k

.github/CODEOWNERS

@@ -1 +0,0 @@
-* @onyx-dot-app/onyx-core-team

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

@@ -65,10 +65,8 @@ jobs:
             NEXT_PUBLIC_POSTHOG_KEY=${{ secrets.POSTHOG_KEY }}
             NEXT_PUBLIC_POSTHOG_HOST=${{ secrets.POSTHOG_HOST }}
             NEXT_PUBLIC_SENTRY_DSN=${{ secrets.SENTRY_DSN }}
-            NEXT_PUBLIC_STRIPE_PUBLISHABLE_KEY=${{ secrets.STRIPE_PUBLISHABLE_KEY }}
             NEXT_PUBLIC_GTM_ENABLED=true
             NEXT_PUBLIC_FORGOT_PASSWORD_ENABLED=true
-            NEXT_PUBLIC_INCLUDE_ERROR_POPUP_SUPPORT_LINK=true
             NODE_OPTIONS=--max-old-space-size=8192
           # needed due to weird interactions with the builds for different platforms
           no-cache: true

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

@@ -12,32 +12,7 @@ env:
   BUILDKIT_PROGRESS: plain
 
 jobs:
-  # 1) Preliminary job to check if the changed files are relevant
-  check_model_server_changes:
-    runs-on: ubuntu-latest
-    outputs:
-      changed: ${{ steps.check.outputs.changed }}
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-
-      - name: Check if relevant files changed
-        id: check
-        run: |
-          # Default to "false"
-          echo "changed=false" >> $GITHUB_OUTPUT
-
-          # Compare the previous commit (github.event.before) to the current one (github.sha)
-          # If any file in backend/model_server/** or backend/Dockerfile.model_server is changed,
-          # set changed=true
-          if git diff --name-only ${{ github.event.before }} ${{ github.sha }} \
-             | grep -E '^backend/model_server/|^backend/Dockerfile.model_server'; then
-            echo "changed=true" >> $GITHUB_OUTPUT
-          fi
-
   build-amd64:
-    needs: [check_model_server_changes]
-    if: needs.check_model_server_changes.outputs.changed == 'true'
     runs-on:
       [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-amd64"]
     steps:
@@ -77,8 +52,6 @@ jobs:
           provenance: false
 
   build-arm64:
-    needs: [check_model_server_changes]
-    if: needs.check_model_server_changes.outputs.changed == 'true'
     runs-on:
       [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-arm64"]
     steps:
@@ -118,8 +91,7 @@ jobs:
           provenance: false
 
   merge-and-scan:
-    needs: [build-amd64, build-arm64, check_model_server_changes]
-    if: needs.check_model_server_changes.outputs.changed == 'true'
+    needs: [build-amd64, build-arm64]
     runs-on: ubuntu-latest
     steps:
       - name: Login to Docker Hub

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

@@ -53,90 +53,24 @@ jobs:
           exclude: '(?i)^(pylint|aio[-_]*).*'
           
       - name: Print report
-        if: always()
+        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
 
-        # be careful enabling the sarif and upload as it may spam the security tab
-        # with a huge amount of items. Work out the issues before enabling upload.       
-#       - name: Run Trivy vulnerability scanner in repo mode
-#         if: always()
-#         uses: aquasecurity/trivy-action@0.29.0
+#       - name: Upload Trivy scan results to GitHub Security tab
+#         uses: github/codeql-action/upload-sarif@v3
 #         with:
-#           scan-type: fs
-#           scan-ref: .
-#           scanners: license
-#           format: table
-#           severity: HIGH,CRITICAL
-# #           format: sarif
-# #           output: trivy-results.sarif
-# 
-# #       - name: Upload Trivy scan results to GitHub Security tab
-# #         uses: github/codeql-action/upload-sarif@v3
-# #         with:
-# #           sarif_file: trivy-results.sarif
-
-  scan-trivy:
-    # See https://runs-on.com/runners/linux/
-    runs-on: [runs-on,runner=2cpu-linux-x64,"run-id=${{ github.run_id }}"]
-      
-    steps:
-    - 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 }}
-
-    # Backend
-    - name: Pull backend docker image
-      run: docker pull onyxdotapp/onyx-backend:latest
-
-    - name: Run Trivy vulnerability scanner on backend
-      uses: aquasecurity/trivy-action@0.29.0
-      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: onyxdotapp/onyx-backend:latest
-        scanners: license
-        severity: HIGH,CRITICAL
-        vuln-type: library
-        exit-code: 0  # Set to 1 if we want a failed scan to fail the workflow
-
-    # Web server
-    - name: Pull web server docker image
-      run: docker pull onyxdotapp/onyx-web-server:latest
-          
-    - name: Run Trivy vulnerability scanner on web server
-      uses: aquasecurity/trivy-action@0.29.0
-      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: onyxdotapp/onyx-web-server:latest
-        scanners: license
-        severity: HIGH,CRITICAL
-        vuln-type: library
-        exit-code: 0
-
-    # Model server
-    - name: Pull model server docker image
-      run: docker pull onyxdotapp/onyx-model-server:latest
-
-    - name: Run Trivy vulnerability scanner
-      uses: aquasecurity/trivy-action@0.29.0
-      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: onyxdotapp/onyx-model-server:latest
-        scanners: license
-        severity: HIGH,CRITICAL
-        vuln-type: library
-        exit-code: 0
+#           sarif_file: trivy-results.sarif

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

@@ -1,6 +1,6 @@
-name: Run Playwright Tests
+name: Run Chromatic Tests
 concurrency:
-  group: Run-Playwright-Tests-${{ github.workflow }}-${{ github.head_ref || github.event.workflow_run.head_branch || github.run_id }}
+  group: Run-Chromatic-Tests-${{ github.workflow }}-${{ github.head_ref || github.event.workflow_run.head_branch || github.run_id }}
   cancel-in-progress: true
 
 on: push
@@ -8,8 +8,6 @@ on: push
 env:
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
   SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
-  GEN_AI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-  MOCK_LLM_RESPONSE: true
 
 jobs:
   playwright-tests:
@@ -198,47 +196,43 @@ jobs:
           cd deployment/docker_compose
           docker compose -f docker-compose.dev.yml -p danswer-stack down -v
 
-# NOTE: Chromatic UI diff testing is currently disabled.
-# We are using Playwright for local and CI testing without visual regression checks.
-# Chromatic may be reintroduced in the future for UI diff testing if needed.
+  chromatic-tests:
+    name: Chromatic Tests
 
-# chromatic-tests:
-#   name: Chromatic Tests
+    needs: playwright-tests
+    runs-on:
+      [
+        runs-on,
+        runner=32cpu-linux-x64,
+        disk=large,
+        "run-id=${{ github.run_id }}",
+      ]
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
 
-#   needs: playwright-tests
-#   runs-on:
-#     [
-#       runs-on,
-#       runner=32cpu-linux-x64,
-#       disk=large,
-#       "run-id=${{ github.run_id }}",
-#     ]
-#   steps:
-#     - name: Checkout code
-#       uses: actions/checkout@v4
-#       with:
-#         fetch-depth: 0
+      - name: Setup node
+        uses: actions/setup-node@v4
+        with:
+          node-version: 22
 
-#     - name: Setup node
-#       uses: actions/setup-node@v4
-#       with:
-#         node-version: 22
+      - name: Install node dependencies
+        working-directory: ./web
+        run: npm ci
 
-#     - name: Install node dependencies
-#       working-directory: ./web
-#       run: npm ci
+      - name: Download Playwright test results
+        uses: actions/download-artifact@v4
+        with:
+          name: test-results
+          path: ./web/test-results
 
-#     - name: Download Playwright test results
-#       uses: actions/download-artifact@v4
-#       with:
-#         name: test-results
-#         path: ./web/test-results
-
-#     - name: Run Chromatic
-#       uses: chromaui/action@latest
-#       with:
-#         playwright: true
-#         projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
-#         workingDir: ./web
-#       env:
-#         CHROMATIC_ARCHIVE_LOCATION: ./test-results
+      - name: Run Chromatic
+        uses: chromaui/action@latest
+        with:
+          playwright: true
+          projectToken: ${{ secrets.CHROMATIC_PROJECT_TOKEN }}
+          workingDir: ./web
+        env:
+          CHROMATIC_ARCHIVE_LOCATION: ./test-results

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

@@ -21,10 +21,10 @@ jobs:
     - name: Set up Helm
       uses: azure/setup-helm@v4.2.0
       with:
-        version: v3.17.0
+        version: v3.14.4
       
     - name: Set up chart-testing
-      uses: helm/chart-testing-action@v2.7.0
+      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)
@@ -37,6 +37,22 @@ jobs:
           echo "changed=true" >> "$GITHUB_OUTPUT"
         fi
 
+#     rkuo: I don't think we need python?
+#     - name: Set up Python
+#       uses: actions/setup-python@v5
+#       with:
+#         python-version: '3.11'
+#         cache: 'pip'
+#         cache-dependency-path: |
+#           backend/requirements/default.txt
+#           backend/requirements/dev.txt
+#           backend/requirements/model_server.txt
+#     - run: |
+#         python -m pip install --upgrade pip
+#         pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
+#         pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
+#         pip install --retries 5 --timeout 30 -r backend/requirements/model_server.txt
+
     # lint all charts if any changes were detected
     - name: Run chart-testing (lint)
       if: steps.list-changed.outputs.changed == 'true'
@@ -46,7 +62,7 @@ jobs:
 
     - name: Create kind cluster
       if: steps.list-changed.outputs.changed == 'true'
-      uses: helm/kind-action@v1.12.0
+      uses: helm/kind-action@v1.10.0
 
     - name: Run chart-testing (install)
       if: steps.list-changed.outputs.changed == 'true'

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

@@ -94,27 +94,23 @@ jobs:
           cd deployment/docker_compose
           ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
           MULTI_TENANT=true \
-          AUTH_TYPE=cloud \
+          AUTH_TYPE=basic \
           REQUIRE_EMAIL_VERIFICATION=false \
           DISABLE_TELEMETRY=true \
           IMAGE_TAG=test \
-          DEV_MODE=true \
-          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack up -d
+          docker compose -f docker-compose.dev.yml -p danswer-stack up -d
         id: start_docker_multi_tenant
 
       # In practice, `cloud` Auth type would require OAUTH credentials to be set.
       - name: Run Multi-Tenant Integration Tests
         run: |
-          echo "Waiting for 3 minutes to ensure API server is ready..."
-          sleep 180
           echo "Running integration tests..."
-          docker run --rm --network onyx-stack_default \
+          docker run --rm --network danswer-stack_default \
             --name test-runner \
             -e POSTGRES_HOST=relational_db \
             -e POSTGRES_USER=postgres \
             -e POSTGRES_PASSWORD=password \
             -e POSTGRES_DB=postgres \
-            -e POSTGRES_USE_NULL_POOL=true \
             -e VESPA_HOST=index \
             -e REDIS_HOST=cache \
             -e API_SERVER_HOST=api_server \
@@ -123,10 +119,6 @@ jobs:
             -e TEST_WEB_HOSTNAME=test-runner \
             -e AUTH_TYPE=cloud \
             -e MULTI_TENANT=true \
-            -e REQUIRE_EMAIL_VERIFICATION=false \
-            -e DISABLE_TELEMETRY=true \
-            -e IMAGE_TAG=test \
-            -e DEV_MODE=true \
             onyxdotapp/onyx-integration:test \
             /app/tests/integration/multitenant_tests
         continue-on-error: true
@@ -134,38 +126,34 @@ jobs:
 
       - name: Check multi-tenant test results
         run: |
-          if [ ${{ steps.run_multitenant_tests.outcome }} == 'failure' ]; then
-            echo "Multi-tenant integration tests failed. Exiting with error."
+          if [ ${{ steps.run_tests.outcome }} == 'failure' ]; then
+            echo "Integration tests failed. Exiting with error."
             exit 1
           else
-            echo "All multi-tenant integration tests passed successfully."
+            echo "All integration tests passed successfully."
           fi
 
       - name: Stop multi-tenant Docker containers
         run: |
           cd deployment/docker_compose
-          docker compose -f docker-compose.multitenant-dev.yml -p onyx-stack down -v
+          docker compose -f docker-compose.dev.yml -p danswer-stack down -v
 
-      # NOTE: Use pre-ping/null pool to reduce flakiness due to dropped connections
       - name: Start Docker containers
         run: |
           cd deployment/docker_compose
           ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
           AUTH_TYPE=basic \
-          POSTGRES_POOL_PRE_PING=true \
-          POSTGRES_USE_NULL_POOL=true \
           REQUIRE_EMAIL_VERIFICATION=false \
           DISABLE_TELEMETRY=true \
           IMAGE_TAG=test \
-          INTEGRATION_TESTS_MODE=true \
-          docker compose -f docker-compose.dev.yml -p onyx-stack up -d
+          docker compose -f docker-compose.dev.yml -p danswer-stack up -d
         id: start_docker
 
       - name: Wait for service to be ready
         run: |
           echo "Starting wait-for-service script..."
 
-          docker logs -f onyx-stack-api_server-1 &
+          docker logs -f danswer-stack-api_server-1 &
 
           start_time=$(date +%s)
           timeout=300  # 5 minutes in seconds
@@ -195,24 +183,15 @@ jobs:
           done
           echo "Finished waiting for service."
 
-      - name: Start Mock Services
-        run: |
-          cd backend/tests/integration/mock_services
-          docker compose -f docker-compose.mock-it-services.yml \
-            -p mock-it-services-stack up -d
-
-      # NOTE: Use pre-ping/null to reduce flakiness due to dropped connections
       - name: Run Standard Integration Tests
         run: |
           echo "Running integration tests..."
-          docker run --rm --network onyx-stack_default \
+          docker run --rm --network danswer-stack_default \
             --name test-runner \
             -e POSTGRES_HOST=relational_db \
             -e POSTGRES_USER=postgres \
             -e POSTGRES_PASSWORD=password \
             -e POSTGRES_DB=postgres \
-            -e POSTGRES_POOL_PRE_PING=true \
-            -e POSTGRES_USE_NULL_POOL=true \
             -e VESPA_HOST=index \
             -e REDIS_HOST=cache \
             -e API_SERVER_HOST=api_server \
@@ -222,8 +201,6 @@ jobs:
             -e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
             -e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
             -e TEST_WEB_HOSTNAME=test-runner \
-            -e MOCK_CONNECTOR_SERVER_HOST=mock_connector_server \
-            -e MOCK_CONNECTOR_SERVER_PORT=8001 \
             onyxdotapp/onyx-integration:test \
             /app/tests/integration/tests \
             /app/tests/integration/connector_job_tests
@@ -239,30 +216,27 @@ jobs:
             echo "All integration tests passed successfully."
           fi
 
-      # ------------------------------------------------------------
-      # Always gather logs BEFORE "down":
-      - name: Dump API server logs
-        if: always()
+      # save before stopping the containers so the logs can be captured
+      - name: Save Docker logs
+        if: success() || failure()
         run: |
           cd deployment/docker_compose
-          docker compose -f docker-compose.dev.yml -p onyx-stack logs --no-color api_server > $GITHUB_WORKSPACE/api_server.log || true
-
-      - name: Dump all-container logs (optional)
-        if: always()
-        run: |
-          cd deployment/docker_compose
-          docker compose -f docker-compose.dev.yml -p onyx-stack logs --no-color > $GITHUB_WORKSPACE/docker-compose.log || true
-
-      - name: Upload logs
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: docker-all-logs
-          path: ${{ github.workspace }}/docker-compose.log
-      # ------------------------------------------------------------
+          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
-        if: always()
         run: |
           cd deployment/docker_compose
-          docker compose -f docker-compose.dev.yml -p onyx-stack down -v
+          docker compose -f docker-compose.dev.yml -p danswer-stack down -v
+
+      - name: Upload logs
+        if: success() || failure()
+        uses: actions/upload-artifact@v4
+        with:
+          name: docker-logs
+          path: ${{ github.workspace }}/docker-compose.log
+
+      - name: Stop Docker containers
+        run: |
+          cd deployment/docker_compose
+          docker compose -f docker-compose.dev.yml -p danswer-stack down -v

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

@@ -39,15 +39,6 @@ env:
   AIRTABLE_TEST_TABLE_ID: ${{ secrets.AIRTABLE_TEST_TABLE_ID }}
   AIRTABLE_TEST_TABLE_NAME: ${{ secrets.AIRTABLE_TEST_TABLE_NAME }}
   AIRTABLE_ACCESS_TOKEN: ${{ secrets.AIRTABLE_ACCESS_TOKEN }}
-  # Sharepoint
-  SHAREPOINT_CLIENT_ID: ${{ secrets.SHAREPOINT_CLIENT_ID }}
-  SHAREPOINT_CLIENT_SECRET: ${{ secrets.SHAREPOINT_CLIENT_SECRET }}
-  SHAREPOINT_CLIENT_DIRECTORY_ID: ${{ secrets.SHAREPOINT_CLIENT_DIRECTORY_ID }}
-  SHAREPOINT_SITE: ${{ secrets.SHAREPOINT_SITE }}
-  # Gitbook
-  GITBOOK_SPACE_ID: ${{ secrets.GITBOOK_SPACE_ID }}
-  GITBOOK_API_KEY: ${{ secrets.GITBOOK_API_KEY }}
-
 jobs:
   connectors-check:
     # See https://runs-on.com/runners/linux/
@@ -74,9 +65,7 @@ jobs:
           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
-          playwright install chromium
-          playwright install-deps chromium
-          
+
       - name: Run Tests
         shell: script -q -e -c "bash --noprofile --norc -eo pipefail {0}"
         run: py.test -o junit_family=xunit2 -xv --ff backend/tests/daily/connectors

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

@@ -1,29 +1,18 @@
-name: Model Server Tests
+name: Connector Tests
 
 on:
   schedule:
     # This cron expression runs the job daily at 16:00 UTC (9am PT)
     - cron: "0 16 * * *"
-  workflow_dispatch:
-    inputs:
-      branch:
-        description: 'Branch to run the workflow on'
-        required: false
-        default: 'main'
-        
+
 env:
   # Bedrock
   AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
   AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
   AWS_REGION_NAME: ${{ secrets.AWS_REGION_NAME }}
 
-  # API keys for testing
-  COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
-  LITELLM_API_KEY: ${{ secrets.LITELLM_API_KEY }}
-  LITELLM_API_URL: ${{ secrets.LITELLM_API_URL }}
+  # OpenAI
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-  AZURE_API_KEY: ${{ secrets.AZURE_API_KEY }}
-  AZURE_API_URL: ${{ secrets.AZURE_API_URL }}
 
 jobs:
   model-check:
@@ -37,23 +26,6 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v4
 
-      - name: Login to Docker Hub
-        uses: docker/login-action@v3
-        with:
-          username: ${{ secrets.DOCKER_USERNAME }}
-          password: ${{ secrets.DOCKER_TOKEN }}
-
-      # tag every docker image with "test" so that we can spin up the correct set
-      # of images during testing
-
-      # We don't need to build the Web Docker image since it's not yet used
-      # in the integration tests. We have a separate action to verify that it builds
-      # successfully.
-      - name: Pull Model Server Docker image
-        run: |
-          docker pull onyxdotapp/onyx-model-server:latest
-          docker tag onyxdotapp/onyx-model-server:latest onyxdotapp/onyx-model-server:test
-          
       - name: Set up Python
         uses: actions/setup-python@v5
         with:
@@ -69,49 +41,6 @@ jobs:
           pip install --retries 5 --timeout 30 -r backend/requirements/default.txt
           pip install --retries 5 --timeout 30 -r backend/requirements/dev.txt
 
-      - name: Start Docker containers
-        run: |
-          cd deployment/docker_compose
-          ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=true \
-          AUTH_TYPE=basic \
-          REQUIRE_EMAIL_VERIFICATION=false \
-          DISABLE_TELEMETRY=true \
-          IMAGE_TAG=test \
-          docker compose -f docker-compose.model-server-test.yml -p onyx-stack up -d indexing_model_server
-        id: start_docker
-
-      - name: Wait for service to be ready
-        run: |
-          echo "Starting wait-for-service script..."
-
-          start_time=$(date +%s)
-          timeout=300  # 5 minutes in seconds
-
-          while true; do
-            current_time=$(date +%s)
-            elapsed_time=$((current_time - start_time))
-            
-            if [ $elapsed_time -ge $timeout ]; then
-              echo "Timeout reached. Service did not become ready in 5 minutes."
-              exit 1
-            fi
-            
-            # Use curl with error handling to ignore specific exit code 56
-            response=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:9000/api/health || echo "curl_error")
-            
-            if [ "$response" = "200" ]; then
-              echo "Service is ready!"
-              break
-            elif [ "$response" = "curl_error" ]; then
-              echo "Curl encountered an error, possibly exit code 56. Continuing to retry..."
-            else
-              echo "Service not ready yet (HTTP status $response). Retrying in 5 seconds..."
-            fi
-            
-            sleep 5
-          done
-          echo "Finished waiting for service."
-          
       - name: Run Tests
         shell: script -q -e -c "bash --noprofile --norc -eo pipefail {0}"
         run: |
@@ -127,23 +56,3 @@ jobs:
             -H 'Content-type: application/json' \
             --data '{"text":"Scheduled Model Tests failed! Check the run at: https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}"}' \
             $SLACK_WEBHOOK
-            
-      - name: Dump all-container logs (optional)
-        if: always()
-        run: |
-          cd deployment/docker_compose
-          docker compose -f docker-compose.model-server-test.yml -p onyx-stack logs --no-color > $GITHUB_WORKSPACE/docker-compose.log || true
-
-      - name: Upload logs
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: docker-all-logs
-          path: ${{ github.workspace }}/docker-compose.log
-          
-      - name: Stop Docker containers
-        if: always()
-        run: |
-          cd deployment/docker_compose
-          docker compose -f docker-compose.model-server-test.yml -p onyx-stack down -v
-          

.gitignore

@@ -7,6 +7,4 @@
 .vscode/
 *.sw?
 /backend/tests/regression/answer_quality/search_test_config.yaml
-/web/test-results/
-backend/onyx/agent_search/main/test_data.json
-backend/tests/regression/answer_quality/test_data.json
+/web/test-results/

.vscode/env_template.txt

@@ -52,9 +52,3 @@ BING_API_KEY=<REPLACE THIS>
 # Enable the full set of Danswer Enterprise Edition features
 # NOTE: DO NOT ENABLE THIS UNLESS YOU HAVE A PAID ENTERPRISE LICENSE (or if you are using this for local testing/development)
 ENABLE_PAID_ENTERPRISE_EDITION_FEATURES=False
-
-# Agent Search configs  # TODO: Remove give proper namings
-AGENT_RETRIEVAL_STATS=False   # Note: This setting will incur substantial re-ranking effort
-AGENT_RERANKING_STATS=True
-AGENT_MAX_QUERY_RETRIEVAL_RESULTS=20
-AGENT_RERANKING_MAX_QUERY_RETRIEVAL_RESULTS=20

.vscode/launch.template.jsonc

@@ -205,7 +205,7 @@
                 "--loglevel=INFO",
                 "--hostname=light@%n",
                 "-Q",
-                "vespa_metadata_sync,connector_deletion,doc_permissions_upsert,checkpoint_cleanup",
+                "vespa_metadata_sync,connector_deletion,doc_permissions_upsert",
             ],
             "presentation": {
 				 "group": "2",

README.md

@@ -24,93 +24,112 @@
 </a>
 </p>
 
-<strong>[Onyx](https://www.onyx.app/)</strong> (formerly Danswer) is the AI platform connected to your company's docs, apps, and people.
-Onyx provides a feature rich Chat interface and plugs into any LLM of your choice.
-Keep knowledge and access controls sync-ed across over 40 connectors like Google Drive, Slack, Confluence, Salesforce, etc.
-Create custom AI agents with unique prompts, knowledge, and actions that the agents can take.
-Onyx can be deployed securely anywhere and for any scale - on a laptop, on-premise, or to cloud.
+<strong>[Onyx](https://www.onyx.app/)</strong> (formerly Danswer) is the AI Assistant connected to your company's docs, apps, and people.
+Onyx provides a Chat interface and plugs into any LLM of your choice. Onyx can be deployed anywhere and for any
+scale - on a laptop, on-premise, or to cloud. Since you own the deployment, your user data and chats are fully in your
+own control. Onyx is dual Licensed with most of it under MIT license and designed to be modular and easily extensible. The system also comes fully ready
+for production usage with user authentication, role management (admin/basic users), chat persistence, and a UI for
+configuring AI Assistants.
 
+Onyx also serves as a Enterprise Search across all common workplace tools such as Slack, Google Drive, Confluence, etc.
+By combining LLMs and team specific knowledge, Onyx becomes a subject matter expert for the team. Imagine ChatGPT if
+it had access to your team's unique knowledge! It enables questions such as "A customer wants feature X, is this already
+supported?" or "Where's the pull request for feature Y?"
 
-<h3>Feature Highlights</h3>
+<h3>Usage</h3>
 
-**Deep research over your team's knowledge:**
+Onyx Web App:
 
-https://private-user-images.githubusercontent.com/32520769/414509312-48392e83-95d0-4fb5-8650-a396e05e0a32.mp4?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.a9D8A0sgKE9AoaoE-mfFbJ6_OKYeqaf7TZ4Han2JfW8
+https://github.com/onyx-dot-app/onyx/assets/32520769/563be14c-9304-47b5-bf0a-9049c2b6f410
 
+Or, plug Onyx into your existing Slack workflows (more integrations to come 😁):
 
-**Use Onyx as a secure AI Chat with any LLM:**
-
-![Onyx Chat Silent Demo](https://github.com/onyx-dot-app/onyx/releases/download/v0.21.1/OnyxChatSilentDemo.gif)
-
-
-**Easily set up connectors to your apps:**
-
-![Onyx Connector Silent Demo](https://github.com/onyx-dot-app/onyx/releases/download/v0.21.1/OnyxConnectorSilentDemo.gif)
-
-
-**Access Onyx where your team already works:**
-
-![Onyx Bot Demo](https://github.com/onyx-dot-app/onyx/releases/download/v0.21.1/OnyxBot.png)
+https://github.com/onyx-dot-app/onyx/assets/25087905/3e19739b-d178-4371-9a38-011430bdec1b
 
+For more details on the Admin UI to manage connectors and users, check out our
+<strong><a href="https://www.youtube.com/watch?v=geNzY1nbCnU">Full Video Demo</a></strong>!
 
 ## Deployment
-**To try it out for free and get started in seconds, check out [Onyx Cloud](https://cloud.onyx.app/signup)**.
 
-Onyx can also be run locally (even on a laptop) or deployed on a virtual machine with a single
+Onyx can easily be run locally (even on a laptop) or deployed on a virtual machine with a single
 `docker compose` command. Checkout our [docs](https://docs.onyx.app/quickstart) to learn more.
 
-We also have built-in support for high-availability/scalable deployment on Kubernetes.
-References [here](https://github.com/onyx-dot-app/onyx/tree/main/deployment).
+We also have built-in support for deployment on Kubernetes. Files for that can be found [here](https://github.com/onyx-dot-app/onyx/tree/main/deployment/kubernetes).
 
+## 💃 Main Features
 
-## 🔍 Other Notable Benefits of Onyx
-- Custom deep learning models for indexing and inference time, only through Onyx + learning from user feedback.
-- Flexible security features like SSO (OIDC/SAML/OAuth2), RBAC, encryption of credentials, etc.
-- Knowledge curation features like document-sets, query history, usage analytics, etc.
-- Scalable deployment options tested up to many tens of thousands users and hundreds of millions of documents.
-
+- Chat UI with the ability to select documents to chat with.
+- Create custom AI Assistants with different prompts and backing knowledge sets.
+- Connect Onyx with LLM of your choice (self-host for a fully airgapped solution).
+- Document Search + AI Answers for natural language queries.
+- Connectors to all common workplace tools like Google Drive, Confluence, Slack, etc.
+- Slack integration to get answers and search results directly in Slack.
 
 ## 🚧 Roadmap
-- New methods in information retrieval (StructRAG, LightGraphRAG, etc.)
-- Personalized Search
-- Organizational understanding and ability to locate and suggest experts from your team.
-- Code Search
-- SQL and Structured Query Language
 
+- Chat/Prompt sharing with specific teammates and user groups.
+- Multimodal model support, chat with images, video etc.
+- Choosing between LLMs and parameters during chat session.
+- Tool calling and agent configurations options.
+- Organizational understanding and ability to locate and suggest experts from your team.
+
+## Other Notable Benefits of Onyx
+
+- User Authentication with document level access management.
+- Best in class Hybrid Search across all sources (BM-25 + prefix aware embedding models).
+- Admin Dashboard to configure connectors, document-sets, access, etc.
+- Custom deep learning models + learn from user feedback.
+- Easy deployment and ability to host Onyx anywhere of your choosing.
 
 ## 🔌 Connectors
-Keep knowledge and access up to sync across 40+ connectors:
 
+Efficiently pulls the latest changes from:
+
+- Slack
+- GitHub
 - Google Drive
 - Confluence
-- Slack
-- Gmail
-- Salesforce
-- Microsoft Sharepoint
-- Github
 - Jira
 - Zendesk
+- Gmail
+- Notion
 - Gong
-- Microsoft Teams
-- Dropbox
+- Slab
+- Linear
+- Productboard
+- Guru
+- Bookstack
+- Document360
+- Sharepoint
+- Hubspot
 - Local Files
 - Websites
 - And more ...
 
-See the full list [here](https://docs.onyx.app/connectors).
+## 📚 Editions
 
-
-## 📚 Licensing
 There are two editions of Onyx:
 
-- Onyx Community Edition (CE) is available freely under the MIT Expat license. Simply follow the Deployment guide above.
-- Onyx Enterprise Edition (EE) includes extra features that are primarily useful for larger organizations.
-For feature details, check out [our website](https://www.onyx.app/pricing).
+- Onyx Community Edition (CE) is available freely under the MIT Expat license. This version has ALL the core features discussed above. This is the version of Onyx you will get if you follow the Deployment guide above.
+- Onyx Enterprise Edition (EE) includes extra features that are primarily useful for larger organizations. Specifically, this includes:
+  - Single Sign-On (SSO), with support for both SAML and OIDC
+  - Role-based access control
+  - Document permission inheritance from connected sources
+  - Usage analytics and query history accessible to admins
+  - Whitelabeling
+  - API key authentication
+  - Encryption of secrets
+  - And many more! Checkout [our website](https://www.onyx.app/) for the latest.
 
 To try the Onyx Enterprise Edition:
-1. Checkout [Onyx Cloud](https://cloud.onyx.app/signup).
-2. For self-hosting the Enterprise Edition, contact us at [founders@onyx.app](mailto:founders@onyx.app) or book a call with us on our [Cal](https://cal.com/team/onyx/founders).
 
+1. Checkout our [Cloud product](https://cloud.onyx.app/signup).
+2. For self-hosting, contact us at [founders@onyx.app](mailto:founders@onyx.app) or book a call with us on our [Cal](https://cal.com/team/danswer/founders).
 
