bump: version 0.43.0 → 0.44.0

Merge pull request #329 from cbcoutinho/feature/nextcloud-ui-improvements
feat: Redesign UI and improve vector visualization
2025-11-19 22:43:03 +00:00 · 2025-11-19 23:42:32 +01:00 · 2025-11-19 19:43:20 +01:00 · 2025-11-19 14:42:06 +01:00 · 2025-11-19 14:10:53 +01:00 · 2025-11-19 13:51:08 +01:00
40 changed files with 3039 additions and 999 deletions
@@ -6,3 +6,4 @@

 !nextcloud_mcp_server/**/*.py
 !nextcloud_mcp_server/**/*.html
+!nextcloud_mcp_server/auth/static/*
@@ -15,12 +15,12 @@ jobs:
      packages: write
    steps:
      - name: Check out
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5
+        uses: actions/checkout@93cb6efe18208431cddfb8368fd83d5badbf9bfd # v5
        with:
          fetch-depth: 0
          token: "${{ secrets.PERSONAL_ACCESS_TOKEN }}"
      - name: Create bump and changelog
-        uses: commitizen-tools/commitizen-action@9615e7be1cf341393c52e865ebbdaa0712176d81 # 0.25.0
+        uses: commitizen-tools/commitizen-action@bb4f1df6601e2a1a891506581b0c53acdc88e07d # 0.26.0
        with:
          github_token: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
          changelog_increment_filename: body.md
@@ -12,7 +12,7 @@ jobs:
      packages: write
    steps:
      - name: Checkout repository
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5
+        uses: actions/checkout@93cb6efe18208431cddfb8368fd83d5badbf9bfd # v5

      - name: Docker meta
        id: meta
@@ -14,7 +14,7 @@ jobs:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5
+        uses: actions/checkout@93cb6efe18208431cddfb8368fd83d5badbf9bfd # v5
        with:
          fetch-depth: 0

@@ -18,7 +18,7 @@ jobs:
      contents: read
    steps:
      - name: Checkout
-        uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5
+        uses: actions/checkout@93cb6efe18208431cddfb8368fd83d5badbf9bfd # v5
      - name: Install uv
        uses: astral-sh/setup-uv@5a7eac68fb9809dea845d802897dc5c723910fa3 # v7.1.3
      - name: Install Python 3.11
@@ -9,7 +9,7 @@ jobs:
  linting:
    runs-on: ubuntu-latest
    steps:
-      - uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+      - uses: actions/checkout@93cb6efe18208431cddfb8368fd83d5badbf9bfd # v5.0.1
      - name: Install the latest version of uv
        uses: astral-sh/setup-uv@5a7eac68fb9809dea845d802897dc5c723910fa3 # v7.1.3
      - name: Check format
@@ -27,7 +27,7 @@ jobs:
    runs-on: ubuntu-latest

    steps:
-      - uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0
+      - uses: actions/checkout@93cb6efe18208431cddfb8368fd83d5badbf9bfd # v5.0.1
        with:
          submodules: 'true'

@@ -1,3 +1,41 @@
+## v0.44.0 (2025-11-19)
+
+### Feat
+
+- Improve vector visualization with static assets and fixes
+- Redesign UI to match Nextcloud ecosystem aesthetic
+
+### Fix
+
+- Improve 3D plot rendering with explicit dimensions and window resize support
+- Preserve 3D plot camera and improve documentation
+- Preserve 3D plot camera position and fix CSS loading
+
+## v0.43.0 (2025-11-18)
+
+### Feat
+
+- Replace custom document chunker with LangChain MarkdownTextSplitter
+
+## v0.42.0 (2025-11-17)
+
+### Feat
+
+- **viz**: Add dual-score display and improve UI controls
+
+## v0.41.0 (2025-11-17)
+
+### Feat
+
+- add configurable fusion algorithms for BM25 hybrid search
+- add chunk position tracking to vector indexing and search
+- add vector viz template and chunk context endpoint
+
+### Fix
+
+- prevent infinite loop in DocumentChunker with position tracking
+- Relax SearchResult validation to support DBSF fusion scores > 1.0
+
 ## v0.40.0 (2025-11-16)

 ### Feat
@@ -1,19 +1,19 @@
-FROM docker.io/library/python:3.12-slim-trixie@sha256:d86b4c74b936c438cd4cc3a9f7256b9a7c27ad68c7caf8c205e18d9845af0164
+FROM docker.io/library/python:3.12-slim-trixie@sha256:2e683fc3e18a248aa23b8022f2a3474b072b04fb851efe9b49f6b516a8944939

-COPY --from=ghcr.io/astral-sh/uv:latest@sha256:f6e3549ed287fee0ddde2460a2a74a2d74366f84b04aaa34c1f19fec40da8652 /uv /uvx /bin/
+COPY --from=ghcr.io/astral-sh/uv:0.9.10@sha256:29bd45092ea8902c0bbb7f0a338f0494a382b1f4b18355df5be270ade679ff1d /uv /uvx /bin/

 # Install dependencies
 # 1. git (required for caldav dependency from git)
 # 2. sqlite for development with token db
 RUN apt update && apt install --no-install-recommends --no-install-suggests -y \
    git \
-    sqlite3
+    sqlite3 && apt clean

 WORKDIR /app

 COPY . .

-RUN uv sync --locked --no-dev --no-editable
+RUN uv sync --locked --no-dev --no-editable --no-cache

 ENV PYTHONUNBUFFERED=1
 ENV VIRTUAL_ENV=/app/.venv
@@ -1,3 +1,7 @@
+<p align="center">
+  <img src="astrolabe.svg" alt="Nextcloud MCP Server" width="128" height="128">
+</p>
+
 # Nextcloud MCP Server

 [![Docker Image](https://img.shields.io/badge/docker-ghcr.io/cbcoutinho/nextcloud--mcp--server-blue)](https://github.com/cbcoutinho/nextcloud-mcp-server/pkgs/container/nextcloud-mcp-server)
@@ -29,6 +33,12 @@ docker run -p 127.0.0.1:8000:8000 --env-file .env --rm \

