feat(#180): feature-flag ingestion pipeline and add brainless one-liner Quick Start

- Conditionally mount ingestion router only when OpenSearch + embedding are configured
- Add `ingestionAvailable` field to /api/health response
- Add `ingestion` feature flag to frontend (hides Search nav, Ingest button,
  OpenSearch badge, indexed badges/filters when disabled)
- Skip ingestion polling when flag is off
- Make OpenSearch + embedding optional in docker-compose via profiles
- Add docker-compose.ingestion.yml override for full-stack ingestion
- Set BATCH_PAGE_SIZE=5 default in Docker local image
- Lead Quick Start with one-liner docker run command
- Document ingestion as opt-in with dedicated section
- Add BATCH_PAGE_SIZE, MAX_FILE_SIZE_MB, MAX_PAGE_COUNT, RATE_LIMIT_RPM to config tables
- Update test counts (380 backend, 159 frontend)
- Date CHANGELOG 0.4.0, bump frontend version to 0.4.0
- Sync CONTRIBUTING.md with E2E Karate test sections

Closes #180

CHANGELOG.md

@@ -4,7 +4,7 @@ All notable changes to Docling Studio will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/), and this project adheres to [Semantic Versioning](https://semver.org/).
 
-## [0.4.0] - Unreleased
+## [0.4.0] - 2026-04-13
 
 ### Added
 

CONTRIBUTING.md

@@ -96,15 +96,43 @@ npx prettier --write src/   # auto-format
 ## Running Tests
 
 ```bash
-# Backend (199 tests)
+# Backend (377 tests)
 cd document-parser
 pytest tests/ -v
 
-# Frontend (129 tests)
+# Frontend (156 tests)
 cd frontend
 npm run test:run
 ```
 
+### E2E API (Karate)
+
+```bash
+# Generate test PDFs + start stack
+python e2e/generate-test-data.py
+docker compose up -d --wait
+
+# Run all API tests
+mvn test -f e2e/api/pom.xml
+
+# Or by tag: @smoke, @regression, @e2e
+mvn test -f e2e/api/pom.xml -Dkarate.options="--tags @smoke"
+```
+
+### E2E UI (Karate UI)
+
+```bash
+# Generate test PDFs + start stack (if not already running)
+python e2e/generate-test-data.py
+docker compose up -d --wait
+
+# Run critical UI tests (CI scope)
+mvn test -f e2e/ui/pom.xml -Dkarate.options="--tags @critical"
+
+# Run all UI tests (local scope)
+mvn test -f e2e/ui/pom.xml -Dkarate.options="--tags @ui"
+```
+
 All tests must pass before submitting a PR.
 
 ## Submitting Changes

Dockerfile

@@ -76,3 +76,4 @@ RUN pip install --no-cache-dir torch torchvision --index-url https://download.py
 RUN chown -R appuser:appuser /app \
     && chown -R appuser:appuser /usr/local/lib/python3.12/site-packages/rapidocr/models
 ENV CONVERSION_ENGINE=local
+ENV BATCH_PAGE_SIZE=5

README.md

@@ -31,9 +31,13 @@ Upload a PDF, configure the extraction pipeline, and visualize the results — t
 - **Configurable Docling pipeline** — OCR, table extraction, code/formula enrichment, picture classification & description, image generation
 - **Bounding box visualization** — color-coded element overlay directly on the PDF
 - **Per-page results** — right panel syncs with the current PDF page
+- **Chunking** — split extracted content into semantic chunks (hierarchical, hybrid, or page-based) with configurable token limits and inline editing
+- **Ingestion pipeline** — Docling → chunking → embedding → OpenSearch vector indexing (one-click from Studio)
 - **Markdown & HTML export** of extracted content
-- **Document management** — upload, list, delete
+- **Document management** — upload, list, delete, search, filter by indexing status
 - **Analysis history** — re-visit and open past analyses
+- **Upload limits** — configurable max file size and max page count per document
+- **Rate limiting** — configurable requests per minute per IP
 - **Dark / Light theme** and **FR / EN** localization
 
