nit

.github/CODEOWNERS

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

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

@@ -65,7 +65,6 @@ 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

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

@@ -4,6 +4,9 @@ on:
   push:
     tags:
       - "*"
+    paths:
+      - 'backend/model_server/**'
+      - 'backend/Dockerfile.model_server'
 
 env:
   REGISTRY_IMAGE: ${{ contains(github.ref_name, 'cloud') && 'onyxdotapp/onyx-model-server-cloud' || 'onyxdotapp/onyx-model-server' }}
@@ -12,43 +15,7 @@ env:
   BUILDKIT_PROGRESS: plain
 
 jobs:
-
-#   Bypassing this for now as the idea of not building is glitching
-#   releases and builds that depends on everything being tagged in docker
-#   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
-
-  check_model_server_changes:
-    runs-on: ubuntu-latest
-    outputs:
-      changed: "true"
-    steps:
-      - name: Bypass check and set output
-        run: echo "changed=true" >> $GITHUB_OUTPUT
-        
   build-amd64:
-    needs: [check_model_server_changes]
-    if: needs.check_model_server_changes.outputs.changed == 'true'
     runs-on:
       [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}-amd64"]
     steps:
@@ -88,8 +55,6 @@ 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:
@@ -129,8 +94,7 @@ 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
@@ -198,47 +198,43 @@ 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-integration-tests.yml

@@ -99,7 +99,7 @@ jobs:
           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.multitenant-dev.yml -p danswer-stack up -d
         id: start_docker_multi_tenant
 
       # In practice, `cloud` Auth type would require OAUTH credentials to be set.
@@ -108,13 +108,12 @@ jobs:
           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 \
@@ -144,28 +143,24 @@ jobs:
       - 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.multitenant-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 +190,15 @@ 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 +208,6 @@ 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
@@ -245,13 +229,13 @@ jobs:
         if: always()
         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
+          docker compose -f docker-compose.dev.yml -p danswer-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
+          docker compose -f docker-compose.dev.yml -p danswer-stack logs --no-color > $GITHUB_WORKSPACE/docker-compose.log || true
 
       - name: Upload logs
         if: always()
@@ -265,4 +249,4 @@ jobs:
         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

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

@@ -1,7 +1,6 @@
 name: Connector Tests
 
 on:
-  merge_group:
   pull_request:
     branches: [main]
   schedule:
@@ -45,14 +44,11 @@ env:
   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/
-    runs-on: [runs-on, runner=8cpu-linux-x64, "run-id=${{ github.run_id }}"]
+    runs-on: [runs-on,runner=8cpu-linux-x64,"run-id=${{ github.run_id }}"]
 
     env:
       PYTHONPATH: ./backend
@@ -75,8 +71,6 @@ 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}"

.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
-          

.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 +24,113 @@
 </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/onyx/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
 

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/3934b1bc7b62_update_github_connector_repo_name_to_.py

@@ -1,125 +0,0 @@
-"""Update GitHub connector repo_name to repositories
-
-Revision ID: 3934b1bc7b62
-Revises: b7c2b63c4a03
-Create Date: 2025-03-05 10:50:30.516962
-
-"""
-from alembic import op
-import sqlalchemy as sa
-import json
-import logging
-
-# revision identifiers, used by Alembic.
-revision = "3934b1bc7b62"
-down_revision = "b7c2b63c4a03"
-branch_labels = None
-depends_on = None
-
-logger = logging.getLogger("alembic.runtime.migration")
-
-
-def upgrade() -> None:
-    # Get all GitHub connectors
-    conn = op.get_bind()
-
-    # First get all GitHub connectors
-    github_connectors = conn.execute(
-        sa.text(
-            """
-            SELECT id, connector_specific_config
-            FROM connector
-            WHERE source = 'GITHUB'
-            """
-        )
-    ).fetchall()
-
-    # Update each connector's config
-    updated_count = 0
-    for connector_id, config in github_connectors:
-        try:
-            if not config:
-                logger.warning(f"Connector {connector_id} has no config, skipping")
-                continue
-
-            # Parse the config if it's a string
-            if isinstance(config, str):
-                config = json.loads(config)
-
-            if "repo_name" not in config:
-                continue
-
-            # Create new config with repositories instead of repo_name
-            new_config = dict(config)
-            repo_name_value = new_config.pop("repo_name")
-            new_config["repositories"] = repo_name_value
-
-            # Update the connector with the new config
-            conn.execute(
-                sa.text(
-                    """
-                    UPDATE connector
-                    SET connector_specific_config = :new_config
-                    WHERE id = :connector_id
-                    """
-                ),
-                {"connector_id": connector_id, "new_config": json.dumps(new_config)},
-            )
-            updated_count += 1
-        except Exception as e:
-            logger.error(f"Error updating connector {connector_id}: {str(e)}")
-
-
-def downgrade() -> None:
-    # Get all GitHub connectors
-    conn = op.get_bind()
-
-    logger.debug(
-        "Starting rollback of GitHub connectors from repositories to repo_name"
-    )
-
-    github_connectors = conn.execute(
-        sa.text(
-            """
-            SELECT id, connector_specific_config
-            FROM connector
-            WHERE source = 'GITHUB'
-            """
-        )
-    ).fetchall()
-
-    logger.debug(f"Found {len(github_connectors)} GitHub connectors to rollback")
-
-    # Revert each GitHub connector to use repo_name instead of repositories
-    reverted_count = 0
-    for connector_id, config in github_connectors:
-        try:
-            if not config:
-                continue
-
-            # Parse the config if it's a string
-            if isinstance(config, str):
-                config = json.loads(config)
-
-            if "repositories" not in config:
-                continue
-
-            # Create new config with repo_name instead of repositories
-            new_config = dict(config)
-            repositories_value = new_config.pop("repositories")
-            new_config["repo_name"] = repositories_value
-
-            # Update the connector with the new config
-            conn.execute(
-                sa.text(
-                    """
-                    UPDATE connector
-                    SET connector_specific_config = :new_config
-                    WHERE id = :connector_id
-                    """
-                ),
-                {"new_config": json.dumps(new_config), "connector_id": connector_id},
-            )
-            reverted_count += 1
-        except Exception as e:
-            logger.error(f"Error reverting connector {connector_id}: {str(e)}")

backend/alembic/versions/3bd4c84fe72f_improved_index.py

@@ -1,84 +0,0 @@
-"""improved index
-
-Revision ID: 3bd4c84fe72f
-Revises: 8f43500ee275
-Create Date: 2025-02-26 13:07:56.217791
-
-"""
-from alembic import op
-
-
-# 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() -> None:
-    # Create a GIN index for full-text search on chat_message.message
-    op.execute(
-        """
-        ALTER TABLE chat_message
-        ADD COLUMN message_tsv tsvector
-        GENERATED ALWAYS AS (to_tsvector('english', message)) STORED;
-        """
-    )
-
-    # Commit the current transaction before creating concurrent indexes
-    op.execute("COMMIT")
-
-    op.execute(
-        """
-        CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_message_tsv
-        ON chat_message
-        USING GIN (message_tsv)
-        """
-    )
-
-    # Also add a stored tsvector column for chat_session.description
-    op.execute(
-        """
-        ALTER TABLE chat_session
-        ADD COLUMN description_tsv tsvector
-        GENERATED ALWAYS AS (to_tsvector('english', coalesce(description, ''))) STORED;
-        """
-    )
-
-    # Commit again before creating the second concurrent index
-    op.execute("COMMIT")
-
-    op.execute(
-        """
-        CREATE INDEX CONCURRENTLY IF NOT EXISTS idx_chat_session_desc_tsv
-        ON chat_session
-        USING GIN (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/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/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/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/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_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

@@ -1,10 +1,10 @@
 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_system_tasks as base_beat_system_tasks,
+)
 from onyx.background.celery.tasks.beat_schedule import (
     beat_task_templates as base_beat_task_templates,
 )

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/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

@@ -16,20 +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
-
-    Only messages of type USER are returned
-    """
     chat_sessions = fetch_chat_sessions_eagerly_by_time(
         start=period[0],
         end=period[1],
@@ -59,17 +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

@@ -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 +9,12 @@ 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()
 
@@ -346,8 +342,7 @@ def _fetch_all_page_restrictions(
 
 
 def confluence_doc_sync(
-    cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
+    cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres
@@ -359,11 +354,7 @@ 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)
 

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 +10,57 @@ 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}")
+    for user_result in confluence_client.paginated_cql_user_retrieval():
+        logger.debug(f"Processing groups for user: {user_result}")
 
-        email = user.email
+        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)
+        if not group_member_emails:
+            logger.warning(f"No groups found for user with email: {email}")
         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

@@ -32,8 +32,7 @@ def _get_slim_doc_generator(
 
 
 def gmail_doc_sync(
-    cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
+    cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres

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

@@ -62,14 +62,12 @@ 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 +104,7 @@ 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 +121,6 @@ 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())
 
@@ -145,8 +132,7 @@ def _get_permissions_from_slim_doc(
 
 
 def gdrive_doc_sync(
-    cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
+    cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres

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

@@ -5,7 +5,7 @@ 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
@@ -17,7 +17,7 @@ logger = setup_logger()
 def _get_slack_document_ids_and_channels(
     cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
 ) -> 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)
@@ -123,8 +123,7 @@ def _fetch_channel_permissions(
 
 
 def slack_doc_sync(
-    cc_pair: ConnectorCredentialPair,
-    callback: IndexingHeartbeatInterface | None,
+    cc_pair: ConnectorCredentialPair, callback: IndexingHeartbeatInterface | None
 ) -> list[DocExternalAccess]:
     """
     Adds the external permissions to the documents in postgres

backend/ee/onyx/external_permissions/sync_params.py

@@ -28,7 +28,6 @@ DocSyncFuncType = Callable[
 
 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 ee_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,
 )
@@ -128,7 +128,7 @@ def get_application() -> FastAPI:
     include_router_with_global_prefix_prepended(application, query_router)
     include_router_with_global_prefix_prepended(application, chat_router)
     include_router_with_global_prefix_prepended(application, standard_answer_router)
-    include_router_with_global_prefix_prepended(application, ee_oauth_router)
+    include_router_with_global_prefix_prepended(application, oauth_router)
 
     # Enterprise-only global settings
     include_router_with_global_prefix_prepended(
@@ -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
@@ -216,7 +216,7 @@ 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 +231,6 @@ 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

@@ -33,7 +33,7 @@ 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
 
 
@@ -49,7 +49,7 @@ async def _get_tenant_id_from_request(
     """
     # 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

backend/ee/onyx/server/oauth.py

@@ -0,0 +1,631 @@
+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")
+    )
+    session: str
+
+    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")
+    session: GoogleDriveOAuth.OAuthSession
+    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

@@ -1,362 +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
-        "read:content-details:confluence%20"  # for permission sync
-        "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/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,
     )

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,
@@ -48,15 +43,10 @@ def fetch_and_process_chat_session_history(
     feedback_type: QAFeedbackType | None,
     limit: int | None = 500,
 ) -> list[ChatSessionSnapshot]:
-    # observed to be slow a scale of 8192 sessions and 4 messages per session
-
-    # this is a little slow (5 seconds)
     chat_sessions = fetch_chat_sessions_eagerly_by_time(
         start=start, end=end, db_session=db_session, limit=limit
     )
 
-    # this is VERY slow (80 seconds) due to create_chat_chain being called
-    # for each session. Needs optimizing.
     chat_session_snapshots = [
         snapshot_from_chat_session(chat_session=chat_session, db_session=db_session)
         for chat_session in chat_sessions
@@ -117,17 +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
@@ -143,7 +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,
@@ -163,12 +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,
@@ -185,16 +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,
     )
 
@@ -205,12 +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,
@@ -232,9 +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
 
 
@@ -245,14 +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.",
-        )
-
-    # this call is very expensive and is timing out via endpoint
-    # TODO: optimize call and/or generate via background task
     complete_chat_session_history = fetch_and_process_chat_session_history(
         db_session=db_session,
         start=start or datetime.fromtimestamp(0, tz=timezone.utc),
@@ -263,9 +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
@@ -41,15 +36,17 @@ 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 +55,13 @@ 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 +70,15 @@ 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 +99,7 @@ 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
         )
@@ -130,48 +126,52 @@ 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 +180,6 @@ 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 +188,7 @@ 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 +212,8 @@ 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

@@ -1,52 +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)
-    gated_tenants_bytes = cast(set[bytes], redis_client.smembers(GATED_TENANTS_KEY))
-    return {tenant_id.decode("utf-8") for tenant_id in gated_tenants_bytes}

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

@@ -55,11 +55,7 @@ logger = logging.getLogger(__name__)
 async def get_or_provision_tenant(
     email: str, referral_source: str | None = None, request: Request | None = None
 ) -> str:
-    """
-    Get existing tenant ID for an email or create a new tenant if none exists.
-    This function should only be called after we have verified we want this user's tenant to exist.
-    It returns the tenant ID associated with the email, creating a new tenant if necessary.
-    """
+    """Get existing tenant ID for an email or create a new tenant if none exists."""
     if not MULTI_TENANT:
         return POSTGRES_DEFAULT_SCHEMA
 
@@ -108,21 +104,21 @@ 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 = (
@@ -138,7 +134,7 @@ 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,
@@ -204,35 +200,14 @@ 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)
@@ -244,6 +219,25 @@ 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/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:

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
@@ -29,13 +28,11 @@ 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 +78,7 @@ 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 +91,19 @@ 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 +173,17 @@ 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 +218,9 @@ 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:
@@ -341,7 +321,6 @@ 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):
@@ -385,7 +364,6 @@ 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):
@@ -457,7 +435,7 @@ 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 +445,6 @@ 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]:
@@ -564,7 +503,6 @@ 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,
         )
@@ -621,32 +559,15 @@ 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/utils.py

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

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

@@ -5,14 +5,14 @@ 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.basic_use_tool_response import (
+    basic_use_tool_response,
+)
+from onyx.agents.agent_search.orchestration.nodes.llm_tool_choice import llm_tool_choice
 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.agents.agent_search.orchestration.nodes.tool_call import tool_call
 from onyx.utils.logger import setup_logger
 
 logger = setup_logger()
@@ -33,13 +33,13 @@ def basic_graph_builder() -> StateGraph:
     )
 
     graph.add_node(
-        node="choose_tool",
-        action=choose_tool,
+        node="llm_tool_choice",
+        action=llm_tool_choice,
     )
 
     graph.add_node(
-        node="call_tool",
-        action=call_tool,
+        node="tool_call",
+        action=tool_call,
     )
 
     graph.add_node(
@@ -51,12 +51,12 @@ def basic_graph_builder() -> StateGraph:
 
     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_edge(start_key="prepare_tool_input", end_key="llm_tool_choice")
 
-    graph.add_conditional_edges("choose_tool", should_continue, ["call_tool", END])
+    graph.add_conditional_edges("llm_tool_choice", should_continue, ["tool_call", END])
 
     graph.add_edge(
-        start_key="call_tool",
+        start_key="tool_call",
         end_key="basic_use_tool_response",
     )
 