 ## 💡 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=onyx-dot-app/onyx&type=Date)](https://star-history.com/#onyx-dot-app/onyx&Date)

backend/Dockerfile

@@ -28,16 +28,14 @@ RUN apt-get update && \
         curl \
         zip \
         ca-certificates \
-        libgnutls30 \
-        libblkid1 \
-        libmount1 \
-        libsmartcols1 \
-        libuuid1 \
+        libgnutls30=3.7.9-2+deb12u3 \
+        libblkid1=2.38.1-5+deb12u1 \
+        libmount1=2.38.1-5+deb12u1 \
+        libsmartcols1=2.38.1-5+deb12u1 \
+        libuuid1=2.38.1-5+deb12u1 \
         libxmlsec1-dev \
         pkg-config \
-        gcc \
-        nano \
-        vim && \
+        gcc && \
     rm -rf /var/lib/apt/lists/* && \
     apt-get clean
 
@@ -103,8 +101,7 @@ COPY ./alembic_tenants /app/alembic_tenants
 COPY ./alembic.ini /app/alembic.ini
 COPY supervisord.conf /usr/etc/supervisord.conf
 
-# Escape hatch scripts
-COPY ./scripts/debugging /app/scripts/debugging
+# Escape hatch
 COPY ./scripts/force_delete_connector_by_id.py /app/scripts/force_delete_connector_by_id.py
 
 # Put logo in assets

backend/alembic/versions/1a03d2c2856b_add_indexes_to_document__tag.py

@@ -1,27 +0,0 @@
-"""Add indexes to document__tag
-
-Revision ID: 1a03d2c2856b
-Revises: 9c00a2bccb83
-Create Date: 2025-02-18 10:45:13.957807
-
-"""
-from alembic import op
-
-# revision identifiers, used by Alembic.
-revision = "1a03d2c2856b"
-down_revision = "9c00a2bccb83"
-branch_labels: None = None
-depends_on: None = None
-
-
-def upgrade() -> None:
-    op.create_index(
-        op.f("ix_document__tag_tag_id"),
-        "document__tag",
-        ["tag_id"],
-        unique=False,
-    )
-
-
-def downgrade() -> None:
-    op.drop_index(op.f("ix_document__tag_tag_id"), table_name="document__tag")

backend/alembic/versions/2cdeff6d8c93_set_built_in_to_default.py

@@ -1,32 +0,0 @@
-"""set built in to default
-
-Revision ID: 2cdeff6d8c93
-Revises: f5437cc136c5
-Create Date: 2025-02-11 14:57:51.308775
-
-"""
-from alembic import op
-
-
-# revision identifiers, used by Alembic.
-revision = "2cdeff6d8c93"
-down_revision = "f5437cc136c5"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Prior to this migration / point in the codebase history,
-    # built in personas were implicitly treated as default personas (with no option to change this)
-    # This migration makes that explicit
-    op.execute(
-        """
-        UPDATE persona
-        SET is_default_persona = TRUE
-        WHERE builtin_persona = TRUE
-    """
-    )
-
-
-def downgrade() -> None:
-    pass

backend/alembic/versions/2f80c6a2550f_add_chat_session_specific_temperature_.py

@@ -1,36 +0,0 @@
-"""add chat session specific temperature override
-
-Revision ID: 2f80c6a2550f
-Revises: 33ea50e88f24
-Create Date: 2025-01-31 10:30:27.289646
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "2f80c6a2550f"
-down_revision = "33ea50e88f24"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "chat_session", sa.Column("temperature_override", sa.Float(), nullable=True)
-    )
-    op.add_column(
-        "user",
-        sa.Column(
-            "temperature_override_enabled",
-            sa.Boolean(),
-            nullable=False,
-            server_default=sa.false(),
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("chat_session", "temperature_override")
-    op.drop_column("user", "temperature_override_enabled")

backend/alembic/versions/33ea50e88f24_foreign_key_input_prompts.py

@@ -1,80 +0,0 @@
-"""foreign key input prompts
-
-Revision ID: 33ea50e88f24
-Revises: a6df6b88ef81
-Create Date: 2025-01-29 10:54:22.141765
-
-"""
-from alembic import op
-
-
-# revision identifiers, used by Alembic.
-revision = "33ea50e88f24"
-down_revision = "a6df6b88ef81"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Safely drop constraints if exists
-    op.execute(
-        """
-        ALTER TABLE inputprompt__user
-        DROP CONSTRAINT IF EXISTS inputprompt__user_input_prompt_id_fkey
-        """
-    )
-    op.execute(
-        """
-        ALTER TABLE inputprompt__user
-        DROP CONSTRAINT IF EXISTS inputprompt__user_user_id_fkey
-        """
-    )
-
-    # Recreate with ON DELETE CASCADE
-    op.create_foreign_key(
-        "inputprompt__user_input_prompt_id_fkey",
-        "inputprompt__user",
-        "inputprompt",
-        ["input_prompt_id"],
-        ["id"],
-        ondelete="CASCADE",
-    )
-
-    op.create_foreign_key(
-        "inputprompt__user_user_id_fkey",
-        "inputprompt__user",
-        "user",
-        ["user_id"],
-        ["id"],
-        ondelete="CASCADE",
-    )
-
-
-def downgrade() -> None:
-    # Drop the new FKs with ondelete
-    op.drop_constraint(
-        "inputprompt__user_input_prompt_id_fkey",
-        "inputprompt__user",
-        type_="foreignkey",
-    )
-    op.drop_constraint(
-        "inputprompt__user_user_id_fkey",
-        "inputprompt__user",
-        type_="foreignkey",
-    )
-
-    # Recreate them without cascading
-    op.create_foreign_key(
-        "inputprompt__user_input_prompt_id_fkey",
-        "inputprompt__user",
-        "inputprompt",
-        ["input_prompt_id"],
-        ["id"],
-    )
-    op.create_foreign_key(
-        "inputprompt__user_user_id_fkey",
-        "inputprompt__user",
-        "user",
-        ["user_id"],
-        ["id"],
-    )

backend/alembic/versions/3bd4c84fe72f_improved_index.py

@@ -1,397 +0,0 @@
-"""improved index
-
-Revision ID: 3bd4c84fe72f
-Revises: 8f43500ee275
-Create Date: 2025-02-26 13:07:56.217791
-
-"""
-from alembic import op
-import time
-from sqlalchemy import text
-
-# revision identifiers, used by Alembic.
-revision = "3bd4c84fe72f"
-down_revision = "8f43500ee275"
-branch_labels = None
-depends_on = None
-
-
-# NOTE:
-# This migration addresses issues with the previous migration (8f43500ee275) which caused
-# an outage by creating an index without using CONCURRENTLY. This migration:
-#
-# 1. Creates more efficient full-text search capabilities using tsvector columns and GIN indexes
-# 2. Uses CONCURRENTLY for all index creation to prevent table locking
-# 3. Explicitly manages transactions with COMMIT statements to allow CONCURRENTLY to work
-# (see: https://www.postgresql.org/docs/9.4/sql-createindex.html#SQL-CREATEINDEX-CONCURRENTLY)
-# (see: https://github.com/sqlalchemy/alembic/issues/277)
-# 4. Adds indexes to both chat_message and chat_session tables for comprehensive search
-
-
-def upgrade():
-    # --- PART 1: chat_message table ---
-    # Step 1: Add nullable column (quick, minimal locking)
-    # op.execute("ALTER TABLE chat_message DROP COLUMN IF EXISTS message_tsv")
-    # op.execute("DROP TRIGGER IF EXISTS chat_message_tsv_trigger ON chat_message")
-    # op.execute("DROP FUNCTION IF EXISTS update_chat_message_tsv()")
-    # op.execute("ALTER TABLE chat_message DROP COLUMN IF EXISTS message_tsv")
-    # # Drop chat_session tsv trigger if it exists
-    # op.execute("DROP TRIGGER IF EXISTS chat_session_tsv_trigger ON chat_session")
-    # op.execute("DROP FUNCTION IF EXISTS update_chat_session_tsv()")
-    # op.execute("ALTER TABLE chat_session DROP COLUMN IF EXISTS title_tsv")
-    # raise Exception("Stop here")
-    time.time()
-    op.execute("ALTER TABLE chat_message ADD COLUMN IF NOT EXISTS message_tsv tsvector")
-
-    # Step 2: Create function and trigger for new/updated rows
-    op.execute(
-        """
-    CREATE OR REPLACE FUNCTION update_chat_message_tsv()
-    RETURNS TRIGGER AS $$
-    BEGIN
-      NEW.message_tsv = to_tsvector('english', NEW.message);
-      RETURN NEW;
-    END;
-    $$ LANGUAGE plpgsql
-    """
-    )
-
-    # Create trigger in a separate execute call
-    op.execute(
-        """
-    CREATE TRIGGER chat_message_tsv_trigger
-    BEFORE INSERT OR UPDATE ON chat_message
-    FOR EACH ROW EXECUTE FUNCTION update_chat_message_tsv()
-    """
-    )
-
-    # Step 3: Update existing rows in batches using Python
-    time.time()
-
-    # Get connection and count total rows
-    connection = op.get_bind()
-    total_count_result = connection.execute(
-        text("SELECT COUNT(*) FROM chat_message")
-    ).scalar()
-    total_count = total_count_result if total_count_result is not None else 0
-    batch_size = 5000
-    batches = 0
-
-    # Calculate total batches needed
-    total_batches = (
-        (total_count + batch_size - 1) // batch_size if total_count > 0 else 0
-    )
-
-    # Process in batches - properly handling UUIDs by using OFFSET/LIMIT approach
-    for batch_num in range(total_batches):
-        offset = batch_num * batch_size
-
-        # Execute update for this batch using OFFSET/LIMIT which works with UUIDs
-        connection.execute(
-            text(
-                """
-            UPDATE chat_message
-            SET message_tsv = to_tsvector('english', message)
-            WHERE id IN (
-                SELECT id FROM chat_message
-                WHERE message_tsv IS NULL
-                ORDER BY id
-                LIMIT :batch_size OFFSET :offset
-            )
-            """
-            ).bindparams(batch_size=batch_size, offset=offset)
-        )
-
-        # Commit each batch
-        connection.execute(text("COMMIT"))
-        # Start a new transaction
-        connection.execute(text("BEGIN"))
-
-        batches += 1
-
-    # Final check for any remaining NULL values
-    connection.execute(
-        text(
-            """
-    UPDATE chat_message SET message_tsv = to_tsvector('english', message)
-    WHERE message_tsv IS NULL
-    """
-        )
-    )
-
-    # Create GIN index concurrently
-    connection.execute(text("COMMIT"))
-
-    time.time()
-
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_message_tsv
-    ON chat_message USING GIN (message_tsv)
-    """
-        )
-    )
-
-    # First drop the trigger as it won't be needed anymore
-    connection.execute(
-        text(
-            """
-    DROP TRIGGER IF EXISTS chat_message_tsv_trigger ON chat_message;
-    """
-        )
-    )
-
-    connection.execute(
-        text(
-            """
-    DROP FUNCTION IF EXISTS update_chat_message_tsv();
-    """
-        )
-    )
-
-    # Add new generated column
-    time.time()
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_message
-    ADD COLUMN message_tsv_gen tsvector
-    GENERATED ALWAYS AS (to_tsvector('english', message)) STORED;
-    """
-        )
-    )
-
-    connection.execute(text("COMMIT"))
-
-    time.time()
-
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_message_tsv_gen
-    ON chat_message USING GIN (message_tsv_gen)
-    """
-        )
-    )
-
-    # Drop old index and column
-    connection.execute(text("COMMIT"))
-
-    connection.execute(
-        text(
-            """
-    DROP INDEX CONCURRENTLY IF EXISTS idx_chat_message_tsv;
-    """
-        )
-    )
-    connection.execute(text("COMMIT"))
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_message DROP COLUMN message_tsv;
-    """
-        )
-    )
-
-    # Rename new column to old name
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_message RENAME COLUMN message_tsv_gen TO message_tsv;
-    """
-        )
-    )
-
-    # --- PART 2: chat_session table ---
-
-    # Step 1: Add nullable column (quick, minimal locking)
-    time.time()
-    connection.execute(
-        text(
-            "ALTER TABLE chat_session ADD COLUMN IF NOT EXISTS description_tsv tsvector"
-        )
-    )
-
-    # Step 2: Create function and trigger for new/updated rows - SPLIT INTO SEPARATE CALLS
-    connection.execute(
-        text(
-            """
-    CREATE OR REPLACE FUNCTION update_chat_session_tsv()
-    RETURNS TRIGGER AS $$
-    BEGIN
-      NEW.description_tsv = to_tsvector('english', COALESCE(NEW.description, ''));
-      RETURN NEW;
-    END;
-    $$ LANGUAGE plpgsql
-    """
-        )
-    )
-
-    # Create trigger in a separate execute call
-    connection.execute(
-        text(
-            """
-    CREATE TRIGGER chat_session_tsv_trigger
-    BEFORE INSERT OR UPDATE ON chat_session
-    FOR EACH ROW EXECUTE FUNCTION update_chat_session_tsv()
-    """
-        )
-    )
-
-    # Step 3: Update existing rows in batches using Python
-    time.time()
-
-    # Get the maximum ID to determine batch count
-    # Cast id to text for MAX function since it's a UUID
-    max_id_result = connection.execute(
-        text("SELECT COALESCE(MAX(id::text), '0') FROM chat_session")
-    ).scalar()
-    max_id_result if max_id_result is not None else "0"
-    batch_size = 5000
-    batches = 0
-
-    # Get all IDs ordered to process in batches
-    rows = connection.execute(
-        text("SELECT id FROM chat_session ORDER BY id")
-    ).fetchall()
-    total_rows = len(rows)
-
-    # Process in batches
-    for batch_num, batch_start in enumerate(range(0, total_rows, batch_size)):
-        batch_end = min(batch_start + batch_size, total_rows)
-        batch_ids = [row[0] for row in rows[batch_start:batch_end]]
-
-        if not batch_ids:
-            continue
-
-        # Use IN clause instead of BETWEEN for UUIDs
-        placeholders = ", ".join([f":id{i}" for i in range(len(batch_ids))])
-        params = {f"id{i}": id_val for i, id_val in enumerate(batch_ids)}
-
-        # Execute update for this batch
-        connection.execute(
-            text(
-                f"""
-            UPDATE chat_session
-            SET description_tsv = to_tsvector('english', COALESCE(description, ''))
-            WHERE id IN ({placeholders})
-            AND description_tsv IS NULL
-            """
-            ).bindparams(**params)
-        )
-
-        # Commit each batch
-        connection.execute(text("COMMIT"))
-        # Start a new transaction
-        connection.execute(text("BEGIN"))
-
-        batches += 1
-
-    # Final check for any remaining NULL values
-    connection.execute(
-        text(
-            """
-    UPDATE chat_session SET description_tsv = to_tsvector('english', COALESCE(description, ''))
-    WHERE description_tsv IS NULL
-    """
-        )
-    )
-
-    # Create GIN index concurrently
-    connection.execute(text("COMMIT"))
-
-    time.time()
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_session_desc_tsv
-    ON chat_session USING GIN (description_tsv)
-    """
-        )
-    )
-
-    # After Final check for chat_session
-    # First drop the trigger as it won't be needed anymore
-    connection.execute(
-        text(
-            """
-    DROP TRIGGER IF EXISTS chat_session_tsv_trigger ON chat_session;
-    """
-        )
-    )
-
-    connection.execute(
-        text(
-            """
-    DROP FUNCTION IF EXISTS update_chat_session_tsv();
-    """
-        )
-    )
-    # Add new generated column
-    time.time()
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_session
-    ADD COLUMN description_tsv_gen tsvector
-    GENERATED ALWAYS AS (to_tsvector('english', COALESCE(description, ''))) STORED;
-    """
-        )
-    )
-
-    # Create new index on generated column
-    connection.execute(text("COMMIT"))
-
-    time.time()
-    connection.execute(
-        text(
-            """
-    CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_session_desc_tsv_gen
-    ON chat_session USING GIN (description_tsv_gen)
-    """
-        )
-    )
-
-    # Drop old index and column
-    connection.execute(text("COMMIT"))
-
-    connection.execute(
-        text(
-            """
-    DROP INDEX CONCURRENTLY IF EXISTS idx_chat_session_desc_tsv;
-    """
-        )
-    )
-    connection.execute(text("COMMIT"))
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_session DROP COLUMN description_tsv;
-    """
-        )
-    )
-
-    # Rename new column to old name
-    connection.execute(
-        text(
-            """
-    ALTER TABLE chat_session RENAME COLUMN description_tsv_gen TO description_tsv;
-    """
-        )
-    )
-
-
-def downgrade() -> None:
-    # Drop the indexes first (use CONCURRENTLY for dropping too)
-    op.execute("COMMIT")
-    op.execute("DROP INDEX CONCURRENTLY IF EXISTS idx_chat_message_tsv;")
-
-    op.execute("COMMIT")
-    op.execute("DROP INDEX CONCURRENTLY IF EXISTS idx_chat_session_desc_tsv;")
-
-    # Then drop the columns
-    op.execute("ALTER TABLE chat_message DROP COLUMN IF EXISTS message_tsv;")
-    op.execute("ALTER TABLE chat_session DROP COLUMN IF EXISTS description_tsv;")
-
-    op.execute("DROP INDEX IF EXISTS idx_chat_message_message_lower;")

backend/alembic/versions/4d58345da04a_lowercase_user_emails.py

@@ -1,37 +0,0 @@
-"""lowercase_user_emails
-
-Revision ID: 4d58345da04a
-Revises: f1ca58b2f2ec
-Create Date: 2025-01-29 07:48:46.784041
-
-"""
-from alembic import op
-from sqlalchemy.sql import text
-
-
-# revision identifiers, used by Alembic.
-revision = "4d58345da04a"
-down_revision = "f1ca58b2f2ec"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Get database connection
-    connection = op.get_bind()
-
-    # Update all user emails to lowercase
-    connection.execute(
-        text(
-            """
-            UPDATE "user"
-            SET email = LOWER(email)
-            WHERE email != LOWER(email)
-            """
-        )
-    )
-
-
-def downgrade() -> None:
-    # Cannot restore original case of emails
-    pass

backend/alembic/versions/4ee1287bd26a_add_multiple_slack_bot_support.py

@@ -5,6 +5,7 @@ Revises: 47e5bef3a1d7
 Create Date: 2024-11-06 13:15:53.302644
 
 """
+import logging
 from typing import cast
 from alembic import op
 import sqlalchemy as sa
@@ -19,8 +20,13 @@ down_revision = "47e5bef3a1d7"
 branch_labels: None = None
 depends_on: None = None
 
+# Configure logging
+logger = logging.getLogger("alembic.runtime.migration")
+logger.setLevel(logging.INFO)
+
 
 def upgrade() -> None:
+    logger.info(f"{revision}: create_table: slack_bot")
     # Create new slack_bot table
     op.create_table(
         "slack_bot",
@@ -57,6 +63,7 @@ def upgrade() -> None:
     )
 
     # Handle existing Slack bot tokens first
+    logger.info(f"{revision}: Checking for existing Slack bot.")
     bot_token = None
     app_token = None
     first_row_id = None
@@ -64,12 +71,15 @@ def upgrade() -> None:
     try:
         tokens = cast(dict, get_kv_store().load("slack_bot_tokens_config_key"))
     except Exception:
+        logger.warning("No existing Slack bot tokens found.")
         tokens = {}
 
     bot_token = tokens.get("bot_token")
     app_token = tokens.get("app_token")
 
     if bot_token and app_token:
+        logger.info(f"{revision}: Found bot and app tokens.")
+
         session = Session(bind=op.get_bind())
         new_slack_bot = SlackBot(
             name="Slack Bot (Migrated)",
@@ -160,9 +170,10 @@ def upgrade() -> None:
     # Clean up old tokens if they existed
     try:
         if bot_token and app_token:
+            logger.info(f"{revision}: Removing old bot and app tokens.")
             get_kv_store().delete("slack_bot_tokens_config_key")
     except Exception:
-        pass
+        logger.warning("tried to delete tokens in dynamic config but failed")
     # Rename the table
     op.rename_table(
         "slack_bot_config__standard_answer_category",
@@ -179,6 +190,8 @@ def upgrade() -> None:
     # Drop the table with CASCADE to handle dependent objects
     op.execute("DROP TABLE slack_bot_config CASCADE")
 
+    logger.info(f"{revision}: Migration complete.")
+
 
 def downgrade() -> None:
     # Recreate the old slack_bot_config table
@@ -260,7 +273,7 @@ def downgrade() -> None:
             }
             get_kv_store().store("slack_bot_tokens_config_key", tokens)
     except Exception:
-        pass
+        logger.warning("Failed to save tokens back to KV store")
 
     # Drop the new tables in reverse order
     op.drop_table("slack_channel_config")

backend/alembic/versions/8f43500ee275_add_index.py

@@ -1,32 +0,0 @@
-"""add index
-
-Revision ID: 8f43500ee275
-Revises: da42808081e3
-Create Date: 2025-02-24 17:35:33.072714
-
-"""
-from alembic import op
-
-
-# revision identifiers, used by Alembic.
-revision = "8f43500ee275"
-down_revision = "da42808081e3"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Create a basic index on the lowercase message column for direct text matching
-    # Limit to 1500 characters to stay well under the 2856 byte limit of btree version 4
-    # op.execute(
-    #     """
-    #     CREATE INDEX idx_chat_message_message_lower
-    #     ON chat_message (LOWER(substring(message, 1, 1500)))
-    #     """
-    # )
-    pass
-
-
-def downgrade() -> None:
-    # Drop the index
-    op.execute("DROP INDEX IF EXISTS idx_chat_message_message_lower;")

backend/alembic/versions/98a5008d8711_agent_tracking.py

@@ -1,107 +0,0 @@
-"""agent_tracking
-
-Revision ID: 98a5008d8711
-Revises: 2f80c6a2550f
-Create Date: 2025-01-29 17:00:00.000001
-
-"""
-from alembic import op
-import sqlalchemy as sa
-from sqlalchemy.dialects import postgresql
-from sqlalchemy.dialects.postgresql import UUID
-
-# revision identifiers, used by Alembic.
-revision = "98a5008d8711"
-down_revision = "2f80c6a2550f"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.create_table(
-        "agent__search_metrics",
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("user_id", postgresql.UUID(as_uuid=True), nullable=True),
-        sa.Column("persona_id", sa.Integer(), nullable=True),
-        sa.Column("agent_type", sa.String(), nullable=False),
-        sa.Column("start_time", sa.DateTime(timezone=True), nullable=False),
-        sa.Column("base_duration_s", sa.Float(), nullable=False),
-        sa.Column("full_duration_s", sa.Float(), nullable=False),
-        sa.Column("base_metrics", postgresql.JSONB(), nullable=True),
-        sa.Column("refined_metrics", postgresql.JSONB(), nullable=True),
-        sa.Column("all_metrics", postgresql.JSONB(), nullable=True),
-        sa.ForeignKeyConstraint(
-            ["persona_id"],
-            ["persona.id"],
-        ),
-        sa.ForeignKeyConstraint(["user_id"], ["user.id"], ondelete="CASCADE"),
-        sa.PrimaryKeyConstraint("id"),
-    )
-
-    # Create sub_question table
-    op.create_table(
-        "agent__sub_question",
-        sa.Column("id", sa.Integer, primary_key=True),
-        sa.Column("primary_question_id", sa.Integer, sa.ForeignKey("chat_message.id")),
-        sa.Column(
-            "chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
-        ),
-        sa.Column("sub_question", sa.Text),
-        sa.Column(
-            "time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
-        ),
-        sa.Column("sub_answer", sa.Text),
-        sa.Column("sub_question_doc_results", postgresql.JSONB(), nullable=True),
-        sa.Column("level", sa.Integer(), nullable=False),
-        sa.Column("level_question_num", sa.Integer(), nullable=False),
-    )
-
-    # Create sub_query table
-    op.create_table(
-        "agent__sub_query",
-        sa.Column("id", sa.Integer, primary_key=True),
-        sa.Column(
-            "parent_question_id", sa.Integer, sa.ForeignKey("agent__sub_question.id")
-        ),
-        sa.Column(
-            "chat_session_id", UUID(as_uuid=True), sa.ForeignKey("chat_session.id")
-        ),
-        sa.Column("sub_query", sa.Text),
-        sa.Column(
-            "time_created", sa.DateTime(timezone=True), server_default=sa.func.now()
-        ),
-    )
-
-    # Create sub_query__search_doc association table
-    op.create_table(
-        "agent__sub_query__search_doc",
-        sa.Column(
-            "sub_query_id",
-            sa.Integer,
-            sa.ForeignKey("agent__sub_query.id"),
-            primary_key=True,
-        ),
-        sa.Column(
-            "search_doc_id",
-            sa.Integer,
-            sa.ForeignKey("search_doc.id"),
-            primary_key=True,
-        ),
-    )
-
-    op.add_column(
-        "chat_message",
-        sa.Column(
-            "refined_answer_improvement",
-            sa.Boolean(),
-            nullable=True,
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("chat_message", "refined_answer_improvement")
-    op.drop_table("agent__sub_query__search_doc")
-    op.drop_table("agent__sub_query")
-    op.drop_table("agent__sub_question")
-    op.drop_table("agent__search_metrics")

backend/alembic/versions/9c00a2bccb83_chat_message_agentic.py

@@ -1,43 +0,0 @@
-"""chat_message_agentic
-
-Revision ID: 9c00a2bccb83
-Revises: b7a7eee5aa15
-Create Date: 2025-02-17 11:15:43.081150
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "9c00a2bccb83"
-down_revision = "b7a7eee5aa15"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # First add the column as nullable
-    op.add_column("chat_message", sa.Column("is_agentic", sa.Boolean(), nullable=True))
-
-    # Update existing rows based on presence of SubQuestions
-    op.execute(
-        """
-        UPDATE chat_message
-        SET is_agentic = EXISTS (
-            SELECT 1
-            FROM agent__sub_question
-            WHERE agent__sub_question.primary_question_id = chat_message.id
-        )
-        WHERE is_agentic IS NULL
-    """
-    )
-
-    # Make the column non-nullable with a default value of False
-    op.alter_column(
-        "chat_message", "is_agentic", nullable=False, server_default=sa.text("false")
-    )
-
-
-def downgrade() -> None:
-    op.drop_column("chat_message", "is_agentic")

backend/alembic/versions/a6df6b88ef81_remove_recent_assistants.py

@@ -1,29 +0,0 @@
-"""remove recent assistants
-
-Revision ID: a6df6b88ef81
-Revises: 4d58345da04a
-Create Date: 2025-01-29 10:25:52.790407
-
-"""
-from alembic import op
-import sqlalchemy as sa
-from sqlalchemy.dialects import postgresql
-
-# revision identifiers, used by Alembic.
-revision = "a6df6b88ef81"
-down_revision = "4d58345da04a"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.drop_column("user", "recent_assistants")
-
-
-def downgrade() -> None:
-    op.add_column(
-        "user",
-        sa.Column(
-            "recent_assistants", postgresql.JSONB(), server_default="[]", nullable=False
-        ),
-    )

backend/alembic/versions/acaab4ef4507_remove_inactive_ccpair_status_on_.py

@@ -1,29 +0,0 @@
-"""remove inactive ccpair status on downgrade
-
-Revision ID: acaab4ef4507
-Revises: b388730a2899
-Create Date: 2025-02-16 18:21:41.330212
-
-"""
-from alembic import op
-from onyx.db.models import ConnectorCredentialPair
-from onyx.db.enums import ConnectorCredentialPairStatus
-from sqlalchemy import update
-
-# revision identifiers, used by Alembic.
-revision = "acaab4ef4507"
-down_revision = "b388730a2899"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    pass
-
-
-def downgrade() -> None:
-    op.execute(
-        update(ConnectorCredentialPair)
-        .where(ConnectorCredentialPair.status == ConnectorCredentialPairStatus.INVALID)
-        .values(status=ConnectorCredentialPairStatus.ACTIVE)
-    )

backend/alembic/versions/b388730a2899_nullable_preferences.py

@@ -1,31 +0,0 @@
-"""nullable preferences
-
-Revision ID: b388730a2899
-Revises: 1a03d2c2856b
-Create Date: 2025-02-17 18:49:22.643902
-
-"""
-from alembic import op
-
-
-# revision identifiers, used by Alembic.
-revision = "b388730a2899"
-down_revision = "1a03d2c2856b"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.alter_column("user", "temperature_override_enabled", nullable=True)
-    op.alter_column("user", "auto_scroll", nullable=True)
-
-
-def downgrade() -> None:
-    # Ensure no null values before making columns non-nullable
-    op.execute(
-        'UPDATE "user" SET temperature_override_enabled = false WHERE temperature_override_enabled IS NULL'
-    )
-    op.execute('UPDATE "user" SET auto_scroll = false WHERE auto_scroll IS NULL')
-
-    op.alter_column("user", "temperature_override_enabled", nullable=False)
-    op.alter_column("user", "auto_scroll", nullable=False)

backend/alembic/versions/b7a7eee5aa15_add_checkpointing_failure_handling.py

@@ -1,124 +0,0 @@
-"""Add checkpointing/failure handling
-
-Revision ID: b7a7eee5aa15
-Revises: f39c5794c10a
-Create Date: 2025-01-24 15:17:36.763172
-
-"""
-from alembic import op
-import sqlalchemy as sa
-from sqlalchemy.dialects import postgresql
-
-# revision identifiers, used by Alembic.
-revision = "b7a7eee5aa15"
-down_revision = "f39c5794c10a"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.add_column(
-        "index_attempt",
-        sa.Column("checkpoint_pointer", sa.String(), nullable=True),
-    )
-    op.add_column(
-        "index_attempt",
-        sa.Column("poll_range_start", sa.DateTime(timezone=True), nullable=True),
-    )
-    op.add_column(
-        "index_attempt",
-        sa.Column("poll_range_end", sa.DateTime(timezone=True), nullable=True),
-    )
-
-    op.create_index(
-        "ix_index_attempt_cc_pair_settings_poll",
-        "index_attempt",
-        [
-            "connector_credential_pair_id",
-            "search_settings_id",
-            "status",
-            sa.text("time_updated DESC"),
-        ],
-    )
-
-    # Drop the old IndexAttemptError table
-    op.drop_index("index_attempt_id", table_name="index_attempt_errors")
-    op.drop_table("index_attempt_errors")
-
-    # Create the new version of the table
-    op.create_table(
-        "index_attempt_errors",
-        sa.Column("id", sa.Integer(), primary_key=True),
-        sa.Column("index_attempt_id", sa.Integer(), nullable=False),
-        sa.Column("connector_credential_pair_id", sa.Integer(), nullable=False),
-        sa.Column("document_id", sa.String(), nullable=True),
-        sa.Column("document_link", sa.String(), nullable=True),
-        sa.Column("entity_id", sa.String(), nullable=True),
-        sa.Column("failed_time_range_start", sa.DateTime(timezone=True), nullable=True),
-        sa.Column("failed_time_range_end", sa.DateTime(timezone=True), nullable=True),
-        sa.Column("failure_message", sa.Text(), nullable=False),
-        sa.Column("is_resolved", sa.Boolean(), nullable=False, default=False),
-        sa.Column(
-            "time_created",
-            sa.DateTime(timezone=True),
-            server_default=sa.text("now()"),
-            nullable=False,
-        ),
-        sa.ForeignKeyConstraint(
-            ["index_attempt_id"],
-            ["index_attempt.id"],
-        ),
-        sa.ForeignKeyConstraint(
-            ["connector_credential_pair_id"],
-            ["connector_credential_pair.id"],
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.execute("SET lock_timeout = '5s'")
-
-    # try a few times to drop the table, this has been observed to fail due to other locks
-    # blocking the drop
-    NUM_TRIES = 10
-    for i in range(NUM_TRIES):
-        try:
-            op.drop_table("index_attempt_errors")
-            break
-        except Exception as e:
-            if i == NUM_TRIES - 1:
-                raise e
-            print(f"Error dropping table: {e}. Retrying...")
-
-    op.execute("SET lock_timeout = DEFAULT")
-
-    # Recreate the old IndexAttemptError table
-    op.create_table(
-        "index_attempt_errors",
-        sa.Column("id", sa.Integer(), primary_key=True),
-        sa.Column("index_attempt_id", sa.Integer(), nullable=True),
-        sa.Column("batch", sa.Integer(), nullable=True),
-        sa.Column("doc_summaries", postgresql.JSONB(), nullable=False),
-        sa.Column("error_msg", sa.Text(), nullable=True),
-        sa.Column("traceback", sa.Text(), nullable=True),
-        sa.Column(
-            "time_created",
-            sa.DateTime(timezone=True),
-            server_default=sa.text("now()"),
-        ),
-        sa.ForeignKeyConstraint(
-            ["index_attempt_id"],
-            ["index_attempt.id"],
-        ),
-    )
-
-    op.create_index(
-        "index_attempt_id",
-        "index_attempt_errors",
-        ["time_created"],
-    )
-
-    op.drop_index("ix_index_attempt_cc_pair_settings_poll")
-    op.drop_column("index_attempt", "checkpoint_pointer")
-    op.drop_column("index_attempt", "poll_range_start")
-    op.drop_column("index_attempt", "poll_range_end")