 
@@ -74,7 +78,7 @@ document-parser/
 ├── services/                 # Use case orchestration
 │   ├── document_service.py   # Upload, delete, preview
 │   └── analysis_service.py   # Async Docling processing
-└── tests/                    # 199 tests (pytest)
+└── tests/                    # 377 tests (pytest)
 ```
 
 ### Frontend structure (feature-based)
@@ -98,14 +102,24 @@ frontend/src/
 
 ## Quick Start
 
-Docling Studio ships two Docker image variants:
+One command, nothing else to install:
+
+```bash
+docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local
+```
+
+Open [http://localhost:3000](http://localhost:3000), upload a PDF, and get results. That's it.
+
+> **Note:** The first analysis takes longer as Docling downloads its ML models (~400 MB). Subsequent runs are fast.
+
+### Image variants
 
 | Variant | Image tag | Size | Description |
 |---------|-----------|------|-------------|
+| **local** | `latest-local` | ~1.9 GB | Full — runs Docling in-process, CPU-only |
 | **remote** | `latest-remote` | ~270 MB | Lightweight — delegates to an external [Docling Serve](https://github.com/DS4SD/docling-serve) instance |
-| **local** | `latest-local` | ~1.9 GB | Full — runs Docling in-process, CPU-only (downloads ML models on first run) |
 
-### Docker — remote mode (fastest)
+For remote mode:
 
 ```bash
 docker run -p 3000:3000 \
@@ -113,27 +127,17 @@ docker run -p 3000:3000 \
   ghcr.io/scub-france/docling-studio:latest-remote
 ```
 
-### Docker — local mode (self-contained)
+### Docker Compose
-
-```bash
-docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local
-```
-
-> **Note:** The first analysis takes longer as Docling downloads its ML models (~400 MB). Subsequent runs are fast.
-
-Open [http://localhost:3000](http://localhost:3000)
-
-### Docker Compose (for development)
 
 ```bash
 git clone https://github.com/scub-france/Docling-Studio.git
 cd Docling-Studio
 
-# Local mode (default)
+# Simple mode (backend + frontend only)
 docker compose up --build
 
-# Remote mode
+# With ingestion pipeline (OpenSearch + embeddings)
-CONVERSION_MODE=remote DOCLING_SERVE_URL=http://your-docling-serve:5001 docker compose up --build
+docker compose --profile ingestion -f docker-compose.yml -f docker-compose.ingestion.yml up --build
 ```
 
 ### Local Development
@@ -162,12 +166,12 @@ npm run dev
 ### Running Tests
 
 ```bash
-# Backend (199 tests)
+# Backend (377 tests)
 cd document-parser
 pip install pytest pytest-asyncio httpx
 pytest tests/ -v
 