@@ -73,7 +73,7 @@ def should_continue(state: BasicState) -> str:
         # If there are no tool calls, basic graph already streamed the answer
         END
         if state.tool_choice is None
-        else "call_tool"
+        else "tool_call"
     )
 
 
@@ -85,7 +85,7 @@ if __name__ == "__main__":
 
     graph = basic_graph_builder()
     compiled_graph = graph.compile()
-    input = BasicInput(unused=True)
+    input = BasicInput(_unused=True)
     primary_llm, fast_llm = get_default_llms()
     with get_session_context_manager() as db_session:
         config, _ = get_test_config(

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

@@ -17,7 +17,7 @@ from onyx.agents.agent_search.orchestration.states import ToolChoiceUpdate
 class BasicInput(BaseModel):
     # Langgraph needs a nonempty input, but we pass in all static
     # data through a RunnableConfig.
-    unused: bool = True
+    _unused: bool = True
 
 
 ## Graph Output State

backend/onyx/agents/agent_search/core_state.py

@@ -9,6 +9,7 @@ class CoreState(BaseModel):
     This is the core state that is shared across all subgraphs.
     """
 
+    base_question: str = ""
     log_messages: Annotated[list[str], add] = []
 
 
@@ -17,4 +18,4 @@ class SubgraphCoreState(BaseModel):
     This is the core state that is shared across all subgraphs.
     """
 
-    log_messages: Annotated[list[str], add] = []
+    log_messages: Annotated[list[str], add]

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

@@ -1,8 +1,8 @@
 from datetime import datetime
 from typing import cast
 
-from langchain_core.messages import BaseMessage
 from langchain_core.messages import HumanMessage
+from langchain_core.messages import merge_message_runs
 from langchain_core.runnables.config import RunnableConfig
 
 from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer.states import (
@@ -12,46 +12,14 @@ from onyx.agents.agent_search.deep_search.initial.generate_individual_sub_answer
     SubQuestionAnswerCheckUpdate,
 )
 from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    binary_string_test,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_RATELIMIT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_LLM_TIMEOUT_MESSAGE,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_POSITIVE_VALUE_STR,
-)
-from onyx.agents.agent_search.shared_graph_utils.constants import AgentLLMErrorType
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
-from onyx.agents.agent_search.shared_graph_utils.models import LLMNodeErrorStrings
 from onyx.agents.agent_search.shared_graph_utils.utils import (
     get_langgraph_node_log_string,
 )
 from onyx.agents.agent_search.shared_graph_utils.utils import parse_question_id
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_VALIDATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_CHECK
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_SUBANSWER_CHECK
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import SUB_ANSWER_CHECK_PROMPT
 from onyx.prompts.agent_search import UNKNOWN_ANSWER
-from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
-
-logger = setup_logger()
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. The sub-answer will be treated as 'relevant'",
-    rate_limit="LLM Rate Limit Error. The sub-answer will be treated as 'relevant'",
-    general_error="General LLM Error. The sub-answer will be treated as 'relevant'",
-)
 
 
-@log_function_time(print_only=True)
 def check_sub_answer(
     state: AnswerQuestionState, config: RunnableConfig
 ) -> SubQuestionAnswerCheckUpdate:
@@ -85,43 +53,14 @@ def check_sub_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,
+    response = list(
+        fast_llm.stream(
             prompt=msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_CHECK,
-            max_tokens=AGENT_MAX_TOKENS_VALIDATION,
         )
+    )
 
-        quality_str: str = cast(str, response.content)
-        answer_quality = binary_string_test(
-            text=quality_str, positive_value=AGENT_POSITIVE_VALUE_STR
-        )
-        log_result = f"Answer quality: {quality_str}"
-
-    except (LLMTimeoutError, TimeoutError):
-        agent_error = AgentErrorLog(
-            error_type=AgentLLMErrorType.TIMEOUT,
-            error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-            error_result=_llm_node_error_strings.timeout,
-        )
-        answer_quality = True
-        log_result = agent_error.error_result
-        logger.error("LLM Timeout Error - check sub answer")
-
-    except LLMRateLimitError:
-        agent_error = AgentErrorLog(
-            error_type=AgentLLMErrorType.RATE_LIMIT,
-            error_message=AGENT_LLM_RATELIMIT_MESSAGE,
-            error_result=_llm_node_error_strings.rate_limit,
-        )
-
-        answer_quality = True
-        log_result = agent_error.error_result
-        logger.error("LLM Rate Limit Error - check sub answer")
+    quality_str: str = merge_message_runs(response, chunk_separator="")[0].content
+    answer_quality = "yes" in quality_str.lower()
 
     return SubQuestionAnswerCheckUpdate(
         answer_quality=answer_quality,
@@ -130,7 +69,7 @@ def check_sub_answer(
                 graph_component="initial  - generate individual sub answer",
                 node_name="check sub answer",
                 node_start_time=node_start_time,
-                result=log_result,
+                result=f"Answer quality: {quality_str}",
             )
         ],
     )

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

@@ -1,4 +1,5 @@
 from datetime import datetime
+from typing import Any
 from typing import cast
 
 from langchain_core.messages import merge_message_runs
@@ -15,23 +16,6 @@ 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,
@@ -46,26 +30,12 @@ from onyx.chat.models import StreamStopInfo
 from onyx.chat.models import StreamStopReason
 from onyx.chat.models import StreamType
 from onyx.configs.agent_configs import AGENT_MAX_ANSWER_CONTEXT_DOCS
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_SUBANSWER_GENERATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_SUBANSWER_GENERATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_SUBANSWER_GENERATION
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import NO_RECOVERED_DOCS
 from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
 
 logger = setup_logger()
 
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="LLM Timeout Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-    rate_limit="LLM Rate Limit Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-    general_error="General LLM Error. A sub-answer could not be constructed and the sub-question will be ignored.",
-)
 
-
-@log_function_time(print_only=True)
 def generate_sub_answer(
     state: AnswerQuestionState,
     config: RunnableConfig,
@@ -81,17 +51,12 @@ def generate_sub_answer(
     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(
@@ -112,76 +77,43 @@ def generate_sub_answer(
             config=fast_llm.config,
         )
 
+        response: list[str | list[str | dict[str, Any]]] = []
         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,
-                max_tokens=AGENT_MAX_TOKENS_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,
+        for message in fast_llm.stream(
+            prompt=msg,
+        ):
+            # 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)}"
                 )
-                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,
+            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,
             )
-
-        except (LLMTimeoutError, TimeoutError):
-            agent_error = AgentErrorLog(
-                error_type=AgentLLMErrorType.TIMEOUT,
-                error_message=AGENT_LLM_TIMEOUT_MESSAGE,
-                error_result=_llm_node_error_strings.timeout,
+            end_stream_token = datetime.now()
+            dispatch_timings.append(
+                (end_stream_token - start_stream_token).microseconds
             )
-            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")
+            response.append(content)
 
-        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"
-            )
+        answer_str = merge_message_runs(response, chunk_separator="")[0].content
+        logger.debug(
+            f"Average dispatch time: {sum(dispatch_timings) / len(dispatch_timings)}"
+        )
 
-        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
+    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)
+    ]
 
     stop_event = StreamStopInfo(
         stop_reason=StreamStopReason.FINISHED,
@@ -199,7 +131,7 @@ def generate_sub_answer(
                 graph_component="initial - generate individual sub answer",
                 node_name="generate sub answer",
                 node_start_time=node_start_time,
-                result=log_results or "",
+                result="",
             )
         ],
     )

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

@@ -42,8 +42,10 @@ class SubQuestionRetrievalIngestionUpdate(LoggerUpdate, BaseModel):
 
 
 class SubQuestionAnsweringInput(SubgraphCoreState):
-    question: str
-    question_id: str
+    question: str = ""
+    question_id: str = (
+        ""  # 0_0 is original question, everything else is <level>_<question_num>.
+    )
     # 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.
 

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

@@ -1,4 +1,5 @@
 from datetime import datetime
+from typing import Any
 from typing import cast
 
 from langchain_core.messages import HumanMessage
@@ -25,32 +26,14 @@ from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
 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,
+    dedup_inference_sections,
 )
-from onyx.agents.agent_search.shared_graph_utils.utils import _should_restrict_tokens
 from onyx.agents.agent_search.shared_graph_utils.utils import (
     dispatch_main_answer_stop_info,
 )
 from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_deduplicated_structured_subquestion_documents,
-)
 from onyx.agents.agent_search.shared_graph_utils.utils import (
     get_langgraph_node_log_string,
 )
@@ -59,21 +42,12 @@ from onyx.agents.agent_search.shared_graph_utils.utils import remove_document_ci
 from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
 from onyx.chat.models import AgentAnswerPiece
 from onyx.chat.models import ExtendedToolResponse
-from onyx.chat.models import StreamingError
-from onyx.configs.agent_configs import AGENT_ANSWER_GENERATION_BY_FAST_LLM
 from onyx.configs.agent_configs import AGENT_MAX_ANSWER_CONTEXT_DOCS
-from onyx.configs.agent_configs import AGENT_MAX_STREAMED_DOCS_FOR_INITIAL_ANSWER
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_ANSWER_GENERATION
 from onyx.configs.agent_configs import AGENT_MIN_ORIG_QUESTION_DOCS
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_INITIAL_ANSWER_GENERATION,
+from onyx.context.search.models import InferenceSection
+from onyx.prompts.agent_search import (
+    INITIAL_ANSWER_PROMPT_W_SUB_QUESTIONS,
 )
-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,
 )
@@ -82,17 +56,8 @@ from onyx.prompts.agent_search import (
 )
 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,
@@ -108,19 +73,15 @@ def generate_initial_answer(
     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
-    )
-
+    sub_questions_cited_documents = state.cited_documents
     orig_question_retrieval_documents = state.orig_question_retrieved_documents
 
-    consolidated_context_docs = structured_subquestion_docs.cited_documents
+    consolidated_context_docs: list[InferenceSection] = sub_questions_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 original_doc_number not in sub_questions_cited_documents:
             if (
                 counter <= AGENT_MIN_ORIG_QUESTION_DOCS
                 or len(consolidated_context_docs) < AGENT_MAX_ANSWER_CONTEXT_DOCS
@@ -129,18 +90,15 @@ def generate_initial_answer(
                 counter += 1
 
     # sort docs by their scores - though the scores refer to different questions
-    relevant_docs = dedup_inference_section_list(consolidated_context_docs)
+    relevant_docs = dedup_inference_sections(
+        consolidated_context_docs, 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,
+    streamed_documents = (
+        relevant_docs
+        if len(relevant_docs) > 0
+        else state.orig_question_retrieved_documents[:15]
     )
 
     # Use the query info from the base document retrieval
@@ -150,14 +108,11 @@ def generate_initial_answer(
         graph_config.tooling.search_tool
     ), "search_tool must be provided for agentic search"
 
-    relevance_list = relevance_from_docs(
-        answer_generation_documents.streaming_documents
-    )
+    relevance_list = relevance_from_docs(relevant_docs)
     for tool_response in yield_search_responses(
         query=question,
-        get_retrieved_sections=lambda: answer_generation_documents.context_documents,
-        get_reranked_sections=lambda: answer_generation_documents.streaming_documents,
-        get_final_context_sections=lambda: answer_generation_documents.context_documents,
+        reranked_sections=streamed_documents,
+        final_context_sections=streamed_documents,
         search_query_info=query_info,
         get_section_relevance=lambda: relevance_list,
         search_tool=graph_config.tooling.search_tool,
@@ -173,7 +128,7 @@ def generate_initial_answer(
             writer,
         )
 
-    if len(answer_generation_documents.context_documents) == 0:
+    if len(relevant_docs) == 0:
         write_custom_event(
             "initial_agent_answer",
             AgentAnswerPiece(
@@ -237,13 +192,9 @@ def generate_initial_answer(
 
         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
-        )
+        model = graph_config.tooling.fast_llm
 
-        doc_context = format_docs(answer_generation_documents.context_documents)
+        doc_context = format_docs(relevant_docs)
         doc_context = trim_prompt_piece(
             config=model.config,
             prompt_piece=doc_context,
@@ -271,95 +222,32 @@ def generate_initial_answer(
             )
         ]
 
-        streamed_tokens: list[str] = [""]
+        streamed_tokens: list[str | list[str | dict[str, Any]]] = [""]
         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,
-                max_tokens=AGENT_MAX_TOKENS_ANSWER_GENERATION
-                if _should_restrict_tokens(model.config)
-                else None,
-            ):
-                # 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,
+        for message in model.stream(msg):
+            # 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)}"
                 )
-                end_stream_token = datetime.now()
-                dispatch_timings.append(
-                    (end_stream_token - start_stream_token).microseconds
-                )
-                response.append(content)
-            return response
+            start_stream_token = datetime.now()
 
-        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,
+                AgentAnswerPiece(
+                    answer_piece=content,
+                    level=0,
+                    level_question_num=0,
+                    answer_type="agent_level_answer",
                 ),
                 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",
-                    )
-                ],
+            end_stream_token = datetime.now()
+            dispatch_timings.append(
+                (end_stream_token - start_stream_token).microseconds
             )
+            streamed_tokens.append(content)
 
         logger.debug(
             f"Average dispatch time for initial answer: {sum(dispatch_timings) / len(dispatch_timings)}"

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

@@ -10,10 +10,8 @@ from onyx.agents.agent_search.deep_search.main.states import (
 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:
@@ -27,7 +25,7 @@ def validate_initial_answer(
         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
+    verdict = True
 
     return InitialAnswerQualityUpdate(
         initial_answer_quality_eval=verdict,

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

@@ -23,8 +23,6 @@ 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,
@@ -34,36 +32,18 @@ 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_MAX_TOKENS_SUBQUESTION_GENERATION
 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,
+    INITIAL_DECOMPOSITION_PROMPT_QUESTIONS_AFTER_SEARCH,
 )
 from onyx.prompts.agent_search import (
-    INITIAL_QUESTION_DECOMPOSITION_PROMPT_ASSUMING_REFINEMENT,
+    INITIAL_QUESTION_DECOMPOSITION_PROMPT,
 )
 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,
@@ -105,15 +85,15 @@ def decompose_orig_question(
             ]
         )
 
-        decomposition_prompt = INITIAL_DECOMPOSITION_PROMPT_QUESTIONS_AFTER_SEARCH_ASSUMING_REFINEMENT.format(
-            question=question, sample_doc_str=sample_doc_str, history=history
+        decomposition_prompt = (
+            INITIAL_DECOMPOSITION_PROMPT_QUESTIONS_AFTER_SEARCH.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
-            )
+        decomposition_prompt = INITIAL_QUESTION_DECOMPOSITION_PROMPT.format(
+            question=question, history=history
         )
 
     # Start decomposition
@@ -132,45 +112,32 @@ def decompose_orig_question(
     )
 
     # dispatches custom events for subquestion tokens, adding in subquestion ids.
+    streamed_tokens = dispatch_separated(
+        model.stream(msg),
+        dispatch_subquestion(0, writer),
+        sep_callback=dispatch_subquestion_sep(0, writer),
+    )
 