backend/alembic/versions/b7c2b63c4a03_add_background_reindex_enabled_field.py

@@ -1,55 +0,0 @@
-"""add background_reindex_enabled field
-
-Revision ID: b7c2b63c4a03
-Revises: f11b408e39d3
-Create Date: 2024-03-26 12:34:56.789012
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-from onyx.db.enums import EmbeddingPrecision
-
-
-# revision identifiers, used by Alembic.
-revision = "b7c2b63c4a03"
-down_revision = "f11b408e39d3"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Add background_reindex_enabled column with default value of True
-    op.add_column(
-        "search_settings",
-        sa.Column(
-            "background_reindex_enabled",
-            sa.Boolean(),
-            nullable=False,
-            server_default="true",
-        ),
-    )
-
-    # Add embedding_precision column with default value of FLOAT
-    op.add_column(
-        "search_settings",
-        sa.Column(
-            "embedding_precision",
-            sa.Enum(EmbeddingPrecision, native_enum=False),
-            nullable=False,
-            server_default=EmbeddingPrecision.FLOAT.name,
-        ),
-    )
-
-    # Add reduced_dimension column with default value of None
-    op.add_column(
-        "search_settings",
-        sa.Column("reduced_dimension", sa.Integer(), nullable=True),
-    )
-
-
-def downgrade() -> None:
-    # Remove the background_reindex_enabled column
-    op.drop_column("search_settings", "background_reindex_enabled")
-    op.drop_column("search_settings", "embedding_precision")
-    op.drop_column("search_settings", "reduced_dimension")

backend/alembic/versions/da42808081e3_migrate_jira_connectors_to_new_format.py

@@ -1,120 +0,0 @@
-"""migrate jira connectors to new format
-
-Revision ID: da42808081e3
-Revises: f13db29f3101
-Create Date: 2025-02-24 11:24:54.396040
-
-"""
-from alembic import op
-import sqlalchemy as sa
-import json
-
-from onyx.configs.constants import DocumentSource
-from onyx.connectors.onyx_jira.utils import extract_jira_project
-
-
-# revision identifiers, used by Alembic.
-revision = "da42808081e3"
-down_revision = "f13db29f3101"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Get all Jira connectors
-    conn = op.get_bind()
-
-    # First get all Jira connectors
-    jira_connectors = conn.execute(
-        sa.text(
-            """
-            SELECT id, connector_specific_config
-            FROM connector
-            WHERE source = :source
-            """
-        ),
-        {"source": DocumentSource.JIRA.value.upper()},
-    ).fetchall()
-
-    # Update each connector's config
-    for connector_id, old_config in jira_connectors:
-        if not old_config:
-            continue
-
-        # Extract project key from URL if it exists
-        new_config: dict[str, str | None] = {}
-        if project_url := old_config.get("jira_project_url"):
-            # Parse the URL to get base and project
-            try:
-                jira_base, project_key = extract_jira_project(project_url)
-                new_config = {"jira_base_url": jira_base, "project_key": project_key}
-            except ValueError:
-                # If URL parsing fails, just use the URL as the base
-                new_config = {
-                    "jira_base_url": project_url.split("/projects/")[0],
-                    "project_key": None,
-                }
-        else:
-            # For connectors without a project URL, we need admin intervention
-            # Mark these for review
-            print(
-                f"WARNING: Jira connector {connector_id} has no project URL configured"
-            )
-            continue
-
-        # Update the connector config
-        conn.execute(
-            sa.text(
-                """
-                UPDATE connector
-                SET connector_specific_config = :new_config
-                WHERE id = :id
-                """
-            ),
-            {"id": connector_id, "new_config": json.dumps(new_config)},
-        )
-
-
-def downgrade() -> None:
-    # Get all Jira connectors
-    conn = op.get_bind()
-
-    # First get all Jira connectors
-    jira_connectors = conn.execute(
-        sa.text(
-            """
-            SELECT id, connector_specific_config
-            FROM connector
-            WHERE source = :source
-            """
-        ),
-        {"source": DocumentSource.JIRA.value.upper()},
-    ).fetchall()
-
-    # Update each connector's config back to the old format
-    for connector_id, new_config in jira_connectors:
-        if not new_config:
-            continue
-
-        old_config = {}
-        base_url = new_config.get("jira_base_url")
-        project_key = new_config.get("project_key")
-
-        if base_url and project_key:
-            old_config = {"jira_project_url": f"{base_url}/projects/{project_key}"}
-        elif base_url:
-            old_config = {"jira_project_url": base_url}
-        else:
-            continue
-
-        # Update the connector config
-        conn.execute(
-            sa.text(
-                """
-                UPDATE connector
-                SET connector_specific_config = :old_config
-                WHERE id = :id
-                """
-            ),
-            {"id": connector_id, "old_config": old_config},
-        )

backend/alembic/versions/eaa3b5593925_add_default_slack_channel_config.py

@@ -1,80 +0,0 @@
-"""add default slack channel config
-
-Revision ID: eaa3b5593925
-Revises: 98a5008d8711
-Create Date: 2025-02-03 18:07:56.552526
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-
-# revision identifiers, used by Alembic.
-revision = "eaa3b5593925"
-down_revision = "98a5008d8711"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # Add is_default column
-    op.add_column(
-        "slack_channel_config",
-        sa.Column("is_default", sa.Boolean(), nullable=False, server_default="false"),
-    )
-
-    op.create_index(
-        "ix_slack_channel_config_slack_bot_id_default",
-        "slack_channel_config",
-        ["slack_bot_id", "is_default"],
-        unique=True,
-        postgresql_where=sa.text("is_default IS TRUE"),
-    )
-
-    # Create default channel configs for existing slack bots without one
-    conn = op.get_bind()
-    slack_bots = conn.execute(sa.text("SELECT id FROM slack_bot")).fetchall()
-
-    for slack_bot in slack_bots:
-        slack_bot_id = slack_bot[0]
-        existing_default = conn.execute(
-            sa.text(
-                "SELECT id FROM slack_channel_config WHERE slack_bot_id = :bot_id AND is_default = TRUE"
-            ),
-            {"bot_id": slack_bot_id},
-        ).fetchone()
-
-        if not existing_default:
-            conn.execute(
-                sa.text(
-                    """
-                    INSERT INTO slack_channel_config (
-                        slack_bot_id, persona_id, channel_config, enable_auto_filters, is_default
-                    ) VALUES (
-                        :bot_id, NULL,
-                        '{"channel_name": null, '
-                        '"respond_member_group_list": [], '
-                        '"answer_filters": [], '
-                        '"follow_up_tags": [], '
-                        '"respond_tag_only": true}',
-                        FALSE, TRUE
-                    )
-                """
-                ),
-                {"bot_id": slack_bot_id},
-            )
-
-
-def downgrade() -> None:
-    # Delete default slack channel configs
-    conn = op.get_bind()
-    conn.execute(sa.text("DELETE FROM slack_channel_config WHERE is_default = TRUE"))
-
-    # Remove index
-    op.drop_index(
-        "ix_slack_channel_config_slack_bot_id_default",
-        table_name="slack_channel_config",
-    )
-
-    # Remove is_default column
-    op.drop_column("slack_channel_config", "is_default")

backend/alembic/versions/f11b408e39d3_force_lowercase_all_users.py

@@ -1,36 +0,0 @@
-"""force lowercase all users
-
-Revision ID: f11b408e39d3
-Revises: 3bd4c84fe72f
-Create Date: 2025-02-26 17:04:55.683500
-
-"""
-
-
-# revision identifiers, used by Alembic.
-revision = "f11b408e39d3"
-down_revision = "3bd4c84fe72f"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # 1) Convert all existing user emails to lowercase
-    from alembic import op
-
-    op.execute(
-        """
-        UPDATE "user"
-        SET email = LOWER(email)
-        """
-    )
-
-    # 2) Add a check constraint to ensure emails are always lowercase
-    op.create_check_constraint("ensure_lowercase_email", "user", "email = LOWER(email)")
-
-
-def downgrade() -> None:
-    # Drop the check constraint
-    from alembic import op
-
-    op.drop_constraint("ensure_lowercase_email", "user", type_="check")

backend/alembic/versions/f13db29f3101_add_composite_index_for_last_modified_.py

@@ -1,27 +0,0 @@
-"""Add composite index for last_modified and last_synced to document
-
-Revision ID: f13db29f3101
-Revises: b388730a2899
-Create Date: 2025-02-18 22:48:11.511389
-
-"""
-from alembic import op
-
-# revision identifiers, used by Alembic.
-revision = "f13db29f3101"
-down_revision = "acaab4ef4507"
-branch_labels: str | None = None
-depends_on: str | None = None
-
-
-def upgrade() -> None:
-    op.create_index(
-        "ix_document_sync_status",
-        "document",
-        ["last_modified", "last_synced"],
-        unique=False,
-    )
-
-
-def downgrade() -> None:
-    op.drop_index("ix_document_sync_status", table_name="document")

backend/alembic/versions/f39c5794c10a_add_background_errors_table.py

@@ -1,40 +0,0 @@
-"""Add background errors table
-
-Revision ID: f39c5794c10a
-Revises: 2cdeff6d8c93
-Create Date: 2025-02-12 17:11:14.527876
-
-"""
-from alembic import op
-import sqlalchemy as sa
-
-# revision identifiers, used by Alembic.
-revision = "f39c5794c10a"
-down_revision = "2cdeff6d8c93"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    op.create_table(
-        "background_error",
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("message", sa.String(), nullable=False),
-        sa.Column(
-            "time_created",
-            sa.DateTime(timezone=True),
-            server_default=sa.text("now()"),
-            nullable=False,
-        ),
-        sa.Column("cc_pair_id", sa.Integer(), nullable=True),
-        sa.PrimaryKeyConstraint("id"),
-        sa.ForeignKeyConstraint(
-            ["cc_pair_id"],
-            ["connector_credential_pair.id"],
-            ondelete="CASCADE",
-        ),
-    )
-
-
-def downgrade() -> None:
-    op.drop_table("background_error")

backend/alembic/versions/f5437cc136c5_delete_non_search_assistants.py

@@ -1,53 +0,0 @@
-"""delete non-search assistants
-
-Revision ID: f5437cc136c5
-Revises: eaa3b5593925
-Create Date: 2025-02-04 16:17:15.677256
-
-"""
-from alembic import op
-
-
-# revision identifiers, used by Alembic.
-revision = "f5437cc136c5"
-down_revision = "eaa3b5593925"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    pass
-
-
-def downgrade() -> None:
-    # Fix: split the statements into multiple op.execute() calls
-    op.execute(
-        """
-        WITH personas_without_search AS (
-            SELECT p.id
-            FROM persona p
-            LEFT JOIN persona__tool pt ON p.id = pt.persona_id
-            LEFT JOIN tool t ON pt.tool_id = t.id
-            GROUP BY p.id
-            HAVING COUNT(CASE WHEN t.in_code_tool_id = 'run_search' THEN 1 END) = 0
-        )
-        UPDATE slack_channel_config
-        SET persona_id = NULL
-        WHERE is_default = TRUE AND persona_id IN (SELECT id FROM personas_without_search)
-        """
-    )
-
-    op.execute(
-        """
-        WITH personas_without_search AS (
-            SELECT p.id
-            FROM persona p
-            LEFT JOIN persona__tool pt ON p.id = pt.persona_id
-            LEFT JOIN tool t ON pt.tool_id = t.id
-            GROUP BY p.id
-            HAVING COUNT(CASE WHEN t.in_code_tool_id = 'run_search' THEN 1 END) = 0
-        )
-        DELETE FROM slack_channel_config
-        WHERE is_default = FALSE AND persona_id IN (SELECT id FROM personas_without_search)
-        """
-    )

backend/alembic_tenants/versions/34e3630c7f32_lowercase_multi_tenant_user_auth.py

@@ -1,42 +0,0 @@
-"""lowercase multi-tenant user auth
-
-Revision ID: 34e3630c7f32
-Revises: a4f6ee863c47
-Create Date: 2025-02-26 15:03:01.211894
-
-"""
-from alembic import op
-
-
-# revision identifiers, used by Alembic.
-revision = "34e3630c7f32"
-down_revision = "a4f6ee863c47"
-branch_labels = None
-depends_on = None
-
-
-def upgrade() -> None:
-    # 1) Convert all existing rows to lowercase
-    op.execute(
-        """
-        UPDATE user_tenant_mapping
-        SET email = LOWER(email)
-        """
-    )
-    # 2) Add a check constraint so that emails cannot be written in uppercase
-    op.create_check_constraint(
-        "ensure_lowercase_email",
-        "user_tenant_mapping",
-        "email = LOWER(email)",
-        schema="public",
-    )
-
-
-def downgrade() -> None:
-    # Drop the check constraint
-    op.drop_constraint(
-        "ensure_lowercase_email",
-        "user_tenant_mapping",
-        schema="public",
-        type_="check",
-    )

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

@@ -4,11 +4,12 @@ from ee.onyx.server.reporting.usage_export_generation import create_new_usage_re
 from onyx.background.celery.apps.primary import celery_app
 from onyx.background.task_utils import build_celery_task_wrapper
 from onyx.configs.app_configs import JOB_TIMEOUT
-from onyx.db.chat import delete_chat_session
-from onyx.db.chat import get_chat_sessions_older_than
-from onyx.db.engine import get_session_with_current_tenant
+from onyx.db.chat import delete_chat_sessions_older_than
+from onyx.db.engine import get_session_with_tenant
 from onyx.server.settings.store import load_settings
 from onyx.utils.logger import setup_logger
+from shared_configs.configs import MULTI_TENANT
+from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
 
 logger = setup_logger()
 
@@ -17,28 +18,11 @@ logger = setup_logger()
 
 @build_celery_task_wrapper(name_chat_ttl_task)
 @celery_app.task(soft_time_limit=JOB_TIMEOUT)
-def perform_ttl_management_task(retention_limit_days: int, *, tenant_id: str) -> None:
-    with get_session_with_current_tenant() as db_session:
-        old_chat_sessions = get_chat_sessions_older_than(
-            retention_limit_days, db_session
-        )
-
-    for user_id, session_id in old_chat_sessions:
-        # one session per delete so that we don't blow up if a deletion fails.
-        with get_session_with_current_tenant() as db_session:
-            try:
-                delete_chat_session(
-                    user_id,
-                    session_id,
-                    db_session,
-                    include_deleted=True,
-                    hard_delete=True,
-                )
-            except Exception:
-                logger.exception(
-                    "delete_chat_session exceptioned. "
-                    f"user_id={user_id} session_id={session_id}"
-                )
+def perform_ttl_management_task(
+    retention_limit_days: int, *, tenant_id: str | None
+) -> None:
+    with get_session_with_tenant(tenant_id) as db_session:
+        delete_chat_sessions_older_than(retention_limit_days, db_session)
 
 
 #####
@@ -51,19 +35,24 @@ def perform_ttl_management_task(retention_limit_days: int, *, tenant_id: str) ->
     ignore_result=True,
     soft_time_limit=JOB_TIMEOUT,
 )
-def check_ttl_management_task(*, tenant_id: str) -> None:
+def check_ttl_management_task(*, tenant_id: str | None) -> None:
     """Runs periodically to check if any ttl tasks should be run and adds them
     to the queue"""
+    token = None
+    if MULTI_TENANT and tenant_id is not None:
+        token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
 
     settings = load_settings()
     retention_limit_days = settings.maximum_chat_retention_days
-    with get_session_with_current_tenant() as db_session:
+    with get_session_with_tenant(tenant_id) as db_session:
         if should_perform_chat_ttl_check(retention_limit_days, db_session):
             perform_ttl_management_task.apply_async(
                 kwargs=dict(
                     retention_limit_days=retention_limit_days, tenant_id=tenant_id
                 ),
             )
+    if token is not None:
+        CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
 
 
 @celery_app.task(
@@ -71,9 +60,9 @@ def check_ttl_management_task(*, tenant_id: str) -> None:
     ignore_result=True,
     soft_time_limit=JOB_TIMEOUT,
 )
-def autogenerate_usage_report_task(*, tenant_id: str) -> None:
+def autogenerate_usage_report_task(*, tenant_id: str | None) -> None:
     """This generates usage report under the /admin/generate-usage/report endpoint"""
-    with get_session_with_current_tenant() as db_session:
+    with get_session_with_tenant(tenant_id) as db_session:
         create_new_usage_report(
             db_session=db_session,
             user_id=None,

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

@@ -1,46 +1,44 @@
 from datetime import timedelta
 from typing import Any
 
-from onyx.background.celery.tasks.beat_schedule import (
-    beat_cloud_tasks as base_beat_system_tasks,
-)
 from onyx.background.celery.tasks.beat_schedule import BEAT_EXPIRES_DEFAULT
 from onyx.background.celery.tasks.beat_schedule import (
-    beat_task_templates as base_beat_task_templates,
+    cloud_tasks_to_schedule as base_cloud_tasks_to_schedule,
 )
-from onyx.background.celery.tasks.beat_schedule import generate_cloud_tasks
 from onyx.background.celery.tasks.beat_schedule import (
-    get_tasks_to_schedule as base_get_tasks_to_schedule,
+    tasks_to_schedule as base_tasks_to_schedule,
 )
+from onyx.configs.constants import ONYX_CLOUD_CELERY_TASK_PREFIX
 from onyx.configs.constants import OnyxCeleryPriority
 from onyx.configs.constants import OnyxCeleryTask
 from shared_configs.configs import MULTI_TENANT
 
-ee_beat_system_tasks: list[dict] = []
-
-ee_beat_task_templates: list[dict] = []
-ee_beat_task_templates.extend(
-    [
-        {
-            "name": "autogenerate-usage-report",
-            "task": OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
-            "schedule": timedelta(days=30),
-            "options": {
-                "priority": OnyxCeleryPriority.MEDIUM,
-                "expires": BEAT_EXPIRES_DEFAULT,
-            },
+ee_cloud_tasks_to_schedule = [
+    {
+        "name": f"{ONYX_CLOUD_CELERY_TASK_PREFIX}_autogenerate-usage-report",
+        "task": OnyxCeleryTask.CLOUD_BEAT_TASK_GENERATOR,
+        "schedule": timedelta(days=30),
+        "options": {
+            "priority": OnyxCeleryPriority.HIGHEST,
+            "expires": BEAT_EXPIRES_DEFAULT,
         },
-        {
-            "name": "check-ttl-management",
-            "task": OnyxCeleryTask.CHECK_TTL_MANAGEMENT_TASK,
-            "schedule": timedelta(hours=1),
-            "options": {
-                "priority": OnyxCeleryPriority.MEDIUM,
-                "expires": BEAT_EXPIRES_DEFAULT,
-            },
+        "kwargs": {
+            "task_name": OnyxCeleryTask.AUTOGENERATE_USAGE_REPORT_TASK,
         },
-    ]
-)
+    },
+    {
+        "name": f"{ONYX_CLOUD_CELERY_TASK_PREFIX}_check-ttl-management",
+        "task": OnyxCeleryTask.CLOUD_BEAT_TASK_GENERATOR,
+        "schedule": timedelta(hours=1),
+        "options": {
+            "priority": OnyxCeleryPriority.HIGHEST,
+            "expires": BEAT_EXPIRES_DEFAULT,
+        },
+        "kwargs": {
+            "task_name": OnyxCeleryTask.CHECK_TTL_MANAGEMENT_TASK,
+        },
+    },
+]
 
 ee_tasks_to_schedule: list[dict] = []
 
@@ -67,14 +65,9 @@ if not MULTI_TENANT:
     ]
 
 
-def get_cloud_tasks_to_schedule(beat_multiplier: float) -> list[dict[str, Any]]:
-    beat_system_tasks = ee_beat_system_tasks + base_beat_system_tasks
-    beat_task_templates = ee_beat_task_templates + base_beat_task_templates
-    cloud_tasks = generate_cloud_tasks(
-        beat_system_tasks, beat_task_templates, beat_multiplier
-    )
-    return cloud_tasks
+def get_cloud_tasks_to_schedule() -> list[dict[str, Any]]:
+    return ee_cloud_tasks_to_schedule + base_cloud_tasks_to_schedule
 
 
 def get_tasks_to_schedule() -> list[dict[str, Any]]:
-    return ee_tasks_to_schedule + base_get_tasks_to_schedule()
+    return ee_tasks_to_schedule + base_tasks_to_schedule

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

@@ -18,7 +18,7 @@ logger = setup_logger()
 
 
 def monitor_usergroup_taskset(
-    tenant_id: str, key_bytes: bytes, r: Redis, db_session: Session
+    tenant_id: str | None, key_bytes: bytes, r: Redis, db_session: Session
 ) -> None:
     """This function is likely to move in the worker refactor happening next."""
     fence_key = key_bytes.decode("utf-8")

backend/ee/onyx/configs/app_configs.py

@@ -59,14 +59,10 @@ SUPER_CLOUD_API_KEY = os.environ.get("SUPER_CLOUD_API_KEY", "api_key")
 
 OAUTH_SLACK_CLIENT_ID = os.environ.get("OAUTH_SLACK_CLIENT_ID", "")
 OAUTH_SLACK_CLIENT_SECRET = os.environ.get("OAUTH_SLACK_CLIENT_SECRET", "")
-OAUTH_CONFLUENCE_CLOUD_CLIENT_ID = os.environ.get(
-    "OAUTH_CONFLUENCE_CLOUD_CLIENT_ID", ""
-)
-OAUTH_CONFLUENCE_CLOUD_CLIENT_SECRET = os.environ.get(
-    "OAUTH_CONFLUENCE_CLOUD_CLIENT_SECRET", ""
-)
-OAUTH_JIRA_CLOUD_CLIENT_ID = os.environ.get("OAUTH_JIRA_CLOUD_CLIENT_ID", "")
-OAUTH_JIRA_CLOUD_CLIENT_SECRET = os.environ.get("OAUTH_JIRA_CLOUD_CLIENT_SECRET", "")
+OAUTH_CONFLUENCE_CLIENT_ID = os.environ.get("OAUTH_CONFLUENCE_CLIENT_ID", "")
+OAUTH_CONFLUENCE_CLIENT_SECRET = os.environ.get("OAUTH_CONFLUENCE_CLIENT_SECRET", "")
+OAUTH_JIRA_CLIENT_ID = os.environ.get("OAUTH_JIRA_CLIENT_ID", "")
+OAUTH_JIRA_CLIENT_SECRET = os.environ.get("OAUTH_JIRA_CLIENT_SECRET", "")
 OAUTH_GOOGLE_DRIVE_CLIENT_ID = os.environ.get("OAUTH_GOOGLE_DRIVE_CLIENT_ID", "")
 OAUTH_GOOGLE_DRIVE_CLIENT_SECRET = os.environ.get(
     "OAUTH_GOOGLE_DRIVE_CLIENT_SECRET", ""
@@ -81,5 +77,3 @@ POSTHOG_HOST = os.environ.get("POSTHOG_HOST") or "https://us.i.posthog.com"
 HUBSPOT_TRACKING_URL = os.environ.get("HUBSPOT_TRACKING_URL")
 
 ANONYMOUS_USER_COOKIE_NAME = "onyx_anonymous_user"
-
-GATED_TENANTS_KEY = "gated_tenants"

backend/ee/onyx/db/connector_credential_pair.py

@@ -4,7 +4,6 @@ from sqlalchemy.orm import Session
 from onyx.configs.constants import DocumentSource
 from onyx.db.connector_credential_pair import get_connector_credential_pair
 from onyx.db.enums import AccessType
-from onyx.db.enums import ConnectorCredentialPairStatus
 from onyx.db.models import Connector
 from onyx.db.models import ConnectorCredentialPair
 from onyx.db.models import UserGroup__ConnectorCredentialPair
@@ -36,11 +35,10 @@ def _delete_connector_credential_pair_user_groups_relationship__no_commit(
 def get_cc_pairs_by_source(
     db_session: Session,
     source_type: DocumentSource,
-    access_type: AccessType | None = None,
-    status: ConnectorCredentialPairStatus | None = None,
+    only_sync: bool,
 ) -> list[ConnectorCredentialPair]:
     """
-    Get all cc_pairs for a given source type with optional filtering by access_type and status
+    Get all cc_pairs for a given source type (and optionally only sync)
     result is sorted by cc_pair id
     """
     query = (
@@ -50,11 +48,8 @@ def get_cc_pairs_by_source(
         .order_by(ConnectorCredentialPair.id)
     )
 
-    if access_type is not None:
-        query = query.filter(ConnectorCredentialPair.access_type == access_type)
-
-    if status is not None:
-        query = query.filter(ConnectorCredentialPair.status == status)
+    if only_sync:
+        query = query.filter(ConnectorCredentialPair.access_type == AccessType.SYNC)
 
     cc_pairs = query.all()
     return cc_pairs

backend/ee/onyx/db/persona.py

@@ -2,11 +2,8 @@ from uuid import UUID
 
 from sqlalchemy.orm import Session
 
-from onyx.configs.constants import NotificationType
 from onyx.db.models import Persona__User
 from onyx.db.models import Persona__UserGroup
-from onyx.db.notification import create_notification
-from onyx.server.features.persona.models import PersonaSharedNotificationData
 
 
 def make_persona_private(
@@ -15,9 +12,6 @@ def make_persona_private(
     group_ids: list[int] | None,
     db_session: Session,
 ) -> None:
-    """NOTE(rkuo): This function batches all updates into a single commit. If we don't
-    dedupe the inputs, the commit will exception."""
-
     db_session.query(Persona__User).filter(
         Persona__User.persona_id == persona_id
     ).delete(synchronize_session="fetch")
@@ -26,22 +20,11 @@ def make_persona_private(
     ).delete(synchronize_session="fetch")
 
     if user_ids:
-        user_ids_set = set(user_ids)
-        for user_id in user_ids_set:
-            db_session.add(Persona__User(persona_id=persona_id, user_id=user_id))
-
-            create_notification(
-                user_id=user_id,
-                notif_type=NotificationType.PERSONA_SHARED,
-                db_session=db_session,
-                additional_data=PersonaSharedNotificationData(
-                    persona_id=persona_id,
-                ).model_dump(),
-            )
+        for user_uuid in user_ids:
+            db_session.add(Persona__User(persona_id=persona_id, user_id=user_uuid))
 
     if group_ids:
-        group_ids_set = set(group_ids)
-        for group_id in group_ids_set:
+        for group_id in group_ids:
             db_session.add(
                 Persona__UserGroup(persona_id=persona_id, user_group_id=group_id)
             )

backend/ee/onyx/db/query_history.py

@@ -134,9 +134,7 @@ def fetch_chat_sessions_eagerly_by_time(
     limit: int | None = 500,
     initial_time: datetime | None = None,
 ) -> list[ChatSession]:
-    """Sorted by oldest to newest, then by message id"""
-
-    asc_time_order: UnaryExpression = asc(ChatSession.time_created)
+    time_order: UnaryExpression = desc(ChatSession.time_created)
     message_order: UnaryExpression = asc(ChatMessage.id)
 
     filters: list[ColumnElement | BinaryExpression] = [
@@ -149,7 +147,8 @@ def fetch_chat_sessions_eagerly_by_time(
     subquery = (
         db_session.query(ChatSession.id, ChatSession.time_created)
         .filter(*filters)
-        .order_by(asc_time_order)
+        .order_by(ChatSession.id, time_order)
+        .distinct(ChatSession.id)
         .limit(limit)
         .subquery()
     )
@@ -165,7 +164,7 @@ def fetch_chat_sessions_eagerly_by_time(
                 ChatMessage.chat_message_feedbacks
             ),
         )
-        .order_by(asc_time_order, message_order)
+        .order_by(time_order, message_order)
     )
 
     chat_sessions = query.all()

backend/ee/onyx/db/usage_export.py

@@ -16,18 +16,13 @@ from onyx.db.models import UsageReport
 from onyx.file_store.file_store import get_default_file_store
 
 
-# Gets skeletons of all messages in the given range
+# Gets skeletons of all message
 def get_empty_chat_messages_entries__paginated(
     db_session: Session,
     period: tuple[datetime, datetime],
     limit: int | None = 500,
     initial_time: datetime | None = None,
 ) -> tuple[Optional[datetime], list[ChatMessageSkeleton]]:
-    """Returns a tuple where:
-    first element is the most recent timestamp out of the sessions iterated
-    - this timestamp can be used to paginate forward in time
-    second element is a list of messages belonging to all the sessions iterated
-    """
     chat_sessions = fetch_chat_sessions_eagerly_by_time(
         start=period[0],
         end=period[1],
@@ -57,17 +52,18 @@ def get_empty_chat_messages_entries__paginated(
     if len(chat_sessions) == 0:
         return None, []
 
-    return chat_sessions[-1].time_created, message_skeletons
+    return chat_sessions[0].time_created, message_skeletons
 
 
 def get_all_empty_chat_message_entries(
     db_session: Session,
     period: tuple[datetime, datetime],
 ) -> Generator[list[ChatMessageSkeleton], None, None]:
-    """period is the range of time over which to fetch messages."""
     initial_time: Optional[datetime] = period[0]
+    ind = 0
     while True:
-        # iterate from oldest to newest
+        ind += 1
+
         time_created, message_skeletons = get_empty_chat_messages_entries__paginated(
             db_session,
             period,

backend/ee/onyx/db/user_group.py

@@ -218,14 +218,14 @@ def fetch_user_groups_for_user(
     return db_session.scalars(stmt).all()
 
 
-def construct_document_id_select_by_usergroup(
+def construct_document_select_by_usergroup(
     user_group_id: int,
 ) -> Select:
     """This returns a statement that should be executed using
     .yield_per() to minimize overhead. The primary consumers of this function
     are background processing task generators."""
     stmt = (
-        select(Document.id)
+        select(Document)
         .join(
             DocumentByConnectorCredentialPair,
             Document.id == DocumentByConnectorCredentialPair.id,
@@ -424,7 +424,7 @@ def _validate_curator_status__no_commit(
         )
 
         # if the user is a curator in any of their groups, set their role to CURATOR
-        # otherwise, set their role to BASIC only if they were previously a CURATOR
+        # otherwise, set their role to BASIC
         if curator_relationships:
             user.role = UserRole.CURATOR
         elif user.role == UserRole.CURATOR:
@@ -631,16 +631,7 @@ def update_user_group(
     removed_users = db_session.scalars(
         select(User).where(User.id.in_(removed_user_ids))  # type: ignore
     ).unique()
-
-    # Filter out admin and global curator users before validating curator status
-    users_to_validate = [
-        user
-        for user in removed_users
-        if user.role not in [UserRole.ADMIN, UserRole.GLOBAL_CURATOR]
-    ]
-
-    if users_to_validate:
-        _validate_curator_status__no_commit(db_session, users_to_validate)
+    _validate_curator_status__no_commit(db_session, list(removed_users))
 
     # update "time_updated" to now
     db_user_group.time_last_modified_by_user = func.now()

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

@@ -9,16 +9,11 @@ from ee.onyx.external_permissions.confluence.constants import ALL_CONF_EMAILS_GR
 from onyx.access.models import DocExternalAccess
 from onyx.access.models import ExternalAccess
 from onyx.connectors.confluence.connector import ConfluenceConnector
-from onyx.connectors.confluence.onyx_confluence import (
-    get_user_email_from_username__server,
-)
 from onyx.connectors.confluence.onyx_confluence import OnyxConfluence
-from onyx.connectors.credentials_provider import OnyxDBCredentialsProvider
+from onyx.connectors.confluence.utils import get_user_email_from_username__server
 from onyx.connectors.models import SlimDocument
 from onyx.db.models import ConnectorCredentialPair
-from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from onyx.utils.logger import setup_logger
-from shared_configs.contextvars import get_current_tenant_id
 
 logger = setup_logger()
 