-# Frontend (129 tests)
+# Frontend (156 tests)
 cd frontend
 npm run test:run
 ```
@@ -202,6 +206,43 @@ All configuration is done via environment variables. See [`.env.example`](.env.e
 | `UPLOAD_DIR` | `./uploads` | File storage directory |
 | `DB_PATH` | `./data/docling_studio.db` | SQLite database path |
 | `CONVERSION_TIMEOUT` | `600` | Max seconds for a single Docling conversion |
+| `BATCH_PAGE_SIZE` | `5` (Docker) / `0` | Pages per batch (`0` = process all at once) |
+| `MAX_FILE_SIZE_MB` | `50` | Maximum upload file size in MB (`0` = unlimited) |
+| `MAX_PAGE_COUNT` | `0` | Maximum number of pages per document (`0` = unlimited) |
+| `RATE_LIMIT_RPM` | `100` | Max requests per minute per IP (`0` = disabled) |
+
+## Upload Limits
+
+Docling Studio enforces configurable limits on uploaded documents to protect the server against oversized files and long-running analyses:
+
+- **`MAX_FILE_SIZE_MB`** (default `50`) — rejects uploads exceeding this size. Validated at two levels: early `Content-Length` check and streaming byte count.
+- **`MAX_PAGE_COUNT`** (default `0` = unlimited) — rejects documents with more pages than allowed. Useful on shared instances or Hugging Face Spaces to cap processing time.
+
+Both limits are exposed in the `/api/health` endpoint so the frontend can display them to the user before upload. Set either to `0` to disable the corresponding check.
+
+## Ingestion Pipeline (opt-in)
+
+Docling Studio can optionally index extracted chunks into [OpenSearch](https://opensearch.org/) for vector and full-text search. This requires two additional services (OpenSearch + embedding) and is **disabled by default**.
+
+To enable ingestion with Docker Compose:
+
+```bash
+docker compose --profile ingestion \
+  -f docker-compose.yml -f docker-compose.ingestion.yml \
+  up --build
+```
+
+When ingestion is enabled, the UI shows:
+- An **Ingest** button in Studio to push chunks to OpenSearch
+- An **OpenSearch** connection status badge in the sidebar
+- **Indexed / Not indexed** filters on the Documents page
+- A **Search** page for full-text and vector search across indexed documents
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `OPENSEARCH_URL` | — | OpenSearch endpoint (empty = ingestion disabled) |
+| `EMBEDDING_URL` | — | Embedding service endpoint (empty = ingestion disabled) |
+| `EMBEDDING_DIMENSION` | `384` | Vector dimension (must match embedding model) |
 
 ## CI / Release
 

docker-compose.ingestion.yml

@@ -0,0 +1,19 @@
+# Override to enable the ingestion pipeline (OpenSearch + embeddings).
+#
+# Usage:
+#   docker compose --profile ingestion -f docker-compose.yml -f docker-compose.ingestion.yml up --build
+#
+# This wires the backend to the OpenSearch and embedding services started
+# by the "ingestion" profile and ensures they are healthy before the
+# backend starts.
+
+services:
+  document-parser:
+    environment:
+      OPENSEARCH_URL: http://opensearch:9200
+      EMBEDDING_URL: http://embedding:8001
+    depends_on:
+      opensearch:
+        condition: service_healthy
+      embedding:
+        condition: service_healthy

docker-compose.yml

@@ -1,6 +1,7 @@
 services:
   # --- OpenSearch (single-node, security disabled) ---
   opensearch:
+    profiles: ["ingestion"]
     image: opensearchproject/opensearch:2
     environment:
       discovery.type: single-node
@@ -16,6 +17,7 @@ services:
 
   # --- Embedding service (sentence-transformers) ---
   embedding:
+    profiles: ["ingestion"]
     build:
       context: ./embedding-service
     environment:
@@ -49,13 +51,8 @@ services:
       RATE_LIMIT_RPM: ${RATE_LIMIT_RPM:-100}
       MAX_FILE_SIZE_MB: ${MAX_FILE_SIZE_MB:-50}
       BATCH_PAGE_SIZE: ${BATCH_PAGE_SIZE:-0}
-      OPENSEARCH_URL: http://opensearch:9200
+      OPENSEARCH_URL: ${OPENSEARCH_URL:-}
-      EMBEDDING_URL: http://embedding:8001
+      EMBEDDING_URL: ${EMBEDDING_URL:-}
-    depends_on:
-      opensearch:
-        condition: service_healthy
-      embedding:
-        condition: service_healthy
     deploy:
       resources:
         limits:

docs/getting-started.md

@@ -1,15 +1,28 @@
 # Getting Started
 
-Docling Studio ships two Docker image variants:
+## Quick Start
 
-| Variant | Image tag | Size | Description |
+One command, nothing else to install:
-|---------|-----------|------|-------------|
+
-| **remote** | `latest-remote` | ~270 MB | Lightweight — delegates to an external [Docling Serve](https://github.com/DS4SD/docling-serve) instance |
+```bash
-| **local** | `latest-local` | ~1.9 GB | Full — runs Docling in-process, CPU-only (downloads ML models on first run) |
+docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local
+```
+
+Open [http://localhost:3000](http://localhost:3000), upload a PDF, and get results. That's it.
+
+!!! note
+    The first analysis takes longer as Docling downloads its ML models (~400 MB). Subsequent runs are fast.
 
 ![Docker architecture](images/docker.png){ width="600" }
 
-## Docker — remote mode (fastest)
+## Image Variants
+
+| Variant | Image tag | Size | Description |
+|---------|-----------|------|-------------|
+| **local** | `latest-local` | ~1.9 GB | Full — runs Docling in-process, CPU-only |
+| **remote** | `latest-remote` | ~270 MB | Lightweight — delegates to an external [Docling Serve](https://github.com/DS4SD/docling-serve) instance |
+
+For remote mode:
 