 # 3. Test the connection
 curl http://127.0.0.1:8000/health/ready
+
+# 4. Connect to the endpoint
+http://127.0.0.1:8000/sse
+
+# 4. Or with --transport streamable-http
+http://127.0.0.1:8000/mcp
 ```

 **Next Steps:**
@@ -123,6 +133,7 @@ This enables natural language queries and helps discover related content across
 - **[App Documentation](docs/)** - Notes, Calendar, Contacts, WebDAV, Deck, Cookbook, Tables
 - **[Document Processing](docs/configuration.md#document-processing)** - OCR and text extraction setup
 - **[Semantic Search Architecture](docs/semantic-search-architecture.md)** - Experimental vector search (Notes only, opt-in)
+- **[Vector Sync UI Guide](docs/user-guide/vector-sync-ui.md)** - Browser interface for semantic search visualization and testing

 ### Advanced Topics
 - **[OAuth Architecture](docs/oauth-architecture.md)** - How OAuth works (experimental)
@@ -2,4 +2,30 @@

 set -euox pipefail

-php /var/www/html/occ app:enable notes
+echo "Installing and configuring notes app for testing..."
+
+# Check if development notes app is mounted at /opt/apps/notes
+if [ -d /opt/apps/notes ]; then
+    echo "Development notes app found at /opt/apps/notes"
+
+    # Remove any existing notes app in apps (from app store or old symlink)
+    if [ -e /var/www/html/custom_apps/notes ]; then
+        echo "Removing existing notes in apps..."
+        rm -rf /var/www/html/custom_apps/notes
+    fi
+
+    # Create symlink from apps to the mounted development version
+    # Per Nextcloud docs: apps outside server root need symlinks in server root
+    echo "Creating symlink: custom_apps/notes -> /opt/apps/notes"
+    ln -sf /opt/apps/notes /var/www/html/custom_apps/notes
+
+    echo "Enabling notes app from /opt/apps (development mode via symlink)"
+    php /var/www/html/occ app:enable notes
+elif [ -d /var/www/html/custom_apps/notes ]; then
+    echo "notes app directory found in apps (already installed)"
+    php /var/www/html/occ app:enable notes
+else
+    echo "notes app not found, installing from app store..."
+    php /var/www/html/occ app:install notes
+    php /var/www/html/occ app:enable notes
+fi
@@ -1,9 +1,9 @@
 dependencies:
 - name: qdrant
  repository: https://qdrant.github.io/qdrant-helm
-  version: 1.15.5
+  version: 1.16.0
 - name: ollama
  repository: https://otwld.github.io/ollama-helm
  version: 1.34.0
-digest: sha256:d51c97d05be2614b751c0dd7267ef7dc959eff5ebef859c5f895c5c554b7a874
-generated: "2025-11-09T17:08:02.86648061Z"
+digest: sha256:9dfb8d6e3d5488f669d4c37f3a766213b598ff3de2aead2c734789736c7835b4
+generated: "2025-11-17T17:08:48.055530019Z"
@@ -2,8 +2,8 @@ apiVersion: v2
 name: nextcloud-mcp-server
 description: A Helm chart for Nextcloud MCP Server - enables AI assistants to interact with Nextcloud
 type: application
-version: 0.40.0
-appVersion: "0.40.0"
+version: 0.44.0
+appVersion: "0.44.0"
 keywords:
  - nextcloud
  - mcp
@@ -27,7 +27,7 @@ annotations:
  grafana_dashboard_folder: "Nextcloud MCP"
 dependencies:
  - name: qdrant
-    version: "1.15.5"
+    version: "1.16.0"
    repository: https://qdrant.github.io/qdrant-helm
    condition: qdrant.networkMode.deploySubchart
  - name: ollama
@@ -3,7 +3,7 @@ services:
  # https://hub.docker.com/_/mariadb
  db:
    # Note: Check the recommend version here: https://docs.nextcloud.com/server/latest/admin_manual/installation/system_requirements.html#server
-    image: docker.io/library/mariadb:lts@sha256:6b848cb24fbbd87429917f6c4422ac53c343e85692eb0fef86553e99e4f422f3
+    image: docker.io/library/mariadb:lts@sha256:1cac8492bd78b1ec693238dc600be173397efd7b55eabc725abc281dc855b482
    restart: always
    command: --transaction-isolation=READ-COMMITTED
    volumes:
@@ -17,11 +17,11 @@ services:
  # Note: Redis is an external service. You can find more information about the configuration here:
  # https://hub.docker.com/_/redis
  redis:
-    image: docker.io/library/redis:alpine@sha256:28c9c4d7596949a24b183eaaab6455f8e5d55ecbf72d02ff5e2c17fe72671d31
+    image: docker.io/library/redis:alpine@sha256:5013e94192ef18a5d8368179c7522e5300f9265cc339cadac76c7b93303a2752
    restart: always

  app:
-    image: docker.io/library/nextcloud:32.0.1@sha256:5b043f7ea2f609d5ff5635f475c30d303bec17775a5c3f7fa435e3818e669120
+    image: docker.io/library/nextcloud:32.0.1@sha256:d572839eeb693026d72a0c6aa48076df0bb8930797ea321e604936ef7189d06e
    restart: always
    ports:
      - 0.0.0.0:8080:80
@@ -34,7 +34,7 @@ services:
      - ./app-hooks:/docker-entrypoint-hooks.d:ro
      # Mount OIDC development directory outside /var/www/html to avoid rsync conflicts
      # The post-installation hook will register /opt/apps as an additional app directory
-      #- ./third_party:/opt/apps:ro
+      - ./third_party:/opt/apps:ro
    environment:
      - NEXTCLOUD_TRUSTED_DOMAINS=app
      - NEXTCLOUD_ADMIN_USER=admin
@@ -225,7 +225,7 @@ services:
      - keycloak-oauth-storage:/app/.oauth

  qdrant:
-    image: qdrant/qdrant:v1.15.5@sha256:0fb8897412abc81d1c0430a899b9a81eb8328aa634e7242d1bc804c1fe8fe863
+    image: qdrant/qdrant:v1.16.0@sha256:1005201498cf927d835383d0f918b17d8c9da7db58550f169f694455e42d78f4
    restart: always
    ports:
      - 127.0.0.1:6333:6333  # REST API
@@ -1,7 +1,8 @@
 # ADR-011: Improving Semantic Search Quality Through Better Chunking and Embeddings

-**Status**: Proposed
+**Status**: Partially Implemented (Chunking Complete, Embeddings Pending)
 **Date**: 2025-11-12
+**Implementation Date**: 2025-11-18 (Chunking)
 **Authors**: Development Team
 **Related**: ADR-003 (Vector Database Architecture), ADR-008 (MCP Sampling for RAG)

@@ -893,3 +894,50 @@ This ADR addresses the root causes of poor semantic search recall:
 - No new infrastructure or ongoing costs

 **Next Steps**: Approve ADR → Implement changes → Reindex → Validate → Production rollout
+
+## Implementation Status
+
+### Completed (2025-11-18)
+
+**✅ Semantic Markdown-Aware Chunking (Option C1 + C3 Hybrid)**
+
+Implementation details:
+- Replaced custom word-based chunking with `MarkdownTextSplitter` from LangChain
+- Optimized for Nextcloud Notes markdown content with special handling for:
+  - Headers (`#`, `##`, `###`, etc.)
+  - Code blocks (` ``` `)
+  - Lists (`-`, `*`, `1.`)
+  - Horizontal rules (`---`)
+  - Paragraphs and sentences
+- Maintained `ChunkWithPosition` interface for backward compatibility
+- Updated configuration defaults:
+  - `DOCUMENT_CHUNK_SIZE`: 512 words → 2048 characters
+  - `DOCUMENT_CHUNK_OVERLAP`: 50 words → 200 characters
+- Updated unit tests to verify position tracking and boundary preservation
+- All tests passing with markdown-aware character-based chunking
+
+**Files Modified**:
+- `nextcloud_mcp_server/vector/document_chunker.py` - LangChain integration
+- `nextcloud_mcp_server/config.py` - Character-based defaults
+- `tests/unit/test_document_chunker.py` - Updated test suite
+
+**Dependencies Added**:
+- `langchain-text-splitters>=1.0.0` (already present in `pyproject.toml`)
+
+**Migration Required**:
+- ⚠️ Full reindex required to apply new chunking strategy
+- Existing documents in vector database use old word-based chunks
+- See "Migration Strategy" section above for reindexing process
+
+### Pending
+
+**⏳ Embedding Model Upgrade (Option E1)**
+
+Still to be implemented:
+- Switch from `nomic-embed-text` (768-dim) to `mxbai-embed-large-v1` (1024-dim)
+- Implement dynamic dimension detection in `ollama_provider.py`
+- Create migration script for collection reindexing
+- Run benchmarking to validate improvement
+- Deploy to production with atomic collection swap
+
+**Estimated Timeline**: 1-2 weeks for implementation and validation
@@ -0,0 +1,93 @@
+# Vector Sync UI Guide
+
+This guide covers the browser-based interface for the Nextcloud MCP Server's semantic search and vector synchronization features.
+
+## Overview
+
+The Vector Sync UI (`/app`) provides an interactive interface to test semantic search queries and visualize results from your Nextcloud documents. It exposes the same retrieval capabilities that LLMs use in Retrieval-Augmented Generation (RAG) workflows, powered by Alpine.js for reactive state, htmx for dynamic updates, and Plotly.js for 3D visualization.
+
+**Supported Apps**: Notes, Files (text/PDF), Calendar (events/tasks), Contacts (CardDAV), and Deck are indexed and searchable.
+
+## Accessing the UI
+
+Navigate to `/app` after authentication:
+- **BasicAuth mode**: `http://localhost:8000/app` (uses credentials from environment)
+- **OAuth mode**: `http://localhost:8000/app` (redirects to login if not authenticated)
+
+## Tabs
+
+### Welcome Page
+
+Landing page that introduces semantic search and RAG workflows. Shows authentication status, explains how vector embeddings work, and provides feature navigation. Adapts content based on whether `VECTOR_SYNC_ENABLED=true`.
+
+### User Info
+
+Displays authentication details and session information:
+- **BasicAuth**: Username, mode badge, Nextcloud host
+- **OAuth**: Username, session ID (truncated), background access status, IdP profile, revocation option
+
+### Vector Sync Status
+
+Real-time monitoring of document indexing:
+- **Indexed Documents**: Total chunks stored in Qdrant vector database (immediately searchable)
+- **Pending Documents**: Queue awaiting embedding processing
+- **Status**: "✓ Idle" (green) when up-to-date, "⟳ Syncing" (orange) during processing
+
+Auto-refreshes every 10 seconds via htmx. Check this tab after adding content to verify indexing completion.
+
+### Vector Visualization
+
+Interactive search interface with 3D PCA plot of semantic space.
+
+**Search Controls**:
+- **Query**: Natural language search (e.g., "health benefits of coffee")
+- **Algorithm**: Semantic (Dense) for pure vector search, or BM25 Hybrid (default) combining vectors + keywords
+- **Fusion** (Hybrid only): RRF (Reciprocal Rank Fusion) or DBSF (Distribution-Based Score Fusion)
+- **Advanced**: Filter by document type, adjust score threshold (0.0-1.0), set result limit (max 100)
+