@@ -262,7 +257,6 @@ def _fetch_all_page_restrictions(
     slim_docs: list[SlimDocument],
     space_permissions_by_space_key: dict[str, ExternalAccess],
     is_cloud: bool,
-    callback: IndexingHeartbeatInterface | None,
 ) -> list[DocExternalAccess]:
     """
     For all pages, if a page has restrictions, then use those restrictions.
@@ -271,12 +265,6 @@ def _fetch_all_page_restrictions(
     document_restrictions: list[DocExternalAccess] = []
 
     for slim_doc in slim_docs:
-        if callback:
-            if callback.should_stop():
-                raise RuntimeError("confluence_doc_sync: Stop signal detected")
-
-            callback.progress("confluence_doc_sync:fetch_all_page_restrictions", 1)
-
         if slim_doc.perm_sync_data is None:
             raise ValueError(
                 f"No permission sync data found for document {slim_doc.id}"
@@ -347,7 +335,6 @@ def _fetch_all_page_restrictions(
 
 def confluence_doc_sync(
     cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres
@@ -359,11 +346,7 @@ def confluence_doc_sync(
     confluence_connector = ConfluenceConnector(
         **cc_pair.connector.connector_specific_config
     )
-
-    provider = OnyxDBCredentialsProvider(
-        get_current_tenant_id(), "confluence", cc_pair.credential_id
-    )
-    confluence_connector.set_credentials_provider(provider)
+    confluence_connector.load_credentials(cc_pair.credential.credential_json)
 
     is_cloud = cc_pair.connector.connector_specific_config.get("is_cloud", False)
 
@@ -374,16 +357,8 @@ def confluence_doc_sync(
 
     slim_docs = []
     logger.debug("Fetching all slim documents from confluence")
-    for doc_batch in confluence_connector.retrieve_all_slim_documents(
-        callback=callback
-    ):
+    for doc_batch in confluence_connector.retrieve_all_slim_documents():
         logger.debug(f"Got {len(doc_batch)} slim documents from confluence")
-        if callback:
-            if callback.should_stop():
-                raise RuntimeError("confluence_doc_sync: Stop signal detected")
-
-            callback.progress("confluence_doc_sync", 1)
-
         slim_docs.extend(doc_batch)
 
     logger.debug("Fetching all page restrictions for space")
@@ -392,5 +367,4 @@ def confluence_doc_sync(
         slim_docs=slim_docs,
         space_permissions_by_space_key=space_permissions_by_space_key,
         is_cloud=is_cloud,
-        callback=callback,
     )

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

@@ -1,11 +1,8 @@
 from ee.onyx.db.external_perm import ExternalUserGroup
 from ee.onyx.external_permissions.confluence.constants import ALL_CONF_EMAILS_GROUP_NAME
-from onyx.background.error_logging import emit_background_error
-from onyx.connectors.confluence.onyx_confluence import (
-    get_user_email_from_username__server,
-)
+from onyx.connectors.confluence.onyx_confluence import build_confluence_client
 from onyx.connectors.confluence.onyx_confluence import OnyxConfluence
-from onyx.connectors.credentials_provider import OnyxDBCredentialsProvider
+from onyx.connectors.confluence.utils import get_user_email_from_username__server
 from onyx.db.models import ConnectorCredentialPair
 from onyx.utils.logger import setup_logger
 
@@ -13,81 +10,48 @@ logger = setup_logger()
 
 
 def _build_group_member_email_map(
-    confluence_client: OnyxConfluence, cc_pair_id: int
+    confluence_client: OnyxConfluence,
 ) -> dict[str, set[str]]:
     group_member_emails: dict[str, set[str]] = {}
-    for user in confluence_client.paginated_cql_user_retrieval():
-        logger.debug(f"Processing groups for user: {user}")
-
-        email = user.email
+    for user_result in confluence_client.paginated_cql_user_retrieval():
+        user = user_result.get("user", {})
+        if not user:
+            logger.warning(f"user result missing user field: {user_result}")
+            continue
+        email = user.get("email")
         if not email:
             # This field is only present in Confluence Server
-            user_name = user.username
+            user_name = user.get("username")
             # If it is present, try to get the email using a Server-specific method
             if user_name:
                 email = get_user_email_from_username__server(
                     confluence_client=confluence_client,
                     user_name=user_name,
                 )
-
         if not email:
             # If we still don't have an email, skip this user
-            msg = f"user result missing email field: {user}"
-            if user.type == "app":
-                logger.warning(msg)
-            else:
-                emit_background_error(msg, cc_pair_id=cc_pair_id)
-                logger.error(msg)
+            logger.warning(f"user result missing email field: {user_result}")
             continue
 
-        all_users_groups: set[str] = set()
-        for group in confluence_client.paginated_groups_by_user_retrieval(user.user_id):
+        for group in confluence_client.paginated_groups_by_user_retrieval(user):
             # group name uniqueness is enforced by Confluence, so we can use it as a group ID
             group_id = group["name"]
             group_member_emails.setdefault(group_id, set()).add(email)
-            all_users_groups.add(group_id)
-
-        if not all_users_groups:
-            msg = f"No groups found for user with email: {email}"
-            emit_background_error(msg, cc_pair_id=cc_pair_id)
-            logger.error(msg)
-        else:
-            logger.debug(f"Found groups {all_users_groups} for user with email {email}")
-
-    if not group_member_emails:
-        msg = "No groups found for any users."
-        emit_background_error(msg, cc_pair_id=cc_pair_id)
-        logger.error(msg)
 
     return group_member_emails
 
 
 def confluence_group_sync(
-    tenant_id: str,
     cc_pair: ConnectorCredentialPair,
 ) -> list[ExternalUserGroup]:
-    provider = OnyxDBCredentialsProvider(tenant_id, "confluence", cc_pair.credential_id)
-    is_cloud = cc_pair.connector.connector_specific_config.get("is_cloud", False)
-    wiki_base: str = cc_pair.connector.connector_specific_config["wiki_base"]
-    url = wiki_base.rstrip("/")
-
-    probe_kwargs = {
-        "max_backoff_retries": 6,
-        "max_backoff_seconds": 10,
-    }
-
-    final_kwargs = {
-        "max_backoff_retries": 10,
-        "max_backoff_seconds": 60,
-    }
-
-    confluence_client = OnyxConfluence(is_cloud, url, provider)
-    confluence_client._probe_connection(**probe_kwargs)
-    confluence_client._initialize_connection(**final_kwargs)
+    confluence_client = build_confluence_client(
+        credentials=cc_pair.credential.credential_json,
+        is_cloud=cc_pair.connector.connector_specific_config.get("is_cloud", False),
+        wiki_base=cc_pair.connector.connector_specific_config["wiki_base"],
+    )
 
     group_member_email_map = _build_group_member_email_map(
         confluence_client=confluence_client,
-        cc_pair_id=cc_pair.id,
     )
     onyx_groups: list[ExternalUserGroup] = []
     all_found_emails = set()

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

@@ -6,7 +6,6 @@ from onyx.access.models import ExternalAccess
 from onyx.connectors.gmail.connector import GmailConnector
 from onyx.connectors.interfaces import GenerateSlimDocumentOutput
 from onyx.db.models import ConnectorCredentialPair
-from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from onyx.utils.logger import setup_logger
 
 logger = setup_logger()
@@ -15,7 +14,6 @@ logger = setup_logger()
 def _get_slim_doc_generator(
     cc_pair: ConnectorCredentialPair,
     gmail_connector: GmailConnector,
-    callback: IndexingHeartbeatInterface | None = None,
 ) -> GenerateSlimDocumentOutput:
     current_time = datetime.now(timezone.utc)
     start_time = (
@@ -25,15 +23,12 @@ def _get_slim_doc_generator(
     )
 
     return gmail_connector.retrieve_all_slim_documents(
-        start=start_time,
-        end=current_time.timestamp(),
-        callback=callback,
+        start=start_time, end=current_time.timestamp()
     )
 
 
 def gmail_doc_sync(
     cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres
@@ -44,19 +39,11 @@ def gmail_doc_sync(
     gmail_connector = GmailConnector(**cc_pair.connector.connector_specific_config)
     gmail_connector.load_credentials(cc_pair.credential.credential_json)
 
-    slim_doc_generator = _get_slim_doc_generator(
-        cc_pair, gmail_connector, callback=callback
-    )
+    slim_doc_generator = _get_slim_doc_generator(cc_pair, gmail_connector)
 
     document_external_access: list[DocExternalAccess] = []
     for slim_doc_batch in slim_doc_generator:
         for slim_doc in slim_doc_batch:
-            if callback:
-                if callback.should_stop():
-                    raise RuntimeError("gmail_doc_sync: Stop signal detected")
-
-                callback.progress("gmail_doc_sync", 1)
-
             if slim_doc.perm_sync_data is None:
                 logger.warning(f"No permissions found for document {slim_doc.id}")
                 continue

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

@@ -10,7 +10,6 @@ from onyx.connectors.google_utils.resources import get_drive_service
 from onyx.connectors.interfaces import GenerateSlimDocumentOutput
 from onyx.connectors.models import SlimDocument
 from onyx.db.models import ConnectorCredentialPair
-from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from onyx.utils.logger import setup_logger
 
 logger = setup_logger()
@@ -21,7 +20,6 @@ _PERMISSION_ID_PERMISSION_MAP: dict[str, dict[str, Any]] = {}
 def _get_slim_doc_generator(
     cc_pair: ConnectorCredentialPair,
     google_drive_connector: GoogleDriveConnector,
-    callback: IndexingHeartbeatInterface | None = None,
 ) -> GenerateSlimDocumentOutput:
     current_time = datetime.now(timezone.utc)
     start_time = (
@@ -31,9 +29,7 @@ def _get_slim_doc_generator(
     )
 
     return google_drive_connector.retrieve_all_slim_documents(
-        start=start_time,
-        end=current_time.timestamp(),
-        callback=callback,
+        start=start_time, end=current_time.timestamp()
     )
 
 
@@ -62,14 +58,12 @@ def _fetch_permissions_for_permission_ids(
         user_email=(owner_email or google_drive_connector.primary_admin_email),
     )
 
-    # We continue on 404 or 403 because the document may not exist or the user may not have access to it
     fetched_permissions = execute_paginated_retrieval(
         retrieval_function=drive_service.permissions().list,
         list_key="permissions",
         fileId=doc_id,
         fields="permissions(id, emailAddress, type, domain)",
         supportsAllDrives=True,
-        continue_on_404_or_403=True,
     )
 
     permissions_for_doc_id = []
@@ -106,13 +100,7 @@ def _get_permissions_from_slim_doc(
     user_emails: set[str] = set()
     group_emails: set[str] = set()
     public = False
-    skipped_permissions = 0
-
     for permission in permissions_list:
-        if not permission:
-            skipped_permissions += 1
-            continue
-
         permission_type = permission["type"]
         if permission_type == "user":
             user_emails.add(permission["emailAddress"])
@@ -129,11 +117,6 @@ def _get_permissions_from_slim_doc(
         elif permission_type == "anyone":
             public = True
 
-    if skipped_permissions > 0:
-        logger.warning(
-            f"Skipped {skipped_permissions} permissions of {len(permissions_list)} for document {slim_doc.id}"
-        )
-
     drive_id = permission_info.get("drive_id")
     group_ids = group_emails | ({drive_id} if drive_id is not None else set())
 
@@ -146,7 +129,6 @@ def _get_permissions_from_slim_doc(
 
 def gdrive_doc_sync(
     cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres
@@ -164,12 +146,6 @@ def gdrive_doc_sync(
     document_external_accesses = []
     for slim_doc_batch in slim_doc_generator:
         for slim_doc in slim_doc_batch:
-            if callback:
-                if callback.should_stop():
-                    raise RuntimeError("gdrive_doc_sync: Stop signal detected")
-
-                callback.progress("gdrive_doc_sync", 1)
-
             ext_access = _get_permissions_from_slim_doc(
                 google_drive_connector=google_drive_connector,
                 slim_doc=slim_doc,

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

@@ -119,7 +119,6 @@ def _build_onyx_groups(
 
 
 def gdrive_group_sync(
-    tenant_id: str,
     cc_pair: ConnectorCredentialPair,
 ) -> list[ExternalUserGroup]:
     # Initialize connector and build credential/service objects

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

@@ -5,9 +5,8 @@ from onyx.access.models import DocExternalAccess
 from onyx.access.models import ExternalAccess
 from onyx.connectors.slack.connector import get_channels
 from onyx.connectors.slack.connector import make_paginated_slack_api_call_w_retries
-from onyx.connectors.slack.connector import SlackConnector
+from onyx.connectors.slack.connector import SlackPollConnector
 from onyx.db.models import ConnectorCredentialPair
-from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from onyx.utils.logger import setup_logger
 
 
@@ -15,12 +14,12 @@ logger = setup_logger()
 
 
 def _get_slack_document_ids_and_channels(
-    cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
+    cc_pair: ConnectorCredentialPair,
 ) -> dict[str, list[str]]:
-    slack_connector = SlackConnector(**cc_pair.connector.connector_specific_config)
+    slack_connector = SlackPollConnector(**cc_pair.connector.connector_specific_config)
     slack_connector.load_credentials(cc_pair.credential.credential_json)
 
-    slim_doc_generator = slack_connector.retrieve_all_slim_documents(callback=callback)
+    slim_doc_generator = slack_connector.retrieve_all_slim_documents()
 
     channel_doc_map: dict[str, list[str]] = {}
     for doc_metadata_batch in slim_doc_generator:
@@ -32,14 +31,6 @@ def _get_slack_document_ids_and_channels(
                 channel_doc_map[channel_id] = []
             channel_doc_map[channel_id].append(doc_metadata.id)
 
-        if callback:
-            if callback.should_stop():
-                raise RuntimeError(
-                    "_get_slack_document_ids_and_channels: Stop signal detected"
-                )
-
-            callback.progress("_get_slack_document_ids_and_channels", 1)
-
     return channel_doc_map
 
 
@@ -124,7 +115,6 @@ def _fetch_channel_permissions(
 
 def slack_doc_sync(
     cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres
@@ -137,7 +127,7 @@ def slack_doc_sync(
     )
     user_id_to_email_map = fetch_user_id_to_email_map(slack_client)
     channel_doc_map = _get_slack_document_ids_and_channels(
-        cc_pair=cc_pair, callback=callback
+        cc_pair=cc_pair,
     )
     workspace_permissions = _fetch_workspace_permissions(
         user_id_to_email_map=user_id_to_email_map,

backend/ee/onyx/external_permissions/sync_params.py

@@ -15,20 +15,17 @@ from ee.onyx.external_permissions.slack.doc_sync import slack_doc_sync
 from onyx.access.models import DocExternalAccess
 from onyx.configs.constants import DocumentSource
 from onyx.db.models import ConnectorCredentialPair
-from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 
 # Defining the input/output types for the sync functions
 DocSyncFuncType = Callable[
     [
         ConnectorCredentialPair,
-        IndexingHeartbeatInterface | None,
     ],
     list[DocExternalAccess],
 ]
 
 GroupSyncFuncType = Callable[
     [
-        str,
         ConnectorCredentialPair,
     ],
     list[ExternalUserGroup],

backend/ee/onyx/main.py

@@ -15,7 +15,7 @@ from ee.onyx.server.enterprise_settings.api import (
 )
 from ee.onyx.server.manage.standard_answer import router as standard_answer_router
 from ee.onyx.server.middleware.tenant_tracking import add_tenant_id_middleware
-from ee.onyx.server.oauth.api import router as oauth_router
+from ee.onyx.server.oauth import router as oauth_router
 from ee.onyx.server.query_and_chat.chat_backend import (
     router as chat_router,
 )
@@ -152,8 +152,4 @@ def get_application() -> FastAPI:
     # environment variable. Used to automate deployment for multiple environments.
     seed_db()
 
-    # for debugging discovered routes
-    # for route in application.router.routes:
-    #     print(f"Path: {route.path}, Methods: {route.methods}")
-
     return application

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

@@ -22,7 +22,7 @@ from onyx.onyxbot.slack.blocks import get_restate_blocks
 from onyx.onyxbot.slack.constants import GENERATE_ANSWER_BUTTON_ACTION_ID
 from onyx.onyxbot.slack.handlers.utils import send_team_member_message
 from onyx.onyxbot.slack.models import SlackMessageInfo
-from onyx.onyxbot.slack.utils import respond_in_thread_or_channel
+from onyx.onyxbot.slack.utils import respond_in_thread
 from onyx.onyxbot.slack.utils import update_emote_react
 from onyx.utils.logger import OnyxLoggingAdapter
 from onyx.utils.logger import setup_logger
@@ -80,7 +80,7 @@ def oneoff_standard_answers(
 def _handle_standard_answers(
     message_info: SlackMessageInfo,
     receiver_ids: list[str] | None,
-    slack_channel_config: SlackChannelConfig,
+    slack_channel_config: SlackChannelConfig | None,
     prompt: Prompt | None,
     logger: OnyxLoggingAdapter,
     client: WebClient,
@@ -94,10 +94,13 @@ def _handle_standard_answers(
     Returns True if standard answers are found to match the user's message and therefore,
     we still need to respond to the users.
     """
+    # if no channel config, then no standard answers are configured
+    if not slack_channel_config:
+        return False
 
     slack_thread_id = message_info.thread_to_respond
     configured_standard_answer_categories = (
-        slack_channel_config.standard_answer_categories
+        slack_channel_config.standard_answer_categories if slack_channel_config else []
     )
     configured_standard_answers = set(
         [
@@ -216,7 +219,7 @@ def _handle_standard_answers(
         all_blocks = restate_question_blocks + answer_blocks
 
         try:
-            respond_in_thread_or_channel(
+            respond_in_thread(
                 client=client,
                 channel=message_info.channel_to_respond,
                 receiver_ids=receiver_ids,
@@ -231,7 +234,6 @@ def _handle_standard_answers(
                     client=client,
                     channel=message_info.channel_to_respond,
                     thread_ts=slack_thread_id,
-                    receiver_ids=receiver_ids,
                 )
 
             return True

backend/ee/onyx/server/middleware/tenant_tracking.py

@@ -10,7 +10,6 @@ from fastapi import Response
 from ee.onyx.auth.users import decode_anonymous_user_jwt_token
 from ee.onyx.configs.app_configs import ANONYMOUS_USER_COOKIE_NAME
 from onyx.auth.api_key import extract_tenant_from_api_key_header
-from onyx.configs.constants import TENANT_ID_COOKIE_NAME
 from onyx.db.engine import is_valid_schema_name
 from onyx.redis.redis_pool import retrieve_auth_token_data_from_redis
 from shared_configs.configs import MULTI_TENANT
@@ -33,7 +32,7 @@ def add_tenant_id_middleware(app: FastAPI, logger: logging.LoggerAdapter) -> Non
             return await call_next(request)
 
         except Exception as e:
-            logger.exception(f"Error in tenant ID middleware: {str(e)}")
+            logger.error(f"Error in tenant ID middleware: {str(e)}")
             raise
 
 
@@ -44,12 +43,11 @@ async def _get_tenant_id_from_request(
     Attempt to extract tenant_id from:
     1) The API key header
     2) The Redis-based token (stored in Cookie: fastapiusersauth)
-    3)  Reset token cookie
     Fallback: POSTGRES_DEFAULT_SCHEMA
     """
     # Check for API key
     tenant_id = extract_tenant_from_api_key_header(request)
-    if tenant_id is not None:
+    if tenant_id:
         return tenant_id
 
     # Check for anonymous user cookie
@@ -64,7 +62,6 @@ async def _get_tenant_id_from_request(
 
     try:
         # Look up token data in Redis
-
         token_data = await retrieve_auth_token_data_from_redis(request)
 
         if not token_data:
@@ -88,18 +85,8 @@ async def _get_tenant_id_from_request(
         if not is_valid_schema_name(tenant_id):
             raise HTTPException(status_code=400, detail="Invalid tenant ID format")
 
+        return tenant_id
+
     except Exception as e:
         logger.error(f"Unexpected error in _get_tenant_id_from_request: {str(e)}")
         raise HTTPException(status_code=500, detail="Internal server error")
-
-    finally:
-        if tenant_id:
-            return tenant_id
-
-        # As a final step, check for explicit tenant_id cookie
-        tenant_id_cookie = request.cookies.get(TENANT_ID_COOKIE_NAME)
-        if tenant_id_cookie and is_valid_schema_name(tenant_id_cookie):
-            return tenant_id_cookie
-
-        # If we've reached this point, return the default schema
-        return POSTGRES_DEFAULT_SCHEMA

backend/ee/onyx/server/oauth.py

@@ -0,0 +1,629 @@
+import base64
+import json
+import uuid
+from typing import Any
+from typing import cast
+
+import requests
+from fastapi import APIRouter
+from fastapi import Depends
+from fastapi import HTTPException
+from fastapi.responses import JSONResponse
+from pydantic import BaseModel
+from sqlalchemy.orm import Session
+
+from ee.onyx.configs.app_configs import OAUTH_CONFLUENCE_CLIENT_ID
+from ee.onyx.configs.app_configs import OAUTH_CONFLUENCE_CLIENT_SECRET
+from ee.onyx.configs.app_configs import OAUTH_GOOGLE_DRIVE_CLIENT_ID
+from ee.onyx.configs.app_configs import OAUTH_GOOGLE_DRIVE_CLIENT_SECRET
+from ee.onyx.configs.app_configs import OAUTH_SLACK_CLIENT_ID
+from ee.onyx.configs.app_configs import OAUTH_SLACK_CLIENT_SECRET
+from onyx.auth.users import current_user
+from onyx.configs.app_configs import WEB_DOMAIN
+from onyx.configs.constants import DocumentSource
+from onyx.connectors.google_utils.google_auth import get_google_oauth_creds
+from onyx.connectors.google_utils.google_auth import sanitize_oauth_credentials
+from onyx.connectors.google_utils.shared_constants import (
+    DB_CREDENTIALS_AUTHENTICATION_METHOD,
+)
+from onyx.connectors.google_utils.shared_constants import (
+    DB_CREDENTIALS_DICT_TOKEN_KEY,
+)
+from onyx.connectors.google_utils.shared_constants import (
+    DB_CREDENTIALS_PRIMARY_ADMIN_KEY,
+)
+from onyx.connectors.google_utils.shared_constants import (
+    GoogleOAuthAuthenticationMethod,
+)
+from onyx.db.credentials import create_credential
+from onyx.db.engine import get_current_tenant_id
+from onyx.db.engine import get_session
+from onyx.db.models import User
+from onyx.redis.redis_pool import get_redis_client
+from onyx.server.documents.models import CredentialBase
+from onyx.utils.logger import setup_logger
+
+
+logger = setup_logger()
+
+router = APIRouter(prefix="/oauth")
+
+
+class SlackOAuth:
+    # https://knock.app/blog/how-to-authenticate-users-in-slack-using-oauth
+    # Example: https://api.slack.com/authentication/oauth-v2#exchanging
+
+    class OAuthSession(BaseModel):
+        """Stored in redis to be looked up on callback"""
+
+        email: str
+        redirect_on_success: str | None  # Where to send the user if OAuth flow succeeds
+
+    CLIENT_ID = OAUTH_SLACK_CLIENT_ID
+    CLIENT_SECRET = OAUTH_SLACK_CLIENT_SECRET
+
+    TOKEN_URL = "https://slack.com/api/oauth.v2.access"
+
+    # SCOPE is per https://docs.onyx.app/connectors/slack
+    BOT_SCOPE = (
+        "channels:history,"
+        "channels:read,"
+        "groups:history,"
+        "groups:read,"
+        "channels:join,"
+        "im:history,"
+        "users:read,"
+        "users:read.email,"
+        "usergroups:read"
+    )
+
+    REDIRECT_URI = f"{WEB_DOMAIN}/admin/connectors/slack/oauth/callback"
+    DEV_REDIRECT_URI = f"https://redirectmeto.com/{REDIRECT_URI}"
+
+    @classmethod
+    def generate_oauth_url(cls, state: str) -> str:
+        return cls._generate_oauth_url_helper(cls.REDIRECT_URI, state)
+
+    @classmethod
+    def generate_dev_oauth_url(cls, state: str) -> str:
+        """dev mode workaround for localhost testing
+        - https://www.nango.dev/blog/oauth-redirects-on-localhost-with-https
+        """
+
+        return cls._generate_oauth_url_helper(cls.DEV_REDIRECT_URI, state)
+
+    @classmethod
+    def _generate_oauth_url_helper(cls, redirect_uri: str, state: str) -> str:
+        url = (
+            f"https://slack.com/oauth/v2/authorize"
+            f"?client_id={cls.CLIENT_ID}"
+            f"&redirect_uri={redirect_uri}"
+            f"&scope={cls.BOT_SCOPE}"
+            f"&state={state}"
+        )
+        return url
+
+    @classmethod
+    def session_dump_json(cls, email: str, redirect_on_success: str | None) -> str:
+        """Temporary state to store in redis. to be looked up on auth response.
+        Returns a json string.
+        """
+        session = SlackOAuth.OAuthSession(
+            email=email, redirect_on_success=redirect_on_success
+        )
+        return session.model_dump_json()
+
+    @classmethod
+    def parse_session(cls, session_json: str) -> OAuthSession:
+        session = SlackOAuth.OAuthSession.model_validate_json(session_json)
+        return session
+
+
+class ConfluenceCloudOAuth:
+    """work in progress"""
+
+    # https://developer.atlassian.com/cloud/confluence/oauth-2-3lo-apps/
+
+    class OAuthSession(BaseModel):
+        """Stored in redis to be looked up on callback"""
+
+        email: str
+        redirect_on_success: str | None  # Where to send the user if OAuth flow succeeds
+
+    CLIENT_ID = OAUTH_CONFLUENCE_CLIENT_ID
+    CLIENT_SECRET = OAUTH_CONFLUENCE_CLIENT_SECRET
+    TOKEN_URL = "https://auth.atlassian.com/oauth/token"
+
+    # All read scopes per https://developer.atlassian.com/cloud/confluence/scopes-for-oauth-2-3LO-and-forge-apps/
+    CONFLUENCE_OAUTH_SCOPE = (
+        "read:confluence-props%20"
+        "read:confluence-content.all%20"
+        "read:confluence-content.summary%20"
+        "read:confluence-content.permission%20"
+        "read:confluence-user%20"
+        "read:confluence-groups%20"
+        "readonly:content.attachment:confluence"
+    )
+
+    REDIRECT_URI = f"{WEB_DOMAIN}/admin/connectors/confluence/oauth/callback"
+    DEV_REDIRECT_URI = f"https://redirectmeto.com/{REDIRECT_URI}"
+
+    # eventually for Confluence Data Center
+    # oauth_url = (
+    #     f"http://localhost:8090/rest/oauth/v2/authorize?client_id={CONFLUENCE_OAUTH_CLIENT_ID}"
+    #     f"&scope={CONFLUENCE_OAUTH_SCOPE_2}"
+    #     f"&redirect_uri={redirectme_uri}"
+    # )
+
+    @classmethod
+    def generate_oauth_url(cls, state: str) -> str:
+        return cls._generate_oauth_url_helper(cls.REDIRECT_URI, state)
+
+    @classmethod
+    def generate_dev_oauth_url(cls, state: str) -> str:
+        """dev mode workaround for localhost testing
+        - https://www.nango.dev/blog/oauth-redirects-on-localhost-with-https
+        """
+        return cls._generate_oauth_url_helper(cls.DEV_REDIRECT_URI, state)
+
+    @classmethod
+    def _generate_oauth_url_helper(cls, redirect_uri: str, state: str) -> str:
+        url = (
+            "https://auth.atlassian.com/authorize"
+            f"?audience=api.atlassian.com"
+            f"&client_id={cls.CLIENT_ID}"
+            f"&redirect_uri={redirect_uri}"
+            f"&scope={cls.CONFLUENCE_OAUTH_SCOPE}"
+            f"&state={state}"
+            "&response_type=code"
+            "&prompt=consent"
+        )
+        return url
+
+    @classmethod
+    def session_dump_json(cls, email: str, redirect_on_success: str | None) -> str:
+        """Temporary state to store in redis. to be looked up on auth response.
+        Returns a json string.
+        """
+        session = ConfluenceCloudOAuth.OAuthSession(
+            email=email, redirect_on_success=redirect_on_success
+        )
+        return session.model_dump_json()
+
+    @classmethod
+    def parse_session(cls, session_json: str) -> SlackOAuth.OAuthSession:
+        session = SlackOAuth.OAuthSession.model_validate_json(session_json)
+        return session
+
+
+class GoogleDriveOAuth:
+    # https://developers.google.com/identity/protocols/oauth2
+    # https://developers.google.com/identity/protocols/oauth2/web-server
+
+    class OAuthSession(BaseModel):
+        """Stored in redis to be looked up on callback"""
+
+        email: str
+        redirect_on_success: str | None  # Where to send the user if OAuth flow succeeds
+
+    CLIENT_ID = OAUTH_GOOGLE_DRIVE_CLIENT_ID
+    CLIENT_SECRET = OAUTH_GOOGLE_DRIVE_CLIENT_SECRET
+
+    TOKEN_URL = "https://oauth2.googleapis.com/token"
+
+    # SCOPE is per https://docs.onyx.app/connectors/google-drive
+    # TODO: Merge with or use google_utils.GOOGLE_SCOPES
+    SCOPE = (
+        "https://www.googleapis.com/auth/drive.readonly%20"
+        "https://www.googleapis.com/auth/drive.metadata.readonly%20"
+        "https://www.googleapis.com/auth/admin.directory.user.readonly%20"
+        "https://www.googleapis.com/auth/admin.directory.group.readonly"
+    )
+
+    REDIRECT_URI = f"{WEB_DOMAIN}/admin/connectors/google-drive/oauth/callback"
+    DEV_REDIRECT_URI = f"https://redirectmeto.com/{REDIRECT_URI}"
+
+    @classmethod
+    def generate_oauth_url(cls, state: str) -> str:
+        return cls._generate_oauth_url_helper(cls.REDIRECT_URI, state)
+
+    @classmethod
+    def generate_dev_oauth_url(cls, state: str) -> str:
+        """dev mode workaround for localhost testing
+        - https://www.nango.dev/blog/oauth-redirects-on-localhost-with-https
+        """
+
+        return cls._generate_oauth_url_helper(cls.DEV_REDIRECT_URI, state)
+
+    @classmethod
+    def _generate_oauth_url_helper(cls, redirect_uri: str, state: str) -> str:
+        # without prompt=consent, a refresh token is only issued the first time the user approves
+        url = (
+            f"https://accounts.google.com/o/oauth2/v2/auth"
+            f"?client_id={cls.CLIENT_ID}"
+            f"&redirect_uri={redirect_uri}"
+            "&response_type=code"
+            f"&scope={cls.SCOPE}"
+            "&access_type=offline"
+            f"&state={state}"
+            "&prompt=consent"
+        )
+        return url
+
+    @classmethod
+    def session_dump_json(cls, email: str, redirect_on_success: str | None) -> str:
+        """Temporary state to store in redis. to be looked up on auth response.
+        Returns a json string.
+        """
+        session = GoogleDriveOAuth.OAuthSession(
+            email=email, redirect_on_success=redirect_on_success
+        )
+        return session.model_dump_json()
+
+    @classmethod
+    def parse_session(cls, session_json: str) -> OAuthSession:
+        session = GoogleDriveOAuth.OAuthSession.model_validate_json(session_json)
+        return session
+
+
+@router.post("/prepare-authorization-request")
+def prepare_authorization_request(
+    connector: DocumentSource,
+    redirect_on_success: str | None,
+    user: User = Depends(current_user),
+    tenant_id: str | None = Depends(get_current_tenant_id),
+) -> JSONResponse:
+    """Used by the frontend to generate the url for the user's browser during auth request.
+
+    Example: https://www.oauth.com/oauth2-servers/authorization/the-authorization-request/
+    """
+
+    # create random oauth state param for security and to retrieve user data later
+    oauth_uuid = uuid.uuid4()
+    oauth_uuid_str = str(oauth_uuid)
+
+    # urlsafe b64 encode the uuid for the oauth url
+    oauth_state = (
+        base64.urlsafe_b64encode(oauth_uuid.bytes).rstrip(b"=").decode("utf-8")
+    )
+
+    if connector == DocumentSource.SLACK:
+        oauth_url = SlackOAuth.generate_oauth_url(oauth_state)
+        session = SlackOAuth.session_dump_json(
+            email=user.email, redirect_on_success=redirect_on_success
+        )
+    elif connector == DocumentSource.GOOGLE_DRIVE:
+        oauth_url = GoogleDriveOAuth.generate_oauth_url(oauth_state)
+        session = GoogleDriveOAuth.session_dump_json(
+            email=user.email, redirect_on_success=redirect_on_success
+        )
+    # elif connector == DocumentSource.CONFLUENCE:
+    #     oauth_url = ConfluenceCloudOAuth.generate_oauth_url(oauth_state)
+    #     session = ConfluenceCloudOAuth.session_dump_json(
+    #         email=user.email, redirect_on_success=redirect_on_success
+    #     )
+    # elif connector == DocumentSource.JIRA:
+    #     oauth_url = JiraCloudOAuth.generate_dev_oauth_url(oauth_state)
+    else:
+        oauth_url = None
+
+    if not oauth_url:
+        raise HTTPException(
+            status_code=404,
+            detail=f"The document source type {connector} does not have OAuth implemented",
+        )
+
+    r = get_redis_client(tenant_id=tenant_id)
+
+    # store important session state to retrieve when the user is redirected back
+    # 10 min is the max we want an oauth flow to be valid
+    r.set(f"da_oauth:{oauth_uuid_str}", session, ex=600)
+
+    return JSONResponse(content={"url": oauth_url})
+
+
+@router.post("/connector/slack/callback")
+def handle_slack_oauth_callback(
+    code: str,
+    state: str,
+    user: User = Depends(current_user),
+    db_session: Session = Depends(get_session),
+    tenant_id: str | None = Depends(get_current_tenant_id),
+) -> JSONResponse:
+    if not SlackOAuth.CLIENT_ID or not SlackOAuth.CLIENT_SECRET:
+        raise HTTPException(
+            status_code=500,
+            detail="Slack client ID or client secret is not configured.",
+        )
+
+    r = get_redis_client(tenant_id=tenant_id)
+
+    # recover the state
+    padded_state = state + "=" * (
+        -len(state) % 4
+    )  # Add padding back (Base64 decoding requires padding)
+    uuid_bytes = base64.urlsafe_b64decode(
+        padded_state
+    )  # Decode the Base64 string back to bytes
+
+    # Convert bytes back to a UUID
+    oauth_uuid = uuid.UUID(bytes=uuid_bytes)
+    oauth_uuid_str = str(oauth_uuid)
+
+    r_key = f"da_oauth:{oauth_uuid_str}"
+
+    session_json_bytes = cast(bytes, r.get(r_key))
+    if not session_json_bytes:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Slack OAuth failed - OAuth state key not found: key={r_key}",
+        )
+
+    session_json = session_json_bytes.decode("utf-8")
+    try:
+        session = SlackOAuth.parse_session(session_json)
+
+        # Exchange the authorization code for an access token
+        response = requests.post(
+            SlackOAuth.TOKEN_URL,
+            headers={"Content-Type": "application/x-www-form-urlencoded"},
+            data={
+                "client_id": SlackOAuth.CLIENT_ID,
+                "client_secret": SlackOAuth.CLIENT_SECRET,
+                "code": code,
+                "redirect_uri": SlackOAuth.REDIRECT_URI,
+            },
+        )
+
+        response_data = response.json()
+
+        if not response_data.get("ok"):
+            raise HTTPException(
+                status_code=400,
+                detail=f"Slack OAuth failed: {response_data.get('error')}",
+            )
+
+        # Extract token and team information
+        access_token: str = response_data.get("access_token")
+        team_id: str = response_data.get("team", {}).get("id")
+        authed_user_id: str = response_data.get("authed_user", {}).get("id")
+
+        credential_info = CredentialBase(
+            credential_json={"slack_bot_token": access_token},
+            admin_public=True,
+            source=DocumentSource.SLACK,
+            name="Slack OAuth",
+        )
+
+        create_credential(credential_info, user, db_session)
+    except Exception as e:
+        return JSONResponse(
+            status_code=500,
+            content={
+                "success": False,
+                "message": f"An error occurred during Slack OAuth: {str(e)}",
+            },
+        )
+    finally:
+        r.delete(r_key)
+
+    # return the result
+    return JSONResponse(
+        content={
+            "success": True,
+            "message": "Slack OAuth completed successfully.",
+            "team_id": team_id,
+            "authed_user_id": authed_user_id,
+            "redirect_on_success": session.redirect_on_success,
+        }
+    )
+
+
+# Work in progress
+# @router.post("/connector/confluence/callback")
+# def handle_confluence_oauth_callback(
+#     code: str,
+#     state: str,
+#     user: User = Depends(current_user),
+#     db_session: Session = Depends(get_session),
+#     tenant_id: str | None = Depends(get_current_tenant_id),
+# ) -> JSONResponse:
+#     if not ConfluenceCloudOAuth.CLIENT_ID or not ConfluenceCloudOAuth.CLIENT_SECRET:
+#         raise HTTPException(
+#             status_code=500,
+#             detail="Confluence client ID or client secret is not configured."
+#         )
+
+#     r = get_redis_client(tenant_id=tenant_id)
+
+#     # recover the state
+#     padded_state = state + '=' * (-len(state) % 4)  # Add padding back (Base64 decoding requires padding)
+#     uuid_bytes = base64.urlsafe_b64decode(padded_state)  # Decode the Base64 string back to bytes
+
+#     # Convert bytes back to a UUID
+#     oauth_uuid = uuid.UUID(bytes=uuid_bytes)
+#     oauth_uuid_str = str(oauth_uuid)
+
+#     r_key = f"da_oauth:{oauth_uuid_str}"
+
+#     result = r.get(r_key)
+#     if not result:
+#         raise HTTPException(
+#             status_code=400,
+#             detail=f"Confluence OAuth failed - OAuth state key not found: key={r_key}"
+#         )
+
+#     try:
+#         session = ConfluenceCloudOAuth.parse_session(result)
+
+#         # Exchange the authorization code for an access token
+#         response = requests.post(
+#             ConfluenceCloudOAuth.TOKEN_URL,
+#             headers={"Content-Type": "application/x-www-form-urlencoded"},
+#             data={
+#                 "client_id": ConfluenceCloudOAuth.CLIENT_ID,
+#                 "client_secret": ConfluenceCloudOAuth.CLIENT_SECRET,
+#                 "code": code,
+#                 "redirect_uri": ConfluenceCloudOAuth.DEV_REDIRECT_URI,
+#             },
+#         )
+
+#         response_data = response.json()
+
+#         if not response_data.get("ok"):
+#             raise HTTPException(
+#                 status_code=400,
+#                 detail=f"ConfluenceCloudOAuth OAuth failed: {response_data.get('error')}"
+#             )
+
+#         # Extract token and team information
+#         access_token: str = response_data.get("access_token")
+#         team_id: str = response_data.get("team", {}).get("id")
+#         authed_user_id: str = response_data.get("authed_user", {}).get("id")
+
+#         credential_info = CredentialBase(
+#             credential_json={"slack_bot_token": access_token},
+#             admin_public=True,
+#             source=DocumentSource.CONFLUENCE,
+#             name="Confluence OAuth",
+#         )
+
+#         logger.info(f"Slack access token: {access_token}")
+
+#         credential = create_credential(credential_info, user, db_session)
+
+#         logger.info(f"new_credential_id={credential.id}")
+#     except Exception as e:
+#         return JSONResponse(
+#             status_code=500,
+#             content={
+#                 "success": False,
+#                 "message": f"An error occurred during Slack OAuth: {str(e)}",
+#             },
+#         )
+#     finally:
+#         r.delete(r_key)
+
+#     # return the result
+#     return JSONResponse(
+#         content={
+#             "success": True,
+#             "message": "Slack OAuth completed successfully.",
+#             "team_id": team_id,
+#             "authed_user_id": authed_user_id,
+#             "redirect_on_success": session.redirect_on_success,
+#         }
+#     )
+
+
+@router.post("/connector/google-drive/callback")
+def handle_google_drive_oauth_callback(
+    code: str,
+    state: str,
+    user: User = Depends(current_user),
+    db_session: Session = Depends(get_session),
+    tenant_id: str | None = Depends(get_current_tenant_id),
+) -> JSONResponse:
+    if not GoogleDriveOAuth.CLIENT_ID or not GoogleDriveOAuth.CLIENT_SECRET:
+        raise HTTPException(
+            status_code=500,
+            detail="Google Drive client ID or client secret is not configured.",
+        )
+
+    r = get_redis_client(tenant_id=tenant_id)
+
+    # recover the state
+    padded_state = state + "=" * (
+        -len(state) % 4
+    )  # Add padding back (Base64 decoding requires padding)
+    uuid_bytes = base64.urlsafe_b64decode(
+        padded_state
+    )  # Decode the Base64 string back to bytes
+
+    # Convert bytes back to a UUID
+    oauth_uuid = uuid.UUID(bytes=uuid_bytes)
+    oauth_uuid_str = str(oauth_uuid)
+
+    r_key = f"da_oauth:{oauth_uuid_str}"
+
+    session_json_bytes = cast(bytes, r.get(r_key))
+    if not session_json_bytes:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Google Drive OAuth failed - OAuth state key not found: key={r_key}",
+        )
+
+    session_json = session_json_bytes.decode("utf-8")
+    try:
+        session = GoogleDriveOAuth.parse_session(session_json)
+
+        # Exchange the authorization code for an access token
+        response = requests.post(
+            GoogleDriveOAuth.TOKEN_URL,
+            headers={"Content-Type": "application/x-www-form-urlencoded"},
+            data={
+                "client_id": GoogleDriveOAuth.CLIENT_ID,
+                "client_secret": GoogleDriveOAuth.CLIENT_SECRET,
+                "code": code,
+                "redirect_uri": GoogleDriveOAuth.REDIRECT_URI,
+                "grant_type": "authorization_code",
+            },
+        )
+
+        response.raise_for_status()
+
+        authorization_response: dict[str, Any] = response.json()
+
+        # the connector wants us to store the json in its authorized_user_info format
+        # returned from OAuthCredentials.get_authorized_user_info().
+        # So refresh immediately via get_google_oauth_creds with the params filled in
+        # from fields in authorization_response to get the json we need
+        authorized_user_info = {}
+        authorized_user_info["client_id"] = OAUTH_GOOGLE_DRIVE_CLIENT_ID
+        authorized_user_info["client_secret"] = OAUTH_GOOGLE_DRIVE_CLIENT_SECRET
+        authorized_user_info["refresh_token"] = authorization_response["refresh_token"]
+
+        token_json_str = json.dumps(authorized_user_info)
+        oauth_creds = get_google_oauth_creds(
+            token_json_str=token_json_str, source=DocumentSource.GOOGLE_DRIVE
+        )
+        if not oauth_creds:
+            raise RuntimeError("get_google_oauth_creds returned None.")
+
+        # save off the credentials
+        oauth_creds_sanitized_json_str = sanitize_oauth_credentials(oauth_creds)
+
+        credential_dict: dict[str, str] = {}
+        credential_dict[DB_CREDENTIALS_DICT_TOKEN_KEY] = oauth_creds_sanitized_json_str
+        credential_dict[DB_CREDENTIALS_PRIMARY_ADMIN_KEY] = session.email
+        credential_dict[
+            DB_CREDENTIALS_AUTHENTICATION_METHOD
+        ] = GoogleOAuthAuthenticationMethod.OAUTH_INTERACTIVE.value
+
+        credential_info = CredentialBase(
+            credential_json=credential_dict,
+            admin_public=True,
+            source=DocumentSource.GOOGLE_DRIVE,
+            name="OAuth (interactive)",
+        )
+
+        create_credential(credential_info, user, db_session)
+    except Exception as e:
+        return JSONResponse(
+            status_code=500,
+            content={
+                "success": False,
+                "message": f"An error occurred during Google Drive OAuth: {str(e)}",
+            },
+        )
+    finally:
+        r.delete(r_key)
+
+    # return the result
+    return JSONResponse(
+        content={
+            "success": True,
+            "message": "Google Drive OAuth completed successfully.",
+            "redirect_on_success": session.redirect_on_success,
+        }
+    )