 ```bash
 docker run -p 3000:3000 \
@@ -17,27 +30,19 @@ docker run -p 3000:3000 \
   ghcr.io/scub-france/docling-studio:latest-remote
 ```
 
-## Docker — local mode (self-contained)
+## Docker Compose
-
-```bash
-docker run -p 3000:3000 ghcr.io/scub-france/docling-studio:latest-local
-```
-
-> **Note:** The first analysis takes longer as Docling downloads its ML models (~400 MB). Subsequent runs are fast.
-
-Open [http://localhost:3000](http://localhost:3000).
-
-## Docker Compose (recommended for development)
 
 ```bash
 git clone https://github.com/scub-france/Docling-Studio.git
 cd Docling-Studio
 
-# Local mode (default)
+# Simple mode (backend + frontend only)
 docker compose up --build
 
-# Remote mode
+# With ingestion pipeline (OpenSearch + embeddings)
-CONVERSION_MODE=remote DOCLING_SERVE_URL=http://your-docling-serve:5001 docker compose up --build
+docker compose --profile ingestion \
+  -f docker-compose.yml -f docker-compose.ingestion.yml \
+  up --build
 ```
 
 ## Local Development
@@ -136,10 +141,48 @@ All configuration is done via environment variables:
 | `UPLOAD_DIR` | `./uploads` | File storage directory |
 | `DB_PATH` | `./data/docling_studio.db` | SQLite database path |
 | `CONVERSION_TIMEOUT` | `600` | Max seconds per Docling conversion |
+| `BATCH_PAGE_SIZE` | `5` (Docker) / `0` | Pages per batch (`0` = process all at once) |
 | `MAX_CONCURRENT_ANALYSES` | `3` | Maximum parallel analysis jobs |
 | `DEPLOYMENT_MODE` | `self-hosted` | `self-hosted` or `huggingface` (shows disclaimer banner) |
+| `MAX_FILE_SIZE_MB` | `50` | Maximum upload file size in MB (`0` = unlimited) |
+| `MAX_PAGE_COUNT` | `0` | Maximum number of pages per document (`0` = unlimited) |
+| `RATE_LIMIT_RPM` | `100` | Max requests per minute per IP (`0` = disabled) |
 | `APP_VERSION` | `dev` | Application version (set automatically by CI/Docker) |
 
+## Upload Limits
+
+Docling Studio enforces configurable limits on uploaded documents to protect the server against oversized files and long-running analyses:
+
+- **`MAX_FILE_SIZE_MB`** (default `50`) — rejects uploads exceeding this size. Validated at two levels: early `Content-Length` check and streaming byte count.
+- **`MAX_PAGE_COUNT`** (default `0` = unlimited) — rejects documents with more pages than allowed. Useful on shared instances or Hugging Face Spaces to cap processing time.
+
+Both limits are exposed in the `/api/health` endpoint so the frontend can display them to the user before upload. Set either to `0` to disable the corresponding check.
+
+## Ingestion Pipeline (opt-in)
+
+Docling Studio can optionally index extracted chunks into [OpenSearch](https://opensearch.org/) for vector and full-text search. This requires two additional services (OpenSearch + embedding) and is **disabled by default**.
+
+To enable ingestion with Docker Compose:
+
+```bash
+docker compose --profile ingestion \
+  -f docker-compose.yml -f docker-compose.ingestion.yml \
+  up --build
+```
+
+When ingestion is enabled, the UI shows:
+
+- An **Ingest** button in Studio to push chunks to OpenSearch
+- An **OpenSearch** connection status badge in the sidebar
+- **Indexed / Not indexed** filters on the Documents page
+- A **Search** page for full-text and vector search across indexed documents
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `OPENSEARCH_URL` | — | OpenSearch endpoint (empty = ingestion disabled) |
+| `EMBEDDING_URL` | — | Embedding service endpoint (empty = ingestion disabled) |
+| `EMBEDDING_DIMENSION` | `384` | Vector dimension (must match embedding model) |
+
 ## System Requirements
 
 | | Remote image | Local image |

docs/index.md

@@ -18,7 +18,8 @@ Upload a PDF, configure the extraction pipeline, and visualize the results — t
 - **Document management** — upload, list, delete
 - **Analysis history** — re-visit and open past analyses