-    streamed_tokens: list[BaseMessage_Content] = []
+    stop_event = StreamStopInfo(
+        stop_reason=StreamStopReason.FINISHED,
+        stream_type=StreamType.SUB_QUESTIONS,
+        level=0,
+    )
+    write_custom_event("stream_finished", stop_event, writer)
 
-    try:
-        streamed_tokens = run_with_timeout(
-            AGENT_TIMEOUT_LLM_SUBQUESTION_GENERATION,
-            dispatch_separated,
-            model.stream(
-                msg,
-                timeout_override=AGENT_TIMEOUT_CONNECT_LLM_SUBQUESTION_GENERATION,
-                max_tokens=AGENT_MAX_TOKENS_SUBQUESTION_GENERATION,
-            ),
-            dispatch_subquestion(0, writer),
-            sep_callback=dispatch_subquestion_sep(0, writer),
-        )
+    deomposition_response = merge_content(*streamed_tokens)
 
-        decomposition_response = merge_content(*streamed_tokens)
+    # this call should only return strings. Commenting out for efficiency
+    # assert [type(tok) == str for tok in streamed_tokens]
 
-        list_of_subqs = cast(str, decomposition_response).split("\n")
+    # use no-op cast() instead of str() which runs code
+    # list_of_subquestions = clean_and_parse_list_string(cast(str, response))
+    list_of_subqs = cast(str, deomposition_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
+    decomp_list: list[str] = [sq.strip() for sq in list_of_subqs if sq.strip() != ""]
 
     return InitialQuestionDecompositionUpdate(
-        initial_sub_questions=initial_sub_questions,
+        initial_sub_questions=decomp_list,
         agent_start_time=agent_start_time,
         agent_refined_start_time=None,
         agent_refined_end_time=None,
@@ -184,7 +151,7 @@ def decompose_orig_question(
                 graph_component="initial - generate sub answers",
                 node_name="decompose original question",
                 node_start_time=node_start_time,
-                result=log_result,
+                result=f"decomposed original question into {len(decomp_list)} subquestions",
             )
         ],
     )

backend/onyx/agents/agent_search/deep_search/main/edges.py

@@ -25,7 +25,7 @@ logger = setup_logger()
 
 def route_initial_tool_choice(
     state: MainState, config: RunnableConfig
-) -> Literal["call_tool", "start_agent_search", "logging_node"]:
+) -> Literal["tool_call", "start_agent_search", "logging_node"]:
     """
     LangGraph edge to route to agent search.
     """
@@ -38,7 +38,7 @@ def route_initial_tool_choice(
         ):
             return "start_agent_search"
         else:
-            return "call_tool"
+            return "tool_call"
     else:
         return "logging_node"
 

backend/onyx/agents/agent_search/deep_search/main/graph_builder.py

@@ -26,8 +26,8 @@ from onyx.agents.agent_search.deep_search.main.nodes.decide_refinement_need impo
 from onyx.agents.agent_search.deep_search.main.nodes.extract_entities_terms import (
     extract_entities_terms,
 )
-from onyx.agents.agent_search.deep_search.main.nodes.generate_validate_refined_answer import (
-    generate_validate_refined_answer,
+from onyx.agents.agent_search.deep_search.main.nodes.generate_refined_answer import (
+    generate_refined_answer,
 )
 from onyx.agents.agent_search.deep_search.main.nodes.ingest_refined_sub_answers import (
     ingest_refined_sub_answers,
@@ -43,14 +43,14 @@ from onyx.agents.agent_search.deep_search.main.states import MainState
 from onyx.agents.agent_search.deep_search.refinement.consolidate_sub_answers.graph_builder import (
     answer_refined_query_graph_builder,
 )
-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.basic_use_tool_response import (
+    basic_use_tool_response,
+)
+from onyx.agents.agent_search.orchestration.nodes.llm_tool_choice import llm_tool_choice
 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.agents.agent_search.orchestration.nodes.tool_call import tool_call
 from onyx.agents.agent_search.shared_graph_utils.utils import get_test_config
 from onyx.utils.logger import setup_logger
 
@@ -77,13 +77,13 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
     # Choose the initial tool
     graph.add_node(
         node="initial_tool_choice",
-        action=choose_tool,
+        action=llm_tool_choice,
     )
 
     # Call the tool, if required
     graph.add_node(
-        node="call_tool",
-        action=call_tool,
+        node="tool_call",
+        action=tool_call,
     )
 
     # Use the tool response
@@ -126,8 +126,8 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
 
     # Node to generate the refined answer
     graph.add_node(
-        node="generate_validate_refined_answer",
-        action=generate_validate_refined_answer,
+        node="generate_refined_answer",
+        action=generate_refined_answer,
     )
 
     # Early node to extract the entities and terms from the initial answer,
@@ -168,11 +168,11 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
     graph.add_conditional_edges(
         "initial_tool_choice",
         route_initial_tool_choice,
-        ["call_tool", "start_agent_search", "logging_node"],
+        ["tool_call", "start_agent_search", "logging_node"],
     )
 
     graph.add_edge(
-        start_key="call_tool",
+        start_key="tool_call",
         end_key="basic_use_tool_response",
     )
     graph.add_edge(
@@ -215,11 +215,11 @@ def main_graph_builder(test_mode: bool = False) -> StateGraph:
 
     graph.add_edge(
         start_key="ingest_refined_sub_answers",
-        end_key="generate_validate_refined_answer",
+        end_key="generate_refined_answer",
     )
 
     graph.add_edge(
-        start_key="generate_validate_refined_answer",
+        start_key="generate_refined_answer",
         end_key="compare_answers",
     )
     graph.add_edge(
@@ -252,7 +252,9 @@ if __name__ == "__main__":
             db_session, primary_llm, fast_llm, search_request
         )
 
-        inputs = MainInput(log_messages=[])
+        inputs = MainInput(
+            base_question=graph_config.inputs.search_request.query, log_messages=[]
+        )
 
         for thing in compiled_graph.stream(
             input=inputs,

backend/onyx/agents/agent_search/deep_search/main/nodes/compare_answers.py

@@ -1,7 +1,6 @@
 from datetime import datetime
 from typing import cast
 
-from langchain_core.messages import BaseMessage
 from langchain_core.messages import HumanMessage
 from langchain_core.runnables import RunnableConfig
 from langgraph.types import StreamWriter
@@ -11,54 +10,16 @@ from onyx.agents.agent_search.deep_search.main.states import (
 )
 from onyx.agents.agent_search.deep_search.main.states import MainState
 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 write_custom_event
 from onyx.chat.models import RefinedAnswerImprovement
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_VALIDATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_COMPARE_ANSWERS
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_COMPARE_ANSWERS
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import (
     INITIAL_REFINED_ANSWER_COMPARISON_PROMPT,
 )
-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="The LLM timed out, and the answers could not be compared.",
-    rate_limit="The LLM encountered a rate limit, and the answers could not be compared.",
-    general_error="The LLM encountered an error, and the answers could not be compared.",
-)
-
-_ANSWER_QUALITY_NOT_SUFFICIENT_MESSAGE = (
-    "Answer quality is not sufficient, so stay with the initial answer."
-)
 
 
-@log_function_time(print_only=True)
 def compare_answers(
     state: MainState, config: RunnableConfig, writer: StreamWriter = lambda _: None
 ) -> InitialRefinedAnswerComparisonUpdate:
@@ -73,79 +34,21 @@ def compare_answers(
     initial_answer = state.initial_answer
     refined_answer = state.refined_answer
 
-    # if answer quality is not sufficient, then stay with the initial answer
-    if not state.refined_answer_quality:
-        write_custom_event(
-            "refined_answer_improvement",
-            RefinedAnswerImprovement(
-                refined_answer_improvement=False,
-            ),
-            writer,
-        )
-
-        return InitialRefinedAnswerComparisonUpdate(
-            refined_answer_improvement_eval=False,
-            log_messages=[
-                get_langgraph_node_log_string(
-                    graph_component="main",
-                    node_name="compare answers",
-                    node_start_time=node_start_time,
-                    result=_ANSWER_QUALITY_NOT_SUFFICIENT_MESSAGE,
-                )
-            ],
-        )
-
     compare_answers_prompt = INITIAL_REFINED_ANSWER_COMPARISON_PROMPT.format(
         question=question, initial_answer=initial_answer, refined_answer=refined_answer
     )
 
     msg = [HumanMessage(content=compare_answers_prompt)]
 
-    agent_error: AgentErrorLog | None = None
     # Get the rewritten queries in a defined format
     model = graph_config.tooling.fast_llm
-    resp: BaseMessage | None = None
-    refined_answer_improvement: bool | None = None
+
     # no need to stream this
-    try:
-        resp = run_with_timeout(
-            AGENT_TIMEOUT_LLM_COMPARE_ANSWERS,
-            model.invoke,
-            prompt=msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_COMPARE_ANSWERS,
-            max_tokens=AGENT_MAX_TOKENS_VALIDATION,
-        )
+    resp = model.invoke(msg)
 
-    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 - compare answers")
-        # continue as True in this support step
-    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 - compare answers")
-        # continue as True in this support step
-
-    if agent_error or resp is None:
-        refined_answer_improvement = True
-        if agent_error:
-            log_result = agent_error.error_result
-        else:
-            log_result = "An answer could not be generated."
-
-    else:
-        refined_answer_improvement = binary_string_test(
-            text=cast(str, resp.content),
-            positive_value=AGENT_POSITIVE_VALUE_STR,
-        )
-        log_result = f"Answer comparison: {refined_answer_improvement}"
+    refined_answer_improvement = (
+        isinstance(resp.content, str) and "yes" in resp.content.lower()
+    )
 
     write_custom_event(
         "refined_answer_improvement",
@@ -162,7 +65,7 @@ def compare_answers(
                 graph_component="main",
                 node_name="compare answers",
                 node_start_time=node_start_time,
-                result=log_result,
+                result=f"Answer comparison: {refined_answer_improvement}",
             )
         ],
     )

backend/onyx/agents/agent_search/deep_search/main/nodes/create_refined_sub_questions.py

@@ -21,18 +21,6 @@ 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.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 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 (
     format_entity_term_extraction,
@@ -42,36 +30,12 @@ from onyx.agents.agent_search.shared_graph_utils.utils import (
 )
 from onyx.agents.agent_search.shared_graph_utils.utils import make_question_id
 from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
-from onyx.chat.models import StreamingError
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_SUBQUESTION_GENERATION
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_REFINED_SUBQUESTION_GENERATION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_LLM_REFINED_SUBQUESTION_GENERATION,
-)
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import (
-    REFINEMENT_QUESTION_DECOMPOSITION_PROMPT_W_INITIAL_SUBQUESTION_ANSWERS,
+    REFINEMENT_QUESTION_DECOMPOSITION_PROMPT,
 )
 from onyx.tools.models import ToolCallKickoff
-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()
-
-_ANSWERED_SUBQUESTIONS_DIVIDER = "\n\n---\n\n"
-
-_llm_node_error_strings = LLMNodeErrorStrings(
-    timeout="The LLM timed out. The sub-questions could not be generated.",
-    rate_limit="The LLM encountered a rate limit. The sub-questions could not be generated.",
-    general_error="The LLM encountered an error. The sub-questions could not be generated.",
-)
 
 
-@log_function_time(print_only=True)
 def create_refined_sub_questions(
     state: MainState, config: RunnableConfig, writer: StreamWriter = lambda _: None
 ) -> RefinedQuestionDecompositionUpdate:
@@ -108,10 +72,8 @@ def create_refined_sub_questions(
 
     initial_question_answers = state.sub_question_results
 
-    addressed_subquestions_with_answers = [
-        f"Subquestion: {x.question}\nSubanswer:\n{x.answer}"
-        for x in initial_question_answers
-        if x.verified_high_quality and x.answer
+    addressed_question_list = [
+        x.question for x in initial_question_answers if x.verified_high_quality
     ]
 
     failed_question_list = [
@@ -120,14 +82,12 @@ def create_refined_sub_questions(
 
     msg = [
         HumanMessage(
-            content=REFINEMENT_QUESTION_DECOMPOSITION_PROMPT_W_INITIAL_SUBQUESTION_ANSWERS.format(
+            content=REFINEMENT_QUESTION_DECOMPOSITION_PROMPT.format(
                 question=question,
                 history=history,
                 entity_term_extraction_str=entity_term_extraction_str,
                 base_answer=base_answer,
-                answered_subquestions_with_answers=_ANSWERED_SUBQUESTIONS_DIVIDER.join(
-                    addressed_subquestions_with_answers
-                ),
+                answered_sub_questions="\n - ".join(addressed_question_list),
                 failed_sub_questions="\n - ".join(failed_question_list),
             ),
         )
@@ -136,68 +96,29 @@ def create_refined_sub_questions(
     # Grader
     model = graph_config.tooling.fast_llm
 
-    agent_error: AgentErrorLog | None = None
-    streamed_tokens: list[BaseMessage_Content] = []
-    try:
-        streamed_tokens = run_with_timeout(
-            AGENT_TIMEOUT_LLM_REFINED_SUBQUESTION_GENERATION,
-            dispatch_separated,
-            model.stream(
-                msg,
-                timeout_override=AGENT_TIMEOUT_CONNECT_LLM_REFINED_SUBQUESTION_GENERATION,
-                max_tokens=AGENT_MAX_TOKENS_SUBQUESTION_GENERATION,
-            ),
-            dispatch_subquestion(1, writer),
-            sep_callback=dispatch_subquestion_sep(1, writer),
-        )
-    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 - create refined sub questions")
-
-    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 - create refined sub questions")
-
-    if agent_error:
-        refined_sub_question_dict: dict[int, RefinementSubQuestion] = {}
-        log_result = agent_error.error_result
-        write_custom_event(
-            "refined_sub_question_creation_error",
-            StreamingError(
-                error="Your LLM was not able to create refined sub questions in time and timed out. Please try again.",
-            ),
-            writer,
-        )
+    streamed_tokens = dispatch_separated(
+        model.stream(msg),
+        dispatch_subquestion(1, writer),
+        sep_callback=dispatch_subquestion_sep(1, writer),
+    )
+    response = merge_content(*streamed_tokens)
 
+    if isinstance(response, str):
+        parsed_response = [q for q in response.split("\n") if q.strip() != ""]
     else:
-        response = merge_content(*streamed_tokens)
+        raise ValueError("LLM response is not a string")
 
-        if isinstance(response, str):
-            parsed_response = [q for q in response.split("\n") if q.strip() != ""]
-        else:
-            raise ValueError("LLM response is not a string")
+    refined_sub_question_dict = {}
+    for sub_question_num, sub_question in enumerate(parsed_response):
+        refined_sub_question = RefinementSubQuestion(
+            sub_question=sub_question,
+            sub_question_id=make_question_id(1, sub_question_num + 1),
+            verified=False,
+            answered=False,
+            answer="",
+        )
 