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

@@ -1,91 +0,0 @@
-import base64
-import uuid
-
-from fastapi import Depends
-from fastapi import HTTPException
-from fastapi.responses import JSONResponse
-
-from ee.onyx.server.oauth.api_router import router
-from ee.onyx.server.oauth.confluence_cloud import ConfluenceCloudOAuth
-from ee.onyx.server.oauth.google_drive import GoogleDriveOAuth
-from ee.onyx.server.oauth.slack import SlackOAuth
-from onyx.auth.users import current_admin_user
-from onyx.configs.app_configs import DEV_MODE
-from onyx.configs.constants import DocumentSource
-from onyx.db.engine import get_current_tenant_id
-from onyx.db.models import User
-from onyx.redis.redis_pool import get_redis_client
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-@router.post("/prepare-authorization-request")
-def prepare_authorization_request(
-    connector: DocumentSource,
-    redirect_on_success: str | None,
-    user: User = Depends(current_admin_user),
-    tenant_id: str | None = Depends(get_current_tenant_id),
-) -> JSONResponse:
-    """Used by the frontend to generate the url for the user's browser during auth request.
-
-    Example: https://www.oauth.com/oauth2-servers/authorization/the-authorization-request/
-    """
-
-    # create random oauth state param for security and to retrieve user data later
-    oauth_uuid = uuid.uuid4()
-    oauth_uuid_str = str(oauth_uuid)
-
-    # urlsafe b64 encode the uuid for the oauth url
-    oauth_state = (
-        base64.urlsafe_b64encode(oauth_uuid.bytes).rstrip(b"=").decode("utf-8")
-    )
-
-    session: str | None = None
-    if connector == DocumentSource.SLACK:
-        if not DEV_MODE:
-            oauth_url = SlackOAuth.generate_oauth_url(oauth_state)
-        else:
-            oauth_url = SlackOAuth.generate_dev_oauth_url(oauth_state)
-
-        session = SlackOAuth.session_dump_json(
-            email=user.email, redirect_on_success=redirect_on_success
-        )
-    elif connector == DocumentSource.CONFLUENCE:
-        if not DEV_MODE:
-            oauth_url = ConfluenceCloudOAuth.generate_oauth_url(oauth_state)
-        else:
-            oauth_url = ConfluenceCloudOAuth.generate_dev_oauth_url(oauth_state)
-        session = ConfluenceCloudOAuth.session_dump_json(
-            email=user.email, redirect_on_success=redirect_on_success
-        )
-    elif connector == DocumentSource.GOOGLE_DRIVE:
-        if not DEV_MODE:
-            oauth_url = GoogleDriveOAuth.generate_oauth_url(oauth_state)
-        else:
-            oauth_url = GoogleDriveOAuth.generate_dev_oauth_url(oauth_state)
-        session = GoogleDriveOAuth.session_dump_json(
-            email=user.email, redirect_on_success=redirect_on_success
-        )
-    else:
-        oauth_url = None
-
-    if not oauth_url:
-        raise HTTPException(
-            status_code=404,
-            detail=f"The document source type {connector} does not have OAuth implemented",
-        )
-
-    if not session:
-        raise HTTPException(
-            status_code=500,
-            detail=f"The document source type {connector} failed to generate an OAuth session.",
-        )
-
-    r = get_redis_client(tenant_id=tenant_id)
-
-    # store important session state to retrieve when the user is redirected back
-    # 10 min is the max we want an oauth flow to be valid
-    r.set(f"da_oauth:{oauth_uuid_str}", session, ex=600)
-
-    return JSONResponse(content={"url": oauth_url})

backend/ee/onyx/server/oauth/api_router.py

@@ -1,3 +0,0 @@
-from fastapi import APIRouter
-
-router: APIRouter = APIRouter(prefix="/oauth")

backend/ee/onyx/server/oauth/confluence_cloud.py

@@ -1,361 +0,0 @@
-import base64
-import uuid
-from datetime import datetime
-from datetime import timedelta
-from datetime import timezone
-from typing import Any
-from typing import cast
-
-import requests
-from fastapi import Depends
-from fastapi import HTTPException
-from fastapi.responses import JSONResponse
-from pydantic import BaseModel
-from pydantic import ValidationError
-from sqlalchemy.orm import Session
-
-from ee.onyx.configs.app_configs import OAUTH_CONFLUENCE_CLOUD_CLIENT_ID
-from ee.onyx.configs.app_configs import OAUTH_CONFLUENCE_CLOUD_CLIENT_SECRET
-from ee.onyx.server.oauth.api_router import router
-from onyx.auth.users import current_admin_user
-from onyx.configs.app_configs import DEV_MODE
-from onyx.configs.app_configs import WEB_DOMAIN
-from onyx.configs.constants import DocumentSource
-from onyx.connectors.confluence.utils import CONFLUENCE_OAUTH_TOKEN_URL
-from onyx.db.credentials import create_credential
-from onyx.db.credentials import fetch_credential_by_id_for_user
-from onyx.db.credentials import update_credential_json
-from onyx.db.engine import get_current_tenant_id
-from onyx.db.engine import get_session
-from onyx.db.models import User
-from onyx.redis.redis_pool import get_redis_client
-from onyx.server.documents.models import CredentialBase
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-
-class ConfluenceCloudOAuth:
-    # https://developer.atlassian.com/cloud/confluence/oauth-2-3lo-apps/
-
-    class OAuthSession(BaseModel):
-        """Stored in redis to be looked up on callback"""
-
-        email: str
-        redirect_on_success: str | None  # Where to send the user if OAuth flow succeeds
-
-    class TokenResponse(BaseModel):
-        access_token: str
-        expires_in: int
-        token_type: str
-        refresh_token: str
-        scope: str
-
-    class AccessibleResources(BaseModel):
-        id: str
-        name: str
-        url: str
-        scopes: list[str]
-        avatarUrl: str
-
-    CLIENT_ID = OAUTH_CONFLUENCE_CLOUD_CLIENT_ID
-    CLIENT_SECRET = OAUTH_CONFLUENCE_CLOUD_CLIENT_SECRET
-    TOKEN_URL = CONFLUENCE_OAUTH_TOKEN_URL
-
-    ACCESSIBLE_RESOURCE_URL = (
-        "https://api.atlassian.com/oauth/token/accessible-resources"
-    )
-
-    # All read scopes per https://developer.atlassian.com/cloud/confluence/scopes-for-oauth-2-3LO-and-forge-apps/
-    CONFLUENCE_OAUTH_SCOPE = (
-        # classic scope
-        "read:confluence-space.summary%20"
-        "read:confluence-props%20"
-        "read:confluence-content.all%20"
-        "read:confluence-content.summary%20"
-        "read:confluence-content.permission%20"
-        "read:confluence-user%20"
-        "read:confluence-groups%20"
-        "readonly:content.attachment:confluence%20"
-        "search:confluence%20"
-        # granular scope
-        "read:attachment:confluence%20"  # possibly unneeded unless calling v2 attachments api
-        "offline_access"
-    )
-
-    REDIRECT_URI = f"{WEB_DOMAIN}/admin/connectors/confluence/oauth/callback"
-    DEV_REDIRECT_URI = f"https://redirectmeto.com/{REDIRECT_URI}"
-
-    # eventually for Confluence Data Center
-    # oauth_url = (
-    #     f"http://localhost:8090/rest/oauth/v2/authorize?client_id={CONFLUENCE_OAUTH_CLIENT_ID}"
-    #     f"&scope={CONFLUENCE_OAUTH_SCOPE_2}"
-    #     f"&redirect_uri={redirectme_uri}"
-    # )
-
-    @classmethod
-    def generate_oauth_url(cls, state: str) -> str:
-        return cls._generate_oauth_url_helper(cls.REDIRECT_URI, state)
-
-    @classmethod
-    def generate_dev_oauth_url(cls, state: str) -> str:
-        """dev mode workaround for localhost testing
-        - https://www.nango.dev/blog/oauth-redirects-on-localhost-with-https
-        """
-        return cls._generate_oauth_url_helper(cls.DEV_REDIRECT_URI, state)
-
-    @classmethod
-    def _generate_oauth_url_helper(cls, redirect_uri: str, state: str) -> str:
-        # https://developer.atlassian.com/cloud/jira/platform/oauth-2-3lo-apps/#1--direct-the-user-to-the-authorization-url-to-get-an-authorization-code
-
-        url = (
-            "https://auth.atlassian.com/authorize"
-            f"?audience=api.atlassian.com"
-            f"&client_id={cls.CLIENT_ID}"
-            f"&scope={cls.CONFLUENCE_OAUTH_SCOPE}"
-            f"&redirect_uri={redirect_uri}"
-            f"&state={state}"
-            "&response_type=code"
-            "&prompt=consent"
-        )
-        return url
-
-    @classmethod
-    def session_dump_json(cls, email: str, redirect_on_success: str | None) -> str:
-        """Temporary state to store in redis. to be looked up on auth response.
-        Returns a json string.
-        """
-        session = ConfluenceCloudOAuth.OAuthSession(
-            email=email, redirect_on_success=redirect_on_success
-        )
-        return session.model_dump_json()
-
-    @classmethod
-    def parse_session(cls, session_json: str) -> OAuthSession:
-        session = ConfluenceCloudOAuth.OAuthSession.model_validate_json(session_json)
-        return session
-
-    @classmethod
-    def generate_finalize_url(cls, credential_id: int) -> str:
-        return f"{WEB_DOMAIN}/admin/connectors/confluence/oauth/finalize?credential={credential_id}"
-
-
-@router.post("/connector/confluence/callback")
-def confluence_oauth_callback(
-    code: str,
-    state: str,
-    user: User = Depends(current_admin_user),
-    db_session: Session = Depends(get_session),
-    tenant_id: str | None = Depends(get_current_tenant_id),
-) -> JSONResponse:
-    """Handles the backend logic for the frontend page that the user is redirected to
-    after visiting the oauth authorization url."""
-
-    if not ConfluenceCloudOAuth.CLIENT_ID or not ConfluenceCloudOAuth.CLIENT_SECRET:
-        raise HTTPException(
-            status_code=500,
-            detail="Confluence Cloud client ID or client secret is not configured.",
-        )
-
-    r = get_redis_client(tenant_id=tenant_id)
-
-    # recover the state
-    padded_state = state + "=" * (
-        -len(state) % 4
-    )  # Add padding back (Base64 decoding requires padding)
-    uuid_bytes = base64.urlsafe_b64decode(
-        padded_state
-    )  # Decode the Base64 string back to bytes
-
-    # Convert bytes back to a UUID
-    oauth_uuid = uuid.UUID(bytes=uuid_bytes)
-    oauth_uuid_str = str(oauth_uuid)
-
-    r_key = f"da_oauth:{oauth_uuid_str}"
-
-    session_json_bytes = cast(bytes, r.get(r_key))
-    if not session_json_bytes:
-        raise HTTPException(
-            status_code=400,
-            detail=f"Confluence Cloud OAuth failed - OAuth state key not found: key={r_key}",
-        )
-
-    session_json = session_json_bytes.decode("utf-8")
-    try:
-        session = ConfluenceCloudOAuth.parse_session(session_json)
-
-        if not DEV_MODE:
-            redirect_uri = ConfluenceCloudOAuth.REDIRECT_URI
-        else:
-            redirect_uri = ConfluenceCloudOAuth.DEV_REDIRECT_URI
-
-        # Exchange the authorization code for an access token
-        response = requests.post(
-            ConfluenceCloudOAuth.TOKEN_URL,
-            headers={"Content-Type": "application/x-www-form-urlencoded"},
-            data={
-                "client_id": ConfluenceCloudOAuth.CLIENT_ID,
-                "client_secret": ConfluenceCloudOAuth.CLIENT_SECRET,
-                "code": code,
-                "redirect_uri": redirect_uri,
-                "grant_type": "authorization_code",
-            },
-        )
-
-        token_response: ConfluenceCloudOAuth.TokenResponse | None = None
-
-        try:
-            token_response = ConfluenceCloudOAuth.TokenResponse.model_validate_json(
-                response.text
-            )
-        except Exception:
-            raise RuntimeError(
-                "Confluence Cloud OAuth failed during code/token exchange."
-            )
-
-        now = datetime.now(timezone.utc)
-        expires_at = now + timedelta(seconds=token_response.expires_in)
-
-        credential_info = CredentialBase(
-            credential_json={
-                "confluence_access_token": token_response.access_token,
-                "confluence_refresh_token": token_response.refresh_token,
-                "created_at": now.isoformat(),
-                "expires_at": expires_at.isoformat(),
-                "expires_in": token_response.expires_in,
-                "scope": token_response.scope,
-            },
-            admin_public=True,
-            source=DocumentSource.CONFLUENCE,
-            name="Confluence Cloud OAuth",
-        )
-
-        credential = create_credential(credential_info, user, db_session)
-    except Exception as e:
-        return JSONResponse(
-            status_code=500,
-            content={
-                "success": False,
-                "message": f"An error occurred during Confluence Cloud OAuth: {str(e)}",
-            },
-        )
-    finally:
-        r.delete(r_key)
-
-    # return the result
-    return JSONResponse(
-        content={
-            "success": True,
-            "message": "Confluence Cloud OAuth completed successfully.",
-            "finalize_url": ConfluenceCloudOAuth.generate_finalize_url(credential.id),
-            "redirect_on_success": session.redirect_on_success,
-        }
-    )
-
-
-@router.get("/connector/confluence/accessible-resources")
-def confluence_oauth_accessible_resources(
-    credential_id: int,
-    user: User = Depends(current_admin_user),
-    db_session: Session = Depends(get_session),
-    tenant_id: str | None = Depends(get_current_tenant_id),
-) -> JSONResponse:
-    """Atlassian's API is weird and does not supply us with enough info to be in a
-    usable state after authorizing.  All API's require a cloud id. We have to list
-    the accessible resources/sites and let the user choose which site to use."""
-
-    credential = fetch_credential_by_id_for_user(credential_id, user, db_session)
-    if not credential:
-        raise HTTPException(400, f"Credential {credential_id} not found.")
-
-    credential_dict = credential.credential_json
-    access_token = credential_dict["confluence_access_token"]
-
-    try:
-        # Exchange the authorization code for an access token
-        response = requests.get(
-            ConfluenceCloudOAuth.ACCESSIBLE_RESOURCE_URL,
-            headers={
-                "Authorization": f"Bearer {access_token}",
-                "Accept": "application/json",
-            },
-        )
-
-        response.raise_for_status()
-        accessible_resources_data = response.json()
-
-        # Validate the list of AccessibleResources
-        try:
-            accessible_resources = [
-                ConfluenceCloudOAuth.AccessibleResources(**resource)
-                for resource in accessible_resources_data
-            ]
-        except ValidationError as e:
-            raise RuntimeError(f"Failed to parse accessible resources: {e}")
-    except Exception as e:
-        return JSONResponse(
-            status_code=500,
-            content={
-                "success": False,
-                "message": f"An error occurred retrieving Confluence Cloud accessible resources: {str(e)}",
-            },
-        )
-
-    # return the result
-    return JSONResponse(
-        content={
-            "success": True,
-            "message": "Confluence Cloud get accessible resources completed successfully.",
-            "accessible_resources": [
-                resource.model_dump() for resource in accessible_resources
-            ],
-        }
-    )
-
-
-@router.post("/connector/confluence/finalize")
-def confluence_oauth_finalize(
-    credential_id: int,
-    cloud_id: str,
-    cloud_name: str,
-    cloud_url: str,
-    user: User = Depends(current_admin_user),
-    db_session: Session = Depends(get_session),
-    tenant_id: str | None = Depends(get_current_tenant_id),
-) -> JSONResponse:
-    """Saves the info for the selected cloud site to the credential.
-    This is the final step in the confluence oauth flow where after the traditional
-    OAuth process, the user has to select a site to associate with the credentials.
-    After this, the credential is usable."""
-
-    credential = fetch_credential_by_id_for_user(credential_id, user, db_session)
-    if not credential:
-        raise HTTPException(
-            status_code=400,
-            detail=f"Confluence Cloud OAuth failed - credential {credential_id} not found.",
-        )
-
-    new_credential_json: dict[str, Any] = dict(credential.credential_json)
-    new_credential_json["cloud_id"] = cloud_id
-    new_credential_json["cloud_name"] = cloud_name
-    new_credential_json["wiki_base"] = cloud_url
-
-    try:
-        update_credential_json(credential_id, new_credential_json, user, db_session)
-    except Exception as e:
-        return JSONResponse(
-            status_code=500,
-            content={
-                "success": False,
-                "message": f"An error occurred during Confluence Cloud OAuth: {str(e)}",
-            },
-        )
-
-    # return the result
-    return JSONResponse(
-        content={
-            "success": True,
-            "message": "Confluence Cloud OAuth finalized successfully.",
-            "redirect_url": f"{WEB_DOMAIN}/admin/connectors/confluence",
-        }
-    )