 - **Feature flags** — capabilities adapt to the conversion engine (local vs remote)
-- **Rate limiting** — 60 requests per minute per IP to protect the backend
+- **Upload limits** — configurable max file size (`MAX_FILE_SIZE_MB`) and max page count (`MAX_PAGE_COUNT`) per document
+- **Rate limiting** — configurable requests per minute per IP (`RATE_LIMIT_RPM`)
 - **Deployment modes** — self-hosted (default) or HuggingFace Spaces (with disclaimer banner)
 - **Health endpoint** — `/api/health` reports engine type, deployment mode, and database status
 - **Dark / Light theme** and **FR / EN** localization

document-parser/api/schemas.py

@@ -34,6 +34,7 @@ class HealthResponse(_CamelModel):
     database: str
     max_page_count: int | None = None
     max_file_size_mb: int | None = None
+    ingestion_available: bool = False
 
 
 class DocumentResponse(_CamelModel):

document-parser/main.py

@@ -138,7 +138,11 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
     document_repo, analysis_repo = _build_repos()
     app.state.analysis_service = _build_analysis_service(document_repo, analysis_repo)
     app.state.document_service = _build_document_service(document_repo, analysis_repo)
-    app.state.ingestion_service = _build_ingestion_service()
+    ingestion_service = _build_ingestion_service()
+    app.state.ingestion_service = ingestion_service
+    if ingestion_service is not None:
+        app.include_router(ingestion_router)
+        logger.info("Ingestion router mounted")
     logger.info("Docling Studio backend ready (engine=%s)", settings.conversion_engine)
     yield
 
@@ -165,7 +169,6 @@ if settings.rate_limit_rpm > 0:
 
 app.include_router(documents_router)
 app.include_router(analyses_router)
-app.include_router(ingestion_router)
 
 
 @app.get("/api/health", response_model=HealthResponse)
@@ -188,4 +191,5 @@ async def health() -> HealthResponse:
         database=db_status,
         max_page_count=settings.max_page_count if settings.max_page_count > 0 else None,
         max_file_size_mb=settings.max_file_size_mb if settings.max_file_size_mb > 0 else None,
+        ingestion_available=getattr(app.state, "ingestion_service", None) is not None,
     )

document-parser/tests/test_api_endpoints.py

@@ -51,6 +51,23 @@ class TestHealthEndpoint:
         assert "maxFileSizeMb" in data
         assert data["maxFileSizeMb"] == 50
 
+    def test_health_exposes_ingestion_available_false(self, client):
+        original = getattr(app.state, "ingestion_service", None)
+        app.state.ingestion_service = None
+        resp = client.get("/api/health")
+        app.state.ingestion_service = original
+        data = resp.json()
+        assert "ingestionAvailable" in data
+        assert data["ingestionAvailable"] is False
+
+    def test_health_exposes_ingestion_available_true(self, client):
+        original = getattr(app.state, "ingestion_service", None)
+        app.state.ingestion_service = MagicMock()
+        resp = client.get("/api/health")
+        app.state.ingestion_service = original
+        data = resp.json()
+        assert data["ingestionAvailable"] is True
+
 
 class TestDocumentEndpoints:
     def test_list_documents(self, client, mock_document_service):

document-parser/tests/test_ingestion_api.py

@@ -104,7 +104,18 @@ class TestIngestionStatus:
 
 
 class TestIngestionDisabled:
-    def test_returns_503_when_disabled(self) -> None:
+    def test_router_not_mounted_returns_404(self) -> None:
+        """When ingestion service is None, router should not be mounted → 404."""
+        app = FastAPI()
+        # Do NOT include ingestion router — simulates main.py conditional mount
+        app.state.ingestion_service = None
+        app.state.analysis_service = AsyncMock()
+        tc = TestClient(app)
+        resp = tc.post("/api/ingestion/job-1")
+        assert resp.status_code == 404
+
+    def test_status_still_returns_503_when_router_mounted_but_service_none(self) -> None:
