_add += len(curr_segment) - prev_length
 
                     last_citation_end = end + length_to_add
 
             if last_citation_end > 0:
-                result += self.curr_segment[:last_citation_end]
-                self.curr_segment = self.curr_segment[last_citation_end:]
+                yield DanswerAnswerPiece(answer_piece=curr_segment[:last_citation_end])
+                curr_segment = curr_segment[last_citation_end:]
+        if possible_citation_found:
+            continue
+        yield DanswerAnswerPiece(answer_piece=curr_segment)
+        curr_segment = ""
 
-        if not possible_citation_found:
-            result += self.curr_segment
-            self.curr_segment = ""
+    if curr_segment:
+        yield DanswerAnswerPiece(answer_piece=curr_segment)
 
-        if result:
-            yield DanswerAnswerPiece(answer_piece=result)
+
+def build_citation_processor(
+    context_docs: list[LlmDoc], doc_id_to_rank_map: DocumentIdOrderMapping
+) -> StreamProcessor:
+    def stream_processor(
+        tokens: Iterator[str],
+    ) -> AnswerQuestionStreamReturn:
+        yield from extract_citations_from_stream(
+            tokens=tokens,
+            context_docs=context_docs,
+            doc_id_to_rank_map=doc_id_to_rank_map,
+        )
+
+    return stream_processor

backend/danswer/llm/answering/stream_processing/quotes_processing.py

@@ -1,11 +1,14 @@
 import math
 import re
+from collections.abc import Callable
 from collections.abc import Generator
+from collections.abc import Iterator
 from json import JSONDecodeError
 from typing import Optional
 
 import regex
 
+from danswer.chat.models import AnswerQuestionStreamReturn
 from danswer.chat.models import DanswerAnswer
 from danswer.chat.models import DanswerAnswerPiece
 from danswer.chat.models import DanswerQuote
@@ -154,7 +157,7 @@ def separate_answer_quotes(
     return _extract_answer_quotes_freeform(clean_up_code_blocks(answer_raw))
 
 
-def _process_answer(
+def process_answer(
     answer_raw: str,
     docs: list[LlmDoc],
     is_json_prompt: bool = True,
@@ -192,7 +195,7 @@ def _stream_json_answer_end(answer_so_far: str, next_token: str) -> bool:
 def _extract_quotes_from_completed_token_stream(
     model_output: str, context_docs: list[LlmDoc], is_json_prompt: bool = True
 ) -> DanswerQuotes:
-    answer, quotes = _process_answer(model_output, context_docs, is_json_prompt)
+    answer, quotes = process_answer(model_output, context_docs, is_json_prompt)
     if answer:
         logger.notice(answer)
     elif model_output:
@@ -201,101 +204,94 @@ def _extract_quotes_from_completed_token_stream(
     return quotes
 
 
-class QuotesProcessor:
-    def __init__(
-        self,
-        context_docs: list[LlmDoc],
-        is_json_prompt: bool = True,
-    ):
-        self.context_docs = context_docs
-        self.is_json_prompt = is_json_prompt
+def process_model_tokens(
+    tokens: Iterator[str],
+    context_docs: list[LlmDoc],
+    is_json_prompt: bool = True,
+) -> Generator[DanswerAnswerPiece | DanswerQuotes, None, None]:
+    """Used in the streaming case to process the model output
+    into an Answer and Quotes
 
-        self.found_answer_start = False if is_json_prompt else True
-        self.found_answer_end = False
-        self.hold_quote = ""
-        self.model_output = ""
-        self.hold = ""
+    Yields Answer tokens back out in a dict for streaming to frontend
+    When Answer section ends, yields dict with answer_finished key
+    Collects all the tokens at the end to form the complete model output"""
+    quote_pat = f"\n{QUOTE_PAT}"
+    # Sometimes worse model outputs new line instead of :
+    quote_loose = f"\n{quote_pat[:-1]}\n"
+    # Sometime model outputs two newlines before quote section
+    quote_pat_full = f"\n{quote_pat}"
+    model_output: str = ""
+    found_answer_start = False if is_json_prompt else True
+    found_answer_end = False
+    hold_quote = ""
 