-        refined_sub_question_dict = {}
-        for sub_question_num, sub_question in enumerate(parsed_response):
-            refined_sub_question = RefinementSubQuestion(
-                sub_question=sub_question,
-                sub_question_id=make_question_id(1, sub_question_num + 1),
-                verified=False,
-                answered=False,
-                answer="",
-            )
-
-            refined_sub_question_dict[sub_question_num + 1] = refined_sub_question
-
-        log_result = f"Created {len(refined_sub_question_dict)} refined sub questions"
+        refined_sub_question_dict[sub_question_num + 1] = refined_sub_question
 
     return RefinedQuestionDecompositionUpdate(
         refined_sub_questions=refined_sub_question_dict,
@@ -207,7 +128,7 @@ def create_refined_sub_questions(
                 graph_component="main",
                 node_name="create refined sub questions",
                 node_start_time=node_start_time,
-                result=log_result,
+                result=f"Created {len(refined_sub_question_dict)} refined sub questions",
             )
         ],
     )

backend/onyx/agents/agent_search/deep_search/main/nodes/decide_refinement_need.py

@@ -11,10 +11,8 @@ from onyx.agents.agent_search.models import GraphConfig
 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 decide_refinement_need(
     state: MainState, config: RunnableConfig
 ) -> RequireRefinemenEvalUpdate:
@@ -28,19 +26,6 @@ def decide_refinement_need(
 
     decision = True  # TODO: just for current testing purposes
 
-    if state.answer_error:
-        return RequireRefinemenEvalUpdate(
-            require_refined_answer_eval=False,
-            log_messages=[
-                get_langgraph_node_log_string(
-                    graph_component="main",
-                    node_name="decide refinement need",
-                    node_start_time=node_start_time,
-                    result="Timeout Error",
-                )
-            ],
-        )
-
     log_messages = [
         get_langgraph_node_log_string(
             graph_component="main",
@@ -50,7 +35,13 @@ def decide_refinement_need(
         )
     ]
 
-    return RequireRefinemenEvalUpdate(
-        require_refined_answer_eval=graph_config.behavior.allow_refinement and decision,
-        log_messages=log_messages,
-    )
+    if graph_config.behavior.allow_refinement:
+        return RequireRefinemenEvalUpdate(
+            require_refined_answer_eval=decision,
+            log_messages=log_messages,
+        )
+    else:
+        return RequireRefinemenEvalUpdate(
+            require_refined_answer_eval=False,
+            log_messages=log_messages,
+        )

backend/onyx/agents/agent_search/deep_search/main/nodes/extract_entities_terms.py

@@ -21,23 +21,11 @@ from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
 from onyx.agents.agent_search.shared_graph_utils.utils import (
     get_langgraph_node_log_string,
 )
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_ENTITY_TERM_EXTRACTION
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_ENTITY_TERM_EXTRACTION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_LLM_ENTITY_TERM_EXTRACTION,
-)
 from onyx.configs.constants import NUM_EXPLORATORY_DOCS
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import ENTITY_TERM_EXTRACTION_PROMPT
 from onyx.prompts.agent_search import ENTITY_TERM_EXTRACTION_PROMPT_JSON_EXAMPLE
-from onyx.utils.threadpool_concurrency import run_with_timeout
-from onyx.utils.timing import log_function_time
 
 
-@log_function_time(print_only=True)
 def extract_entities_terms(
     state: MainState, config: RunnableConfig
 ) -> EntityTermExtractionUpdate:
@@ -91,43 +79,29 @@ def extract_entities_terms(
     ]
     fast_llm = graph_config.tooling.fast_llm
     # Grader
+    llm_response = fast_llm.invoke(
+        prompt=msg,
+    )
+
+    cleaned_response = (
+        str(llm_response.content).replace("```json\n", "").replace("\n```", "")
+    )
+    first_bracket = cleaned_response.find("{")
+    last_bracket = cleaned_response.rfind("}")
+    cleaned_response = cleaned_response[first_bracket : last_bracket + 1]
+
     try:
-        llm_response = run_with_timeout(
-            AGENT_TIMEOUT_LLM_ENTITY_TERM_EXTRACTION,
-            fast_llm.invoke,
-            prompt=msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_ENTITY_TERM_EXTRACTION,
-            max_tokens=AGENT_MAX_TOKENS_ENTITY_TERM_EXTRACTION,
+        entity_extraction_result = EntityExtractionResult.model_validate_json(
+            cleaned_response
         )
-
-        cleaned_response = (
-            str(llm_response.content).replace("```json\n", "").replace("\n```", "")
-        )
-        first_bracket = cleaned_response.find("{")
-        last_bracket = cleaned_response.rfind("}")
-        cleaned_response = cleaned_response[first_bracket : last_bracket + 1]
-
-        try:
-            entity_extraction_result = EntityExtractionResult.model_validate_json(
-                cleaned_response
-            )
-        except ValueError:
-            logger.error(
-                "Failed to parse LLM response as JSON in Entity-Term Extraction"
-            )
-            entity_extraction_result = EntityExtractionResult(
-                retrieved_entities_relationships=EntityRelationshipTermExtraction(),
-            )
-    except (LLMTimeoutError, TimeoutError):
-        logger.error("LLM Timeout Error - extract entities terms")
+    except ValueError:
+        logger.error("Failed to parse LLM response as JSON in Entity-Term Extraction")
         entity_extraction_result = EntityExtractionResult(
-            retrieved_entities_relationships=EntityRelationshipTermExtraction(),
-        )
-
-    except LLMRateLimitError:
-        logger.error("LLM Rate Limit Error - extract entities terms")
-        entity_extraction_result = EntityExtractionResult(
-            retrieved_entities_relationships=EntityRelationshipTermExtraction(),
+            retrieved_entities_relationships=EntityRelationshipTermExtraction(
+                entities=[],
+                relationships=[],
+                terms=[],
+            ),
         )
 
     return EntityTermExtractionUpdate(

backend/onyx/agents/agent_search/deep_search/main/nodes/generate_refined_answer.py

@@ -1,4 +1,5 @@
 from datetime import datetime
+from typing import Any
 from typing import cast
 
 from langchain_core.messages import HumanMessage
@@ -10,50 +11,27 @@ from onyx.agents.agent_search.deep_search.main.models import (
     AgentRefinedMetrics,
 )
 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 MainState
 from onyx.agents.agent_search.deep_search.main.states import (
     RefinedAnswerUpdate,
 )
 from onyx.agents.agent_search.models import GraphConfig
-from onyx.agents.agent_search.shared_graph_utils.agent_prompt_ops import (
-    binary_string_test_after_answer_separator,
-)
 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_ANSWER_SEPARATOR
-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.models import InferenceSection
 from onyx.agents.agent_search.shared_graph_utils.models import RefinedAgentStats
 from onyx.agents.agent_search.shared_graph_utils.operators import (
-    dedup_inference_section_list,
+    dedup_inference_sections,
 )
-from onyx.agents.agent_search.shared_graph_utils.utils import _should_restrict_tokens
 from onyx.agents.agent_search.shared_graph_utils.utils import (
     dispatch_main_answer_stop_info,
 )
 from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
-from onyx.agents.agent_search.shared_graph_utils.utils import (
-    get_deduplicated_structured_subquestion_documents,
-)
 from onyx.agents.agent_search.shared_graph_utils.utils import (
     get_langgraph_node_log_string,
 )
@@ -65,60 +43,26 @@ from onyx.agents.agent_search.shared_graph_utils.utils import (
 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_REFINED_ANSWER
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_ANSWER_GENERATION
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_VALIDATION
 from onyx.configs.agent_configs import AGENT_MIN_ORIG_QUESTION_DOCS
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_REFINED_ANSWER_GENERATION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_REFINED_ANSWER_VALIDATION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_LLM_REFINED_ANSWER_GENERATION,
-)
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_LLM_REFINED_ANSWER_VALIDATION,
-)
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import (
     REFINED_ANSWER_PROMPT_W_SUB_QUESTIONS,
 )
 from onyx.prompts.agent_search import (
     REFINED_ANSWER_PROMPT_WO_SUB_QUESTIONS,
 )
-from onyx.prompts.agent_search import (
-    REFINED_ANSWER_VALIDATION_PROMPT,
-)
 from onyx.prompts.agent_search import (
     SUB_QUESTION_ANSWER_TEMPLATE_REFINED,
 )
 from onyx.prompts.agent_search import UNKNOWN_ANSWER
 from onyx.tools.tool_implementations.search.search_tool import yield_search_responses
-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="The LLM timed out. The refined answer could not be generated.",
-    rate_limit="The LLM encountered a rate limit. The refined answer could not be generated.",
-    general_error="The LLM encountered an error. The refined answer could not be generated.",
-)
 
 
-@log_function_time(print_only=True)
-def generate_validate_refined_answer(
+def generate_refined_answer(
     state: MainState, config: RunnableConfig, writer: StreamWriter = lambda _: None
 ) -> RefinedAnswerUpdate:
     """
-    LangGraph node to generate the refined answer and validate it.
+    LangGraph node to generate the refined answer.
     """
 
     node_start_time = datetime.now()
@@ -132,24 +76,19 @@ def generate_validate_refined_answer(
     )
 
     verified_reranked_documents = state.verified_reranked_documents
-
-    # get all documents cited in sub-questions
-    structured_subquestion_docs = get_deduplicated_structured_subquestion_documents(
-        state.sub_question_results
-    )
-
+    sub_questions_cited_documents = state.cited_documents
     original_question_verified_documents = (
         state.orig_question_verified_reranked_documents
     )
     original_question_retrieved_documents = state.orig_question_retrieved_documents
 
-    consolidated_context_docs = structured_subquestion_docs.cited_documents
+    consolidated_context_docs: list[InferenceSection] = sub_questions_cited_documents
 
     counter = 0
     for original_doc_number, original_doc in enumerate(
         original_question_verified_documents
     ):
-        if original_doc_number not in structured_subquestion_docs.cited_documents:
+        if original_doc_number not in sub_questions_cited_documents:
             if (
                 counter <= AGENT_MIN_ORIG_QUESTION_DOCS
                 or len(consolidated_context_docs)
@@ -160,16 +99,14 @@ def generate_validate_refined_answer(
                 counter += 1
 
     # sort docs by their scores - though the scores refer to different questions
-    relevant_docs = dedup_inference_section_list(consolidated_context_docs)
+    relevant_docs = dedup_inference_sections(
+        consolidated_context_docs, consolidated_context_docs
+    )
 
-    # 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=original_question_retrieved_documents,
-        max_docs=AGENT_MAX_STREAMED_DOCS_FOR_REFINED_ANSWER,
+    streaming_docs = (
+        relevant_docs
+        if len(relevant_docs) > 0
+        else original_question_retrieved_documents[:15]
     )
 
     query_info = get_query_info(state.orig_question_sub_query_retrieval_results)
@@ -177,14 +114,11 @@ def generate_validate_refined_answer(
         graph_config.tooling.search_tool
     ), "search_tool must be provided for agentic search"
     # stream refined answer docs, or original question docs if no relevant docs are found
-    relevance_list = relevance_from_docs(
-        answer_generation_documents.streaming_documents
-    )
+    relevance_list = relevance_from_docs(relevant_docs)
     for tool_response in yield_search_responses(
         query=question,
-        get_retrieved_sections=lambda: answer_generation_documents.context_documents,
-        get_reranked_sections=lambda: answer_generation_documents.streaming_documents,
-        get_final_context_sections=lambda: answer_generation_documents.context_documents,
+        reranked_sections=streaming_docs,
+        final_context_sections=streaming_docs,
         search_query_info=query_info,
         get_section_relevance=lambda: relevance_list,
         search_tool=graph_config.tooling.search_tool,
@@ -264,13 +198,8 @@ def generate_validate_refined_answer(
         else REFINED_ANSWER_PROMPT_WO_SUB_QUESTIONS
     )
 
-    model = (
-        graph_config.tooling.fast_llm
-        if AGENT_ANSWER_GENERATION_BY_FAST_LLM
-        else graph_config.tooling.primary_llm
-    )
-
-    relevant_docs_str = format_docs(answer_generation_documents.context_documents)
+    model = graph_config.tooling.fast_llm
+    relevant_docs_str = format_docs(relevant_docs)
     relevant_docs_str = trim_prompt_piece(
         model.config,
         relevant_docs_str,
@@ -300,93 +229,30 @@ def generate_validate_refined_answer(
         )
     ]
 
-    streamed_tokens: list[str] = [""]
+    streamed_tokens: list[str | list[str | dict[str, Any]]] = [""]
     dispatch_timings: list[float] = []
-    agent_error: AgentErrorLog | None = None
-
-    def stream_refined_answer() -> list[str]:
-        for message in model.stream(
-            msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_REFINED_ANSWER_GENERATION,
-            max_tokens=AGENT_MAX_TOKENS_ANSWER_GENERATION
-            if _should_restrict_tokens(model.config)
-            else None,
-        ):
-            # 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(
-                "refined_agent_answer",
-                AgentAnswerPiece(
-                    answer_piece=content,
-                    level=1,
-                    level_question_num=0,
-                    answer_type="agent_level_answer",
-                ),
-                writer,
+    for message in model.stream(msg):
+        # 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)}"
             )
-            end_stream_token = datetime.now()
-            dispatch_timings.append(
-                (end_stream_token - start_stream_token).microseconds
-            )
-            streamed_tokens.append(content)
-        return streamed_tokens
 
-    try:
-        streamed_tokens = run_with_timeout(
-            AGENT_TIMEOUT_LLM_REFINED_ANSWER_GENERATION,
-            stream_refined_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 refined 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 refined answer")
-
-    if agent_error:
+        start_stream_token = datetime.now()
         write_custom_event(
-            "initial_agent_answer",
-            StreamingError(
-                error=AGENT_LLM_TIMEOUT_MESSAGE,
+            "refined_agent_answer",
+            AgentAnswerPiece(
+                answer_piece=content,
+                level=1,
+                level_question_num=0,
+                answer_type="agent_level_answer",
             ),
             writer,
         )
-
-        return RefinedAnswerUpdate(
-            refined_answer=None,
-            refined_answer_quality=False,  # TODO: replace this with the actual check value
-            refined_agent_stats=None,
-            agent_refined_end_time=None,
-            agent_refined_metrics=AgentRefinedMetrics(
-                refined_doc_boost_factor=0.0,
-                refined_question_boost_factor=0.0,
-                duration_s=None,
-            ),
-            log_messages=[
-                get_langgraph_node_log_string(
-                    graph_component="main",
-                    node_name="generate refined answer",
-                    node_start_time=node_start_time,
-                    result=agent_error.error_result or "An LLM error occurred",
-                )
-            ],
-        )
+        end_stream_token = datetime.now()
+        dispatch_timings.append((end_stream_token - start_stream_token).microseconds)
+        streamed_tokens.append(content)
 
     logger.debug(
         f"Average dispatch time for refined answer: {sum(dispatch_timings) / len(dispatch_timings)}"
@@ -395,48 +261,54 @@ def generate_validate_refined_answer(
     response = merge_content(*streamed_tokens)
     answer = cast(str, response)
 