+        """If router is mounted but service is None, endpoints return 503."""
         app = FastAPI()
         app.include_router(router)
         app.state.ingestion_service = None

frontend/package-lock.json

@@ -1,12 +1,12 @@
 {
   "name": "docling-studio",
-  "version": "0.3.0",
+  "version": "0.3.1",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {
     "": {
       "name": "docling-studio",
-      "version": "0.3.0",
+      "version": "0.3.1",
       "dependencies": {
         "dompurify": "^3.3.3",
         "marked": "^17.0.4",

frontend/package.json

@@ -1,6 +1,6 @@
 {
   "name": "docling-studio",
-  "version": "0.3.1",
+  "version": "0.4.0",
   "private": true,
   "type": "module",
   "scripts": {

frontend/src/features/chunking/ui/ChunkPanel.vue

@@ -202,7 +202,10 @@
       </div>
     </div>
 
-    <div class="chunk-empty" v-else-if="!chunkingStore.rechunking">
+    <div
+      class="chunk-empty"
+      v-if="!pageChunks.length && !chunkingStore.rechunking && deleteConfirmIdx === -1"
+    >
       <p>
         {{ chunks.length ? t('chunking.noChunksOnPage') : t('chunking.noChunks') }}
       </p>

frontend/src/features/feature-flags/store.test.ts

@@ -82,6 +82,38 @@ describe('useFeatureFlagStore', () => {
     expect(store.maxFileSizeMb).toBe(0)
   })
 
+  it('enables ingestion when ingestionAvailable is true', async () => {
+    mockApiFetch.mockResolvedValue({
+      status: 'ok',
+      engine: 'local',
+      ingestionAvailable: true,
+    })
+    const store = useFeatureFlagStore()
+    await store.load()
+    expect(store.ingestionAvailable).toBe(true)
+    expect(store.isEnabled('ingestion')).toBe(true)
+  })
+
+  it('disables ingestion when ingestionAvailable is false', async () => {
+    mockApiFetch.mockResolvedValue({
+      status: 'ok',
+      engine: 'local',
+      ingestionAvailable: false,
+    })
+    const store = useFeatureFlagStore()
+    await store.load()
+    expect(store.ingestionAvailable).toBe(false)
+    expect(store.isEnabled('ingestion')).toBe(false)
+  })
+
+  it('defaults ingestionAvailable to false when missing', async () => {
+    mockApiFetch.mockResolvedValue({ status: 'ok', engine: 'local' })
+    const store = useFeatureFlagStore()
+    await store.load()
+    expect(store.ingestionAvailable).toBe(false)
+    expect(store.isEnabled('ingestion')).toBe(false)
+  })
+
   it('handles health endpoint failure gracefully', async () => {
     mockApiFetch.mockRejectedValue(new Error('Network error'))
     const store = useFeatureFlagStore()

frontend/src/features/feature-flags/store.ts

@@ -13,9 +13,10 @@ interface HealthResponse {
   deploymentMode?: DeploymentMode
   maxPageCount?: number
   maxFileSizeMb?: number
+  ingestionAvailable?: boolean
 }
 
-export type FeatureFlag = 'chunking' | 'disclaimer'
+export type FeatureFlag = 'chunking' | 'disclaimer' | 'ingestion'
 
 interface FeatureFlagDef {
   description: string
@@ -25,6 +26,7 @@ interface FeatureFlagDef {
 interface FeatureFlagContext {
   engine: ConversionEngine | null
   deploymentMode: DeploymentMode | null
+  ingestionAvailable: boolean
 }
 
 const featureRegistry: Record<FeatureFlag, FeatureFlagDef> = {
@@ -36,6 +38,10 @@ const featureRegistry: Record<FeatureFlag, FeatureFlagDef> = {
     description: 'Show shared-instance disclaimer banner',
     isEnabled: (ctx) => ctx.deploymentMode === 'huggingface',
   },
+  ingestion: {
+    description: 'OpenSearch ingestion pipeline (embedding + vector indexing)',
+    isEnabled: (ctx) => ctx.ingestionAvailable,
+  },
 }
 
 export const useFeatureFlagStore = defineStore('feature-flags', () => {
@@ -43,6 +49,7 @@ export const useFeatureFlagStore = defineStore('feature-flags', () => {
   const deploymentMode = ref<DeploymentMode | null>(null)
   const maxPageCount = ref<number>(0)
   const maxFileSizeMb = ref<number>(0)