+**3D Visualization**:
+
+The plot uses Principal Component Analysis (PCA) to reduce 768-dimensional embeddings to 3D. Documents are positioned by semantic similarity with the query point shown in red. Point size and opacity indicate relevance, and the Viridis color scale shows relative scores (yellow = highest match).
+
+**Critical Fix**: Vectors are L2-normalized before PCA to match Qdrant's cosine distance, ensuring query points position accurately near similar documents. Without normalization, magnitude differences cause misleading spatial separation.
+
+**Results List**:
+
+Each result shows document title (clickable link to Nextcloud), excerpt, raw score, relative percentage, and document type. Click "Show Chunk" to view the matched text segment with surrounding context (up to 500 characters before/after).
+
+## Configuration
+
+**Required**:
+```bash
+VECTOR_SYNC_ENABLED=true
+```
+
+**Optional** (for browser-accessible links):
+```bash
+NEXTCLOUD_PUBLIC_ISSUER_URL=https://your-public-nextcloud-url.com
+```
+
+**Admin Access**: Webhooks tab only visible to Nextcloud admins (verified via Provisioning API).
+
+## Use Cases
+
+**Testing Search Queries**: Preview results before they reach LLMs in RAG workflows. Compare semantic vs. hybrid algorithms, verify relevance scores, and validate that correct documents are retrieved. Use chunk context to see exactly which text segments match and why unexpected documents appear.
+
+**Monitoring Indexing**: Track real-time progress after creating or modifying documents. Check if the queue is backing up (high pending count) or confirm the system is idle after bulk imports. Verify documents become searchable immediately after indexing completes.
+
+**Algorithm Comparison**: Pure semantic search excels at conceptual queries and synonyms. BM25 hybrid combines semantic understanding with precise keyword matching for better accuracy on specific terms. Experiment with RRF vs. DBSF fusion for different score distributions.
+
+## Troubleshooting
+
+**Vector Sync Tab Not Visible**: Set `VECTOR_SYNC_ENABLED=true` and restart the server.
+
+**No Search Results**: Check Vector Sync Status to confirm documents are indexed (not just pending). Try broader queries or lower the score threshold in Advanced options. Initial indexing may take time depending on document volume.
+
+**Links to Nextcloud Apps Not Working**: Set `NEXTCLOUD_PUBLIC_ISSUER_URL` to your browser-accessible Nextcloud URL for correct link generation.
+
+## Related Documentation
+
+- [Configuration Guide](../configuration.md) - Environment variables and settings
+- [Authentication Modes](../authentication.md) - BasicAuth vs OAuth setup
+- [Installation Guide](../installation.md) - Getting started
+- [ADR-008: MCP Sampling for RAG](../ADR-008-mcp-sampling-for-rag.md) - Technical details on RAG workflows
@@ -24,6 +24,7 @@ from starlette.middleware.authentication import AuthenticationMiddleware
 from starlette.middleware.cors import CORSMiddleware
 from starlette.responses import JSONResponse, RedirectResponse
 from starlette.routing import Mount, Route
+from starlette.staticfiles import StaticFiles

 from nextcloud_mcp_server.auth import (
    InsufficientScopeError,
@@ -1491,7 +1492,7 @@ def get_app(transport: str = "sse", enabled_apps: list[str] | None = None):
    # Create a separate Starlette app for browser routes that need session auth
    # This prevents SessionAuthBackend from interfering with FastMCP's OAuth
    browser_routes = [
-        Route("/", user_info_html, methods=["GET"]),  # /app → webapp (HTML UI)
+        Route("/", user_info_html, methods=["GET"]),  # /app → user info with all tabs
        Route(
            "/revoke", revoke_session, methods=["POST"], name="revoke_session_endpoint"
        ),  # /app/revoke → revoke_session
@@ -1527,6 +1528,14 @@ def get_app(transport: str = "sse", enabled_apps: list[str] | None = None):
        ),
    ]

+    # Add static files mount if directory exists
+    static_dir = os.path.join(os.path.dirname(__file__), "auth", "static")
+    if os.path.isdir(static_dir):
+        browser_routes.append(
+            Mount("/static", StaticFiles(directory=static_dir), name="static")
+        )
+        logger.info(f"Mounted static files from {static_dir}")
+
    browser_app = Starlette(routes=browser_routes)
    browser_app.add_middleware(
        AuthenticationMiddleware,  # type: ignore[invalid-argument-type]
@@ -0,0 +1,192 @@
+.viz-layout {
+    display: flex;
+    flex-direction: column;
+    gap: 16px;
+    height: 100%;
+    min-height: 0;
+    overflow-y: auto;
+}
+.viz-card {
+    background: var(--color-main-background);
+    border-radius: 0;
+    padding: 16px;
+    box-shadow: none;
+}
+.viz-controls-card {
+    flex: 0 0 auto;
+    border-bottom: 1px solid var(--color-border);
+    padding-bottom: 16px;
+}
+.viz-controls-grid {
+    display: grid;
+    grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+    gap: 12px;
+    align-items: end;
+}
+@media (min-width: 768px) {
+    .viz-controls-grid {
+        grid-template-columns: 2fr 1.5fr 1.5fr auto auto;
+    }
+}
+.viz-control-group {
+    display: flex;
+    flex-direction: column;
+    gap: 4px;
+}
+.viz-control-group label {
+    font-weight: 500;
+    color: var(--color-main-text);
+    font-size: 13px;
+}
+.viz-control-group input[type="text"],
+.viz-control-group input[type="number"],
+.viz-control-group select {
+    width: 100%;
+    padding: 7px 10px;
+    border: 1px solid var(--color-border-dark);
+    border-radius: var(--border-radius);
+    font-size: 14px;
+    background: var(--color-main-background);
+    color: var(--color-main-text);
+}
+.viz-control-group input:focus,
+.viz-control-group select:focus {
+    outline: none;
+    border-color: var(--color-primary-element);
+}
+.viz-control-group input[type="range"] {
+    width: 100%;
+}
+.viz-control-group select[multiple] {
+    min-height: 100px;
+}
+.viz-weight-display {
+    display: inline-block;
+    min-width: 40px;
+    text-align: right;
+    color: #666;
+}
+.viz-btn {
+    background: var(--color-primary-element);
+    color: white;
+    border: none;
+    padding: 7px 16px;
+    border-radius: var(--border-radius);
+    cursor: pointer;
+    font-size: 14px;
+    font-weight: 500;
+    white-space: nowrap;
+}
+.viz-btn:hover {
+    background: #0052a3;
+}
+.viz-btn-secondary {
+    background: #6c757d;
+    color: white;
+    border: none;
+    padding: 7px 16px;
+    border-radius: var(--border-radius);
+    cursor: pointer;
+    font-size: 14px;
+    white-space: nowrap;
+}
+.viz-btn-secondary:hover {
+    background: #5a6268;
+}
+.viz-card-plot {
+    flex: 0 0 auto;
+    display: flex;
+    flex-direction: column;
+    min-height: 500px;
+    height: 600px;
+    /* Remove horizontal padding to extend to full viewport width */
+    padding-left: 0;
+    padding-right: 0;
+    margin-left: -16px;
+    margin-right: -16px;
+}
+#viz-plot-container {
+    width: 100%;
+    height: 100%;
+    position: relative;
+    overflow: visible;
+}
+#viz-plot {
+    width: 100%;
+    height: 100%;
+}
+.viz-loading {
+    text-align: center;
+    padding: 40px;
+    color: #666;
+}
+.viz-loading-overlay {
+    position: absolute;
+    inset: 0;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    background: white;
+    color: #666;
+}
+.viz-no-results {
+    text-align: center;
+    padding: 40px;
+    color: #666;
+    font-style: italic;
+}
+.viz-advanced-section {
+    margin-top: 12px;
+    padding: 12px;
+    background: var(--color-background-hover);
+    border-radius: var(--border-radius);
+    border: 1px solid var(--color-border);
+}
+.viz-info-box {
+    background: var(--color-primary-element-light);
+    border-left: 3px solid var(--color-primary-element);
+    padding: 10px 12px;
+    margin-bottom: 16px;
+    font-size: 13px;
+    color: var(--color-main-text);
+}
+.chunk-toggle-btn {
+    background: #6c757d;
+    color: white;
+    border: none;
+    padding: 4px 10px;
+    border-radius: 3px;
+    cursor: pointer;
+    font-size: 12px;
+    margin-top: 6px;
+}
+.chunk-toggle-btn:hover {
+    background: #5a6268;
+}
+.chunk-context {
+    background: var(--color-background-hover);
+    border: 1px solid var(--color-border);
+    border-radius: var(--border-radius);
+    padding: 12px;
+    margin-top: 8px;
+    font-family: 'SFMono-Regular', 'Consolas', 'Liberation Mono', 'Menlo', monospace;
+    font-size: 13px;
+    line-height: 1.6;
+    white-space: pre-wrap;
+    word-wrap: break-word;
+}
+.chunk-text {
+    color: var(--color-text-maxcontrast);
+}
+.chunk-matched {
+    background: #fff3cd;
+    border: 1px solid #ffc107;
+    padding: 2px 4px;
+    border-radius: var(--border-radius);
+    font-weight: 500;
+    color: var(--color-main-text);
+}
+.chunk-ellipsis {
+    color: var(--color-text-maxcontrast);
+    font-style: italic;
+}
@@ -0,0 +1,253 @@
+// Initialize vizApp for vector visualization
+function vizApp() {
+    return {
+        query: '',
+        algorithm: 'bm25_hybrid',
+        fusion: 'rrf',
+        showAdvanced: false,
+        showQueryPoint: true,
+        docTypes: [''],
+        limit: 50,
+        scoreThreshold: 0.0,
+        loading: false,
+        results: [],
+        coordinates: null,
+        queryCoords: null,
+        expandedChunks: {},
+        chunkLoading: {},
+
+        init() {
+            // Set up window resize listener to resize plot
+            window.addEventListener('resize', () => {
+                if (this.coordinates && this.results.length > 0) {
+                    Plotly.Plots.resize('viz-plot');
+                }
+            });
+        },
+
+        async executeSearch() {
+            this.loading = true;
+            this.results = [];
+
+            try {
+                const params = new URLSearchParams({
+                    query: this.query,
+                    algorithm: this.algorithm,
+                    limit: this.limit,