-    def process_token(
-        self, token: str | None
-    ) -> Generator[DanswerAnswerPiece | DanswerQuotes, None, None]:
-        # None -> end of stream
-        if token is None:
-            if self.model_output:
-                yield _extract_quotes_from_completed_token_stream(
-                    model_output=self.model_output,
-                    context_docs=self.context_docs,
-                    is_json_prompt=self.is_json_prompt,
-                )
-            return
+    for token in tokens:
+        model_previous = model_output
+        model_output += token
 
-        model_previous = self.model_output
-        self.model_output += token
-
-        if not self.found_answer_start:
-            m = answer_pattern.search(self.model_output)
+        if not found_answer_start:
+            m = answer_pattern.search(model_output)
             if m:
-                self.found_answer_start = True
+                found_answer_start = True
 
-                # Prevent heavy cases of hallucinations
-                if self.is_json_prompt and len(self.model_output) > 70:
+                # Prevent heavy cases of hallucinations where model is never providing a JSON
+                # We want to quickly update the user - not stream forever
+                if is_json_prompt and len(model_output) > 70:
                     logger.warning("LLM did not produce json as prompted")
-                    self.found_answer_end = True
-                    return
+                    found_answer_end = True
+                    continue
 
-                remaining = self.model_output[m.end() :]
-
-                # Look for an unescaped quote, which means the answer is entirely contained
-                # in this token e.g. if the token is `{"answer": "blah", "qu`
-                quote_indices = [i for i, char in enumerate(remaining) if char == '"']
-                for quote_idx in quote_indices:
-                    # Check if quote is escaped by counting backslashes before it
-                    num_backslashes = 0
-                    pos = quote_idx - 1
-                    while pos >= 0 and remaining[pos] == "\\":
-                        num_backslashes += 1
-                        pos -= 1
-                    # If even number of backslashes, quote is not escaped
-                    if num_backslashes % 2 == 0:
-                        yield DanswerAnswerPiece(answer_piece=remaining[:quote_idx])
-                        return
-
-                # If no unescaped quote found, yield the remaining string
+                remaining = model_output[m.end() :]
                 if len(remaining) > 0:
                     yield DanswerAnswerPiece(answer_piece=remaining)
-                return
+                continue
 
-        if self.found_answer_start and not self.found_answer_end:
-            if self.is_json_prompt and _stream_json_answer_end(model_previous, token):
-                self.found_answer_end = True
+        if found_answer_start and not found_answer_end:
+            if is_json_prompt and _stream_json_answer_end(model_previous, token):
+                found_answer_end = True
 
+                # return the remaining part of the answer e.g. token might be 'd.", ' and we should yield 'd.'
                 if token:
                     try:
                         answer_token_section = token.index('"')
                         yield DanswerAnswerPiece(
-                            answer_piece=self.hold_quote + token[:answer_token_section]
+                            answer_piece=hold_quote + token[:answer_token_section]
                         )
                     except ValueError:
                         logger.error("Quotation mark not found in token")
-                        yield DanswerAnswerPiece(answer_piece=self.hold_quote + token)
+                        yield DanswerAnswerPiece(answer_piece=hold_quote + token)
                 yield DanswerAnswerPiece(answer_piece=None)
-                return
-
-            elif not self.is_json_prompt:
-                quote_pat = f"\n{QUOTE_PAT}"
-                quote_loose = f"\n{quote_pat[:-1]}\n"
-                quote_pat_full = f"\n{quote_pat}"
-
-                if (
-                    quote_pat in self.hold_quote + token
-                    or quote_loose in self.hold_quote + token
-                ):
-                    self.found_answer_end = True
+                continue
+            elif not is_json_prompt:
+                if quote_pat in hold_quote + token or quote_loose in hold_quote + token:
+                    found_answer_end = True
                     yield DanswerAnswerPiece(answer_piece=None)
-                    return
-                if self.hold_quote + token in quote_pat_full:
-                    self.hold_quote += token
-                    return
+                    continue
+                if hold_quote + token in quote_pat_full:
+                    hold_quote += token
+                    continue
+            yield DanswerAnswerPiece(answer_piece=hold_quote + token)
+            hold_quote = ""
 