+  const ingestionAvailable = ref(false)
   const appVersion = ref<string>(__APP_VERSION__)
   const loaded = ref(false)
   const error = ref<string | null>(null)
@@ -50,6 +57,7 @@ export const useFeatureFlagStore = defineStore('feature-flags', () => {
   const context = computed<FeatureFlagContext>(() => ({
     engine: engine.value,
     deploymentMode: deploymentMode.value,
+    ingestionAvailable: ingestionAvailable.value,
   }))
 
   function isEnabled(flag: FeatureFlag): boolean {
@@ -65,6 +73,7 @@ export const useFeatureFlagStore = defineStore('feature-flags', () => {
       deploymentMode.value = data.deploymentMode ?? 'self-hosted'
       maxPageCount.value = data.maxPageCount ?? 0
       maxFileSizeMb.value = data.maxFileSizeMb ?? 0
+      ingestionAvailable.value = data.ingestionAvailable ?? false
       appMaxFileSizeMb.value = maxFileSizeMb.value
       appMaxPageCount.value = maxPageCount.value
       if (data.version) appVersion.value = data.version
@@ -81,6 +90,7 @@ export const useFeatureFlagStore = defineStore('feature-flags', () => {
     deploymentMode,
     maxPageCount,
     maxFileSizeMb,
+    ingestionAvailable,
     appVersion,
     loaded,
     error,

frontend/src/pages/DocumentsPage.vue

@@ -9,7 +9,7 @@
           class="search-input"
           :placeholder="t('ingestion.search')"
         />
-        <div class="filter-group">
+        <div v-if="ingestionEnabled" class="filter-group">
           <button
             v-for="f in filters"
             :key="f.value"
@@ -54,17 +54,19 @@
             </div>
           </div>
           <div class="doc-row-actions">
-            <span
+            <template v-if="ingestionEnabled">
-              v-if="ingestionStore.ingestedDocs[doc.id]"
+              <span
-              class="status-badge indexed"
+                v-if="ingestionStore.ingestedDocs[doc.id]"
-              :title="t('ingestion.chunksIndexed', { n: ingestionStore.ingestedDocs[doc.id] })"
+                class="status-badge indexed"
-            >
+                :title="t('ingestion.chunksIndexed', { n: ingestionStore.ingestedDocs[doc.id] })"
-              {{ t('ingestion.indexed') }}
+              >
-              <span class="badge-count">{{ ingestionStore.ingestedDocs[doc.id] }}</span>
+                {{ t('ingestion.indexed') }}
-            </span>
+                <span class="badge-count">{{ ingestionStore.ingestedDocs[doc.id] }}</span>
-            <span v-else class="status-badge not-indexed">
+              </span>
-              {{ t('ingestion.notIndexed') }}
+              <span v-else class="status-badge not-indexed">
-            </span>
+                {{ t('ingestion.notIndexed') }}
+              </span>
+            </template>
             <button
               class="action-btn"
               :title="t('ingestion.openInStudio')"
@@ -77,7 +79,7 @@
               </svg>
             </button>
             <button
-              v-if="ingestionStore.ingestedDocs[doc.id]"
+              v-if="ingestionEnabled && ingestionStore.ingestedDocs[doc.id]"
               class="action-btn unindex"
               :title="t('ingestion.deleteIndex')"
               @click="confirmRemoveFromIndex(doc.id)"
@@ -110,13 +112,16 @@
 import { computed, onMounted, ref } from 'vue'
 import { useRouter } from 'vue-router'
 import { useDocumentStore } from '../features/document/store'
+import { useFeatureFlagStore } from '../features/feature-flags/store'
 import { useIngestionStore } from '../features/ingestion/store'
 import { useI18n } from '../shared/i18n'
 import { formatSize } from '../shared/format'
 import type { Document } from '../shared/types'
 
 const docStore = useDocumentStore()
+const featureStore = useFeatureFlagStore()
 const ingestionStore = useIngestionStore()
+const ingestionEnabled = computed(() => featureStore.isEnabled('ingestion'))
 const router = useRouter()