+                    score_threshold: this.scoreThreshold,
+                });
+
+                if (this.algorithm === 'bm25_hybrid') {
+                    params.append('fusion', this.fusion);
+                }
+
+                const selectedTypes = this.docTypes.filter(t => t !== '');
+                if (selectedTypes.length > 0) {
+                    params.append('doc_types', selectedTypes.join(','));
+                }
+
+                const response = await fetch(`/app/vector-viz/search?${params}`);
+                const data = await response.json();
+
+                if (data.success) {
+                    this.results = data.results;
+                    this.coordinates = data.coordinates_3d;
+                    this.queryCoords = data.query_coords;
+                    this.renderPlot(this.coordinates, this.queryCoords, this.results);
+                } else {
+                    alert('Search failed: ' + data.error);
+                }
+            } catch (error) {
+                alert('Error: ' + error.message);
+            } finally {
+                this.loading = false;
+            }
+        },
+
+        updatePlot() {
+            // Toggle query point visibility without recreating the plot
+            // This preserves camera position naturally since layout is untouched
+            if (this.coordinates && this.queryCoords && this.results.length > 0) {
+                const plotDiv = document.getElementById('viz-plot');
+
+                // If plot exists, just toggle the query trace visibility
+                if (plotDiv && plotDiv.data && plotDiv.data.length >= 2) {
+                    // Trace index 1 is the query point
+                    Plotly.restyle('viz-plot', { visible: this.showQueryPoint }, [1]);
+                } else {
+                    // Plot doesn't exist yet, render it
+                    this.renderPlot(this.coordinates, this.queryCoords, this.results);
+                }
+            }
+        },
+
+        renderPlot(coordinates, queryCoords, results) {
+            // Get container dimensions before creating layout
+            const container = document.getElementById('viz-plot-container');
+            const width = container.clientWidth;
+            const height = container.clientHeight;
+
+            const scores = results.map(r => r.score);
+
+            // Trace 1: Document results (always visible)
+            const documentTrace = {
+                x: coordinates.map(c => c[0]),
+                y: coordinates.map(c => c[1]),
+                z: coordinates.map(c => c[2]),
+                mode: 'markers',
+                type: 'scatter3d',
+                name: 'Documents',
+                visible: true,
+                customdata: results.map((r, i) => ({
+                    title: r.title,
+                    raw_score: r.original_score,
+                    relative_score: r.score,
+                    x: coordinates[i][0],
+                    y: coordinates[i][1],
+                    z: coordinates[i][2]
+                })),
+                hovertemplate:
+                    '<b>%{customdata.title}</b><br>' +
+                    'Raw Score: %{customdata.raw_score:.3f} (%{customdata.relative_score:.0%} relative)<br>' +
+                    '(x=%{customdata.x}, y=%{customdata.y}, z=%{customdata.z})' +
+                    '<extra></extra>',
+                marker: {
+                    size: results.map(r => 4 + (Math.pow(r.score, 2) * 10)),
+                    opacity: results.map(r => 0.3 + (r.score * 0.7)),
+                    color: scores,
+                    colorscale: 'Viridis',
+                    showscale: true,
+                    colorbar: {
+                        title: 'Relative Score',
+                        x: 1.02,
+                        xanchor: 'left',
+                        thickness: 20,
+                        len: 0.8
+                    },
+                    cmin: 0,
+                    cmax: 1
+                }
+            };
+
+            // Trace 2: Query point (visibility controlled by toggle)
+            const queryTrace = {
+                x: [queryCoords[0]],
+                y: [queryCoords[1]],
+                z: [queryCoords[2]],
+                mode: 'markers',
+                type: 'scatter3d',
+                name: 'Query',
+                visible: this.showQueryPoint,  // Initial visibility from state
+                hovertemplate:
+                    '<b>Search Query</b><br>' +
+                    `(x=${queryCoords[0]}, y=${queryCoords[1]}, z=${queryCoords[2]})` +
+                    '<extra></extra>',
+                marker: {
+                    size: 10,
+                    color: '#ef5350',  // Subdued red (Material Design Red 400)
+                    line: {
+                        color: '#c62828',  // Darker red border (Material Design Red 800)
+                        width: 1
+                    }
+                }
+            };
+
+            const layout = {
+                title: `Vector Space (PCA 3D) - ${results.length} results`,
+                width: width,   // Explicit width from container
+                height: height, // Explicit height from container
+                scene: {
+                    xaxis: { title: 'PC1' },
+                    yaxis: { title: 'PC2' },
+                    zaxis: { title: 'PC3' },
+                    camera: {
+                        eye: { x: 1.5, y: 1.5, z: 1.5 }
+                    },
+                    // Full width for 3D scene
+                    domain: {
+                        x: [0, 1],
+                        y: [0, 1]
+                    }
+                },
+                hovermode: 'closest',
+                autosize: true,  // Enable auto-sizing for window resizes
+                showlegend: false,  // Hide legend
+                margin: { l: 0, r: 100, t: 40, b: 0 }  // Right margin for colorbar
+            };
+
+            // Always render both traces - visibility is controlled by the visible property
+            const traces = [documentTrace, queryTrace];
+
+            // Enable responsive resizing
+            const config = {
+                responsive: true,
+                displayModeBar: true
+            };
+
+            // Use newPlot() with explicit dimensions - renders at correct size immediately
+            // Camera position will be preserved by subsequent Plotly.restyle() calls in updatePlot()
+            Plotly.newPlot('viz-plot', traces, layout, config);
+        },
+
+        getNextcloudUrl(result) {
+            // Use global NEXTCLOUD_BASE_URL if set, otherwise construct from window location
+            const baseUrl = window.NEXTCLOUD_BASE_URL || '';
+            switch (result.doc_type) {
+                case 'note':
+                    return `${baseUrl}/apps/notes/note/${result.id}`;
+                case 'file':
+                    return `${baseUrl}/apps/files/?fileId=${result.id}`;
+                case 'calendar':
+                    return `${baseUrl}/apps/calendar`;
+                case 'contact':
+                    return `${baseUrl}/apps/contacts`;
+                case 'deck':
+                    return `${baseUrl}/apps/deck`;
+                default:
+                    return `${baseUrl}`;
+            }
+        },
+
+        hasChunkPosition(result) {
+            return result.chunk_start_offset != null && result.chunk_end_offset != null;
+        },
+
+        isChunkExpanded(resultKey) {
+            return this.expandedChunks[resultKey] !== undefined;
+        },
+
+        async toggleChunk(result) {
+            const resultKey = `${result.doc_type}_${result.id}`;
+
+            if (this.isChunkExpanded(resultKey)) {
+                delete this.expandedChunks[resultKey];
+                return;
+            }
+
+            this.chunkLoading[resultKey] = true;
+
+            try {
+                const params = new URLSearchParams({
+                    doc_type: result.doc_type,
+                    doc_id: result.id,
+                    start: result.chunk_start_offset,
+                    end: result.chunk_end_offset,
+                    context: 500
+                });
+
+                const response = await fetch(`/app/chunk-context?${params}`);
+                const data = await response.json();
+
+                if (data.success) {
+                    this.expandedChunks[resultKey] = data;
+                } else {
+                    alert('Failed to load chunk: ' + data.error);
+                }
+            } catch (error) {
+                alert('Error loading chunk: ' + error.message);
+            } finally {
+                delete this.chunkLoading[resultKey];
+            }
+        }
+    };
+}
@@ -0,0 +1,524 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta http-equiv="X-UA-Compatible" content="IE=edge">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1">
+    <meta name="apple-mobile-web-app-capable" content="yes">
+    <meta name="theme-color" content="#0082c9">
+    <title>{% block title %}Nextcloud MCP Server{% endblock %}</title>
+
+    <!-- Favicon -->
