quick nit

Co-authored-by: Richard Kuo (Onyx) <rkuo@onyx.app>

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

@@ -0,0 +1,209 @@
+name: Run MIT Integration Tests v2
+concurrency:
+  group: Run-MIT-Integration-Tests-${{ github.workflow }}-${{ github.head_ref || github.event.workflow_run.head_branch || github.run_id }}
+  cancel-in-progress: true
+
+on:
+  merge_group:
+  pull_request:
+    branches:
+      - main
+      - "release/**"
+
+env:
+  OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+  SLACK_BOT_TOKEN: ${{ secrets.SLACK_BOT_TOKEN }}
+  CONFLUENCE_TEST_SPACE_URL: ${{ secrets.CONFLUENCE_TEST_SPACE_URL }}
+  CONFLUENCE_USER_NAME: ${{ secrets.CONFLUENCE_USER_NAME }}
+  CONFLUENCE_ACCESS_TOKEN: ${{ secrets.CONFLUENCE_ACCESS_TOKEN }}
+
+jobs:
+  integration-tests-mit:
+    # See https://runs-on.com/runners/linux/
+    runs-on: [runs-on, runner=32cpu-linux-x64, "run-id=${{ github.run_id }}"]
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Login to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKER_USERNAME }}
+          password: ${{ secrets.DOCKER_TOKEN }}
+
+      # tag every docker image with "test" so that we can spin up the correct set
+      # of images during testing
+
+      # We don't need to build the Web Docker image since it's not yet used
+      # in the integration tests. We have a separate action to verify that it builds
+      # successfully.
+      - name: Pull Web Docker image
+        run: |
+          docker pull onyxdotapp/onyx-web-server:latest
+          docker tag onyxdotapp/onyx-web-server:latest onyxdotapp/onyx-web-server:test
+
+      # we use the runs-on cache for docker builds
+      # in conjunction with runs-on runners, it has better speed and unlimited caching
+      # https://runs-on.com/caching/s3-cache-for-github-actions/
+      # https://runs-on.com/caching/docker/
+      # https://github.com/moby/buildkit#s3-cache-experimental
+
+      # images are built and run locally for testing purposes. Not pushed.
+      - name: Build Backend Docker image
+        uses: ./.github/actions/custom-build-and-push
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile
+          platforms: linux/amd64
+          tags: onyxdotapp/onyx-backend:test
+          push: false
+          load: true
+          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
+          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/backend/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
+
+      - name: Build Model Server Docker image
+        uses: ./.github/actions/custom-build-and-push
+        with:
+          context: ./backend
+          file: ./backend/Dockerfile.model_server
+          platforms: linux/amd64
+          tags: onyxdotapp/onyx-model-server:test
+          push: false
+          load: true
+          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
+          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/model-server/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
+
+      - name: Build integration test Docker image
+        uses: ./.github/actions/custom-build-and-push
+        with:
+          context: ./backend
+          file: ./backend/tests/integration/Dockerfile
+          platforms: linux/amd64
+          tags: onyxdotapp/onyx-integration:test
+          push: false
+          load: true
+          cache-from: type=s3,prefix=cache/${{ github.repository }}/integration-tests/integration/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }}
+          cache-to: type=s3,prefix=cache/${{ github.repository }}/integration-tests/integration/,region=${{ env.RUNS_ON_AWS_REGION }},bucket=${{ env.RUNS_ON_S3_BUCKET_CACHE }},mode=max
+
+      # NOTE: Use pre-ping/null pool to reduce flakiness due to dropped connections
+      - name: Start Docker containers
+        run: |
+          cd deployment/docker_compose
+          AUTH_TYPE=basic \
+          POSTGRES_POOL_PRE_PING=true \
+          POSTGRES_USE_NULL_POOL=true \
+          REQUIRE_EMAIL_VERIFICATION=false \
+          DISABLE_TELEMETRY=true \
+          IMAGE_TAG=test \
+          INTEGRATION_TESTS_MODE=true \
+          docker compose -f docker-compose.dev.yml -p onyx-stack up -d
+        id: start_docker
+
+      - name: Wait for service to be ready
+        run: |
+          echo "Starting wait-for-service script..."
+
+          docker logs -f onyx-stack-api_server-1 &
+
+          start_time=$(date +%s)
+          timeout=300  # 5 minutes in seconds
+
+          while true; do
+            current_time=$(date +%s)
+            elapsed_time=$((current_time - start_time))
+            
+            if [ $elapsed_time -ge $timeout ]; then
+              echo "Timeout reached. Service did not become ready in 5 minutes."
+              exit 1
+            fi
+            
+            # Use curl with error handling to ignore specific exit code 56
+            response=$(curl -s -o /dev/null -w "%{http_code}" http://localhost:8080/health || echo "curl_error")
+            
+            if [ "$response" = "200" ]; then
+              echo "Service is ready!"
+              break
+            elif [ "$response" = "curl_error" ]; then
+              echo "Curl encountered an error, possibly exit code 56. Continuing to retry..."
+            else
+              echo "Service not ready yet (HTTP status $response). Retrying in 5 seconds..."
+            fi
+            
+            sleep 5
+          done
+          echo "Finished waiting for service."
+
+      - name: Start Mock Services
+        run: |
+          cd backend/tests/integration/mock_services
+          docker compose -f docker-compose.mock-it-services.yml \
+            -p mock-it-services-stack up -d
+
+      # NOTE: Use pre-ping/null to reduce flakiness due to dropped connections
+      - name: Run Standard Integration Tests
+        run: |
+          echo "Running integration tests..."
+          docker run --rm --network onyx-stack_default \
+            --name test-runner \
+            -e POSTGRES_HOST=relational_db \
+            -e POSTGRES_USER=postgres \
+            -e POSTGRES_PASSWORD=password \
+            -e POSTGRES_DB=postgres \
+            -e POSTGRES_POOL_PRE_PING=true \
+            -e POSTGRES_USE_NULL_POOL=true \
+            -e VESPA_HOST=index \
+            -e REDIS_HOST=cache \
+            -e API_SERVER_HOST=api_server \
+            -e OPENAI_API_KEY=${OPENAI_API_KEY} \
+            -e SLACK_BOT_TOKEN=${SLACK_BOT_TOKEN} \
+            -e CONFLUENCE_TEST_SPACE_URL=${CONFLUENCE_TEST_SPACE_URL} \
+            -e CONFLUENCE_USER_NAME=${CONFLUENCE_USER_NAME} \
+            -e CONFLUENCE_ACCESS_TOKEN=${CONFLUENCE_ACCESS_TOKEN} \
+            -e TEST_WEB_HOSTNAME=test-runner \
+            -e MOCK_CONNECTOR_SERVER_HOST=mock_connector_server \
+            -e MOCK_CONNECTOR_SERVER_PORT=8001 \
+            onyxdotapp/onyx-integration:test \
+            /app/tests/integration/tests \
+            /app/tests/integration/connector_job_tests
+        continue-on-error: true
+        id: run_tests
+
+      - name: Check test results
+        run: |
+          if [ ${{ steps.run_tests.outcome }} == 'failure' ]; then
+            echo "Integration tests failed. Exiting with error."
+            exit 1
+          else
+            echo "All integration tests passed successfully."
+          fi
+
+      # ------------------------------------------------------------
+      # Always gather logs BEFORE "down":
+      - name: Dump API server logs
+        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
+
+      - name: Dump all-container logs (optional)
+        if: always()
+        run: |
+          cd deployment/docker_compose
+          docker compose -f docker-compose.dev.yml -p onyx-stack logs --no-color > $GITHUB_WORKSPACE/docker-compose.log || true
+
+      - name: Upload logs
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: docker-all-logs
+          path: ${{ github.workspace }}/docker-compose.log
+      # ------------------------------------------------------------
+
+      - name: Stop Docker containers
+        if: always()
+        run: |
+          cd deployment/docker_compose
+          docker compose -f docker-compose.dev.yml -p onyx-stack down -v

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

@@ -9,6 +9,10 @@ on:
     - cron: "0 16 * * *"
 
 env:
+  # AWS
+  AWS_ACCESS_KEY_ID_DAILY_CONNECTOR_TESTS: ${{ secrets.AWS_ACCESS_KEY_ID_DAILY_CONNECTOR_TESTS }}
+  AWS_SECRET_ACCESS_KEY_DAILY_CONNECTOR_TESTS: ${{ secrets.AWS_SECRET_ACCESS_KEY_DAILY_CONNECTOR_TESTS }}
+  
   # Confluence
   CONFLUENCE_TEST_SPACE_URL: ${{ secrets.CONFLUENCE_TEST_SPACE_URL }}
   CONFLUENCE_TEST_SPACE: ${{ secrets.CONFLUENCE_TEST_SPACE }}

.vscode/launch.template.jsonc

@@ -6,396 +6,419 @@
     // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
     "version": "0.2.0",
     "compounds": [
-		{
-			// Dummy entry used to label the group
-			"name": "--- Compound ---",
-		  	"configurations": [
-		  		"--- Individual ---"
-		  	],
-			"presentation": {
-				 "group": "1",
-			 }
-		},
-        {
-            "name": "Run All Onyx Services",
-            "configurations": [
-                "Web Server",
-                "Model Server",
-                "API Server",
-                "Slack Bot",
-		  		"Celery primary", 
-		  		"Celery light", 
-		  		"Celery heavy", 
-		  		"Celery indexing", 
-		  		"Celery beat",
-                "Celery monitoring",
-            ],
-			"presentation": {
-				 "group": "1",
-			 }
-        },
-		{
-			"name": "Web / Model / API",
-		  	"configurations": [
-		  		"Web Server", 
-		  		"Model Server", 
-		  		"API Server",
-		  	],
-			"presentation": {
-				 "group": "1",
-			 }
-		},
-		{
-			"name": "Celery (all)",
-		  	"configurations": [
-		  		"Celery primary", 
-		  		"Celery light", 
-		  		"Celery heavy", 
-		  		"Celery indexing", 
-		  		"Celery beat",
-                "Celery monitoring",
-		  	],
-			"presentation": {
-				 "group": "1",
-			 }
-		}
+      {
+        // Dummy entry used to label the group
+        "name": "--- Compound ---",
+        "configurations": ["--- Individual ---"],
+        "presentation": {
+          "group": "1"
+        }
+      },
+      {
+        "name": "Run All Onyx Services",
+        "configurations": [
+          "Web Server",
+          "Model Server",
+          "API Server",
+          "Slack Bot",
+          "Celery primary",
+          "Celery light",
+          "Celery heavy",
+          "Celery indexing",
+          "Celery user files indexing",
+          "Celery beat",
+          "Celery monitoring"
+        ],
+        "presentation": {
+          "group": "1"
+        }
+      },
+      {
+        "name": "Web / Model / API",
+        "configurations": ["Web Server", "Model Server", "API Server"],
+        "presentation": {
+          "group": "1"
+        }
+      },
+      {
+        "name": "Celery (all)",
+        "configurations": [
+          "Celery primary",
+          "Celery light",
+          "Celery heavy",
+          "Celery indexing",
+          "Celery user files indexing",
+          "Celery beat",
+          "Celery monitoring"
+        ],
+        "presentation": {
+          "group": "1"
+        }
+      }
     ],
     "configurations": [
-		{
-	    	// Dummy entry used to label the group
-			"name": "--- Individual ---",
-			"type": "node",
-			"request": "launch",
-			"presentation": {
-				"group": "2",
-				"order": 0
-			}
-		},
-        {
-            "name": "Web Server",
-            "type": "node",
-            "request": "launch",
-            "cwd": "${workspaceRoot}/web",
-            "runtimeExecutable": "npm",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "runtimeArgs": [
-                "run", "dev"
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "console": "integratedTerminal",
-            "consoleTitle": "Web Server Console"
+      {
+        // Dummy entry used to label the group
+        "name": "--- Individual ---",
+        "type": "node",
+        "request": "launch",
+        "presentation": {
+          "group": "2",
+          "order": 0
+        }
+      },
+      {
+        "name": "Web Server",
+        "type": "node",
+        "request": "launch",
+        "cwd": "${workspaceRoot}/web",
+        "runtimeExecutable": "npm",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "runtimeArgs": ["run", "dev"],
+        "presentation": {
+          "group": "2"
         },
-        {
-            "name": "Model Server",
-            "consoleName": "Model Server",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "uvicorn",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_LEVEL": "DEBUG",
-                "PYTHONUNBUFFERED": "1"
-            },
-            "args": [
-                "model_server.main:app",
-                "--reload",
-                "--port",
-                "9000"
-            ],
-            "presentation": {
-				 "group": "2",
-			},
-            "consoleTitle": "Model Server Console"
+        "console": "integratedTerminal",
+        "consoleTitle": "Web Server Console"
+      },
+      {
+        "name": "Model Server",
+        "consoleName": "Model Server",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "uvicorn",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1"
         },
-        {
-            "name": "API Server",
-            "consoleName": "API Server",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "uvicorn",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_DANSWER_MODEL_INTERACTIONS": "True",
-                "LOG_LEVEL": "DEBUG",
-                "PYTHONUNBUFFERED": "1"
-            },
-            "args": [
-                "onyx.main:app",
-                "--reload",
-                "--port",
-                "8080"
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "API Server Console"
+        "args": ["model_server.main:app", "--reload", "--port", "9000"],
+        "presentation": {
+          "group": "2"
         },
-        // For the listener to access the Slack API,
-        // DANSWER_BOT_SLACK_APP_TOKEN & DANSWER_BOT_SLACK_BOT_TOKEN need to be set in .env file located in the root of the project
-        {
-            "name": "Slack Bot",
-            "consoleName": "Slack Bot",
-            "type": "debugpy",
-            "request": "launch",
-            "program": "onyx/onyxbot/slack/listener.py",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_LEVEL": "DEBUG",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
-            "presentation": {
-				 "group": "2",
-			},
-            "consoleTitle": "Slack Bot Console"
+        "consoleTitle": "Model Server Console"
+      },
+      {
+        "name": "API Server",
+        "consoleName": "API Server",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "uvicorn",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_DANSWER_MODEL_INTERACTIONS": "True",
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1"
         },
-        {
-            "name": "Celery primary",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "celery",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_LEVEL": "INFO",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
-            "args": [
-                "-A",
-                "onyx.background.celery.versioned_apps.primary",
-                "worker",
-                "--pool=threads",
-                "--concurrency=4",
-                "--prefetch-multiplier=1",
-                "--loglevel=INFO",
-                "--hostname=primary@%n",
-                "-Q",
-                "celery",
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "Celery primary Console"
+        "args": ["onyx.main:app", "--reload", "--port", "8080"],
+        "presentation": {
+          "group": "2"
         },
-        {
-            "name": "Celery light",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "celery",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_LEVEL": "INFO",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
-            "args": [
-                "-A",
-                "onyx.background.celery.versioned_apps.light",
-                "worker",
-                "--pool=threads",
-                "--concurrency=64",
-                "--prefetch-multiplier=8",
-                "--loglevel=INFO",
-                "--hostname=light@%n",
-                "-Q",
-                "vespa_metadata_sync,connector_deletion,doc_permissions_upsert,checkpoint_cleanup",
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "Celery light Console"
+        "consoleTitle": "API Server Console"
+      },
+      // For the listener to access the Slack API,
+      // DANSWER_BOT_SLACK_APP_TOKEN & DANSWER_BOT_SLACK_BOT_TOKEN need to be set in .env file located in the root of the project
+      {
+        "name": "Slack Bot",
+        "consoleName": "Slack Bot",
+        "type": "debugpy",
+        "request": "launch",
+        "program": "onyx/onyxbot/slack/listener.py",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
         },
-        {
-            "name": "Celery heavy",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "celery",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_LEVEL": "INFO",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
-            "args": [
-                "-A",
-                "onyx.background.celery.versioned_apps.heavy",
-                "worker",
-                "--pool=threads",
-                "--concurrency=4",
-                "--prefetch-multiplier=1",
-                "--loglevel=INFO",
-                "--hostname=heavy@%n",
-                "-Q",
-                "connector_pruning,connector_doc_permissions_sync,connector_external_group_sync",
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "Celery heavy Console"
+        "presentation": {
+          "group": "2"
         },
-        {
-            "name": "Celery indexing",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "celery",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "ENABLE_MULTIPASS_INDEXING": "false",
-                "LOG_LEVEL": "DEBUG",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
-            "args": [
-                "-A",
-                "onyx.background.celery.versioned_apps.indexing",
-                "worker",
-                "--pool=threads",
-                "--concurrency=1",
-                "--prefetch-multiplier=1",
-                "--loglevel=INFO",
-                "--hostname=indexing@%n",
-                "-Q",
-                "connector_indexing",
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "Celery indexing Console"
+        "consoleTitle": "Slack Bot Console"
+      },
+      {
+        "name": "Celery primary",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "celery",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "INFO",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
         },
-        {
-            "name": "Celery monitoring",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "celery",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {},
-            "args": [
-                "-A",
-                "onyx.background.celery.versioned_apps.monitoring",
-                "worker",
-                "--pool=solo",
-                "--concurrency=1",
-                "--prefetch-multiplier=1",
-                "--loglevel=INFO",
-                "--hostname=monitoring@%n",
-                "-Q",
-                "monitoring",
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "Celery monitoring Console"
+        "args": [
+          "-A",
+          "onyx.background.celery.versioned_apps.primary",
+          "worker",
+          "--pool=threads",
+          "--concurrency=4",
+          "--prefetch-multiplier=1",
+          "--loglevel=INFO",
+          "--hostname=primary@%n",
+          "-Q",
+          "celery"
+        ],
+        "presentation": {
+          "group": "2"
         },
-        {
-            "name": "Celery beat",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "celery",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_LEVEL": "DEBUG",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
-            "args": [
-                "-A",
-                "onyx.background.celery.versioned_apps.beat",
-                "beat",
-                "--loglevel=INFO",
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "Celery beat Console"
+        "consoleTitle": "Celery primary Console"
+      },
+      {
+        "name": "Celery light",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "celery",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "INFO",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
         },
-        {
-            "name": "Pytest",
-            "consoleName": "Pytest",
-            "type": "debugpy",
-            "request": "launch",
-            "module": "pytest",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_LEVEL": "DEBUG",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
-            "args": [
-                "-v"
-                // Specify a sepcific module/test to run or provide nothing to run all tests
-                //"tests/unit/onyx/llm/answering/test_prune_and_merge.py"
-            ],
-            "presentation": {
-				 "group": "2",
-			 },
-            "consoleTitle": "Pytest Console"
+        "args": [
+          "-A",
+          "onyx.background.celery.versioned_apps.light",
+          "worker",
+          "--pool=threads",
+          "--concurrency=64",
+          "--prefetch-multiplier=8",
+          "--loglevel=INFO",
+          "--hostname=light@%n",
+          "-Q",
+          "vespa_metadata_sync,connector_deletion,doc_permissions_upsert"
+        ],
+        "presentation": {
+          "group": "2"
         },
-		{
-	    	// Dummy entry used to label the group
-			"name": "--- Tasks ---",
-			"type": "node",
-			"request": "launch",
-			"presentation": {
-				"group": "3",
-				"order": 0
-			}
-		},
-        {
-            "name": "Clear and Restart External Volumes and Containers",
-            "type": "node",
-            "request": "launch",
-            "runtimeExecutable": "bash",
-            "runtimeArgs": ["${workspaceFolder}/backend/scripts/restart_containers.sh"],
-            "cwd": "${workspaceFolder}",
-            "console": "integratedTerminal",
-            "stopOnEntry": true,
-            "presentation": {
-				 "group": "3",
-			 },
+        "consoleTitle": "Celery light Console"
+      },
+      {
+        "name": "Celery heavy",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "celery",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "INFO",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
         },
-        {
-	        // Celery jobs launched through a single background script (legacy)
-	        // Recommend using the "Celery (all)" compound launch instead.
-            "name": "Background Jobs",
-            "consoleName": "Background Jobs",
-            "type": "debugpy",
-            "request": "launch",
-            "program": "scripts/dev_run_background_jobs.py",
-            "cwd": "${workspaceFolder}/backend",
-            "envFile": "${workspaceFolder}/.vscode/.env",
-            "env": {
-                "LOG_DANSWER_MODEL_INTERACTIONS": "True",
-                "LOG_LEVEL": "DEBUG",
-                "PYTHONUNBUFFERED": "1",
-                "PYTHONPATH": "."
-            },
+        "args": [
+          "-A",
+          "onyx.background.celery.versioned_apps.heavy",
+          "worker",
+          "--pool=threads",
+          "--concurrency=4",
+          "--prefetch-multiplier=1",
+          "--loglevel=INFO",
+          "--hostname=heavy@%n",
+          "-Q",
+          "connector_pruning,connector_doc_permissions_sync,connector_external_group_sync"
+        ],
+        "presentation": {
+          "group": "2"
         },
-        {
-            "name": "Install Python Requirements",
-            "type": "node",
-            "request": "launch",
-            "runtimeExecutable": "bash",
-            "runtimeArgs": [
-                "-c",
-                "pip install -r backend/requirements/default.txt && pip install -r backend/requirements/dev.txt && pip install -r backend/requirements/ee.txt && pip install -r backend/requirements/model_server.txt"
-            ],
-            "cwd": "${workspaceFolder}",
-            "console": "integratedTerminal",
-            "presentation": {
-                 "group": "3"
-            }
+        "consoleTitle": "Celery heavy Console"
+      },
+      {
+        "name": "Celery indexing",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "celery",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "ENABLE_MULTIPASS_INDEXING": "false",
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
         },
+        "args": [
+          "-A",
+          "onyx.background.celery.versioned_apps.indexing",
+          "worker",
+          "--pool=threads",
+          "--concurrency=1",
+          "--prefetch-multiplier=1",
+          "--loglevel=INFO",
+          "--hostname=indexing@%n",
+          "-Q",
+          "connector_indexing"
+        ],
+        "presentation": {
+          "group": "2"
+        },
+        "consoleTitle": "Celery indexing Console"
+      },
+      {
+        "name": "Celery monitoring",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "celery",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {},
+        "args": [
+          "-A",
+          "onyx.background.celery.versioned_apps.monitoring",
+          "worker",
+          "--pool=solo",
+          "--concurrency=1",
+          "--prefetch-multiplier=1",
+          "--loglevel=INFO",
+          "--hostname=monitoring@%n",
+          "-Q",
+          "monitoring"
+        ],
+        "presentation": {
+          "group": "2"
+        },
+        "consoleTitle": "Celery monitoring Console"
+      },
+      {
+        "name": "Celery beat",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "celery",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
+        },
+        "args": [
+          "-A",
+          "onyx.background.celery.versioned_apps.beat",
+          "beat",
+          "--loglevel=INFO"
+        ],
+        "presentation": {
+          "group": "2"
+        },
+        "consoleTitle": "Celery beat Console"
+      },
+      {
+        "name": "Celery user files indexing",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "celery",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
+        },
+        "args": [
+          "-A",
+          "onyx.background.celery.versioned_apps.indexing",
+          "worker",
+          "--pool=threads",
+          "--concurrency=1",
+          "--prefetch-multiplier=1",
+          "--loglevel=INFO",
+          "--hostname=user_files_indexing@%n",
+          "-Q",
+          "user_files_indexing"
+        ],
+        "presentation": {
+          "group": "2"
+        },
+        "consoleTitle": "Celery user files indexing Console"
+      },
+      {
+        "name": "Pytest",
+        "consoleName": "Pytest",
+        "type": "debugpy",
+        "request": "launch",
+        "module": "pytest",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
+        },
+        "args": [
+          "-v"
+          // Specify a sepcific module/test to run or provide nothing to run all tests
+          //"tests/unit/onyx/llm/answering/test_prune_and_merge.py"
+        ],
+        "presentation": {
+          "group": "2"
+        },
+        "consoleTitle": "Pytest Console"
+      },
+      {
+        // Dummy entry used to label the group
+        "name": "--- Tasks ---",
+        "type": "node",
+        "request": "launch",
+        "presentation": {
+          "group": "3",
+          "order": 0
+        }
+      },
+      {
+        "name": "Clear and Restart External Volumes and Containers",
+        "type": "node",
+        "request": "launch",
+        "runtimeExecutable": "bash",
+        "runtimeArgs": [
+          "${workspaceFolder}/backend/scripts/restart_containers.sh"
+        ],
+        "cwd": "${workspaceFolder}",
+        "console": "integratedTerminal",
+        "stopOnEntry": true,
+        "presentation": {
+          "group": "3"
+        }
+      },
+      {
+        // Celery jobs launched through a single background script (legacy)
+        // Recommend using the "Celery (all)" compound launch instead.
+        "name": "Background Jobs",
+        "consoleName": "Background Jobs",
+        "type": "debugpy",
+        "request": "launch",
+        "program": "scripts/dev_run_background_jobs.py",
+        "cwd": "${workspaceFolder}/backend",
+        "envFile": "${workspaceFolder}/.vscode/.env",
+        "env": {
+          "LOG_DANSWER_MODEL_INTERACTIONS": "True",
+          "LOG_LEVEL": "DEBUG",
+          "PYTHONUNBUFFERED": "1",
+          "PYTHONPATH": "."
+        }
+      },
+      {
+        "name": "Install Python Requirements",
+        "type": "node",
+        "request": "launch",
+        "runtimeExecutable": "bash",
+        "runtimeArgs": [
+          "-c",
+          "pip install -r backend/requirements/default.txt && pip install -r backend/requirements/dev.txt && pip install -r backend/requirements/ee.txt && pip install -r backend/requirements/model_server.txt"
+        ],
+        "cwd": "${workspaceFolder}",
+        "console": "integratedTerminal",
+        "presentation": {
+          "group": "3"
+        }
+      },
+      {
+        "name": "Debug React Web App in Chrome",
+        "type": "chrome",
+        "request": "launch",
+        "url": "http://localhost:3000",
+        "webRoot": "${workspaceFolder}/web"
+      }
     ]
-}
+  }
+  

backend/alembic/versions/8e1ac4f39a9f_enable_contextual_retrieval.py

@@ -0,0 +1,50 @@
+"""enable contextual retrieval
+
+Revision ID: 8e1ac4f39a9f
+Revises: 9aadf32dfeb4
+Create Date: 2024-12-20 13:29:09.918661
+
+"""
+from alembic import op
+import sqlalchemy as sa
+
+
+# revision identifiers, used by Alembic.
+revision = "8e1ac4f39a9f"
+down_revision = "9aadf32dfeb4"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    op.add_column(
+        "search_settings",
+        sa.Column(
+            "enable_contextual_rag",
+            sa.Boolean(),
+            nullable=False,
+            server_default="false",
+        ),
+    )
+    op.add_column(
+        "search_settings",
+        sa.Column(
+            "contextual_rag_llm_name",
+            sa.String(),
+            nullable=True,
+        ),
+    )
+    op.add_column(
+        "search_settings",
+        sa.Column(
+            "contextual_rag_llm_provider",
+            sa.String(),
+            nullable=True,
+        ),
+    )
+
+
+def downgrade() -> None:
+    op.drop_column("search_settings", "enable_contextual_rag")
+    op.drop_column("search_settings", "contextual_rag_llm_name")
+    op.drop_column("search_settings", "contextual_rag_llm_provider")

backend/alembic/versions/9aadf32dfeb4_add_user_files.py

@@ -0,0 +1,113 @@
+"""add user files
+
+Revision ID: 9aadf32dfeb4
+Revises: 3781a5eb12cb
+Create Date: 2025-01-26 16:08:21.551022
+
+"""
+from alembic import op
+import sqlalchemy as sa
+import datetime
+
+
+# revision identifiers, used by Alembic.
+revision = "9aadf32dfeb4"
+down_revision = "3781a5eb12cb"
+branch_labels = None
+depends_on = None
+
+
+def upgrade() -> None:
+    # Create user_folder table without parent_id
+    op.create_table(
+        "user_folder",
+        sa.Column("id", sa.Integer(), primary_key=True, autoincrement=True),
+        sa.Column("user_id", sa.UUID(), sa.ForeignKey("user.id"), nullable=True),
+        sa.Column("name", sa.String(length=255), nullable=True),
+        sa.Column("description", sa.String(length=255), nullable=True),
+        sa.Column("display_priority", sa.Integer(), nullable=True, default=0),
+        sa.Column(
+            "created_at", sa.DateTime(timezone=True), server_default=sa.func.now()
+        ),
+    )
+
+    # Create user_file table with folder_id instead of parent_folder_id
+    op.create_table(
+        "user_file",
+        sa.Column("id", sa.Integer(), primary_key=True, autoincrement=True),
+        sa.Column("user_id", sa.UUID(), sa.ForeignKey("user.id"), nullable=True),
+        sa.Column(
+            "folder_id",
+            sa.Integer(),
+            sa.ForeignKey("user_folder.id"),
+            nullable=True,
+        ),
+        sa.Column("link_url", sa.String(), nullable=True),
+        sa.Column("token_count", sa.Integer(), nullable=True),
+        sa.Column("file_type", sa.String(), nullable=True),
+        sa.Column("file_id", sa.String(length=255), nullable=False),
+        sa.Column("document_id", sa.String(length=255), nullable=False),
+        sa.Column("name", sa.String(length=255), nullable=False),
+        sa.Column(
+            "created_at",
+            sa.DateTime(),
+            default=datetime.datetime.utcnow,
+        ),
+        sa.Column(
+            "cc_pair_id",
+            sa.Integer(),
+            sa.ForeignKey("connector_credential_pair.id"),
+            nullable=True,
+            unique=True,
+        ),
+    )
+
+    # Create persona__user_file table
+    op.create_table(
+        "persona__user_file",
+        sa.Column(
+            "persona_id", sa.Integer(), sa.ForeignKey("persona.id"), primary_key=True
+        ),
+        sa.Column(
+            "user_file_id",
+            sa.Integer(),
+            sa.ForeignKey("user_file.id"),
+            primary_key=True,
+        ),
+    )
+
+    # Create persona__user_folder table
+    op.create_table(
+        "persona__user_folder",
+        sa.Column(
+            "persona_id", sa.Integer(), sa.ForeignKey("persona.id"), primary_key=True
+        ),
+        sa.Column(
+            "user_folder_id",
+            sa.Integer(),
+            sa.ForeignKey("user_folder.id"),
+            primary_key=True,
+        ),
+    )
+
+    op.add_column(
+        "connector_credential_pair",
+        sa.Column("is_user_file", sa.Boolean(), nullable=True, default=False),
+    )
+
+    # Update existing records to have is_user_file=False instead of NULL
+    op.execute(
+        "UPDATE connector_credential_pair SET is_user_file = FALSE WHERE is_user_file IS NULL"
+    )
+
+
+def downgrade() -> None:
+    # Drop the persona__user_folder table
+    op.drop_table("persona__user_folder")
+    # Drop the persona__user_file table
+    op.drop_table("persona__user_file")
+    # Drop the user_file table
+    op.drop_table("user_file")
+    # Drop the user_folder table
+    op.drop_table("user_folder")
+    op.drop_column("connector_credential_pair", "is_user_file")

backend/ee/onyx/access/access.py

@@ -93,12 +93,12 @@ def _get_access_for_documents(
         )
 
         # To avoid collisions of group namings between connectors, they need to be prefixed
-        access_map[document_id] = DocumentAccess(
-            user_emails=non_ee_access.user_emails,
-            user_groups=set(user_group_info.get(document_id, [])),
+        access_map[document_id] = DocumentAccess.build(
+            user_emails=list(non_ee_access.user_emails),
+            user_groups=user_group_info.get(document_id, []),
             is_public=is_public_anywhere,
-            external_user_emails=ext_u_emails,
-            external_user_group_ids=ext_u_groups,
+            external_user_emails=list(ext_u_emails),
+            external_user_group_ids=list(ext_u_groups),
         )
     return access_map
 

backend/ee/onyx/chat/process_message.py

@@ -2,7 +2,6 @@ from ee.onyx.server.query_and_chat.models import OneShotQAResponse
 from onyx.chat.models import AllCitations
 from onyx.chat.models import LLMRelevanceFilterResponse
 from onyx.chat.models import OnyxAnswerPiece
-from onyx.chat.models import OnyxContexts
 from onyx.chat.models import QADocsResponse
 from onyx.chat.models import StreamingError
 from onyx.chat.process_message import ChatPacketStream
@@ -32,8 +31,6 @@ def gather_stream_for_answer_api(
             response.llm_selected_doc_indices = packet.llm_selected_doc_indices
         elif isinstance(packet, AllCitations):
             response.citations = packet.citations
-        elif isinstance(packet, OnyxContexts):
-            response.contexts = packet
 
     if answer:
         response.answer = answer

backend/ee/onyx/configs/app_configs.py

@@ -25,6 +25,10 @@ SAML_CONF_DIR = os.environ.get("SAML_CONF_DIR") or "/app/ee/onyx/configs/saml_co
 #####
 # Auto Permission Sync
 #####
+DEFAULT_PERMISSION_DOC_SYNC_FREQUENCY = int(
+    os.environ.get("DEFAULT_PERMISSION_DOC_SYNC_FREQUENCY") or 5 * 60
+)
+
 # In seconds, default is 5 minutes
 CONFLUENCE_PERMISSION_GROUP_SYNC_FREQUENCY = int(
     os.environ.get("CONFLUENCE_PERMISSION_GROUP_SYNC_FREQUENCY") or 5 * 60
@@ -39,6 +43,7 @@ CONFLUENCE_ANONYMOUS_ACCESS_IS_PUBLIC = (
 CONFLUENCE_PERMISSION_DOC_SYNC_FREQUENCY = int(
     os.environ.get("CONFLUENCE_PERMISSION_DOC_SYNC_FREQUENCY") or 5 * 60
 )
+
 NUM_PERMISSION_WORKERS = int(os.environ.get("NUM_PERMISSION_WORKERS") or 2)
 
 
@@ -72,6 +77,13 @@ OAUTH_GOOGLE_DRIVE_CLIENT_SECRET = os.environ.get(
     "OAUTH_GOOGLE_DRIVE_CLIENT_SECRET", ""
 )
 
+GOOGLE_DRIVE_PERMISSION_GROUP_SYNC_FREQUENCY = int(
+    os.environ.get("GOOGLE_DRIVE_PERMISSION_GROUP_SYNC_FREQUENCY") or 5 * 60
+)
+
+SLACK_PERMISSION_DOC_SYNC_FREQUENCY = int(
+    os.environ.get("SLACK_PERMISSION_DOC_SYNC_FREQUENCY") or 5 * 60
+)
 
 # The posthog client does not accept empty API keys or hosts however it fails silently
 # when the capture is called. These defaults prevent Posthog issues from breaking the Onyx app

backend/ee/onyx/external_permissions/sync_params.py

@@ -3,6 +3,8 @@ from collections.abc import Generator
 
 from ee.onyx.configs.app_configs import CONFLUENCE_PERMISSION_DOC_SYNC_FREQUENCY
 from ee.onyx.configs.app_configs import CONFLUENCE_PERMISSION_GROUP_SYNC_FREQUENCY
+from ee.onyx.configs.app_configs import GOOGLE_DRIVE_PERMISSION_GROUP_SYNC_FREQUENCY
+from ee.onyx.configs.app_configs import SLACK_PERMISSION_DOC_SYNC_FREQUENCY
 from ee.onyx.db.external_perm import ExternalUserGroup
 from ee.onyx.external_permissions.confluence.doc_sync import confluence_doc_sync
 from ee.onyx.external_permissions.confluence.group_sync import confluence_group_sync
@@ -66,13 +68,13 @@ GROUP_PERMISSIONS_IS_CC_PAIR_AGNOSTIC: set[DocumentSource] = {
 DOC_PERMISSION_SYNC_PERIODS: dict[DocumentSource, int] = {
     # Polling is not supported so we fetch all doc permissions every 5 minutes
     DocumentSource.CONFLUENCE: CONFLUENCE_PERMISSION_DOC_SYNC_FREQUENCY,
-    DocumentSource.SLACK: 5 * 60,
+    DocumentSource.SLACK: SLACK_PERMISSION_DOC_SYNC_FREQUENCY,
 }
 
 # If nothing is specified here, we run the doc_sync every time the celery beat runs
 EXTERNAL_GROUP_SYNC_PERIODS: dict[DocumentSource, int] = {
     # Polling is not supported so we fetch all group permissions every 30 minutes
-    DocumentSource.GOOGLE_DRIVE: 5 * 60,
+    DocumentSource.GOOGLE_DRIVE: GOOGLE_DRIVE_PERMISSION_GROUP_SYNC_FREQUENCY,
     DocumentSource.CONFLUENCE: CONFLUENCE_PERMISSION_GROUP_SYNC_FREQUENCY,
 }
 