backend/ee/onyx/server/oauth/google_drive.py

@@ -1,229 +0,0 @@
-import base64
-import json
-import uuid
-from typing import Any
-from typing import cast
-
-import requests
-from fastapi import Depends
-from fastapi import HTTPException
-from fastapi.responses import JSONResponse
-from pydantic import BaseModel
-from sqlalchemy.orm import Session
-
-from ee.onyx.configs.app_configs import OAUTH_GOOGLE_DRIVE_CLIENT_ID
-from ee.onyx.configs.app_configs import OAUTH_GOOGLE_DRIVE_CLIENT_SECRET
-from ee.onyx.server.oauth.api_router import router
-from onyx.auth.users import current_admin_user
-from onyx.configs.app_configs import DEV_MODE
-from onyx.configs.app_configs import WEB_DOMAIN
-from onyx.configs.constants import DocumentSource
-from onyx.connectors.google_utils.google_auth import get_google_oauth_creds
-from onyx.connectors.google_utils.google_auth import sanitize_oauth_credentials
-from onyx.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_AUTHENTICATION_METHOD,
-)
-from onyx.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_DICT_TOKEN_KEY,
-)
-from onyx.connectors.google_utils.shared_constants import (
-    DB_CREDENTIALS_PRIMARY_ADMIN_KEY,
-)
-from onyx.connectors.google_utils.shared_constants import (
-    GoogleOAuthAuthenticationMethod,
-)
-from onyx.db.credentials import create_credential
-from onyx.db.engine import get_current_tenant_id
-from onyx.db.engine import get_session
-from onyx.db.models import User
-from onyx.redis.redis_pool import get_redis_client
-from onyx.server.documents.models import CredentialBase
-
-
-class GoogleDriveOAuth:
-    # https://developers.google.com/identity/protocols/oauth2
-    # https://developers.google.com/identity/protocols/oauth2/web-server
-
-    class OAuthSession(BaseModel):
-        """Stored in redis to be looked up on callback"""
-
-        email: str
-        redirect_on_success: str | None  # Where to send the user if OAuth flow succeeds
-
-    CLIENT_ID = OAUTH_GOOGLE_DRIVE_CLIENT_ID
-    CLIENT_SECRET = OAUTH_GOOGLE_DRIVE_CLIENT_SECRET
-
-    TOKEN_URL = "https://oauth2.googleapis.com/token"
-
-    # SCOPE is per https://docs.danswer.dev/connectors/google-drive
-    # TODO: Merge with or use google_utils.GOOGLE_SCOPES
-    SCOPE = (
-        "https://www.googleapis.com/auth/drive.readonly%20"
-        "https://www.googleapis.com/auth/drive.metadata.readonly%20"
-        "https://www.googleapis.com/auth/admin.directory.user.readonly%20"
-        "https://www.googleapis.com/auth/admin.directory.group.readonly"
-    )
-
-    REDIRECT_URI = f"{WEB_DOMAIN}/admin/connectors/google-drive/oauth/callback"
-    DEV_REDIRECT_URI = f"https://redirectmeto.com/{REDIRECT_URI}"
-
-    @classmethod
-    def generate_oauth_url(cls, state: str) -> str:
-        return cls._generate_oauth_url_helper(cls.REDIRECT_URI, state)
-
-    @classmethod
-    def generate_dev_oauth_url(cls, state: str) -> str:
-        """dev mode workaround for localhost testing
-        - https://www.nango.dev/blog/oauth-redirects-on-localhost-with-https
-        """
-
-        return cls._generate_oauth_url_helper(cls.DEV_REDIRECT_URI, state)
-
-    @classmethod
-    def _generate_oauth_url_helper(cls, redirect_uri: str, state: str) -> str:
-        # without prompt=consent, a refresh token is only issued the first time the user approves
-        url = (
-            f"https://accounts.google.com/o/oauth2/v2/auth"
-            f"?client_id={cls.CLIENT_ID}"
-            f"&redirect_uri={redirect_uri}"
-            "&response_type=code"
-            f"&scope={cls.SCOPE}"
-            "&access_type=offline"
-            f"&state={state}"
-            "&prompt=consent"
-        )
-        return url
-
-    @classmethod
-    def session_dump_json(cls, email: str, redirect_on_success: str | None) -> str:
-        """Temporary state to store in redis. to be looked up on auth response.
-        Returns a json string.
-        """
-        session = GoogleDriveOAuth.OAuthSession(
-            email=email, redirect_on_success=redirect_on_success
-        )
-        return session.model_dump_json()
-
-    @classmethod
-    def parse_session(cls, session_json: str) -> OAuthSession:
-        session = GoogleDriveOAuth.OAuthSession.model_validate_json(session_json)
-        return session
-
-
-@router.post("/connector/google-drive/callback")
-def handle_google_drive_oauth_callback(
-    code: str,
-    state: str,
-    user: User = Depends(current_admin_user),
-    db_session: Session = Depends(get_session),
-    tenant_id: str | None = Depends(get_current_tenant_id),
-) -> JSONResponse:
-    if not GoogleDriveOAuth.CLIENT_ID or not GoogleDriveOAuth.CLIENT_SECRET:
-        raise HTTPException(
-            status_code=500,
-            detail="Google Drive client ID or client secret is not configured.",
-        )
-
-    r = get_redis_client(tenant_id=tenant_id)
-
-    # recover the state
-    padded_state = state + "=" * (
-        -len(state) % 4
-    )  # Add padding back (Base64 decoding requires padding)
-    uuid_bytes = base64.urlsafe_b64decode(
-        padded_state
-    )  # Decode the Base64 string back to bytes
-
-    # Convert bytes back to a UUID
-    oauth_uuid = uuid.UUID(bytes=uuid_bytes)
-    oauth_uuid_str = str(oauth_uuid)
-
-    r_key = f"da_oauth:{oauth_uuid_str}"
-
-    session_json_bytes = cast(bytes, r.get(r_key))
-    if not session_json_bytes:
-        raise HTTPException(
-            status_code=400,
-            detail=f"Google Drive OAuth failed - OAuth state key not found: key={r_key}",
-        )
-
-    session_json = session_json_bytes.decode("utf-8")
-    try:
-        session = GoogleDriveOAuth.parse_session(session_json)
-
-        if not DEV_MODE:
-            redirect_uri = GoogleDriveOAuth.REDIRECT_URI
-        else:
-            redirect_uri = GoogleDriveOAuth.DEV_REDIRECT_URI
-
-        # Exchange the authorization code for an access token
-        response = requests.post(
-            GoogleDriveOAuth.TOKEN_URL,
-            headers={"Content-Type": "application/x-www-form-urlencoded"},
-            data={
-                "client_id": GoogleDriveOAuth.CLIENT_ID,
-                "client_secret": GoogleDriveOAuth.CLIENT_SECRET,
-                "code": code,
-                "redirect_uri": redirect_uri,
-                "grant_type": "authorization_code",
-            },
-        )
-
-        response.raise_for_status()
-
-        authorization_response: dict[str, Any] = response.json()
-
-        # the connector wants us to store the json in its authorized_user_info format
-        # returned from OAuthCredentials.get_authorized_user_info().
-        # So refresh immediately via get_google_oauth_creds with the params filled in
-        # from fields in authorization_response to get the json we need
-        authorized_user_info = {}
-        authorized_user_info["client_id"] = OAUTH_GOOGLE_DRIVE_CLIENT_ID
-        authorized_user_info["client_secret"] = OAUTH_GOOGLE_DRIVE_CLIENT_SECRET
-        authorized_user_info["refresh_token"] = authorization_response["refresh_token"]
-
-        token_json_str = json.dumps(authorized_user_info)
-        oauth_creds = get_google_oauth_creds(
-            token_json_str=token_json_str, source=DocumentSource.GOOGLE_DRIVE
-        )
-        if not oauth_creds:
-            raise RuntimeError("get_google_oauth_creds returned None.")
-
-        # save off the credentials
-        oauth_creds_sanitized_json_str = sanitize_oauth_credentials(oauth_creds)
-
-        credential_dict: dict[str, str] = {}
-        credential_dict[DB_CREDENTIALS_DICT_TOKEN_KEY] = oauth_creds_sanitized_json_str
-        credential_dict[DB_CREDENTIALS_PRIMARY_ADMIN_KEY] = session.email
-        credential_dict[
-            DB_CREDENTIALS_AUTHENTICATION_METHOD
-        ] = GoogleOAuthAuthenticationMethod.OAUTH_INTERACTIVE.value
-
-        credential_info = CredentialBase(
-            credential_json=credential_dict,
-            admin_public=True,
-            source=DocumentSource.GOOGLE_DRIVE,
-            name="OAuth (interactive)",
-        )
-
-        create_credential(credential_info, user, db_session)
-    except Exception as e:
-        return JSONResponse(
-            status_code=500,
-            content={
-                "success": False,
-                "message": f"An error occurred during Google Drive OAuth: {str(e)}",
-            },
-        )
-    finally:
-        r.delete(r_key)
-
-    # return the result
-    return JSONResponse(
-        content={
-            "success": True,
-            "message": "Google Drive OAuth completed successfully.",
-            "finalize_url": None,
-            "redirect_on_success": session.redirect_on_success,
-        }
-    )

backend/ee/onyx/server/oauth/slack.py

@@ -1,197 +0,0 @@
-import base64
-import uuid
-from typing import cast
-
-import requests
-from fastapi import Depends
-from fastapi import HTTPException
-from fastapi.responses import JSONResponse
-from pydantic import BaseModel
-from sqlalchemy.orm import Session
-
-from ee.onyx.configs.app_configs import OAUTH_SLACK_CLIENT_ID
-from ee.onyx.configs.app_configs import OAUTH_SLACK_CLIENT_SECRET
-from ee.onyx.server.oauth.api_router import router
-from onyx.auth.users import current_admin_user
-from onyx.configs.app_configs import DEV_MODE
-from onyx.configs.app_configs import WEB_DOMAIN
-from onyx.configs.constants import DocumentSource
-from onyx.db.credentials import create_credential
-from onyx.db.engine import get_current_tenant_id
-from onyx.db.engine import get_session
-from onyx.db.models import User
-from onyx.redis.redis_pool import get_redis_client
-from onyx.server.documents.models import CredentialBase
-
-
-class SlackOAuth:
-    # https://knock.app/blog/how-to-authenticate-users-in-slack-using-oauth
-    # Example: https://api.slack.com/authentication/oauth-v2#exchanging
-
-    class OAuthSession(BaseModel):
-        """Stored in redis to be looked up on callback"""
-
-        email: str
-        redirect_on_success: str | None  # Where to send the user if OAuth flow succeeds
-
-    CLIENT_ID = OAUTH_SLACK_CLIENT_ID
-    CLIENT_SECRET = OAUTH_SLACK_CLIENT_SECRET
-
-    TOKEN_URL = "https://slack.com/api/oauth.v2.access"
-
-    # SCOPE is per https://docs.danswer.dev/connectors/slack
-    BOT_SCOPE = (
-        "channels:history,"
-        "channels:read,"
-        "groups:history,"
-        "groups:read,"
-        "channels:join,"
-        "im:history,"
-        "users:read,"
-        "users:read.email,"
-        "usergroups:read"
-    )
-
-    REDIRECT_URI = f"{WEB_DOMAIN}/admin/connectors/slack/oauth/callback"
-    DEV_REDIRECT_URI = f"https://redirectmeto.com/{REDIRECT_URI}"
-
-    @classmethod
-    def generate_oauth_url(cls, state: str) -> str:
-        return cls._generate_oauth_url_helper(cls.REDIRECT_URI, state)
-
-    @classmethod
-    def generate_dev_oauth_url(cls, state: str) -> str:
-        """dev mode workaround for localhost testing
-        - https://www.nango.dev/blog/oauth-redirects-on-localhost-with-https
-        """
-
-        return cls._generate_oauth_url_helper(cls.DEV_REDIRECT_URI, state)
-
-    @classmethod
-    def _generate_oauth_url_helper(cls, redirect_uri: str, state: str) -> str:
-        url = (
-            f"https://slack.com/oauth/v2/authorize"
-            f"?client_id={cls.CLIENT_ID}"
-            f"&redirect_uri={redirect_uri}"
-            f"&scope={cls.BOT_SCOPE}"
-            f"&state={state}"
-        )
-        return url
-
-    @classmethod
-    def session_dump_json(cls, email: str, redirect_on_success: str | None) -> str:
-        """Temporary state to store in redis. to be looked up on auth response.
-        Returns a json string.
-        """
-        session = SlackOAuth.OAuthSession(
-            email=email, redirect_on_success=redirect_on_success
-        )
-        return session.model_dump_json()
-
-    @classmethod
-    def parse_session(cls, session_json: str) -> OAuthSession:
-        session = SlackOAuth.OAuthSession.model_validate_json(session_json)
-        return session
-
-
-@router.post("/connector/slack/callback")
-def handle_slack_oauth_callback(
-    code: str,
-    state: str,
-    user: User = Depends(current_admin_user),
-    db_session: Session = Depends(get_session),
-    tenant_id: str | None = Depends(get_current_tenant_id),
-) -> JSONResponse:
-    if not SlackOAuth.CLIENT_ID or not SlackOAuth.CLIENT_SECRET:
-        raise HTTPException(
-            status_code=500,
-            detail="Slack client ID or client secret is not configured.",
-        )
-
-    r = get_redis_client(tenant_id=tenant_id)
-
-    # recover the state
-    padded_state = state + "=" * (
-        -len(state) % 4
-    )  # Add padding back (Base64 decoding requires padding)
-    uuid_bytes = base64.urlsafe_b64decode(
-        padded_state
-    )  # Decode the Base64 string back to bytes
-
-    # Convert bytes back to a UUID
-    oauth_uuid = uuid.UUID(bytes=uuid_bytes)
-    oauth_uuid_str = str(oauth_uuid)
-
-    r_key = f"da_oauth:{oauth_uuid_str}"
-
-    session_json_bytes = cast(bytes, r.get(r_key))
-    if not session_json_bytes:
-        raise HTTPException(
-            status_code=400,
-            detail=f"Slack OAuth failed - OAuth state key not found: key={r_key}",
-        )
-
-    session_json = session_json_bytes.decode("utf-8")
-    try:
-        session = SlackOAuth.parse_session(session_json)
-
-        if not DEV_MODE:
-            redirect_uri = SlackOAuth.REDIRECT_URI
-        else:
-            redirect_uri = SlackOAuth.DEV_REDIRECT_URI
-
-        # Exchange the authorization code for an access token
-        response = requests.post(
-            SlackOAuth.TOKEN_URL,
-            headers={"Content-Type": "application/x-www-form-urlencoded"},
-            data={
-                "client_id": SlackOAuth.CLIENT_ID,
-                "client_secret": SlackOAuth.CLIENT_SECRET,
-                "code": code,
-                "redirect_uri": redirect_uri,
-            },
-        )
-
-        response_data = response.json()
-
-        if not response_data.get("ok"):
-            raise HTTPException(
-                status_code=400,
-                detail=f"Slack OAuth failed: {response_data.get('error')}",
-            )
-
-        # Extract token and team information
-        access_token: str = response_data.get("access_token")
-        team_id: str = response_data.get("team", {}).get("id")
-        authed_user_id: str = response_data.get("authed_user", {}).get("id")
-
-        credential_info = CredentialBase(
-            credential_json={"slack_bot_token": access_token},
-            admin_public=True,
-            source=DocumentSource.SLACK,
-            name="Slack OAuth",
-        )
-
-        create_credential(credential_info, user, db_session)
-    except Exception as e:
-        return JSONResponse(
-            status_code=500,
-            content={
-                "success": False,
-                "message": f"An error occurred during Slack OAuth: {str(e)}",
-            },
-        )
-    finally:
-        r.delete(r_key)
-
-    # return the result
-    return JSONResponse(
-        content={
-            "success": True,
-            "message": "Slack OAuth completed successfully.",
-            "finalize_url": None,
-            "redirect_on_success": session.redirect_on_success,
-            "team_id": team_id,
-            "authed_user_id": authed_user_id,
-        }
-    )

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

@@ -179,7 +179,6 @@ def handle_simplified_chat_message(
         chunks_below=0,
         full_doc=chat_message_req.full_doc,
         structured_response_format=chat_message_req.structured_response_format,
-        use_agentic_search=chat_message_req.use_agentic_search,
     )
 
     packets = stream_chat_message_objects(
@@ -302,7 +301,6 @@ def handle_send_message_simple_with_history(
         chunks_below=0,
         full_doc=req.full_doc,
         structured_response_format=req.structured_response_format,
-        use_agentic_search=req.use_agentic_search,
     )
 
     packets = stream_chat_message_objects(

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

@@ -57,9 +57,6 @@ class BasicCreateChatMessageRequest(ChunkContext):
     # https://platform.openai.com/docs/guides/structured-outputs/introduction
     structured_response_format: dict | None = None
 
-    # If True, uses agentic search instead of basic search
-    use_agentic_search: bool = False
-
 
 class BasicCreateChatMessageWithHistoryRequest(ChunkContext):
     # Last element is the new query. All previous elements are historical context
@@ -74,8 +71,6 @@ class BasicCreateChatMessageWithHistoryRequest(ChunkContext):
     # only works if using an OpenAI model. See the following for more details:
     # https://platform.openai.com/docs/guides/structured-outputs/introduction
     structured_response_format: dict | None = None
-    # If True, uses agentic search instead of basic search
-    use_agentic_search: bool = False
 
 
 class SimpleDoc(BaseModel):
@@ -125,12 +120,9 @@ class OneShotQARequest(ChunkContext):
     # will also disable Thread-based Rewording if specified
     query_override: str | None = None
 
-    # If True, skips generating an AI response to the search query
+    # If True, skips generative an AI response to the search query
     skip_gen_ai_answer_generation: bool = False
 
-    # If True, uses agentic search instead of basic search
-    use_agentic_search: bool = False
-
     @model_validator(mode="after")
     def check_persona_fields(self) -> "OneShotQARequest":
         if self.persona_override_config is None and self.persona_id is None:

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

@@ -83,7 +83,6 @@ def handle_search_request(
         user=user,
         llm=llm,
         fast_llm=fast_llm,
-        skip_query_analysis=False,
         db_session=db_session,
         bypass_acl=False,
     )
@@ -197,8 +196,6 @@ def get_answer_stream(
         retrieval_details=query_request.retrieval_options,
         rerank_settings=query_request.rerank_settings,
         db_session=db_session,
-        use_agentic_search=query_request.use_agentic_search,
-        skip_gen_ai_answer_generation=query_request.skip_gen_ai_answer_generation,
     )
 
     packets = stream_chat_message_objects(

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

@@ -13,7 +13,7 @@ from sqlalchemy import select
 from sqlalchemy.orm import Session
 
 from onyx.db.api_key import is_api_key_email_address
-from onyx.db.engine import get_session_with_current_tenant
+from onyx.db.engine import get_session_with_tenant
 from onyx.db.models import ChatMessage
 from onyx.db.models import ChatSession
 from onyx.db.models import TokenRateLimit
@@ -28,21 +28,21 @@ from onyx.server.query_and_chat.token_limit import _user_is_rate_limited_by_glob
 from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
 
 
-def _check_token_rate_limits(user: User | None) -> None:
+def _check_token_rate_limits(user: User | None, tenant_id: str | None) -> None:
     if user is None:
         # Unauthenticated users are only rate limited by global settings
-        _user_is_rate_limited_by_global()
+        _user_is_rate_limited_by_global(tenant_id)
 
     elif is_api_key_email_address(user.email):
         # API keys are only rate limited by global settings
-        _user_is_rate_limited_by_global()
+        _user_is_rate_limited_by_global(tenant_id)
 
     else:
         run_functions_tuples_in_parallel(
             [
-                (_user_is_rate_limited, (user.id,)),
-                (_user_is_rate_limited_by_group, (user.id,)),
-                (_user_is_rate_limited_by_global, ()),
+                (_user_is_rate_limited, (user.id, tenant_id)),
+                (_user_is_rate_limited_by_group, (user.id, tenant_id)),
+                (_user_is_rate_limited_by_global, (tenant_id,)),
             ]
         )
 
@@ -52,8 +52,8 @@ User rate limits
 """
 
 
-def _user_is_rate_limited(user_id: UUID) -> None:
-    with get_session_with_current_tenant() as db_session:
+def _user_is_rate_limited(user_id: UUID, tenant_id: str | None) -> None:
+    with get_session_with_tenant(tenant_id) as db_session:
         user_rate_limits = fetch_all_user_token_rate_limits(
             db_session=db_session, enabled_only=True, ordered=False
         )
@@ -93,8 +93,8 @@ User Group rate limits
 """
 
 
-def _user_is_rate_limited_by_group(user_id: UUID) -> None:
-    with get_session_with_current_tenant() as db_session:
+def _user_is_rate_limited_by_group(user_id: UUID, tenant_id: str | None) -> None:
+    with get_session_with_tenant(tenant_id) as db_session:
         group_rate_limits = _fetch_all_user_group_rate_limits(user_id, db_session)
 
         if group_rate_limits:

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

@@ -2,7 +2,6 @@ import csv
 import io
 from datetime import datetime
 from datetime import timezone
-from http import HTTPStatus
 from uuid import UUID
 
 from fastapi import APIRouter
@@ -22,10 +21,8 @@ from ee.onyx.server.query_history.models import QuestionAnswerPairSnapshot
 from onyx.auth.users import current_admin_user
 from onyx.auth.users import get_display_email
 from onyx.chat.chat_utils import create_chat_chain
-from onyx.configs.app_configs import ONYX_QUERY_HISTORY_TYPE
 from onyx.configs.constants import MessageType
 from onyx.configs.constants import QAFeedbackType
-from onyx.configs.constants import QueryHistoryType
 from onyx.configs.constants import SessionType
 from onyx.db.chat import get_chat_session_by_id
 from onyx.db.chat import get_chat_sessions_by_user
@@ -38,8 +35,6 @@ from onyx.server.query_and_chat.models import ChatSessionsResponse
 
 router = APIRouter()
 
-ONYX_ANONYMIZED_EMAIL = "anonymous@anonymous.invalid"
-
 
 def fetch_and_process_chat_session_history(
     db_session: Session,
@@ -112,17 +107,6 @@ def get_user_chat_sessions(
     _: User | None = Depends(current_admin_user),
     db_session: Session = Depends(get_session),
 ) -> ChatSessionsResponse:
-    # we specifically don't allow this endpoint if "anonymized" since
-    # this is a direct query on the user id
-    if ONYX_QUERY_HISTORY_TYPE in [
-        QueryHistoryType.DISABLED,
-        QueryHistoryType.ANONYMIZED,
-    ]:
-        raise HTTPException(
-            status_code=HTTPStatus.FORBIDDEN,
-            detail="Per user query history has been disabled by the administrator.",
-        )
-
     try:
         chat_sessions = get_chat_sessions_by_user(
             user_id=user_id, deleted=False, db_session=db_session, limit=0
@@ -138,7 +122,6 @@ def get_user_chat_sessions(
                 name=chat.description,
                 persona_id=chat.persona_id,
                 time_created=chat.time_created.isoformat(),
-                time_updated=chat.time_updated.isoformat(),
                 shared_status=chat.shared_status,
                 folder_id=chat.folder_id,
                 current_alternate_model=chat.current_alternate_model,
@@ -158,12 +141,6 @@ def get_chat_session_history(
     _: User | None = Depends(current_admin_user),
     db_session: Session = Depends(get_session),
 ) -> PaginatedReturn[ChatSessionMinimal]:
-    if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.DISABLED:
-        raise HTTPException(
-            status_code=HTTPStatus.FORBIDDEN,
-            detail="Query history has been disabled by the administrator.",
-        )
-
     page_of_chat_sessions = get_page_of_chat_sessions(
         page_num=page_num,
         page_size=page_size,
@@ -180,16 +157,11 @@ def get_chat_session_history(
         feedback_filter=feedback_type,
     )
 
-    minimal_chat_sessions: list[ChatSessionMinimal] = []
-
-    for chat_session in page_of_chat_sessions:
-        minimal_chat_session = ChatSessionMinimal.from_chat_session(chat_session)
-        if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.ANONYMIZED:
-            minimal_chat_session.user_email = ONYX_ANONYMIZED_EMAIL
-        minimal_chat_sessions.append(minimal_chat_session)
-
     return PaginatedReturn(
-        items=minimal_chat_sessions,
+        items=[
+            ChatSessionMinimal.from_chat_session(chat_session)
+            for chat_session in page_of_chat_sessions
+        ],
         total_items=total_filtered_chat_sessions_count,
     )
 
@@ -200,12 +172,6 @@ def get_chat_session_admin(
     _: User | None = Depends(current_admin_user),
     db_session: Session = Depends(get_session),
 ) -> ChatSessionSnapshot:
-    if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.DISABLED:
-        raise HTTPException(
-            status_code=HTTPStatus.FORBIDDEN,
-            detail="Query history has been disabled by the administrator.",
-        )
-
     try:
         chat_session = get_chat_session_by_id(
             chat_session_id=chat_session_id,
@@ -227,9 +193,6 @@ def get_chat_session_admin(
             f"Could not create snapshot for chat session with id '{chat_session_id}'",
         )
 
-    if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.ANONYMIZED:
-        snapshot.user_email = ONYX_ANONYMIZED_EMAIL
-
     return snapshot
 
 
@@ -240,12 +203,6 @@ def get_query_history_as_csv(
     end: datetime | None = None,
     db_session: Session = Depends(get_session),
 ) -> StreamingResponse:
-    if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.DISABLED:
-        raise HTTPException(
-            status_code=HTTPStatus.FORBIDDEN,
-            detail="Query history has been disabled by the administrator.",
-        )
-
     complete_chat_session_history = fetch_and_process_chat_session_history(
         db_session=db_session,
         start=start or datetime.fromtimestamp(0, tz=timezone.utc),
@@ -256,9 +213,6 @@ def get_query_history_as_csv(
 
     question_answer_pairs: list[QuestionAnswerPairSnapshot] = []
     for chat_session_snapshot in complete_chat_session_history:
-        if ONYX_QUERY_HISTORY_TYPE == QueryHistoryType.ANONYMIZED:
-            chat_session_snapshot.user_email = ONYX_ANONYMIZED_EMAIL
-
         question_answer_pairs.extend(
             QuestionAnswerPairSnapshot.from_chat_session_snapshot(chat_session_snapshot)
         )

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

@@ -18,16 +18,11 @@ from ee.onyx.server.tenants.anonymous_user_path import (
 from ee.onyx.server.tenants.anonymous_user_path import modify_anonymous_user_path
 from ee.onyx.server.tenants.anonymous_user_path import validate_anonymous_user_path
 from ee.onyx.server.tenants.billing import fetch_billing_information
-from ee.onyx.server.tenants.billing import fetch_stripe_checkout_session
 from ee.onyx.server.tenants.billing import fetch_tenant_stripe_information
 from ee.onyx.server.tenants.models import AnonymousUserPath
 from ee.onyx.server.tenants.models import BillingInformation
 from ee.onyx.server.tenants.models import ImpersonateRequest
 from ee.onyx.server.tenants.models import ProductGatingRequest
-from ee.onyx.server.tenants.models import ProductGatingResponse
-from ee.onyx.server.tenants.models import SubscriptionSessionResponse
-from ee.onyx.server.tenants.models import SubscriptionStatusResponse
-from ee.onyx.server.tenants.product_gating import store_product_gating
 from ee.onyx.server.tenants.provisioning import delete_user_from_control_plane
 from ee.onyx.server.tenants.user_mapping import get_tenant_id_for_email
 from ee.onyx.server.tenants.user_mapping import remove_all_users_from_tenant
@@ -39,17 +34,18 @@ from onyx.auth.users import get_redis_strategy
 from onyx.auth.users import optional_user
 from onyx.auth.users import User
 from onyx.configs.app_configs import WEB_DOMAIN
-from onyx.configs.constants import FASTAPI_USERS_AUTH_COOKIE_NAME
 from onyx.db.auth import get_user_count
+from onyx.db.engine import get_current_tenant_id
 from onyx.db.engine import get_session
-from onyx.db.engine import get_session_with_shared_schema
 from onyx.db.engine import get_session_with_tenant
+from onyx.db.notification import create_notification
 from onyx.db.users import delete_user_from_db
 from onyx.db.users import get_user_by_email
 from onyx.server.manage.models import UserByEmail
+from onyx.server.settings.store import load_settings
+from onyx.server.settings.store import store_settings
 from onyx.utils.logger import setup_logger
 from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
-from shared_configs.contextvars import get_current_tenant_id
 
 stripe.api_key = STRIPE_SECRET_KEY
 logger = setup_logger()
@@ -58,14 +54,13 @@ router = APIRouter(prefix="/tenants")
 
 @router.get("/anonymous-user-path")
 async def get_anonymous_user_path_api(
+    tenant_id: str | None = Depends(get_current_tenant_id),
     _: User | None = Depends(current_admin_user),
 ) -> AnonymousUserPath:
-    tenant_id = get_current_tenant_id()
-
     if tenant_id is None:
         raise HTTPException(status_code=404, detail="Tenant not found")
 
-    with get_session_with_shared_schema() as db_session:
+    with get_session_with_tenant(tenant_id=None) as db_session:
         current_path = get_anonymous_user_path(tenant_id, db_session)
 
     return AnonymousUserPath(anonymous_user_path=current_path)
@@ -74,15 +69,15 @@ async def get_anonymous_user_path_api(
 @router.post("/anonymous-user-path")
 async def set_anonymous_user_path_api(
     anonymous_user_path: str,
+    tenant_id: str = Depends(get_current_tenant_id),
     _: User | None = Depends(current_admin_user),
 ) -> None:
-    tenant_id = get_current_tenant_id()
     try:
         validate_anonymous_user_path(anonymous_user_path)
     except ValueError as e:
         raise HTTPException(status_code=400, detail=str(e))
 
-    with get_session_with_shared_schema() as db_session:
+    with get_session_with_tenant(tenant_id=None) as db_session:
         try:
             modify_anonymous_user_path(tenant_id, anonymous_user_path, db_session)
         except IntegrityError:
@@ -103,7 +98,7 @@ async def login_as_anonymous_user(
     anonymous_user_path: str,
     _: User | None = Depends(optional_user),
 ) -> Response:
-    with get_session_with_shared_schema() as db_session:
+    with get_session_with_tenant(tenant_id=None) as db_session:
         tenant_id = get_tenant_id_for_anonymous_user_path(
             anonymous_user_path, db_session
         )
@@ -116,7 +111,6 @@ async def login_as_anonymous_user(
     token = generate_anonymous_user_jwt_token(tenant_id)
 
     response = Response()
-    response.delete_cookie(FASTAPI_USERS_AUTH_COOKIE_NAME)
     response.set_cookie(
         key=ANONYMOUS_USER_COOKIE_NAME,
         value=token,
@@ -130,48 +124,52 @@ async def login_as_anonymous_user(
 @router.post("/product-gating")
 def gate_product(
     product_gating_request: ProductGatingRequest, _: None = Depends(control_plane_dep)
-) -> ProductGatingResponse:
+) -> None:
     """
     Gating the product means that the product is not available to the tenant.
     They will be directed to the billing page.
-    We gate the product when their subscription has ended.
+    We gate the product when
+    1) User has ended free trial without adding payment method
+    2) User's card has declined
     """
-    try:
-        store_product_gating(
-            product_gating_request.tenant_id, product_gating_request.application_status
-        )
-        return ProductGatingResponse(updated=True, error=None)
+    tenant_id = product_gating_request.tenant_id
+    token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
 
-    except Exception as e:
-        logger.exception("Failed to gate product")
-        return ProductGatingResponse(updated=False, error=str(e))
+    settings = load_settings()
+    settings.product_gating = product_gating_request.product_gating
+    store_settings(settings)
+
+    if product_gating_request.notification:
+        with get_session_with_tenant(tenant_id) as db_session:
+            create_notification(None, product_gating_request.notification, db_session)
+
+    if token is not None:
+        CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
 
 
-@router.get("/billing-information")
+@router.get("/billing-information", response_model=BillingInformation)
 async def billing_information(
     _: User = Depends(current_admin_user),
-) -> BillingInformation | SubscriptionStatusResponse:
+) -> BillingInformation:
     logger.info("Fetching billing information")
-    tenant_id = get_current_tenant_id()
-    return fetch_billing_information(tenant_id)
+    return BillingInformation(
+        **fetch_billing_information(CURRENT_TENANT_ID_CONTEXTVAR.get())
+    )
 
 
 @router.post("/create-customer-portal-session")
-async def create_customer_portal_session(
-    _: User = Depends(current_admin_user),
-) -> dict:
-    tenant_id = get_current_tenant_id()
-
+async def create_customer_portal_session(_: User = Depends(current_admin_user)) -> dict:
     try:
+        # Fetch tenant_id and current tenant's information
+        tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get()
         stripe_info = fetch_tenant_stripe_information(tenant_id)
         stripe_customer_id = stripe_info.get("stripe_customer_id")
         if not stripe_customer_id:
             raise HTTPException(status_code=400, detail="Stripe customer ID not found")
         logger.info(stripe_customer_id)
-
         portal_session = stripe.billing_portal.Session.create(
             customer=stripe_customer_id,
-            return_url=f"{WEB_DOMAIN}/admin/billing",
+            return_url=f"{WEB_DOMAIN}/admin/cloud-settings",
         )
         logger.info(portal_session)
         return {"url": portal_session.url}
@@ -180,22 +178,6 @@ async def create_customer_portal_session(
         raise HTTPException(status_code=500, detail=str(e))
 
 
-@router.post("/create-subscription-session")
-async def create_subscription_session(
-    _: User = Depends(current_admin_user),
-) -> SubscriptionSessionResponse:
-    try:
-        tenant_id = CURRENT_TENANT_ID_CONTEXTVAR.get()
-        if not tenant_id:
-            raise HTTPException(status_code=400, detail="Tenant ID not found")
-        session_id = fetch_stripe_checkout_session(tenant_id)
-        return SubscriptionSessionResponse(sessionId=session_id)
-
-    except Exception as e:
-        logger.exception("Failed to create resubscription session")
-        raise HTTPException(status_code=500, detail=str(e))
-
-
 @router.post("/impersonate")
 async def impersonate_user(
     impersonate_request: ImpersonateRequest,
@@ -204,7 +186,7 @@ async def impersonate_user(
     """Allows a cloud superuser to impersonate another user by generating an impersonation JWT token"""
     tenant_id = get_tenant_id_for_email(impersonate_request.email)
 
-    with get_session_with_tenant(tenant_id=tenant_id) as tenant_session:
+    with get_session_with_tenant(tenant_id) as tenant_session:
         user_to_impersonate = get_user_by_email(
             impersonate_request.email, tenant_session
         )
@@ -228,9 +210,8 @@ async def leave_organization(
     user_email: UserByEmail,
     current_user: User | None = Depends(current_admin_user),
     db_session: Session = Depends(get_session),
+    tenant_id: str = Depends(get_current_tenant_id),
 ) -> None:
-    tenant_id = get_current_tenant_id()
-
     if current_user is None or current_user.email != user_email.user_email:
         raise HTTPException(
             status_code=403, detail="You can only leave the organization as yourself"

backend/ee/onyx/server/tenants/billing.py

@@ -6,8 +6,6 @@ import stripe
 from ee.onyx.configs.app_configs import STRIPE_PRICE_ID
 from ee.onyx.configs.app_configs import STRIPE_SECRET_KEY
 from ee.onyx.server.tenants.access import generate_data_plane_token
-from ee.onyx.server.tenants.models import BillingInformation
-from ee.onyx.server.tenants.models import SubscriptionStatusResponse
 from onyx.configs.app_configs import CONTROL_PLANE_API_BASE_URL
 from onyx.utils.logger import setup_logger
 