+    <link rel="icon" type="image/svg+xml" href="data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' width='32' height='32' viewBox='0 0 512 512'><rect width='512' height='512' rx='80' ry='80' fill='%230082C9'/><path d='M255.9 21.04c-11.8 0-22.2 4.08-28.6 10.01-5.6 4.98-8.6 11.41-8.6 18.11 0 5.55 2.2 11.01 5.9 15.48-16.4 4.97-30.1 13.64-39 24.53 22.1-7.67 45.7-11.86 70.3-11.86 24.6 0 48.3 4.19 70.3 11.86-8.9-10.89-22.6-19.56-39-24.53 3.9-4.47 5.9-9.93 5.9-15.48 0-6.7-3-13.13-8.5-18.11-6.4-5.93-16.9-10.01-28.7-10.01zm0 20.34c5.3 0 10.1 1.27 13.6 3.52 1.7 1.16 3.4 2.43 3.4 4.27 0 1.76-1.7 3.03-3.4 4.19-3.5 2.33-8.3 3.61-13.6 3.61-5.3 0-10.1-1.28-13.6-3.61-1.6-1.16-3.3-2.43-3.3-4.19 0-1.84 1.7-3.11 3.3-4.27 3.5-2.25 8.3-3.52 13.6-3.52zm.1 48.1c-110.8 0-200.72 90.02-200.72 200.82S145.2 491 256 491s200.7-89.9 200.7-200.7c0-110.8-89.9-200.82-200.7-200.82zm0 32.62c92.9 0 168.2 75.3 168.2 168.2 0 92.8-75.3 168.2-168.2 168.2-92.9 0-168.26-75.4-168.26-168.2 0-92.9 75.36-168.2 168.26-168.2zm-8.2 6.3c-9.6.5-19 1.9-28.3 4.1l2.3 7.8c8.4-2 17.1-3.3 26-3.8v-8.1zm16.2 0v8.1c9 .5 17.7 1.8 26 3.8l2.2-7.8c-9.1-2.2-18.6-3.6-28.2-4.1zm-60 8.5c-9 3.2-17.6 7-25.8 11.6l4.1 7.1c7.7-4.3 15.6-7.9 23.9-10.8l-2.2-7.9zm103.7 0-2 7.9c8.4 2.9 16.2 6.5 23.8 10.8l4.2-7.1c-8.2-4.6-16.9-8.4-26-11.6zm-143.3 20.3c-7.5 5.4-14.6 11.4-21.1 17.9l5.8 5.8c5.9-6.1 12.5-11.7 19.5-16.6l-4.2-7.1zm182.9 0-4 7.1c6.9 4.9 13.5 10.5 19.5 16.6l5.7-5.8c-6.5-6.5-13.7-12.5-21.2-17.9zm-91.4 11.5c-37 0-67.4 28.6-70.3 64.9l15.9 4.7c.7-29.6 24.7-53.4 54.4-53.4 30.1 0 54.4 24.4 54.4 54.3 0 15-6.2 28.7-16 38.5l.1.1c1.7 2.7 3 5.6 4.1 8.6.9 3 1.7 5.7 2.3 8.6v.4c33.8-16.7 57.2-51.5 57.2-91.7 0-3.8-.2-7.3-.6-10.9-3.2-3.3-6.3-6.4-9.8-9.5 1.5 6.5 2.3 13.4 2.3 20.4 0 28.7-13 54.7-33.5 71.8 6.3-10.6 10.1-23 10.1-36.3 0-38.9-31.7-70.5-70.6-70.5zm-91.8 14.6c-3.3 3.1-6.5 6.2-9.7 9.5-.3 3.6-.5 7.1-.5 10.9 0 7.3.7 14.2 2.1 20.9l9.1 2.7c-2.1-7.5-3.1-15.4-3.1-23.6 0-7 .7-13.9 2.1-20.4zm-31.6 4c-5.8 7.1-10.9 14.6-15.4 22.6l7.1 4c4.1-7.4 8.8-14.3 14-20.8l-5.7-5.8zm246.8 0-5.7 5.8c5.3 6.5 10 13.4 13.9 20.8l7.1-4c-4.4-8-9.5-15.5-15.3-22.6zm-269.2 37.1c-2.5 5.7-4.6 11.4-6.4 17.6l.1-.3c3.4-5 7.9-9.3 12.9-12.5l.3-.6-6.9-4.2zm291.8 0-7.2 4.2c3.2 7.3 5.7 15.1 7.6 23.1l7.9-2.1c-2.1-8.8-4.9-17.3-8.3-25.2zm-261.2 11.5c-13.4.1-25.7 9-29.7 22.5l114.8 34.2c-4.9 16.7 4.6 34.2 21.2 39.2L361.7 366c16.6 5 34.1-4.4 39.1-21l-114.6-34.4c4.9-16.5-4.7-34.1-21.3-39.1 0 0-72.4-21.5-114.8-34.3-3.1-.9-6.3-1.4-9.4-1.3zm-42.09 29.7c-.9 6.9-1.4 14-1.4 21.3 0 1.3.1 2.9.1 4.2h8.09v-4.2c0-6.5.4-12.9 1.2-19.2l-7.99-2.1zm314.59 0-7.9 2.1c.7 6.3 1.3 12.7 1.3 19.2 0 1.3 0 2.9-.2 4.2h8.2v-4.2c0-7.3-.5-14.4-1.4-21.3zm-157.3 24.7c6.3 0 11.5 5 11.5 11.3 0 6.4-5.2 11.6-11.5 11.6s-11.5-5.2-11.5-11.6c0-6.3 5.2-11.3 11.5-11.3zM98.51 307.4c1 8.2 2.89 16.4 5.09 24.3l7.9-2.1c-2.1-7.2-3.8-14.6-4.8-22.2h-8.19zm306.69 0c-1.1 7.6-2.7 15-4.8 22.2l7.8 2.1c2.2-7.9 4.1-16.1 5.2-24.3h-8.2zm-191.3 10.9c-19 13.3-31.4 35.3-31.4 60.1 0 10.4 2.3 20.4 6.2 29.7 8.8 4.9 17.9 8.8 27.6 11.7-10.8-10.7-17.5-25.2-17.5-41.4 0-19 9.3-36 23.7-46.3-3.8-4.1-6.7-8.7-8.6-13.8zM116.8 345l-7.9 2c3.1 7.6 6.8 14.7 11 21.6l6.9-4.2c-3.8-6.2-7-12.8-10-19.4zm194.8 20.5c.9 4.1 1.4 8.5 1.4 12.9 0 16.2-6.7 30.7-17.4 41.4 9.6-2.9 18.8-6.8 27.5-11.7 4-9.3 6.2-19.3 6.2-29.7 0-2.7-.2-5.2-.4-7.7l-17.3-5.2zM136 377.9l-7.1 4.1c4.7 6.2 9.7 12.1 15.3 17.3l5.7-5.5c-5.1-5-9.7-10.3-13.9-15.9zm243.9 2.3-.2.1c-2.1.3-4 .6-6.2.7h-.1c-3.6 4.5-7.3 8.8-11.5 12.8l5.8 5.5c5.5-5.2 10.5-11.1 15.2-17.3l-3-1.8zm-217.8 24-5.9 5.9c6 4.8 12.2 9.7 18.8 13.6l3.8-7.8c-5.7-2.9-11.4-6.8-16.7-11.7zm187.7 0c-5.4 4.9-11.1 8.8-16.8 11.7l3.9 7.8c6.5-3.9 12.8-8.8 18.7-13.6l-5.8-5.9zm-156.4 19.5-4.1 6.8c6.6 4 13.7 5.8 20.7 8.8l2.2-7.9c-6.5-1.9-12.7-4.8-18.8-7.7zm125.2 0c-6.2 2.9-12.5 5.8-19.1 7.7l2.3 7.9c7.2-3 14-4.8 20.7-8.8l-3.9-6.8zm-90.7 11.7-2 7.8c7.1 1 14.5 1.9 21.9 1.9v-7.7c-6.8 0-13.5-1.1-19.9-2zm55.9 0c-6.3.9-13 2-19.8 2v7.7c7.5 0 14.8-.9 22.1-1.9l-2.3-7.8z' fill='%23fff'/></svg>">
+
+    <!-- Open Sans font -->
+    <style>
+        @font-face {
+            font-family: 'Open Sans';
+            font-style: normal;
+            font-weight: normal;
+            src: local('Open Sans'), local('OpenSans');
+        }
+        @font-face {
+            font-family: 'Open Sans';
+            font-style: normal;
+            font-weight: bold;
+            src: local('Open Sans Semibold'), local('OpenSans-Semibold');
+        }
+    </style>
+
+    {% block extra_head %}{% endblock %}
+
+    <style>
+        /* Nextcloud App Design System */
+
+        /* CSS Variables */
+        :root {
+            /* Primary Colors */
+            --color-primary: #00679e;
+            --color-primary-element: #00679e;
+            --color-primary-light: #e5eff5;
+            --color-primary-element-light: #e5eff5;
+
+            /* Background Colors */
+            --color-main-background: #ffffff;
+            --color-background-dark: #ededed;
+            --color-background-hover: #f5f5f5;
+
+            /* Text Colors */
+            --color-main-text: #222222;
+            --color-text-maxcontrast: #6b6b6b;
+            --color-text-light: #767676;
+
+            /* Border Colors */
+            --color-border: #ededed;
+            --color-border-dark: #dbdbdb;
+
+            /* Borders & Radius */
+            --border-radius: 3px;
+            --border-radius-large: 10px;
+            --border-radius-pill: 100px;
+
+            /* Spacing */
+            --default-grid-baseline: 4px;
+            --default-clickable-area: 44px;
+        }
+
+        /* SVG Icon Styles */
+        .nav-icon {
+            width: 20px;
+            height: 20px;
+            display: inline-block;
+            fill: var(--color-main-text);
+            opacity: 0.7;
+        }
+
+        .app-navigation-entry.active .nav-icon {
+            fill: var(--color-primary-element);
+            opacity: 1;
+        }
+
+        /* General */
+        * {
+            box-sizing: border-box;
+        }
+
+        body {
+            font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
+            color: var(--color-main-text);
+            background: var(--color-main-background);
+            margin: 0;
+            padding: 0;
+        }
+
+        h1, h2, h3 {
+            font-weight: 300;
+            line-height: 1.2;
+        }
+
+        h1 {
+            font-size: 32px;
+            margin: 0 0 20px 0;
+            color: var(--color-main-text);
+        }
+
+        h2 {
+            font-size: 20px;
+            margin: 20px 0 12px 0;
+            color: var(--color-main-text);
+            border-bottom: 1px solid var(--color-border);
+            padding-bottom: 8px;
+        }
+
+        h3 {
+            font-size: 16px;
+            margin: 16px 0 8px 0;
+            color: var(--color-main-text);
+            font-weight: 500;
+        }
+
+        img {
+            max-width: 100%;
+        }
+
+        /* App Header (simplified, no full menu) */
+        .app-header {
+            height: 50px;
+            background: var(--color-primary-element);
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+            position: sticky;
+            top: 0;
+            z-index: 100;
+            display: flex;
+            align-items: center;
+            padding: 0 20px;
+        }
+
+        .app-header__brand {
+            color: white;
+            font-size: 18px;
+            font-weight: 600;
+            text-decoration: none;
+            display: flex;
+            align-items: center;
+            gap: 12px;
+        }
+
+        .app-header__brand:hover {
+            opacity: 0.9;
+        }
+
+        .app-header__logo {
+            height: 32px;
+            width: 32px;
+            fill: white;
+        }
+
+        /* App Layout */
+        .app-content-wrapper {
+            display: flex;
+            height: calc(100vh - 50px);
+            overflow: hidden;
+        }
+
+        /* Side Navigation */
+        #app-navigation {
+            width: 250px;
+            background: var(--color-main-background);
+            border-right: 1px solid var(--color-border);
+            display: flex;
+            flex-direction: column;
+            flex-shrink: 0;
+            transition: margin-left 0.3s ease;
+        }
+
+        #app-navigation.app-navigation--closed {
+            margin-left: -250px;
+        }
+
+        .app-navigation__content {
+            flex: 1;
+            overflow-y: auto;
+            padding: 8px;
+            display: flex;
+            flex-direction: column;
+        }
+
+        .app-navigation-list {
+            list-style: none;
+            padding: 0;
+            margin: 0;
+            flex: 1;
+        }
+
+        .app-navigation-entry {
+            position: relative;
+            margin-bottom: 2px;
+        }
+
+        .app-navigation-entry__wrapper {
+            display: flex;
+            align-items: center;
+            position: relative;
+        }
+
+        .app-navigation-entry-link {
+            display: flex;
+            align-items: center;
+            padding: 0 8px;
+            min-height: var(--default-clickable-area);
+            border-radius: var(--border-radius);
+            transition: background-color 100ms ease-in-out;
+            text-decoration: none;
+            color: var(--color-main-text);
+            flex: 1;
+            font-size: 14px;
+        }
+
+        .app-navigation-entry-link:hover {
+            background-color: var(--color-background-hover);
+        }
+
+        .app-navigation-entry.active .app-navigation-entry-link {
+            background-color: var(--color-primary-element-light);
+            font-weight: 500;
+        }
+
+        .app-navigation-entry-icon {
+            width: var(--default-clickable-area);
+            height: var(--default-clickable-area);
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            margin-right: 0;
+        }
+
+        .app-navigation-entry__name {
+            flex: 1;
+            white-space: nowrap;
+            overflow: hidden;
+            text-overflow: ellipsis;
+        }
+
+        .app-navigation-entry__counter {
+            margin-left: auto;
+            padding: 2px 6px;
+            border-radius: var(--border-radius-pill);
+            background-color: var(--color-background-dark);
+            font-size: 11px;
+            color: var(--color-text-maxcontrast);
+            min-width: 20px;
+            text-align: center;
+        }
+
+        .app-navigation__settings {
+            list-style: none;
+            padding: 8px 0 0 0;
+            margin: 8px 0 0 0;
+            border-top: 1px solid var(--color-border);
+            flex-shrink: 0;
+        }
+
+        .app-navigation-toggle {
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            position: fixed;