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

@@ -44,7 +44,7 @@ async def _get_tenant_id_from_request(
     Attempt to extract tenant_id from:
     1) The API key header
     2) The Redis-based token (stored in Cookie: fastapiusersauth)
-    3)  Reset token cookie
+    3) The anonymous user cookie
     Fallback: POSTGRES_DEFAULT_SCHEMA
     """
     # Check for API key
@@ -52,41 +52,55 @@ async def _get_tenant_id_from_request(
     if tenant_id is not None:
         return tenant_id
 
-    # Check for anonymous user cookie
-    anonymous_user_cookie = request.cookies.get(ANONYMOUS_USER_COOKIE_NAME)
-    if anonymous_user_cookie:
-        try:
-            anonymous_user_data = decode_anonymous_user_jwt_token(anonymous_user_cookie)
-            return anonymous_user_data.get("tenant_id", POSTGRES_DEFAULT_SCHEMA)
-        except Exception as e:
-            logger.error(f"Error decoding anonymous user cookie: {str(e)}")
-            # Continue and attempt to authenticate
-
     try:
         # Look up token data in Redis
 
         token_data = await retrieve_auth_token_data_from_redis(request)
 
-        if not token_data:
-            logger.debug(
-                "Token data not found or expired in Redis, defaulting to POSTGRES_DEFAULT_SCHEMA"
+        if token_data:
+            tenant_id_from_payload = token_data.get(
+                "tenant_id", POSTGRES_DEFAULT_SCHEMA
             )
-            # Return POSTGRES_DEFAULT_SCHEMA, so non-authenticated requests are sent to the default schema
-            # The CURRENT_TENANT_ID_CONTEXTVAR is initialized with POSTGRES_DEFAULT_SCHEMA,
-            # so we maintain consistency by returning it here when no valid tenant is found.
-            return POSTGRES_DEFAULT_SCHEMA
 
-        tenant_id_from_payload = token_data.get("tenant_id", POSTGRES_DEFAULT_SCHEMA)
+            tenant_id = (
+                str(tenant_id_from_payload)
+                if tenant_id_from_payload is not None
+                else None
+            )
 
-        # Since token_data.get() can return None, ensure we have a string
-        tenant_id = (
-            str(tenant_id_from_payload)
-            if tenant_id_from_payload is not None
-            else POSTGRES_DEFAULT_SCHEMA
+            if tenant_id and not is_valid_schema_name(tenant_id):
+                raise HTTPException(status_code=400, detail="Invalid tenant ID format")
+
+        # Check for anonymous user cookie
+        anonymous_user_cookie = request.cookies.get(ANONYMOUS_USER_COOKIE_NAME)
+        if anonymous_user_cookie:
+            try:
+                anonymous_user_data = decode_anonymous_user_jwt_token(
+                    anonymous_user_cookie
+                )
+                tenant_id = anonymous_user_data.get(
+                    "tenant_id", POSTGRES_DEFAULT_SCHEMA
+                )
+
+                if not tenant_id or not is_valid_schema_name(tenant_id):
+                    raise HTTPException(
+                        status_code=400, detail="Invalid tenant ID format"
+                    )
+
+                return tenant_id
+
+            except Exception as e:
+                logger.error(f"Error decoding anonymous user cookie: {str(e)}")
+                # Continue and attempt to authenticate
+
+        logger.debug(
+            "Token data not found or expired in Redis, defaulting to POSTGRES_DEFAULT_SCHEMA"
         )
 
-        if not is_valid_schema_name(tenant_id):
-            raise HTTPException(status_code=400, detail="Invalid tenant ID format")
+        # Return POSTGRES_DEFAULT_SCHEMA, so non-authenticated requests are sent to the default schema
+        # The CURRENT_TENANT_ID_CONTEXTVAR is initialized with POSTGRES_DEFAULT_SCHEMA,
+        # so we maintain consistency by returning it here when no valid tenant is found.
+        return POSTGRES_DEFAULT_SCHEMA
 
     except Exception as e:
         logger.error(f"Unexpected error in _get_tenant_id_from_request: {str(e)}")

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

@@ -14,7 +14,6 @@ from ee.onyx.server.query_and_chat.models import (
     BasicCreateChatMessageWithHistoryRequest,
 )
 from ee.onyx.server.query_and_chat.models import ChatBasicResponse
-from ee.onyx.server.query_and_chat.models import SimpleDoc
 from onyx.auth.users import current_user
 from onyx.chat.chat_utils import combine_message_thread
 from onyx.chat.chat_utils import create_chat_chain
@@ -56,25 +55,6 @@ logger = setup_logger()
 router = APIRouter(prefix="/chat")
 
 
-def _translate_doc_response_to_simple_doc(
-    doc_response: QADocsResponse,
-) -> list[SimpleDoc]:
-    return [
-        SimpleDoc(
-            id=doc.document_id,
-            semantic_identifier=doc.semantic_identifier,
-            link=doc.link,
-            blurb=doc.blurb,
-            match_highlights=[
-                highlight for highlight in doc.match_highlights if highlight
-            ],
-            source_type=doc.source_type,
-            metadata=doc.metadata,
-        )
-        for doc in doc_response.top_documents
-    ]
-
-
 def _get_final_context_doc_indices(
     final_context_docs: list[LlmDoc] | None,
     top_docs: list[SavedSearchDoc] | None,
@@ -111,9 +91,6 @@ def _convert_packet_stream_to_response(
         elif isinstance(packet, QADocsResponse):
             response.top_documents = packet.top_documents
 
-            # TODO: deprecate `simple_search_docs`
-            response.simple_search_docs = _translate_doc_response_to_simple_doc(packet)
-
             # This is a no-op if agent_sub_questions hasn't already been filled
             if packet.level is not None and packet.level_question_num is not None:
                 id = (packet.level, packet.level_question_num)

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

@@ -8,7 +8,6 @@ from pydantic import model_validator
 
 from ee.onyx.server.manage.models import StandardAnswer
 from onyx.chat.models import CitationInfo
-from onyx.chat.models import OnyxContexts
 from onyx.chat.models import PersonaOverrideConfig
 from onyx.chat.models import QADocsResponse
 from onyx.chat.models import SubQuestionIdentifier
@@ -164,8 +163,6 @@ class ChatBasicResponse(BaseModel):
     cited_documents: dict[int, str] | None = None
 
     # FOR BACKWARDS COMPATIBILITY
-    # TODO: deprecate both of these
-    simple_search_docs: list[SimpleDoc] | None = None
     llm_chunks_indices: list[int] | None = None
 
     # agentic fields
@@ -220,4 +217,3 @@ class OneShotQAResponse(BaseModel):
     llm_selected_doc_indices: list[int] | None = None
     error_msg: str | None = None
     chat_message_id: int | None = None
-    contexts: OnyxContexts | None = None

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

@@ -1,4 +1,5 @@
 import asyncio
+import concurrent.futures
 import logging
 import uuid
 
@@ -94,6 +95,7 @@ async def get_or_provision_tenant(
         # Notify control plane if we have created / assigned a new tenant
         if not DEV_MODE:
             await notify_control_plane(tenant_id, email, referral_source)
+
         return tenant_id
 
     except Exception as e:
@@ -505,8 +507,24 @@ async def setup_tenant(tenant_id: str) -> None:
     try:
         token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
 
-        # Run Alembic migrations
-        await asyncio.to_thread(run_alembic_migrations, tenant_id)
+        # Run Alembic migrations in a completely isolated way
+        # This function runs in a separate thread with its own event loop context
+        def isolated_migration_runner():
+            # Reset contextvar to prevent it from being shared with the parent thread
+            # This ensures no shared asyncio primitives between threads
+            token = CURRENT_TENANT_ID_CONTEXTVAR.set(tenant_id)
+            try:
+                # Run migrations in this isolated thread
+                run_alembic_migrations(tenant_id)
+            finally:
+                # Clean up the contextvar
+                CURRENT_TENANT_ID_CONTEXTVAR.reset(token)
+
+        # Use a dedicated ThreadPoolExecutor for complete isolation
+        # This prevents asyncio loop/lock sharing issues
+        with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
+            loop = asyncio.get_running_loop()
+            await loop.run_in_executor(executor, isolated_migration_runner)
 
         # Configure the tenant with default settings
         with get_session_with_tenant(tenant_id=tenant_id) as db_session:

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

@@ -70,6 +70,7 @@ def add_users_to_tenant(emails: list[str], tenant_id: str) -> None:
     """
     Add users to a tenant with proper transaction handling.
     Checks if users already have a tenant mapping to avoid duplicates.
+    If a user already has an active mapping to any tenant, the new mapping will be added as inactive.
     """
     with get_session_with_tenant(tenant_id=POSTGRES_DEFAULT_SCHEMA) as db_session:
         try:
@@ -88,9 +89,25 @@ def add_users_to_tenant(emails: list[str], tenant_id: str) -> None:
                     .first()
                 )
 
+                # If user already has an active mapping, add this one as inactive
                 if not existing_mapping:
-                    # Only add if mapping doesn't exist
-                    db_session.add(UserTenantMapping(email=email, tenant_id=tenant_id))
+                    # Check if the user already has an active mapping to any tenant
+                    has_active_mapping = (
+                        db_session.query(UserTenantMapping)
+                        .filter(
+                            UserTenantMapping.email == email,
+                            UserTenantMapping.active == True,  # noqa: E712
+                        )
+                        .first()
+                    )
+
+                    db_session.add(
+                        UserTenantMapping(
+                            email=email,
+                            tenant_id=tenant_id,
+                            active=False if has_active_mapping else True,
+                        )
+                    )
 
             # Commit the transaction
             db_session.commit()

backend/onyx/access/access.py

@@ -18,7 +18,7 @@ def _get_access_for_document(
         document_id=document_id,
     )
 
-    return DocumentAccess.build(
+    doc_access = DocumentAccess.build(
         user_emails=info[1] if info and info[1] else [],
         user_groups=[],
         external_user_emails=[],
@@ -26,6 +26,8 @@ def _get_access_for_document(
         is_public=info[2] if info else False,
     )
 
+    return doc_access
+
 
 def get_access_for_document(
     document_id: str,
@@ -38,12 +40,12 @@ def get_access_for_document(
 
 
 def get_null_document_access() -> DocumentAccess:
-    return DocumentAccess(
-        user_emails=set(),
-        user_groups=set(),
+    return DocumentAccess.build(
+        user_emails=[],
+        user_groups=[],
         is_public=False,
-        external_user_emails=set(),
-        external_user_group_ids=set(),
+        external_user_emails=[],
+        external_user_group_ids=[],
     )
 
 
@@ -55,19 +57,18 @@ def _get_access_for_documents(
         db_session=db_session,
         document_ids=document_ids,
     )
-    doc_access = {
-        document_id: DocumentAccess(
-            user_emails=set([email for email in user_emails if email]),
+    doc_access = {}
+    for document_id, user_emails, is_public in document_access_info:
+        doc_access[document_id] = DocumentAccess.build(
+            user_emails=[email for email in user_emails if email],
             # MIT version will wipe all groups and external groups on update
-            user_groups=set(),
+            user_groups=[],
             is_public=is_public,
-            external_user_emails=set(),
-            external_user_group_ids=set(),
+            external_user_emails=[],
+            external_user_group_ids=[],
         )
-        for document_id, user_emails, is_public in document_access_info
-    }
 
-    # Sometimes the document has not be indexed by the indexing job yet, in those cases
+    # Sometimes the document has not been indexed by the indexing job yet, in those cases
     # the document does not exist and so we use least permissive. Specifically the EE version
     # checks the MIT version permissions and creates a superset. This ensures that this flow
     # does not fail even if the Document has not yet been indexed.

backend/onyx/access/models.py

@@ -56,34 +56,46 @@ class DocExternalAccess:
         )
 
 
-@dataclass(frozen=True)
+@dataclass(frozen=True, init=False)
 class DocumentAccess(ExternalAccess):
     # User emails for Onyx users, None indicates admin
     user_emails: set[str | None]
+
     # Names of user groups associated with this document
     user_groups: set[str]
 
-    def to_acl(self) -> set[str]:
-        return set(
-            [
-                prefix_user_email(user_email)
-                for user_email in self.user_emails
-                if user_email
-            ]
-            + [prefix_user_group(group_name) for group_name in self.user_groups]
-            + [
-                prefix_user_email(user_email)
-                for user_email in self.external_user_emails
-            ]
-            + [
-                # The group names are already prefixed by the source type
-                # This adds an additional prefix of "external_group:"
-                prefix_external_group(group_name)
-                for group_name in self.external_user_group_ids
-            ]
-            + ([PUBLIC_DOC_PAT] if self.is_public else [])
+    external_user_emails: set[str]
+    external_user_group_ids: set[str]
+    is_public: bool
+
+    def __init__(self) -> None:
+        raise TypeError(
+            "Use `DocumentAccess.build(...)` instead of creating an instance directly."
         )
 
+    def to_acl(self) -> set[str]:
+        # the acl's emitted by this function are prefixed by type
+        # to get the native objects, access the member variables directly
+
+        acl_set: set[str] = set()
+        for user_email in self.user_emails:
+            if user_email:
+                acl_set.add(prefix_user_email(user_email))
+
+        for group_name in self.user_groups:
+            acl_set.add(prefix_user_group(group_name))
+
+        for external_user_email in self.external_user_emails:
+            acl_set.add(prefix_user_email(external_user_email))
+
+        for external_group_id in self.external_user_group_ids:
+            acl_set.add(prefix_external_group(external_group_id))
+
+        if self.is_public:
+            acl_set.add(PUBLIC_DOC_PAT)
+
+        return acl_set
+
     @classmethod
     def build(
         cls,
@@ -93,29 +105,32 @@ class DocumentAccess(ExternalAccess):
         external_user_group_ids: list[str],
         is_public: bool,
     ) -> "DocumentAccess":
-        return cls(
-            external_user_emails={
-                prefix_user_email(external_email)
-                for external_email in external_user_emails
-            },
-            external_user_group_ids={
-                prefix_external_group(external_group_id)
-                for external_group_id in external_user_group_ids
-            },
-            user_emails={
-                prefix_user_email(user_email)
-                for user_email in user_emails
-                if user_email
-            },
-            user_groups=set(user_groups),
-            is_public=is_public,
+        """Don't prefix incoming data wth acl type, prefix on read from to_acl!"""
+
+        obj = object.__new__(cls)
+        object.__setattr__(
+            obj, "user_emails", {user_email for user_email in user_emails if user_email}
         )
+        object.__setattr__(obj, "user_groups", set(user_groups))
+        object.__setattr__(
+            obj,
+            "external_user_emails",
+            {external_email for external_email in external_user_emails},
+        )
+        object.__setattr__(
+            obj,
+            "external_user_group_ids",
+            {external_group_id for external_group_id in external_user_group_ids},
+        )
+        object.__setattr__(obj, "is_public", is_public)
+
+        return obj
 
 
-default_public_access = DocumentAccess(
-    external_user_emails=set(),
-    external_user_group_ids=set(),
-    user_emails=set(),
-    user_groups=set(),
+default_public_access = DocumentAccess.build(
+    external_user_emails=[],
+    external_user_group_ids=[],
+    user_emails=[],
+    user_groups=[],
     is_public=True,
 )

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

@@ -7,7 +7,6 @@ from langgraph.types import StreamWriter
 
 from onyx.agents.agent_search.shared_graph_utils.utils import write_custom_event
 from onyx.chat.models import LlmDoc
-from onyx.chat.models import OnyxContext
 from onyx.chat.stream_processing.answer_response_handler import AnswerResponseHandler
 from onyx.chat.stream_processing.answer_response_handler import CitationResponseHandler
 from onyx.chat.stream_processing.answer_response_handler import (
@@ -24,7 +23,7 @@ def process_llm_stream(
     should_stream_answer: bool,
     writer: StreamWriter,
     final_search_results: list[LlmDoc] | None = None,
-    displayed_search_results: list[OnyxContext] | list[LlmDoc] | None = None,
+    displayed_search_results: list[LlmDoc] | None = None,
 ) -> AIMessageChunk:
     tool_call_chunk = AIMessageChunk(content="")
 

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

@@ -156,7 +156,6 @@ def generate_initial_answer(
     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,
         search_query_info=query_info,
         get_section_relevance=lambda: relevance_list,

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

@@ -183,7 +183,6 @@ def generate_validate_refined_answer(
     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,
         search_query_info=query_info,
         get_section_relevance=lambda: relevance_list,

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

@@ -57,7 +57,6 @@ def format_results(
         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,
             search_query_info=query_info,
             get_section_relevance=lambda: relevance_list,

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

@@ -13,9 +13,7 @@ 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,
-)
+from onyx.tools.tool_implementations.search.search_utils import section_to_llm_doc
 from onyx.tools.tool_implementations.search_like_tool_utils import (
     FINAL_CONTEXT_DOCUMENTS_ID,
 )
@@ -59,9 +57,7 @@ def basic_use_tool_response(
             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)
-                    )
+                    initial_search_results.append(section_to_llm_doc(section))
 
     new_tool_call_chunk = AIMessageChunk(content="")
     if not agent_config.behavior.skip_gen_ai_answer_generation:

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

@@ -321,8 +321,10 @@ def dispatch_separated(
     sep: str = DISPATCH_SEP_CHAR,
 ) -> list[BaseMessage_Content]:
     num = 1
+    accumulated_tokens = ""
     streamed_tokens: list[BaseMessage_Content] = []
     for token in tokens:
+        accumulated_tokens += cast(str, token.content)
         content = cast(str, token.content)
         if sep in content:
             sub_question_parts = content.split(sep)

backend/onyx/auth/users.py

@@ -360,7 +360,6 @@ class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]):
                 reason="Password must contain at least one special character from the following set: "
                 f"{PASSWORD_SPECIAL_CHARS}."
             )
-
         return
 
     async def oauth_callback(

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

@@ -1,6 +1,5 @@
 from datetime import timedelta
 from typing import Any
-from typing import cast
 
 from celery import Celery
 from celery import signals
@@ -10,12 +9,10 @@ from celery.utils.log import get_task_logger
 
 import onyx.background.celery.apps.app_base as app_base
 from onyx.background.celery.tasks.beat_schedule import CLOUD_BEAT_MULTIPLIER_DEFAULT
-from onyx.configs.constants import ONYX_CLOUD_REDIS_RUNTIME
-from onyx.configs.constants import ONYX_CLOUD_TENANT_ID
 from onyx.configs.constants import POSTGRES_CELERY_BEAT_APP_NAME
 from onyx.db.engine import get_all_tenant_ids
 from onyx.db.engine import SqlEngine
-from onyx.redis.redis_pool import get_redis_replica_client
+from onyx.server.runtime.onyx_runtime import OnyxRuntime
 from onyx.utils.variable_functionality import fetch_versioned_implementation
 from shared_configs.configs import IGNORED_SYNCING_TENANT_LIST
 from shared_configs.configs import MULTI_TENANT
@@ -141,8 +138,6 @@ class DynamicTenantScheduler(PersistentScheduler):
         """Only updates the actual beat schedule on the celery app when it changes"""
         do_update = False
 
-        r = get_redis_replica_client(tenant_id=ONYX_CLOUD_TENANT_ID)
-
         task_logger.debug("_try_updating_schedule starting")
 
         tenant_ids = get_all_tenant_ids()
@@ -152,16 +147,7 @@ class DynamicTenantScheduler(PersistentScheduler):
         current_schedule = self.schedule.items()
 
         # get potential new state
-        beat_multiplier = CLOUD_BEAT_MULTIPLIER_DEFAULT
-        beat_multiplier_raw = r.get(f"{ONYX_CLOUD_REDIS_RUNTIME}:beat_multiplier")
-        if beat_multiplier_raw is not None:
-            try:
-                beat_multiplier_bytes = cast(bytes, beat_multiplier_raw)
-                beat_multiplier = float(beat_multiplier_bytes.decode())
-            except ValueError:
-                task_logger.error(
-                    f"Invalid beat_multiplier value: {beat_multiplier_raw}"
-                )
+        beat_multiplier = OnyxRuntime.get_beat_multiplier()
 
         new_schedule = self._generate_schedule(tenant_ids, beat_multiplier)
 

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

@@ -111,6 +111,7 @@ celery_app.autodiscover_tasks(
         "onyx.background.celery.tasks.vespa",
         "onyx.background.celery.tasks.connector_deletion",
         "onyx.background.celery.tasks.doc_permission_syncing",
+        "onyx.background.celery.tasks.user_file_folder_sync",
         "onyx.background.celery.tasks.indexing",
         "onyx.background.celery.tasks.tenant_provisioning",
     ]

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

@@ -174,6 +174,9 @@ def on_worker_init(sender: Worker, **kwargs: Any) -> None:
                 f"search_settings={attempt.search_settings_id}"
             )
             logger.warning(failure_reason)
+            logger.exception(
+                f"Marking attempt {attempt.id} as canceled due to validation error 2"
+            )
             mark_attempt_canceled(attempt.id, db_session, failure_reason)
 
 
@@ -285,5 +288,6 @@ celery_app.autodiscover_tasks(
         "onyx.background.celery.tasks.shared",
         "onyx.background.celery.tasks.vespa",
         "onyx.background.celery.tasks.llm_model_update",
+        "onyx.background.celery.tasks.user_file_folder_sync",
     ]
 )

backend/onyx/background/celery/memory_monitoring.py

@@ -14,7 +14,7 @@ logger = setup_logger()
 # Only set up memory monitoring in container environment
 if is_running_in_container():
     # Set up a dedicated memory monitoring logger
-    MEMORY_LOG_DIR = "/var/log/persisted-logs/memory"
+    MEMORY_LOG_DIR = "/var/log/memory"
     MEMORY_LOG_FILE = os.path.join(MEMORY_LOG_DIR, "memory_usage.log")
     MEMORY_LOG_MAX_BYTES = 10 * 1024 * 1024  # 10MB
     MEMORY_LOG_BACKUP_COUNT = 5  # Keep 5 backup files

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

@@ -21,6 +21,7 @@ BEAT_EXPIRES_DEFAULT = 15 * 60  # 15 minutes (in seconds)
 # we have a better implementation (backpressure, etc)
 # Note that DynamicTenantScheduler can adjust the runtime value for this via Redis
 CLOUD_BEAT_MULTIPLIER_DEFAULT = 8.0
+CLOUD_DOC_PERMISSION_SYNC_MULTIPLIER_DEFAULT = 1.0
 
 # tasks that run in either self-hosted on cloud
 beat_task_templates: list[dict] = []
@@ -63,6 +64,15 @@ beat_task_templates.extend(
                 "expires": BEAT_EXPIRES_DEFAULT,
             },
         },
+        {
+            "name": "check-for-user-file-folder-sync",
+            "task": OnyxCeleryTask.CHECK_FOR_USER_FILE_FOLDER_SYNC,
+            "schedule": timedelta(seconds=30),
+            "options": {
+                "priority": OnyxCeleryPriority.MEDIUM,
+                "expires": BEAT_EXPIRES_DEFAULT,
+            },
+        },
         {
             "name": "check-for-pruning",
             "task": OnyxCeleryTask.CHECK_FOR_PRUNING,

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

@@ -389,6 +389,8 @@ def monitor_connector_deletion_taskset(
             db_session=db_session,
             cc_pair_id=cc_pair_id,
         )
+        credential_id_to_delete: int | None = None
+        connector_id_to_delete: int | None = None
         if not cc_pair:
             task_logger.warning(
                 f"Connector deletion - cc_pair not found: cc_pair={cc_pair_id}"
@@ -443,26 +445,35 @@ def monitor_connector_deletion_taskset(
                 db_session=db_session,
             )
 
+            # Store IDs before potentially expiring cc_pair
+            connector_id_to_delete = cc_pair.connector_id
+            credential_id_to_delete = cc_pair.credential_id
+
             # Explicitly delete document by connector credential pair records before deleting the connector
             # This is needed because connector_id is a primary key in that table and cascading deletes won't work
             delete_all_documents_by_connector_credential_pair__no_commit(
                 db_session=db_session,
-                connector_id=cc_pair.connector_id,
-                credential_id=cc_pair.credential_id,
+                connector_id=connector_id_to_delete,
+                credential_id=credential_id_to_delete,
             )
 
+            # Flush to ensure document deletion happens before connector deletion
             db_session.flush()
 
+            # Expire the cc_pair to ensure SQLAlchemy doesn't try to manage its state
+            # related to the deleted DocumentByConnectorCredentialPair during commit
+            db_session.expire(cc_pair)
+
             # finally, delete the cc-pair
             delete_connector_credential_pair__no_commit(
                 db_session=db_session,
-                connector_id=cc_pair.connector_id,
-                credential_id=cc_pair.credential_id,
+                connector_id=connector_id_to_delete,
+                credential_id=credential_id_to_delete,
             )
             # if there are no credentials left, delete the connector
             connector = fetch_connector_by_id(
                 db_session=db_session,
-                connector_id=cc_pair.connector_id,
+                connector_id=connector_id_to_delete,
             )
             if not connector or not len(connector.credentials):
                 task_logger.info(
@@ -495,15 +506,15 @@ def monitor_connector_deletion_taskset(
 
             task_logger.exception(
                 f"Connector deletion exceptioned: "
-                f"cc_pair={cc_pair_id} connector={cc_pair.connector_id} credential={cc_pair.credential_id}"
+                f"cc_pair={cc_pair_id} connector={connector_id_to_delete} credential={credential_id_to_delete}"
             )
             raise e
 
     task_logger.info(
         f"Connector deletion succeeded: "
         f"cc_pair={cc_pair_id} "
-        f"connector={cc_pair.connector_id} "
-        f"credential={cc_pair.credential_id} "
+        f"connector={connector_id_to_delete} "
+        f"credential={credential_id_to_delete} "
         f"docs_deleted={fence_data.num_tasks}"
     )
 
@@ -553,7 +564,7 @@ def validate_connector_deletion_fences(
 def validate_connector_deletion_fence(
     tenant_id: str,
     key_bytes: bytes,
-    queued_tasks: set[str],
+    queued_upsert_tasks: set[str],
     r: Redis,
 ) -> None:
     """Checks for the error condition where an indexing fence is set but the associated celery tasks don't exist.
@@ -640,7 +651,7 @@ def validate_connector_deletion_fence(
 
         member_bytes = cast(bytes, member)
         member_str = member_bytes.decode("utf-8")
-        if member_str in queued_tasks:
+        if member_str in queued_upsert_tasks:
             continue
 
         tasks_not_in_celery += 1

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

@@ -17,6 +17,7 @@ from redis.exceptions import LockError
 from redis.lock import Lock as RedisLock
 from sqlalchemy.orm import Session
 
+from ee.onyx.configs.app_configs import DEFAULT_PERMISSION_DOC_SYNC_FREQUENCY
 from ee.onyx.db.connector_credential_pair import get_all_auto_sync_cc_pairs
 from ee.onyx.db.document import upsert_document_external_perms
 from ee.onyx.external_permissions.sync_params import DOC_PERMISSION_SYNC_PERIODS
@@ -63,6 +64,7 @@ from onyx.redis.redis_connector_doc_perm_sync import RedisConnectorPermissionSyn
 from onyx.redis.redis_pool import get_redis_client
 from onyx.redis.redis_pool import get_redis_replica_client
 from onyx.redis.redis_pool import redis_lock_dump
+from onyx.server.runtime.onyx_runtime import OnyxRuntime
 from onyx.server.utils import make_short_id
 from onyx.utils.logger import doc_permission_sync_ctx
 from onyx.utils.logger import format_error_for_logging
@@ -106,9 +108,10 @@ def _is_external_doc_permissions_sync_due(cc_pair: ConnectorCredentialPair) -> b
 
     source_sync_period = DOC_PERMISSION_SYNC_PERIODS.get(cc_pair.connector.source)
 
-    # If RESTRICTED_FETCH_PERIOD[source] is None, we always run the sync.
     if not source_sync_period:
-        return True
+        source_sync_period = DEFAULT_PERMISSION_DOC_SYNC_FREQUENCY
+
+    source_sync_period *= int(OnyxRuntime.get_doc_permission_sync_multiplier())
 
     # If the last sync is greater than the full fetch period, we run the sync
     next_sync = last_perm_sync + timedelta(seconds=source_sync_period)
@@ -286,7 +289,7 @@ def try_creating_permissions_sync_task(
             ),
             queue=OnyxCeleryQueues.CONNECTOR_DOC_PERMISSIONS_SYNC,
             task_id=custom_task_id,
-            priority=OnyxCeleryPriority.HIGH,
+            priority=OnyxCeleryPriority.MEDIUM,
         )
 
         # fill in the celery task id

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

@@ -271,7 +271,7 @@ def try_creating_external_group_sync_task(
             ),
             queue=OnyxCeleryQueues.CONNECTOR_EXTERNAL_GROUP_SYNC,
             task_id=custom_task_id,
-            priority=OnyxCeleryPriority.HIGH,
+            priority=OnyxCeleryPriority.MEDIUM,
         )
 
         payload.celery_task_id = result.id

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

@@ -72,6 +72,7 @@ from onyx.redis.redis_pool import get_redis_replica_client
 from onyx.redis.redis_pool import redis_lock_dump
 from onyx.redis.redis_pool import SCAN_ITER_COUNT_DEFAULT
 from onyx.redis.redis_utils import is_fence
+from onyx.server.runtime.onyx_runtime import OnyxRuntime
 from onyx.utils.logger import setup_logger
 from onyx.utils.variable_functionality import global_version
 from shared_configs.configs import INDEXING_MODEL_SERVER_HOST
@@ -364,6 +365,7 @@ def check_for_indexing(self: Task, *, tenant_id: str) -> int | None:
     Occcasionally does some validation of existing state to clear up error conditions"""
 
     time_start = time.monotonic()
+    task_logger.warning("check_for_indexing - Starting")
 
     tasks_created = 0
     locked = False
@@ -401,7 +403,11 @@ def check_for_indexing(self: Task, *, tenant_id: str) -> int | None:
                     logger.warning(f"Adding {key_bytes} to the lookup table.")
                     redis_client.sadd(OnyxRedisConstants.ACTIVE_FENCES, key_bytes)
 
-            redis_client.set(OnyxRedisSignals.BLOCK_BUILD_FENCE_LOOKUP_TABLE, 1, ex=300)
+            redis_client.set(
+                OnyxRedisSignals.BLOCK_BUILD_FENCE_LOOKUP_TABLE,
+                1,
+                ex=OnyxRuntime.get_build_fence_lookup_table_interval(),
+            )
 
         # 1/3: KICKOFF
 
@@ -428,7 +434,9 @@ def check_for_indexing(self: Task, *, tenant_id: str) -> int | None:
         lock_beat.reacquire()
         cc_pair_ids: list[int] = []
         with get_session_with_current_tenant() as db_session:
-            cc_pairs = fetch_connector_credential_pairs(db_session)
+            cc_pairs = fetch_connector_credential_pairs(
+                db_session, include_user_files=True
+            )
             for cc_pair_entry in cc_pairs:
                 cc_pair_ids.append(cc_pair_entry.id)
 
@@ -447,12 +455,18 @@ def check_for_indexing(self: Task, *, tenant_id: str) -> int | None:
                         not search_settings_instance.status.is_current()
                         and not search_settings_instance.background_reindex_enabled
                     ):
+                        task_logger.warning("SKIPPING DUE TO NON-LIVE SEARCH SETTINGS")
+
                         continue
 
                     redis_connector_index = redis_connector.new_index(
                         search_settings_instance.id
                     )
                     if redis_connector_index.fenced:
+                        task_logger.info(
+                            f"check_for_indexing - Skipping fenced connector: "
+                            f"cc_pair={cc_pair_id} search_settings={search_settings_instance.id}"
+                        )
                         continue
 
                     cc_pair = get_connector_credential_pair_from_id(
@@ -460,6 +474,9 @@ def check_for_indexing(self: Task, *, tenant_id: str) -> int | None:
                         cc_pair_id=cc_pair_id,
                     )
                     if not cc_pair:
+                        task_logger.warning(
+                            f"check_for_indexing - CC pair not found: cc_pair={cc_pair_id}"
+                        )
                         continue
 
                     last_attempt = get_last_attempt_for_cc_pair(
@@ -473,7 +490,20 @@ def check_for_indexing(self: Task, *, tenant_id: str) -> int | None:
                         secondary_index_building=len(search_settings_list) > 1,
                         db_session=db_session,
                     ):
+                        task_logger.info(
+                            f"check_for_indexing - Not indexing cc_pair_id: {cc_pair_id} "
+                            f"search_settings={search_settings_instance.id}, "
+                            f"last_attempt={last_attempt.id if last_attempt else None}, "
+                            f"secondary_index_building={len(search_settings_list) > 1}"
+                        )
                         continue
+                    else:
+                        task_logger.info(
+                            f"check_for_indexing - Will index cc_pair_id: {cc_pair_id} "
+                            f"search_settings={search_settings_instance.id}, "
+                            f"last_attempt={last_attempt.id if last_attempt else None}, "
+                            f"secondary_index_building={len(search_settings_list) > 1}"
+                        )
 
                     reindex = False
                     if search_settings_instance.status.is_current():
@@ -512,6 +542,12 @@ def check_for_indexing(self: Task, *, tenant_id: str) -> int | None:
                             f"search_settings={search_settings_instance.id}"
                         )
                         tasks_created += 1
+                    else:
+                        task_logger.info(
+                            f"Failed to create indexing task: "
+                            f"cc_pair={cc_pair.id} "
+                            f"search_settings={search_settings_instance.id}"
+                        )
 
         lock_beat.reacquire()
 
@@ -1144,6 +1180,9 @@ def connector_indexing_proxy_task(
     if result.status == IndexingWatchdogTerminalStatus.TERMINATED_BY_SIGNAL:
         try:
             with get_session_with_current_tenant() as db_session:
+                logger.exception(
+                    f"Marking attempt {index_attempt_id} as canceled due to termination signal"
+                )
                 mark_attempt_canceled(
                     index_attempt_id,
                     db_session,

backend/onyx/background/celery/tasks/indexing/utils.py

@@ -371,6 +371,7 @@ def should_index(
 
     # don't kick off indexing for `NOT_APPLICABLE` sources
     if connector.source == DocumentSource.NOT_APPLICABLE:
+        print(f"Not indexing cc_pair={cc_pair.id}: NOT_APPLICABLE source")
         return False
 
     # User can still manually create single indexing attempts via the UI for the
@@ -380,6 +381,9 @@ def should_index(
             search_settings_instance.status == IndexModelStatus.PRESENT
             and secondary_index_building
         ):
+            print(
+                f"Not indexing cc_pair={cc_pair.id}: DISABLE_INDEX_UPDATE_ON_SWAP is True and secondary index building"
+            )
             return False
 
     # When switching over models, always index at least once
@@ -388,19 +392,31 @@ def should_index(
             # No new index if the last index attempt succeeded
             # Once is enough. The model will never be able to swap otherwise.
             if last_index.status == IndexingStatus.SUCCESS:
+                print(
+                    f"Not indexing cc_pair={cc_pair.id}: FUTURE model with successful last index attempt={last_index.id}"
+                )
                 return False
 
             # No new index if the last index attempt is waiting to start
             if last_index.status == IndexingStatus.NOT_STARTED:
+                print(
+                    f"Not indexing cc_pair={cc_pair.id}: FUTURE model with NOT_STARTED last index attempt={last_index.id}"
+                )
                 return False
 
             # No new index if the last index attempt is running
             if last_index.status == IndexingStatus.IN_PROGRESS:
+                print(
+                    f"Not indexing cc_pair={cc_pair.id}: FUTURE model with IN_PROGRESS last index attempt={last_index.id}"
+                )
                 return False
         else:
             if (
                 connector.id == 0 or connector.source == DocumentSource.INGESTION_API
             ):  # Ingestion API
+                print(
+                    f"Not indexing cc_pair={cc_pair.id}: FUTURE model with Ingestion API source"
+                )
                 return False
         return True
 
@@ -412,6 +428,9 @@ def should_index(
         or connector.id == 0
         or connector.source == DocumentSource.INGESTION_API
     ):
+        print(
+            f"Not indexing cc_pair={cc_pair.id}: Connector is paused or is Ingestion API"
+        )
         return False
 
     if search_settings_instance.status.is_current():
@@ -424,11 +443,16 @@ def should_index(
         return True
 
     if connector.refresh_freq is None:
+        print(f"Not indexing cc_pair={cc_pair.id}: refresh_freq is None")
         return False
 
     current_db_time = get_db_current_time(db_session)
     time_since_index = current_db_time - last_index.time_updated
     if time_since_index.total_seconds() < connector.refresh_freq:
+        print(
+            f"Not indexing cc_pair={cc_pair.id}: Last index attempt={last_index.id} "
+            f"too recent ({time_since_index.total_seconds()}s < {connector.refresh_freq}s)"
+        )
         return False
 
     return True
@@ -508,6 +532,13 @@ def try_creating_indexing_task(
 
         custom_task_id = redis_connector_index.generate_generator_task_id()
 