-            yield DanswerAnswerPiece(answer_piece=self.hold_quote + token)
-            self.hold_quote = ""
+    logger.debug(f"Raw Model QnA Output: {model_output}")
+
+    yield _extract_quotes_from_completed_token_stream(
+        model_output=model_output,
+        context_docs=context_docs,
+        is_json_prompt=is_json_prompt,
+    )
+
+
+def build_quotes_processor(
+    context_docs: list[LlmDoc], is_json_prompt: bool
+) -> Callable[[Iterator[str]], AnswerQuestionStreamReturn]:
+    def stream_processor(
+        tokens: Iterator[str],
+    ) -> AnswerQuestionStreamReturn:
+        yield from process_model_tokens(
+            tokens=tokens,
+            context_docs=context_docs,
+            is_json_prompt=is_json_prompt,
+        )
+
+    return stream_processor

backend/danswer/llm/answering/tool/tool_response_handler.py

@@ -1,207 +0,0 @@
-from collections.abc import Generator
-
-from langchain_core.messages import AIMessageChunk
-from langchain_core.messages import BaseMessage
-from langchain_core.messages import ToolCall
-
-from danswer.llm.answering.llm_response_handler import LLMCall
-from danswer.llm.answering.llm_response_handler import ResponsePart
-from danswer.llm.interfaces import LLM
-from danswer.tools.force import ForceUseTool
-from danswer.tools.message import build_tool_message
-from danswer.tools.message import ToolCallSummary
-from danswer.tools.models import ToolCallFinalResult
-from danswer.tools.models import ToolCallKickoff
-from danswer.tools.models import ToolResponse
-from danswer.tools.tool import Tool
-from danswer.tools.tool_runner import (
-    check_which_tools_should_run_for_non_tool_calling_llm,
-)
-from danswer.tools.tool_runner import ToolRunner
-from danswer.tools.tool_selection import select_single_tool_for_non_tool_calling_llm
-from danswer.utils.logger import setup_logger
-
-
-logger = setup_logger()
-
-
-class ToolResponseHandler:
-    def __init__(self, tools: list[Tool]):
-        self.tools = tools
-
-        self.tool_call_chunk: AIMessageChunk | None = None
-        self.tool_call_requests: list[ToolCall] = []
-
-        self.tool_runner: ToolRunner | None = None
-        self.tool_call_summary: ToolCallSummary | None = None
-
-        self.tool_kickoff: ToolCallKickoff | None = None
-        self.tool_responses: list[ToolResponse] = []
-        self.tool_final_result: ToolCallFinalResult | None = None
-
-    @classmethod
-    def get_tool_call_for_non_tool_calling_llm(
-        cls, llm_call: LLMCall, llm: LLM
-    ) -> tuple[Tool, dict] | None:
-        if llm_call.force_use_tool.force_use:
-            # if we are forcing a tool, we don't need to check which tools to run
-            tool = next(
-                (
-                    t
-                    for t in llm_call.tools
-                    if t.name == llm_call.force_use_tool.tool_name
-                ),
-                None,
-            )
-            if not tool:
-                raise RuntimeError(
-                    f"Tool '{llm_call.force_use_tool.tool_name}' not found"
-                )
-
-            tool_args = (
-                llm_call.force_use_tool.args
-                if llm_call.force_use_tool.args is not None
-                else tool.get_args_for_non_tool_calling_llm(
-                    query=llm_call.prompt_builder.get_user_message_content(),
-                    history=llm_call.prompt_builder.raw_message_history,
-                    llm=llm,
-                    force_run=True,
-                )
-            )
-
-            if tool_args is None:
-                raise RuntimeError(f"Tool '{tool.name}' did not return args")
-
-            return (tool, tool_args)
-        else:
-            tool_options = check_which_tools_should_run_for_non_tool_calling_llm(
-                tools=llm_call.tools,
-                query=llm_call.prompt_builder.get_user_message_content(),
-                history=llm_call.prompt_builder.raw_message_history,
-                llm=llm,
-            )
-
-            available_tools_and_args = [
-                (llm_call.tools[ind], args)
-                for ind, args in enumerate(tool_options)
-                if args is not None
-            ]
-
-            logger.info(
-                f"Selecting single tool from tools: {[(tool.name, args) for tool, args in available_tools_and_args]}"
-            )
-
-            chosen_tool_and_args = (
-                select_single_tool_for_non_tool_calling_llm(
-                    tools_and_args=available_tools_and_args,
-                    history=llm_call.prompt_builder.raw_message_history,
-                    query=llm_call.prompt_builder.get_user_message_content(),