-    # run a validation step for the refined answer only
-
-    msg = [
-        HumanMessage(
-            content=REFINED_ANSWER_VALIDATION_PROMPT.format(
-                question=question,
-                history=prompt_enrichment_components.history,
-                answered_sub_questions=sub_question_answer_str,
-                relevant_docs=relevant_docs_str,
-                proposed_answer=answer,
-                persona_specification=persona_contextualized_prompt,
-            )
-        )
-    ]
-
-    validation_model = graph_config.tooling.fast_llm
-    try:
-        validation_response = run_with_timeout(
-            AGENT_TIMEOUT_LLM_REFINED_ANSWER_VALIDATION,
-            validation_model.invoke,
-            prompt=msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_REFINED_ANSWER_VALIDATION,
-            max_tokens=AGENT_MAX_TOKENS_VALIDATION,
-        )
-        refined_answer_quality = binary_string_test_after_answer_separator(
-            text=cast(str, validation_response.content),
-            positive_value=AGENT_POSITIVE_VALUE_STR,
-            separator=AGENT_ANSWER_SEPARATOR,
-        )
-    except (LLMTimeoutError, TimeoutError):
-        refined_answer_quality = True
-        logger.error("LLM Timeout Error - validate refined answer")
-
-    except LLMRateLimitError:
-        refined_answer_quality = True
-        logger.error("LLM Rate Limit Error - validate refined answer")
-
     refined_agent_stats = RefinedAgentStats(
         revision_doc_efficiency=refined_doc_effectiveness,
         revision_question_efficiency=revision_question_efficiency,
     )
 
+    logger.debug(f"\n\n---INITIAL ANSWER ---\n\n Answer:\n Agent: {initial_answer}")
+    logger.debug("-" * 10)
+    logger.debug(f"\n\n---REVISED AGENT ANSWER ---\n\n Answer:\n Agent: {answer}")
+
+    logger.debug("-" * 100)
+
+    if state.initial_agent_stats:
+        initial_doc_boost_factor = state.initial_agent_stats.agent_effectiveness.get(
+            "utilized_chunk_ratio", "--"
+        )
+        initial_support_boost_factor = (
+            state.initial_agent_stats.agent_effectiveness.get("support_ratio", "--")
+        )
+        num_initial_verified_docs = state.initial_agent_stats.original_question.get(
+            "num_verified_documents", "--"
+        )
+        initial_verified_docs_avg_score = (
+            state.initial_agent_stats.original_question.get("verified_avg_score", "--")
+        )
+        initial_sub_questions_verified_docs = (
+            state.initial_agent_stats.sub_questions.get("num_verified_documents", "--")
+        )
+
+        logger.debug("INITIAL AGENT STATS")
+        logger.debug(f"Document Boost Factor: {initial_doc_boost_factor}")
+        logger.debug(f"Support Boost Factor: {initial_support_boost_factor}")
+        logger.debug(f"Originally Verified Docs: {num_initial_verified_docs}")
+        logger.debug(
+            f"Originally Verified Docs Avg Score: {initial_verified_docs_avg_score}"
+        )
+        logger.debug(
+            f"Sub-Questions Verified Docs: {initial_sub_questions_verified_docs}"
+        )
+    if refined_agent_stats:
+        logger.debug("-" * 10)
+        logger.debug("REFINED AGENT STATS")
+        logger.debug(
+            f"Revision Doc Factor: {refined_agent_stats.revision_doc_efficiency}"
+        )
+        logger.debug(
+            f"Revision Question Factor: {refined_agent_stats.revision_question_efficiency}"
+        )
+
     agent_refined_end_time = datetime.now()
     if state.agent_refined_start_time:
         agent_refined_duration = (
@@ -453,7 +325,7 @@ def generate_validate_refined_answer(
 
     return RefinedAnswerUpdate(
         refined_answer=answer,
-        refined_answer_quality=refined_answer_quality,
+        refined_answer_quality=True,  # TODO: replace this with the actual check value
         refined_agent_stats=refined_agent_stats,
         agent_refined_end_time=agent_refined_end_time,
         agent_refined_metrics=agent_refined_metrics,

backend/onyx/agents/agent_search/deep_search/main/operations.py

@@ -13,6 +13,7 @@ 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.context.search.models import IndexFilters
 from onyx.tools.models import SearchQueryInfo
 from onyx.utils.logger import setup_logger
 
@@ -143,6 +144,8 @@ def get_query_info(results: list[QueryRetrievalResult]) -> SearchQueryInfo:
         if result.query_info is not None:
             query_info = result.query_info
             break
-
-    assert query_info is not None, "must have query info"
-    return query_info
+    return query_info or SearchQueryInfo(
+        predicted_search=None,
+        final_filters=IndexFilters(access_control_list=None),
+        recency_bias_multiplier=1.0,
+    )

backend/onyx/agents/agent_search/deep_search/main/states.py

@@ -17,7 +17,6 @@ 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
 from onyx.agents.agent_search.shared_graph_utils.models import AgentChunkRetrievalStats
-from onyx.agents.agent_search.shared_graph_utils.models import AgentErrorLog
 from onyx.agents.agent_search.shared_graph_utils.models import (
     EntityRelationshipTermExtraction,
 )
@@ -77,7 +76,6 @@ class InitialAnswerUpdate(LoggerUpdate):
     """
 
     initial_answer: str | None = None
-    answer_error: AgentErrorLog | None = None
     initial_agent_stats: InitialAgentResultStats | None = None
     generated_sub_questions: list[str] = []
     agent_base_end_time: datetime | None = None
@@ -90,7 +88,6 @@ class RefinedAnswerUpdate(RefinedAgentEndStats, LoggerUpdate):
     """
 
     refined_answer: str | None = None
-    answer_error: AgentErrorLog | None = None
     refined_agent_stats: RefinedAgentStats | None = None
     refined_answer_quality: bool = False
 

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/nodes/expand_queries.py

@@ -16,47 +16,16 @@ from onyx.agents.agent_search.deep_search.shared.expanded_retrieval.states impor
     QueryExpansionUpdate,
 )
 from onyx.agents.agent_search.models import GraphConfig
-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 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 parse_question_id
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_SUBQUERY_GENERATION
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_QUERY_REWRITING_GENERATION,
-)
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_QUERY_REWRITING_GENERATION
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import (
     QUERY_REWRITING_PROMPT,
 )
-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="Query rewriting failed due to LLM timeout - the original question will be used.",
-    rate_limit="Query rewriting failed due to LLM rate limit - the original question will be used.",
-    general_error="Query rewriting failed due to LLM error - the original question will be used.",
-)
 
 
-@log_function_time(print_only=True)
 def expand_queries(
     state: ExpandedRetrievalInput,
     config: RunnableConfig,
@@ -72,7 +41,7 @@ def expand_queries(
     node_start_time = datetime.now()
     question = state.question
 
-    model = graph_config.tooling.fast_llm
+    llm = graph_config.tooling.fast_llm
     sub_question_id = state.sub_question_id
     if sub_question_id is None:
         level, question_num = 0, 0
@@ -85,46 +54,13 @@ def expand_queries(
         )
     ]
 
-    agent_error: AgentErrorLog | None = None
-    llm_response_list: list[BaseMessage_Content] = []
-    llm_response = ""
-    rewritten_queries = []
+    llm_response_list = dispatch_separated(
+        llm.stream(prompt=msg), dispatch_subquery(level, question_num, writer)
+    )
 
-    try:
-        llm_response_list = run_with_timeout(
-            AGENT_TIMEOUT_LLM_QUERY_REWRITING_GENERATION,
-            dispatch_separated,
-            model.stream(
-                prompt=msg,
-                timeout_override=AGENT_TIMEOUT_CONNECT_LLM_QUERY_REWRITING_GENERATION,
-                max_tokens=AGENT_MAX_TOKENS_SUBQUERY_GENERATION,
-            ),
-            dispatch_subquery(level, question_num, writer),
-        )
-        llm_response = merge_message_runs(llm_response_list, chunk_separator="")[
-            0
-        ].content
-        rewritten_queries = llm_response.split("\n")
-        log_result = f"Number of expanded queries: {len(rewritten_queries)}"
+    llm_response = merge_message_runs(llm_response_list, chunk_separator="")[0].content
 
-    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 - expand queries")
-        log_result = agent_error.error_result
-
-    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 - expand queries")
-        log_result = agent_error.error_result
-    # use subquestion as query if query generation fails
+    rewritten_queries = llm_response.split("\n")
 
     return QueryExpansionUpdate(
         expanded_queries=rewritten_queries,
@@ -133,7 +69,7 @@ def expand_queries(
                 graph_component="shared - expanded retrieval",
                 node_name="expand queries",
                 node_start_time=node_start_time,
-                result=log_result,
+                result=f"Number of expanded queries: {len(rewritten_queries)}",
             )
         ],
     )

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/nodes/format_results.py

@@ -56,9 +56,8 @@ def format_results(
         relevance_list = relevance_from_docs(reranked_documents)
         for tool_response in yield_search_responses(
             query=state.question,
-            get_retrieved_sections=lambda: reranked_documents,
-            get_reranked_sections=lambda: state.retrieved_documents,
-            get_final_context_sections=lambda: reranked_documents,
+            reranked_sections=state.retrieved_documents,
+            final_context_sections=reranked_documents,
             search_query_info=query_info,
             get_section_relevance=lambda: relevance_list,
             search_tool=graph_config.tooling.search_tool,

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/nodes/rerank_documents.py

@@ -21,15 +21,12 @@ from onyx.agents.agent_search.shared_graph_utils.utils import (
 from onyx.configs.agent_configs import AGENT_RERANKING_MAX_QUERY_RETRIEVAL_RESULTS
 from onyx.configs.agent_configs import AGENT_RERANKING_STATS
 from onyx.context.search.models import InferenceSection
-from onyx.context.search.models import RerankingDetails
+from onyx.context.search.models import SearchRequest
+from onyx.context.search.pipeline import retrieval_preprocessing
 from onyx.context.search.postprocessing.postprocessing import rerank_sections
-from onyx.context.search.postprocessing.postprocessing import should_rerank
 from onyx.db.engine import get_session_context_manager
-from onyx.db.search_settings import get_current_search_settings
-from onyx.utils.timing import log_function_time
 
 
-@log_function_time(print_only=True)
 def rerank_documents(
     state: ExpandedRetrievalState, config: RunnableConfig
 ) -> DocRerankingUpdate:
@@ -42,8 +39,6 @@ def rerank_documents(
 
     # Rerank post retrieval and verification. First, create a search query
     # then create the list of reranked sections
-    # If no question defined/question is None in the state, use the original
-    # question from the search request as query
 
     graph_config = cast(GraphConfig, config["metadata"]["config"])
     question = (
@@ -52,42 +47,44 @@ def rerank_documents(
     assert (
         graph_config.tooling.search_tool
     ), "search_tool must be provided for agentic search"
+    with get_session_context_manager() as db_session:
+        # we ignore some of the user specified fields since this search is
+        # internal to agentic search, but we still want to pass through
+        # persona (for stuff like document sets) and rerank settings
+        # (to not make an unnecessary db call).
+        search_request = SearchRequest(
+            query=question,
+            persona=graph_config.inputs.search_request.persona,
+            rerank_settings=graph_config.inputs.search_request.rerank_settings,
+        )
+        _search_query = retrieval_preprocessing(
+            search_request=search_request,
+            user=graph_config.tooling.search_tool.user,  # bit of a hack
+            llm=graph_config.tooling.fast_llm,
+            db_session=db_session,
+        )
 
-    # Note that these are passed in values from the API and are overrides which are typically None
-    rerank_settings = graph_config.inputs.search_request.rerank_settings
-    allow_agent_reranking = graph_config.behavior.allow_agent_reranking
+    # skip section filtering
 
-    if rerank_settings is None:
-        with get_session_context_manager() as db_session:
-            search_settings = get_current_search_settings(db_session)
-            if not search_settings.disable_rerank_for_streaming:
-                rerank_settings = RerankingDetails.from_db_model(search_settings)
-
-    # Initial default: no reranking. Will be overwritten below if reranking is warranted
-    reranked_documents = verified_documents
-
-    if should_rerank(rerank_settings) and len(verified_documents) > 0:
+    if (
+        _search_query.rerank_settings
+        and _search_query.rerank_settings.rerank_model_name
+        and _search_query.rerank_settings.num_rerank > 0
+        and len(verified_documents) > 0
+    ):
         if len(verified_documents) > 1:
-            if not allow_agent_reranking:
-                logger.info("Use of local rerank model without GPU, skipping reranking")
-            # No reranking, stay with verified_documents as default
-
-            else:
-                # Reranking is warranted, use the rerank_sections functon
-                reranked_documents = rerank_sections(
-                    query_str=question,
-                    # if runnable, then rerank_settings is not None
-                    rerank_settings=cast(RerankingDetails, rerank_settings),
-                    sections_to_rerank=verified_documents,
-                )
-        else:
-            logger.warning(
-                f"{len(verified_documents)} verified document(s) found, skipping reranking"
+            reranked_documents = rerank_sections(
+                _search_query,
+                verified_documents,
             )
-            # No reranking, stay with verified_documents as default
+        else:
+            num = "No" if len(verified_documents) == 0 else "One"
+            logger.warning(f"{num} verified document(s) found, skipping reranking")
+            reranked_documents = verified_documents
     else:
         logger.warning("No reranking settings found, using unranked documents")
-        # No reranking, stay with verified_documents as default
+        reranked_documents = verified_documents
+
     if AGENT_RERANKING_STATS:
         fit_scores = get_fit_scores(verified_documents, reranked_documents)
     else:

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/nodes/retrieve_documents.py

@@ -23,15 +23,12 @@ from onyx.configs.agent_configs import AGENT_RETRIEVAL_STATS
 from onyx.context.search.models import InferenceSection
 from onyx.db.engine import get_session_context_manager
 from onyx.tools.models import SearchQueryInfo
-from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.tool_implementations.search.search_tool import (
     SEARCH_RESPONSE_SUMMARY_ID,
 )
 from onyx.tools.tool_implementations.search.search_tool import SearchResponseSummary
-from onyx.utils.timing import log_function_time
 
 
-@log_function_time(print_only=True)
 def retrieve_documents(
     state: RetrievalInput, config: RunnableConfig
 ) -> DocRetrievalUpdate:
@@ -70,12 +67,9 @@ def retrieve_documents(
     with get_session_context_manager() as db_session:
         for tool_response in search_tool.run(
             query=query_to_retrieve,
-            override_kwargs=SearchToolOverrideKwargs(
-                force_no_rerank=True,
-                alternate_db_session=db_session,
-                retrieved_sections_callback=callback_container.append,
-                skip_query_analysis=not state.base_search,
-            ),
+            force_no_rerank=True,
+            alternate_db_session=db_session,
+            retrieved_sections_callback=callback_container.append,
         ):
             # get retrieved docs to send to the rest of the graph
             if tool_response.id == SEARCH_RESPONSE_SUMMARY_ID:
@@ -91,7 +85,7 @@ def retrieve_documents(
     retrieved_docs = retrieved_docs[:AGENT_MAX_QUERY_RETRIEVAL_RESULTS]
 
     if AGENT_RETRIEVAL_STATS:
-        pre_rerank_docs = callback_container[0] if callback_container else []
+        pre_rerank_docs = callback_container[0]
         fit_scores = get_fit_scores(
             pre_rerank_docs,
             retrieved_docs,