@@ -16,19 +14,6 @@ stripe.api_key = STRIPE_SECRET_KEY
 logger = setup_logger()
 
 
-def fetch_stripe_checkout_session(tenant_id: str) -> str:
-    token = generate_data_plane_token()
-    headers = {
-        "Authorization": f"Bearer {token}",
-        "Content-Type": "application/json",
-    }
-    url = f"{CONTROL_PLANE_API_BASE_URL}/create-checkout-session"
-    params = {"tenant_id": tenant_id}
-    response = requests.post(url, headers=headers, params=params)
-    response.raise_for_status()
-    return response.json()["sessionId"]
-
-
 def fetch_tenant_stripe_information(tenant_id: str) -> dict:
     token = generate_data_plane_token()
     headers = {
@@ -42,9 +27,7 @@ def fetch_tenant_stripe_information(tenant_id: str) -> dict:
     return response.json()
 
 
-def fetch_billing_information(
-    tenant_id: str,
-) -> BillingInformation | SubscriptionStatusResponse:
+def fetch_billing_information(tenant_id: str) -> dict:
     logger.info("Fetching billing information")
     token = generate_data_plane_token()
     headers = {
@@ -55,19 +38,8 @@ def fetch_billing_information(
     params = {"tenant_id": tenant_id}
     response = requests.get(url, headers=headers, params=params)
     response.raise_for_status()
-
-    response_data = response.json()
-
-    # Check if the response indicates no subscription
-    if (
-        isinstance(response_data, dict)
-        and "subscribed" in response_data
-        and not response_data["subscribed"]
-    ):
-        return SubscriptionStatusResponse(**response_data)
-
-    # Otherwise, parse as BillingInformation
-    return BillingInformation(**response_data)
+    billing_info = response.json()
+    return billing_info
 
 
 def register_tenant_users(tenant_id: str, number_of_users: int) -> stripe.Subscription:

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

@@ -1,8 +1,7 @@
-from datetime import datetime
-
 from pydantic import BaseModel
 
-from onyx.server.settings.models import ApplicationStatus
+from onyx.configs.constants import NotificationType
+from onyx.server.settings.models import GatingType
 
 
 class CheckoutSessionCreationRequest(BaseModel):
@@ -16,24 +15,15 @@ class CreateTenantRequest(BaseModel):
 
 class ProductGatingRequest(BaseModel):
     tenant_id: str
-    application_status: ApplicationStatus
-
-
-class SubscriptionStatusResponse(BaseModel):
-    subscribed: bool
+    product_gating: GatingType
+    notification: NotificationType | None = None
 
 
 class BillingInformation(BaseModel):
-    stripe_subscription_id: str
-    status: str
-    current_period_start: datetime
-    current_period_end: datetime
-    number_of_seats: int
-    cancel_at_period_end: bool
-    canceled_at: datetime | None
-    trial_start: datetime | None
-    trial_end: datetime | None
     seats: int
+    subscription_status: str
+    billing_start: str
+    billing_end: str
     payment_method_enabled: bool
 
 
@@ -58,12 +48,3 @@ class TenantDeletionPayload(BaseModel):
 
 class AnonymousUserPath(BaseModel):
     anonymous_user_path: str | None
-
-
-class ProductGatingResponse(BaseModel):
-    updated: bool
-    error: str | None
-
-
-class SubscriptionSessionResponse(BaseModel):
-    sessionId: str

backend/ee/onyx/server/tenants/product_gating.py

@@ -1,51 +0,0 @@
-from typing import cast
-
-from ee.onyx.configs.app_configs import GATED_TENANTS_KEY
-from onyx.configs.constants import ONYX_CLOUD_TENANT_ID
-from onyx.redis.redis_pool import get_redis_client
-from onyx.redis.redis_pool import get_redis_replica_client
-from onyx.server.settings.models import ApplicationStatus
-from onyx.server.settings.store import load_settings
-from onyx.server.settings.store import store_settings
-from onyx.setup import setup_logger
-from shared_configs.contextvars import CURRENT_TENANT_ID_CONTEXTVAR
-
-logger = setup_logger()
-
-
-def update_tenant_gating(tenant_id: str, status: ApplicationStatus) -> None:
-    redis_client = get_redis_client(tenant_id=ONYX_CLOUD_TENANT_ID)
-
-    # Store the full status
-    status_key = f"tenant:{tenant_id}:status"
-    redis_client.set(status_key, status.value)
-
-    # Maintain the GATED_ACCESS set
-    if status == ApplicationStatus.GATED_ACCESS:
-        redis_client.sadd(GATED_TENANTS_KEY, tenant_id)
-    else:
-        redis_client.srem(GATED_TENANTS_KEY, tenant_id)
-
-
-def store_product_gating(tenant_id: str, application_status: ApplicationStatus) -> None:
-    try:
-        token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
-
-        settings = load_settings()
-        settings.application_status = application_status
-        store_settings(settings)
-
-        # Store gated tenant information in Redis
-        update_tenant_gating(tenant_id, application_status)
-
-        if token is not None:
-            CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
-
-    except Exception:
-        logger.exception("Failed to gate product")
-        raise
-
-
-def get_gated_tenants() -> set[str]:
-    redis_client = get_redis_replica_client(tenant_id=ONYX_CLOUD_TENANT_ID)
-    return cast(set[str], redis_client.smembers(GATED_TENANTS_KEY))

backend/ee/onyx/server/tenants/provisioning.py

@@ -24,7 +24,6 @@ from ee.onyx.server.tenants.user_mapping import get_tenant_id_for_email
 from ee.onyx.server.tenants.user_mapping import user_owns_a_tenant
 from onyx.auth.users import exceptions
 from onyx.configs.app_configs import CONTROL_PLANE_API_BASE_URL
-from onyx.configs.app_configs import DEV_MODE
 from onyx.configs.constants import MilestoneRecordType
 from onyx.db.engine import get_session_with_tenant
 from onyx.db.engine import get_sqlalchemy_engine
@@ -86,8 +85,7 @@ async def create_tenant(email: str, referral_source: str | None = None) -> str:
         # Provision tenant on data plane
         await provision_tenant(tenant_id, email)
         # Notify control plane
-        if not DEV_MODE:
-            await notify_control_plane(tenant_id, email, referral_source)
+        await notify_control_plane(tenant_id, email, referral_source)
     except Exception as e:
         logger.error(f"Tenant provisioning failed: {e}")
         await rollback_tenant_provisioning(tenant_id)
@@ -104,21 +102,21 @@ async def provision_tenant(tenant_id: str, email: str) -> None:
             status_code=409, detail="User already belongs to an organization"
         )
 
-    logger.debug(f"Provisioning tenant {tenant_id} for user {email}")
+    logger.info(f"Provisioning tenant: {tenant_id}")
     token = None
 
     try:
         if not create_schema_if_not_exists(tenant_id):
-            logger.debug(f"Created schema for tenant {tenant_id}")
+            logger.info(f"Created schema for tenant {tenant_id}")
         else:
-            logger.debug(f"Schema already exists for tenant {tenant_id}")
+            logger.info(f"Schema already exists for tenant {tenant_id}")
 
         token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
 
         # Await the Alembic migrations
         await asyncio.to_thread(run_alembic_migrations, tenant_id)
 
-        with get_session_with_tenant(tenant_id=tenant_id) as db_session:
+        with get_session_with_tenant(tenant_id) as db_session:
             configure_default_api_keys(db_session)
 
             current_search_settings = (
@@ -134,7 +132,7 @@ async def provision_tenant(tenant_id: str, email: str) -> None:
 
         add_users_to_tenant([email], tenant_id)
 
-        with get_session_with_tenant(tenant_id=tenant_id) as db_session:
+        with get_session_with_tenant(tenant_id) as db_session:
             create_milestone_and_report(
                 user=None,
                 distinct_id=tenant_id,
@@ -200,35 +198,14 @@ async def rollback_tenant_provisioning(tenant_id: str) -> None:
 
 
 def configure_default_api_keys(db_session: Session) -> None:
-    if ANTHROPIC_DEFAULT_API_KEY:
-        anthropic_provider = LLMProviderUpsertRequest(
-            name="Anthropic",
-            provider=ANTHROPIC_PROVIDER_NAME,
-            api_key=ANTHROPIC_DEFAULT_API_KEY,
-            default_model_name="claude-3-7-sonnet-20250219",
-            fast_default_model_name="claude-3-5-sonnet-20241022",
-            model_names=ANTHROPIC_MODEL_NAMES,
-            display_model_names=["claude-3-5-sonnet-20241022"],
-        )
-        try:
-            full_provider = upsert_llm_provider(anthropic_provider, db_session)
-            update_default_provider(full_provider.id, db_session)
-        except Exception as e:
-            logger.error(f"Failed to configure Anthropic provider: {e}")
-    else:
-        logger.error(
-            "ANTHROPIC_DEFAULT_API_KEY not set, skipping Anthropic provider configuration"
-        )
-
     if OPENAI_DEFAULT_API_KEY:
         open_provider = LLMProviderUpsertRequest(
             name="OpenAI",
             provider=OPENAI_PROVIDER_NAME,
             api_key=OPENAI_DEFAULT_API_KEY,
-            default_model_name="gpt-4o",
+            default_model_name="gpt-4",
             fast_default_model_name="gpt-4o-mini",
             model_names=OPEN_AI_MODEL_NAMES,
-            display_model_names=["o1", "o3-mini", "gpt-4o", "gpt-4o-mini"],
         )
         try:
             full_provider = upsert_llm_provider(open_provider, db_session)
@@ -240,6 +217,25 @@ def configure_default_api_keys(db_session: Session) -> None:
             "OPENAI_DEFAULT_API_KEY not set, skipping OpenAI provider configuration"
         )
 
+    if ANTHROPIC_DEFAULT_API_KEY:
+        anthropic_provider = LLMProviderUpsertRequest(
+            name="Anthropic",
+            provider=ANTHROPIC_PROVIDER_NAME,
+            api_key=ANTHROPIC_DEFAULT_API_KEY,
+            default_model_name="claude-3-5-sonnet-20241022",
+            fast_default_model_name="claude-3-5-sonnet-20241022",
+            model_names=ANTHROPIC_MODEL_NAMES,
+        )
+        try:
+            full_provider = upsert_llm_provider(anthropic_provider, db_session)
+            update_default_provider(full_provider.id, db_session)
+        except Exception as e:
+            logger.error(f"Failed to configure Anthropic provider: {e}")
+    else:
+        logger.error(
+            "ANTHROPIC_DEFAULT_API_KEY not set, skipping Anthropic provider configuration"
+        )
+
     if COHERE_DEFAULT_API_KEY:
         cloud_embedding_provider = CloudEmbeddingProviderCreationRequest(
             provider_type=EmbeddingProvider.COHERE,

backend/ee/onyx/server/tenants/user_mapping.py

@@ -28,7 +28,7 @@ def get_tenant_id_for_email(email: str) -> str:
 
 
 def user_owns_a_tenant(email: str) -> bool:
-    with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
+    with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
         result = (
             db_session.query(UserTenantMapping)
             .filter(UserTenantMapping.email == email)
@@ -38,7 +38,7 @@ def user_owns_a_tenant(email: str) -> bool:
 
 
 def add_users_to_tenant(emails: list[str], tenant_id: str) -> None:
-    with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
+    with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
         try:
             for email in emails:
                 db_session.add(UserTenantMapping(email=email, tenant_id=tenant_id))
@@ -48,7 +48,7 @@ def add_users_to_tenant(emails: list[str], tenant_id: str) -> None:
 
 
 def remove_users_from_tenant(emails: list[str], tenant_id: str) -> None:
-    with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
+    with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
         try:
             mappings_to_delete = (
                 db_session.query(UserTenantMapping)
@@ -71,7 +71,7 @@ def remove_users_from_tenant(emails: list[str], tenant_id: str) -> None:
 
 
 def remove_all_users_from_tenant(tenant_id: str) -> None:
-    with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
+    with get_session_with_tenant(POSTGRES_DEFAULT_SCHEMA) as db_session:
         db_session.query(UserTenantMapping).filter(
             UserTenantMapping.tenant_id == tenant_id
         ).delete()

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

@@ -58,7 +58,6 @@ class UserGroup(BaseModel):
                     credential=CredentialSnapshot.from_credential_db_model(
                         cc_pair_relationship.cc_pair.credential
                     ),
-                    access_type=cc_pair_relationship.cc_pair.access_type,
                 )
                 for cc_pair_relationship in user_group_model.cc_pair_relationships
                 if cc_pair_relationship.is_current

backend/model_server/constants.py

@@ -6,7 +6,7 @@ MODEL_WARM_UP_STRING = "hi " * 512
 DEFAULT_OPENAI_MODEL = "text-embedding-3-small"
 DEFAULT_COHERE_MODEL = "embed-english-light-v3.0"
 DEFAULT_VOYAGE_MODEL = "voyage-large-2-instruct"
-DEFAULT_VERTEX_MODEL = "text-embedding-005"
+DEFAULT_VERTEX_MODEL = "text-embedding-004"
 
 
 class EmbeddingModelTextType:
@@ -28,9 +28,3 @@ class EmbeddingModelTextType:
     @staticmethod
     def get_type(provider: EmbeddingProvider, text_type: EmbedTextType) -> str:
         return EmbeddingModelTextType.PROVIDER_TEXT_TYPE_MAP[provider][text_type]
-
-
-class GPUStatus:
-    CUDA = "cuda"
-    MAC_MPS = "mps"
-    NONE = "none"

backend/model_server/encoders.py

@@ -5,7 +5,6 @@ from types import TracebackType
 from typing import cast
 from typing import Optional
 
-import aioboto3  # type: ignore
 import httpx
 import openai
 import vertexai  # type: ignore
@@ -13,7 +12,6 @@ import voyageai  # type: ignore
 from cohere import AsyncClient as CohereAsyncClient
 from fastapi import APIRouter
 from fastapi import HTTPException
-from fastapi import Request
 from google.oauth2 import service_account  # type: ignore
 from litellm import aembedding
 from litellm.exceptions import RateLimitError
@@ -29,13 +27,11 @@ from model_server.constants import DEFAULT_VERTEX_MODEL
 from model_server.constants import DEFAULT_VOYAGE_MODEL
 from model_server.constants import EmbeddingModelTextType
 from model_server.constants import EmbeddingProvider
-from model_server.utils import pass_aws_key
 from model_server.utils import simple_log_function_time
 from onyx.utils.logger import setup_logger
 from shared_configs.configs import API_BASED_EMBEDDING_TIMEOUT
 from shared_configs.configs import INDEXING_ONLY
 from shared_configs.configs import OPENAI_EMBEDDING_TIMEOUT
-from shared_configs.configs import VERTEXAI_EMBEDDING_LOCAL_BATCH_SIZE
 from shared_configs.enums import EmbedTextType
 from shared_configs.enums import RerankerProvider
 from shared_configs.model_server_models import Embedding
@@ -81,7 +77,7 @@ class CloudEmbedding:
         self._closed = False
 
     async def _embed_openai(
-        self, texts: list[str], model: str | None, reduced_dimension: int | None
+        self, texts: list[str], model: str | None
     ) -> list[Embedding]:
         if not model:
             model = DEFAULT_OPENAI_MODEL
@@ -94,28 +90,19 @@ class CloudEmbedding:
         final_embeddings: list[Embedding] = []
         try:
             for text_batch in batch_list(texts, _OPENAI_MAX_INPUT_LEN):
-                response = await client.embeddings.create(
-                    input=text_batch,
-                    model=model,
-                    dimensions=reduced_dimension or openai.NOT_GIVEN,
-                )
+                response = await client.embeddings.create(input=text_batch, model=model)
                 final_embeddings.extend(
                     [embedding.embedding for embedding in response.data]
                 )
             return final_embeddings
         except Exception as e:
             error_string = (
-                f"Exception embedding text with OpenAI - {type(e)}: "
-                f"Model: {model} "
-                f"Provider: {self.provider} "
-                f"Exception: {e}"
+                f"Error embedding text with OpenAI: {str(e)} \n"
+                f"Model: {model} \n"
+                f"Provider: {self.provider} \n"
+                f"Texts: {texts}"
             )
             logger.error(error_string)
-
-            # only log text when it's not an authentication error.
-            if not isinstance(e, openai.AuthenticationError):
-                logger.debug(f"Exception texts: {texts}")
-
             raise RuntimeError(error_string)
 
     async def _embed_cohere(
@@ -185,24 +172,17 @@ class CloudEmbedding:
         vertexai.init(project=project_id, credentials=credentials)
         client = TextEmbeddingModel.from_pretrained(model)
 
-        inputs = [TextEmbeddingInput(text, embedding_type) for text in texts]
-
-        # Split into batches of 25 texts
-        max_texts_per_batch = VERTEXAI_EMBEDDING_LOCAL_BATCH_SIZE
-        batches = [
-            inputs[i : i + max_texts_per_batch]
-            for i in range(0, len(inputs), max_texts_per_batch)
-        ]
-
-        # Dispatch all embedding calls asynchronously at once
-        tasks = [
-            client.get_embeddings_async(batch, auto_truncate=True) for batch in batches
-        ]
-
-        # Wait for all tasks to complete in parallel
-        results = await asyncio.gather(*tasks)
-
-        return [embedding.values for batch in results for embedding in batch]
+        embeddings = await client.get_embeddings_async(
+            [
+                TextEmbeddingInput(
+                    text,
+                    embedding_type,
+                )
+                for text in texts
+            ],
+            auto_truncate=True,  # This is the default
+        )
+        return [embedding.values for embedding in embeddings]
 
     async def _embed_litellm_proxy(
         self, texts: list[str], model_name: str | None
@@ -237,10 +217,9 @@ class CloudEmbedding:
         text_type: EmbedTextType,
         model_name: str | None = None,
         deployment_name: str | None = None,
-        reduced_dimension: int | None = None,
     ) -> list[Embedding]:
         if self.provider == EmbeddingProvider.OPENAI:
-            return await self._embed_openai(texts, model_name, reduced_dimension)
+            return await self._embed_openai(texts, model_name)
         elif self.provider == EmbeddingProvider.AZURE:
             return await self._embed_azure(texts, f"azure/{deployment_name}")
         elif self.provider == EmbeddingProvider.LITELLM:
@@ -341,8 +320,6 @@ async def embed_text(
     prefix: str | None,
     api_url: str | None,
     api_version: str | None,
-    reduced_dimension: int | None,
-    gpu_type: str = "UNKNOWN",
 ) -> list[Embedding]:
     if not all(texts):
         logger.error("Empty strings provided for embedding")
@@ -385,7 +362,6 @@ async def embed_text(
                 model_name=model_name,
                 deployment_name=deployment_name,
                 text_type=text_type,
-                reduced_dimension=reduced_dimension,
             )
 
         if any(embedding is None for embedding in embeddings):
@@ -397,11 +373,8 @@ async def embed_text(
 
         elapsed = time.monotonic() - start
         logger.info(
-            f"event=embedding_provider "
-            f"texts={len(texts)} "
-            f"chars={total_chars} "
-            f"provider={provider_type} "
-            f"elapsed={elapsed:.2f}"
+            f"Successfully embedded {len(texts)} texts with {total_chars} total characters "
+            f"with provider {provider_type} in {elapsed:.2f}"
         )
     elif model_name is not None:
         logger.info(
@@ -430,14 +403,6 @@ async def embed_text(
             f"Successfully embedded {len(texts)} texts with {total_chars} total characters "
             f"with local model {model_name} in {elapsed:.2f}"
         )
-        logger.info(
-            f"event=embedding_model "
-            f"texts={len(texts)} "
-            f"chars={total_chars} "
-            f"model={model_name} "
-            f"gpu={gpu_type} "
-            f"elapsed={elapsed:.2f}"
-        )
     else:
         logger.error("Neither model name nor provider specified for embedding")
         raise ValueError(
@@ -457,7 +422,7 @@ async def local_rerank(query: str, docs: list[str], model_name: str) -> list[flo
     )
 
 
-async def cohere_rerank_api(
+async def cohere_rerank(
     query: str, docs: list[str], model_name: str, api_key: str
 ) -> list[float]:
     cohere_client = CohereAsyncClient(api_key=api_key)
@@ -467,45 +432,6 @@ async def cohere_rerank_api(
     return [result.relevance_score for result in sorted_results]
 
 
-async def cohere_rerank_aws(
-    query: str,
-    docs: list[str],
-    model_name: str,
-    region_name: str,
-    aws_access_key_id: str,
-    aws_secret_access_key: str,
-) -> list[float]:
-    session = aioboto3.Session(
-        aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key
-    )
-    async with session.client(
-        "bedrock-runtime", region_name=region_name
-    ) as bedrock_client:
-        body = json.dumps(
-            {
-                "query": query,
-                "documents": docs,
-                "api_version": 2,
-            }
-        )
-        # Invoke the Bedrock model asynchronously
-        response = await bedrock_client.invoke_model(
-            modelId=model_name,
-            accept="application/json",
-            contentType="application/json",
-            body=body,
-        )
-
-        # Read the response asynchronously
-        response_body = json.loads(await response["body"].read())
-
-        # Extract and sort the results
-        results = response_body.get("results", [])
-        sorted_results = sorted(results, key=lambda item: item["index"])
-
-        return [result["relevance_score"] for result in sorted_results]
-
-
 async def litellm_rerank(
     query: str, docs: list[str], api_url: str, model_name: str, api_key: str | None
 ) -> list[float]:
@@ -529,15 +455,8 @@ async def litellm_rerank(
 
 
 @router.post("/bi-encoder-embed")
-async def route_bi_encoder_embed(
-    request: Request,
-    embed_request: EmbedRequest,
-) -> EmbedResponse:
-    return await process_embed_request(embed_request, request.app.state.gpu_type)
-
-
 async def process_embed_request(
-    embed_request: EmbedRequest, gpu_type: str = "UNKNOWN"
+    embed_request: EmbedRequest,
 ) -> EmbedResponse:
     if not embed_request.texts:
         raise HTTPException(status_code=400, detail="No texts to be embedded")
@@ -564,9 +483,7 @@ async def process_embed_request(
             text_type=embed_request.text_type,
             api_url=embed_request.api_url,
             api_version=embed_request.api_version,
-            reduced_dimension=embed_request.reduced_dimension,
             prefix=prefix,
-            gpu_type=gpu_type,
         )
         return EmbedResponse(embeddings=embeddings)
     except RateLimitError as e:
@@ -621,32 +538,15 @@ async def process_rerank_request(rerank_request: RerankRequest) -> RerankRespons
         elif rerank_request.provider_type == RerankerProvider.COHERE:
             if rerank_request.api_key is None:
                 raise RuntimeError("Cohere Rerank Requires an API Key")
-            sim_scores = await cohere_rerank_api(
+            sim_scores = await cohere_rerank(
                 query=rerank_request.query,
                 docs=rerank_request.documents,
                 model_name=rerank_request.model_name,
                 api_key=rerank_request.api_key,
             )
             return RerankResponse(scores=sim_scores)
-
-        elif rerank_request.provider_type == RerankerProvider.BEDROCK:
-            if rerank_request.api_key is None:
-                raise RuntimeError("Bedrock Rerank Requires an API Key")
-            aws_access_key_id, aws_secret_access_key, aws_region = pass_aws_key(
-                rerank_request.api_key
-            )
-            sim_scores = await cohere_rerank_aws(
-                query=rerank_request.query,
-                docs=rerank_request.documents,
-                model_name=rerank_request.model_name,
-                region_name=aws_region,
-                aws_access_key_id=aws_access_key_id,
-                aws_secret_access_key=aws_secret_access_key,
-            )
-            return RerankResponse(scores=sim_scores)
         else:
             raise ValueError(f"Unsupported provider: {rerank_request.provider_type}")
-
     except Exception as e:
         logger.exception(f"Error during reranking process:\n{str(e)}")
         raise HTTPException(

backend/model_server/main.py

@@ -16,7 +16,6 @@ from model_server.custom_models import router as custom_models_router
 from model_server.custom_models import warm_up_intent_model
 from model_server.encoders import router as encoders_router
 from model_server.management_endpoints import router as management_router
-from model_server.utils import get_gpu_type
 from onyx import __version__
 from onyx.utils.logger import setup_logger
 from shared_configs.configs import INDEXING_ONLY
@@ -59,10 +58,12 @@ def _move_files_recursively(source: Path, dest: Path, overwrite: bool = False) -
 
 @asynccontextmanager
 async def lifespan(app: FastAPI) -> AsyncGenerator:
-    gpu_type = get_gpu_type()
-    logger.notice(f"Torch GPU Detection: gpu_type={gpu_type}")
-
-    app.state.gpu_type = gpu_type
+    if torch.cuda.is_available():
+        logger.notice("CUDA GPU is available")
+    elif torch.backends.mps.is_available():
+        logger.notice("Mac MPS is available")
+    else:
+        logger.notice("GPU is not available, using CPU")
 
     if TEMP_HF_CACHE_PATH.is_dir():
         logger.notice("Moving contents of temp_huggingface to huggingface cache.")

backend/model_server/management_endpoints.py

@@ -1,9 +1,7 @@
+import torch
 from fastapi import APIRouter
 from fastapi import Response
 
-from model_server.constants import GPUStatus
-from model_server.utils import get_gpu_type
-
 router = APIRouter(prefix="/api")
 
 
@@ -13,7 +11,10 @@ async def healthcheck() -> Response:
 
 
 @router.get("/gpu-status")
-async def route_gpu_status() -> dict[str, bool | str]:
-    gpu_type = get_gpu_type()
-    gpu_available = gpu_type != GPUStatus.NONE
-    return {"gpu_available": gpu_available, "type": gpu_type}
+async def gpu_status() -> dict[str, bool | str]:
+    if torch.cuda.is_available():
+        return {"gpu_available": True, "type": "cuda"}
+    elif torch.backends.mps.is_available():
+        return {"gpu_available": True, "type": "mps"}
+    else:
+        return {"gpu_available": False, "type": "none"}

backend/model_server/utils.py

@@ -8,9 +8,6 @@ from typing import Any
 from typing import cast
 from typing import TypeVar
 
-import torch
-
-from model_server.constants import GPUStatus
 from onyx.utils.logger import setup_logger
 
 logger = setup_logger()
@@ -61,41 +58,3 @@ def simple_log_function_time(
             return cast(F, wrapped_sync_func)
 
     return decorator
-
-
-def get_gpu_type() -> str:
-    if torch.cuda.is_available():
-        return GPUStatus.CUDA
-    if torch.backends.mps.is_available():
-        return GPUStatus.MAC_MPS
-
-    return GPUStatus.NONE
-
-
-def pass_aws_key(api_key: str) -> tuple[str, str, str]:
-    """Parse AWS API key string into components.
-
-    Args:
-        api_key: String in format 'aws_ACCESSKEY_SECRETKEY_REGION'
-
-    Returns:
-        Tuple of (access_key, secret_key, region)
-
-    Raises:
-        ValueError: If key format is invalid
-    """
-    if not api_key.startswith("aws"):
-        raise ValueError("API key must start with 'aws' prefix")
-
-    parts = api_key.split("_")
-    if len(parts) != 4:
-        raise ValueError(
-            f"API key must be in format 'aws_ACCESSKEY_SECRETKEY_REGION', got {len(parts) - 1} parts"
-            "this is an onyx specific format for formatting the aws secrets for bedrock"
-        )
-
-    try:
-        _, aws_access_key_id, aws_secret_access_key, aws_region = parts
-        return aws_access_key_id, aws_secret_access_key, aws_region
-    except Exception as e:
-        raise ValueError(f"Failed to parse AWS key components: {str(e)}")

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

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

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

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

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

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

backend/onyx/agents/agent_search/core_state.py

@@ -1,20 +0,0 @@
-from operator import add
-from typing import Annotated
-
-from pydantic import BaseModel
-
-
-class CoreState(BaseModel):
-    """
-    This is the core state that is shared across all subgraphs.
-    """
-
-    log_messages: Annotated[list[str], add] = []
-
-
-class SubgraphCoreState(BaseModel):
-    """
-    This is the core state that is shared across all subgraphs.
-    """
-
-    log_messages: Annotated[list[str], add] = []

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

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

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

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

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

@@ -1,134 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import BaseMessage
-from langchain_core.messages import HumanMessage
-from langchain_core.runnables.config import RunnableConfig
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionState,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnswerCheckUpdate,
-)
-from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    binary_string_test,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_RATELIMIT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_TIMEOUT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_POSITIVE_VALUE_STR,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import AgentLLMErrorType
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import parse_question_id
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_CHECK
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_SUBANSWER_CHECK
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
-from onyx.prompts.agent_search import SUB_ANSWER_CHECK_PROMPT
-from onyx.prompts.agent_search import UNKNOWN_ANSWER
-from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-logger = setup_logger()
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. The sub-answer will be treated as 'relevant'",
-    rate_limit="LLM Rate Limit Error. The sub-answer will be treated as 'relevant'",
-    general_error="General LLM Error. The sub-answer will be treated as 'relevant'",
-)
-
-
-@log_function_time(print_only=True)
-def check_sub_answer(
-    state: AnswerQuestionState, config: RunnableConfig
-) -> SubQuestionAnswerCheckUpdate:
-    """
-    LangGraph node to check the quality of the sub-answer. The answer
-    is represented as a boolean value.
-    """
-    node_start_time = datetime.now()
-
-    level, question_num = parse_question_id(state.question_id)
-    if state.answer == UNKNOWN_ANSWER:
-        return SubQuestionAnswerCheckUpdate(
-            answer_quality=False,
-            log_messages=[
-                get_langgraph_node_log_string(
-                    graph_component="initial  - generate individual sub answer",
-                    node_name="check sub answer",
-                    node_start_time=node_start_time,
-                    result="unknown answer",
-                )
-            ],
-        )
-    msg = [
-        HumanMessage(
-            content=SUB_ANSWER_CHECK_PROMPT.format(
-                question=state.question,
-                base_answer=state.answer,
-            )
-        )
-    ]
-
-    graph_config = cast(GraphConfig, config["metadata"]["config"])
-    fast_llm = graph_config.tooling.fast_llm
-    agent_error: AgentErrorLog | None = None
-    response: BaseMessage | None = None
-    try:
-        response = run_with_timeout(
-            AGENT_TIMEOUT_LLM_SUBANSWER_CHECK,
-            fast_llm.invoke,
-            prompt=msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_CHECK,
-        )
-
-        quality_str: str = cast(str, response.content)
-        answer_quality = binary_string_test(
-            text=quality_str, positive_value=AGENT_POSITIVE_VALUE_STR
-        )
-        log_result = f"Answer quality: {quality_str}"
-
-    except (LLMTimeoutError, TimeoutError):
-        agent_error = AgentErrorLog(
-            error_type=AgentLLMErrorType.TIMEOUT,
-            error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-            error_result=_llm_node_error_strings.timeout,
-        )
-        answer_quality = True
-        log_result = agent_error.error_result
-        logger.error("LLM Timeout Error - check sub answer")
-
-    except LLMRateLimitError:
-        agent_error = AgentErrorLog(
-            error_type=AgentLLMErrorType.RATE_LIMIT,
-            error_message=AGENT_LLM_RATELIMIT_MESSAGE,
-            error_result=_llm_node_error_strings.rate_limit,
-        )
-
-        answer_quality = True
-        log_result = agent_error.error_result
-        logger.error("LLM Rate Limit Error - check sub answer")
-
-    return SubQuestionAnswerCheckUpdate(
-        answer_quality=answer_quality,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial  - generate individual sub answer",
-                node_name="check sub answer",
-                node_start_time=node_start_time,
-                result=log_result,
-            )
-        ],
-    )