+            top: 60px;
+            left: 10px;
+            z-index: 110;
+            background: var(--color-main-background);
+            border: 1px solid var(--color-border);
+            border-radius: var(--border-radius);
+            padding: 8px 12px;
+            cursor: pointer;
+            box-shadow: 0 0 5px rgba(0,0,0,0.1);
+            transition: left 0.3s ease;
+        }
+
+        .app-navigation-toggle:hover {
+            background: var(--color-background-hover);
+        }
+
+        #app-navigation:not(.app-navigation--closed) ~ * .app-navigation-toggle {
+            left: 260px;
+        }
+
+        /* Main Content Area */
+        #app-content {
+            flex: 1;
+            overflow-y: auto;
+            background: var(--color-main-background);
+        }
+
+        .page-content {
+            max-width: 1000px;
+            margin: 0 auto;
+            padding: 24px;
+        }
+
+        .content-section {
+            background: var(--color-main-background);
+            border-radius: 0;
+            padding: 0;
+            box-shadow: none;
+        }
+
+        .content-section h1 {
+            font-size: 24px;
+            font-weight: 600;
+            margin-bottom: 24px;
+        }
+
+        .content-section h2 {
+            font-size: 18px;
+            font-weight: 500;
+            margin: 24px 0 12px 0;
+            border-bottom: none;
+            padding-bottom: 0;
+        }
+
+        .content-section h3 {
+            font-size: 16px;
+            font-weight: 500;
+        }
+
+        /* Responsive */
+        @media (max-width: 768px) {
+            #app-navigation {
+                position: fixed;
+                height: calc(100vh - 50px);
+                z-index: 105;
+                box-shadow: 2px 0 8px rgba(0,0,0,0.1);
+            }
+
+            .page-content {
+                padding: 16px;
+            }
+        }
+
+        /* Footer */
+        footer.page-footer {
+            background-color: #0F0833;
+            color: #ffffff;
+            padding: 40px 0;
+            margin-top: 60px;
+        }
+
+        footer.page-footer .bootstrap-container {
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 0 20px;
+        }
+
+        footer.page-footer h1 {
+            font-size: 15px;
+            font-weight: bold;
+            line-height: 1.8;
+            color: #ffffff;
+            margin-top: 20px;
+        }
+
+        footer.page-footer ul {
+            list-style-type: none;
+            padding-left: 0;
+        }
+
+        footer.page-footer li {
+            font-size: 13px;
+            line-height: 1.8;
+            color: #ffffff;
+            margin-top: 0;
+        }
+
+        footer.page-footer li a {
+            color: #ffffff;
+            text-decoration: none;
+            display: block;
+            padding: 4px 0;
+        }
+
+        footer.page-footer li a:hover {
+            text-decoration: underline;
+        }
+
+        footer.page-footer p {
+            font-size: 15px;
+            line-height: 1.8;
+            color: #ffffff;
+        }
+
+        footer.page-footer p.copyright {
+            color: rgba(255, 255, 255, 0.5);
+            font-size: 13px;
+            text-align: center;
+            margin-top: 30px;
+        }
+
+        /* Buttons */
+        .btn {
+            border-radius: 50px;
+            padding: 10px 20px;
+            text-decoration: none;
+            display: inline-block;
+            cursor: pointer;
+            border: none;
+            font-size: 14px;
+            transition: all 0.3s;
+        }
+
+        .btn-primary {
+            background: #0082C9;
+            border: 1px solid #0062C9;
+            color: #fff;
+        }
+
+        .btn-primary:hover {
+            background: #006ba3;
+        }
+
+        /* Tables */
+        table {
+            width: 100%;
+            border-collapse: collapse;
+            margin: 20px 0;
+        }
+
+        td {
+            padding: 12px 8px;
+            border-bottom: 1px solid var(--color-border);
+            font-size: 14px;
+        }
+
+        td:first-child {
+            width: 180px;
+            color: var(--color-text-maxcontrast);
+            font-weight: 500;
+        }
+
+        code {
+            background-color: var(--color-background-dark);
+            padding: 2px 6px;
+            border-radius: var(--border-radius);
+            font-family: 'SFMono-Regular', 'Consolas', 'Liberation Mono', 'Menlo', monospace;
+            font-size: 90%;
+            color: var(--color-main-text);
+        }
+
+        /* Badges */
+        .badge {
+            display: inline-block;
+            padding: 3px 8px;
+            border-radius: 12px;
+            font-size: 12px;
+            font-weight: bold;
+            text-transform: uppercase;
+        }
+
+        .badge-oauth {
+            background-color: #4caf50;
+            color: white;
+        }
+
+        .badge-basic {
+            background-color: #2196f3;
+            color: white;
+        }
+
+        /* Messages */
+        .warning {
+            background-color: #fff3cd;
+            border-left: 4px solid #ffc107;
+            padding: 15px;
+            margin: 15px 0;
+            color: #856404;
+        }
+
+        .info-message {
+            background-color: #e3f2fd;
+            border-left: 4px solid #2196f3;
+            padding: 15px;
+            margin: 15px 0;
+            color: #1565c0;
+        }
+
+        .error {
+            background-color: #ffebee;
+            border-left: 4px solid #d32f2f;
+            padding: 15px;
+            margin: 15px 0;
+            color: #c62828;
+        }
+
+        .success {
+            background-color: #e8f5e9;
+            border: 2px solid #4caf50;
+            padding: 30px;
+            border-radius: 8px;
+            text-align: center;
+        }
+
+        .success h1 {
+            color: #4caf50;
+        }
+
+        {% block extra_styles %}{% endblock %}
+    </style>
+</head>
+<body>
+    <!-- App Header -->
+    <header class="app-header">
+        <a href="/app" class="app-header__brand">
+            <svg class="app-header__logo" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512">
+                <path d="M255.9 21.04c-11.8 0-22.2 4.08-28.6 10.01-5.6 4.98-8.6 11.41-8.6 18.11 0 5.55 2.2 11.01 5.9 15.48-16.4 4.97-30.1 13.64-39 24.53 22.1-7.67 45.7-11.86 70.3-11.86 24.6 0 48.3 4.19 70.3 11.86-8.9-10.89-22.6-19.56-39-24.53 3.9-4.47 5.9-9.93 5.9-15.48 0-6.7-3-13.13-8.5-18.11-6.4-5.93-16.9-10.01-28.7-10.01zm0 20.34c5.3 0 10.1 1.27 13.6 3.52 1.7 1.16 3.4 2.43 3.4 4.27 0 1.76-1.7 3.03-3.4 4.19-3.5 2.33-8.3 3.61-13.6 3.61-5.3 0-10.1-1.28-13.6-3.61-1.6-1.16-3.3-2.43-3.3-4.19 0-1.84 1.7-3.11 3.3-4.27 3.5-2.25 8.3-3.52 13.6-3.52zm.1 48.1c-110.8 0-200.72 90.02-200.72 200.82S145.2 491 256 491s200.7-89.9 200.7-200.7c0-110.8-89.9-200.82-200.7-200.82zm0 32.62c92.9 0 168.2 75.3 168.2 168.2 0 92.8-75.3 168.2-168.2 168.2-92.9 0-168.26-75.4-168.26-168.2 0-92.9 75.36-168.2 168.26-168.2zm-8.2 6.3c-9.6.5-19 1.9-28.3 4.1l2.3 7.8c8.4-2 17.1-3.3 26-3.8v-8.1zm16.2 0v8.1c9 .5 17.7 1.8 26 3.8l2.2-7.8c-9.1-2.2-18.6-3.6-28.2-4.1zm-60 8.5c-9 3.2-17.6 7-25.8 11.6l4.1 7.1c7.7-4.3 15.6-7.9 23.9-10.8l-2.2-7.9zm103.7 0-2 7.9c8.4 2.9 16.2 6.5 23.8 10.8l4.2-7.1c-8.2-4.6-16.9-8.4-26-11.6zm-143.3 20.3c-7.5 5.4-14.6 11.4-21.1 17.9l5.8 5.8c5.9-6.1 12.5-11.7 19.5-16.6l-4.2-7.1zm182.9 0-4 7.1c6.9 4.9 13.5 10.5 19.5 16.6l5.7-5.8c-6.5-6.5-13.7-12.5-21.2-17.9zm-91.4 11.5c-37 0-67.4 28.6-70.3 64.9l15.9 4.7c.7-29.6 24.7-53.4 54.4-53.4 30.1 0 54.4 24.4 54.4 54.3 0 15-6.2 28.7-16 38.5l.1.1c1.7 2.7 3 5.6 4.1 8.6.9 3 1.7 5.7 2.3 8.6v.4c33.8-16.7 57.2-51.5 57.2-91.7 0-3.8-.2-7.3-.6-10.9-3.2-3.3-6.3-6.4-9.8-9.5 1.5 6.5 2.3 13.4 2.3 20.4 0 28.7-13 54.7-33.5 71.8 6.3-10.6 10.1-23 10.1-36.3 0-38.9-31.7-70.5-70.6-70.5zm-91.8 14.6c-3.3 3.1-6.5 6.2-9.7 9.5-.3 3.6-.5 7.1-.5 10.9 0 7.3.7 14.2 2.1 20.9l9.1 2.7c-2.1-7.5-3.1-15.4-3.1-23.6 0-7 .7-13.9 2.1-20.4zm-31.6 4c-5.8 7.1-10.9 14.6-15.4 22.6l7.1 4c4.1-7.4 8.8-14.3 14-20.8l-5.7-5.8zm246.8 0-5.7 5.8c5.3 6.5 10 13.4 13.9 20.8l7.1-4c-4.4-8-9.5-15.5-15.3-22.6zm-269.2 37.1c-2.5 5.7-4.6 11.4-6.4 17.6l.1-.3c3.4-5 7.9-9.3 12.9-12.5l.3-.6-6.9-4.2zm291.8 0-7.2 4.2c3.2 7.3 5.7 15.1 7.6 23.1l7.9-2.1c-2.1-8.8-4.9-17.3-8.3-25.2zm-261.2 11.5c-13.4.1-25.7 9-29.7 22.5l114.8 34.2c-4.9 16.7 4.6 34.2 21.2 39.2L361.7 366c16.6 5 34.1-4.4 39.1-21l-114.6-34.4c4.9-16.5-4.7-34.1-21.3-39.1 0 0-72.4-21.5-114.8-34.3-3.1-.9-6.3-1.4-9.4-1.3zm-42.09 29.7c-.9 6.9-1.4 14-1.4 21.3 0 1.3.1 2.9.1 4.2h8.09v-4.2c0-6.5.4-12.9 1.2-19.2l-7.99-2.1zm314.59 0-7.9 2.1c.7 6.3 1.3 12.7 1.3 19.2 0 1.3 0 2.9-.2 4.2h8.2v-4.2c0-7.3-.5-14.4-1.4-21.3zm-157.3 24.7c6.3 0 11.5 5 11.5 11.3 0 6.4-5.2 11.6-11.5 11.6s-11.5-5.2-11.5-11.6c0-6.3 5.2-11.3 11.5-11.3zM98.51 307.4c1 8.2 2.89 16.4 5.09 24.3l7.9-2.1c-2.1-7.2-3.8-14.6-4.8-22.2h-8.19zm306.69 0c-1.1 7.6-2.7 15-4.8 22.2l7.8 2.1c2.2-7.9 4.1-16.1 5.2-24.3h-8.2zm-191.3 10.9c-19 13.3-31.4 35.3-31.4 60.1 0 10.4 2.3 20.4 6.2 29.7 8.8 4.9 17.9 8.8 27.6 11.7-10.8-10.7-17.5-25.2-17.5-41.4 0-19 9.3-36 23.7-46.3-3.8-4.1-6.7-8.7-8.6-13.8zM116.8 345l-7.9 2c3.1 7.6 6.8 14.7 11 21.6l6.9-4.2c-3.8-6.2-7-12.8-10-19.4zm194.8 20.5c.9 4.1 1.4 8.5 1.4 12.9 0 16.2-6.7 30.7-17.4 41.4 9.6-2.9 18.8-6.8 27.5-11.7 4-9.3 6.2-19.3 6.2-29.7 0-2.7-.2-5.2-.4-7.7l-17.3-5.2zM136 377.9l-7.1 4.1c4.7 6.2 9.7 12.1 15.3 17.3l5.7-5.5c-5.1-5-9.7-10.3-13.9-15.9zm243.9 2.3-.2.1c-2.1.3-4 .6-6.2.7h-.1c-3.6 4.5-7.3 8.8-11.5 12.8l5.8 5.5c5.5-5.2 10.5-11.1 15.2-17.3l-3-1.8zm-217.8 24-5.9 5.9c6 4.8 12.2 9.7 18.8 13.6l3.8-7.8c-5.7-2.9-11.4-6.8-16.7-11.7zm187.7 0c-5.4 4.9-11.1 8.8-16.8 11.7l3.9 7.8c6.5-3.9 12.8-8.8 18.7-13.6l-5.8-5.9zm-156.4 19.5-4.1 6.8c6.6 4 13.7 5.8 20.7 8.8l2.2-7.9c-6.5-1.9-12.7-4.8-18.8-7.7zm125.2 0c-6.2 2.9-12.5 5.8-19.1 7.7l2.3 7.9c7.2-3 14-4.8 20.7-8.8l-3.9-6.8zm-90.7 11.7-2 7.8c7.1 1 14.5 1.9 21.9 1.9v-7.7c-6.8 0-13.5-1.1-19.9-2zm55.9 0c-6.3.9-13 2-19.8 2v7.7c7.5 0 14.8-.9 22.1-1.9l-2.3-7.8z" fill="#fff"/>