+        # Determine which queue to use based on whether this is a user file
+        queue = (
+            OnyxCeleryQueues.USER_FILES_INDEXING
+            if cc_pair.is_user_file
+            else OnyxCeleryQueues.CONNECTOR_INDEXING
+        )
+
         # when the task is sent, we have yet to finish setting up the fence
         # therefore, the task must contain code that blocks until the fence is ready
         result = celery_app.send_task(
@@ -518,7 +549,7 @@ def try_creating_indexing_task(
                 search_settings_id=search_settings.id,
                 tenant_id=tenant_id,
             ),
-            queue=OnyxCeleryQueues.CONNECTOR_INDEXING,
+            queue=queue,
             task_id=custom_task_id,
             priority=OnyxCeleryPriority.MEDIUM,
         )

backend/onyx/background/celery/tasks/shared/RetryDocumentIndex.py

@@ -6,6 +6,7 @@ from tenacity import wait_random_exponential
 
 from onyx.document_index.interfaces import DocumentIndex
 from onyx.document_index.interfaces import VespaDocumentFields
+from onyx.document_index.interfaces import VespaDocumentUserFields
 
 
 class RetryDocumentIndex:
@@ -52,11 +53,13 @@ class RetryDocumentIndex:
         *,
         tenant_id: str,
         chunk_count: int | None,
-        fields: VespaDocumentFields,
+        fields: VespaDocumentFields | None,
+        user_fields: VespaDocumentUserFields | None,
     ) -> int:
         return self.index.update_single(
             doc_id,
             tenant_id=tenant_id,
             chunk_count=chunk_count,
             fields=fields,
+            user_fields=user_fields,
         )

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

@@ -164,6 +164,7 @@ def document_by_cc_pair_cleanup_task(
                     tenant_id=tenant_id,
                     chunk_count=doc.chunk_count,
                     fields=fields,
+                    user_fields=None,
                 )
 
                 # there are still other cc_pair references to the doc, so just resync to Vespa

backend/onyx/background/celery/tasks/user_file_folder_sync/tasks.py

@@ -0,0 +1,266 @@
+import time
+from typing import List
+
+from celery import shared_task
+from celery import Task
+from celery.exceptions import SoftTimeLimitExceeded
+from redis.lock import Lock as RedisLock
+from sqlalchemy.orm import Session
+from tenacity import RetryError
+
+from onyx.background.celery.apps.app_base import task_logger
+from onyx.background.celery.tasks.shared.RetryDocumentIndex import RetryDocumentIndex
+from onyx.background.celery.tasks.shared.tasks import LIGHT_SOFT_TIME_LIMIT
+from onyx.background.celery.tasks.shared.tasks import LIGHT_TIME_LIMIT
+from onyx.background.celery.tasks.shared.tasks import OnyxCeleryTaskCompletionStatus
+from onyx.configs.app_configs import JOB_TIMEOUT
+from onyx.configs.constants import CELERY_USER_FILE_FOLDER_SYNC_BEAT_LOCK_TIMEOUT
+from onyx.configs.constants import OnyxCeleryTask
+from onyx.configs.constants import OnyxRedisLocks
+from onyx.db.connector_credential_pair import (
+    get_connector_credential_pairs_with_user_files,
+)
+from onyx.db.document import get_document
+from onyx.db.engine import get_session_with_current_tenant
+from onyx.db.models import ConnectorCredentialPair
+from onyx.db.models import Document
+from onyx.db.models import DocumentByConnectorCredentialPair
+from onyx.db.search_settings import get_active_search_settings
+from onyx.db.user_documents import fetch_user_files_for_documents
+from onyx.db.user_documents import fetch_user_folders_for_documents
+from onyx.document_index.factory import get_default_document_index
+from onyx.document_index.interfaces import VespaDocumentUserFields
+from onyx.httpx.httpx_pool import HttpxPool
+from onyx.redis.redis_pool import get_redis_client
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+@shared_task(
+    name=OnyxCeleryTask.CHECK_FOR_USER_FILE_FOLDER_SYNC,
+    ignore_result=True,
+    soft_time_limit=JOB_TIMEOUT,
+    trail=False,
+    bind=True,
+)
+def check_for_user_file_folder_sync(self: Task, *, tenant_id: str) -> bool | None:
+    """Runs periodically to check for documents that need user file folder metadata updates.
+    This task fetches all connector credential pairs with user files, gets the documents
+    associated with them, and updates the user file and folder metadata in Vespa.
+    """
+
+    time_start = time.monotonic()
+
+    r = get_redis_client()
+
+    lock_beat: RedisLock = r.lock(
+        OnyxRedisLocks.CHECK_USER_FILE_FOLDER_SYNC_BEAT_LOCK,
+        timeout=CELERY_USER_FILE_FOLDER_SYNC_BEAT_LOCK_TIMEOUT,
+    )
+
+    # these tasks should never overlap
+    if not lock_beat.acquire(blocking=False):
+        return None
+
+    try:
+        with get_session_with_current_tenant() as db_session:
+            # Get all connector credential pairs that have user files
+            cc_pairs = get_connector_credential_pairs_with_user_files(db_session)
+
+            if not cc_pairs:
+                task_logger.info("No connector credential pairs with user files found")
+                return True
+
+            # Get all documents associated with these cc_pairs
+            document_ids = get_documents_for_cc_pairs(cc_pairs, db_session)
+
+            if not document_ids:
+                task_logger.info(
+                    "No documents found for connector credential pairs with user files"
+                )
+                return True
+
+            # Fetch current user file and folder IDs for these documents
+            doc_id_to_user_file_id = fetch_user_files_for_documents(
+                document_ids=document_ids, db_session=db_session
+            )
+            doc_id_to_user_folder_id = fetch_user_folders_for_documents(
+                document_ids=document_ids, db_session=db_session
+            )
+
+            # Update Vespa metadata for each document
+            for doc_id in document_ids:
+                user_file_id = doc_id_to_user_file_id.get(doc_id)
+                user_folder_id = doc_id_to_user_folder_id.get(doc_id)
+
+                if user_file_id is not None or user_folder_id is not None:
+                    # Schedule a task to update the document metadata
+                    update_user_file_folder_metadata.apply_async(
+                        args=(doc_id,),  # Use tuple instead of list for args
+                        kwargs={
+                            "tenant_id": tenant_id,
+                            "user_file_id": user_file_id,
+                            "user_folder_id": user_folder_id,
+                        },
+                        queue="vespa_metadata_sync",
+                    )
+
+            task_logger.info(
+                f"Scheduled metadata updates for {len(document_ids)} documents. "
+                f"Elapsed time: {time.monotonic() - time_start:.2f}s"
+            )
+
+            return True
+    except Exception as e:
+        task_logger.exception(f"Error in check_for_user_file_folder_sync: {e}")
+        return False
+    finally:
+        lock_beat.release()
+
+
+def get_documents_for_cc_pairs(
+    cc_pairs: List[ConnectorCredentialPair], db_session: Session
+) -> List[str]:
+    """Get all document IDs associated with the given connector credential pairs."""
+    if not cc_pairs:
+        return []
+
+    cc_pair_ids = [cc_pair.id for cc_pair in cc_pairs]
+
+    # Query to get document IDs from DocumentByConnectorCredentialPair
+    # Note: DocumentByConnectorCredentialPair uses connector_id and credential_id, not cc_pair_id
+    doc_cc_pairs = (
+        db_session.query(Document.id)
+        .join(
+            DocumentByConnectorCredentialPair,
+            Document.id == DocumentByConnectorCredentialPair.id,
+        )
+        .filter(
+            db_session.query(ConnectorCredentialPair)
+            .filter(
+                ConnectorCredentialPair.id.in_(cc_pair_ids),
+                ConnectorCredentialPair.connector_id
+                == DocumentByConnectorCredentialPair.connector_id,
+                ConnectorCredentialPair.credential_id
+                == DocumentByConnectorCredentialPair.credential_id,
+            )
+            .exists()
+        )
+        .all()
+    )
+
+    return [doc_id for (doc_id,) in doc_cc_pairs]
+
+
+@shared_task(
+    name=OnyxCeleryTask.UPDATE_USER_FILE_FOLDER_METADATA,
+    bind=True,
+    soft_time_limit=LIGHT_SOFT_TIME_LIMIT,
+    time_limit=LIGHT_TIME_LIMIT,
+    max_retries=3,
+)
+def update_user_file_folder_metadata(
+    self: Task,
+    document_id: str,
+    *,
+    tenant_id: str,
+    user_file_id: int | None,
+    user_folder_id: int | None,
+) -> bool:
+    """Updates the user file and folder metadata for a document in Vespa."""
+    start = time.monotonic()
+    completion_status = OnyxCeleryTaskCompletionStatus.UNDEFINED
+
+    try:
+        with get_session_with_current_tenant() as db_session:
+            active_search_settings = get_active_search_settings(db_session)
+            doc_index = get_default_document_index(
+                search_settings=active_search_settings.primary,
+                secondary_search_settings=active_search_settings.secondary,
+                httpx_client=HttpxPool.get("vespa"),
+            )
+
+            retry_index = RetryDocumentIndex(doc_index)
+
+            doc = get_document(document_id, db_session)
+            if not doc:
+                elapsed = time.monotonic() - start
+                task_logger.info(
+                    f"doc={document_id} "
+                    f"action=no_operation "
+                    f"elapsed={elapsed:.2f}"
+                )
+                completion_status = OnyxCeleryTaskCompletionStatus.SKIPPED
+                return False
+
+            # Create user fields object with file and folder IDs
+            user_fields = VespaDocumentUserFields(
+                user_file_id=str(user_file_id) if user_file_id is not None else None,
+                user_folder_id=str(user_folder_id)
+                if user_folder_id is not None
+                else None,
+            )
+
+            # Update Vespa. OK if doc doesn't exist. Raises exception otherwise.
+            chunks_affected = retry_index.update_single(
+                document_id,
+                tenant_id=tenant_id,
+                chunk_count=doc.chunk_count,
+                fields=None,  # We're only updating user fields
+                user_fields=user_fields,
+            )
+
+            elapsed = time.monotonic() - start
+            task_logger.info(
+                f"doc={document_id} "
+                f"action=user_file_folder_sync "
+                f"user_file_id={user_file_id} "
+                f"user_folder_id={user_folder_id} "
+                f"chunks={chunks_affected} "
+                f"elapsed={elapsed:.2f}"
+            )
+            completion_status = OnyxCeleryTaskCompletionStatus.SUCCEEDED
+            return True
+
+    except SoftTimeLimitExceeded:
+        task_logger.info(f"SoftTimeLimitExceeded exception. doc={document_id}")
+        completion_status = OnyxCeleryTaskCompletionStatus.SOFT_TIME_LIMIT
+    except Exception as ex:
+        e: Exception | None = None
+        while True:
+            if isinstance(ex, RetryError):
+                task_logger.warning(
+                    f"Tenacity retry failed: num_attempts={ex.last_attempt.attempt_number}"
+                )
+
+                # only set the inner exception if it is of type Exception
+                e_temp = ex.last_attempt.exception()
+                if isinstance(e_temp, Exception):
+                    e = e_temp
+            else:
+                e = ex
+
+            task_logger.exception(
+                f"update_user_file_folder_metadata exceptioned: doc={document_id}"
+            )
+
+            completion_status = OnyxCeleryTaskCompletionStatus.RETRYABLE_EXCEPTION
+            if (
+                self.max_retries is not None
+                and self.request.retries >= self.max_retries
+            ):
+                completion_status = (
+                    OnyxCeleryTaskCompletionStatus.NON_RETRYABLE_EXCEPTION
+                )
+
+            # Exponential backoff from 2^4 to 2^6 ... i.e. 16, 32, 64
+            countdown = 2 ** (self.request.retries + 4)
+            self.retry(exc=e, countdown=countdown)  # this will raise a celery exception
+            break  # we won't hit this, but it looks weird not to have it
+    finally:
+        task_logger.info(
+            f"update_user_file_folder_metadata completed: status={completion_status.value} doc={document_id}"
+        )
+
+    return False

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

@@ -80,7 +80,8 @@ def check_for_vespa_sync_task(self: Task, *, tenant_id: str) -> bool | None:
     """Runs periodically to check if any document needs syncing.
     Generates sets of tasks for Celery if syncing is needed."""
 
-    # Useful for debugging timing issues with reacquisitions. TODO: remove once more generalized logging is in place
+    # Useful for debugging timing issues with reacquisitions.
+    # TODO: remove once more generalized logging is in place
     task_logger.info("check_for_vespa_sync_task started")
 
     time_start = time.monotonic()
@@ -572,6 +573,7 @@ def vespa_metadata_sync_task(self: Task, document_id: str, *, tenant_id: str) ->
                     tenant_id=tenant_id,
                     chunk_count=doc.chunk_count,
                     fields=fields,
+                    user_fields=None,
                 )
 
                 # update db last. Worst case = we crash right before this and

backend/onyx/background/indexing/run_indexing.py

@@ -274,7 +274,6 @@ def _run_indexing(
                 "Search settings must be set for indexing. This should not be possible."
             )
 
-        # search_settings = index_attempt_start.search_settings
         db_connector = index_attempt_start.connector_credential_pair.connector
         db_credential = index_attempt_start.connector_credential_pair.credential
         ctx = RunIndexingContext(
@@ -638,6 +637,9 @@ def _run_indexing(
             # and mark the CCPair as invalid. This prevents the connector from being
             # used in the future until the credentials are updated.
             with get_session_with_current_tenant() as db_session_temp:
+                logger.exception(
+                    f"Marking attempt {index_attempt_id} as canceled due to validation error."
+                )
                 mark_attempt_canceled(
                     index_attempt_id,
                     db_session_temp,
@@ -684,6 +686,9 @@ def _run_indexing(
 
         elif isinstance(e, ConnectorStopSignal):
             with get_session_with_current_tenant() as db_session_temp:
+                logger.exception(
+                    f"Marking attempt {index_attempt_id} as canceled due to stop signal."
+                )
                 mark_attempt_canceled(
                     index_attempt_id,
                     db_session_temp,
@@ -746,6 +751,7 @@ def _run_indexing(
                 f"Connector succeeded: "
                 f"docs={document_count} chunks={chunk_count} elapsed={elapsed_time:.2f}s"
             )
+
         else:
             mark_attempt_partially_succeeded(index_attempt_id, db_session_temp)
             logger.info(

backend/onyx/chat/models.py

@@ -127,6 +127,10 @@ class StreamStopInfo(SubQuestionIdentifier):
         return data
 
 
+class UserKnowledgeFilePacket(BaseModel):
+    user_files: list[FileDescriptor]
+
+
 class LLMRelevanceFilterResponse(BaseModel):
     llm_selected_doc_indices: list[int]
 
@@ -194,17 +198,6 @@ class StreamingError(BaseModel):
     stack_trace: str | None = None
 
 
-class OnyxContext(BaseModel):
-    content: str
-    document_id: str
-    semantic_identifier: str
-    blurb: str
-
-
-class OnyxContexts(BaseModel):
-    contexts: list[OnyxContext]
-
-
 class OnyxAnswer(BaseModel):
     answer: str | None
 
@@ -270,7 +263,6 @@ class PersonaOverrideConfig(BaseModel):
 AnswerQuestionPossibleReturn = (
     OnyxAnswerPiece
     | CitationInfo
-    | OnyxContexts
     | FileChatDisplay
     | CustomToolResponse
     | StreamingError

backend/onyx/chat/process_message.py

@@ -29,7 +29,6 @@ from onyx.chat.models import LLMRelevanceFilterResponse
 from onyx.chat.models import MessageResponseIDInfo
 from onyx.chat.models import MessageSpecificCitations
 from onyx.chat.models import OnyxAnswerPiece
-from onyx.chat.models import OnyxContexts
 from onyx.chat.models import PromptConfig
 from onyx.chat.models import QADocsResponse
 from onyx.chat.models import RefinedAnswerImprovement
@@ -37,6 +36,7 @@ from onyx.chat.models import StreamingError
 from onyx.chat.models import StreamStopInfo
 from onyx.chat.models import StreamStopReason
 from onyx.chat.models import SubQuestionKey
+from onyx.chat.models import UserKnowledgeFilePacket
 from onyx.chat.prompt_builder.answer_prompt_builder import AnswerPromptBuilder
 from onyx.chat.prompt_builder.answer_prompt_builder import default_build_system_message
 from onyx.chat.prompt_builder.answer_prompt_builder import default_build_user_message
@@ -52,6 +52,7 @@ from onyx.context.search.enums import LLMEvaluationType
 from onyx.context.search.enums import OptionalSearchSetting
 from onyx.context.search.enums import QueryFlow
 from onyx.context.search.enums import SearchType
+from onyx.context.search.models import BaseFilters
 from onyx.context.search.models import InferenceSection
 from onyx.context.search.models import RetrievalDetails
 from onyx.context.search.models import SearchRequest
@@ -65,6 +66,7 @@ from onyx.context.search.utils import relevant_sections_to_indices
 from onyx.db.chat import attach_files_to_chat_message
 from onyx.db.chat import create_db_search_doc
 from onyx.db.chat import create_new_chat_message
+from onyx.db.chat import create_search_doc_from_user_file
 from onyx.db.chat import get_chat_message
 from onyx.db.chat import get_chat_session_by_id
 from onyx.db.chat import get_db_search_doc_by_id
@@ -73,6 +75,7 @@ from onyx.db.chat import get_or_create_root_message
 from onyx.db.chat import reserve_message_id
 from onyx.db.chat import translate_db_message_to_chat_message_detail
 from onyx.db.chat import translate_db_search_doc_to_server_search_doc
+from onyx.db.chat import update_chat_session_updated_at_timestamp
 from onyx.db.engine import get_session_context_manager
 from onyx.db.milestone import check_multi_assistant_milestone
 from onyx.db.milestone import create_milestone_if_not_exists
@@ -80,12 +83,16 @@ from onyx.db.milestone import update_user_assistant_milestone
 from onyx.db.models import SearchDoc as DbSearchDoc
 from onyx.db.models import ToolCall
 from onyx.db.models import User
+from onyx.db.models import UserFile
 from onyx.db.persona import get_persona_by_id
 from onyx.db.search_settings import get_current_search_settings
 from onyx.document_index.factory import get_default_document_index
 from onyx.file_store.models import ChatFileType
 from onyx.file_store.models import FileDescriptor
+from onyx.file_store.models import InMemoryChatFile
 from onyx.file_store.utils import load_all_chat_files
+from onyx.file_store.utils import load_all_user_file_files
+from onyx.file_store.utils import load_all_user_files
 from onyx.file_store.utils import save_files
 from onyx.llm.exceptions import GenAIDisabledException
 from onyx.llm.factory import get_llms_for_persona
@@ -98,6 +105,7 @@ from onyx.server.query_and_chat.models import ChatMessageDetail
 from onyx.server.query_and_chat.models import CreateChatMessageRequest
 from onyx.server.utils import get_json_line
 from onyx.tools.force import ForceUseTool
+from onyx.tools.models import SearchToolOverrideKwargs
 from onyx.tools.models import ToolResponse
 from onyx.tools.tool import Tool
 from onyx.tools.tool_constructor import construct_tools
@@ -130,7 +138,6 @@ from onyx.tools.tool_implementations.internet_search.internet_search_tool import
 from onyx.tools.tool_implementations.search.search_tool import (
     FINAL_CONTEXT_DOCUMENTS_ID,
 )
-from onyx.tools.tool_implementations.search.search_tool import SEARCH_DOC_CONTENT_ID
 from onyx.tools.tool_implementations.search.search_tool import (
     SEARCH_RESPONSE_SUMMARY_ID,
 )
@@ -176,11 +183,14 @@ def _handle_search_tool_response_summary(
     db_session: Session,
     selected_search_docs: list[DbSearchDoc] | None,
     dedupe_docs: bool = False,
+    user_files: list[UserFile] | None = None,
+    loaded_user_files: list[InMemoryChatFile] | None = None,
 ) -> tuple[QADocsResponse, list[DbSearchDoc], list[int] | None]:
     response_sumary = cast(SearchResponseSummary, packet.response)
 
     is_extended = isinstance(packet, ExtendedToolResponse)
     dropped_inds = None
+
     if not selected_search_docs:
         top_docs = chunks_or_sections_to_search_docs(response_sumary.top_sections)
 
@@ -194,9 +204,31 @@ def _handle_search_tool_response_summary(
             create_db_search_doc(server_search_doc=doc, db_session=db_session)
             for doc in deduped_docs
         ]
+
     else:
         reference_db_search_docs = selected_search_docs
 
+    doc_ids = {doc.id for doc in reference_db_search_docs}
+    if user_files is not None:
+        for user_file in user_files:
+            if user_file.id not in doc_ids:
+                associated_chat_file = None
+                if loaded_user_files is not None:
+                    associated_chat_file = next(
+                        (
+                            file
+                            for file in loaded_user_files
+                            if file.file_id == str(user_file.file_id)
+                        ),
+                        None,
+                    )
+                # Use create_search_doc_from_user_file to properly add the document to the database
+                if associated_chat_file is not None:
+                    db_doc = create_search_doc_from_user_file(
+                        user_file, associated_chat_file, db_session
+                    )
+                    reference_db_search_docs.append(db_doc)
+
     response_docs = [
         translate_db_search_doc_to_server_search_doc(db_search_doc)
         for db_search_doc in reference_db_search_docs
@@ -254,7 +286,10 @@ def _handle_internet_search_tool_response_summary(
 
 
 def _get_force_search_settings(
-    new_msg_req: CreateChatMessageRequest, tools: list[Tool]
+    new_msg_req: CreateChatMessageRequest,
+    tools: list[Tool],
+    user_file_ids: list[int],
+    user_folder_ids: list[int],
 ) -> ForceUseTool:
     internet_search_available = any(
         isinstance(tool, InternetSearchTool) for tool in tools
@@ -262,8 +297,11 @@ def _get_force_search_settings(
     search_tool_available = any(isinstance(tool, SearchTool) for tool in tools)
 
     if not internet_search_available and not search_tool_available:
-        # Does not matter much which tool is set here as force is false and neither tool is available
-        return ForceUseTool(force_use=False, tool_name=SearchTool._NAME)
+        if new_msg_req.force_user_file_search:
+            return ForceUseTool(force_use=True, tool_name=SearchTool._NAME)
+        else:
+            # Does not matter much which tool is set here as force is false and neither tool is available
+            return ForceUseTool(force_use=False, tool_name=SearchTool._NAME)
 
     tool_name = SearchTool._NAME if search_tool_available else InternetSearchTool._NAME
     # Currently, the internet search tool does not support query override
@@ -273,12 +311,25 @@ def _get_force_search_settings(
         else None
     )
 
+    # Create override_kwargs for the search tool if user_file_ids are provided
+    override_kwargs = None
+    if (user_file_ids or user_folder_ids) and tool_name == SearchTool._NAME:
+        override_kwargs = SearchToolOverrideKwargs(
+            force_no_rerank=False,
+            alternate_db_session=None,
+            retrieved_sections_callback=None,
+            skip_query_analysis=False,
+            user_file_ids=user_file_ids,
+            user_folder_ids=user_folder_ids,
+        )
+
     if new_msg_req.file_descriptors:
         # If user has uploaded files they're using, don't run any of the search tools
         return ForceUseTool(force_use=False, tool_name=tool_name)
 
     should_force_search = any(
         [
+            new_msg_req.force_user_file_search,
             new_msg_req.retrieval_options
             and new_msg_req.retrieval_options.run_search
             == OptionalSearchSetting.ALWAYS,
@@ -291,15 +342,22 @@ def _get_force_search_settings(
     if should_force_search:
         # If we are using selected docs, just put something here so the Tool doesn't need to build its own args via an LLM call
         args = {"query": new_msg_req.message} if new_msg_req.search_doc_ids else args
-        return ForceUseTool(force_use=True, tool_name=tool_name, args=args)
 
-    return ForceUseTool(force_use=False, tool_name=tool_name, args=args)
+        return ForceUseTool(
+            force_use=True,
+            tool_name=tool_name,
+            args=args,
+            override_kwargs=override_kwargs,
+        )
+
+    return ForceUseTool(
+        force_use=False, tool_name=tool_name, args=args, override_kwargs=override_kwargs
+    )
 
 
 ChatPacket = (
     StreamingError
     | QADocsResponse
-    | OnyxContexts
     | LLMRelevanceFilterResponse
     | FinalUsedContextDocsResponse
     | ChatMessageDetail
@@ -313,6 +371,7 @@ ChatPacket = (
     | AgenticMessageResponseIDInfo
     | StreamStopInfo
     | AgentSearchPacket
+    | UserKnowledgeFilePacket
 )
 ChatPacketStream = Iterator[ChatPacket]
 
@@ -358,6 +417,10 @@ def stream_chat_message_objects(
     llm: LLM
 
     try:
+        # Move these variables inside the try block
+        file_id_to_user_file = {}
+        ordered_user_files = None
+
         user_id = user.id if user is not None else None
 
         chat_session = get_chat_session_by_id(
@@ -537,6 +600,70 @@ def stream_chat_message_objects(
         )
         req_file_ids = [f["id"] for f in new_msg_req.file_descriptors]
         latest_query_files = [file for file in files if file.file_id in req_file_ids]
+        user_file_ids = new_msg_req.user_file_ids or []
+        user_folder_ids = new_msg_req.user_folder_ids or []
+
+        if persona.user_files:
+            for file in persona.user_files:
+                user_file_ids.append(file.id)
+        if persona.user_folders:
+            for folder in persona.user_folders:
+                user_folder_ids.append(folder.id)
+
+        # Initialize flag for user file search
+        use_search_for_user_files = False
+
+        user_files: list[InMemoryChatFile] | None = None
+        search_for_ordering_only = False
+        user_file_files: list[UserFile] | None = None
+        if user_file_ids or user_folder_ids:
+            # Load user files
+            user_files = load_all_user_files(
+                user_file_ids or [],
+                user_folder_ids or [],
+                db_session,
+            )
+            user_file_files = load_all_user_file_files(
+                user_file_ids or [],
+                user_folder_ids or [],
+                db_session,
+            )
+            # Store mapping of file_id to file for later reordering
+            if user_files:
+                file_id_to_user_file = {file.file_id: file for file in user_files}
+
+            # Calculate token count for the files
+            from onyx.db.user_documents import calculate_user_files_token_count
+            from onyx.chat.prompt_builder.citations_prompt import (
+                compute_max_document_tokens_for_persona,
+            )
+
+            total_tokens = calculate_user_files_token_count(
+                user_file_ids or [],
+                user_folder_ids or [],
+                db_session,
+            )
+
+            # Calculate available tokens for documents based on prompt, user input, etc.
+            available_tokens = compute_max_document_tokens_for_persona(
+                db_session=db_session,
+                persona=persona,
+                actual_user_input=message_text,  # Use the actual user message
+            )
+
+            logger.debug(
+                f"Total file tokens: {total_tokens}, Available tokens: {available_tokens}"
+            )
+
+            # ALWAYS use search for user files, but track if we need it for context or just ordering
+            use_search_for_user_files = True
+            # If files are small enough for context, we'll just use search for ordering
+            search_for_ordering_only = total_tokens <= available_tokens
+
+            if search_for_ordering_only:
+                # Add original user files to context since they fit
+                if user_files:
+                    latest_query_files.extend(user_files)
 
         if user_message:
             attach_files_to_chat_message(
@@ -679,8 +806,10 @@ def stream_chat_message_objects(
             prompt_config=prompt_config,
             db_session=db_session,
             user=user,
+            user_knowledge_present=bool(user_files or user_folder_ids),
             llm=llm,
             fast_llm=fast_llm,
+            use_file_search=new_msg_req.force_user_file_search,
             search_tool_config=SearchToolConfig(
                 answer_style_config=answer_style_config,
                 document_pruning_config=document_pruning_config,
@@ -710,17 +839,138 @@ def stream_chat_message_objects(
         for tool_list in tool_dict.values():
             tools.extend(tool_list)
 
+        force_use_tool = _get_force_search_settings(
+            new_msg_req, tools, user_file_ids, user_folder_ids
+        )
+
+        # Set force_use if user files exceed token limit
+        if use_search_for_user_files:
+            try:
+                # Check if search tool is available in the tools list
+                search_tool_available = any(
+                    isinstance(tool, SearchTool) for tool in tools
+                )
+
+                # If no search tool is available, add one
+                if not search_tool_available:
+                    logger.info("No search tool available, creating one for user files")
+                    # Create a basic search tool config
+                    search_tool_config = SearchToolConfig(
+                        answer_style_config=answer_style_config,
+                        document_pruning_config=document_pruning_config,
+                        retrieval_options=retrieval_options or RetrievalDetails(),
+                    )
+
+                    # Create and add the search tool
+                    search_tool = SearchTool(
+                        db_session=db_session,
+                        user=user,
+                        persona=persona,
+                        retrieval_options=search_tool_config.retrieval_options,
+                        prompt_config=prompt_config,
+                        llm=llm,
+                        fast_llm=fast_llm,
+                        pruning_config=search_tool_config.document_pruning_config,
+                        answer_style_config=search_tool_config.answer_style_config,
+                        evaluation_type=(
+                            LLMEvaluationType.BASIC
+                            if persona.llm_relevance_filter
+                            else LLMEvaluationType.SKIP
+                        ),
+                        bypass_acl=bypass_acl,
+                    )
+
+                    # Add the search tool to the tools list
+                    tools.append(search_tool)
+
+                    logger.info(
+                        "Added search tool for user files that exceed token limit"
+                    )
+
+                # Now set force_use_tool.force_use to True
+                force_use_tool.force_use = True
+                force_use_tool.tool_name = SearchTool._NAME
+
+                # Set query argument if not already set
+                if not force_use_tool.args:
+                    force_use_tool.args = {"query": final_msg.message}
+
+                # Pass the user file IDs to the search tool
+                if user_file_ids or user_folder_ids:
+                    # Create a BaseFilters object with user_file_ids
+                    if not retrieval_options:
+                        retrieval_options = RetrievalDetails()
+                    if not retrieval_options.filters:
+                        retrieval_options.filters = BaseFilters()
+
+                    # Set user file and folder IDs in the filters
+                    retrieval_options.filters.user_file_ids = user_file_ids
+                    retrieval_options.filters.user_folder_ids = user_folder_ids
+
+                    # Create override kwargs for the search tool
+                    override_kwargs = SearchToolOverrideKwargs(
+                        force_no_rerank=search_for_ordering_only,  # Skip reranking for ordering-only
+                        alternate_db_session=None,
+                        retrieved_sections_callback=None,
+                        skip_query_analysis=search_for_ordering_only,  # Skip query analysis for ordering-only
+                        user_file_ids=user_file_ids,
+                        user_folder_ids=user_folder_ids,
+                        ordering_only=search_for_ordering_only,  # Set ordering_only flag for fast path
+                    )
+
+                    # Set the override kwargs in the force_use_tool
+                    force_use_tool.override_kwargs = override_kwargs
+
+                    if search_for_ordering_only:
+                        logger.info(
+                            "Fast path: Configured search tool with optimized settings for ordering-only"
+                        )
+                        logger.info(
+                            "Fast path: Skipping reranking and query analysis for ordering-only mode"
+                        )
+                        logger.info(
+                            f"Using {len(user_file_ids or [])} files and {len(user_folder_ids or [])} folders"
+                        )
+                    else:
+                        logger.info(
+                            "Configured search tool to use ",
+                            f"{len(user_file_ids or [])} files and {len(user_folder_ids or [])} folders",
+                        )
+            except Exception as e:
+                logger.exception(
+                    f"Error configuring search tool for user files: {str(e)}"
+                )
+                use_search_for_user_files = False
+
         # TODO: unify message history with single message history
         message_history = [
             PreviousMessage.from_chat_message(msg, files) for msg in history_msgs
         ]
+        if not use_search_for_user_files and user_files:
+            yield UserKnowledgeFilePacket(
+                user_files=[
+                    FileDescriptor(
+                        id=str(file.file_id), type=ChatFileType.USER_KNOWLEDGE
+                    )
+                    for file in user_files
+                ]
+            )
+
+        if search_for_ordering_only:
+            logger.info(
+                "Performance: Forcing LLMEvaluationType.SKIP to prevent chunk evaluation for ordering-only search"
+            )
 
         search_request = SearchRequest(
             query=final_msg.message,
             evaluation_type=(
-                LLMEvaluationType.BASIC
-                if persona.llm_relevance_filter
-                else LLMEvaluationType.SKIP
+                LLMEvaluationType.SKIP
+                if search_for_ordering_only
+                else (
+                    LLMEvaluationType.BASIC
+                    if persona.llm_relevance_filter
+                    else LLMEvaluationType.SKIP
+                )
             ),
             human_selected_filters=(
                 retrieval_options.filters if retrieval_options else None
@@ -739,7 +989,6 @@ def stream_chat_message_objects(
             ),
         )
 
-        force_use_tool = _get_force_search_settings(new_msg_req, tools)
         prompt_builder = AnswerPromptBuilder(
             user_message=default_build_user_message(
                 user_query=final_msg.message,
@@ -808,8 +1057,22 @@ def stream_chat_message_objects(
                 info = info_by_subq[
                     SubQuestionKey(level=level, question_num=level_question_num)
                 ]
+
+                # Skip LLM relevance processing entirely for ordering-only mode
+                if search_for_ordering_only and packet.id == SECTION_RELEVANCE_LIST_ID:
+                    logger.info(
+                        "Fast path: Completely bypassing section relevance processing for ordering-only mode"
+                    )
+                    # Skip this packet entirely since it would trigger LLM processing
+                    continue
+
                 # TODO: don't need to dedupe here when we do it in agent flow
                 if packet.id == SEARCH_RESPONSE_SUMMARY_ID:
+                    if search_for_ordering_only:
+                        logger.info(
+                            "Fast path: Skipping document deduplication for ordering-only mode"
+                        )
+
                     (
                         info.qa_docs_response,
                         info.reference_db_search_docs,
@@ -819,16 +1082,91 @@ def stream_chat_message_objects(
                         db_session=db_session,
                         selected_search_docs=selected_db_search_docs,
                         # Deduping happens at the last step to avoid harming quality by dropping content early on
+                        # Skip deduping completely for ordering-only mode to save time
                         dedupe_docs=(
-                            retrieval_options.dedupe_docs
-                            if retrieval_options
-                            else False
+                            False
+                            if search_for_ordering_only
+                            else (
+                                retrieval_options.dedupe_docs
+                                if retrieval_options
+                                else False
+                            )
                         ),
+                        user_files=user_file_files if search_for_ordering_only else [],
+                        loaded_user_files=user_files
+                        if search_for_ordering_only
+                        else [],
                     )
+
+                    # If we're using search just for ordering user files
+                    if (
+                        search_for_ordering_only
+                        and user_files
+                        and info.qa_docs_response
+                    ):
+                        logger.info(
+                            f"ORDERING: Processing search results for ordering {len(user_files)} user files"
+                        )
+                        import time
+
+                        ordering_start = time.time()
+
+                        # Extract document order from search results
+                        doc_order = []
+                        for doc in info.qa_docs_response.top_documents:
+                            doc_id = doc.document_id
+                            if str(doc_id).startswith("USER_FILE_CONNECTOR__"):
+                                file_id = doc_id.replace("USER_FILE_CONNECTOR__", "")
+                                if file_id in file_id_to_user_file:
+                                    doc_order.append(file_id)
+
+                        logger.info(
+                            f"ORDERING: Found {len(doc_order)} files from search results"
+                        )
+
+                        # Add any files that weren't in search results at the end
+                        missing_files = [
+                            f_id
+                            for f_id in file_id_to_user_file.keys()
+                            if f_id not in doc_order
+                        ]
+
+                        missing_files.extend(doc_order)
+                        doc_order = missing_files
+
+                        logger.info(
+                            f"ORDERING: Added {len(missing_files)} missing files to the end"
+                        )
+
+                        # Reorder user files based on search results
+                        ordered_user_files = [
+                            file_id_to_user_file[f_id]
+                            for f_id in doc_order
+                            if f_id in file_id_to_user_file
+                        ]
+
+                        time.time() - ordering_start
+
+                        yield UserKnowledgeFilePacket(
+                            user_files=[
+                                FileDescriptor(
+                                    id=str(file.file_id),
+                                    type=ChatFileType.USER_KNOWLEDGE,
+                                )
+                                for file in ordered_user_files
+                            ]
+                        )
+
                     yield info.qa_docs_response
                 elif packet.id == SECTION_RELEVANCE_LIST_ID:
                     relevance_sections = packet.response
 
+                    if search_for_ordering_only:
+                        logger.info(
+                            "Performance: Skipping relevance filtering for ordering-only mode"
+                        )
+                        continue
+
                     if info.reference_db_search_docs is None:
                         logger.warning(
                             "No reference docs found for relevance filtering"
@@ -918,8 +1256,6 @@ def stream_chat_message_objects(
                             response=custom_tool_response.tool_result,
                             tool_name=custom_tool_response.tool_name,
                         )
-                elif packet.id == SEARCH_DOC_CONTENT_ID and include_contexts:
-                    yield cast(OnyxContexts, packet.response)
 
             elif isinstance(packet, StreamStopInfo):
                 if packet.stop_reason == StreamStopReason.FINISHED:
@@ -940,7 +1276,7 @@ def stream_chat_message_objects(
                     ]
                     info.tool_result = packet
                 yield cast(ChatPacket, packet)
-        logger.debug("Reached end of stream")
+
     except ValueError as e:
         logger.exception("Failed to process chat message.")
 