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/nodes/verify_documents.py

@@ -1,7 +1,5 @@
-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
 
@@ -12,41 +10,14 @@ from onyx.agents.agent_search.deep_search.shared.expanded_retrieval.states impor
     DocVerificationUpdate,
 )
 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.agent_prompt_ops import (
     trim_prompt_piece,
 )
-from onyx.agents.agent_search.shared_graph_utils.constants import (
-    AGENT_POSITIVE_VALUE_STR,
-)
-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.configs.agent_configs import AGENT_MAX_TOKENS_VALIDATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_CONNECT_LLM_DOCUMENT_VERIFICATION
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_DOCUMENT_VERIFICATION
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.prompts.agent_search import (
     DOCUMENT_VERIFICATION_PROMPT,
 )
-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="The LLM timed out. The document could not be verified. The document will be treated as 'relevant'",
-    rate_limit="The LLM encountered a rate limit. The document could not be verified. The document will be treated as 'relevant'",
-    general_error="The LLM encountered an error. The document could not be verified. The document will be treated as 'relevant'",
-)
 
 
-@log_function_time(print_only=True)
 def verify_documents(
     state: DocVerificationInput, config: RunnableConfig
 ) -> DocVerificationUpdate:
@@ -55,14 +26,12 @@ def verify_documents(
 
     Args:
         state (DocVerificationInput): The current state
-        config (RunnableConfig): Configuration containing AgentSearchConfig
+        config (RunnableConfig): Configuration containing ProSearchConfig
 
     Updates:
         verified_documents: list[InferenceSection]
     """
 
-    node_start_time = datetime.now()
-
     question = state.question
     retrieved_document_to_verify = state.retrieved_document_to_verify
     document_content = retrieved_document_to_verify.combined_content
@@ -82,44 +51,12 @@ def verify_documents(
         )
     ]
 
-    response: BaseMessage | None = None
+    response = fast_llm.invoke(msg)
 
-    verified_documents = [
-        retrieved_document_to_verify
-    ]  # default is to treat document as relevant
-
-    try:
-        response = run_with_timeout(
-            AGENT_TIMEOUT_LLM_DOCUMENT_VERIFICATION,
-            fast_llm.invoke,
-            prompt=msg,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_DOCUMENT_VERIFICATION,
-            max_tokens=AGENT_MAX_TOKENS_VALIDATION,
-        )
-
-        assert isinstance(response.content, str)
-        if not binary_string_test(
-            text=response.content, positive_value=AGENT_POSITIVE_VALUE_STR
-        ):
-            verified_documents = []
-
-    except (LLMTimeoutError, TimeoutError):
-        # In this case, we decide to continue and don't raise an error, as
-        # little harm in letting some docs through that are less relevant.
-        logger.error("LLM Timeout Error - verify documents")
-
-    except LLMRateLimitError:
-        # In this case, we decide to continue and don't raise an error, as
-        # little harm in letting some docs through that are less relevant.
-        logger.error("LLM Rate Limit Error - verify documents")
+    verified_documents = []
+    if isinstance(response.content, str) and "yes" in response.content.lower():
+        verified_documents.append(retrieved_document_to_verify)
 
     return DocVerificationUpdate(
         verified_documents=verified_documents,
-        log_messages=[
-            get_langgraph_node_log_string(
-                graph_component="shared - expanded retrieval",
-                node_name="verify documents",
-                node_start_time=node_start_time,
-            )
-        ],
     )

backend/onyx/agents/agent_search/deep_search/shared/expanded_retrieval/states.py

@@ -21,13 +21,9 @@ from onyx.context.search.models import InferenceSection
 
 
 class ExpandedRetrievalInput(SubgraphCoreState):
-    # exception from 'no default value'for LangGraph input states
-    # Here, sub_question_id default None implies usage for the
-    # original question. This is sometimes needed for nested sub-graphs
-
+    question: str = ""
+    base_search: bool = False
     sub_question_id: str | None = None
-    question: str
-    base_search: bool
 
 
 ## Update/Return States
@@ -38,7 +34,7 @@ class QueryExpansionUpdate(LoggerUpdate, BaseModel):
     log_messages: list[str] = []
 
 
-class DocVerificationUpdate(LoggerUpdate, BaseModel):
+class DocVerificationUpdate(BaseModel):
     verified_documents: Annotated[list[InferenceSection], dedup_inference_sections] = []
 
 
@@ -92,4 +88,4 @@ class DocVerificationInput(ExpandedRetrievalInput):
 
 
 class RetrievalInput(ExpandedRetrievalInput):
-    query_to_retrieve: str
+    query_to_retrieve: str = ""

backend/onyx/agents/agent_search/models.py

@@ -67,7 +67,6 @@ class GraphSearchConfig(BaseModel):
     # Whether to allow creation of refinement questions (and entity extraction, etc.)
     allow_refinement: bool = True
     skip_gen_ai_answer_generation: bool = False
-    allow_agent_reranking: bool = False
 
 
 class GraphConfig(BaseModel):

backend/onyx/agents/agent_search/orchestration/nodes/basic_use_tool_response.py

@@ -9,23 +9,18 @@ from onyx.agents.agent_search.basic.states import BasicState
 from onyx.agents.agent_search.basic.utils import process_llm_stream
 from onyx.agents.agent_search.models import GraphConfig
 from onyx.chat.models import LlmDoc
+from onyx.chat.models import OnyxContexts
 from onyx.tools.tool_implementations.search.search_tool import (
-    SEARCH_RESPONSE_SUMMARY_ID,
-)
-from onyx.tools.tool_implementations.search.search_tool import SearchResponseSummary
-from onyx.tools.tool_implementations.search.search_utils import (
-    context_from_inference_section,
+    SEARCH_DOC_CONTENT_ID,
 )
 from onyx.tools.tool_implementations.search_like_tool_utils import (
     FINAL_CONTEXT_DOCUMENTS_ID,
 )
 from onyx.utils.logger import setup_logger
-from onyx.utils.timing import log_function_time
 
 logger = setup_logger()
 
 
-@log_function_time(print_only=True)
 def basic_use_tool_response(
     state: BasicState, config: RunnableConfig, writer: StreamWriter = lambda _: None
 ) -> BasicOutput:
@@ -55,13 +50,11 @@ def basic_use_tool_response(
     for yield_item in tool_call_responses:
         if yield_item.id == FINAL_CONTEXT_DOCUMENTS_ID:
             final_search_results = cast(list[LlmDoc], yield_item.response)
-        elif yield_item.id == SEARCH_RESPONSE_SUMMARY_ID:
-            search_response_summary = cast(SearchResponseSummary, yield_item.response)
-            for section in search_response_summary.top_sections:
-                if section.center_chunk.document_id not in initial_search_results:
-                    initial_search_results.append(
-                        context_from_inference_section(section)
-                    )
+        elif yield_item.id == SEARCH_DOC_CONTENT_ID:
+            search_contexts = cast(OnyxContexts, yield_item.response).contexts
+            for doc in search_contexts:
+                if doc.document_id not in initial_search_results:
+                    initial_search_results.append(doc)
 
     new_tool_call_chunk = AIMessageChunk(content="")
     if not agent_config.behavior.skip_gen_ai_answer_generation:

backend/onyx/agents/agent_search/orchestration/nodes/llm_tool_choice.py

@@ -15,17 +15,8 @@ from onyx.chat.tool_handling.tool_response_handler import get_tool_by_name
 from onyx.chat.tool_handling.tool_response_handler import (
     get_tool_call_for_non_tool_calling_llm_impl,
 )
-from onyx.context.search.preprocessing.preprocessing import query_analysis
-from onyx.context.search.retrieval.search_runner import get_query_embedding
-from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.tool import Tool
-from onyx.tools.tool_implementations.search.search_tool import SearchTool
 from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_in_background
-from onyx.utils.threadpool_concurrency import TimeoutThread
-from onyx.utils.threadpool_concurrency import wait_on_background
-from onyx.utils.timing import log_function_time
-from shared_configs.model_server_models import Embedding
 
 logger = setup_logger()
 
@@ -34,8 +25,7 @@ logger = setup_logger()
 # and a function that handles extracting the necessary fields
 # from the state and config
 # TODO: fan-out to multiple tool call nodes? Make this configurable?
-@log_function_time(print_only=True)
-def choose_tool(
+def llm_tool_choice(
     state: ToolChoiceState,
     config: RunnableConfig,
     writer: StreamWriter = lambda _: None,
@@ -47,31 +37,6 @@ def choose_tool(
     should_stream_answer = state.should_stream_answer
 
     agent_config = cast(GraphConfig, config["metadata"]["config"])
-
-    force_use_tool = agent_config.tooling.force_use_tool
-
-    embedding_thread: TimeoutThread[Embedding] | None = None
-    keyword_thread: TimeoutThread[tuple[bool, list[str]]] | None = None
-    override_kwargs: SearchToolOverrideKwargs | None = None
-    if (
-        not agent_config.behavior.use_agentic_search
-        and agent_config.tooling.search_tool is not None
-        and (
-            not force_use_tool.force_use or force_use_tool.tool_name == SearchTool.name
-        )
-    ):
-        override_kwargs = SearchToolOverrideKwargs()
-        # Run in a background thread to avoid blocking the main thread
-        embedding_thread = run_in_background(
-            get_query_embedding,
-            agent_config.inputs.search_request.query,
-            agent_config.persistence.db_session,
-        )
-        keyword_thread = run_in_background(
-            query_analysis,
-            agent_config.inputs.search_request.query,
-        )
-
     using_tool_calling_llm = agent_config.tooling.using_tool_calling_llm
     prompt_builder = state.prompt_snapshot or agent_config.inputs.prompt_builder
 
@@ -82,6 +47,7 @@ def choose_tool(
     tools = [
         tool for tool in (agent_config.tooling.tools or []) if tool.name in state.tools
     ]
+    force_use_tool = agent_config.tooling.force_use_tool
 
     tool, tool_args = None, None
     if force_use_tool.force_use and force_use_tool.args is not None:
@@ -105,22 +71,11 @@ def choose_tool(
     # If we have a tool and tool args, we are ready to request a tool call.
     # This only happens if the tool call was forced or we are using a non-tool calling LLM.
     if tool and tool_args:
-        if embedding_thread and tool.name == SearchTool._NAME:
-            # Wait for the embedding thread to finish
-            embedding = wait_on_background(embedding_thread)
-            assert override_kwargs is not None, "must have override kwargs"
-            override_kwargs.precomputed_query_embedding = embedding
-        if keyword_thread and tool.name == SearchTool._NAME:
-            is_keyword, keywords = wait_on_background(keyword_thread)
-            assert override_kwargs is not None, "must have override kwargs"
-            override_kwargs.precomputed_is_keyword = is_keyword
-            override_kwargs.precomputed_keywords = keywords
         return ToolChoiceUpdate(
             tool_choice=ToolChoice(
                 tool=tool,
                 tool_args=tool_args,
                 id=str(uuid4()),
-                search_tool_override_kwargs=override_kwargs,
             ),
         )
 
@@ -143,16 +98,8 @@ def choose_tool(
         # For tool calling LLMs, we want to insert the task prompt as part of this flow, this is because the LLM
         # may choose to not call any tools and just generate the answer, in which case the task prompt is needed.
         prompt=built_prompt,
-        tools=(
-            [tool.tool_definition() for tool in tools] or None
-            if using_tool_calling_llm
-            else None
-        ),
-        tool_choice=(
-            "required"
-            if tools and force_use_tool.force_use and using_tool_calling_llm
-            else None
-        ),
+        tools=[tool.tool_definition() for tool in tools] or None,
+        tool_choice=("required" if tools and force_use_tool.force_use else None),
         structured_response_format=structured_response_format,
     )
 
@@ -198,22 +145,10 @@ def choose_tool(
     logger.debug(f"Selected tool: {selected_tool.name}")
     logger.debug(f"Selected tool call request: {selected_tool_call_request}")
 
-    if embedding_thread and selected_tool.name == SearchTool._NAME:
-        # Wait for the embedding thread to finish
-        embedding = wait_on_background(embedding_thread)
-        assert override_kwargs is not None, "must have override kwargs"
-        override_kwargs.precomputed_query_embedding = embedding
-    if keyword_thread and selected_tool.name == SearchTool._NAME:
-        is_keyword, keywords = wait_on_background(keyword_thread)
-        assert override_kwargs is not None, "must have override kwargs"
-        override_kwargs.precomputed_is_keyword = is_keyword
-        override_kwargs.precomputed_keywords = keywords
-
     return ToolChoiceUpdate(
         tool_choice=ToolChoice(
             tool=selected_tool,
             tool_args=selected_tool_call_request["args"],
             id=selected_tool_call_request["id"],
-            search_tool_override_kwargs=override_kwargs,
         ),
     )

backend/onyx/agents/agent_search/orchestration/nodes/tool_call.py

@@ -28,7 +28,7 @@ def emit_packet(packet: AnswerPacket, writer: StreamWriter) -> None:
     write_custom_event("basic_response", packet, writer)
 
 
-def call_tool(
+def tool_call(
     state: ToolChoiceUpdate,
     config: RunnableConfig,
     writer: StreamWriter = lambda _: None,
@@ -44,9 +44,7 @@ def call_tool(
     tool = tool_choice.tool
     tool_args = tool_choice.tool_args
     tool_id = tool_choice.id
-    tool_runner = ToolRunner(
-        tool, tool_args, override_kwargs=tool_choice.search_tool_override_kwargs
-    )
+    tool_runner = ToolRunner(tool, tool_args)
     tool_kickoff = tool_runner.kickoff()
 
     emit_packet(tool_kickoff, writer)

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

@@ -2,7 +2,6 @@ from pydantic import BaseModel
 
 from onyx.chat.prompt_builder.answer_prompt_builder import PromptSnapshot
 from onyx.tools.message import ToolCallSummary
-from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.models import ToolCallFinalResult
 from onyx.tools.models import ToolCallKickoff
 from onyx.tools.models import ToolResponse
@@ -36,7 +35,6 @@ class ToolChoice(BaseModel):
     tool: Tool
     tool_args: dict
     id: str | None
-    search_tool_override_kwargs: SearchToolOverrideKwargs | None = None
 
     class Config:
         arbitrary_types_allowed = True

backend/onyx/agents/agent_search/run_graph.py

@@ -12,7 +12,7 @@ from onyx.agents.agent_search.deep_search.main.graph_builder import (
     main_graph_builder as main_graph_builder_a,
 )
 from onyx.agents.agent_search.deep_search.main.states import (
-    MainInput as MainInput,
+    MainInput as MainInput_a,
 )
 from onyx.agents.agent_search.models import GraphConfig
 from onyx.agents.agent_search.shared_graph_utils.utils import get_test_config
@@ -21,7 +21,6 @@ from onyx.chat.models import AnswerPacket
 from onyx.chat.models import AnswerStream
 from onyx.chat.models import ExtendedToolResponse
 from onyx.chat.models import RefinedAnswerImprovement
-from onyx.chat.models import StreamingError
 from onyx.chat.models import StreamStopInfo
 from onyx.chat.models import SubQueryPiece
 from onyx.chat.models import SubQuestionPiece
@@ -34,7 +33,6 @@ from onyx.llm.factory import get_default_llms
 from onyx.tools.tool_runner import ToolCallKickoff
 from onyx.utils.logger import setup_logger
 