+            </svg>
+            <span>Nextcloud MCP Server</span>
+        </a>
+    </header>
+
+    <!-- App Content Wrapper (Sidebar + Main Content) -->
+    {% block content %}{% endblock %}
+
+    {% block scripts %}{% endblock %}
+</body>
+</html>
@@ -0,0 +1,19 @@
+{% extends "base.html" %}
+
+{% block title %}{{ error_title|default('Error') }} - Nextcloud MCP Server{% endblock %}
+
+{% block content %}
+<h1>{{ error_title|default('Error') }}</h1>
+
+<div class="error">
+    <strong>Error:</strong> {{ error_message }}
+</div>
+
+{% if login_url %}
+<p><a href="{{ login_url }}" class="btn btn-primary">Login again</a></p>
+{% endif %}
+
+{% if back_url %}
+<p><a href="{{ back_url }}" class="btn">Go Back</a></p>
+{% endif %}
+{% endblock %}
@@ -0,0 +1,21 @@
+{% extends "base.html" %}
+
+{% block title %}{{ success_title|default('Success') }} - Nextcloud MCP Server{% endblock %}
+
+{% block extra_head %}
+{% if redirect_url and redirect_delay %}
+<meta http-equiv="refresh" content="{{ redirect_delay }};url={{ redirect_url }}">
+{% endif %}
+{% endblock %}
+
+{% block content %}
+<div class="success">
+    <h1>{{ success_title|default('✓ Success') }}</h1>
+    {% for message in success_messages %}
+    <p>{{ message }}</p>
+    {% endfor %}
+    {% if redirect_url %}
+    <p>Redirecting...</p>
+    {% endif %}
+</div>
+{% endblock %}
@@ -0,0 +1,650 @@
+{% extends "base.html" %}
+
+{% block title %}Nextcloud MCP Server{% endblock %}
+
+{% block extra_head %}
+    <!-- htmx for dynamic loading -->
+    <script src="https://unpkg.com/htmx.org@1.9.10"></script>
+
+    <!-- Alpine.js for state management -->
+    <script defer src="https://cdn.jsdelivr.net/npm/alpinejs@3.x.x/dist/cdn.min.js"></script>
+
+    <!-- Plotly.js for vector visualization -->
+    <script src="https://cdn.plot.ly/plotly-3.3.0.min.js"></script>
+
+    <!-- Vector Viz static assets -->
+    <link rel="stylesheet" href="/app/static/vector-viz.css">
+{% endblock %}
+
+{% block extra_styles %}
+    /* Smooth htmx transitions */
+    .htmx-swapping {
+        opacity: 0;
+        transition: opacity 200ms ease-out;
+    }
+
+    .htmx-settling {
+        opacity: 1;
+        transition: opacity 200ms ease-in;
+    }
+
+    /* Logout button styling */
+    .logout-section {
+        margin-top: 20px;
+        padding-top: 20px;
+        border-top: 1px solid var(--color-border);
+    }
+
+    /* Welcome tab specific styles */
+    .hero-section {
+        background: linear-gradient(135deg, var(--color-primary-element) 0%, #0082c9 100%);
+        color: white;
+        padding: 60px 24px;
+        margin: -24px -24px 40px -24px;
+        border-radius: 0 0 var(--border-radius-large) var(--border-radius-large);
+        text-align: center;
+    }
+
+    .hero-section h1 {
+        color: white;
+        font-size: 36px;
+        margin: 0 0 16px 0;
+        font-weight: 600;
+    }
+
+    .hero-section p {
+        font-size: 18px;
+        opacity: 0.95;
+        max-width: 700px;
+        margin: 0 auto;
+        line-height: 1.6;
+    }
+
+    .feature-grid {
+        display: grid;
+        grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
+        gap: 24px;
+        margin: 32px 0;
+    }
+
+    .feature-card {
+        background: var(--color-main-background);
+        border: 2px solid var(--color-border);
+        border-radius: var(--border-radius-large);
+        padding: 24px;
+        transition: all 0.2s;
+        cursor: pointer;
+        text-decoration: none;
+        color: inherit;
+        display: block;
+    }
+
+    .feature-card:hover {
+        border-color: var(--color-primary-element);
+        box-shadow: 0 4px 12px rgba(0, 103, 158, 0.15);
+        transform: translateY(-2px);
+    }
+
+    .feature-card h3 {
+        color: var(--color-primary-element);
+        font-size: 20px;
+        margin: 12px 0 8px 0;
+        font-weight: 600;
+        display: flex;
+        align-items: center;
+        gap: 12px;
+    }
+
+    .feature-card p {
+        color: var(--color-text-maxcontrast);
+        font-size: 14px;
+        line-height: 1.6;
+        margin: 8px 0 0 0;
+    }
+
+    .feature-icon {
+        width: 48px;
+        height: 48px;
+        background: var(--color-primary-element-light);
+        border-radius: var(--border-radius);
+        display: flex;
+        align-items: center;
+        justify-content: center;
+        margin-bottom: 8px;
+    }
+
+    .feature-icon svg {
+        width: 28px;
+        height: 28px;
+        fill: var(--color-primary-element);
+    }
+
+    .info-section {
+        background: var(--color-background-hover);
+        border-radius: var(--border-radius-large);
+        padding: 32px;
+        margin: 32px 0;
+    }
+
+    .info-section h2 {
+        color: var(--color-main-text);
+        font-size: 24px;
+        margin: 0 0 16px 0;
+        border: none;
+        padding: 0;
+    }
+
+    .info-section p {
+        color: var(--color-text-maxcontrast);
+        line-height: 1.7;
+        margin: 12px 0;
+    }
+
+    .info-section ul {
+        margin: 12px 0;
+        padding-left: 24px;
+    }
+
+    .info-section li {
+        color: var(--color-text-maxcontrast);
+        line-height: 1.7;
+        margin: 8px 0;
+    }
+
+    .info-section code {
+        background: var(--color-main-background);
+        padding: 2px 8px;
+        border-radius: var(--border-radius);
+        font-size: 13px;
+    }
+
+    .auth-status {
+        background: var(--color-primary-element-light);
+        border-left: 4px solid var(--color-primary-element);
+        padding: 16px 20px;
+        margin: 24px 0;
+        border-radius: var(--border-radius);
+        display: flex;
+        align-items: center;
+        gap: 12px;
+    }
+
+    .auth-status svg {
+        width: 24px;
+        height: 24px;
+        fill: var(--color-primary-element);
+        flex-shrink: 0;
+    }
+
+    .auth-status-text {
+        flex: 1;
+    }
+
+    .auth-status-text strong {
+        display: block;
+        color: var(--color-main-text);
+        font-size: 14px;
+        margin-bottom: 4px;
+    }
+
+    .auth-status-text span {
+        color: var(--color-text-maxcontrast);
+        font-size: 13px;
+    }
+{% endblock %}
+
+{% block content %}
+<div class="app-content-wrapper" x-data="{ activeSection: 'welcome', navOpen: true }">
+    <!-- Side Navigation -->
+    <nav id="app-navigation" :class="{ 'app-navigation--closed': !navOpen }">
+        <div class="app-navigation__content">
+            <!-- Navigation List -->
+            <ul class="app-navigation-list">
+                <li class="app-navigation-entry" :class="{ 'active': activeSection === 'welcome' }">
+                    <div class="app-navigation-entry__wrapper">
+                        <a href="#"
+                           @click.prevent="activeSection = 'welcome'"
+                           class="app-navigation-entry-link">
+                            <span class="app-navigation-entry-icon">
+                                <svg class="nav-icon" viewBox="0 0 24 24">
+                                    <path d="M10,20V14H14V20H19V12H22L12,3L2,12H5V20H10Z" />
+                                </svg>
+                            </span>
+                            <span class="app-navigation-entry__name">Welcome</span>
+                        </a>
+                    </div>
+                </li>
+
+                <li class="app-navigation-entry" :class="{ 'active': activeSection === 'user-info' }">
+                    <div class="app-navigation-entry__wrapper">
+                        <a href="#"
+                           @click.prevent="activeSection = 'user-info'"
+                           class="app-navigation-entry-link">
+                            <span class="app-navigation-entry-icon">
+                                <svg class="nav-icon" viewBox="0 0 24 24">
+                                    <path d="M12,4A4,4 0 0,1 16,8A4,4 0 0,1 12,12A4,4 0 0,1 8,8A4,4 0 0,1 12,4M12,14C16.42,14 20,15.79 20,18V20H4V18C4,15.79 7.58,14 12,14Z" />
+                                </svg>
+                            </span>
+                            <span class="app-navigation-entry__name">User Info</span>
+                        </a>
+                    </div>
+                </li>
+
+                {% if show_vector_sync_tab %}
+                <li class="app-navigation-entry" :class="{ 'active': activeSection === 'vector-sync' }">
+                    <div class="app-navigation-entry__wrapper">
+                        <a href="#"
+                           @click.prevent="activeSection = 'vector-sync'"
+                           class="app-navigation-entry-link">
+                            <span class="app-navigation-entry-icon">
+                                <svg class="nav-icon" viewBox="0 0 24 24">
+                                    <path d="M12,18A6,6 0 0,1 6,12C6,11 6.25,10.03 6.7,9.2L5.24,7.74C4.46,8.97 4,10.43 4,12A8,8 0 0,0 12,20V23L16,19L12,15M12,4V1L8,5L12,9V6A6,6 0 0,1 18,12C18,13 17.75,13.97 17.3,14.8L18.76,16.26C19.54,15.03 20,13.57 20,12A8,8 0 0,0 12,4Z" />
+                                </svg>
+                            </span>
+                            <span class="app-navigation-entry__name">Vector Sync</span>
+                        </a>
+                    </div>
+                </li>
+
+                <li class="app-navigation-entry" :class="{ 'active': activeSection === 'vector-viz' }">
+                    <div class="app-navigation-entry__wrapper">
+                        <a href="#"
+                           @click.prevent="activeSection = 'vector-viz'"
+                           class="app-navigation-entry-link">
+                            <span class="app-navigation-entry-icon">
+                                <svg class="nav-icon" viewBox="0 0 24 24">