-                    llm=llm,
-                )
-                if available_tools_and_args
-                else None
-            )
-
-            logger.notice(f"Chosen tool: {chosen_tool_and_args}")
-            return chosen_tool_and_args
-
-    def _handle_tool_call(self) -> Generator[ResponsePart, None, None]:
-        if not self.tool_call_chunk or not self.tool_call_chunk.tool_calls:
-            return
-
-        self.tool_call_requests = self.tool_call_chunk.tool_calls
-
-        selected_tool: Tool | None = None
-        selected_tool_call_request: ToolCall | None = None
-        for tool_call_request in self.tool_call_requests:
-            known_tools_by_name = [
-                tool for tool in self.tools if tool.name == tool_call_request["name"]
-            ]
-
-            if not known_tools_by_name:
-                logger.error(
-                    "Tool call requested with unknown name field. \n"
-                    f"self.tools: {self.tools}"
-                    f"tool_call_request: {tool_call_request}"
-                )
-                continue
-            else:
-                selected_tool = known_tools_by_name[0]
-                selected_tool_call_request = tool_call_request
-
-            if selected_tool and selected_tool_call_request:
-                break
-
-        if not selected_tool or not selected_tool_call_request:
-            return
-
-        logger.info(f"Selected tool: {selected_tool.name}")
-        logger.debug(f"Selected tool call request: {selected_tool_call_request}")
-        self.tool_runner = ToolRunner(selected_tool, selected_tool_call_request["args"])
-        self.tool_kickoff = self.tool_runner.kickoff()
-        yield self.tool_kickoff
-
-        for response in self.tool_runner.tool_responses():
-            self.tool_responses.append(response)
-            yield response
-
-        self.tool_final_result = self.tool_runner.tool_final_result()
-        yield self.tool_final_result
-
-        self.tool_call_summary = ToolCallSummary(
-            tool_call_request=self.tool_call_chunk,
-            tool_call_result=build_tool_message(
-                selected_tool_call_request, self.tool_runner.tool_message_content()
-            ),
-        )
-
-    def handle_response_part(
-        self,
-        response_item: BaseMessage | None,
-        previous_response_items: list[BaseMessage],
-    ) -> Generator[ResponsePart, None, None]:
-        if response_item is None:
-            yield from self._handle_tool_call()
-
-        if isinstance(response_item, AIMessageChunk) and (
-            response_item.tool_call_chunks or response_item.tool_calls
-        ):
-            if self.tool_call_chunk is None:
-                self.tool_call_chunk = response_item
-            else:
-                self.tool_call_chunk += response_item  # type: ignore
-
-        return
-
-    def next_llm_call(self, current_llm_call: LLMCall) -> LLMCall | None:
-        if (
-            self.tool_runner is None
-            or self.tool_call_summary is None
-            or self.tool_kickoff is None
-            or self.tool_final_result is None
-        ):
-            return None
-
-        tool_runner = self.tool_runner
-        new_prompt_builder = tool_runner.tool.build_next_prompt(
-            prompt_builder=current_llm_call.prompt_builder,
-            tool_call_summary=self.tool_call_summary,
-            tool_responses=self.tool_responses,
-            using_tool_calling_llm=current_llm_call.using_tool_calling_llm,
-        )
-        return LLMCall(
-            prompt_builder=new_prompt_builder,
-            tools=[],  # for now, only allow one tool call per response
-            force_use_tool=ForceUseTool(
-                force_use=False,
-                tool_name="",
-                args=None,
-            ),
-            files=current_llm_call.files,
-            using_tool_calling_llm=current_llm_call.using_tool_calling_llm,
-            tool_call_info=[
-                self.tool_kickoff,
-                *self.tool_responses,
-                self.tool_final_result,
-            ],
-        )

backend/danswer/llm/chat_llm.py

@@ -83,10 +83,8 @@ def _convert_litellm_message_to_langchain_message(
                     "args": json.loads(tool_call.function.arguments),
                     "id": tool_call.id,
                 }
-                for tool_call in tool_calls
-            ]
-            if tool_calls
-            else [],
+                for tool_call in (tool_calls if tool_calls else [])
+            ],
         )
     elif role == "system":
         return SystemMessage(content=content)