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

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

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

@@ -1,203 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import merge_message_runs
-from langchain_core.runnables.config import RunnableConfig
-from langgraph.types import StreamWriter
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionState,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    SubQuestionAnswerGenerationUpdate,
-)
-from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    build_sub_question_answer_prompt,
-)
-from onyx.agents.agent_search.shared_graph_utils.calculations import (
-    dedup_sort_inference_section_list,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_RATELIMIT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_TIMEOUT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AgentLLMErrorType,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    LLM_ANSWER_ERROR_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
-from onyx.agents.agent_search.shared_graph_utils.utils import get_answer_citation_ids
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_persona_agent_prompt_expressions,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import parse_question_id
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import AgentAnswerPiece
-from onyx.chat.models import StreamStopInfo
-from onyx.chat.models import StreamStopReason
-from onyx.chat.models import StreamType
-from onyx.configs.agent_configs import AGENT_MAX_ANSWER_CONTEXT_DOCS
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_GENERATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_SUBANSWER_GENERATION
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
-from onyx.prompts.agent_search import NO_RECOVERED_DOCS
-from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-logger = setup_logger()
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-    rate_limit="LLM Rate Limit Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-    general_error="General LLM Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-)
-
-
-@log_function_time(print_only=True)
-def generate_sub_answer(
-    state: AnswerQuestionState,
-    config: RunnableConfig,
-    writer: StreamWriter = lambda _: None,
-) -> SubQuestionAnswerGenerationUpdate:
-    """
-    LangGraph node to generate a sub-answer.
-    """
-    node_start_time = datetime.now()
-
-    graph_config = cast(GraphConfig, config["metadata"]["config"])
-    question = state.question
-    state.verified_reranked_documents
-    level, question_num = parse_question_id(state.question_id)
-    context_docs = state.context_documents[:AGENT_MAX_ANSWER_CONTEXT_DOCS]
-
-    context_docs = dedup_sort_inference_section_list(context_docs)
-
-    persona_contextualized_prompt = get_persona_agent_prompt_expressions(
-        graph_config.inputs.search_request.persona
-    ).contextualized_prompt
-
-    if len(context_docs) == 0:
-        answer_str = NO_RECOVERED_DOCS
-        cited_documents: list = []
-        log_results = "No documents retrieved"
-        write_custom_event(
-            "sub_answers",
-            AgentAnswerPiece(
-                answer_piece=answer_str,
-                level=level,
-                level_question_num=question_num,
-                answer_type="agent_sub_answer",
-            ),
-            writer,
-        )
-    else:
-        fast_llm = graph_config.tooling.fast_llm
-        msg = build_sub_question_answer_prompt(
-            question=question,
-            original_question=graph_config.inputs.search_request.query,
-            docs=context_docs,
-            persona_specification=persona_contextualized_prompt,
-            config=fast_llm.config,
-        )
-
-        dispatch_timings: list[float] = []
-        agent_error: AgentErrorLog | None = None
-        response: list[str] = []
-
-        def stream_sub_answer() -> list[str]:
-            for message in fast_llm.stream(
-                prompt=msg,
-                timeout_override=AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_GENERATION,
-            ):
-                # TODO: in principle, the answer here COULD contain images, but we don't support that yet
-                content = message.content
-                if not isinstance(content, str):
-                    raise ValueError(
-                        f"Expected content to be a string, but got {type(content)}"
-                    )
-                start_stream_token = datetime.now()
-                write_custom_event(
-                    "sub_answers",
-                    AgentAnswerPiece(
-                        answer_piece=content,
-                        level=level,
-                        level_question_num=question_num,
-                        answer_type="agent_sub_answer",
-                    ),
-                    writer,
-                )
-                end_stream_token = datetime.now()
-                dispatch_timings.append(
-                    (end_stream_token - start_stream_token).microseconds
-                )
-                response.append(content)
-            return response
-
-        try:
-            response = run_with_timeout(
-                AGENT_TIMEOUT_LLM_SUBANSWER_GENERATION,
-                stream_sub_answer,
-            )
-
-        except (LLMTimeoutError, TimeoutError):
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.TIMEOUT,
-                error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-                error_result=_llm_node_error_strings.timeout,
-            )
-            logger.error("LLM Timeout Error - generate sub answer")
-        except LLMRateLimitError:
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.RATE_LIMIT,
-                error_message=AGENT_LLM_RATELIMIT_MESSAGE,
-                error_result=_llm_node_error_strings.rate_limit,
-            )
-            logger.error("LLM Rate Limit Error - generate sub answer")
-
-        if agent_error:
-            answer_str = LLM_ANSWER_ERROR_MESSAGE
-            cited_documents = []
-            log_results = (
-                agent_error.error_result
-                or "Sub-answer generation failed due to LLM error"
-            )
-
-        else:
-            answer_str = merge_message_runs(response, chunk_separator="")[0].content
-            answer_citation_ids = get_answer_citation_ids(answer_str)
-            cited_documents = [
-                context_docs[id] for id in answer_citation_ids if id < len(context_docs)
-            ]
-            log_results = None
-
-    stop_event = StreamStopInfo(
-        stop_reason=StreamStopReason.FINISHED,
-        stream_type=StreamType.SUB_ANSWER,
-        level=level,
-        level_question_num=question_num,
-    )
-    write_custom_event("stream_finished", stop_event, writer)
-
-    return SubQuestionAnswerGenerationUpdate(
-        answer=answer_str,
-        cited_documents=cited_documents,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial - generate individual sub answer",
-                node_name="generate sub answer",
-                node_start_time=node_start_time,
-                result=log_results or "",
-            )
-        ],
-    )

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

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

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

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

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

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

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

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

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

@@ -1,419 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_content
-from langchain_core.runnables import RunnableConfig
-from langgraph.types import StreamWriter
-
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalState,
-)
-from onyx.agents.agent_search.deep_search.main.models import AgentBaseMetrics
-from onyx.agents.agent_search.deep_search.main.operations import (
-    calculate_initial_agent_stats,
-)
-from onyx.agents.agent_search.deep_search.main.operations import get_query_info
-from onyx.agents.agent_search.deep_search.main.operations import logger
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialAnswerUpdate,
-)
-from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    get_prompt_enrichment_components,
-)
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    trim_prompt_piece,
-)
-from onyx.agents.agent_search.shared_graph_utils.calculations import (
-    get_answer_generation_documents,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_RATELIMIT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_TIMEOUT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AgentLLMErrorType,
-)
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
-from onyx.agents.agent_search.shared_graph_utils.models import InitialAgentResultStats
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
-from onyx.agents.agent_search.shared_graph_utils.operators import (
-    dedup_inference_section_list,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    dispatch_main_answer_stop_info,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_deduplicated_structured_subquestion_documents,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import relevance_from_docs
-from onyx.agents.agent_search.shared_graph_utils.utils import remove_document_citations
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import AgentAnswerPiece
-from onyx.chat.models import ExtendedToolResponse
-from onyx.chat.models import StreamingError
-from onyx.configs.agent_configs import AGENT_ANSWER_GENERATION_BY_FAST_LLM
-from onyx.configs.agent_configs import AGENT_MAX_ANSWER_CONTEXT_DOCS
-from onyx.configs.agent_configs import AGENT_MAX_STREAMED_DOCS_FOR_INITIAL_ANSWER
-from onyx.configs.agent_configs import AGENT_MIN_ORIG_QUESTION_DOCS
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_INITIAL_ANSWER_GENERATION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_LLM_INITIAL_ANSWER_GENERATION,
-)
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
-from onyx.prompts.agent_search import INITIAL_ANSWER_PROMPT_W_SUB_QUESTIONS
-from onyx.prompts.agent_search import (
-    INITIAL_ANSWER_PROMPT_WO_SUB_QUESTIONS,
-)
-from onyx.prompts.agent_search import (
-    SUB_QUESTION_ANSWER_TEMPLATE,
-)
-from onyx.prompts.agent_search import UNKNOWN_ANSWER
-from onyx.tools.tool_implementations.search.search_tool import yield_search_responses
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. The initial answer could not be generated.",
-    rate_limit="LLM Rate Limit Error. The initial answer could not be generated.",
-    general_error="General LLM Error. The initial answer could not be generated.",
-)
-
-
-@log_function_time(print_only=True)
-def generate_initial_answer(
-    state: SubQuestionRetrievalState,
-    config: RunnableConfig,
-    writer: StreamWriter = lambda _: None,
-) -> InitialAnswerUpdate:
-    """
-    LangGraph node to generate the initial answer, using the initial sub-questions/sub-answers and the
-    documents retrieved for the original question.
-    """
-    node_start_time = datetime.now()
-
-    graph_config = cast(GraphConfig, config["metadata"]["config"])
-    question = graph_config.inputs.search_request.query
-    prompt_enrichment_components = get_prompt_enrichment_components(graph_config)
-
-    # get all documents cited in sub-questions
-    structured_subquestion_docs = get_deduplicated_structured_subquestion_documents(
-        state.sub_question_results
-    )
-
-    orig_question_retrieval_documents = state.orig_question_retrieved_documents
-
-    consolidated_context_docs = structured_subquestion_docs.cited_documents
-    counter = 0
-    for original_doc_number, original_doc in enumerate(
-        orig_question_retrieval_documents
-    ):
-        if original_doc_number not in structured_subquestion_docs.cited_documents:
-            if (
-                counter <= AGENT_MIN_ORIG_QUESTION_DOCS
-                or len(consolidated_context_docs) < AGENT_MAX_ANSWER_CONTEXT_DOCS
-            ):
-                consolidated_context_docs.append(original_doc)
-                counter += 1
-
-    # sort docs by their scores - though the scores refer to different questions
-    relevant_docs = dedup_inference_section_list(consolidated_context_docs)
-
-    sub_questions: list[str] = []
-
-    # Create the list of documents to stream out. Start with the
-    # ones that wil be in the context (or, if len == 0, use docs
-    # that were retrieved for the original question)
-    answer_generation_documents = get_answer_generation_documents(
-        relevant_docs=relevant_docs,
-        context_documents=structured_subquestion_docs.context_documents,
-        original_question_docs=orig_question_retrieval_documents,
-        max_docs=AGENT_MAX_STREAMED_DOCS_FOR_INITIAL_ANSWER,
-    )
-
-    # Use the query info from the base document retrieval
-    query_info = get_query_info(state.orig_question_sub_query_retrieval_results)
-
-    assert (
-        graph_config.tooling.search_tool
-    ), "search_tool must be provided for agentic search"
-
-    relevance_list = relevance_from_docs(
-        answer_generation_documents.streaming_documents
-    )
-    for tool_response in yield_search_responses(
-        query=question,
-        reranked_sections=answer_generation_documents.streaming_documents,
-        final_context_sections=answer_generation_documents.context_documents,
-        search_query_info=query_info,
-        get_section_relevance=lambda: relevance_list,
-        search_tool=graph_config.tooling.search_tool,
-    ):
-        write_custom_event(
-            "tool_response",
-            ExtendedToolResponse(
-                id=tool_response.id,
-                response=tool_response.response,
-                level=0,
-                level_question_num=0,  # 0, 0 is the base question
-            ),
-            writer,
-        )
-
-    if len(answer_generation_documents.context_documents) == 0:
-        write_custom_event(
-            "initial_agent_answer",
-            AgentAnswerPiece(
-                answer_piece=UNKNOWN_ANSWER,
-                level=0,
-                level_question_num=0,
-                answer_type="agent_level_answer",
-            ),
-            writer,
-        )
-        dispatch_main_answer_stop_info(0, writer)
-
-        answer = UNKNOWN_ANSWER
-        initial_agent_stats = InitialAgentResultStats(
-            sub_questions={},
-            original_question={},
-            agent_effectiveness={},
-        )
-
-    else:
-        sub_question_answer_results = state.sub_question_results
-
-        # Collect the sub-questions and sub-answers and construct an appropriate
-        # prompt string.
-        # Consider replacing by a function.
-        answered_sub_questions: list[str] = []
-        all_sub_questions: list[str] = []  # Separate list for tracking all questions
-
-        for idx, sub_question_answer_result in enumerate(
-            sub_question_answer_results, start=1
-        ):
-            all_sub_questions.append(sub_question_answer_result.question)
-
-            is_valid_answer = (
-                sub_question_answer_result.verified_high_quality
-                and sub_question_answer_result.answer
-                and sub_question_answer_result.answer != UNKNOWN_ANSWER
-            )
-
-            if is_valid_answer:
-                answered_sub_questions.append(
-                    SUB_QUESTION_ANSWER_TEMPLATE.format(
-                        sub_question=sub_question_answer_result.question,
-                        sub_answer=sub_question_answer_result.answer,
-                        sub_question_num=idx,
-                    )
-                )
-
-        sub_question_answer_str = (
-            "\n\n------\n\n".join(answered_sub_questions)
-            if answered_sub_questions
-            else ""
-        )
-
-        # Use the appropriate prompt based on whether there are sub-questions.
-        base_prompt = (
-            INITIAL_ANSWER_PROMPT_W_SUB_QUESTIONS
-            if answered_sub_questions
-            else INITIAL_ANSWER_PROMPT_WO_SUB_QUESTIONS
-        )
-
-        sub_questions = all_sub_questions  # Replace the original assignment
-
-        model = (
-            graph_config.tooling.fast_llm
-            if AGENT_ANSWER_GENERATION_BY_FAST_LLM
-            else graph_config.tooling.primary_llm
-        )
-
-        doc_context = format_docs(answer_generation_documents.context_documents)
-        doc_context = trim_prompt_piece(
-            config=model.config,
-            prompt_piece=doc_context,
-            reserved_str=(
-                base_prompt
-                + sub_question_answer_str
-                + prompt_enrichment_components.persona_prompts.contextualized_prompt
-                + prompt_enrichment_components.history
-                + prompt_enrichment_components.date_str
-            ),
-        )
-
-        msg = [
-            HumanMessage(
-                content=base_prompt.format(
-                    question=question,
-                    answered_sub_questions=remove_document_citations(
-                        sub_question_answer_str
-                    ),
-                    relevant_docs=doc_context,
-                    persona_specification=prompt_enrichment_components.persona_prompts.contextualized_prompt,
-                    history=prompt_enrichment_components.history,
-                    date_prompt=prompt_enrichment_components.date_str,
-                )
-            )
-        ]
-
-        streamed_tokens: list[str] = [""]
-        dispatch_timings: list[float] = []
-
-        agent_error: AgentErrorLog | None = None
-
-        def stream_initial_answer() -> list[str]:
-            response: list[str] = []
-            for message in model.stream(
-                msg,
-                timeout_override=AGENT_TIMEOUT_CONNECT_LLM_INITIAL_ANSWER_GENERATION,
-            ):
-                # TODO: in principle, the answer here COULD contain images, but we don't support that yet
-                content = message.content
-                if not isinstance(content, str):
-                    raise ValueError(
-                        f"Expected content to be a string, but got {type(content)}"
-                    )
-                start_stream_token = datetime.now()
-
-                write_custom_event(
-                    "initial_agent_answer",
-                    AgentAnswerPiece(
-                        answer_piece=content,
-                        level=0,
-                        level_question_num=0,
-                        answer_type="agent_level_answer",
-                    ),
-                    writer,
-                )
-                end_stream_token = datetime.now()
-                dispatch_timings.append(
-                    (end_stream_token - start_stream_token).microseconds
-                )
-                response.append(content)
-            return response
-
-        try:
-            streamed_tokens = run_with_timeout(
-                AGENT_TIMEOUT_LLM_INITIAL_ANSWER_GENERATION,
-                stream_initial_answer,
-            )
-
-        except (LLMTimeoutError, TimeoutError):
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.TIMEOUT,
-                error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-                error_result=_llm_node_error_strings.timeout,
-            )
-            logger.error("LLM Timeout Error - generate initial answer")
-
-        except LLMRateLimitError:
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.RATE_LIMIT,
-                error_message=AGENT_LLM_RATELIMIT_MESSAGE,
-                error_result=_llm_node_error_strings.rate_limit,
-            )
-            logger.error("LLM Rate Limit Error - generate initial answer")
-
-        if agent_error:
-            write_custom_event(
-                "initial_agent_answer",
-                StreamingError(
-                    error=AGENT_LLM_TIMEOUT_MESSAGE,
-                ),
-                writer,
-            )
-            return InitialAnswerUpdate(
-                initial_answer=None,
-                answer_error=AgentErrorLog(
-                    error_message=agent_error.error_message or "An LLM error occurred",
-                    error_type=agent_error.error_type,
-                    error_result=agent_error.error_result,
-                ),
-                initial_agent_stats=None,
-                generated_sub_questions=sub_questions,
-                agent_base_end_time=None,
-                agent_base_metrics=None,
-                log_messages=[
-                    get_langgraph_node_log_string(
-                        graph_component="initial - generate initial answer",
-                        node_name="generate initial answer",
-                        node_start_time=node_start_time,
-                        result=agent_error.error_result or "An LLM error occurred",
-                    )
-                ],
-            )
-
-        logger.debug(
-            f"Average dispatch time for initial answer: {sum(dispatch_timings) / len(dispatch_timings)}"
-        )
-
-        dispatch_main_answer_stop_info(0, writer)
-        response = merge_content(*streamed_tokens)
-        answer = cast(str, response)
-
-        initial_agent_stats = calculate_initial_agent_stats(
-            state.sub_question_results, state.orig_question_retrieval_stats
-        )
-
-        logger.debug(
-            f"\n\nYYYYY--Sub-Questions:\n\n{sub_question_answer_str}\n\nStats:\n\n"
-        )
-
-        if initial_agent_stats:
-            logger.debug(initial_agent_stats.original_question)
-            logger.debug(initial_agent_stats.sub_questions)
-            logger.debug(initial_agent_stats.agent_effectiveness)
-
-    agent_base_end_time = datetime.now()
-
-    if agent_base_end_time and state.agent_start_time:
-        duration_s = (agent_base_end_time - state.agent_start_time).total_seconds()
-    else:
-        duration_s = None
-
-    agent_base_metrics = AgentBaseMetrics(
-        num_verified_documents_total=len(relevant_docs),
-        num_verified_documents_core=state.orig_question_retrieval_stats.verified_count,
-        verified_avg_score_core=state.orig_question_retrieval_stats.verified_avg_scores,
-        num_verified_documents_base=initial_agent_stats.sub_questions.get(
-            "num_verified_documents"
-        ),
-        verified_avg_score_base=initial_agent_stats.sub_questions.get(
-            "verified_avg_score"
-        ),
-        base_doc_boost_factor=initial_agent_stats.agent_effectiveness.get(
-            "utilized_chunk_ratio"
-        ),
-        support_boost_factor=initial_agent_stats.agent_effectiveness.get(
-            "support_ratio"
-        ),
-        duration_s=duration_s,
-    )
-
-    return InitialAnswerUpdate(
-        initial_answer=answer,
-        initial_agent_stats=initial_agent_stats,
-        generated_sub_questions=sub_questions,
-        agent_base_end_time=agent_base_end_time,
-        agent_base_metrics=agent_base_metrics,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial - generate initial answer",
-                node_name="generate initial answer",
-                node_start_time=node_start_time,
-                result="",
-            )
-        ],
-    )

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

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

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

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

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

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

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

@@ -1,81 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.graph_builder import (
-    answer_query_graph_builder,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_sub_answers.edges import (
-    parallelize_initial_sub_question_answering,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_sub_answers.nodes.decompose_orig_question import (
-    decompose_orig_question,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_sub_answers.nodes.format_initial_sub_answers import (
-    format_initial_sub_answers,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_sub_answers.states import (
-    SubQuestionAnsweringInput,
-)
-from onyx.agents.agent_search.deep_search.initial.generate_sub_answers.states import (
-    SubQuestionAnsweringState,
-)
-from onyx.utils.logger import setup_logger
-
-logger = setup_logger()
-
-test_mode = False
-
-
-def generate_sub_answers_graph_builder() -> StateGraph:
-    """
-    LangGraph graph builder for the initial sub-answer generation process.
-    It generates the initial sub-questions and produces the answers.
-    """
-
-    graph = StateGraph(
-        state_schema=SubQuestionAnsweringState,
-        input=SubQuestionAnsweringInput,
-    )
-
-    # Decompose the original question into sub-questions
-    graph.add_node(
-        node="decompose_orig_question",
-        action=decompose_orig_question,
-    )
-
-    # The sub-graph that executes the initial sub-question answering for
-    # each of the sub-questions.
-    answer_sub_question_subgraphs = answer_query_graph_builder().compile()
-    graph.add_node(
-        node="answer_sub_question_subgraphs",
-        action=answer_sub_question_subgraphs,
-    )
-
-    # Node that collects and formats the initial sub-question answers
-    graph.add_node(
-        node="format_initial_sub_question_answers",
-        action=format_initial_sub_answers,
-    )
-
-    graph.add_edge(
-        start_key=START,
-        end_key="decompose_orig_question",
-    )
-
-    graph.add_conditional_edges(
-        source="decompose_orig_question",
-        path=parallelize_initial_sub_question_answering,
-        path_map=["answer_sub_question_subgraphs"],
-    )
-    graph.add_edge(
-        start_key=["answer_sub_question_subgraphs"],
-        end_key="format_initial_sub_question_answers",
-    )
-
-    graph.add_edge(
-        start_key="format_initial_sub_question_answers",
-        end_key=END,
-    )
-
-    return graph

backend/onyx/agents/agent_search/deep_search/initial/generate_sub_answers/nodes/decompose_orig_question.py

@@ -1,188 +0,0 @@
-from datetime import datetime
-from typing import cast
-
-from langchain_core.messages import HumanMessage
-from langchain_core.messages import merge_content
-from langchain_core.runnables import RunnableConfig
-from langgraph.types import StreamWriter
-
-from onyx.agents.agent_search.deep_search.initial.generate_initial_answer.states import (
-    SubQuestionRetrievalState,
-)
-from onyx.agents.agent_search.deep_search.main.models import (
-    AgentRefinedMetrics,
-)
-from onyx.agents.agent_search.deep_search.main.operations import dispatch_subquestion
-from onyx.agents.agent_search.deep_search.main.operations import (
-    dispatch_subquestion_sep,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialQuestionDecompositionUpdate,
-)
-from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    build_history_prompt,
-)
-from onyx.agents.agent_search.shared_graph_utils.models import BaseMessage_Content
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
-from onyx.agents.agent_search.shared_graph_utils.utils import dispatch_separated
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import StreamStopInfo
-from onyx.chat.models import StreamStopReason
-from onyx.chat.models import StreamType
-from onyx.chat.models import SubQuestionPiece
-from onyx.configs.agent_configs import AGENT_NUM_DOCS_FOR_DECOMPOSITION
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_SUBQUESTION_GENERATION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_LLM_SUBQUESTION_GENERATION,
-)
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
-from onyx.prompts.agent_search import (
-    INITIAL_DECOMPOSITION_PROMPT_QUESTIONS_AFTER_SEARCH_ASSUMING_REFINEMENT,
-)
-from onyx.prompts.agent_search import (
-    INITIAL_QUESTION_DECOMPOSITION_PROMPT_ASSUMING_REFINEMENT,
-)
-from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-logger = setup_logger()
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. Sub-questions could not be generated.",
-    rate_limit="LLM Rate Limit Error. Sub-questions could not be generated.",
-    general_error="General LLM Error. Sub-questions could not be generated.",
-)
-
-
-@log_function_time(print_only=True)
-def decompose_orig_question(
-    state: SubQuestionRetrievalState,
-    config: RunnableConfig,
-    writer: StreamWriter = lambda _: None,
-) -> InitialQuestionDecompositionUpdate:
-    """
-    LangGraph node to decompose the original question into sub-questions.
-    """
-    node_start_time = datetime.now()
-
-    graph_config = cast(GraphConfig, config["metadata"]["config"])
-    question = graph_config.inputs.search_request.query
-    perform_initial_search_decomposition = (
-        graph_config.behavior.perform_initial_search_decomposition
-    )
-    # Get the rewritten queries in a defined format
-    model = graph_config.tooling.fast_llm
-
-    history = build_history_prompt(graph_config, question)
-
-    # Use the initial search results to inform the decomposition
-    agent_start_time = datetime.now()
-
-    # Initial search to inform decomposition. Just get top 3 fits
-
-    if perform_initial_search_decomposition:
-        # Due to unfortunate state representation in LangGraph, we need here to double check that the retrieval has
-        # happened prior to this point, allowing silent failure here since it is not critical for decomposition in
-        # all queries.
-        if not state.exploratory_search_results:
-            logger.error("Initial search for decomposition failed")
-
-        sample_doc_str = "\n\n".join(
-            [
-                doc.combined_content
-                for doc in state.exploratory_search_results[
-                    :AGENT_NUM_DOCS_FOR_DECOMPOSITION
-                ]
-            ]
-        )
-
-        decomposition_prompt = INITIAL_DECOMPOSITION_PROMPT_QUESTIONS_AFTER_SEARCH_ASSUMING_REFINEMENT.format(
-            question=question, sample_doc_str=sample_doc_str, history=history
-        )
-
-    else:
-        decomposition_prompt = (
-            INITIAL_QUESTION_DECOMPOSITION_PROMPT_ASSUMING_REFINEMENT.format(
-                question=question, history=history
-            )
-        )
-
-    # Start decomposition
-
-    msg = [HumanMessage(content=decomposition_prompt)]
-
-    # Send the initial question as a subquestion with number 0
-    write_custom_event(
-        "decomp_qs",
-        SubQuestionPiece(
-            sub_question=question,
-            level=0,
-            level_question_num=0,
-        ),
-        writer,
-    )
-
-    # dispatches custom events for subquestion tokens, adding in subquestion ids.
-
-    streamed_tokens: list[BaseMessage_Content] = []
-
-    try:
-        streamed_tokens = run_with_timeout(
-            AGENT_TIMEOUT_LLM_SUBQUESTION_GENERATION,
-            dispatch_separated,
-            model.stream(
-                msg,
-                timeout_override=AGENT_TIMEOUT_CONNECT_LLM_SUBQUESTION_GENERATION,
-            ),
-            dispatch_subquestion(0, writer),
-            sep_callback=dispatch_subquestion_sep(0, writer),
-        )
-
-        decomposition_response = merge_content(*streamed_tokens)
-
-        list_of_subqs = cast(str, decomposition_response).split("\n")
-
-        initial_sub_questions = [sq.strip() for sq in list_of_subqs if sq.strip() != ""]
-        log_result = f"decomposed original question into {len(initial_sub_questions)} subquestions"
-
-        stop_event = StreamStopInfo(
-            stop_reason=StreamStopReason.FINISHED,
-            stream_type=StreamType.SUB_QUESTIONS,
-            level=0,
-        )
-        write_custom_event("stream_finished", stop_event, writer)
-
-    except (LLMTimeoutError, TimeoutError) as e:
-        logger.error("LLM Timeout Error - decompose orig question")
-        raise e  # fail loudly on this critical step
-    except LLMRateLimitError as e:
-        logger.error("LLM Rate Limit Error - decompose orig question")
-        raise e
-
-    return InitialQuestionDecompositionUpdate(
-        initial_sub_questions=initial_sub_questions,
-        agent_start_time=agent_start_time,
-        agent_refined_start_time=None,
-        agent_refined_end_time=None,
-        agent_refined_metrics=AgentRefinedMetrics(
-            refined_doc_boost_factor=None,
-            refined_question_boost_factor=None,
-            duration_s=None,
-        ),
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial - generate sub answers",
-                node_name="decompose original question",
-                node_start_time=node_start_time,
-                result=log_result,
-            )
-        ],
-    )

backend/onyx/agents/agent_search/deep_search/initial/generate_sub_answers/nodes/format_initial_sub_answers.py

@@ -1,50 +0,0 @@
-from datetime import datetime
-
-from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
-    AnswerQuestionOutput,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    SubQuestionResultsUpdate,
-)
-from onyx.agents.agent_search.shared_graph_utils.operators import (
-    dedup_inference_sections,
-)
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_langgraph_node_log_string,
-)
-
-
-def format_initial_sub_answers(
-    state: AnswerQuestionOutput,
-) -> SubQuestionResultsUpdate:
-    """
-    LangGraph node to format the answers to the initial sub-questions, including
-    deduping verified documents and context documents.
-    """
-    node_start_time = datetime.now()
-
-    documents = []
-    context_documents = []
-    cited_documents = []
-    answer_results = state.answer_results
-    for answer_result in answer_results:
-        documents.extend(answer_result.verified_reranked_documents)
-        context_documents.extend(answer_result.context_documents)
-        cited_documents.extend(answer_result.cited_documents)
-
-    return SubQuestionResultsUpdate(
-        # Deduping is done by the documents operator for the main graph
-        # so we might not need to dedup here
-        verified_reranked_documents=dedup_inference_sections(documents, []),
-        context_documents=dedup_inference_sections(context_documents, []),
-        cited_documents=dedup_inference_sections(cited_documents, []),
-        sub_question_results=answer_results,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="initial - generate sub answers",
-                node_name="format initial sub answers",
-                node_start_time=node_start_time,
-                result="",
-            )
-        ],
-    )

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

@@ -1,34 +0,0 @@
-from typing import TypedDict
-
-from onyx.agents.agent_search.core_state import CoreState
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialAnswerUpdate,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    InitialQuestionDecompositionUpdate,
-)
-from onyx.agents.agent_search.deep_search.main.states import (
-    SubQuestionResultsUpdate,
-)
-from onyx.context.search.models import InferenceSection
-
-
-### States ###
-class SubQuestionAnsweringInput(CoreState):
-    exploratory_search_results: list[InferenceSection]
-
-
-## Graph State
-class SubQuestionAnsweringState(
-    # This includes the core state
-    SubQuestionAnsweringInput,
-    InitialQuestionDecompositionUpdate,
-    InitialAnswerUpdate,
-    SubQuestionResultsUpdate,
-):
-    pass
-
-
-## Graph Output State
-class SubQuestionAnsweringOutput(TypedDict):
-    log_messages: list[str]

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

@@ -1,81 +0,0 @@
-from langgraph.graph import END
-from langgraph.graph import START
-from langgraph.graph import StateGraph
-
-from onyx.agents.agent_search.deep_search.initial.retrieve_orig_question_docs.nodes.format_orig_question_search_input import (
-    format_orig_question_search_input,
-)
-from onyx.agents.agent_search.deep_search.initial.retrieve_orig_question_docs.nodes.format_orig_question_search_output import (
-    format_orig_question_search_output,
-)
-from onyx.agents.agent_search.deep_search.initial.retrieve_orig_question_docs.states import (
-    BaseRawSearchInput,
-)
-from onyx.agents.agent_search.deep_search.initial.retrieve_orig_question_docs.states import (
-    BaseRawSearchOutput,
-)
-from onyx.agents.agent_search.deep_search.initial.retrieve_orig_question_docs.states import (
-    BaseRawSearchState,
-)
-from onyx.agents.agent_search.deep_search.shared.expanded_retrieval.graph_builder import (
-    expanded_retrieval_graph_builder,
-)
-
-
-def retrieve_orig_question_docs_graph_builder() -> StateGraph:
-    """
-    LangGraph graph builder for the retrieval of documents
-    that are relevant to the original question. This is
-    largely a wrapper around the expanded retrieval process to
-    ensure parallelism with the sub-question answer process.
-    """
-    graph = StateGraph(
-        state_schema=BaseRawSearchState,
-        input=BaseRawSearchInput,
-        output=BaseRawSearchOutput,
-    )
-
-    ### Add nodes ###
-
-    # Format the original question search output
-    graph.add_node(
-        node="format_orig_question_search_output",
-        action=format_orig_question_search_output,
-    )
-
-    # The sub-graph that executes the expanded retrieval process
-    expanded_retrieval = expanded_retrieval_graph_builder().compile()
-    graph.add_node(
-        node="retrieve_orig_question_docs_subgraph",
-        action=expanded_retrieval,
-    )
-
-    # Format the original question search input
-    graph.add_node(
-        node="format_orig_question_search_input",
-        action=format_orig_question_search_input,
-    )
-
-    ### Add edges ###
-
-    graph.add_edge(start_key=START, end_key="format_orig_question_search_input")
-
-    graph.add_edge(
-        start_key="format_orig_question_search_input",
-        end_key="retrieve_orig_question_docs_subgraph",
-    )
-    graph.add_edge(
-        start_key="retrieve_orig_question_docs_subgraph",
-        end_key="format_orig_question_search_output",
-    )
-
-    graph.add_edge(
-        start_key="format_orig_question_search_output",
-        end_key=END,
-    )
-
-    return graph
-
-
-if __name__ == "__main__":
-    pass