@@ -1022,10 +1358,16 @@ def stream_chat_message_objects(
             error=ERROR_TYPE_CANCELLED if answer.is_cancelled() else None,
             tool_call=(
                 ToolCall(
-                    tool_id=tool_name_to_tool_id[info.tool_result.tool_name],
-                    tool_name=info.tool_result.tool_name,
-                    tool_arguments=info.tool_result.tool_args,
-                    tool_result=info.tool_result.tool_result,
+                    tool_id=tool_name_to_tool_id.get(info.tool_result.tool_name, 0)
+                    if info.tool_result
+                    else None,
+                    tool_name=info.tool_result.tool_name if info.tool_result else None,
+                    tool_arguments=info.tool_result.tool_args
+                    if info.tool_result
+                    else None,
+                    tool_result=info.tool_result.tool_result
+                    if info.tool_result
+                    else None,
                 )
                 if info.tool_result
                 else None
@@ -1069,6 +1411,8 @@ def stream_chat_message_objects(
             prev_message = next_answer_message
 
         logger.debug("Committing messages")
+        # Explicitly update the timestamp on the chat session
+        update_chat_session_updated_at_timestamp(chat_session_id, db_session)
         db_session.commit()  # actually save user / assistant message
 
         yield AgenticMessageResponseIDInfo(agentic_message_ids=agentic_message_ids)

backend/onyx/chat/prompt_builder/utils.py

@@ -19,6 +19,7 @@ def translate_onyx_msg_to_langchain(
     # attached. Just ignore them for now.
     if not isinstance(msg, ChatMessage):
         files = msg.files
+
     content = build_content_with_imgs(
         msg.message, files, message_type=msg.message_type, exclude_images=exclude_images
     )

backend/onyx/chat/prune_and_merge.py

@@ -153,6 +153,8 @@ def _apply_pruning(
     # remove docs that are explicitly marked as not for QA
     sections = _remove_sections_to_ignore(sections=sections)
 
+    section_idx_token_count: dict[int, int] = {}
+
     final_section_ind = None
     total_tokens = 0
     for ind, section in enumerate(sections):
@@ -202,10 +204,20 @@ def _apply_pruning(
             section_token_count = DOC_EMBEDDING_CONTEXT_SIZE
 
         total_tokens += section_token_count
+        section_idx_token_count[ind] = section_token_count
+
         if total_tokens > token_limit:
             final_section_ind = ind
             break
 
+    try:
+        logger.debug(f"Number of documents after pruning: {ind + 1}")
+        logger.debug("Number of tokens per document (pruned):")
+        for x, y in section_idx_token_count.items():
+            logger.debug(f"{x + 1}: {y}")
+    except Exception as e:
+        logger.error(f"Error logging prune statistics: {e}")
+
     if final_section_ind is not None:
         if is_manually_selected_docs or use_sections:
             if final_section_ind != len(sections) - 1:
@@ -301,6 +313,10 @@ def prune_sections(
 
 
 def _merge_doc_chunks(chunks: list[InferenceChunk]) -> InferenceSection:
+    assert (
+        len(set([chunk.document_id for chunk in chunks])) == 1
+    ), "One distinct document must be passed into merge_doc_chunks"
+
     # Assuming there are no duplicates by this point
     sorted_chunks = sorted(chunks, key=lambda x: x.chunk_id)
 
@@ -358,6 +374,26 @@ def _merge_sections(sections: list[InferenceSection]) -> list[InferenceSection]:
         reverse=True,
     )
 
+    try:
+        num_original_sections = len(sections)
+        num_original_document_ids = len(
+            set([section.center_chunk.document_id for section in sections])
+        )
+        num_merged_sections = len(new_sections)
+        num_merged_document_ids = len(
+            set([section.center_chunk.document_id for section in new_sections])
+        )
+        logger.debug(
+            f"Merged {num_original_sections} sections from {num_original_document_ids} documents "
+            f"into {num_merged_sections} new sections in {num_merged_document_ids} documents"
+        )
+
+        logger.debug("Number of chunks per document (new ranking):")
+        for x, y in enumerate(new_sections):
+            logger.debug(f"{x + 1}: {len(y.chunks)}")
+    except Exception as e:
+        logger.error(f"Error logging merge statistics: {e}")
+
     return new_sections
 
 

backend/onyx/chat/stream_processing/utils.py

@@ -3,7 +3,6 @@ from collections.abc import Sequence
 from pydantic import BaseModel
 
 from onyx.chat.models import LlmDoc
-from onyx.chat.models import OnyxContext
 from onyx.context.search.models import InferenceChunk
 
 
@@ -12,7 +11,7 @@ class DocumentIdOrderMapping(BaseModel):
 
 
 def map_document_id_order(
-    chunks: Sequence[InferenceChunk | LlmDoc | OnyxContext], one_indexed: bool = True
+    chunks: Sequence[InferenceChunk | LlmDoc], one_indexed: bool = True
 ) -> DocumentIdOrderMapping:
     order_mapping = {}
     current = 1 if one_indexed else 0

backend/onyx/chat/tool_handling/tool_response_handler.py

@@ -180,6 +180,10 @@ def get_tool_call_for_non_tool_calling_llm_impl(
         if tool_args is None:
             raise RuntimeError(f"Tool '{tool.name}' did not return args")
 
+        # If we have override_kwargs, add them to the tool_args
+        if force_use_tool.override_kwargs is not None:
+            tool_args["override_kwargs"] = force_use_tool.override_kwargs
+
         return (tool, tool_args)
     else:
         tool_options = check_which_tools_should_run_for_non_tool_calling_llm(

backend/onyx/configs/app_configs.py

@@ -170,7 +170,7 @@ POSTGRES_USER = os.environ.get("POSTGRES_USER") or "postgres"
 POSTGRES_PASSWORD = urllib.parse.quote_plus(
     os.environ.get("POSTGRES_PASSWORD") or "password"
 )
-POSTGRES_HOST = os.environ.get("POSTGRES_HOST") or "localhost"
+POSTGRES_HOST = os.environ.get("POSTGRES_HOST") or "127.0.0.1"
 POSTGRES_PORT = os.environ.get("POSTGRES_PORT") or "5432"
 POSTGRES_DB = os.environ.get("POSTGRES_DB") or "postgres"
 AWS_REGION_NAME = os.environ.get("AWS_REGION_NAME") or "us-east-2"
@@ -437,7 +437,7 @@ LINEAR_CLIENT_ID = os.getenv("LINEAR_CLIENT_ID")
 LINEAR_CLIENT_SECRET = os.getenv("LINEAR_CLIENT_SECRET")
 
 # Slack specific configs
-SLACK_NUM_THREADS = int(os.getenv("SLACK_NUM_THREADS") or 2)
+SLACK_NUM_THREADS = int(os.getenv("SLACK_NUM_THREADS") or 8)
 
 DASK_JOB_CLIENT_ENABLED = (
     os.environ.get("DASK_JOB_CLIENT_ENABLED", "").lower() == "true"
@@ -495,6 +495,11 @@ NUM_SECONDARY_INDEXING_WORKERS = int(
 ENABLE_MULTIPASS_INDEXING = (
     os.environ.get("ENABLE_MULTIPASS_INDEXING", "").lower() == "true"
 )
+# Enable contextual retrieval
+ENABLE_CONTEXTUAL_RAG = os.environ.get("ENABLE_CONTEXTUAL_RAG", "").lower() == "true"
+
+DEFAULT_CONTEXTUAL_RAG_LLM_NAME = "gpt-4o-mini"
+DEFAULT_CONTEXTUAL_RAG_LLM_PROVIDER = "DevEnvPresetOpenAI"
 # Finer grained chunking for more detail retention
 # Slightly larger since the sentence aware split is a max cutoff so most minichunks will be under MINI_CHUNK_SIZE
 # tokens. But we need it to be at least as big as 1/4th chunk size to avoid having a tiny mini-chunk at the end
@@ -536,6 +541,17 @@ MAX_FILE_SIZE_BYTES = int(
     os.environ.get("MAX_FILE_SIZE_BYTES") or 2 * 1024 * 1024 * 1024
 )  # 2GB in bytes
 
+# Use document summary for contextual rag
+USE_DOCUMENT_SUMMARY = os.environ.get("USE_DOCUMENT_SUMMARY", "true").lower() == "true"
+# Use chunk summary for contextual rag
+USE_CHUNK_SUMMARY = os.environ.get("USE_CHUNK_SUMMARY", "true").lower() == "true"
+# Average summary embeddings for contextual rag (not yet implemented)
+AVERAGE_SUMMARY_EMBEDDINGS = (
+    os.environ.get("AVERAGE_SUMMARY_EMBEDDINGS", "false").lower() == "true"
+)
+
+MAX_TOKENS_FOR_FULL_INCLUSION = 4096
+
 #####
 # Miscellaneous
 #####

backend/onyx/configs/chat_configs.py

@@ -3,7 +3,7 @@ import os
 INPUT_PROMPT_YAML = "./onyx/seeding/input_prompts.yaml"
 PROMPTS_YAML = "./onyx/seeding/prompts.yaml"
 PERSONAS_YAML = "./onyx/seeding/personas.yaml"
-
+USER_FOLDERS_YAML = "./onyx/seeding/user_folders.yaml"
 NUM_RETURNED_HITS = 50
 # Used for LLM filtering and reranking
 # We want this to be approximately the number of results we want to show on the first page

backend/onyx/configs/constants.py

@@ -102,6 +102,8 @@ CELERY_GENERIC_BEAT_LOCK_TIMEOUT = 120
 
 CELERY_VESPA_SYNC_BEAT_LOCK_TIMEOUT = 120
 
+CELERY_USER_FILE_FOLDER_SYNC_BEAT_LOCK_TIMEOUT = 120
+
 CELERY_PRIMARY_WORKER_LOCK_TIMEOUT = 120
 
 
@@ -269,6 +271,7 @@ class FileOrigin(str, Enum):
     CONNECTOR = "connector"
     GENERATED_REPORT = "generated_report"
     INDEXING_CHECKPOINT = "indexing_checkpoint"
+    PLAINTEXT_CACHE = "plaintext_cache"
     OTHER = "other"
 
 
@@ -309,6 +312,7 @@ class OnyxCeleryQueues:
 
     # Indexing queue
     CONNECTOR_INDEXING = "connector_indexing"
+    USER_FILES_INDEXING = "user_files_indexing"
 
     # Monitoring queue
     MONITORING = "monitoring"
@@ -327,6 +331,7 @@ class OnyxRedisLocks:
     CHECK_CONNECTOR_EXTERNAL_GROUP_SYNC_BEAT_LOCK = (
         "da_lock:check_connector_external_group_sync_beat"
     )
+    CHECK_USER_FILE_FOLDER_SYNC_BEAT_LOCK = "da_lock:check_user_file_folder_sync_beat"
     MONITOR_BACKGROUND_PROCESSES_LOCK = "da_lock:monitor_background_processes"
     CHECK_AVAILABLE_TENANTS_LOCK = "da_lock:check_available_tenants"
     PRE_PROVISION_TENANT_LOCK = "da_lock:pre_provision_tenant"
@@ -382,6 +387,7 @@ ONYX_CLOUD_TENANT_ID = "cloud"
 
 # the redis namespace for runtime variables
 ONYX_CLOUD_REDIS_RUNTIME = "runtime"
+CLOUD_BUILD_FENCE_LOOKUP_TABLE_INTERVAL_DEFAULT = 600
 
 
 class OnyxCeleryTask:
@@ -396,6 +402,7 @@ class OnyxCeleryTask:
 
     # Tenant pre-provisioning
     PRE_PROVISION_TENANT = f"{ONYX_CLOUD_CELERY_TASK_PREFIX}_pre_provision_tenant"
+    UPDATE_USER_FILE_FOLDER_METADATA = "update_user_file_folder_metadata"
 
     CHECK_FOR_CONNECTOR_DELETION = "check_for_connector_deletion_task"
     CHECK_FOR_VESPA_SYNC_TASK = "check_for_vespa_sync_task"
@@ -404,6 +411,7 @@ class OnyxCeleryTask:
     CHECK_FOR_DOC_PERMISSIONS_SYNC = "check_for_doc_permissions_sync"
     CHECK_FOR_EXTERNAL_GROUP_SYNC = "check_for_external_group_sync"
     CHECK_FOR_LLM_MODEL_UPDATE = "check_for_llm_model_update"
+    CHECK_FOR_USER_FILE_FOLDER_SYNC = "check_for_user_file_folder_sync"
 
     # Connector checkpoint cleanup
     CHECK_FOR_CHECKPOINT_CLEANUP = "check_for_checkpoint_cleanup"

backend/onyx/connectors/blob/connector.py

@@ -87,7 +87,7 @@ class BlobStorageConnector(LoadConnector, PollConnector):
                 credentials.get(key)
                 for key in ["aws_access_key_id", "aws_secret_access_key"]
             ):
-                raise ConnectorMissingCredentialError("Google Cloud Storage")
+                raise ConnectorMissingCredentialError("Amazon S3")
 
             session = boto3.Session(
                 aws_access_key_id=credentials["aws_access_key_id"],

backend/onyx/connectors/confluence/connector.py

@@ -65,20 +65,6 @@ _RESTRICTIONS_EXPANSION_FIELDS = [
 
 _SLIM_DOC_BATCH_SIZE = 5000
 
-_ATTACHMENT_EXTENSIONS_TO_FILTER_OUT = [
-    "gif",
-    "mp4",
-    "mov",
-    "mp3",
-    "wav",
-]
-_FULL_EXTENSION_FILTER_STRING = "".join(
-    [
-        f" and title!~'*.{extension}'"
-        for extension in _ATTACHMENT_EXTENSIONS_TO_FILTER_OUT
-    ]
-)
-
 ONE_HOUR = 3600
 
 
@@ -209,7 +195,6 @@ class ConfluenceConnector(
     def _construct_attachment_query(self, confluence_page_id: str) -> str:
         attachment_query = f"type=attachment and container='{confluence_page_id}'"
         attachment_query += self.cql_label_filter
-        attachment_query += _FULL_EXTENSION_FILTER_STRING
         return attachment_query
 
     def _get_comment_string_for_page_id(self, page_id: str) -> str:
@@ -374,11 +359,13 @@ class ConfluenceConnector(
                 if not validate_attachment_filetype(
                     attachment,
                 ):
+                    logger.info(f"Skipping attachment: {attachment['title']}")
                     continue
 
+                logger.info(f"Processing attachment: {attachment['title']}")
+
                 # Attempt to get textual content or image summarization:
                 try:
-                    logger.info(f"Processing attachment: {attachment['title']}")
                     response = convert_attachment_to_content(
                         confluence_client=self.confluence_client,
                         attachment=attachment,

backend/onyx/connectors/egnyte/connector.py

@@ -28,8 +28,9 @@ from onyx.connectors.models import TextSection
 from onyx.file_processing.extract_file_text import detect_encoding
 from onyx.file_processing.extract_file_text import extract_file_text
 from onyx.file_processing.extract_file_text import get_file_ext
+from onyx.file_processing.extract_file_text import is_accepted_file_ext
 from onyx.file_processing.extract_file_text import is_text_file_extension
-from onyx.file_processing.extract_file_text import is_valid_file_ext
+from onyx.file_processing.extract_file_text import OnyxExtensionType
 from onyx.file_processing.extract_file_text import read_text_file
 from onyx.utils.logger import setup_logger
 from onyx.utils.retry_wrapper import request_with_retries
@@ -69,7 +70,9 @@ def _process_egnyte_file(
 
     file_name = file_metadata["name"]
     extension = get_file_ext(file_name)
-    if not is_valid_file_ext(extension):
+    if not is_accepted_file_ext(
+        extension, OnyxExtensionType.Plain | OnyxExtensionType.Document
+    ):
         logger.warning(f"Skipping file '{file_name}' with extension '{extension}'")
         return None
 

backend/onyx/connectors/file/connector.py

@@ -22,8 +22,9 @@ from onyx.db.engine import get_session_with_current_tenant
 from onyx.db.pg_file_store import get_pgfilestore_by_file_name
 from onyx.file_processing.extract_file_text import extract_text_and_images
 from onyx.file_processing.extract_file_text import get_file_ext
-from onyx.file_processing.extract_file_text import is_valid_file_ext
+from onyx.file_processing.extract_file_text import is_accepted_file_ext
 from onyx.file_processing.extract_file_text import load_files_from_zip
+from onyx.file_processing.extract_file_text import OnyxExtensionType
 from onyx.file_processing.image_utils import store_image_and_create_section
 from onyx.file_store.file_store import get_default_file_store
 from onyx.utils.logger import setup_logger
@@ -51,7 +52,7 @@ def _read_files_and_metadata(
             file_content, ignore_dirs=True
         ):
             yield os.path.join(directory_path, file_info.filename), subfile, metadata
-    elif is_valid_file_ext(extension):
+    elif is_accepted_file_ext(extension, OnyxExtensionType.All):
         yield file_name, file_content, metadata
     else:
         logger.warning(f"Skipping file '{file_name}' with extension '{extension}'")
@@ -122,7 +123,7 @@ def _process_file(
         logger.warning(f"No file record found for '{file_name}' in PG; skipping.")
         return []
 
-    if not is_valid_file_ext(extension):
+    if not is_accepted_file_ext(extension, OnyxExtensionType.All):
         logger.warning(
             f"Skipping file '{file_name}' with unrecognized extension '{extension}'"
         )

backend/onyx/connectors/fireflies/connector.py

@@ -45,6 +45,8 @@ _FIREFLIES_API_QUERY = """
     }
 """
 
+ONE_MINUTE = 60
+
 
 def _create_doc_from_transcript(transcript: dict) -> Document | None:
     sections: List[TextSection] = []
@@ -106,6 +108,8 @@ def _create_doc_from_transcript(transcript: dict) -> Document | None:
     )
 
 
+# If not all transcripts are being indexed, try using a more-recently-generated
+# API key.
 class FirefliesConnector(PollConnector, LoadConnector):
     def __init__(self, batch_size: int = INDEX_BATCH_SIZE) -> None:
         self.batch_size = batch_size
@@ -191,6 +195,9 @@ class FirefliesConnector(PollConnector, LoadConnector):
     def poll_source(
         self, start: SecondsSinceUnixEpoch, end: SecondsSinceUnixEpoch
     ) -> GenerateDocumentsOutput:
+        # add some leeway to account for any timezone funkiness and/or bad handling
+        # of start time on the Fireflies side
+        start = max(0, start - ONE_MINUTE)
         start_datetime = datetime.fromtimestamp(start, tz=timezone.utc).strftime(
             "%Y-%m-%dT%H:%M:%S.000Z"
         )

backend/onyx/connectors/github/connector.py

@@ -276,7 +276,26 @@ class GithubConnector(CheckpointConnector[GithubConnectorCheckpoint]):
             return checkpoint
 
         assert checkpoint.cached_repo is not None, "No repo saved in checkpoint"
-        repo = checkpoint.cached_repo.to_Repository(self.github_client.requester)
+
+        # Try to access the requester - different PyGithub versions may use different attribute names
+        try:
+            # Try direct access to a known attribute name first
+            if hasattr(self.github_client, "_requester"):
+                requester = self.github_client._requester
+            elif hasattr(self.github_client, "_Github__requester"):
+                requester = self.github_client._Github__requester
+            else:
+                # If we can't find the requester attribute, we need to fall back to recreating the repo
+                raise AttributeError("Could not find requester attribute")
+
+            repo = checkpoint.cached_repo.to_Repository(requester)
+        except Exception as e:
+            # If all else fails, re-fetch the repo directly
+            logger.warning(
+                f"Failed to deserialize repository: {e}. Attempting to re-fetch."
+            )
+            repo_id = checkpoint.cached_repo.id
+            repo = self.github_client.get_repo(repo_id)
 
         if self.include_prs and checkpoint.stage == GithubConnectorStage.PRS:
             logger.info(f"Fetching PRs for repo: {repo.name}")

backend/onyx/connectors/google_drive/connector.py

@@ -28,7 +28,9 @@ from onyx.connectors.google_drive.doc_conversion import (
 )
 from onyx.connectors.google_drive.file_retrieval import crawl_folders_for_files
 from onyx.connectors.google_drive.file_retrieval import get_all_files_for_oauth
-from onyx.connectors.google_drive.file_retrieval import get_all_files_in_my_drive
+from onyx.connectors.google_drive.file_retrieval import (
+    get_all_files_in_my_drive_and_shared,
+)
 from onyx.connectors.google_drive.file_retrieval import get_files_in_shared_drive
 from onyx.connectors.google_drive.file_retrieval import get_root_folder_id
 from onyx.connectors.google_drive.models import DriveRetrievalStage
@@ -86,13 +88,18 @@ def _extract_ids_from_urls(urls: list[str]) -> list[str]:
 
 def _convert_single_file(
     creds: Any,
-    primary_admin_email: str,
     allow_images: bool,
     size_threshold: int,
+    retriever_email: str,
     file: dict[str, Any],
 ) -> Document | ConnectorFailure | None:
-    user_email = file.get("owners", [{}])[0].get("emailAddress") or primary_admin_email
+    # We used to always get the user email from the file owners when available,
+    # but this was causing issues with shared folders where the owner was not included in the service account
+    # now we use the email of the account that successfully listed the file. Leaving this in case we end up
+    # wanting to retry with file owners and/or admin email at some point.
+    # user_email = file.get("owners", [{}])[0].get("emailAddress") or primary_admin_email
 
+    user_email = retriever_email
     # Only construct these services when needed
     user_drive_service = lazy_eval(
         lambda: get_drive_service(creds, user_email=user_email)
@@ -450,10 +457,11 @@ class GoogleDriveConnector(SlimConnector, CheckpointConnector[GoogleDriveCheckpo
                 logger.info(f"Getting all files in my drive as '{user_email}'")
 
                 yield from add_retrieval_info(
-                    get_all_files_in_my_drive(
+                    get_all_files_in_my_drive_and_shared(
                         service=drive_service,
                         update_traversed_ids_func=self._update_traversed_parent_ids,
                         is_slim=is_slim,
+                        include_shared_with_me=self.include_files_shared_with_me,
                         start=curr_stage.completed_until if resuming else start,
                         end=end,
                     ),
@@ -916,20 +924,28 @@ class GoogleDriveConnector(SlimConnector, CheckpointConnector[GoogleDriveCheckpo
             convert_func = partial(
                 _convert_single_file,
                 self.creds,
-                self.primary_admin_email,
                 self.allow_images,
                 self.size_threshold,
             )
             # Fetch files in batches
             batches_complete = 0
-            files_batch: list[GoogleDriveFileType] = []
+            files_batch: list[RetrievedDriveFile] = []
 
             def _yield_batch(
-                files_batch: list[GoogleDriveFileType],
+                files_batch: list[RetrievedDriveFile],
             ) -> Iterator[Document | ConnectorFailure]:
                 nonlocal batches_complete
                 # Process the batch using run_functions_tuples_in_parallel
-                func_with_args = [(convert_func, (file,)) for file in files_batch]
+                func_with_args = [
+                    (
+                        convert_func,
+                        (
+                            file.user_email,
+                            file.drive_file,
+                        ),
+                    )
+                    for file in files_batch
+                ]
                 results = cast(
                     list[Document | ConnectorFailure | None],
                     run_functions_tuples_in_parallel(func_with_args, max_workers=8),
@@ -967,7 +983,7 @@ class GoogleDriveConnector(SlimConnector, CheckpointConnector[GoogleDriveCheckpo
                     )
 
                     continue
-                files_batch.append(retrieved_file.drive_file)
+                files_batch.append(retrieved_file)
 
                 if len(files_batch) < self.batch_size:
                     continue

backend/onyx/connectors/google_drive/doc_conversion.py

@@ -30,6 +30,7 @@ from onyx.file_processing.file_validation import is_valid_image_type
 from onyx.file_processing.image_summarization import summarize_image_with_error_handling
 from onyx.file_processing.image_utils import store_image_and_create_section
 from onyx.llm.interfaces import LLM
+from onyx.utils.lazy import lazy_eval
 from onyx.utils.logger import setup_logger
 
 logger = setup_logger()
@@ -76,6 +77,26 @@ def is_gdrive_image_mime_type(mime_type: str) -> bool:
     return is_valid_image_type(mime_type)
 
 
+def download_request(service: GoogleDriveService, file_id: str) -> bytes:
+    """
+    Download the file from Google Drive.
+    """
+    # For other file types, download the file
+    # Use the correct API call for downloading files
+    request = service.files().get_media(fileId=file_id)
+    response_bytes = io.BytesIO()
+    downloader = MediaIoBaseDownload(response_bytes, request)
+    done = False
+    while not done:
+        _, done = downloader.next_chunk()
+
+    response = response_bytes.getvalue()
+    if not response:
+        logger.warning(f"Failed to download {file_id}")
+        return bytes()
+    return response
+
+
 def _download_and_extract_sections_basic(
     file: dict[str, str],
     service: GoogleDriveService,
@@ -87,35 +108,17 @@ def _download_and_extract_sections_basic(
     mime_type = file["mimeType"]
     link = file.get("webViewLink", "")
 
-    try:
-        # skip images if not explicitly enabled
-        if not allow_images and is_gdrive_image_mime_type(mime_type):
-            return []
+    # skip images if not explicitly enabled
+    if not allow_images and is_gdrive_image_mime_type(mime_type):
+        return []
 
-        # For Google Docs, Sheets, and Slides, export as plain text
-        if mime_type in GOOGLE_MIME_TYPES_TO_EXPORT:
-            export_mime_type = GOOGLE_MIME_TYPES_TO_EXPORT[mime_type]
-            # Use the correct API call for exporting files
-            request = service.files().export_media(
-                fileId=file_id, mimeType=export_mime_type
-            )
-            response_bytes = io.BytesIO()
-            downloader = MediaIoBaseDownload(response_bytes, request)
-            done = False
-            while not done:
-                _, done = downloader.next_chunk()
-
-            response = response_bytes.getvalue()
-            if not response:
-                logger.warning(f"Failed to export {file_name} as {export_mime_type}")
-                return []
-
-            text = response.decode("utf-8")
-            return [TextSection(link=link, text=text)]
-
-        # For other file types, download the file
-        # Use the correct API call for downloading files
-        request = service.files().get_media(fileId=file_id)
+    # For Google Docs, Sheets, and Slides, export as plain text
+    if mime_type in GOOGLE_MIME_TYPES_TO_EXPORT:
+        export_mime_type = GOOGLE_MIME_TYPES_TO_EXPORT[mime_type]
+        # Use the correct API call for exporting files
+        request = service.files().export_media(
+            fileId=file_id, mimeType=export_mime_type
+        )
         response_bytes = io.BytesIO()
         downloader = MediaIoBaseDownload(response_bytes, request)
         done = False
@@ -124,88 +127,97 @@ def _download_and_extract_sections_basic(
 
         response = response_bytes.getvalue()
         if not response:
-            logger.warning(f"Failed to download {file_name}")
+            logger.warning(f"Failed to export {file_name} as {export_mime_type}")
             return []
 
-        # Process based on mime type
-        if mime_type == "text/plain":
-            text = response.decode("utf-8")
-            return [TextSection(link=link, text=text)]
+        text = response.decode("utf-8")
+        return [TextSection(link=link, text=text)]
 
-        elif (
-            mime_type
-            == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
-        ):
-            text, _ = docx_to_text_and_images(io.BytesIO(response))
-            return [TextSection(link=link, text=text)]
+    # For other file types, download the file
+    # Use the correct API call for downloading files
+    response_call = lazy_eval(lambda: download_request(service, file_id))
 
-        elif (
-            mime_type
-            == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
-        ):
-            text = xlsx_to_text(io.BytesIO(response))
-            return [TextSection(link=link, text=text)]
+    # Process based on mime type
+    if mime_type == "text/plain":
+        text = response_call().decode("utf-8")
+        return [TextSection(link=link, text=text)]
 
-        elif (
-            mime_type
-            == "application/vnd.openxmlformats-officedocument.presentationml.presentation"
-        ):
-            text = pptx_to_text(io.BytesIO(response))
-            return [TextSection(link=link, text=text)]
+    elif (
+        mime_type
+        == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+    ):
+        text, _ = docx_to_text_and_images(io.BytesIO(response_call()))
+        return [TextSection(link=link, text=text)]
 
-        elif is_gdrive_image_mime_type(mime_type):
-            # For images, store them for later processing
-            sections: list[TextSection | ImageSection] = []
-            try:
-                with get_session_with_current_tenant() as db_session:
+    elif (
+        mime_type == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
+    ):
+        text = xlsx_to_text(io.BytesIO(response_call()))
+        return [TextSection(link=link, text=text)]
+
+    elif (
+        mime_type
+        == "application/vnd.openxmlformats-officedocument.presentationml.presentation"
+    ):
+        text = pptx_to_text(io.BytesIO(response_call()))
+        return [TextSection(link=link, text=text)]
+
+    elif is_gdrive_image_mime_type(mime_type):
+        # For images, store them for later processing
+        sections: list[TextSection | ImageSection] = []
+        try:
+            with get_session_with_current_tenant() as db_session:
+                section, embedded_id = store_image_and_create_section(
+                    db_session=db_session,
+                    image_data=response_call(),
+                    file_name=file_id,
+                    display_name=file_name,
+                    media_type=mime_type,
+                    file_origin=FileOrigin.CONNECTOR,
+                    link=link,
+                )
+                sections.append(section)
+        except Exception as e:
+            logger.error(f"Failed to process image {file_name}: {e}")
+        return sections
+
+    elif mime_type == "application/pdf":
+        text, _pdf_meta, images = read_pdf_file(io.BytesIO(response_call()))
+        pdf_sections: list[TextSection | ImageSection] = [
+            TextSection(link=link, text=text)
+        ]
+
+        # Process embedded images in the PDF
+        try:
+            with get_session_with_current_tenant() as db_session:
+                for idx, (img_data, img_name) in enumerate(images):
                     section, embedded_id = store_image_and_create_section(
                         db_session=db_session,
-                        image_data=response,
-                        file_name=file_id,
-                        display_name=file_name,
-                        media_type=mime_type,
+                        image_data=img_data,
+                        file_name=f"{file_id}_img_{idx}",
+                        display_name=img_name or f"{file_name} - image {idx}",
                         file_origin=FileOrigin.CONNECTOR,
-                        link=link,
                     )
-                    sections.append(section)
-            except Exception as e:
-                logger.error(f"Failed to process image {file_name}: {e}")
-            return sections
+                    pdf_sections.append(section)
+        except Exception as e:
+            logger.error(f"Failed to process PDF images in {file_name}: {e}")
+        return pdf_sections
 
-        elif mime_type == "application/pdf":
-            text, _pdf_meta, images = read_pdf_file(io.BytesIO(response))
-            pdf_sections: list[TextSection | ImageSection] = [
-                TextSection(link=link, text=text)
-            ]
-
-            # Process embedded images in the PDF
-            try:
-                with get_session_with_current_tenant() as db_session:
-                    for idx, (img_data, img_name) in enumerate(images):
-                        section, embedded_id = store_image_and_create_section(
-                            db_session=db_session,
-                            image_data=img_data,
-                            file_name=f"{file_id}_img_{idx}",
-                            display_name=img_name or f"{file_name} - image {idx}",
-                            file_origin=FileOrigin.CONNECTOR,
-                        )
-                        pdf_sections.append(section)
-            except Exception as e:
-                logger.error(f"Failed to process PDF images in {file_name}: {e}")
-            return pdf_sections
-
-        else:
-            # For unsupported file types, try to extract text
-            try:
-                text = extract_file_text(io.BytesIO(response), file_name)
-                return [TextSection(link=link, text=text)]
-            except Exception as e:
-                logger.warning(f"Failed to extract text from {file_name}: {e}")
-                return []
-
-    except Exception as e:
-        logger.error(f"Error processing file {file_name}: {e}")
-        return []
+    else:
+        # For unsupported file types, try to extract text
+        if mime_type in [
+            "application/vnd.google-apps.video",
+            "application/vnd.google-apps.audio",
+            "application/zip",
+        ]:
+            return []
+        # For unsupported file types, try to extract text
+        try:
+            text = extract_file_text(io.BytesIO(response_call()), file_name)
+            return [TextSection(link=link, text=text)]
+        except Exception as e:
+            logger.warning(f"Failed to extract text from {file_name}: {e}")
+            return []
 
 
 def convert_drive_item_to_document(

backend/onyx/connectors/google_drive/file_retrieval.py

@@ -214,10 +214,11 @@ def get_files_in_shared_drive(
         yield file
 
 
-def get_all_files_in_my_drive(
+def get_all_files_in_my_drive_and_shared(
     service: GoogleDriveService,
     update_traversed_ids_func: Callable,
     is_slim: bool,
+    include_shared_with_me: bool,
     start: SecondsSinceUnixEpoch | None = None,
     end: SecondsSinceUnixEpoch | None = None,
 ) -> Iterator[GoogleDriveFileType]:
@@ -229,7 +230,8 @@ def get_all_files_in_my_drive(
     # Get all folders being queried and add them to the traversed set
     folder_query = f"mimeType = '{DRIVE_FOLDER_TYPE}'"
     folder_query += " and trashed = false"
-    folder_query += " and 'me' in owners"
+    if not include_shared_with_me:
+        folder_query += " and 'me' in owners"
     found_folders = False
     for file in execute_paginated_retrieval(
         retrieval_function=service.files().list,
@@ -246,7 +248,8 @@ def get_all_files_in_my_drive(
     # Then get the files
     file_query = f"mimeType != '{DRIVE_FOLDER_TYPE}'"
     file_query += " and trashed = false"
-    file_query += " and 'me' in owners"
+    if not include_shared_with_me:
+        file_query += " and 'me' in owners"
     file_query += _generate_time_range_filter(start, end)
     yield from execute_paginated_retrieval(
         retrieval_function=service.files().list,

backend/onyx/connectors/highspot/client.py

@@ -75,7 +75,7 @@ class HighspotClient:
 
         self.key = key
         self.secret = secret
-        self.base_url = base_url
+        self.base_url = base_url.rstrip("/") + "/"
         self.timeout = timeout
 
         # Set up session with retry logic

backend/onyx/connectors/highspot/connector.py

@@ -20,8 +20,8 @@ from onyx.connectors.models import ConnectorMissingCredentialError
 from onyx.connectors.models import Document
 from onyx.connectors.models import SlimDocument
 from onyx.connectors.models import TextSection
+from onyx.file_processing.extract_file_text import ALL_ACCEPTED_FILE_EXTENSIONS
 from onyx.file_processing.extract_file_text import extract_file_text
-from onyx.file_processing.extract_file_text import VALID_FILE_EXTENSIONS
 from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from onyx.utils.logger import setup_logger
 
@@ -298,7 +298,7 @@ class HighspotConnector(LoadConnector, PollConnector, SlimConnector):
 
             elif (
                 is_valid_format
-                and file_extension in VALID_FILE_EXTENSIONS
+                and file_extension in ALL_ACCEPTED_FILE_EXTENSIONS
                 and can_download
             ):
                 # For documents, try to get the text content

backend/onyx/connectors/models.py

@@ -163,6 +163,9 @@ class DocumentBase(BaseModel):
                 attributes.append(k + INDEX_SEPARATOR + v)
         return attributes
 