-
 logger = setup_logger()
 
 _COMPILED_GRAPH: CompiledStateGraph | None = None
@@ -74,15 +72,13 @@ def _parse_agent_event(
             return cast(AnswerPacket, event["data"])
         elif event["name"] == "refined_answer_improvement":
             return cast(RefinedAnswerImprovement, event["data"])
-        elif event["name"] == "refined_sub_question_creation_error":
-            return cast(StreamingError, event["data"])
     return None
 
 
 def manage_sync_streaming(
     compiled_graph: CompiledStateGraph,
     config: GraphConfig,
-    graph_input: BasicInput | MainInput,
+    graph_input: BasicInput | MainInput_a,
 ) -> Iterable[StreamEvent]:
     message_id = config.persistence.message_id if config.persistence else None
     for event in compiled_graph.stream(
@@ -96,7 +92,7 @@ def manage_sync_streaming(
 def run_graph(
     compiled_graph: CompiledStateGraph,
     config: GraphConfig,
-    input: BasicInput | MainInput,
+    input: BasicInput | MainInput_a,
 ) -> AnswerStream:
     config.behavior.perform_initial_search_decomposition = (
         INITIAL_SEARCH_DECOMPOSITION_ENABLED
@@ -127,7 +123,9 @@ def run_main_graph(
 ) -> AnswerStream:
     compiled_graph = load_compiled_graph()
 
-    input = MainInput(log_messages=[])
+    input = MainInput_a(
+        base_question=config.inputs.search_request.query, log_messages=[]
+    )
 
     # Agent search is not a Tool per se, but this is helpful for the frontend
     yield ToolCallKickoff(
@@ -142,7 +140,7 @@ def run_basic_graph(
 ) -> AnswerStream:
     graph = basic_graph_builder()
     compiled_graph = graph.compile()
-    input = BasicInput(unused=True)
+    input = BasicInput()
     return run_graph(compiled_graph, config, input)
 
 
@@ -174,7 +172,9 @@ if __name__ == "__main__":
             # search_request.persona = get_persona_by_id(1, None, db_session)
             # config.perform_initial_search_path_decision = False
             config.behavior.perform_initial_search_decomposition = True
-            input = MainInput(log_messages=[])
+            input = MainInput_a(
+                base_question=config.inputs.search_request.query, log_messages=[]
+            )
 
             tool_responses: list = []
             for output in run_graph(compiled_graph, config, input):

backend/onyx/agents/agent_search/shared_graph_utils/agent_prompt_ops.py

@@ -7,7 +7,6 @@ from onyx.agents.agent_search.models import GraphConfig
 from onyx.agents.agent_search.shared_graph_utils.models import (
     AgentPromptEnrichmentComponents,
 )
-from onyx.agents.agent_search.shared_graph_utils.utils import format_docs
 from onyx.agents.agent_search.shared_graph_utils.utils import (
     get_persona_agent_prompt_expressions,
 )
@@ -41,7 +40,13 @@ def build_sub_question_answer_prompt(
 
     date_str = build_date_time_string()
 
-    docs_str = format_docs(docs)
+    # TODO: This should include document metadata and title
+    docs_format_list = [
+        f"Document Number: [D{doc_num + 1}]\nContent: {doc.combined_content}\n\n"
+        for doc_num, doc in enumerate(docs)
+    ]
+
+    docs_str = "\n\n".join(docs_format_list)
 
     docs_str = trim_prompt_piece(
         config,
@@ -145,38 +150,3 @@ def get_prompt_enrichment_components(
         history=history,
         date_str=date_str,
     )
-
-
-def binary_string_test(text: str, positive_value: str = "yes") -> bool:
-    """
-    Tests if a string contains a positive value (case-insensitive).
-
-    Args:
-        text: The string to test
-        positive_value: The value to look for (defaults to "yes")
-
-    Returns:
-        True if the positive value is found in the text
-    """
-    return positive_value.lower() in text.lower()
-
-
-def binary_string_test_after_answer_separator(
-    text: str, positive_value: str = "yes", separator: str = "Answer:"
-) -> bool:
-    """
-    Tests if a string contains a positive value (case-insensitive).
-
-    Args:
-        text: The string to test
-        positive_value: The value to look for (defaults to "yes")
-
-    Returns:
-        True if the positive value is found in the text
-    """
-
-    if separator not in text:
-        return False
-    relevant_text = text.split(f"{separator}")[-1]
-
-    return binary_string_test(relevant_text, positive_value)

backend/onyx/agents/agent_search/shared_graph_utils/calculations.py

@@ -1,11 +1,7 @@
 import numpy as np
 
-from onyx.agents.agent_search.shared_graph_utils.models import AnswerGenerationDocuments
 from onyx.agents.agent_search.shared_graph_utils.models import RetrievalFitScoreMetrics
 from onyx.agents.agent_search.shared_graph_utils.models import RetrievalFitStats
-from onyx.agents.agent_search.shared_graph_utils.operators import (
-    dedup_inference_section_list,
-)
 from onyx.chat.models import SectionRelevancePiece
 from onyx.context.search.models import InferenceSection
 from onyx.utils.logger import setup_logger
@@ -100,106 +96,3 @@ def get_fit_scores(
     )
 
     return fit_eval
-
-
-def get_answer_generation_documents(
-    relevant_docs: list[InferenceSection],
-    context_documents: list[InferenceSection],
-    original_question_docs: list[InferenceSection],
-    max_docs: int,
-) -> AnswerGenerationDocuments:
-    """
-    Create a deduplicated list of documents to stream, prioritizing relevant docs.
-
-    Args:
-        relevant_docs: Primary documents to include
-        context_documents: Additional context documents to append
-        original_question_docs: Original question documents to append
-        max_docs: Maximum number of documents to return
-
-    Returns:
-        List of deduplicated documents, limited to max_docs
-    """
-    # get relevant_doc ids
-    relevant_doc_ids = [doc.center_chunk.document_id for doc in relevant_docs]
-
-    # Start with relevant docs or fallback to original question docs
-    streaming_documents = relevant_docs.copy()
-
-    # Use a set for O(1) lookups of document IDs
-    seen_doc_ids = {doc.center_chunk.document_id for doc in streaming_documents}
-
-    # Combine additional documents to check in one iteration
-    additional_docs = context_documents + original_question_docs
-    for doc_idx, doc in enumerate(additional_docs):
-        doc_id = doc.center_chunk.document_id
-        if doc_id not in seen_doc_ids:
-            streaming_documents.append(doc)
-            seen_doc_ids.add(doc_id)
-
-    streaming_documents = dedup_inference_section_list(streaming_documents)
-
-    relevant_streaming_docs = [
-        doc
-        for doc in streaming_documents
-        if doc.center_chunk.document_id in relevant_doc_ids
-    ]
-    relevant_streaming_docs = dedup_sort_inference_section_list(relevant_streaming_docs)
-
-    additional_streaming_docs = [
-        doc
-        for doc in streaming_documents
-        if doc.center_chunk.document_id not in relevant_doc_ids
-    ]
-    additional_streaming_docs = dedup_sort_inference_section_list(
-        additional_streaming_docs
-    )
-
-    for doc in additional_streaming_docs:
-        if doc.center_chunk.score:
-            doc.center_chunk.score += -2.0
-        else:
-            doc.center_chunk.score = -2.0
-
-    sorted_streaming_documents = relevant_streaming_docs + additional_streaming_docs
-
-    return AnswerGenerationDocuments(
-        streaming_documents=sorted_streaming_documents[:max_docs],
-        context_documents=relevant_streaming_docs[:max_docs],
-    )
-
-
-def dedup_sort_inference_section_list(
-    sections: list[InferenceSection],
-) -> list[InferenceSection]:
-    """Deduplicates InferenceSections by document_id and sorts by score.
-
-    Args:
-        sections: List of InferenceSections to deduplicate and sort
-
-    Returns:
-        Deduplicated list of InferenceSections sorted by score in descending order
-    """
-    # dedupe/merge with existing framework
-    sections = dedup_inference_section_list(sections)
-
-    # Use dict to deduplicate by document_id, keeping highest scored version
-    unique_sections: dict[str, InferenceSection] = {}
-    for section in sections:
-        doc_id = section.center_chunk.document_id
-        if doc_id not in unique_sections:
-            unique_sections[doc_id] = section
-            continue
-
-        # Keep version with higher score
-        existing_score = unique_sections[doc_id].center_chunk.score or 0
-        new_score = section.center_chunk.score or 0
-        if new_score > existing_score:
-            unique_sections[doc_id] = section
-
-    # Sort by score in descending order, handling None scores
-    sorted_sections = sorted(
-        unique_sections.values(), key=lambda x: x.center_chunk.score or 0, reverse=True
-    )
-
-    return sorted_sections

backend/onyx/agents/agent_search/shared_graph_utils/constants.py

@@ -1,24 +0,0 @@
-from enum import Enum
-
-AGENT_LLM_TIMEOUT_MESSAGE = "The agent timed out. Please try again."
-AGENT_LLM_ERROR_MESSAGE = "The agent encountered an error. Please try again."
-AGENT_LLM_RATELIMIT_MESSAGE = (
-    "The agent encountered a rate limit error. Please try again."
-)
-LLM_ANSWER_ERROR_MESSAGE = "The question was not answered due to an LLM error."
-
-AGENT_POSITIVE_VALUE_STR = "yes"
-AGENT_NEGATIVE_VALUE_STR = "no"
-
-AGENT_ANSWER_SEPARATOR = "Answer:"
-
-
-EMBEDDING_KEY = "embedding"
-IS_KEYWORD_KEY = "is_keyword"
-KEYWORDS_KEY = "keywords"
-
-
-class AgentLLMErrorType(str, Enum):
-    TIMEOUT = "timeout"
-    RATE_LIMIT = "rate_limit"
-    GENERAL_ERROR = "general_error"

backend/onyx/agents/agent_search/shared_graph_utils/models.py

@@ -1,5 +1,3 @@
-from typing import Any
-
 from pydantic import BaseModel
 
 from onyx.agents.agent_search.deep_search.main.models import (
@@ -58,12 +56,6 @@ class InitialAgentResultStats(BaseModel):
     agent_effectiveness: dict[str, float | int | None]
 
 
-class AgentErrorLog(BaseModel):
-    error_message: str
-    error_type: str
-    error_result: str
-
-
 class RefinedAgentStats(BaseModel):
     revision_doc_efficiency: float | None
     revision_question_efficiency: float | None
@@ -118,11 +110,6 @@ class SubQuestionAnswerResults(BaseModel):
     sub_question_retrieval_stats: AgentChunkRetrievalStats
 
 
-class StructuredSubquestionDocuments(BaseModel):
-    cited_documents: list[InferenceSection]
-    context_documents: list[InferenceSection]
-
-
 class CombinedAgentMetrics(BaseModel):
     timings: AgentTimings
     base_metrics: AgentBaseMetrics | None
@@ -139,17 +126,3 @@ class AgentPromptEnrichmentComponents(BaseModel):
     persona_prompts: PersonaPromptExpressions
     history: str
     date_str: str
-
-
-class LLMNodeErrorStrings(BaseModel):
-    timeout: str = "LLM Timeout Error"
-    rate_limit: str = "LLM Rate Limit Error"
-    general_error: str = "General LLM Error"
-
-
-class AnswerGenerationDocuments(BaseModel):
-    streaming_documents: list[InferenceSection]
-    context_documents: list[InferenceSection]
-
-
-BaseMessage_Content = str | list[str | dict[str, Any]]

backend/onyx/agents/agent_search/shared_graph_utils/operators.py

@@ -12,13 +12,6 @@ def dedup_inference_sections(
     return deduped
 
 
-def dedup_inference_section_list(
-    list: list[InferenceSection],
-) -> list[InferenceSection]:
-    deduped = _merge_sections(list)
-    return deduped
-
-
 def dedup_question_answer_results(
     question_answer_results_1: list[SubQuestionAnswerResults],
     question_answer_results_2: list[SubQuestionAnswerResults],

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

@@ -20,18 +20,10 @@ from onyx.agents.agent_search.models import GraphInputs
 from onyx.agents.agent_search.models import GraphPersistence
 from onyx.agents.agent_search.models import GraphSearchConfig
 from onyx.agents.agent_search.models import GraphTooling
-from onyx.agents.agent_search.shared_graph_utils.models import BaseMessage_Content
 from onyx.agents.agent_search.shared_graph_utils.models import (
     EntityRelationshipTermExtraction,
 )
 from onyx.agents.agent_search.shared_graph_utils.models import PersonaPromptExpressions
-from onyx.agents.agent_search.shared_graph_utils.models import (
-    StructuredSubquestionDocuments,
-)
-from onyx.agents.agent_search.shared_graph_utils.models import SubQuestionAnswerResults
-from onyx.agents.agent_search.shared_graph_utils.operators import (
-    dedup_inference_section_list,
-)
 from onyx.chat.models import AnswerPacket
 from onyx.chat.models import AnswerStyleConfig
 from onyx.chat.models import CitationConfig
@@ -42,11 +34,6 @@ from onyx.chat.models import StreamStopInfo
 from onyx.chat.models import StreamStopReason
 from onyx.chat.models import StreamType
 from onyx.chat.prompt_builder.answer_prompt_builder import AnswerPromptBuilder
-from onyx.configs.agent_configs import AGENT_MAX_TOKENS_HISTORY_SUMMARY
-from onyx.configs.agent_configs import (
-    AGENT_TIMEOUT_CONNECT_LLM_HISTORY_SUMMARY_GENERATION,
-)
-from onyx.configs.agent_configs import AGENT_TIMEOUT_LLM_HISTORY_SUMMARY_GENERATION
 from onyx.configs.chat_configs import CHAT_TARGET_CHUNK_PERCENTAGE
 from onyx.configs.chat_configs import MAX_CHUNKS_FED_TO_CHAT
 from onyx.configs.constants import DEFAULT_PERSONA_ID
@@ -59,10 +46,7 @@ from onyx.context.search.models import SearchRequest
 from onyx.db.engine import get_session_context_manager
 from onyx.db.persona import get_persona_by_id
 from onyx.db.persona import Persona
-from onyx.llm.chat_llm import LLMRateLimitError
-from onyx.llm.chat_llm import LLMTimeoutError
 from onyx.llm.interfaces import LLM
-from onyx.llm.interfaces import LLMConfig
 from onyx.prompts.agent_search import (
     ASSISTANT_SYSTEM_PROMPT_DEFAULT,
 )
@@ -74,7 +58,6 @@ from onyx.prompts.agent_search import (
 )
 from onyx.prompts.prompt_utils import handle_onyx_date_awareness
 from onyx.tools.force import ForceUseTool
-from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.tool_constructor import SearchToolConfig
 from onyx.tools.tool_implementations.search.search_tool import (
     SEARCH_RESPONSE_SUMMARY_ID,
@@ -82,10 +65,8 @@ from onyx.tools.tool_implementations.search.search_tool import (
 from onyx.tools.tool_implementations.search.search_tool import SearchResponseSummary
 from onyx.tools.tool_implementations.search.search_tool import SearchTool
 from onyx.tools.utils import explicit_tool_calling_supported
-from onyx.utils.logger import setup_logger
-from onyx.utils.threadpool_concurrency import run_with_timeout
 