 const { t } = useI18n()
 
@@ -173,7 +178,7 @@ function confirmRemoveFromIndex(docId: string) {
 }
 
 async function handleDelete(docId: string) {
-  if (ingestionStore.ingestedDocs[docId]) {
+  if (ingestionEnabled.value && ingestionStore.ingestedDocs[docId]) {
     await ingestionStore.deleteIngested(docId)
   }
   await docStore.remove(docId)
@@ -181,7 +186,9 @@ async function handleDelete(docId: string) {
 
 onMounted(() => {
   docStore.load()
-  ingestionStore.checkAvailability()
+  if (ingestionEnabled.value) {
+    ingestionStore.checkAvailability()
+  }
 })
 </script>
 

frontend/src/pages/SearchPage.vue

@@ -4,7 +4,7 @@
       <h1 class="page-title">{{ t('nav.search') }}</h1>
     </div>
 
-    <div v-if="!ingestionStore.available" class="tab-empty">
+    <div v-if="!ingestionEnabled || !ingestionStore.available" class="tab-empty">
       {{ t('ingestion.unavailable') }}
     </div>
 
@@ -50,13 +50,16 @@
 </template>
 
 <script setup lang="ts">
-import { onMounted, ref } from 'vue'
+import { computed, onMounted, ref } from 'vue'
 import { useSearchStore } from '../features/search/store'
+import { useFeatureFlagStore } from '../features/feature-flags/store'
 import { useIngestionStore } from '../features/ingestion/store'
 import { useI18n } from '../shared/i18n'
 
 const searchStore = useSearchStore()
+const featureStore = useFeatureFlagStore()
 const ingestionStore = useIngestionStore()
+const ingestionEnabled = computed(() => featureStore.isEnabled('ingestion'))
 const { t } = useI18n()
 
 const searchInput = ref('')
@@ -70,7 +73,9 @@ function runSearch() {
 }
 
 onMounted(() => {
-  ingestionStore.checkAvailability()
+  if (ingestionEnabled.value) {
+    ingestionStore.checkAvailability()
+  }
 })
 </script>
 

frontend/src/pages/StudioPage.vue

@@ -67,7 +67,7 @@
             {{ t('studio.prepare') }}
           </button>
           <button
-            v-if="chunkingEnabled && ingestionStore.available"
+            v-if="chunkingEnabled && ingestionEnabled && ingestionStore.available"
             class="toggle-btn"
             data-e2e="toggle-btn"
             :class="{ active: mode === 'ingest' }"
@@ -504,6 +504,7 @@ const analysisStore = useAnalysisStore()
 const ingestionStore = useIngestionStore()
 const { t } = useI18n()
 const chunkingEnabled = useFeatureFlag('chunking')
+const ingestionEnabled = useFeatureFlag('ingestion')
 
 const mode = ref('configure')
 const currentPage = ref(1)
@@ -636,7 +637,9 @@ watch(
 onMounted(async () => {
   await documentStore.load()
   analysisStore.load()
-  ingestionStore.checkAvailability()
+  if (ingestionEnabled.value) {
+    ingestionStore.checkAvailability()
+  }
 
   // Restore analysis from history via query param
   const analysisId = route.query.analysisId

frontend/src/shared/ui/AppSidebar.vue

@@ -46,6 +46,7 @@
       </RouterLink>
 
       <RouterLink
+        v-if="ingestionEnabled"
         to="/search"
         class="nav-item"
         data-e2e="nav-search"
@@ -96,7 +97,7 @@
 
     <div class="sidebar-footer">
       <div
-        v-if="ingestionStore.available"
+        v-if="ingestionEnabled && ingestionStore.available"
         class="opensearch-status"
         :title="
           ingestionStore.opensearchConnected
@@ -136,6 +137,7 @@ import { useIngestionStore } from '../../features/ingestion/store'
 
 const featureStore = useFeatureFlagStore()
 const ingestionStore = useIngestionStore()
+const ingestionEnabled = computed(() => featureStore.isEnabled('ingestion'))
 const version = computed(() => featureStore.appVersion)
 const route = useRoute()
 const { t } = useI18n()
@@ -145,8 +147,10 @@ defineProps({
 })
 
 onMounted(() => {
-  ingestionStore.checkAvailability()
+  if (ingestionEnabled.value) {
-  ingestionStore.startPolling(30_000)
+    ingestionStore.checkAvailability()
+    ingestionStore.startPolling(30_000)
+  }
 })
 
 onBeforeUnmount(() => {