+    def get_text_content(self) -> str:
+        return " ".join([section.text for section in self.sections if section.text])
+
 
 class Document(DocumentBase):
     """Used for Onyx ingestion api, the ID is required"""

backend/onyx/connectors/slack/connector.py

@@ -14,6 +14,8 @@ from typing import cast
 from pydantic import BaseModel
 from slack_sdk import WebClient
 from slack_sdk.errors import SlackApiError
+from slack_sdk.http_retry import ConnectionErrorRetryHandler
+from slack_sdk.http_retry import RetryHandler
 from typing_extensions import override
 
 from onyx.configs.app_configs import ENABLE_EXPENSIVE_EXPERT_CALLS
@@ -26,6 +28,8 @@ from onyx.connectors.exceptions import InsufficientPermissionsError
 from onyx.connectors.exceptions import UnexpectedValidationError
 from onyx.connectors.interfaces import CheckpointConnector
 from onyx.connectors.interfaces import CheckpointOutput
+from onyx.connectors.interfaces import CredentialsConnector
+from onyx.connectors.interfaces import CredentialsProviderInterface
 from onyx.connectors.interfaces import GenerateSlimDocumentOutput
 from onyx.connectors.interfaces import SecondsSinceUnixEpoch
 from onyx.connectors.interfaces import SlimConnector
@@ -38,15 +42,16 @@ from onyx.connectors.models import DocumentFailure
 from onyx.connectors.models import EntityFailure
 from onyx.connectors.models import SlimDocument
 from onyx.connectors.models import TextSection
+from onyx.connectors.slack.onyx_retry_handler import OnyxRedisSlackRetryHandler
 from onyx.connectors.slack.utils import expert_info_from_slack_id
 from onyx.connectors.slack.utils import get_message_link
 from onyx.connectors.slack.utils import make_paginated_slack_api_call_w_retries
 from onyx.connectors.slack.utils import make_slack_api_call_w_retries
 from onyx.connectors.slack.utils import SlackTextCleaner
 from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
+from onyx.redis.redis_pool import get_redis_client
 from onyx.utils.logger import setup_logger
 
-
 logger = setup_logger()
 
 _SLACK_LIMIT = 900
@@ -493,9 +498,13 @@ def _process_message(
         )
 
 
-class SlackConnector(SlimConnector, CheckpointConnector[SlackCheckpoint]):
+class SlackConnector(
+    SlimConnector, CredentialsConnector, CheckpointConnector[SlackCheckpoint]
+):
     FAST_TIMEOUT = 1
 
+    MAX_RETRIES = 7  # arbitrarily selected
+
     def __init__(
         self,
         channels: list[str] | None = None,
@@ -514,16 +523,49 @@ class SlackConnector(SlimConnector, CheckpointConnector[SlackCheckpoint]):
         # just used for efficiency
         self.text_cleaner: SlackTextCleaner | None = None
         self.user_cache: dict[str, BasicExpertInfo | None] = {}
+        self.credentials_provider: CredentialsProviderInterface | None = None
+        self.credential_prefix: str | None = None
+        self.delay_lock: str | None = None  # the redis key for the shared lock
+        self.delay_key: str | None = None  # the redis key for the shared delay
 
     def load_credentials(self, credentials: dict[str, Any]) -> dict[str, Any] | None:
+        raise NotImplementedError("Use set_credentials_provider with this connector.")
+
+    def set_credentials_provider(
+        self, credentials_provider: CredentialsProviderInterface
+    ) -> None:
+        credentials = credentials_provider.get_credentials()
+        tenant_id = credentials_provider.get_tenant_id()
+        self.redis = get_redis_client(tenant_id=tenant_id)
+
+        self.credential_prefix = (
+            f"connector:slack:credential_{credentials_provider.get_provider_key()}"
+        )
+        self.delay_lock = f"{self.credential_prefix}:delay_lock"
+        self.delay_key = f"{self.credential_prefix}:delay"
+
+        # NOTE: slack has a built in RateLimitErrorRetryHandler, but it isn't designed
+        # for concurrent workers. We've extended it with OnyxRedisSlackRetryHandler.
+        connection_error_retry_handler = ConnectionErrorRetryHandler()
+        onyx_rate_limit_error_retry_handler = OnyxRedisSlackRetryHandler(
+            max_retry_count=self.MAX_RETRIES,
+            delay_lock=self.delay_lock,
+            delay_key=self.delay_key,
+            r=self.redis,
+        )
+        custom_retry_handlers: list[RetryHandler] = [
+            connection_error_retry_handler,
+            onyx_rate_limit_error_retry_handler,
+        ]
+
         bot_token = credentials["slack_bot_token"]
-        self.client = WebClient(token=bot_token)
+        self.client = WebClient(token=bot_token, retry_handlers=custom_retry_handlers)
         # use for requests that must return quickly (e.g. realtime flows where user is waiting)
         self.fast_client = WebClient(
             token=bot_token, timeout=SlackConnector.FAST_TIMEOUT
         )
         self.text_cleaner = SlackTextCleaner(client=self.client)
-        return None
+        self.credentials_provider = credentials_provider
 
     def retrieve_all_slim_documents(
         self,

backend/onyx/connectors/slack/onyx_retry_handler.py

@@ -0,0 +1,159 @@
+import math
+import random
+import time
+from typing import cast
+from typing import Optional
+
+from redis import Redis
+from redis.lock import Lock as RedisLock
+from slack_sdk.http_retry.handler import RetryHandler
+from slack_sdk.http_retry.request import HttpRequest
+from slack_sdk.http_retry.response import HttpResponse
+from slack_sdk.http_retry.state import RetryState
+
+from onyx.utils.logger import setup_logger
+
+logger = setup_logger()
+
+
+class OnyxRedisSlackRetryHandler(RetryHandler):
+    """
+    This class uses Redis to share a rate limit among multiple threads.
+
+    Threads that encounter a rate limit will observe the shared delay, increment the
+    shared delay with the retry value, and use the new shared value as a wait interval.
+
+    This has the effect of serializing calls when a rate limit is hit, which is what
+    needs to happens if the server punishes us with additional limiting when we make
+    a call too early. We believe this is what Slack is doing based on empirical
+    observation, meaning we see indefinite hangs if we're too aggressive.
+
+    Another way to do this is just to do exponential backoff. Might be easier?
+
+    Adapted from slack's RateLimitErrorRetryHandler.
+    """
+
+    LOCK_TTL = 60  # used to serialize access to the retry TTL
+    LOCK_BLOCKING_TIMEOUT = 60  # how long to wait for the lock
+
+    """RetryHandler that does retries for rate limited errors."""
+
+    def __init__(
+        self,
+        max_retry_count: int,
+        delay_lock: str,
+        delay_key: str,
+        r: Redis,
+    ):
+        """
+        delay_lock: the redis key to use with RedisLock (to synchronize access to delay_key)
+        delay_key: the redis key containing a shared TTL
+        """
+        super().__init__(max_retry_count=max_retry_count)
+        self._redis: Redis = r
+        self._delay_lock = delay_lock
+        self._delay_key = delay_key
+
+    def _can_retry(
+        self,
+        *,
+        state: RetryState,
+        request: HttpRequest,
+        response: Optional[HttpResponse] = None,
+        error: Optional[Exception] = None,
+    ) -> bool:
+        return response is not None and response.status_code == 429
+
+    def prepare_for_next_attempt(
+        self,
+        *,
+        state: RetryState,
+        request: HttpRequest,
+        response: Optional[HttpResponse] = None,
+        error: Optional[Exception] = None,
+    ) -> None:
+        """It seems this function is responsible for the wait to retry ... aka we
+        actually sleep in this function."""
+        retry_after_value: list[str] | None = None
+        retry_after_header_name: Optional[str] = None
+        duration_s: float = 1.0  # seconds
+
+        if response is None:
+            # NOTE(rkuo): this logic comes from RateLimitErrorRetryHandler.
+            # This reads oddly, as if the caller itself could raise the exception.
+            # We don't have the luxury of changing this.
+            if error:
+                raise error
+
+            return
+
+        state.next_attempt_requested = True  # this signals the caller to retry
+
+        # calculate wait duration based on retry-after + some jitter
+        for k in response.headers.keys():
+            if k.lower() == "retry-after":
+                retry_after_header_name = k
+                break
+
+        try:
+            if retry_after_header_name is None:
+                # This situation usually does not arise. Just in case.
+                raise ValueError(
+                    "OnyxRedisSlackRetryHandler.prepare_for_next_attempt: retry-after header name is None"
+                )
+
+            retry_after_value = response.headers.get(retry_after_header_name)
+            if not retry_after_value:
+                raise ValueError(
+                    "OnyxRedisSlackRetryHandler.prepare_for_next_attempt: retry-after header value is None"
+                )
+
+            retry_after_value_int = int(
+                retry_after_value[0]
+            )  # will raise ValueError if somehow we can't convert to int
+            jitter = retry_after_value_int * 0.25 * random.random()
+            duration_s = math.ceil(retry_after_value_int + jitter)
+        except ValueError:
+            duration_s += random.random()
+
+        # lock and extend the ttl
+        lock: RedisLock = self._redis.lock(
+            self._delay_lock,
+            timeout=OnyxRedisSlackRetryHandler.LOCK_TTL,
+            thread_local=False,
+        )
+
+        acquired = lock.acquire(
+            blocking_timeout=OnyxRedisSlackRetryHandler.LOCK_BLOCKING_TIMEOUT / 2
+        )
+
+        ttl_ms: int | None = None
+
+        try:
+            if acquired:
+                # if we can get the lock, then read and extend the ttl
+                ttl_ms = cast(int, self._redis.pttl(self._delay_key))
+                if ttl_ms < 0:  # negative values are error status codes ... see docs
+                    ttl_ms = 0
+                ttl_ms_new = ttl_ms + int(duration_s * 1000.0)
+                self._redis.set(self._delay_key, "1", px=ttl_ms_new)
+            else:
+                # if we can't get the lock, just go ahead.
+                # TODO: if we know our actual parallelism, multiplying by that
+                # would be a pretty good idea
+                ttl_ms_new = int(duration_s * 1000.0)
+        finally:
+            if acquired:
+                lock.release()
+
+        logger.warning(
+            f"OnyxRedisSlackRetryHandler.prepare_for_next_attempt wait: "
+            f"retry-after={retry_after_value} "
+            f"shared_delay_ms={ttl_ms} new_shared_delay_ms={ttl_ms_new}"
+        )
+
+        # TODO: would be good to take an event var and sleep in short increments to
+        # allow for a clean exit / exception
+        time.sleep(ttl_ms_new / 1000.0)
+
+        state.increment_current_attempt()

backend/onyx/connectors/slack/utils.py

@@ -1,5 +1,4 @@
 import re
-import time
 from collections.abc import Callable
 from collections.abc import Generator
 from functools import lru_cache
@@ -64,71 +63,72 @@ def _make_slack_api_call_paginated(
     return paginated_call
 
 
-def make_slack_api_rate_limited(
-    call: Callable[..., SlackResponse], max_retries: int = 7
-) -> Callable[..., SlackResponse]:
-    """Wraps calls to slack API so that they automatically handle rate limiting"""
+# NOTE(rkuo): we may not need this any more if the integrated retry handlers work as
+# expected.  Do we want to keep this around?
 
-    @wraps(call)
-    def rate_limited_call(**kwargs: Any) -> SlackResponse:
-        last_exception = None
+# def make_slack_api_rate_limited(
+#     call: Callable[..., SlackResponse], max_retries: int = 7
+# ) -> Callable[..., SlackResponse]:
+#     """Wraps calls to slack API so that they automatically handle rate limiting"""
 
-        for _ in range(max_retries):
-            try:
-                # Make the API call
-                response = call(**kwargs)
+#     @wraps(call)
+#     def rate_limited_call(**kwargs: Any) -> SlackResponse:
+#         last_exception = None
 
-                # Check for errors in the response, will raise `SlackApiError`
-                # if anything went wrong
-                response.validate()
-                return response
+#         for _ in range(max_retries):
+#             try:
+#                 # Make the API call
+#                 response = call(**kwargs)
 
-            except SlackApiError as e:
-                last_exception = e
-                try:
-                    error = e.response["error"]
-                except KeyError:
-                    error = "unknown error"
+#                 # Check for errors in the response, will raise `SlackApiError`
+#                 # if anything went wrong
+#                 response.validate()
+#                 return response
 
-                if error == "ratelimited":
-                    # Handle rate limiting: get the 'Retry-After' header value and sleep for that duration
-                    retry_after = int(e.response.headers.get("Retry-After", 1))
-                    logger.info(
-                        f"Slack call rate limited, retrying after {retry_after} seconds. Exception: {e}"
-                    )
-                    time.sleep(retry_after)
-                elif error in ["already_reacted", "no_reaction", "internal_error"]:
-                    # Log internal_error and return the response instead of failing
-                    logger.warning(
-                        f"Slack call encountered '{error}', skipping and continuing..."
-                    )
-                    return e.response
-                else:
-                    # Raise the error for non-transient errors
-                    raise
+#             except SlackApiError as e:
+#                 last_exception = e
+#                 try:
+#                     error = e.response["error"]
+#                 except KeyError:
+#                     error = "unknown error"
 
-        # If the code reaches this point, all retries have been exhausted
-        msg = f"Max retries ({max_retries}) exceeded"
-        if last_exception:
-            raise Exception(msg) from last_exception
-        else:
-            raise Exception(msg)
+#                 if error == "ratelimited":
+#                     # Handle rate limiting: get the 'Retry-After' header value and sleep for that duration
+#                     retry_after = int(e.response.headers.get("Retry-After", 1))
+#                     logger.info(
+#                         f"Slack call rate limited, retrying after {retry_after} seconds. Exception: {e}"
+#                     )
+#                     time.sleep(retry_after)
+#                 elif error in ["already_reacted", "no_reaction", "internal_error"]:
+#                     # Log internal_error and return the response instead of failing
+#                     logger.warning(
+#                         f"Slack call encountered '{error}', skipping and continuing..."
+#                     )
+#                     return e.response
+#                 else:
+#                     # Raise the error for non-transient errors
+#                     raise
 
-    return rate_limited_call
+#         # If the code reaches this point, all retries have been exhausted
+#         msg = f"Max retries ({max_retries}) exceeded"
+#         if last_exception:
+#             raise Exception(msg) from last_exception
+#         else:
+#             raise Exception(msg)
+
+#     return rate_limited_call
 
 
 def make_slack_api_call_w_retries(
     call: Callable[..., SlackResponse], **kwargs: Any
 ) -> SlackResponse:
-    return basic_retry_wrapper(make_slack_api_rate_limited(call))(**kwargs)
+    return basic_retry_wrapper(call)(**kwargs)
 
 
 def make_paginated_slack_api_call_w_retries(
     call: Callable[..., SlackResponse], **kwargs: Any
 ) -> Generator[dict[str, Any], None, None]:
-    return _make_slack_api_call_paginated(
-        basic_retry_wrapper(make_slack_api_rate_limited(call))
-    )(**kwargs)
+    return _make_slack_api_call_paginated(basic_retry_wrapper(call))(**kwargs)
 
 
 def expert_info_from_slack_id(
@@ -142,7 +142,7 @@ def expert_info_from_slack_id(
     if user_id in user_cache:
         return user_cache[user_id]
 
-    response = make_slack_api_rate_limited(client.users_info)(user=user_id)
+    response = client.users_info(user=user_id)
 
     if not response["ok"]:
         user_cache[user_id] = None
@@ -175,9 +175,7 @@ class SlackTextCleaner:
     def _get_slack_name(self, user_id: str) -> str:
         if user_id not in self._id_to_name_map:
             try:
-                response = make_slack_api_rate_limited(self._client.users_info)(
-                    user=user_id
-                )
+                response = self._client.users_info(user=user_id)
                 # prefer display name if set, since that is what is shown in Slack
                 self._id_to_name_map[user_id] = (
                     response["user"]["profile"]["display_name"]

backend/onyx/context/search/models.py

@@ -60,7 +60,7 @@ class SearchSettingsCreationRequest(InferenceSettings, IndexingSetting):
         inference_settings = InferenceSettings.from_db_model(search_settings)
         indexing_setting = IndexingSetting.from_db_model(search_settings)
 
-        return cls(**inference_settings.dict(), **indexing_setting.dict())
+        return cls(**inference_settings.model_dump(), **indexing_setting.model_dump())
 
 
 class SavedSearchSettings(InferenceSettings, IndexingSetting):
@@ -80,6 +80,9 @@ class SavedSearchSettings(InferenceSettings, IndexingSetting):
             reduced_dimension=search_settings.reduced_dimension,
             # Whether switching to this model requires re-indexing
             background_reindex_enabled=search_settings.background_reindex_enabled,
+            enable_contextual_rag=search_settings.enable_contextual_rag,
+            contextual_rag_llm_name=search_settings.contextual_rag_llm_name,
+            contextual_rag_llm_provider=search_settings.contextual_rag_llm_provider,
             # Reranking Details
             rerank_model_name=search_settings.rerank_model_name,
             rerank_provider_type=search_settings.rerank_provider_type,
@@ -102,6 +105,8 @@ class BaseFilters(BaseModel):
     document_set: list[str] | None = None
     time_cutoff: datetime | None = None
     tags: list[Tag] | None = None
+    user_file_ids: list[int] | None = None
+    user_folder_ids: list[int] | None = None
 
 
 class IndexFilters(BaseFilters):
@@ -218,6 +223,8 @@ class InferenceChunk(BaseChunk):
     # to specify that a set of words should be highlighted. For example:
     # ["<hi>the</hi> <hi>answer</hi> is 42", "he couldn't find an <hi>answer</hi>"]
     match_highlights: list[str]
+    doc_summary: str
+    chunk_context: str
 
     # when the doc was last updated
     updated_at: datetime | None

backend/onyx/context/search/pipeline.py

@@ -158,6 +158,47 @@ class SearchPipeline:
 
         return cast(list[InferenceChunk], self._retrieved_chunks)
 
+    def get_ordering_only_chunks(
+        self,
+        query: str,
+        user_file_ids: list[int] | None = None,
+        user_folder_ids: list[int] | None = None,
+    ) -> list[InferenceChunk]:
+        """Optimized method that only retrieves chunks for ordering purposes.
+        Skips all extra processing and uses minimal configuration to speed up retrieval.
+        """
+        logger.info("Fast path: Using optimized chunk retrieval for ordering-only mode")
+
+        # Create minimal filters with just user file/folder IDs
+        filters = IndexFilters(
+            user_file_ids=user_file_ids or [],
+            user_folder_ids=user_folder_ids or [],
+            access_control_list=None,
+        )
+
+        # Use a simplified query that skips all unnecessary processing
+        minimal_query = SearchQuery(
+            query=query,
+            search_type=SearchType.SEMANTIC,
+            filters=filters,
+            # Set minimal options needed for retrieval
+            evaluation_type=LLMEvaluationType.SKIP,
+            recency_bias_multiplier=1.0,
+            chunks_above=0,  # No need for surrounding context
+            chunks_below=0,  # No need for surrounding context
+            processed_keywords=[],  # Empty list instead of None
+            rerank_settings=None,
+            hybrid_alpha=0.0,
+            max_llm_filter_sections=0,
+        )
+
+        # Retrieve chunks using the minimal configuration
+        return retrieve_chunks(
+            query=minimal_query,
+            document_index=self.document_index,
+            db_session=self.db_session,
+        )
+
     @log_function_time(print_only=True)
     def _get_sections(self) -> list[InferenceSection]:
         """Returns an expanded section from each of the chunks.
@@ -339,6 +380,12 @@ class SearchPipeline:
         self._retrieved_sections = self._get_sections()
         return self._retrieved_sections
 
+    @property
+    def merged_retrieved_sections(self) -> list[InferenceSection]:
+        """Should be used to display in the UI in order to prevent displaying
+        multiple sections for the same document as separate "documents"."""
+        return _merge_sections(sections=self.retrieved_sections)
+
     @property
     def reranked_sections(self) -> list[InferenceSection]:
         """Reranking is always done at the chunk level since section merging could create arbitrarily
@@ -385,6 +432,10 @@ class SearchPipeline:
             self.search_query.evaluation_type == LLMEvaluationType.SKIP
             or DISABLE_LLM_DOC_RELEVANCE
         ):
+            if self.search_query.evaluation_type == LLMEvaluationType.SKIP:
+                logger.info(
+                    "Fast path: Skipping section relevance evaluation for ordering-only mode"
+                )
             return None
 
         if self.search_query.evaluation_type == LLMEvaluationType.UNSPECIFIED:
@@ -415,6 +466,10 @@ class SearchPipeline:
                 raise ValueError(
                     "Basic search evaluation operation called while DISABLE_LLM_DOC_RELEVANCE is enabled."
                 )
+            # NOTE: final_context_sections must be accessed before accessing self._postprocessing_generator
+            # since the property sets the generator. DO NOT REMOVE.
+            _ = self.final_context_sections
+
             self._section_relevance = next(
                 cast(
                     Iterator[list[SectionRelevancePiece]],

backend/onyx/context/search/postprocessing/postprocessing.py

@@ -11,6 +11,7 @@ from langchain_core.messages import SystemMessage
 from onyx.chat.models import SectionRelevancePiece
 from onyx.configs.app_configs import BLURB_SIZE
 from onyx.configs.app_configs import IMAGE_ANALYSIS_SYSTEM_PROMPT
+from onyx.configs.chat_configs import DISABLE_LLM_DOC_RELEVANCE
 from onyx.configs.constants import RETURN_SEPARATOR
 from onyx.configs.llm_configs import get_search_time_image_analysis_enabled
 from onyx.configs.model_configs import CROSS_ENCODER_RANGE_MAX
@@ -196,9 +197,21 @@ def cleanup_chunks(chunks: list[InferenceChunkUncleaned]) -> list[InferenceChunk
             RETURN_SEPARATOR
         )
 
+    def _remove_contextual_rag(chunk: InferenceChunkUncleaned) -> str:
+        # remove document summary
+        if chunk.content.startswith(chunk.doc_summary):
+            chunk.content = chunk.content[len(chunk.doc_summary) :].lstrip()
+        # remove chunk context
+        if chunk.content.endswith(chunk.chunk_context):
+            chunk.content = chunk.content[
+                : len(chunk.content) - len(chunk.chunk_context)
+            ].rstrip()
+        return chunk.content
+
     for chunk in chunks:
         chunk.content = _remove_title(chunk)
         chunk.content = _remove_metadata_suffix(chunk)
+        chunk.content = _remove_contextual_rag(chunk)
 
     return [chunk.to_inference_chunk() for chunk in chunks]
 
@@ -354,6 +367,21 @@ def filter_sections(
 
     Returns a list of the unique chunk IDs that were marked as relevant
     """
+    # Log evaluation type to help with debugging
+    logger.info(f"filter_sections called with evaluation_type={query.evaluation_type}")
+
+    # Fast path: immediately return empty list for SKIP evaluation type (ordering-only mode)
+    if query.evaluation_type == LLMEvaluationType.SKIP:
+        return []
+
+    # Additional safeguard: Log a warning if this function is ever called with SKIP evaluation type
+    # This should never happen if our fast paths are working correctly
+    if query.evaluation_type == LLMEvaluationType.SKIP:
+        logger.warning(
+            "WARNING: filter_sections called with SKIP evaluation_type. This should never happen!"
+        )
+        return []
+
     sections_to_filter = sections_to_filter[: query.max_llm_filter_sections]
 
     contents = [
@@ -386,6 +414,16 @@ def search_postprocessing(
     llm: LLM,
     rerank_metrics_callback: Callable[[RerankMetricsContainer], None] | None = None,
 ) -> Iterator[list[InferenceSection] | list[SectionRelevancePiece]]:
+    # Fast path for ordering-only: detect it by checking if evaluation_type is SKIP
+    if search_query.evaluation_type == LLMEvaluationType.SKIP:
+        logger.info(
+            "Fast path: Detected ordering-only mode, bypassing all post-processing"
+        )
+        # Immediately yield the sections without any processing and an empty relevance list
+        yield retrieved_sections
+        yield cast(list[SectionRelevancePiece], [])
+        return
+
     post_processing_tasks: list[FunctionCall] = []
 
     if not retrieved_sections:
@@ -422,10 +460,14 @@ def search_postprocessing(
         sections_yielded = True
 
     llm_filter_task_id = None
-    if search_query.evaluation_type in [
-        LLMEvaluationType.BASIC,
-        LLMEvaluationType.UNSPECIFIED,
-    ]:
+    # Only add LLM filtering if not in SKIP mode and if LLM doc relevance is not disabled
+    if (
+        search_query.evaluation_type not in [LLMEvaluationType.SKIP]
+        and not DISABLE_LLM_DOC_RELEVANCE
+        and search_query.evaluation_type
+        in [LLMEvaluationType.BASIC, LLMEvaluationType.UNSPECIFIED]
+    ):
+        logger.info("Adding LLM filtering task for document relevance evaluation")
         post_processing_tasks.append(
             FunctionCall(
                 filter_sections,
@@ -437,6 +479,10 @@ def search_postprocessing(
             )
         )
         llm_filter_task_id = post_processing_tasks[-1].result_id
+    elif search_query.evaluation_type == LLMEvaluationType.SKIP:
+        logger.info("Fast path: Skipping LLM filtering task for ordering-only mode")
+    elif DISABLE_LLM_DOC_RELEVANCE:
+        logger.info("Skipping LLM filtering task because LLM doc relevance is disabled")
 
     post_processing_results = (
         run_functions_in_parallel(post_processing_tasks)

backend/onyx/context/search/preprocessing/preprocessing.py

@@ -165,7 +165,18 @@ def retrieval_preprocessing(
     user_acl_filters = (
         None if bypass_acl else build_access_filters_for_user(user, db_session)
     )
+    user_file_ids = preset_filters.user_file_ids or []
+    user_folder_ids = preset_filters.user_folder_ids or []
+    if persona and persona.user_files:
+        user_file_ids = user_file_ids + [
+            file.id
+            for file in persona.user_files
+            if file.id not in (preset_filters.user_file_ids or [])
+        ]
+
     final_filters = IndexFilters(
+        user_file_ids=user_file_ids,
+        user_folder_ids=user_folder_ids,
         source_type=preset_filters.source_type or predicted_source_filters,
         document_set=preset_filters.document_set,
         time_cutoff=time_filter or predicted_time_cutoff,

backend/onyx/db/chat.py

@@ -26,6 +26,7 @@ from onyx.agents.agent_search.shared_graph_utils.models import (
 from onyx.auth.schemas import UserRole
 from onyx.chat.models import DocumentRelevance
 from onyx.configs.chat_configs import HARD_DELETE_CHATS
+from onyx.configs.constants import DocumentSource
 from onyx.configs.constants import MessageType
 from onyx.context.search.models import InferenceSection
 from onyx.context.search.models import RetrievalDocs
@@ -44,9 +45,11 @@ from onyx.db.models import SearchDoc
 from onyx.db.models import SearchDoc as DBSearchDoc
 from onyx.db.models import ToolCall
 from onyx.db.models import User
+from onyx.db.models import UserFile
 from onyx.db.persona import get_best_persona_id_for_user
 from onyx.db.pg_file_store import delete_lobj_by_name
 from onyx.file_store.models import FileDescriptor
+from onyx.file_store.models import InMemoryChatFile
 from onyx.llm.override_models import LLMOverride
 from onyx.llm.override_models import PromptOverride
 from onyx.server.query_and_chat.models import ChatMessageDetail
@@ -854,6 +857,87 @@ def get_db_search_doc_by_id(doc_id: int, db_session: Session) -> DBSearchDoc | N
     return search_doc
 
 
+def create_search_doc_from_user_file(
+    db_user_file: UserFile, associated_chat_file: InMemoryChatFile, db_session: Session
+) -> SearchDoc:
+    """Create a SearchDoc in the database from a UserFile and return it.
+    This ensures proper ID generation by SQLAlchemy and prevents duplicate key errors.
+    """
+    blurb = ""
+    if associated_chat_file and associated_chat_file.content:
+        try:
+            # Try to decode as UTF-8, but handle errors gracefully
+            content_sample = associated_chat_file.content[:100]
+            # Remove null bytes which can cause SQL errors
+            content_sample = content_sample.replace(b"\x00", b"")
+            blurb = content_sample.decode("utf-8", errors="replace")
+        except Exception:
+            # If decoding fails completely, provide a generic description
+            blurb = f"[Binary file: {db_user_file.name}]"
+
+    db_search_doc = SearchDoc(
+        document_id=db_user_file.document_id,
+        chunk_ind=0,  # Default to 0 for user files
+        semantic_id=db_user_file.name,
+        link=db_user_file.link_url,
+        blurb=blurb,
+        source_type=DocumentSource.FILE,  # Assuming internal source for user files
+        boost=0,  # Default boost
+        hidden=False,  # Default visibility
+        doc_metadata={},  # Empty metadata
+        score=0.0,  # Default score of 0.0 instead of None
+        is_relevant=None,  # No relevance initially
+        relevance_explanation=None,  # No explanation initially
+        match_highlights=[],  # No highlights initially
+        updated_at=db_user_file.created_at,  # Use created_at as updated_at
+        primary_owners=[],  # Empty list instead of None
+        secondary_owners=[],  # Empty list instead of None
+        is_internet=False,  # Not from internet
+    )
+
+    db_session.add(db_search_doc)
+    db_session.flush()  # Get the ID but don't commit yet
+
+    return db_search_doc
+
+
+def translate_db_user_file_to_search_doc(
+    db_user_file: UserFile, associated_chat_file: InMemoryChatFile
+) -> SearchDoc:
+    blurb = ""
+    if associated_chat_file and associated_chat_file.content:
+        try:
+            # Try to decode as UTF-8, but handle errors gracefully
+            content_sample = associated_chat_file.content[:100]
+            # Remove null bytes which can cause SQL errors
+            content_sample = content_sample.replace(b"\x00", b"")
+            blurb = content_sample.decode("utf-8", errors="replace")
+        except Exception:
+            # If decoding fails completely, provide a generic description
+            blurb = f"[Binary file: {db_user_file.name}]"
+
+    return SearchDoc(
+        # Don't set ID - let SQLAlchemy auto-generate it
+        document_id=db_user_file.document_id,
+        chunk_ind=0,  # Default to 0 for user files
+        semantic_id=db_user_file.name,
+        link=db_user_file.link_url,
+        blurb=blurb,
+        source_type=DocumentSource.FILE,  # Assuming internal source for user files
+        boost=0,  # Default boost
+        hidden=False,  # Default visibility
+        doc_metadata={},  # Empty metadata
+        score=0.0,  # Default score of 0.0 instead of None
+        is_relevant=None,  # No relevance initially
+        relevance_explanation=None,  # No explanation initially
+        match_highlights=[],  # No highlights initially
+        updated_at=db_user_file.created_at,  # Use created_at as updated_at
+        primary_owners=[],  # Empty list instead of None
+        secondary_owners=[],  # Empty list instead of None
+        is_internet=False,  # Not from internet
+    )
+
+
 def translate_db_search_doc_to_server_search_doc(
     db_search_doc: SearchDoc,
     remove_doc_content: bool = False,
@@ -1089,3 +1173,20 @@ def log_agent_sub_question_results(
             db_session.commit()
 
     return None
+
+
+def update_chat_session_updated_at_timestamp(
+    chat_session_id: UUID, db_session: Session
+) -> None:
+    """
+    Explicitly update the timestamp on a chat session without modifying other fields.
+    This is useful when adding messages to a chat session to reflect recent activity.
+    """
+
+    # Direct SQL update to avoid loading the entire object if it's not already loaded
+    db_session.execute(
+        update(ChatSession)
+        .where(ChatSession.id == chat_session_id)
+        .values(time_updated=func.now())
+    )
+    # No commit - the caller is responsible for committing the transaction

backend/onyx/db/connector_credential_pair.py

@@ -27,6 +27,7 @@ from onyx.db.models import IndexModelStatus
 from onyx.db.models import SearchSettings
 from onyx.db.models import User
 from onyx.db.models import User__UserGroup
+from onyx.db.models import UserFile
 from onyx.db.models import UserGroup__ConnectorCredentialPair
 from onyx.db.models import UserRole
 from onyx.server.models import StatusResponse
@@ -106,11 +107,13 @@ def get_connector_credential_pairs_for_user(
     eager_load_connector: bool = False,
     eager_load_credential: bool = False,
     eager_load_user: bool = False,
+    include_user_files: bool = False,
 ) -> list[ConnectorCredentialPair]:
     if eager_load_user:
         assert (
             eager_load_credential
         ), "eager_load_credential must be True if eager_load_user is True"
+
     stmt = select(ConnectorCredentialPair).distinct()
 
     if eager_load_connector:
@@ -126,6 +129,9 @@ def get_connector_credential_pairs_for_user(
     if ids:
         stmt = stmt.where(ConnectorCredentialPair.id.in_(ids))
 
+    if not include_user_files:
+        stmt = stmt.where(ConnectorCredentialPair.is_user_file != True)  # noqa: E712
+
     return list(db_session.scalars(stmt).unique().all())
 
 
@@ -153,14 +159,16 @@ def get_connector_credential_pairs_for_user_parallel(
 
 
 def get_connector_credential_pairs(
-    db_session: Session,
-    ids: list[int] | None = None,
+    db_session: Session, ids: list[int] | None = None, include_user_files: bool = False
 ) -> list[ConnectorCredentialPair]:
     stmt = select(ConnectorCredentialPair).distinct()
 
     if ids:
         stmt = stmt.where(ConnectorCredentialPair.id.in_(ids))
 
+    if not include_user_files:
+        stmt = stmt.where(ConnectorCredentialPair.is_user_file != True)  # noqa: E712
+
     return list(db_session.scalars(stmt).all())
 
 
@@ -207,12 +215,15 @@ def get_connector_credential_pair_for_user(
     connector_id: int,
     credential_id: int,
     user: User | None,
+    include_user_files: bool = False,
     get_editable: bool = True,
 ) -> ConnectorCredentialPair | None:
     stmt = select(ConnectorCredentialPair)
     stmt = _add_user_filters(stmt, user, get_editable)
     stmt = stmt.where(ConnectorCredentialPair.connector_id == connector_id)
     stmt = stmt.where(ConnectorCredentialPair.credential_id == credential_id)
+    if not include_user_files:
+        stmt = stmt.where(ConnectorCredentialPair.is_user_file != True)  # noqa: E712
     result = db_session.execute(stmt)
     return result.scalar_one_or_none()
 
@@ -321,6 +332,9 @@ def _update_connector_credential_pair(
         cc_pair.total_docs_indexed += net_docs
     if status is not None:
         cc_pair.status = status
+    if cc_pair.is_user_file:
+        cc_pair.status = ConnectorCredentialPairStatus.PAUSED
+
     db_session.commit()
 
 
@@ -446,6 +460,7 @@ def add_credential_to_connector(
     initial_status: ConnectorCredentialPairStatus = ConnectorCredentialPairStatus.ACTIVE,
     last_successful_index_time: datetime | None = None,
     seeding_flow: bool = False,
+    is_user_file: bool = False,
 ) -> StatusResponse:
     connector = fetch_connector_by_id(connector_id, db_session)
 
@@ -511,6 +526,7 @@ def add_credential_to_connector(
         access_type=access_type,
         auto_sync_options=auto_sync_options,
         last_successful_index_time=last_successful_index_time,
+        is_user_file=is_user_file,
     )
     db_session.add(association)
     db_session.flush()  # make sure the association has an id
@@ -587,8 +603,12 @@ def remove_credential_from_connector(
 
 def fetch_connector_credential_pairs(
     db_session: Session,
+    include_user_files: bool = False,
 ) -> list[ConnectorCredentialPair]:
-    return db_session.query(ConnectorCredentialPair).all()
+    stmt = select(ConnectorCredentialPair)
+    if not include_user_files:
+        stmt = stmt.where(ConnectorCredentialPair.is_user_file != True)  # noqa: E712
+    return list(db_session.scalars(stmt).unique().all())
 
 
 def resync_cc_pair(
@@ -634,3 +654,23 @@ def resync_cc_pair(
     )
 
     db_session.commit()
+
+
+def get_connector_credential_pairs_with_user_files(
+    db_session: Session,
+) -> list[ConnectorCredentialPair]:
+    """
+    Get all connector credential pairs that have associated user files.
+
+    Args:
+        db_session: Database session
+
+    Returns:
+        List of ConnectorCredentialPair objects that have user files
+    """
+    return (
+        db_session.query(ConnectorCredentialPair)
+        .join(UserFile, UserFile.cc_pair_id == ConnectorCredentialPair.id)
+        .distinct()
+        .all()
+    )

backend/onyx/db/document_set.py

@@ -605,7 +605,6 @@ def fetch_document_sets_for_document(
     result = fetch_document_sets_for_documents([document_id], db_session)
     if not result:
         return []
-
     return result[0][1]
 