-logger = setup_logger()
+BaseMessage_Content = str | list[str | dict[str, Any]]
 
 
 # Post-processing
@@ -237,10 +218,7 @@ def get_test_config(
         using_tool_calling_llm=using_tool_calling_llm,
     )
 
-    chat_session_id = (
-        os.environ.get("ONYX_AS_CHAT_SESSION_ID")
-        or "00000000-0000-0000-0000-000000000000"
-    )
+    chat_session_id = os.environ.get("ONYX_AS_CHAT_SESSION_ID")
     assert (
         chat_session_id is not None
     ), "ONYX_AS_CHAT_SESSION_ID must be set for backend tests"
@@ -363,12 +341,8 @@ def retrieve_search_docs(
     with get_session_context_manager() as db_session:
         for tool_response in search_tool.run(
             query=question,
-            override_kwargs=SearchToolOverrideKwargs(
-                force_no_rerank=True,
-                alternate_db_session=db_session,
-                retrieved_sections_callback=None,
-                skip_query_analysis=False,
-            ),
+            force_no_rerank=True,
+            alternate_db_session=db_session,
         ):
             # get retrieved docs to send to the rest of the graph
             if tool_response.id == SEARCH_RESPONSE_SUMMARY_ID:
@@ -398,27 +372,8 @@ def summarize_history(
         )
     )
 
-    try:
-        history_response = run_with_timeout(
-            AGENT_TIMEOUT_LLM_HISTORY_SUMMARY_GENERATION,
-            llm.invoke,
-            history_context_prompt,
-            timeout_override=AGENT_TIMEOUT_CONNECT_LLM_HISTORY_SUMMARY_GENERATION,
-            max_tokens=AGENT_MAX_TOKENS_HISTORY_SUMMARY,
-        )
-    except (LLMTimeoutError, TimeoutError):
-        logger.error("LLM Timeout Error - summarize history")
-        return (
-            history  # this is what is done at this point anyway, so we default to this
-        )
-    except LLMRateLimitError:
-        logger.error("LLM Rate Limit Error - summarize history")
-        return (
-            history  # this is what is done at this point anyway, so we default to this
-        )
-
+    history_response = llm.invoke(history_context_prompt)
     assert isinstance(history_response.content, str)
-
     return history_response.content
 
 
@@ -484,33 +439,3 @@ def remove_document_citations(text: str) -> str:
     #   \d+  - one or more digits
     #   \]   - literal ] character
     return re.sub(r"\[(?:D|Q)?\d+\]", "", text)
-
-
-def get_deduplicated_structured_subquestion_documents(
-    sub_question_results: list[SubQuestionAnswerResults],
-) -> StructuredSubquestionDocuments:
-    """
-    Extract and deduplicate all cited documents from sub-question results.
-
-    Args:
-        sub_question_results: List of sub-question results containing cited documents
-
-    Returns:
-        Deduplicated list of cited documents
-    """
-    cited_docs = [
-        doc for result in sub_question_results for doc in result.cited_documents
-    ]
-    context_docs = [
-        doc for result in sub_question_results for doc in result.context_documents
-    ]
-    return StructuredSubquestionDocuments(
-        cited_documents=dedup_inference_section_list(cited_docs),
-        context_documents=dedup_inference_section_list(context_docs),
-    )
-
-
-def _should_restrict_tokens(llm_config: LLMConfig) -> bool:
-    return not (
-        llm_config.model_provider == "openai" and llm_config.model_name.startswith("o")
-    )

backend/onyx/auth/api_key.py

@@ -10,7 +10,6 @@ from pydantic import BaseModel
 
 from onyx.auth.schemas import UserRole
 from onyx.configs.app_configs import API_KEY_HASH_ROUNDS
-from shared_configs.configs import MULTI_TENANT
 
 
 _API_KEY_HEADER_NAME = "Authorization"
@@ -36,7 +35,8 @@ class ApiKeyDescriptor(BaseModel):
 
 
 def generate_api_key(tenant_id: str | None = None) -> str:
-    if not MULTI_TENANT or not tenant_id:
+    # For backwards compatibility, if no tenant_id, generate old style key
+    if not tenant_id:
         return _API_KEY_PREFIX + secrets.token_urlsafe(_API_KEY_LEN)
 
     encoded_tenant = quote(tenant_id)  # URL encode the tenant ID

backend/onyx/auth/email_utils.py

@@ -1,9 +1,7 @@
 import smtplib
-from datetime import datetime
 from email.mime.multipart import MIMEMultipart
 from email.mime.text import MIMEText
-from email.utils import formatdate
-from email.utils import make_msgid
+from textwrap import dedent
 
 from onyx.configs.app_configs import EMAIL_CONFIGURED
 from onyx.configs.app_configs import EMAIL_FROM
@@ -12,156 +10,26 @@ from onyx.configs.app_configs import SMTP_PORT
 from onyx.configs.app_configs import SMTP_SERVER
 from onyx.configs.app_configs import SMTP_USER
 from onyx.configs.app_configs import WEB_DOMAIN
-from onyx.configs.constants import AuthType
 from onyx.configs.constants import TENANT_ID_COOKIE_NAME
 from onyx.db.models import User
-from shared_configs.configs import MULTI_TENANT
-
-HTML_EMAIL_TEMPLATE = """\
-<!DOCTYPE html>
-<html lang="en">
-<head>
-  <meta charset="UTF-8">
-  <meta name="viewport" content="width=device-width" />
-  <title>{title}</title>
-  <style>
-    body, table, td, a {{
-      font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
-      text-size-adjust: 100%;
-      margin: 0;
-      padding: 0;
-      -webkit-font-smoothing: antialiased;
-      -webkit-text-size-adjust: none;
-    }}
-    body {{
-      background-color: #f7f7f7;
-      color: #333;
-    }}
-    .body-content {{
-      color: #333;
-    }}
-    .email-container {{
-      width: 100%;
-      max-width: 600px;
-      margin: 0 auto;
-      background-color: #ffffff;
-      border-radius: 6px;
-      overflow: hidden;
-      border: 1px solid #eaeaea;
-    }}
-    .header {{
-      background-color: #000000;
-      padding: 20px;
-      text-align: center;
-    }}
-    .header img {{
-      max-width: 140px;
-    }}
-    .body-content {{
-      padding: 20px 30px;
-    }}
-    .title {{
-      font-size: 20px;
-      font-weight: bold;
-      margin: 0 0 10px;
-    }}
-    .message {{
-      font-size: 16px;
-      line-height: 1.5;
-      margin: 0 0 20px;
-    }}
-    .cta-button {{
-      display: inline-block;
-      padding: 12px 20px;
-      background-color: #000000;
-      color: #ffffff !important;
-      text-decoration: none;
-      border-radius: 4px;
-      font-weight: 500;
-    }}
-    .footer {{
-      font-size: 13px;
-      color: #6A7280;
-      text-align: center;
-      padding: 20px;
-    }}
-    .footer a {{
-      color: #6b7280;
-      text-decoration: underline;
-    }}
-  </style>
-</head>
-<body>
-  <table role="presentation" class="email-container" cellpadding="0" cellspacing="0">
-    <tr>
-      <td class="header">
-        <img
-          style="background-color: #ffffff; border-radius: 8px;"
-          src="https://www.onyx.app/logos/customer/onyx.png"
-          alt="Onyx Logo"
-        >
-      </td>
-    </tr>
-    <tr>
-      <td class="body-content">
-        <h1 class="title">{heading}</h1>
-        <div class="message">
-          {message}
-        </div>
-        {cta_block}
-      </td>
-    </tr>
-    <tr>
-      <td class="footer">
-        © {year} Onyx. All rights reserved.
-        <br>
-        Have questions? Join our Slack community <a href="https://join.slack.com/t/onyx-dot-app/shared_invite/zt-2twesxdr6-5iQitKZQpgq~hYIZ~dv3KA">here</a>.
-      </td>
-    </tr>
-  </table>
-</body>
-</html>
-"""
-
-
-def build_html_email(
-    heading: str, message: str, cta_text: str | None = None, cta_link: str | None = None
-) -> str:
-    if cta_text and cta_link:
-        cta_block = f'<a class="cta-button" href="{cta_link}">{cta_text}</a>'
-    else:
-        cta_block = ""
-    return HTML_EMAIL_TEMPLATE.format(
-        title=heading,
-        heading=heading,
-        message=message,
-        cta_block=cta_block,
-        year=datetime.now().year,
-    )
 
 
 def send_email(
     user_email: str,
     subject: str,
-    html_body: str,
-    text_body: str,
+    body: str,
     mail_from: str = EMAIL_FROM,
 ) -> None:
     if not EMAIL_CONFIGURED:
         raise ValueError("Email is not configured.")
 
-    msg = MIMEMultipart("alternative")
+    msg = MIMEMultipart()
     msg["Subject"] = subject
     msg["To"] = user_email
-    msg["From"] = mail_from
-    msg["Date"] = formatdate(localtime=True)
-    msg["Message-ID"] = make_msgid(domain="onyx.app")
+    if mail_from:
+        msg["From"] = mail_from
 
-    part_text = MIMEText(text_body, "plain")
-    part_html = MIMEText(html_body, "html")
-
-    msg.attach(part_text)
-    msg.attach(part_html)
+    msg.attach(MIMEText(body))
 
     try:
         with smtplib.SMTP(SMTP_SERVER, SMTP_PORT) as s:
@@ -172,89 +40,41 @@ def send_email(
         raise e
 
 
-def send_subscription_cancellation_email(user_email: str) -> None:
-    # Example usage of the reusable HTML
-    subject = "Your Onyx Subscription Has Been Canceled"
-    heading = "Subscription Canceled"
-    message = (
-        "<p>We're sorry to see you go.</p>"
-        "<p>Your subscription has been canceled and will end on your next billing date.</p>"
-        "<p>If you change your mind, you can always come back!</p>"
-    )
-    cta_text = "Renew Subscription"
-    cta_link = "https://www.onyx.app/pricing"
-    html_content = build_html_email(heading, message, cta_text, cta_link)
-    text_content = (
-        "We're sorry to see you go.\n"
-        "Your subscription has been canceled and will end on your next billing date.\n"
-        "If you change your mind, visit https://www.onyx.app/pricing"
-    )
-    send_email(user_email, subject, html_content, text_content)
-
-
-def send_user_email_invite(
-    user_email: str, current_user: User, auth_type: AuthType
-) -> None:
+def send_user_email_invite(user_email: str, current_user: User) -> None:
     subject = "Invitation to Join Onyx Organization"
-    heading = "You've Been Invited!"
+    body = dedent(
+        f"""\
+        Hello,
 
-    # the exact action taken by the user, and thus the message, depends on the auth type
-    message = f"<p>You have been invited by {current_user.email} to join an organization on Onyx.</p>"
-    if auth_type == AuthType.CLOUD:
-        message += (
-            "<p>To join the organization, please click the button below to set a password "
-            "or login with Google and complete your registration.</p>"
-        )
-    elif auth_type == AuthType.BASIC:
-        message += (
-            "<p>To join the organization, please click the button below to set a password "
-            "and complete your registration.</p>"
-        )
-    elif auth_type == AuthType.GOOGLE_OAUTH:
-        message += (
-            "<p>To join the organization, please click the button below to login with Google "
-            "and complete your registration.</p>"
-        )
-    elif auth_type == AuthType.OIDC or auth_type == AuthType.SAML:
-        message += (
-            "<p>To join the organization, please click the button below to"
-            " complete your registration.</p>"
-        )
-    else:
-        raise ValueError(f"Invalid auth type: {auth_type}")
+        You have been invited to join an organization on Onyx.
 
-    cta_text = "Join Organization"
-    cta_link = f"{WEB_DOMAIN}/auth/signup?email={user_email}"
-    html_content = build_html_email(heading, message, cta_text, cta_link)
+        To join the organization, please visit the following link:
 
-    # text content is the fallback for clients that don't support HTML
-    # not as critical, so not having special cases for each auth type
-    text_content = (
-        f"You have been invited by {current_user.email} to join an organization on Onyx.\n"
-        "To join the organization, please visit the following link:\n"
-        f"{WEB_DOMAIN}/auth/signup?email={user_email}\n"
+        {WEB_DOMAIN}/auth/signup?email={user_email}
+
+        You'll be asked to set a password or login with Google to complete your registration.
+
+        Best regards,
+        The Onyx Team
+    """
     )
-    if auth_type == AuthType.CLOUD:
-        text_content += "You'll be asked to set a password or login with Google to complete your registration."
 
-    send_email(user_email, subject, html_content, text_content)
+    send_email(user_email, subject, body, current_user.email)
 
 
 def send_forgot_password_email(
     user_email: str,
     token: str,
-    tenant_id: str,
     mail_from: str = EMAIL_FROM,
+    tenant_id: str | None = None,
 ) -> None:
-    # Builds a forgot password email with or without fancy HTML
     subject = "Onyx Forgot Password"
     link = f"{WEB_DOMAIN}/auth/reset-password?token={token}"
-    if MULTI_TENANT:
+    if tenant_id:
         link += f"&{TENANT_ID_COOKIE_NAME}={tenant_id}"
-    message = f"<p>Click the following link to reset your password:</p><p>{link}</p>"
-    html_content = build_html_email("Reset Your Password", message)
-    text_content = f"Click the following link to reset your password: {link}"
-    send_email(user_email, subject, html_content, text_content, mail_from)
+        # Keep search param same name as cookie for simplicity
+    body = f"Click the following link to reset your password: {link}"
+    send_email(user_email, subject, body, mail_from)
 
 
 def send_user_verification_email(
@@ -262,12 +82,7 @@ def send_user_verification_email(
     token: str,
     mail_from: str = EMAIL_FROM,
 ) -> None:
-    # Builds a verification email
     subject = "Onyx Email Verification"
     link = f"{WEB_DOMAIN}/auth/verify-email?token={token}"
-    message = (
-        f"<p>Click the following link to verify your email address:</p><p>{link}</p>"
-    )
-    html_content = build_html_email("Verify Your Email", message)
-    text_content = f"Click the following link to verify your email address: {link}"
-    send_email(user_email, subject, html_content, text_content, mail_from)
+    body = f"Click the following link to verify your email address: {link}"
+    send_email(user_email, subject, body, mail_from)

backend/onyx/auth/noauth_user.py

@@ -42,5 +42,4 @@ def fetch_no_auth_user(
         role=UserRole.BASIC if anonymous_user_enabled else UserRole.ADMIN,
         preferences=load_no_auth_user_preferences(store),
         is_anonymous_user=anonymous_user_enabled,
-        password_configured=False,
     )