 

backend/onyx/db/models.py

@@ -212,6 +212,10 @@ class User(SQLAlchemyBaseUserTableUUID, Base):
         back_populates="creator",
         primaryjoin="User.id == foreign(ConnectorCredentialPair.creator_id)",
     )
+    folders: Mapped[list["UserFolder"]] = relationship(
+        "UserFolder", back_populates="user"
+    )
+    files: Mapped[list["UserFile"]] = relationship("UserFile", back_populates="user")
 
     @validates("email")
     def validate_email(self, key: str, value: str) -> str:
@@ -419,6 +423,7 @@ class ConnectorCredentialPair(Base):
     """
 
     __tablename__ = "connector_credential_pair"
+    is_user_file: Mapped[bool] = mapped_column(Boolean, default=False)
     # NOTE: this `id` column has to use `Sequence` instead of `autoincrement=True`
     # due to some SQLAlchemy quirks + this not being a primary key column
     id: Mapped[int] = mapped_column(
@@ -505,6 +510,10 @@ class ConnectorCredentialPair(Base):
         primaryjoin="foreign(ConnectorCredentialPair.creator_id) == remote(User.id)",
     )
 
+    user_file: Mapped["UserFile"] = relationship(
+        "UserFile", back_populates="cc_pair", uselist=False
+    )
+
     background_errors: Mapped[list["BackgroundError"]] = relationship(
         "BackgroundError", back_populates="cc_pair", cascade="all, delete-orphan"
     )
@@ -791,6 +800,15 @@ class SearchSettings(Base):
     # Mini and Large Chunks (large chunk also checks for model max context)
     multipass_indexing: Mapped[bool] = mapped_column(Boolean, default=True)
 
+    # Contextual RAG
+    enable_contextual_rag: Mapped[bool] = mapped_column(Boolean, default=False)
+
+    # Contextual RAG LLM
+    contextual_rag_llm_name: Mapped[str | None] = mapped_column(String, nullable=True)
+    contextual_rag_llm_provider: Mapped[str | None] = mapped_column(
+        String, nullable=True
+    )
+
     multilingual_expansion: Mapped[list[str]] = mapped_column(
         postgresql.ARRAY(String), default=[]
     )
@@ -1799,6 +1817,17 @@ class Persona(Base):
         secondary="persona__user_group",
         viewonly=True,
     )
+    # Relationship to UserFile
+    user_files: Mapped[list["UserFile"]] = relationship(
+        "UserFile",
+        secondary="persona__user_file",
+        back_populates="assistants",
+    )
+    user_folders: Mapped[list["UserFolder"]] = relationship(
+        "UserFolder",
+        secondary="persona__user_folder",
+        back_populates="assistants",
+    )
     labels: Mapped[list["PersonaLabel"]] = relationship(
         "PersonaLabel",
         secondary=Persona__PersonaLabel.__table__,
@@ -1815,6 +1844,24 @@ class Persona(Base):
     )
 
 
+class Persona__UserFolder(Base):
+    __tablename__ = "persona__user_folder"
+
+    persona_id: Mapped[int] = mapped_column(ForeignKey("persona.id"), primary_key=True)
+    user_folder_id: Mapped[int] = mapped_column(
+        ForeignKey("user_folder.id"), primary_key=True
+    )
+
+
+class Persona__UserFile(Base):
+    __tablename__ = "persona__user_file"
+
+    persona_id: Mapped[int] = mapped_column(ForeignKey("persona.id"), primary_key=True)
+    user_file_id: Mapped[int] = mapped_column(
+        ForeignKey("user_file.id"), primary_key=True
+    )
+
+
 class PersonaLabel(Base):
     __tablename__ = "persona_label"
 
@@ -2337,6 +2384,64 @@ class InputPrompt__User(Base):
     disabled: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
 
 
+class UserFolder(Base):
+    __tablename__ = "user_folder"
+
+    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
+    user_id: Mapped[UUID | None] = mapped_column(ForeignKey("user.id"), nullable=False)
+    name: Mapped[str] = mapped_column(nullable=False)
+    description: Mapped[str] = mapped_column(nullable=False)
+    created_at: Mapped[datetime.datetime] = mapped_column(
+        DateTime(timezone=True), server_default=func.now()
+    )
+    user: Mapped["User"] = relationship(back_populates="folders")
+    files: Mapped[list["UserFile"]] = relationship(back_populates="folder")
+    assistants: Mapped[list["Persona"]] = relationship(
+        "Persona",
+        secondary=Persona__UserFolder.__table__,
+        back_populates="user_folders",
+    )
+
+
+class UserDocument(str, Enum):
+    CHAT = "chat"
+    RECENT = "recent"
+    FILE = "file"
+
+
+class UserFile(Base):
+    __tablename__ = "user_file"
+
+    id: Mapped[int] = mapped_column(primary_key=True, autoincrement=True)
+    user_id: Mapped[UUID | None] = mapped_column(ForeignKey("user.id"), nullable=False)
+    assistants: Mapped[list["Persona"]] = relationship(
+        "Persona",
+        secondary=Persona__UserFile.__table__,
+        back_populates="user_files",
+    )
+    folder_id: Mapped[int | None] = mapped_column(
+        ForeignKey("user_folder.id"), nullable=True
+    )
+
+    file_id: Mapped[str] = mapped_column(nullable=False)
+    document_id: Mapped[str] = mapped_column(nullable=False)
+    name: Mapped[str] = mapped_column(nullable=False)
+    created_at: Mapped[datetime.datetime] = mapped_column(
+        default=datetime.datetime.utcnow
+    )
+    user: Mapped["User"] = relationship(back_populates="files")
+    folder: Mapped["UserFolder"] = relationship(back_populates="files")
+    token_count: Mapped[int | None] = mapped_column(Integer, nullable=True)
+
+    cc_pair_id: Mapped[int | None] = mapped_column(
+        ForeignKey("connector_credential_pair.id"), nullable=True, unique=True
+    )
+    cc_pair: Mapped["ConnectorCredentialPair"] = relationship(
+        "ConnectorCredentialPair", back_populates="user_file"
+    )
+    link_url: Mapped[str | None] = mapped_column(String, nullable=True)
+
+
 """
 Multi-tenancy related tables
 """

backend/onyx/db/persona.py

@@ -33,6 +33,8 @@ from onyx.db.models import StarterMessage
 from onyx.db.models import Tool
 from onyx.db.models import User
 from onyx.db.models import User__UserGroup
+from onyx.db.models import UserFile
+from onyx.db.models import UserFolder
 from onyx.db.models import UserGroup
 from onyx.db.notification import create_notification
 from onyx.server.features.persona.models import PersonaSharedNotificationData
@@ -209,7 +211,6 @@ def create_update_persona(
         if not all_prompt_ids:
             raise ValueError("No prompt IDs provided")
 
-        is_default_persona: bool | None = create_persona_request.is_default_persona
         # Default persona validation
         if create_persona_request.is_default_persona:
             if not create_persona_request.is_public:
@@ -221,7 +222,7 @@ def create_update_persona(
                     user.role == UserRole.CURATOR
                     or user.role == UserRole.GLOBAL_CURATOR
                 ):
-                    is_default_persona = None
+                    pass
                 elif user.role != UserRole.ADMIN:
                     raise ValueError("Only admins can make a default persona")
 
@@ -249,7 +250,9 @@ def create_update_persona(
             num_chunks=create_persona_request.num_chunks,
             llm_relevance_filter=create_persona_request.llm_relevance_filter,
             llm_filter_extraction=create_persona_request.llm_filter_extraction,
-            is_default_persona=is_default_persona,
+            is_default_persona=create_persona_request.is_default_persona,
+            user_file_ids=create_persona_request.user_file_ids,
+            user_folder_ids=create_persona_request.user_folder_ids,
         )
 
         versioned_make_persona_private = fetch_versioned_implementation(
@@ -344,6 +347,8 @@ def get_personas_for_user(
             selectinload(Persona.groups),
             selectinload(Persona.users),
             selectinload(Persona.labels),
+            selectinload(Persona.user_files),
+            selectinload(Persona.user_folders),
         )
 
     results = db_session.execute(stmt).scalars().all()
@@ -438,6 +443,8 @@ def upsert_persona(
     builtin_persona: bool = False,
     is_default_persona: bool | None = None,
     label_ids: list[int] | None = None,
+    user_file_ids: list[int] | None = None,
+    user_folder_ids: list[int] | None = None,
     chunks_above: int = CONTEXT_CHUNKS_ABOVE,
     chunks_below: int = CONTEXT_CHUNKS_BELOW,
 ) -> Persona:
@@ -463,6 +470,7 @@ def upsert_persona(
             user=user,
             get_editable=True,
         )
+
     # Fetch and attach tools by IDs
     tools = None
     if tool_ids is not None:
@@ -481,6 +489,26 @@ def upsert_persona(
         if not document_sets and document_set_ids:
             raise ValueError("document_sets not found")
 
+    # Fetch and attach user_files by IDs
+    user_files = None
+    if user_file_ids is not None:
+        user_files = (
+            db_session.query(UserFile).filter(UserFile.id.in_(user_file_ids)).all()
+        )
+        if not user_files and user_file_ids:
+            raise ValueError("user_files not found")
+
+    # Fetch and attach user_folders by IDs
+    user_folders = None
+    if user_folder_ids is not None:
+        user_folders = (
+            db_session.query(UserFolder)
+            .filter(UserFolder.id.in_(user_folder_ids))
+            .all()
+        )
+        if not user_folders and user_folder_ids:
+            raise ValueError("user_folders not found")
+
     # Fetch and attach prompts by IDs
     prompts = None
     if prompt_ids is not None:
@@ -549,6 +577,14 @@ def upsert_persona(
         if tools is not None:
             existing_persona.tools = tools or []
 
+        if user_file_ids is not None:
+            existing_persona.user_files.clear()
+            existing_persona.user_files = user_files or []
+
+        if user_folder_ids is not None:
+            existing_persona.user_folders.clear()
+            existing_persona.user_folders = user_folders or []
+
         # We should only update display priority if it is not already set
         if existing_persona.display_priority is None:
             existing_persona.display_priority = display_priority
@@ -590,6 +626,8 @@ def upsert_persona(
             is_default_persona=is_default_persona
             if is_default_persona is not None
             else False,
+            user_folders=user_folders or [],
+            user_files=user_files or [],
             labels=labels or [],
         )
         db_session.add(new_persona)

backend/onyx/db/search_settings.py

@@ -62,6 +62,9 @@ def create_search_settings(
         multipass_indexing=search_settings.multipass_indexing,
         embedding_precision=search_settings.embedding_precision,
         reduced_dimension=search_settings.reduced_dimension,
+        enable_contextual_rag=search_settings.enable_contextual_rag,
+        contextual_rag_llm_name=search_settings.contextual_rag_llm_name,
+        contextual_rag_llm_provider=search_settings.contextual_rag_llm_provider,
         multilingual_expansion=search_settings.multilingual_expansion,
         disable_rerank_for_streaming=search_settings.disable_rerank_for_streaming,
         rerank_model_name=search_settings.rerank_model_name,
@@ -319,6 +322,7 @@ def get_old_default_embedding_model() -> IndexingSetting:
         passage_prefix=(ASYM_PASSAGE_PREFIX if is_overridden else ""),
         index_name="danswer_chunk",
         multipass_indexing=False,
+        enable_contextual_rag=False,
         api_url=None,
     )
 
@@ -333,5 +337,6 @@ def get_new_default_embedding_model() -> IndexingSetting:
         passage_prefix=ASYM_PASSAGE_PREFIX,
         index_name=f"danswer_chunk_{clean_model_name(DOCUMENT_ENCODER_MODEL)}",
         multipass_indexing=False,
+        enable_contextual_rag=False,
         api_url=None,
     )

backend/onyx/db/user_documents.py

@@ -0,0 +1,466 @@
+import datetime
+import time
+from typing import List
+from uuid import UUID
+
+from fastapi import UploadFile
+from sqlalchemy import and_
+from sqlalchemy import func
+from sqlalchemy.orm import joinedload
+from sqlalchemy.orm import Session
+
+from onyx.auth.users import get_current_tenant_id
+from onyx.configs.constants import DocumentSource
+from onyx.connectors.models import InputType
+from onyx.db.connector import create_connector
+from onyx.db.connector_credential_pair import add_credential_to_connector
+from onyx.db.credentials import create_credential
+from onyx.db.enums import AccessType
+from onyx.db.models import ConnectorCredentialPair
+from onyx.db.models import Document
+from onyx.db.models import DocumentByConnectorCredentialPair
+from onyx.db.models import Persona
+from onyx.db.models import Persona__UserFile
+from onyx.db.models import User
+from onyx.db.models import UserFile
+from onyx.db.models import UserFolder
+from onyx.server.documents.connector import trigger_indexing_for_cc_pair
+from onyx.server.documents.connector import upload_files
+from onyx.server.documents.models import ConnectorBase
+from onyx.server.documents.models import CredentialBase
+from onyx.server.models import StatusResponse
+
+USER_FILE_CONSTANT = "USER_FILE_CONNECTOR"
+
+
+def create_user_files(
+    files: List[UploadFile],
+    folder_id: int | None,
+    user: User | None,
+    db_session: Session,
+    link_url: str | None = None,
+) -> list[UserFile]:
+    upload_response = upload_files(files, db_session)
+    user_files = []
+
+    for file_path, file in zip(upload_response.file_paths, files):
+        new_file = UserFile(
+            user_id=user.id if user else None,
+            folder_id=folder_id,
+            file_id=file_path,
+            document_id="USER_FILE_CONNECTOR__" + file_path,
+            name=file.filename,
+            token_count=None,
+            link_url=link_url,
+        )
+        db_session.add(new_file)
+        user_files.append(new_file)
+    db_session.commit()
+    return user_files
+
+
+def create_user_file_with_indexing(
+    files: List[UploadFile],
+    folder_id: int | None,
+    user: User,
+    db_session: Session,
+    trigger_index: bool = True,
+) -> list[UserFile]:
+    """Create user files and trigger immediate indexing"""
+    # Create the user files first
+    user_files = create_user_files(files, folder_id, user, db_session)
+
+    # Create connector and credential for each file
+    for user_file in user_files:
+        cc_pair = create_file_connector_credential(user_file, user, db_session)
+        user_file.cc_pair_id = cc_pair.data
+
+    db_session.commit()
+
+    # Trigger immediate high-priority indexing for all created files
+    if trigger_index:
+        tenant_id = get_current_tenant_id()
+        for user_file in user_files:
+            # Use the existing trigger_indexing_for_cc_pair function but with highest priority
+            if user_file.cc_pair_id:
+                trigger_indexing_for_cc_pair(
+                    [],
+                    user_file.cc_pair.connector_id,
+                    False,
+                    tenant_id,
+                    db_session,
+                    is_user_file=True,
+                )
+
+    return user_files
+
+
+def create_file_connector_credential(
+    user_file: UserFile, user: User, db_session: Session
+) -> StatusResponse:
+    """Create connector and credential for a user file"""
+    connector_base = ConnectorBase(
+        name=f"UserFile-{user_file.file_id}-{int(time.time())}",
+        source=DocumentSource.FILE,
+        input_type=InputType.LOAD_STATE,
+        connector_specific_config={
+            "file_locations": [user_file.file_id],
+        },
+        refresh_freq=None,
+        prune_freq=None,
+        indexing_start=None,
+    )
+
+    connector = create_connector(db_session=db_session, connector_data=connector_base)
+
+    credential_info = CredentialBase(
+        credential_json={},
+        admin_public=True,
+        source=DocumentSource.FILE,
+        curator_public=True,
+        groups=[],
+        name=f"UserFileCredential-{user_file.file_id}-{int(time.time())}",
+        is_user_file=True,
+    )
+
+    credential = create_credential(credential_info, user, db_session)
+
+    return add_credential_to_connector(
+        db_session=db_session,
+        user=user,
+        connector_id=connector.id,
+        credential_id=credential.id,
+        cc_pair_name=f"UserFileCCPair-{user_file.file_id}-{int(time.time())}",
+        access_type=AccessType.PRIVATE,
+        auto_sync_options=None,
+        groups=[],
+        is_user_file=True,
+    )
+
+
+def get_user_file_indexing_status(
+    file_ids: list[int], db_session: Session
+) -> dict[int, bool]:
+    """Get indexing status for multiple user files"""
+    status_dict = {}
+
+    # Query UserFile with cc_pair join
+    files_with_pairs = (
+        db_session.query(UserFile)
+        .filter(UserFile.id.in_(file_ids))
+        .options(joinedload(UserFile.cc_pair))
+        .all()
+    )
+
+    for file in files_with_pairs:
+        if file.cc_pair and file.cc_pair.last_successful_index_time:
+            status_dict[file.id] = True
+        else:
+            status_dict[file.id] = False
+
+    return status_dict
+
+
+def calculate_user_files_token_count(
+    file_ids: list[int], folder_ids: list[int], db_session: Session
+) -> int:
+    """Calculate total token count for specified files and folders"""
+    total_tokens = 0
+
+    # Get tokens from individual files
+    if file_ids:
+        file_tokens = (
+            db_session.query(func.sum(UserFile.token_count))
+            .filter(UserFile.id.in_(file_ids))
+            .scalar()
+            or 0
+        )
+        total_tokens += file_tokens
+
+    # Get tokens from folders
+    if folder_ids:
+        folder_files_tokens = (
+            db_session.query(func.sum(UserFile.token_count))
+            .filter(UserFile.folder_id.in_(folder_ids))
+            .scalar()
+            or 0
+        )
+        total_tokens += folder_files_tokens
+
+    return total_tokens
+
+
+def load_all_user_files(
+    file_ids: list[int], folder_ids: list[int], db_session: Session
+) -> list[UserFile]:
+    """Load all user files from specified file IDs and folder IDs"""
+    result = []
+
+    # Get individual files
+    if file_ids:
+        files = db_session.query(UserFile).filter(UserFile.id.in_(file_ids)).all()
+        result.extend(files)
+
+    # Get files from folders
+    if folder_ids:
+        folder_files = (
+            db_session.query(UserFile).filter(UserFile.folder_id.in_(folder_ids)).all()
+        )
+        result.extend(folder_files)
+
+    return result
+
+
+def get_user_files_from_folder(folder_id: int, db_session: Session) -> list[UserFile]:
+    return db_session.query(UserFile).filter(UserFile.folder_id == folder_id).all()
+
+
+def share_file_with_assistant(
+    file_id: int, assistant_id: int, db_session: Session
+) -> None:
+    file = db_session.query(UserFile).filter(UserFile.id == file_id).first()
+    assistant = db_session.query(Persona).filter(Persona.id == assistant_id).first()
+
+    if file and assistant:
+        file.assistants.append(assistant)
+        db_session.commit()
+
+
+def unshare_file_with_assistant(
+    file_id: int, assistant_id: int, db_session: Session
+) -> None:
+    db_session.query(Persona__UserFile).filter(
+        and_(
+            Persona__UserFile.user_file_id == file_id,
+            Persona__UserFile.persona_id == assistant_id,
+        )
+    ).delete()
+    db_session.commit()
+
+
+def share_folder_with_assistant(
+    folder_id: int, assistant_id: int, db_session: Session
+) -> None:
+    folder = db_session.query(UserFolder).filter(UserFolder.id == folder_id).first()
+    assistant = db_session.query(Persona).filter(Persona.id == assistant_id).first()
+
+    if folder and assistant:
+        for file in folder.files:
+            share_file_with_assistant(file.id, assistant_id, db_session)
+
+
+def unshare_folder_with_assistant(
+    folder_id: int, assistant_id: int, db_session: Session
+) -> None:
+    folder = db_session.query(UserFolder).filter(UserFolder.id == folder_id).first()
+
+    if folder:
+        for file in folder.files:
+            unshare_file_with_assistant(file.id, assistant_id, db_session)
+
+
+def fetch_user_files_for_documents(
+    document_ids: list[str],
+    db_session: Session,
+) -> dict[str, int | None]:
+    """
+    Fetches user file IDs for the given document IDs.
+
+    Args:
+        document_ids: List of document IDs to fetch user files for
+        db_session: Database session
+
+    Returns:
+        Dictionary mapping document IDs to user file IDs (or None if no user file exists)
+    """
+    # First, get the document to cc_pair mapping
+    doc_cc_pairs = (
+        db_session.query(Document.id, ConnectorCredentialPair.id)
+        .join(
+            DocumentByConnectorCredentialPair,
+            Document.id == DocumentByConnectorCredentialPair.id,
+        )
+        .join(
+            ConnectorCredentialPair,
+            and_(
+                DocumentByConnectorCredentialPair.connector_id
+                == ConnectorCredentialPair.connector_id,
+                DocumentByConnectorCredentialPair.credential_id
+                == ConnectorCredentialPair.credential_id,
+            ),
+        )
+        .filter(Document.id.in_(document_ids))
+        .all()
+    )
+
+    # Get cc_pair to user_file mapping
+    cc_pair_to_user_file = (
+        db_session.query(ConnectorCredentialPair.id, UserFile.id)
+        .join(UserFile, UserFile.cc_pair_id == ConnectorCredentialPair.id)
+        .filter(
+            ConnectorCredentialPair.id.in_(
+                [cc_pair_id for _, cc_pair_id in doc_cc_pairs]
+            )
+        )
+        .all()
+    )
+
+    # Create mapping from cc_pair_id to user_file_id
+    cc_pair_to_user_file_dict = {
+        cc_pair_id: user_file_id for cc_pair_id, user_file_id in cc_pair_to_user_file
+    }
+
+    # Create the final result mapping document_id to user_file_id
+    result: dict[str, int | None] = {doc_id: None for doc_id in document_ids}
+    for doc_id, cc_pair_id in doc_cc_pairs:
+        if cc_pair_id in cc_pair_to_user_file_dict:
+            result[doc_id] = cc_pair_to_user_file_dict[cc_pair_id]
+
+    return result
+
+
+def fetch_user_folders_for_documents(
+    document_ids: list[str],
+    db_session: Session,
+) -> dict[str, int | None]:
+    """
+    Fetches user folder IDs for the given document IDs.
+
+    For each document, returns the folder ID that the document's associated user file belongs to.
+
+    Args:
+        document_ids: List of document IDs to fetch user folders for
+        db_session: Database session
+
+    Returns:
+        Dictionary mapping document IDs to user folder IDs (or None if no user folder exists)
+    """
+    # First, get the document to cc_pair mapping
+    doc_cc_pairs = (
+        db_session.query(Document.id, ConnectorCredentialPair.id)
+        .join(
+            DocumentByConnectorCredentialPair,
+            Document.id == DocumentByConnectorCredentialPair.id,
+        )
+        .join(
+            ConnectorCredentialPair,
+            and_(
+                DocumentByConnectorCredentialPair.connector_id
+                == ConnectorCredentialPair.connector_id,
+                DocumentByConnectorCredentialPair.credential_id
+                == ConnectorCredentialPair.credential_id,
+            ),
+        )
+        .filter(Document.id.in_(document_ids))
+        .all()
+    )
+
+    # Get cc_pair to user_file and folder mapping
+    cc_pair_to_folder = (
+        db_session.query(ConnectorCredentialPair.id, UserFile.folder_id)
+        .join(UserFile, UserFile.cc_pair_id == ConnectorCredentialPair.id)
+        .filter(
+            ConnectorCredentialPair.id.in_(
+                [cc_pair_id for _, cc_pair_id in doc_cc_pairs]
+            )
+        )
+        .all()
+    )
+
+    # Create mapping from cc_pair_id to folder_id
+    cc_pair_to_folder_dict = {
+        cc_pair_id: folder_id for cc_pair_id, folder_id in cc_pair_to_folder
+    }
+
+    # Create the final result mapping document_id to folder_id
+    result: dict[str, int | None] = {doc_id: None for doc_id in document_ids}
+    for doc_id, cc_pair_id in doc_cc_pairs:
+        if cc_pair_id in cc_pair_to_folder_dict:
+            result[doc_id] = cc_pair_to_folder_dict[cc_pair_id]
+
+    return result
+
+
+def get_user_file_from_id(db_session: Session, user_file_id: int) -> UserFile | None:
+    return db_session.query(UserFile).filter(UserFile.id == user_file_id).first()
+
+
+# def fetch_user_files_for_documents(
+# #     document_ids: list[str],
+# #     db_session: Session,
+# # ) -> dict[str, int | None]:
+# #     # Query UserFile objects for the given document_ids
+# #     user_files = (
+# #         db_session.query(UserFile).filter(UserFile.document_id.in_(document_ids)).all()
+# #     )
+
+# #     # Create a dictionary mapping document_ids to UserFile objects
+# #     result: dict[str, int | None] = {doc_id: None for doc_id in document_ids}
+# #     for user_file in user_files:
+# #         result[user_file.document_id] = user_file.id
+
+# #     return result
+
+
+def upsert_user_folder(
+    db_session: Session,
+    id: int | None = None,
+    user_id: UUID | None = None,
+    name: str | None = None,
+    description: str | None = None,
+    created_at: datetime.datetime | None = None,
+    user: User | None = None,
+    files: list[UserFile] | None = None,
+    assistants: list[Persona] | None = None,
+) -> UserFolder:
+    if id is not None:
+        user_folder = db_session.query(UserFolder).filter_by(id=id).first()
+    else:
+        user_folder = (
+            db_session.query(UserFolder).filter_by(name=name, user_id=user_id).first()
+        )
+
+    if user_folder:
+        if user_id is not None:
+            user_folder.user_id = user_id
+        if name is not None:
+            user_folder.name = name
+        if description is not None:
+            user_folder.description = description
+        if created_at is not None:
+            user_folder.created_at = created_at
+        if user is not None:
+            user_folder.user = user
+        if files is not None:
+            user_folder.files = files
+        if assistants is not None:
+            user_folder.assistants = assistants
+    else:
+        user_folder = UserFolder(
+            id=id,
+            user_id=user_id,
+            name=name,
+            description=description,
+            created_at=created_at or datetime.datetime.utcnow(),
+            user=user,
+            files=files or [],
+            assistants=assistants or [],
+        )
+        db_session.add(user_folder)
+
+    db_session.flush()
+    return user_folder
+
+
+def get_user_folder_by_name(db_session: Session, name: str) -> UserFolder | None:
+    return db_session.query(UserFolder).filter(UserFolder.name == name).first()
+
+
+def update_user_file_token_count__no_commit(
+    user_file_id_to_token_count: dict[int, int | None],
+    db_session: Session,
+) -> None:
+    for user_file_id, token_count in user_file_id_to_token_count.items():
+        db_session.query(UserFile).filter(UserFile.id == user_file_id).update(
+            {UserFile.token_count: token_count}
+        )

backend/onyx/document_index/interfaces.py

@@ -104,6 +104,16 @@ class VespaDocumentFields:
     aggregated_chunk_boost_factor: float | None = None
 
 
+@dataclass
+class VespaDocumentUserFields:
+    """
+    Fields that are specific to the user who is indexing the document.
+    """
+
+    user_file_id: str | None = None
+    user_folder_id: str | None = None
+
+
 @dataclass
 class UpdateRequest:
     """
@@ -258,7 +268,8 @@ class Updatable(abc.ABC):
         *,
         tenant_id: str,
         chunk_count: int | None,
-        fields: VespaDocumentFields,
+        fields: VespaDocumentFields | None,
+        user_fields: VespaDocumentUserFields | None,
     ) -> int:
         """
         Updates all chunks for a document with the specified fields.

backend/onyx/document_index/vespa/app_config/schemas/danswer_chunk.sd

@@ -98,6 +98,12 @@ schema DANSWER_CHUNK_NAME {
         field metadata type string {
             indexing: summary | attribute
         }
+        field chunk_context type string {
+            indexing: summary | attribute
+        }
+        field doc_summary type string {
+            indexing: summary | attribute
+        }
         field metadata_suffix type string {
             indexing: summary | attribute
         }
@@ -114,12 +120,22 @@ schema DANSWER_CHUNK_NAME {
             indexing: summary | attribute
             rank: filter
             attribute: fast-search
-        }
+        } 
         field document_sets type weightedset<string> {
             indexing: summary | attribute
             rank: filter
             attribute: fast-search
         }
+        field user_file type int {
+            indexing: summary | attribute
+            rank: filter
+            attribute: fast-search
+        }
+        field user_folder type int {
+            indexing: summary | attribute
+            rank: filter
+            attribute: fast-search
+        }
     }
 
     # If using different tokenization settings, the fieldset has to be removed, and the field must

backend/onyx/document_index/vespa/chunk_retrieval.py

@@ -24,9 +24,11 @@ from onyx.document_index.vespa.shared_utils.vespa_request_builders import (
 from onyx.document_index.vespa_constants import ACCESS_CONTROL_LIST
 from onyx.document_index.vespa_constants import BLURB
 from onyx.document_index.vespa_constants import BOOST
+from onyx.document_index.vespa_constants import CHUNK_CONTEXT
 from onyx.document_index.vespa_constants import CHUNK_ID
 from onyx.document_index.vespa_constants import CONTENT
 from onyx.document_index.vespa_constants import CONTENT_SUMMARY
+from onyx.document_index.vespa_constants import DOC_SUMMARY
 from onyx.document_index.vespa_constants import DOC_UPDATED_AT
 from onyx.document_index.vespa_constants import DOCUMENT_ID
 from onyx.document_index.vespa_constants import DOCUMENT_ID_ENDPOINT
@@ -126,7 +128,8 @@ def _vespa_hit_to_inference_chunk(
     return InferenceChunkUncleaned(
         chunk_id=fields[CHUNK_ID],
         blurb=fields.get(BLURB, ""),  # Unused
-        content=fields[CONTENT],  # Includes extra title prefix and metadata suffix
+        content=fields[CONTENT],  # Includes extra title prefix and metadata suffix;
+        # also sometimes context for contextual rag
         source_links=source_links_dict or {0: ""},
         section_continuation=fields[SECTION_CONTINUATION],
         document_id=fields[DOCUMENT_ID],
@@ -143,6 +146,8 @@ def _vespa_hit_to_inference_chunk(
         large_chunk_reference_ids=fields.get(LARGE_CHUNK_REFERENCE_IDS, []),
         metadata=metadata,
         metadata_suffix=fields.get(METADATA_SUFFIX),
+        doc_summary=fields.get(DOC_SUMMARY, ""),
+        chunk_context=fields.get(CHUNK_CONTEXT, ""),
         match_highlights=match_highlights,
         updated_at=updated_at,
     )
@@ -345,6 +350,19 @@ def query_vespa(
     filtered_hits = [hit for hit in hits if hit["fields"].get(CONTENT) is not None]
 
     inference_chunks = [_vespa_hit_to_inference_chunk(hit) for hit in filtered_hits]
+
+    try:
+        num_retrieved_inference_chunks = len(inference_chunks)
+        num_retrieved_document_ids = len(
+            set([chunk.document_id for chunk in inference_chunks])
+        )
+        logger.debug(
+            f"Retrieved {num_retrieved_inference_chunks} inference chunks for {num_retrieved_document_ids} documents"
+        )
+    except Exception as e:
+        # Debug logging only, should not fail the retrieval
+        logger.error(f"Error logging retrieval statistics: {e}")
+
     # Good Debugging Spot
     return inference_chunks
 

backend/onyx/document_index/vespa/index.py

@@ -36,6 +36,7 @@ from onyx.document_index.interfaces import MinimalDocumentIndexingInfo
 from onyx.document_index.interfaces import UpdateRequest
 from onyx.document_index.interfaces import VespaChunkRequest
 from onyx.document_index.interfaces import VespaDocumentFields
+from onyx.document_index.interfaces import VespaDocumentUserFields
 from onyx.document_index.vespa.chunk_retrieval import batch_search_api_retrieval
 from onyx.document_index.vespa.chunk_retrieval import (
     parallel_visit_api_retrieval,
@@ -70,6 +71,8 @@ from onyx.document_index.vespa_constants import NUM_THREADS
 from onyx.document_index.vespa_constants import SEARCH_THREAD_NUMBER_PAT
 from onyx.document_index.vespa_constants import TENANT_ID_PAT
 from onyx.document_index.vespa_constants import TENANT_ID_REPLACEMENT
+from onyx.document_index.vespa_constants import USER_FILE
+from onyx.document_index.vespa_constants import USER_FOLDER
 from onyx.document_index.vespa_constants import VESPA_APPLICATION_ENDPOINT
 from onyx.document_index.vespa_constants import VESPA_DIM_REPLACEMENT_PAT
 from onyx.document_index.vespa_constants import VESPA_TIMEOUT
@@ -187,7 +190,7 @@ class VespaIndex(DocumentIndex):
     ) -> None:
         if MULTI_TENANT:
             logger.info(
-                "Skipping Vespa index seup for multitenant (would wipe all indices)"
+                "Skipping Vespa index setup for multitenant (would wipe all indices)"
             )
             return None
 
@@ -592,7 +595,8 @@ class VespaIndex(DocumentIndex):
         self,
         doc_chunk_id: UUID,
         index_name: str,
-        fields: VespaDocumentFields,
+        fields: VespaDocumentFields | None,
+        user_fields: VespaDocumentUserFields | None,
         doc_id: str,
         http_client: httpx.Client,
     ) -> None:
@@ -603,21 +607,31 @@ class VespaIndex(DocumentIndex):
 
         update_dict: dict[str, dict] = {"fields": {}}
 
-        if fields.boost is not None:
-            update_dict["fields"][BOOST] = {"assign": fields.boost}
+        if fields is not None:
+            if fields.boost is not None:
+                update_dict["fields"][BOOST] = {"assign": fields.boost}
 
-        if fields.document_sets is not None:
-            update_dict["fields"][DOCUMENT_SETS] = {
-                "assign": {document_set: 1 for document_set in fields.document_sets}
-            }
+            if fields.document_sets is not None:
+                update_dict["fields"][DOCUMENT_SETS] = {
+                    "assign": {document_set: 1 for document_set in fields.document_sets}
+                }
 
-        if fields.access is not None:
-            update_dict["fields"][ACCESS_CONTROL_LIST] = {
-                "assign": {acl_entry: 1 for acl_entry in fields.access.to_acl()}
-            }
+            if fields.access is not None:
+                update_dict["fields"][ACCESS_CONTROL_LIST] = {
+                    "assign": {acl_entry: 1 for acl_entry in fields.access.to_acl()}
+                }
 
-        if fields.hidden is not None:
-            update_dict["fields"][HIDDEN] = {"assign": fields.hidden}
+            if fields.hidden is not None:
+                update_dict["fields"][HIDDEN] = {"assign": fields.hidden}
+
+        if user_fields is not None:
+            if user_fields.user_file_id is not None:
+                update_dict["fields"][USER_FILE] = {"assign": user_fields.user_file_id}
+
+            if user_fields.user_folder_id is not None:
+                update_dict["fields"][USER_FOLDER] = {
+                    "assign": user_fields.user_folder_id
+                }
 
         if not update_dict["fields"]:
             logger.error("Update request received but nothing to update.")
@@ -649,7 +663,8 @@ class VespaIndex(DocumentIndex):
         *,
         chunk_count: int | None,
         tenant_id: str,
-        fields: VespaDocumentFields,
+        fields: VespaDocumentFields | None,
+        user_fields: VespaDocumentUserFields | None,
     ) -> int:
         """Note: if the document id does not exist, the update will be a no-op and the
         function will complete with no errors or exceptions.
@@ -682,7 +697,12 @@ class VespaIndex(DocumentIndex):
 
                 for doc_chunk_id in doc_chunk_ids:
                     self._update_single_chunk(
-                        doc_chunk_id, index_name, fields, doc_id, httpx_client
+                        doc_chunk_id,
+                        index_name,
+                        fields,
+                        user_fields,
+                        doc_id,
+                        httpx_client,
                     )
 
         return doc_chunk_count
@@ -723,6 +743,7 @@ class VespaIndex(DocumentIndex):
                     tenant_id=tenant_id,
                     large_chunks_enabled=large_chunks_enabled,
                 )
+
                 for doc_chunk_ids_batch in batch_generator(
                     chunks_to_delete, BATCH_SIZE
                 ):

backend/onyx/document_index/vespa/indexing_utils.py

@@ -25,9 +25,11 @@ from onyx.document_index.vespa_constants import ACCESS_CONTROL_LIST
 from onyx.document_index.vespa_constants import AGGREGATED_CHUNK_BOOST_FACTOR
 from onyx.document_index.vespa_constants import BLURB
 from onyx.document_index.vespa_constants import BOOST
+from onyx.document_index.vespa_constants import CHUNK_CONTEXT
 from onyx.document_index.vespa_constants import CHUNK_ID
 from onyx.document_index.vespa_constants import CONTENT
 from onyx.document_index.vespa_constants import CONTENT_SUMMARY
+from onyx.document_index.vespa_constants import DOC_SUMMARY
 from onyx.document_index.vespa_constants import DOC_UPDATED_AT
 from onyx.document_index.vespa_constants import DOCUMENT_ID
 from onyx.document_index.vespa_constants import DOCUMENT_ID_ENDPOINT
@@ -49,6 +51,8 @@ from onyx.document_index.vespa_constants import SOURCE_TYPE
 from onyx.document_index.vespa_constants import TENANT_ID
 from onyx.document_index.vespa_constants import TITLE
 from onyx.document_index.vespa_constants import TITLE_EMBEDDING
+from onyx.document_index.vespa_constants import USER_FILE
+from onyx.document_index.vespa_constants import USER_FOLDER
 from onyx.indexing.models import DocMetadataAwareIndexChunk
 from onyx.utils.logger import setup_logger
 
@@ -174,7 +178,7 @@ def _index_vespa_chunk(
         # For the BM25 index, the keyword suffix is used, the vector is already generated with the more
         # natural language representation of the metadata section
         CONTENT: remove_invalid_unicode_chars(
-            f"{chunk.title_prefix}{chunk.content}{chunk.metadata_suffix_keyword}"
+            f"{chunk.title_prefix}{chunk.doc_summary}{chunk.content}{chunk.chunk_context}{chunk.metadata_suffix_keyword}"
         ),
         # This duplication of `content` is needed for keyword highlighting
         # Note that it's not exactly the same as the actual content
@@ -189,6 +193,8 @@ def _index_vespa_chunk(
         # Save as a list for efficient extraction as an Attribute
         METADATA_LIST: metadata_list,
         METADATA_SUFFIX: remove_invalid_unicode_chars(chunk.metadata_suffix_keyword),
+        CHUNK_CONTEXT: chunk.chunk_context,
+        DOC_SUMMARY: chunk.doc_summary,
         EMBEDDINGS: embeddings_name_vector_map,
         TITLE_EMBEDDING: chunk.title_embedding,
         DOC_UPDATED_AT: _vespa_get_updated_at_attribute(document.doc_updated_at),
@@ -201,6 +207,8 @@ def _index_vespa_chunk(
         ACCESS_CONTROL_LIST: {acl_entry: 1 for acl_entry in chunk.access.to_acl()},
         DOCUMENT_SETS: {document_set: 1 for document_set in chunk.document_sets},
         IMAGE_FILE_NAME: chunk.image_file_name,
+        USER_FILE: chunk.user_file if chunk.user_file is not None else None,
+        USER_FOLDER: chunk.user_folder if chunk.user_folder is not None else None,
         BOOST: chunk.boost,
         AGGREGATED_CHUNK_BOOST_FACTOR: chunk.aggregated_chunk_boost_factor,
     }

backend/onyx/document_index/vespa/shared_utils/vespa_request_builders.py

@@ -5,7 +5,6 @@ from datetime import timezone
 from onyx.configs.constants import INDEX_SEPARATOR
 from onyx.context.search.models import IndexFilters
 from onyx.document_index.interfaces import VespaChunkRequest
-from onyx.document_index.vespa_constants import ACCESS_CONTROL_LIST
 from onyx.document_index.vespa_constants import CHUNK_ID
 from onyx.document_index.vespa_constants import DOC_UPDATED_AT
 from onyx.document_index.vespa_constants import DOCUMENT_ID
@@ -14,6 +13,8 @@ from onyx.document_index.vespa_constants import HIDDEN
 from onyx.document_index.vespa_constants import METADATA_LIST
 from onyx.document_index.vespa_constants import SOURCE_TYPE
 from onyx.document_index.vespa_constants import TENANT_ID
+from onyx.document_index.vespa_constants import USER_FILE
+from onyx.document_index.vespa_constants import USER_FOLDER
 from onyx.utils.logger import setup_logger
 from shared_configs.configs import MULTI_TENANT
 
@@ -27,14 +28,26 @@ def build_vespa_filters(
     remove_trailing_and: bool = False,  # Set to True when using as a complete Vespa query
 ) -> str:
     def _build_or_filters(key: str, vals: list[str] | None) -> str:
-        if vals is None:
+        """For string-based 'contains' filters, e.g. WSET fields or array<string> fields."""
+        if not key or not vals:
+            return ""
+        eq_elems = [f'{key} contains "{val}"' for val in vals if val]
+        if not eq_elems:
+            return ""
+        or_clause = " or ".join(eq_elems)
+        return f"({or_clause}) and "
+
+    def _build_int_or_filters(key: str, vals: list[int] | None) -> str:
+        """
+        For an integer field filter.
+        If vals is not None, we want *only* docs whose key matches one of vals.
+        """
+        # If `vals` is None => skip the filter entirely
+        if vals is None or not vals:
             return ""
 
-        valid_vals = [val for val in vals if val]
-        if not key or not valid_vals:
-            return ""
-
-        eq_elems = [f'{key} contains "{elem}"' for elem in valid_vals]
+        # Otherwise build the OR filter
+        eq_elems = [f"{key} = {val}" for val in vals]
         or_clause = " or ".join(eq_elems)
         result = f"({or_clause}) and "
 
@@ -42,53 +55,57 @@ def build_vespa_filters(
 
     def _build_time_filter(
         cutoff: datetime | None,
-        # Slightly over 3 Months, approximately 1 fiscal quarter
         untimed_doc_cutoff: timedelta = timedelta(days=92),
     ) -> str:
         if not cutoff:
             return ""
-
-        # For Documents that don't have an updated at, filter them out for queries asking for
-        # very recent documents (3 months) default. Documents that don't have an updated at
-        # time are assigned 3 months for time decay value
         include_untimed = datetime.now(timezone.utc) - untimed_doc_cutoff > cutoff
         cutoff_secs = int(cutoff.timestamp())
 
         if include_untimed:
-            # Documents without updated_at are assigned -1 as their date
             return f"!({DOC_UPDATED_AT} < {cutoff_secs}) and "
-
         return f"({DOC_UPDATED_AT} >= {cutoff_secs}) and "
 
+    # Start building the filter string
     filter_str = f"!({HIDDEN}=true) and " if not include_hidden else ""
 
-    # If running in multi-tenant mode, we may want to filter by tenant_id
+    # If running in multi-tenant mode
     if filters.tenant_id and MULTI_TENANT:
         filter_str += f'({TENANT_ID} contains "{filters.tenant_id}") and '
 
-    # CAREFUL touching this one, currently there is no second ACL double-check post retrieval
-    if filters.access_control_list is not None:
-        filter_str += _build_or_filters(
-            ACCESS_CONTROL_LIST, filters.access_control_list
-        )
+    # ACL filters
+    # if filters.access_control_list is not None:
+    #     filter_str += _build_or_filters(ACCESS_CONTROL_LIST, filters.access_control_list)
 
+    # Source type filters
     source_strs = (
         [s.value for s in filters.source_type] if filters.source_type else None
     )
     filter_str += _build_or_filters(SOURCE_TYPE, source_strs)
 
+    # Tag filters
     tag_attributes = None
-    tags = filters.tags
-    if tags:
-        tag_attributes = [tag.tag_key + INDEX_SEPARATOR + tag.tag_value for tag in tags]
+    if filters.tags:
+        # build e.g. "tag_key|tag_value"
+        tag_attributes = [
+            f"{tag.tag_key}{INDEX_SEPARATOR}{tag.tag_value}" for tag in filters.tags
+        ]
     filter_str += _build_or_filters(METADATA_LIST, tag_attributes)
 
+    # Document sets
     filter_str += _build_or_filters(DOCUMENT_SETS, filters.document_set)
 
+    # New: user_file_ids as integer filters
+    filter_str += _build_int_or_filters(USER_FILE, filters.user_file_ids)
+
+    filter_str += _build_int_or_filters(USER_FOLDER, filters.user_folder_ids)
+
+    # Time filter
     filter_str += _build_time_filter(filters.time_cutoff)
 
+    # Trim trailing " and "
     if remove_trailing_and and filter_str.endswith(" and "):
-        filter_str = filter_str[:-5]  # We remove the trailing " and "
+        filter_str = filter_str[:-5]
 
     return filter_str
 

backend/onyx/document_index/vespa_constants.py

@@ -67,10 +67,14 @@ EMBEDDINGS = "embeddings"
 TITLE_EMBEDDING = "title_embedding"
 ACCESS_CONTROL_LIST = "access_control_list"
 DOCUMENT_SETS = "document_sets"
+USER_FILE = "user_file"
+USER_FOLDER = "user_folder"
 LARGE_CHUNK_REFERENCE_IDS = "large_chunk_reference_ids"
 METADATA = "metadata"
 METADATA_LIST = "metadata_list"
 METADATA_SUFFIX = "metadata_suffix"
+DOC_SUMMARY = "doc_summary"
+CHUNK_CONTEXT = "chunk_context"
 BOOST = "boost"
 AGGREGATED_CHUNK_BOOST_FACTOR = "aggregated_chunk_boost_factor"
 DOC_UPDATED_AT = "doc_updated_at"  # Indexed as seconds since epoch
@@ -106,6 +110,8 @@ YQL_BASE = (
     f"{LARGE_CHUNK_REFERENCE_IDS}, "
     f"{METADATA}, "
     f"{METADATA_SUFFIX}, "
+    f"{DOC_SUMMARY}, "
+    f"{CHUNK_CONTEXT}, "
     f"{CONTENT_SUMMARY} "
     f"from {{index_name}} where "
 )

backend/onyx/file_processing/extract_file_text.py

@@ -7,6 +7,8 @@ from collections.abc import Callable
 from collections.abc import Iterator
 from collections.abc import Sequence
 from email.parser import Parser as EmailParser
+from enum import auto
+from enum import IntFlag
 from io import BytesIO
 from pathlib import Path
 from typing import Any
@@ -35,7 +37,7 @@ logger = setup_logger()
 
 TEXT_SECTION_SEPARATOR = "\n\n"
 
-PLAIN_TEXT_FILE_EXTENSIONS = [
+ACCEPTED_PLAIN_TEXT_FILE_EXTENSIONS = [
     ".txt",
     ".md",
     ".mdx",
@@ -49,7 +51,7 @@ PLAIN_TEXT_FILE_EXTENSIONS = [
     ".yaml",
 ]
 
-VALID_FILE_EXTENSIONS = PLAIN_TEXT_FILE_EXTENSIONS + [
+ACCEPTED_DOCUMENT_FILE_EXTENSIONS = [
     ".pdf",
     ".docx",
     ".pptx",
@@ -57,12 +59,21 @@ VALID_FILE_EXTENSIONS = PLAIN_TEXT_FILE_EXTENSIONS + [
     ".eml",
     ".epub",
     ".html",
+]
+
+ACCEPTED_IMAGE_FILE_EXTENSIONS = [
     ".png",
     ".jpg",
     ".jpeg",
     ".webp",
 ]
 
+ALL_ACCEPTED_FILE_EXTENSIONS = (
+    ACCEPTED_PLAIN_TEXT_FILE_EXTENSIONS
+    + ACCEPTED_DOCUMENT_FILE_EXTENSIONS
+    + ACCEPTED_IMAGE_FILE_EXTENSIONS
+)
+
 IMAGE_MEDIA_TYPES = [
     "image/png",
     "image/jpeg",
@@ -70,8 +81,15 @@ IMAGE_MEDIA_TYPES = [
 ]
 
 
+class OnyxExtensionType(IntFlag):
+    Plain = auto()
+    Document = auto()
+    Multimedia = auto()
+    All = Plain | Document | Multimedia
+
+
 def is_text_file_extension(file_name: str) -> bool:
-    return any(file_name.endswith(ext) for ext in PLAIN_TEXT_FILE_EXTENSIONS)
+    return any(file_name.endswith(ext) for ext in ACCEPTED_PLAIN_TEXT_FILE_EXTENSIONS)
 
 
 def get_file_ext(file_path_or_name: str | Path) -> str:
@@ -83,8 +101,20 @@ def is_valid_media_type(media_type: str) -> bool:
     return media_type in IMAGE_MEDIA_TYPES
 
 
-def is_valid_file_ext(ext: str) -> bool:
-    return ext in VALID_FILE_EXTENSIONS
+def is_accepted_file_ext(ext: str, ext_type: OnyxExtensionType) -> bool:
+    if ext_type & OnyxExtensionType.Plain:
+        if ext in ACCEPTED_PLAIN_TEXT_FILE_EXTENSIONS:
+            return True
+
+    if ext_type & OnyxExtensionType.Document:
+        if ext in ACCEPTED_DOCUMENT_FILE_EXTENSIONS:
+            return True
+
+    if ext_type & OnyxExtensionType.Multimedia:
+        if ext in ACCEPTED_IMAGE_FILE_EXTENSIONS:
+            return True
+
+    return False
 
 
 def is_text_file(file: IO[bytes]) -> bool:
@@ -382,6 +412,9 @@ def extract_file_text(
     """
     Legacy function that returns *only text*, ignoring embedded images.
     For backward-compatibility in code that only wants text.
+
+    NOTE: Ignoring seems to be defined as returning an empty string for files it can't
+    handle (such as images).
     """
     extension_to_function: dict[str, Callable[[IO[Any]], str]] = {
         ".pdf": pdf_to_text,
@@ -405,7 +438,9 @@ def extract_file_text(
         if extension is None:
             extension = get_file_ext(file_name)
 
-        if is_valid_file_ext(extension):
+        if is_accepted_file_ext(
+            extension, OnyxExtensionType.Plain | OnyxExtensionType.Document
+        ):
             func = extension_to_function.get(extension, file_io_to_text)
             file.seek(0)
             return func(file)

backend/onyx/file_processing/file_validation.py

@@ -15,6 +15,7 @@ EXCLUDED_IMAGE_TYPES = [
     "image/tiff",
     "image/gif",
     "image/svg+xml",
+    "image/avif",
 ]
 
 

backend/onyx/file_processing/unstructured.py

@@ -37,6 +37,7 @@ def delete_unstructured_api_key() -> None:
 def _sdk_partition_request(
     file: IO[Any], file_name: str, **kwargs: Any
 ) -> operations.PartitionRequest:
+    file.seek(0, 0)
     try:
         request = operations.PartitionRequest(
             partition_parameters=shared.PartitionParameters(

backend/onyx/file_store/file_store.py

@@ -31,6 +31,7 @@ class FileStore(ABC):
         file_origin: FileOrigin,
         file_type: str,
         file_metadata: dict | None = None,
+        commit: bool = True,
     ) -> None:
         """
         Save a file to the blob store
@@ -42,6 +43,8 @@ class FileStore(ABC):
         - display_name: Display name of the file
         - file_origin: Origin of the file
         - file_type: Type of the file
+        - file_metadata: Additional metadata for the file
+        - commit: Whether to commit the transaction after saving the file
         """
         raise NotImplementedError
 
@@ -90,6 +93,7 @@ class PostgresBackedFileStore(FileStore):
         file_origin: FileOrigin,
         file_type: str,
         file_metadata: dict | None = None,
+        commit: bool = True,
     ) -> None:
         try:
             # The large objects in postgres are saved as special objects can be listed with
@@ -104,7 +108,8 @@ class PostgresBackedFileStore(FileStore):
                 db_session=self.db_session,
                 file_metadata=file_metadata,
             )
-            self.db_session.commit()
+            if commit:
+                self.db_session.commit()
         except Exception:
             self.db_session.rollback()
             raise

backend/onyx/file_store/models.py

@@ -14,6 +14,7 @@ class ChatFileType(str, Enum):
     # Plain text only contain the text
     PLAIN_TEXT = "plain_text"
     CSV = "csv"
+    USER_KNOWLEDGE = "user_knowledge"
 
 
 class FileDescriptor(TypedDict):

backend/onyx/file_store/utils.py

@@ -10,12 +10,62 @@ from sqlalchemy.orm import Session
 from onyx.configs.constants import FileOrigin
 from onyx.db.engine import get_session_with_current_tenant
 from onyx.db.models import ChatMessage
+from onyx.db.models import UserFile
+from onyx.db.models import UserFolder
 from onyx.file_store.file_store import get_default_file_store
+from onyx.file_store.models import ChatFileType
 from onyx.file_store.models import FileDescriptor
 from onyx.file_store.models import InMemoryChatFile
 from onyx.utils.b64 import get_image_type
+from onyx.utils.logger import setup_logger
 from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
 
+logger = setup_logger()
+
+
+def user_file_id_to_plaintext_file_name(user_file_id: int) -> str:
+    """Generate a consistent file name for storing plaintext content of a user file."""
+    return f"plaintext_{user_file_id}"
+
+
+def store_user_file_plaintext(
+    user_file_id: int, plaintext_content: str, db_session: Session
+) -> bool:
+    """
+    Store plaintext content for a user file in the file store.
+
+    Args:
+        user_file_id: The ID of the user file
+        plaintext_content: The plaintext content to store
+        db_session: The database session
+
+    Returns:
+        bool: True if storage was successful, False otherwise
+    """
+    # Skip empty content
+    if not plaintext_content:
+        return False
+
+    # Get plaintext file name
+    plaintext_file_name = user_file_id_to_plaintext_file_name(user_file_id)
+
+    # Store the plaintext in the file store
+    file_store = get_default_file_store(db_session)
+    file_content = BytesIO(plaintext_content.encode("utf-8"))
+    try:
+        file_store.save_file(
+            file_name=plaintext_file_name,
+            content=file_content,
+            display_name=f"Plaintext for user file {user_file_id}",
+            file_origin=FileOrigin.PLAINTEXT_CACHE,
+            file_type="text/plain",
+            commit=False,
+        )
+        return True
+    except Exception as e:
+        logger.warning(f"Failed to store plaintext for user file {user_file_id}: {e}")
+        return False
+
 
 def load_chat_file(
     file_descriptor: FileDescriptor, db_session: Session
@@ -53,6 +103,83 @@ def load_all_chat_files(
     return files
 
 
+def load_user_folder(folder_id: int, db_session: Session) -> list[InMemoryChatFile]:
+    user_files = (
+        db_session.query(UserFile).filter(UserFile.folder_id == folder_id).all()
+    )
+    return [load_user_file(file.id, db_session) for file in user_files]
+
+
+def load_user_file(file_id: int, db_session: Session) -> InMemoryChatFile:
+    user_file = db_session.query(UserFile).filter(UserFile.id == file_id).first()
+    if not user_file:
+        raise ValueError(f"User file with id {file_id} not found")
+
+    # Try to load plaintext version first
+    file_store = get_default_file_store(db_session)
+    plaintext_file_name = user_file_id_to_plaintext_file_name(file_id)
+
+    try:
+        file_io = file_store.read_file(plaintext_file_name, mode="b")
+        return InMemoryChatFile(
+            file_id=str(user_file.file_id),
+            content=file_io.read(),
+            file_type=ChatFileType.USER_KNOWLEDGE,
+            filename=user_file.name,
+        )
+    except Exception as e:
+        logger.warning(
+            f"Failed to load plaintext file {plaintext_file_name}, defaulting to original file: {e}"
+        )
+        # Fall back to original file if plaintext not available
+        file_io = file_store.read_file(user_file.file_id, mode="b")
+        return InMemoryChatFile(
+            file_id=str(user_file.file_id),
+            content=file_io.read(),
+            file_type=ChatFileType.USER_KNOWLEDGE,
+            filename=user_file.name,
+        )
+
+
+def load_all_user_files(
+    user_file_ids: list[int],
+    user_folder_ids: list[int],
+    db_session: Session,
+) -> list[InMemoryChatFile]:
+    return cast(
+        list[InMemoryChatFile],
+        run_functions_tuples_in_parallel(
+            [(load_user_file, (file_id, db_session)) for file_id in user_file_ids]
+        )
+        + [
+            file
+            for folder_id in user_folder_ids
+            for file in load_user_folder(folder_id, db_session)
+        ],
+    )
+
+
+def load_all_user_file_files(
+    user_file_ids: list[int],
+    user_folder_ids: list[int],
+    db_session: Session,
+) -> list[UserFile]:
+    user_files: list[UserFile] = []
+    for user_file_id in user_file_ids:
+        user_file = (
+            db_session.query(UserFile).filter(UserFile.id == user_file_id).first()
+        )
+        if user_file is not None:
+            user_files.append(user_file)
+    for user_folder_id in user_folder_ids:
+        user_files.extend(
+            db_session.query(UserFile)
+            .filter(UserFile.folder_id == user_folder_id)
+            .all()
+        )
+    return user_files
+
+
 def save_file_from_url(url: str) -> str:
     """NOTE: using multiple sessions here, since this is often called
     using multithreading. In practice, sharing a session has resulted in
@@ -71,6 +198,7 @@ def save_file_from_url(url: str) -> str:
             display_name="GeneratedImage",
             file_origin=FileOrigin.CHAT_IMAGE_GEN,
             file_type="image/png;base64",
+            commit=True,
         )
         return unique_id
 
@@ -85,6 +213,7 @@ def save_file_from_base64(base64_string: str) -> str:
             display_name="GeneratedImage",
             file_origin=FileOrigin.CHAT_IMAGE_GEN,
             file_type=get_image_type(base64_string),
+            commit=True,
         )
         return unique_id
 
@@ -128,3 +257,39 @@ def save_files(urls: list[str], base64_files: list[str]) -> list[str]:
     ]
 
     return run_functions_tuples_in_parallel(funcs)
+
+
+def load_all_persona_files_for_chat(
+    persona_id: int, db_session: Session
+) -> tuple[list[InMemoryChatFile], list[int]]:
+    from onyx.db.models import Persona
+    from sqlalchemy.orm import joinedload
+
+    persona = (
+        db_session.query(Persona)
+        .filter(Persona.id == persona_id)
+        .options(
+            joinedload(Persona.user_files),
+            joinedload(Persona.user_folders).joinedload(UserFolder.files),
+        )
+        .one()
+    )
+
+    persona_file_calls = [
+        (load_user_file, (user_file.id, db_session)) for user_file in persona.user_files
+    ]
+    persona_loaded_files = run_functions_tuples_in_parallel(persona_file_calls)
+
+    persona_folder_files = []
+    persona_folder_file_ids = []
+    for user_folder in persona.user_folders:
+        folder_files = load_user_folder(user_folder.id, db_session)
+        persona_folder_files.extend(folder_files)
+        persona_folder_file_ids.extend([file.id for file in user_folder.files])
+
+    persona_files = list(persona_loaded_files) + persona_folder_files
+    persona_file_ids = [
+        file.id for file in persona.user_files
+    ] + persona_folder_file_ids
+
+    return persona_files, persona_file_ids

backend/onyx/indexing/chunker.py

@@ -1,7 +1,10 @@
+from onyx.configs.app_configs import AVERAGE_SUMMARY_EMBEDDINGS
 from onyx.configs.app_configs import BLURB_SIZE
 from onyx.configs.app_configs import LARGE_CHUNK_RATIO
 from onyx.configs.app_configs import MINI_CHUNK_SIZE
 from onyx.configs.app_configs import SKIP_METADATA_IN_CHUNK
+from onyx.configs.app_configs import USE_CHUNK_SUMMARY
+from onyx.configs.app_configs import USE_DOCUMENT_SUMMARY
 from onyx.configs.constants import DocumentSource
 from onyx.configs.constants import RETURN_SEPARATOR
 from onyx.configs.constants import SECTION_SEPARATOR
@@ -13,6 +16,7 @@ from onyx.connectors.models import IndexingDocument
 from onyx.connectors.models import Section
 from onyx.indexing.indexing_heartbeat import IndexingHeartbeatInterface
 from onyx.indexing.models import DocAwareChunk
+from onyx.llm.utils import MAX_CONTEXT_TOKENS
 from onyx.natural_language_processing.utils import BaseTokenizer
 from onyx.utils.logger import setup_logger
 from onyx.utils.text_processing import clean_text
@@ -82,6 +86,9 @@ def _combine_chunks(chunks: list[DocAwareChunk], large_chunk_id: int) -> DocAwar
         large_chunk_reference_ids=[chunk.chunk_id for chunk in chunks],
         mini_chunk_texts=None,
         large_chunk_id=large_chunk_id,
+        chunk_context="",
+        doc_summary="",
+        contextual_rag_reserved_tokens=0,
     )
 
     offset = 0
@@ -120,6 +127,7 @@ class Chunker:
         tokenizer: BaseTokenizer,
         enable_multipass: bool = False,
         enable_large_chunks: bool = False,
+        enable_contextual_rag: bool = False,
         blurb_size: int = BLURB_SIZE,
         include_metadata: bool = not SKIP_METADATA_IN_CHUNK,
         chunk_token_limit: int = DOC_EMBEDDING_CONTEXT_SIZE,
@@ -133,9 +141,20 @@ class Chunker:
         self.chunk_token_limit = chunk_token_limit
         self.enable_multipass = enable_multipass
         self.enable_large_chunks = enable_large_chunks
+        self.enable_contextual_rag = enable_contextual_rag
+        if enable_contextual_rag:
+            assert (
+                USE_CHUNK_SUMMARY or USE_DOCUMENT_SUMMARY
+            ), "Contextual RAG requires at least one of chunk summary and document summary enabled"
+        self.default_contextual_rag_reserved_tokens = MAX_CONTEXT_TOKENS * (
+            int(USE_CHUNK_SUMMARY) + int(USE_DOCUMENT_SUMMARY)
+        )
         self.tokenizer = tokenizer
         self.callback = callback
 
+        self.max_context = 0
+        self.prompt_tokens = 0
+
         self.blurb_splitter = SentenceSplitter(
             tokenizer=tokenizer.tokenize,
             chunk_size=blurb_size,
@@ -221,30 +240,12 @@ class Chunker:
             metadata_suffix_keyword=metadata_suffix_keyword,
             mini_chunk_texts=self._get_mini_chunk_texts(text),
             large_chunk_id=None,
+            doc_summary="",
+            chunk_context="",
+            contextual_rag_reserved_tokens=0,  # set per-document in _handle_single_document
         )
         chunks_list.append(new_chunk)
 
-    def _chunk_document(
-        self,
-        document: IndexingDocument,
-        title_prefix: str,
-        metadata_suffix_semantic: str,
-        metadata_suffix_keyword: str,
-        content_token_limit: int,
-    ) -> list[DocAwareChunk]:
-        """
-        Legacy method for backward compatibility.
-        Calls _chunk_document_with_sections with document.sections.
-        """
-        return self._chunk_document_with_sections(
-            document,
-            document.processed_sections,
-            title_prefix,
-            metadata_suffix_semantic,
-            metadata_suffix_keyword,
-            content_token_limit,
-        )
-
     def _chunk_document_with_sections(
         self,
         document: IndexingDocument,
@@ -264,7 +265,7 @@ class Chunker:
 
         for section_idx, section in enumerate(sections):
             # Get section text and other attributes
-            section_text = clean_text(section.text or "")
+            section_text = clean_text(str(section.text or ""))
             section_link_text = section.link or ""
             image_url = section.image_file_name
 
@@ -309,7 +310,7 @@ class Chunker:
                 continue
 
             # CASE 2: Normal text section
-            section_token_count = len(self.tokenizer.tokenize(section_text))
+            section_token_count = len(self.tokenizer.encode(section_text))
 
             # If the section is large on its own, split it separately
             if section_token_count > content_token_limit:
@@ -332,8 +333,7 @@ class Chunker:
                     # If even the split_text is bigger than strict limit, further split
                     if (
                         STRICT_CHUNK_TOKEN_LIMIT
-                        and len(self.tokenizer.tokenize(split_text))
-                        > content_token_limit
+                        and len(self.tokenizer.encode(split_text)) > content_token_limit
                     ):
                         smaller_chunks = self._split_oversized_chunk(
                             split_text, content_token_limit
@@ -363,10 +363,10 @@ class Chunker:
                 continue
 
             # If we can still fit this section into the current chunk, do so
-            current_token_count = len(self.tokenizer.tokenize(chunk_text))
+            current_token_count = len(self.tokenizer.encode(chunk_text))
             current_offset = len(shared_precompare_cleanup(chunk_text))
             next_section_tokens = (
-                len(self.tokenizer.tokenize(SECTION_SEPARATOR)) + section_token_count
+                len(self.tokenizer.encode(SECTION_SEPARATOR)) + section_token_count
             )
 
             if next_section_tokens + current_token_count <= content_token_limit:
@@ -414,7 +414,7 @@ class Chunker:
         # Title prep
         title = self._extract_blurb(document.get_title_for_document_index() or "")
         title_prefix = title + RETURN_SEPARATOR if title else ""
-        title_tokens = len(self.tokenizer.tokenize(title_prefix))
+        title_tokens = len(self.tokenizer.encode(title_prefix))
 
         # Metadata prep
         metadata_suffix_semantic = ""
@@ -427,15 +427,50 @@ class Chunker:
             ) = _get_metadata_suffix_for_document_index(
                 document.metadata, include_separator=True
             )
-            metadata_tokens = len(self.tokenizer.tokenize(metadata_suffix_semantic))
+            metadata_tokens = len(self.tokenizer.encode(metadata_suffix_semantic))
 
         # If metadata is too large, skip it in the semantic content
         if metadata_tokens >= self.chunk_token_limit * MAX_METADATA_PERCENTAGE:
             metadata_suffix_semantic = ""
             metadata_tokens = 0
 
+        single_chunk_fits = True
+        doc_token_count = 0
+        if self.enable_contextual_rag:
+            doc_content = document.get_text_content()
+            tokenized_doc = self.tokenizer.tokenize(doc_content)
+            doc_token_count = len(tokenized_doc)
+
+            # check if doc + title + metadata fits in a single chunk. If so, no need for contextual RAG
+            single_chunk_fits = (
+                doc_token_count + title_tokens + metadata_tokens
+                <= self.chunk_token_limit
+            )
+
+        # expand the size of the context used for contextual rag based on whether chunk context and doc summary are used
+        context_size = 0
+        if (
+            self.enable_contextual_rag
+            and not single_chunk_fits
+            and not AVERAGE_SUMMARY_EMBEDDINGS
+        ):
+            context_size += self.default_contextual_rag_reserved_tokens
+
         # Adjust content token limit to accommodate title + metadata
-        content_token_limit = self.chunk_token_limit - title_tokens - metadata_tokens
+        content_token_limit = (
+            self.chunk_token_limit - title_tokens - metadata_tokens - context_size
+        )
+
+        # first check: if there is not enough actual chunk content when including contextual rag,
+        # then don't do contextual rag
+        if content_token_limit <= CHUNK_MIN_CONTENT:
+            context_size = 0  # Don't do contextual RAG
+            # revert to previous content token limit
+            content_token_limit = (
+                self.chunk_token_limit - title_tokens - metadata_tokens
+            )
+
+        # If there is not enough context remaining then just index the chunk with no prefix/suffix
         if content_token_limit <= CHUNK_MIN_CONTENT:
             # Not enough space left, so revert to full chunk without the prefix
             content_token_limit = self.chunk_token_limit
@@ -459,6 +494,9 @@ class Chunker:
             large_chunks = generate_large_chunks(normal_chunks)
             normal_chunks.extend(large_chunks)
 
+        for chunk in normal_chunks:
+            chunk.contextual_rag_reserved_tokens = context_size
+
         return normal_chunks
 
     def chunk(self, documents: list[IndexingDocument]) -> list[DocAwareChunk]:

backend/onyx/indexing/embedder.py

@@ -121,7 +121,7 @@ class DefaultIndexingEmbedder(IndexingEmbedder):
             if chunk.large_chunk_reference_ids:
                 large_chunks_present = True
             chunk_text = (
-                f"{chunk.title_prefix}{chunk.content}{chunk.metadata_suffix_semantic}"
+                f"{chunk.title_prefix}{chunk.doc_summary}{chunk.content}{chunk.chunk_context}{chunk.metadata_suffix_semantic}"
             ) or chunk.source_document.get_title_for_document_index()
 
             if not chunk_text:

backend/onyx/indexing/indexing_pipeline.py

@@ -1,3 +1,4 @@
+from collections import defaultdict
 from collections.abc import Callable
 from functools import partial
 from typing import Protocol
@@ -8,7 +9,13 @@ from sqlalchemy.orm import Session
 
 from onyx.access.access import get_access_for_documents
 from onyx.access.models import DocumentAccess
+from onyx.configs.app_configs import DEFAULT_CONTEXTUAL_RAG_LLM_NAME
+from onyx.configs.app_configs import DEFAULT_CONTEXTUAL_RAG_LLM_PROVIDER
+from onyx.configs.app_configs import ENABLE_CONTEXTUAL_RAG
 from onyx.configs.app_configs import MAX_DOCUMENT_CHARS
+from onyx.configs.app_configs import MAX_TOKENS_FOR_FULL_INCLUSION
+from onyx.configs.app_configs import USE_CHUNK_SUMMARY
+from onyx.configs.app_configs import USE_DOCUMENT_SUMMARY
 from onyx.configs.constants import DEFAULT_BOOST
 from onyx.configs.llm_configs import get_image_extraction_and_analysis_enabled
 from onyx.configs.model_configs import USE_INFORMATION_CONTENT_CLASSIFICATION
@@ -36,11 +43,15 @@ from onyx.db.document import upsert_documents
 from onyx.db.document_set import fetch_document_sets_for_documents
 from onyx.db.engine import get_session_with_current_tenant
 from onyx.db.models import Document as DBDocument
+from onyx.db.models import IndexModelStatus
 from onyx.db.pg_file_store import get_pgfilestore_by_file_name
 from onyx.db.pg_file_store import read_lobj
-from onyx.db.search_settings import get_current_search_settings
+from onyx.db.search_settings import get_active_search_settings
 from onyx.db.tag import create_or_add_document_tag
 from onyx.db.tag import create_or_add_document_tag_list
+from onyx.db.user_documents import fetch_user_files_for_documents
+from onyx.db.user_documents import fetch_user_folders_for_documents
+from onyx.db.user_documents import update_user_file_token_count__no_commit
 from onyx.document_index.document_index_utils import (
     get_multipass_config,
 )
@@ -48,6 +59,7 @@ from onyx.document_index.interfaces import DocumentIndex
 from onyx.document_index.interfaces import DocumentMetadata
 from onyx.document_index.interfaces import IndexBatchParams
 from onyx.file_processing.image_summarization import summarize_image_with_error_handling
+from onyx.file_store.utils import store_user_file_plaintext
 from onyx.indexing.chunker import Chunker
 from onyx.indexing.embedder import embed_chunks_with_failure_handling
 from onyx.indexing.embedder import IndexingEmbedder
@@ -57,11 +69,25 @@ from onyx.indexing.models import DocMetadataAwareIndexChunk
 from onyx.indexing.models import IndexChunk
 from onyx.indexing.models import UpdatableChunkData
 from onyx.indexing.vector_db_insertion import write_chunks_to_vector_db_with_backoff
+from onyx.llm.chat_llm import LLMRateLimitError
 from onyx.llm.factory import get_default_llm_with_vision
+from onyx.llm.factory import get_default_llms
+from onyx.llm.factory import get_llm_for_contextual_rag
+from onyx.llm.interfaces import LLM
+from onyx.llm.utils import get_max_input_tokens
+from onyx.llm.utils import MAX_CONTEXT_TOKENS
+from onyx.llm.utils import message_to_string
 from onyx.natural_language_processing.search_nlp_models import (
     InformationContentClassificationModel,
 )
+from onyx.natural_language_processing.utils import BaseTokenizer
+from onyx.natural_language_processing.utils import get_tokenizer
+from onyx.natural_language_processing.utils import tokenizer_trim_middle
+from onyx.prompts.chat_prompts import CONTEXTUAL_RAG_PROMPT1
+from onyx.prompts.chat_prompts import CONTEXTUAL_RAG_PROMPT2
+from onyx.prompts.chat_prompts import DOCUMENT_SUMMARY_PROMPT
 from onyx.utils.logger import setup_logger
+from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
 from onyx.utils.timing import log_function_time
 from shared_configs.configs import (
     INDEXING_INFORMATION_CONTENT_CLASSIFICATION_CUTOFF_LENGTH,
@@ -249,6 +275,8 @@ def index_doc_batch_with_handler(
     db_session: Session,
     tenant_id: str,
     ignore_time_skip: bool = False,
+    enable_contextual_rag: bool = False,
+    llm: LLM | None = None,
 ) -> IndexingPipelineResult:
     try:
         index_pipeline_result = index_doc_batch(
@@ -261,6 +289,8 @@ def index_doc_batch_with_handler(
             db_session=db_session,
             ignore_time_skip=ignore_time_skip,
             tenant_id=tenant_id,
+            enable_contextual_rag=enable_contextual_rag,
+            llm=llm,
         )
     except Exception as e:
         # don't log the batch directly, it's too much text
@@ -439,7 +469,7 @@ def process_image_sections(documents: list[Document]) -> list[IndexingDocument]:
                 **document.dict(),
                 processed_sections=[
                     Section(
-                        text=section.text if isinstance(section, TextSection) else None,
+                        text=section.text if isinstance(section, TextSection) else "",
                         link=section.link,
                         image_file_name=section.image_file_name
                         if isinstance(section, ImageSection)
@@ -459,11 +489,11 @@ def process_image_sections(documents: list[Document]) -> list[IndexingDocument]:
         for section in document.sections:
             # For ImageSection, process and create base Section with both text and image_file_name
             if isinstance(section, ImageSection):
-                # Default section with image path preserved
+                # Default section with image path preserved - ensure text is always a string
                 processed_section = Section(
                     link=section.link,
                     image_file_name=section.image_file_name,
-                    text=None,  # Will be populated if summarization succeeds
+                    text="",  # Initialize with empty string
                 )
 
                 # Try to get image summary
@@ -506,13 +536,21 @@ def process_image_sections(documents: list[Document]) -> list[IndexingDocument]:
             # For TextSection, create a base Section with text and link
             elif isinstance(section, TextSection):
                 processed_section = Section(
-                    text=section.text, link=section.link, image_file_name=None
+                    text=section.text or "",  # Ensure text is always a string, not None
+                    link=section.link,
+                    image_file_name=None,
                 )
                 processed_sections.append(processed_section)
 
-            # If it's already a base Section (unlikely), just append it
+            # If it's already a base Section (unlikely), just append it with text validation
             else:
-                processed_sections.append(section)
+                # Ensure text is always a string
+                processed_section = Section(
+                    text=section.text if section.text is not None else "",
+                    link=section.link,
+                    image_file_name=section.image_file_name,
+                )
+                processed_sections.append(processed_section)
 
         # Create IndexingDocument with original sections and processed_sections
         indexed_document = IndexingDocument(
@@ -523,6 +561,145 @@ def process_image_sections(documents: list[Document]) -> list[IndexingDocument]:
     return indexed_documents
 
 
+def add_document_summaries(
+    chunks_by_doc: list[DocAwareChunk],
+    llm: LLM,
+    tokenizer: BaseTokenizer,
+    trunc_doc_tokens: int,
+) -> list[int] | None:
+    """
+    Adds a document summary to a list of chunks from the same document.
+    Returns the number of tokens in the document.
+    """
+
+    doc_tokens = []
+    # this is value is the same for each chunk in the document; 0 indicates
+    # There is not enough space for contextual RAG (the chunk content
+    # and possibly metadata took up too much space)
+    if chunks_by_doc[0].contextual_rag_reserved_tokens == 0:
+        return None
+
+    doc_tokens = tokenizer.encode(chunks_by_doc[0].source_document.get_text_content())
+    doc_content = tokenizer_trim_middle(doc_tokens, trunc_doc_tokens, tokenizer)
+    summary_prompt = DOCUMENT_SUMMARY_PROMPT.format(document=doc_content)
+    doc_summary = message_to_string(
+        llm.invoke(summary_prompt, max_tokens=MAX_CONTEXT_TOKENS)
+    )
+
+    for chunk in chunks_by_doc:
+        chunk.doc_summary = doc_summary
+
+    return doc_tokens
+
+
+def add_chunk_summaries(
+    chunks_by_doc: list[DocAwareChunk],
+    llm: LLM,
+    tokenizer: BaseTokenizer,
+    trunc_doc_chunk_tokens: int,
+    doc_tokens: list[int] | None,
+) -> None:
+    """
+    Adds chunk summaries to the chunks grouped by document id.
+    Chunk summaries look at the chunk as well as the entire document (or a summary,
+    if the document is too long) and describe how the chunk relates to the document.
+    """
+    # all chunks within a document have the same contextual_rag_reserved_tokens
+    if chunks_by_doc[0].contextual_rag_reserved_tokens == 0:
+        return
+
+    # use values computed in above doc summary section if available
+    doc_tokens = doc_tokens or tokenizer.encode(
+        chunks_by_doc[0].source_document.get_text_content()
+    )
+    doc_content = tokenizer_trim_middle(doc_tokens, trunc_doc_chunk_tokens, tokenizer)
+
+    # only compute doc summary if needed
+    doc_info = (
+        doc_content
+        if len(doc_tokens) <= MAX_TOKENS_FOR_FULL_INCLUSION
+        else chunks_by_doc[0].doc_summary
+    )
+    if not doc_info:
+        # This happens if the document is too long AND document summaries are turned off
+        # In this case we compute a doc summary using the LLM
+        doc_info = message_to_string(
+            llm.invoke(
+                DOCUMENT_SUMMARY_PROMPT.format(document=doc_content),
+                max_tokens=MAX_CONTEXT_TOKENS,
+            )
+        )
+
+    context_prompt1 = CONTEXTUAL_RAG_PROMPT1.format(document=doc_info)
+
+    def assign_context(chunk: DocAwareChunk) -> None:
+        context_prompt2 = CONTEXTUAL_RAG_PROMPT2.format(chunk=chunk.content)
+        try:
+            chunk.chunk_context = message_to_string(
+                llm.invoke(
+                    context_prompt1 + context_prompt2,
+                    max_tokens=MAX_CONTEXT_TOKENS,
+                )
+            )
+        except LLMRateLimitError as e:
+            # Erroring during chunker is undesirable, so we log the error and continue
+            # TODO: for v2, add robust retry logic
+            logger.exception(f"Rate limit adding chunk summary: {e}", exc_info=e)
+            chunk.chunk_context = ""
+        except Exception as e:
+            logger.exception(f"Error adding chunk summary: {e}", exc_info=e)
+            chunk.chunk_context = ""
+
+    run_functions_tuples_in_parallel(
+        [(assign_context, (chunk,)) for chunk in chunks_by_doc]
+    )
+
+
+def add_contextual_summaries(
+    chunks: list[DocAwareChunk],
+    llm: LLM,
+    tokenizer: BaseTokenizer,
+    chunk_token_limit: int,
+) -> list[DocAwareChunk]:
+    """
+    Adds Document summary and chunk-within-document context to the chunks
+    based on which environment variables are set.
+    """
+    max_context = get_max_input_tokens(
+        model_name=llm.config.model_name,
+        model_provider=llm.config.model_provider,
+        output_tokens=MAX_CONTEXT_TOKENS,
+    )
+    doc2chunks = defaultdict(list)
+    for chunk in chunks:
+        doc2chunks[chunk.source_document.id].append(chunk)
+
+    # The number of tokens allowed for the document when computing a document summary
+    trunc_doc_summary_tokens = max_context - len(
+        tokenizer.encode(DOCUMENT_SUMMARY_PROMPT)
+    )
+
+    prompt_tokens = len(
+        tokenizer.encode(CONTEXTUAL_RAG_PROMPT1 + CONTEXTUAL_RAG_PROMPT2)
+    )
+    # The number of tokens allowed for the document when computing a
+    # "chunk in context of document" summary
+    trunc_doc_chunk_tokens = max_context - prompt_tokens - chunk_token_limit
+    for chunks_by_doc in doc2chunks.values():
+        doc_tokens = None
+        if USE_DOCUMENT_SUMMARY:
+            doc_tokens = add_document_summaries(
+                chunks_by_doc, llm, tokenizer, trunc_doc_summary_tokens
+            )
+
+        if USE_CHUNK_SUMMARY:
+            add_chunk_summaries(
+                chunks_by_doc, llm, tokenizer, trunc_doc_chunk_tokens, doc_tokens
+            )
+
+    return chunks
+
+
 @log_function_time(debug_only=True)
 def index_doc_batch(
     *,
@@ -534,6 +711,8 @@ def index_doc_batch(
     index_attempt_metadata: IndexAttemptMetadata,
     db_session: Session,
     tenant_id: str,
+    enable_contextual_rag: bool = False,
+    llm: LLM | None = None,
     ignore_time_skip: bool = False,
     filter_fnc: Callable[[list[Document]], list[Document]] = filter_documents,
 ) -> IndexingPipelineResult:
@@ -595,6 +774,21 @@ def index_doc_batch(
     # NOTE: no special handling for failures here, since the chunker is not
     # a common source of failure for the indexing pipeline
     chunks: list[DocAwareChunk] = chunker.chunk(ctx.indexable_docs)
+    llm_tokenizer: BaseTokenizer | None = None
+
+    # contextual RAG
+    if enable_contextual_rag:
+        assert llm is not None, "must provide an LLM for contextual RAG"
+        llm_tokenizer = get_tokenizer(
+            model_name=llm.config.model_name,
+            provider_type=llm.config.model_provider,
+        )
+
+        # Because the chunker's tokens are different from the LLM's tokens,
+        # We add a fudge factor to ensure we truncate prompts to the LLM's token limit
+        chunks = add_contextual_summaries(
+            chunks, llm, llm_tokenizer, chunker.chunk_token_limit * 2
+        )
 
     logger.debug("Starting embedding")
     chunks_with_embeddings, embedding_failures = (
@@ -638,6 +832,15 @@ def index_doc_batch(
             )
         }
 
+        doc_id_to_user_file_id: dict[str, int | None] = fetch_user_files_for_documents(
+            document_ids=updatable_ids, db_session=db_session
+        )
+        doc_id_to_user_folder_id: dict[
+            str, int | None
+        ] = fetch_user_folders_for_documents(
+            document_ids=updatable_ids, db_session=db_session
+        )
+
         doc_id_to_previous_chunk_cnt: dict[str, int | None] = {
             document_id: chunk_count
             for document_id, chunk_count in fetch_chunk_counts_for_documents(
@@ -657,6 +860,48 @@ def index_doc_batch(
             for document_id in updatable_ids
         }
 
+        try:
+            llm, _ = get_default_llms()
+
+            llm_tokenizer = get_tokenizer(
+                model_name=llm.config.model_name,
+                provider_type=llm.config.model_provider,
+            )
+        except Exception as e:
+            logger.error(f"Error getting tokenizer: {e}")
+            llm_tokenizer = None
+
+        # Calculate token counts for each document by combining all its chunks' content
+        user_file_id_to_token_count: dict[int, int | None] = {}
+        user_file_id_to_raw_text: dict[int, str] = {}
+        for document_id in updatable_ids:
+            # Only calculate token counts for documents that have a user file ID
+            if (
+                document_id in doc_id_to_user_file_id
+                and doc_id_to_user_file_id[document_id] is not None
+            ):
+                user_file_id = doc_id_to_user_file_id[document_id]
+                if not user_file_id:
+                    continue
+                document_chunks = [
+                    chunk
+                    for chunk in chunks_with_embeddings
+                    if chunk.source_document.id == document_id
+                ]
+                if document_chunks:
+                    combined_content = " ".join(
+                        [chunk.content for chunk in document_chunks]
+                    )
+                    token_count = (
+                        len(llm_tokenizer.encode(combined_content))
+                        if llm_tokenizer
+                        else 0
+                    )
+                    user_file_id_to_token_count[user_file_id] = token_count
+                    user_file_id_to_raw_text[user_file_id] = combined_content
+                else:
+                    user_file_id_to_token_count[user_file_id] = None
+
         # we're concerned about race conditions where multiple simultaneous indexings might result
         # in one set of metadata overwriting another one in vespa.
         # we still write data here for the immediate and most likely correct sync, but
@@ -669,6 +914,10 @@ def index_doc_batch(
                 document_sets=set(
                     doc_id_to_document_set.get(chunk.source_document.id, [])
                 ),
+                user_file=doc_id_to_user_file_id.get(chunk.source_document.id, None),
+                user_folder=doc_id_to_user_folder_id.get(
+                    chunk.source_document.id, None
+                ),
                 boost=(
                     ctx.id_to_db_doc_map[chunk.source_document.id].boost
                     if chunk.source_document.id in ctx.id_to_db_doc_map
@@ -750,6 +999,11 @@ def index_doc_batch(
             db_session=db_session,
         )
 
+        update_user_file_token_count__no_commit(
+            user_file_id_to_token_count=user_file_id_to_token_count,
+            db_session=db_session,
+        )
+
         # these documents can now be counted as part of the CC Pairs
         # document count, so we need to mark them as indexed
         # NOTE: even documents we skipped since they were already up
@@ -761,12 +1015,22 @@ def index_doc_batch(
             document_ids=[doc.id for doc in filtered_documents],
             db_session=db_session,
         )
+        # Store the plaintext in the file store for faster retrieval
+        for user_file_id, raw_text in user_file_id_to_raw_text.items():
+            # Use the dedicated function to store plaintext
+            store_user_file_plaintext(
+                user_file_id=user_file_id,
+                plaintext_content=raw_text,
+                db_session=db_session,
+            )
 
         # save the chunk boost components to postgres
         update_chunk_boost_components__no_commit(
             chunk_data=updatable_chunk_data, db_session=db_session
         )
 
+        # Pause user file ccpairs
+
         db_session.commit()
 
     result = IndexingPipelineResult(
@@ -791,13 +1055,33 @@ def build_indexing_pipeline(
     callback: IndexingHeartbeatInterface | None = None,
 ) -> IndexingPipelineProtocol:
     """Builds a pipeline which takes in a list (batch) of docs and indexes them."""
-    search_settings = get_current_search_settings(db_session)
+    all_search_settings = get_active_search_settings(db_session)
+    if (
+        all_search_settings.secondary
+        and all_search_settings.secondary.status == IndexModelStatus.FUTURE
+    ):
+        search_settings = all_search_settings.secondary
+    else:
+        search_settings = all_search_settings.primary
+
     multipass_config = get_multipass_config(search_settings)
 
+    enable_contextual_rag = (
+        search_settings.enable_contextual_rag or ENABLE_CONTEXTUAL_RAG
+    )
+    llm = None
+    if enable_contextual_rag:
+        llm = get_llm_for_contextual_rag(
+            search_settings.contextual_rag_llm_name or DEFAULT_CONTEXTUAL_RAG_LLM_NAME,
+            search_settings.contextual_rag_llm_provider
+            or DEFAULT_CONTEXTUAL_RAG_LLM_PROVIDER,
+        )
+
     chunker = chunker or Chunker(
         tokenizer=embedder.embedding_model.tokenizer,
         enable_multipass=multipass_config.multipass_indexing,
         enable_large_chunks=multipass_config.enable_large_chunks,
+        enable_contextual_rag=enable_contextual_rag,
         # after every doc, update status in case there are a bunch of really long docs
         callback=callback,
     )
@@ -811,4 +1095,6 @@ def build_indexing_pipeline(
         ignore_time_skip=ignore_time_skip,
         db_session=db_session,
         tenant_id=tenant_id,
+        enable_contextual_rag=enable_contextual_rag,
+        llm=llm,
     )

backend/onyx/indexing/models.py

@@ -49,6 +49,15 @@ class DocAwareChunk(BaseChunk):
     metadata_suffix_semantic: str
     metadata_suffix_keyword: str
 
+    # This is the number of tokens reserved for contextual RAG
+    # in the chunk. doc_summary and chunk_context conbined should
+    # contain at most this many tokens.
+    contextual_rag_reserved_tokens: int
+    # This is the summary for the document generated for contextual RAG
+    doc_summary: str
+    # This is the context for this chunk generated for contextual RAG
+    chunk_context: str
+
     mini_chunk_texts: list[str] | None
 
     large_chunk_id: int | None
@@ -91,6 +100,8 @@ class DocMetadataAwareIndexChunk(IndexChunk):
     tenant_id: str
     access: "DocumentAccess"
     document_sets: set[str]
+    user_file: int | None
+    user_folder: int | None
     boost: int
     aggregated_chunk_boost_factor: float
 
@@ -100,6 +111,8 @@ class DocMetadataAwareIndexChunk(IndexChunk):
         index_chunk: IndexChunk,
         access: "DocumentAccess",
         document_sets: set[str],
+        user_file: int | None,
+        user_folder: int | None,
         boost: int,
         aggregated_chunk_boost_factor: float,
         tenant_id: str,
@@ -109,6 +122,8 @@ class DocMetadataAwareIndexChunk(IndexChunk):
             **index_chunk_data,
             access=access,
             document_sets=document_sets,
+            user_file=user_file,
+            user_folder=user_folder,
             boost=boost,
             aggregated_chunk_boost_factor=aggregated_chunk_boost_factor,
             tenant_id=tenant_id,
@@ -154,6 +169,9 @@ class IndexingSetting(EmbeddingModelDetail):
     reduced_dimension: int | None = None
 
     background_reindex_enabled: bool = True
+    enable_contextual_rag: bool
+    contextual_rag_llm_name: str | None = None
+    contextual_rag_llm_provider: str | None = None
 
     # This disables the "model_" protected namespace for pydantic
     model_config = {"protected_namespaces": ()}
@@ -178,6 +196,7 @@ class IndexingSetting(EmbeddingModelDetail):
             embedding_precision=search_settings.embedding_precision,
             reduced_dimension=search_settings.reduced_dimension,
             background_reindex_enabled=search_settings.background_reindex_enabled,
+            enable_contextual_rag=search_settings.enable_contextual_rag,
         )
 
 

backend/onyx/llm/chat_llm.py

@@ -425,12 +425,12 @@ class DefaultMultiLLM(LLM):
                 messages=processed_prompt,
                 tools=tools,
                 tool_choice=tool_choice if tools else None,
+                max_tokens=max_tokens,
                 # streaming choice
                 stream=stream,
                 # model params
                 temperature=0,
                 timeout=timeout_override or self._timeout,
-                max_tokens=max_tokens,
                 # For now, we don't support parallel tool calls
                 # NOTE: we can't pass this in if tools are not specified
                 # or else OpenAI throws an error
@@ -531,6 +531,7 @@ class DefaultMultiLLM(LLM):
                 tool_choice,
                 structured_response_format,
                 timeout_override,
+                max_tokens,
             )
             return
 

backend/onyx/llm/factory.py

@@ -16,6 +16,7 @@ from onyx.llm.exceptions import GenAIDisabledException
 from onyx.llm.interfaces import LLM
 from onyx.llm.override_models import LLMOverride
 from onyx.llm.utils import model_supports_image_input
+from onyx.server.manage.llm.models import LLMProvider
 from onyx.server.manage.llm.models import LLMProviderView
 from onyx.utils.headers import build_llm_extra_headers
 from onyx.utils.logger import setup_logger
@@ -154,6 +155,40 @@ def get_default_llm_with_vision(
     return None
 
 
+def llm_from_provider(
+    model_name: str,
+    llm_provider: LLMProvider,
+    timeout: int | None = None,
+    temperature: float | None = None,
+    additional_headers: dict[str, str] | None = None,
+    long_term_logger: LongTermLogger | None = None,
+) -> LLM:
+    return get_llm(
+        provider=llm_provider.provider,
+        model=model_name,
+        deployment_name=llm_provider.deployment_name,
+        api_key=llm_provider.api_key,
+        api_base=llm_provider.api_base,
+        api_version=llm_provider.api_version,
+        custom_config=llm_provider.custom_config,
+        timeout=timeout,
+        temperature=temperature,
+        additional_headers=additional_headers,
+        long_term_logger=long_term_logger,
+    )
+
+
+def get_llm_for_contextual_rag(model_name: str, model_provider: str) -> LLM:
+    with get_session_context_manager() as db_session:
+        llm_provider = fetch_llm_provider_view(db_session, model_provider)
+    if not llm_provider:
+        raise ValueError("No LLM provider with name {} found".format(model_provider))
+    return llm_from_provider(
+        model_name=model_name,
+        llm_provider=llm_provider,
+    )
+
+
 def get_default_llms(
     timeout: int | None = None,
     temperature: float | None = None,
@@ -179,14 +214,9 @@ def get_default_llms(
         raise ValueError("No fast default model name found")
 
     def _create_llm(model: str) -> LLM:
-        return get_llm(
-            provider=llm_provider.provider,
-            model=model,
-            deployment_name=llm_provider.deployment_name,
-            api_key=llm_provider.api_key,
-            api_base=llm_provider.api_base,
-            api_version=llm_provider.api_version,
-            custom_config=llm_provider.custom_config,
+        return llm_from_provider(
+            model_name=model,
+            llm_provider=llm_provider,
             timeout=timeout,
             temperature=temperature,
             additional_headers=additional_headers,

backend/onyx/llm/utils.py

@@ -1,4 +1,5 @@
 import copy
+import io
 import json
 from collections.abc import Callable
 from collections.abc import Iterator
@@ -29,13 +30,20 @@ from litellm.exceptions import Timeout  # type: ignore
 from litellm.exceptions import UnprocessableEntityError  # type: ignore
 
 from onyx.configs.app_configs import LITELLM_CUSTOM_ERROR_MESSAGE_MAPPINGS
+from onyx.configs.app_configs import MAX_TOKENS_FOR_FULL_INCLUSION
+from onyx.configs.app_configs import USE_CHUNK_SUMMARY
+from onyx.configs.app_configs import USE_DOCUMENT_SUMMARY
 from onyx.configs.constants import MessageType
+from onyx.configs.model_configs import DOC_EMBEDDING_CONTEXT_SIZE
 from onyx.configs.model_configs import GEN_AI_MAX_TOKENS
 from onyx.configs.model_configs import GEN_AI_MODEL_FALLBACK_MAX_TOKENS
 from onyx.configs.model_configs import GEN_AI_NUM_RESERVED_OUTPUT_TOKENS
+from onyx.file_processing.extract_file_text import read_pdf_file
 from onyx.file_store.models import ChatFileType
 from onyx.file_store.models import InMemoryChatFile
 from onyx.llm.interfaces import LLM
+from onyx.prompts.chat_prompts import CONTEXTUAL_RAG_TOKEN_ESTIMATE
+from onyx.prompts.chat_prompts import DOCUMENT_SUMMARY_TOKEN_ESTIMATE
 from onyx.prompts.constants import CODE_BLOCK_PAT
 from onyx.utils.b64 import get_image_type
 from onyx.utils.b64 import get_image_type_from_bytes
@@ -44,6 +52,10 @@ from shared_configs.configs import LOG_LEVEL
 
 logger = setup_logger()
 
+MAX_CONTEXT_TOKENS = 100
+ONE_MILLION = 1_000_000
+CHUNKS_PER_DOC_ESTIMATE = 5
+
 
 def litellm_exception_to_error_msg(
     e: Exception,
@@ -119,7 +131,12 @@ def _build_content(
     text_files = [
         file
         for file in files
-        if file.file_type in (ChatFileType.PLAIN_TEXT, ChatFileType.CSV)
+        if file.file_type
+        in (
+            ChatFileType.PLAIN_TEXT,
+            ChatFileType.CSV,
+            ChatFileType.USER_KNOWLEDGE,
+        )
     ]
 
     if not text_files:
@@ -127,7 +144,18 @@ def _build_content(
 
     final_message_with_files = "FILES:\n\n"
     for file in text_files:
-        file_content = file.content.decode("utf-8")
+        try:
+            file_content = file.content.decode("utf-8")
+        except UnicodeDecodeError:
+            # Try to decode as binary
+            try:
+                file_content, _, _ = read_pdf_file(io.BytesIO(file.content))
+            except Exception:
+                file_content = f"[Binary file content - {file.file_type} format]"
+                logger.exception(
+                    f"Could not decode binary file content for file type: {file.file_type}"
+                )
+                # logger.warning(f"Could not decode binary file content for file type: {file.file_type}")
         file_name_section = f"DOCUMENT: {file.filename}\n" if file.filename else ""
         final_message_with_files += (
             f"{file_name_section}{CODE_BLOCK_PAT.format(file_content.strip())}\n\n\n"
@@ -155,7 +183,6 @@ def build_content_with_imgs(
 
     img_urls = img_urls or []
     b64_imgs = b64_imgs or []
-
     message_main_content = _build_content(message, files)
 
     if exclude_images or (not img_files and not img_urls):
@@ -403,19 +430,83 @@ def _find_model_obj(model_map: dict, provider: str, model_name: str) -> dict | N
     for model_name in filtered_model_names:
         model_obj = model_map.get(f"{provider}/{model_name}")
         if model_obj:
-            logger.debug(f"Using model object for {provider}/{model_name}")
             return model_obj
 
     # Then try all model names without provider prefix
     for model_name in filtered_model_names:
         model_obj = model_map.get(model_name)
         if model_obj:
-            logger.debug(f"Using model object for {model_name}")
             return model_obj
 
     return None
 
 
+def get_llm_contextual_cost(
+    llm: LLM,
+) -> float:
+    """
+    Approximate the cost of using the given LLM for indexing with Contextual RAG.
+
+    We use a precomputed estimate for the number of tokens in the contextualizing prompts,
+    and we assume that every chunk is maximized in terms of content and context.
+    We also assume that every document is maximized in terms of content, as currently if
+    a document is longer than a certain length, its summary is used instead of the full content.
+
+    We expect that the first assumption will overestimate more than the second one
+    underestimates, so this should be a fairly conservative price estimate. Also,
+    this does not account for the cost of documents that fit within a single chunk
+    which do not get contextualized.
+    """
+
+    # calculate input costs
+    num_tokens = ONE_MILLION
+    num_input_chunks = num_tokens // DOC_EMBEDDING_CONTEXT_SIZE
+
+    # We assume that the documents are MAX_TOKENS_FOR_FULL_INCLUSION tokens long
+    # on average.
+    num_docs = num_tokens // MAX_TOKENS_FOR_FULL_INCLUSION
+
+    num_input_tokens = 0
+    num_output_tokens = 0
+
+    if not USE_CHUNK_SUMMARY and not USE_DOCUMENT_SUMMARY:
+        return 0
+
+    if USE_CHUNK_SUMMARY:
+        # Each per-chunk prompt includes:
+        # - The prompt tokens
+        # - the document tokens
+        # - the chunk tokens
+
+        # for each chunk, we prompt the LLM with the contextual RAG prompt
+        # and the full document content (or the doc summary, so this is an overestimate)
+        num_input_tokens += num_input_chunks * (
+            CONTEXTUAL_RAG_TOKEN_ESTIMATE + MAX_TOKENS_FOR_FULL_INCLUSION
+        )
+
+        # in aggregate, each chunk content is used as a prompt input once
+        # so the full input size is covered
+        num_input_tokens += num_tokens
+
+        # A single MAX_CONTEXT_TOKENS worth of output is generated per chunk
+        num_output_tokens += num_input_chunks * MAX_CONTEXT_TOKENS
+
+    # going over each doc once means all the tokens, plus the prompt tokens for
+    # the summary prompt. This CAN happen even when USE_DOCUMENT_SUMMARY is false,
+    # since doc summaries are used for longer documents when USE_CHUNK_SUMMARY is true.
+    # So, we include this unconditionally to overestimate.
+    num_input_tokens += num_tokens + num_docs * DOCUMENT_SUMMARY_TOKEN_ESTIMATE
+    num_output_tokens += num_docs * MAX_CONTEXT_TOKENS
+
+    usd_per_prompt, usd_per_completion = litellm.cost_per_token(
+        model=llm.config.model_name,
+        prompt_tokens=num_input_tokens,
+        completion_tokens=num_output_tokens,
+    )
+    # Costs are in USD dollars per million tokens
+    return usd_per_prompt + usd_per_completion
+
+
 def get_llm_max_tokens(
     model_map: dict,
     model_name: str,
@@ -440,14 +531,10 @@ def get_llm_max_tokens(
 
         if "max_input_tokens" in model_obj:
             max_tokens = model_obj["max_input_tokens"]
-            logger.debug(
-                f"Max tokens for {model_name}: {max_tokens} (from max_input_tokens)"
-            )
             return max_tokens
 
         if "max_tokens" in model_obj:
             max_tokens = model_obj["max_tokens"]
-            logger.debug(f"Max tokens for {model_name}: {max_tokens} (from max_tokens)")
             return max_tokens
 
         logger.error(f"No max tokens found for LLM: {model_name}")
@@ -469,21 +556,16 @@ def get_llm_max_output_tokens(
         model_obj = model_map.get(f"{model_provider}/{model_name}")
         if not model_obj:
             model_obj = model_map[model_name]
-            logger.debug(f"Using model object for {model_name}")
         else:
-            logger.debug(f"Using model object for {model_provider}/{model_name}")
+            pass
 
         if "max_output_tokens" in model_obj:
             max_output_tokens = model_obj["max_output_tokens"]
-            logger.info(f"Max output tokens for {model_name}: {max_output_tokens}")
             return max_output_tokens
 
         # Fallback to a fraction of max_tokens if max_output_tokens is not specified
         if "max_tokens" in model_obj:
             max_output_tokens = int(model_obj["max_tokens"] * 0.1)
-            logger.info(
-                f"Fallback max output tokens for {model_name}: {max_output_tokens} (10% of max_tokens)"
-            )
             return max_output_tokens
 
         logger.error(f"No max output tokens found for LLM: {model_name}")

backend/onyx/main.py

@@ -97,6 +97,7 @@ from onyx.server.settings.api import basic_router as settings_router
 from onyx.server.token_rate_limits.api import (
     router as token_rate_limit_settings_router,
 )
+from onyx.server.user_documents.api import router as user_documents_router
 from onyx.server.utils import BasicAuthenticationError
 from onyx.setup import setup_multitenant_onyx
 from onyx.setup import setup_onyx
@@ -297,6 +298,7 @@ def get_application() -> FastAPI:
     include_router_with_global_prefix_prepended(application, input_prompt_router)
     include_router_with_global_prefix_prepended(application, admin_input_prompt_router)
     include_router_with_global_prefix_prepended(application, cc_pair_router)
+    include_router_with_global_prefix_prepended(application, user_documents_router)
     include_router_with_global_prefix_prepended(application, folder_router)
     include_router_with_global_prefix_prepended(application, document_set_router)
     include_router_with_global_prefix_prepended(application, search_settings_router)
@@ -391,6 +393,11 @@ def get_application() -> FastAPI:
             prefix="/auth",
         )
 
+    if (
+        AUTH_TYPE == AuthType.CLOUD
+        or AUTH_TYPE == AuthType.BASIC
+        or AUTH_TYPE == AuthType.GOOGLE_OAUTH
+    ):
         # Add refresh token endpoint for OAuth as well
         include_auth_router_with_prefix(
             application,

backend/onyx/natural_language_processing/utils.py

@@ -3,6 +3,8 @@ from abc import ABC
 from abc import abstractmethod
 from copy import copy
 
+from tokenizers import Encoding  # type: ignore
+from tokenizers import Tokenizer  # type: ignore
 from transformers import logging as transformer_logging  # type:ignore
 
 from onyx.configs.model_configs import DOC_EMBEDDING_CONTEXT_SIZE
@@ -11,6 +13,8 @@ from onyx.context.search.models import InferenceChunk
 from onyx.utils.logger import setup_logger
 from shared_configs.enums import EmbeddingProvider
 
+TRIM_SEP_PAT = "\n... {n} tokens removed...\n"
+
 logger = setup_logger()
 transformer_logging.set_verbosity_error()
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
@@ -67,16 +71,27 @@ class TiktokenTokenizer(BaseTokenizer):
 
 class HuggingFaceTokenizer(BaseTokenizer):
     def __init__(self, model_name: str):
-        from tokenizers import Tokenizer  # type: ignore
+        self.encoder: Tokenizer = Tokenizer.from_pretrained(model_name)
 
-        self.encoder = Tokenizer.from_pretrained(model_name)
+    def _safer_encode(self, string: str) -> Encoding:
+        """
+        Encode a string using the HuggingFaceTokenizer, but if it fails,
+        encode the string as ASCII and decode it back to a string. This helps
+        in cases where the string has weird characters like \udeb4.
+        """
+        try:
+            return self.encoder.encode(string, add_special_tokens=False)
+        except Exception:
+            return self.encoder.encode(
+                string.encode("ascii", "ignore").decode(), add_special_tokens=False
+            )
 
     def encode(self, string: str) -> list[int]:
         # this returns no special tokens
-        return self.encoder.encode(string, add_special_tokens=False).ids
+        return self._safer_encode(string).ids
 
     def tokenize(self, string: str) -> list[str]:
-        return self.encoder.encode(string, add_special_tokens=False).tokens
+        return self._safer_encode(string).tokens
 
     def decode(self, tokens: list[int]) -> str:
         return self.encoder.decode(tokens)
@@ -159,9 +174,26 @@ def tokenizer_trim_content(
     content: str, desired_length: int, tokenizer: BaseTokenizer
 ) -> str:
     tokens = tokenizer.encode(content)
-    if len(tokens) > desired_length:
-        content = tokenizer.decode(tokens[:desired_length])
-    return content
+    if len(tokens) <= desired_length:
+        return content
+
+    return tokenizer.decode(tokens[:desired_length])
+
+
+def tokenizer_trim_middle(
+    tokens: list[int], desired_length: int, tokenizer: BaseTokenizer
+) -> str:
+    if len(tokens) <= desired_length:
+        return tokenizer.decode(tokens)
+    sep_str = TRIM_SEP_PAT.format(n=len(tokens) - desired_length)
+    sep_tokens = tokenizer.encode(sep_str)
+    slice_size = (desired_length - len(sep_tokens)) // 2
+    assert slice_size > 0, "Slice size is not positive, desired length is too short"
+    return (
+        tokenizer.decode(tokens[:slice_size])
+        + sep_str
+        + tokenizer.decode(tokens[-slice_size:])
+    )
 
 
 def tokenizer_trim_chunks(

backend/onyx/onyxbot/slack/listener.py

@@ -594,7 +594,7 @@ def prefilter_requests(req: SocketModeRequest, client: TenantSocketModeClient) -
         bot_tag_id = get_onyx_bot_slack_bot_id(client.web_client)
         if event_type == "message":
             is_dm = event.get("channel_type") == "im"
-            is_tagged = bot_tag_id and bot_tag_id in msg
+            is_tagged = bot_tag_id and f"<@{bot_tag_id}>" in msg
             is_onyx_bot_msg = bot_tag_id and bot_tag_id in event.get("user", "")
 
             # OnyxBot should never respond to itself
@@ -727,7 +727,11 @@ def build_request_details(
         event = cast(dict[str, Any], req.payload["event"])
         msg = cast(str, event["text"])
         channel = cast(str, event["channel"])
-        tagged = event.get("type") == "app_mention"
+        # Check for both app_mention events and messages containing bot tag
+        bot_tag_id = get_onyx_bot_slack_bot_id(client.web_client)
+        tagged = (event.get("type") == "app_mention") or (
+            event.get("type") == "message" and bot_tag_id and f"<@{bot_tag_id}>" in msg
+        )
         message_ts = event.get("ts")
         thread_ts = event.get("thread_ts")
         sender_id = event.get("user") or None

backend/onyx/onyxbot/slack/utils.py

@@ -145,7 +145,7 @@ def update_emote_react(
 
 def remove_onyx_bot_tag(message_str: str, client: WebClient) -> str:
     bot_tag_id = get_onyx_bot_slack_bot_id(web_client=client)
-    return re.sub(rf"<@{bot_tag_id}>\s", "", message_str)
+    return re.sub(rf"<@{bot_tag_id}>\s*", "", message_str)
 
 
 def _check_for_url_in_block(block: Block) -> bool:

backend/onyx/prompts/chat_prompts.py

@@ -220,3 +220,29 @@ Chat History:
 
 Based on the above, what is a short name to convey the topic of the conversation?
 """.strip()
+
+# NOTE: the prompt separation is partially done for efficiency; previously I tried
+# to do it all in one prompt with sequential format() calls but this will cause a backend
+# error when the document contains any {} as python will expect the {} to be filled by
+# format() arguments
+CONTEXTUAL_RAG_PROMPT1 = """<document>
+{document}
+</document>
+Here is the chunk we want to situate within the whole document"""
+
+CONTEXTUAL_RAG_PROMPT2 = """<chunk>
+{chunk}
+</chunk>
+Please give a short succinct context to situate this chunk within the overall document
+for the purposes of improving search retrieval of the chunk. Answer only with the succinct
+context and nothing else. """
+
+CONTEXTUAL_RAG_TOKEN_ESTIMATE = 64  # 19 + 45
+
+DOCUMENT_SUMMARY_PROMPT = """<document>
+{document}
+</document>
+Please give a short succinct summary of the entire document. Answer only with the succinct
+summary and nothing else. """
+
+DOCUMENT_SUMMARY_TOKEN_ESTIMATE = 29

backend/onyx/redis/redis_connector_doc_perm_sync.py

@@ -195,7 +195,7 @@ class RedisConnectorPermissionSync:
                 ),
                 queue=OnyxCeleryQueues.DOC_PERMISSIONS_UPSERT,
                 task_id=custom_task_id,
-                priority=OnyxCeleryPriority.HIGH,
+                priority=OnyxCeleryPriority.MEDIUM,
                 ignore_result=True,
             )
             async_results.append(result)