+                                    <path d="M22,21H2V3H4V19H6V10H10V19H12V6H16V19H18V14H22V21Z" />
+                                </svg>
+                            </span>
+                            <span class="app-navigation-entry__name">Vector Viz</span>
+                        </a>
+                    </div>
+                </li>
+                {% endif %}
+
+                {% if show_webhooks_tab %}
+                <li class="app-navigation-entry" :class="{ 'active': activeSection === 'webhooks' }">
+                    <div class="app-navigation-entry__wrapper">
+                        <a href="#"
+                           @click.prevent="activeSection = 'webhooks'"
+                           class="app-navigation-entry-link">
+                            <span class="app-navigation-entry-icon">
+                                <svg class="nav-icon" viewBox="0 0 24 24">
+                                    <path d="M10.59,13.41C11,13.8 11,14.44 10.59,14.83C10.2,15.22 9.56,15.22 9.17,14.83C7.22,12.88 7.22,9.71 9.17,7.76V7.76L12.71,4.22C14.66,2.27 17.83,2.27 19.78,4.22C21.73,6.17 21.73,9.34 19.78,11.29L18.29,12.78C18.3,11.96 18.17,11.14 17.89,10.36L18.36,9.88C19.54,8.71 19.54,6.81 18.36,5.64C17.19,4.46 15.29,4.46 14.12,5.64L10.59,9.17C9.41,10.34 9.41,12.24 10.59,13.41M13.41,9.17C13.8,8.78 14.44,8.78 14.83,9.17C16.78,11.12 16.78,14.29 14.83,16.24V16.24L11.29,19.78C9.34,21.73 6.17,21.73 4.22,19.78C2.27,17.83 2.27,14.66 4.22,12.71L5.71,11.22C5.7,12.04 5.83,12.86 6.11,13.65L5.64,14.12C4.46,15.29 4.46,17.19 5.64,18.36C6.81,19.54 8.71,19.54 9.88,18.36L13.41,14.83C14.59,13.66 14.59,11.76 13.41,10.59C13,10.2 13,9.56 13.41,9.17Z" />
+                                </svg>
+                            </span>
+                            <span class="app-navigation-entry__name">Webhooks</span>
+                        </a>
+                    </div>
+                </li>
+                {% endif %}
+            </ul>
+
+            <!-- Settings/Logout at bottom -->
+            {% if logout_url %}
+            <ul class="app-navigation__settings">
+                <li class="app-navigation-entry">
+                    <div class="app-navigation-entry__wrapper">
+                        <a href="{{ logout_url }}" class="app-navigation-entry-link">
+                            <span class="app-navigation-entry-icon">
+                                <svg class="nav-icon" viewBox="0 0 24 24">
+                                    <path d="M16,17V14H9V10H16V7L21,12L16,17M14,2A2,2 0 0,1 16,4V6H14V4H5V20H14V18H16V20A2,2 0 0,1 14,22H5A2,2 0 0,1 3,20V4A2,2 0 0,1 5,2H14Z" />
+                                </svg>
+                            </span>
+                            <span class="app-navigation-entry__name">Logout</span>
+                        </a>
+                    </div>
+                </li>
+            </ul>
+            {% endif %}
+        </div>
+
+        <!-- Toggle Button (mobile) -->
+        <button @click="navOpen = !navOpen"
+                class="app-navigation-toggle"
+                :aria-expanded="navOpen.toString()">
+            ☰
+        </button>
+    </nav>
+
+    <!-- Main Content Area -->
+    <main id="app-content">
+        <div class="page-content">
+            <!-- Welcome Section -->
+            <div x-show="activeSection === 'welcome'">
+                <!-- Hero Section -->
+                <div class="hero-section">
+                    <h1>Welcome to Nextcloud MCP Server</h1>
+                    <p>
+                        Interactive user interface for semantic search and document retrieval.
+                        Test queries, visualize results, and explore your Nextcloud content using RAG workflows.
+                    </p>
+                </div>
+
+                <!-- Authentication Status -->
+                <div class="auth-status">
+                    <svg viewBox="0 0 24 24">
+                        <path d="M12,4A4,4 0 0,1 16,8A4,4 0 0,1 12,12A4,4 0 0,1 8,8A4,4 0 0,1 12,4M12,14C16.42,14 20,15.79 20,18V20H4V18C4,15.79 7.58,14 12,14Z" />
+                    </svg>
+                    <div class="auth-status-text">
+                        <strong>Authenticated as: {{ username }}</strong>
+                        <span>Authentication mode: <code>{{ auth_mode }}</code></span>
+                    </div>
+                </div>
+
+                {% if vector_sync_enabled %}
+                <!-- Vector Sync Enabled Content -->
+                <div class="info-section">
+                    <h2>About Semantic Search</h2>
+                    <p>
+                        This interface provides access to <strong>semantic search</strong> capabilities powered by vector embeddings.
+                        Unlike traditional keyword search, semantic search understands the <em>meaning</em> of your queries and finds
+                        conceptually similar content across your Nextcloud apps.
+                    </p>
+                    <p>
+                        <strong>How it works:</strong>
+                    </p>
+                    <ul>
+                        <li>Documents from Notes, Calendar, Files, Contacts, and Deck are indexed into a vector database</li>
+                        <li>Each document chunk is converted to a 768-dimensional vector embedding that captures semantic meaning</li>
+                        <li>Queries are also converted to embeddings and matched against document vectors using similarity search</li>
+                        <li>Results can be retrieved using pure semantic search or hybrid BM25 search combining keywords and semantics</li>
+                    </ul>
+                </div>
+
+                <div class="info-section">
+                    <h2>RAG Workflow Integration</h2>
+                    <p>
+                        This UI allows you to <strong>test the same queries that Large Language Models (LLMs) would use</strong> in a
+                        Retrieval-Augmented Generation (RAG) workflow. When an AI assistant needs to answer questions about your data:
+                    </p>
+                    <ul>
+                        <li><strong>Step 1:</strong> The assistant converts your question into a search query</li>
+                        <li><strong>Step 2:</strong> The MCP server retrieves relevant document chunks using semantic search</li>
+                        <li><strong>Step 3:</strong> Retrieved context is passed to the LLM to generate an informed answer</li>
+                    </ul>
+
+                    <!-- RAG Workflow Diagram -->
+                    <div style="background: var(--color-main-background); border: 2px solid var(--color-primary-element); border-radius: var(--border-radius-large); padding: 24px; margin: 24px 0; overflow-x: auto;">
+                        <div style="text-align: center; font-weight: 600; margin-bottom: 20px; color: var(--color-primary-element); font-size: 16px;">
+                            MCP Sampling RAG Workflow
+                        </div>
+
+                        <!-- Four-component bidirectional flow -->
+                        <div style="max-width: 1000px; margin: 0 auto;">
+                            <div style="display: grid; grid-template-columns: 0.7fr auto 1fr auto 1fr auto 0.9fr; gap: 10px; align-items: center;">
+                                <!-- User -->
+                                <div style="background: var(--color-background-hover); border: 2px solid var(--color-border); border-radius: var(--border-radius-large); padding: 14px; text-align: center;">
+                                    <div style="font-size: 26px; margin-bottom: 5px;">👤</div>
+                                    <div style="font-weight: 600; color: var(--color-main-text); font-size: 12px;">User</div>
+                                    <div style="font-size: 9px; color: var(--color-text-maxcontrast); font-style: italic; margin-top: 5px; line-height: 1.2;">
+                                        "What are health<br>benefits of coffee?"
+                                    </div>
+                                </div>
+
+                                <!-- Arrow User <-> Client -->
+                                <div style="text-align: center;">
+                                    <div style="font-size: 20px; color: var(--color-text-maxcontrast);">↔</div>
+                                </div>
+
+                                <!-- MCP Client + LLM (combined) -->
+                                <div style="background: var(--color-primary-element-light); border: 2px solid var(--color-primary-element); border-radius: var(--border-radius-large); padding: 12px; text-align: center;">
+                                    <div style="font-weight: 600; color: var(--color-primary-element); font-size: 13px; margin-bottom: 8px;">MCP Client + LLM</div>
+
+                                    <div style="background: var(--color-main-background); border-radius: var(--border-radius); padding: 8px; margin-bottom: 6px;">
+                                        <div style="font-size: 9px; color: var(--color-text-maxcontrast);">(Claude Code)</div>
+                                    </div>
+
+                                    <div style="background: var(--color-main-background); border-radius: var(--border-radius); padding: 8px; border: 2px solid var(--color-primary-element);">
+                                        <div style="font-size: 16px; margin-bottom: 2px;">🧠</div>
+                                        <div style="font-weight: 600; color: var(--color-main-text); font-size: 10px;">Client's LLM</div>
+                                        <div style="font-size: 8px; color: var(--color-text-maxcontrast);">(Claude)</div>
+                                    </div>
+
+                                    <div style="margin-top: 8px; font-size: 8px; color: var(--color-text-maxcontrast); line-height: 1.2;">
+                                        <strong>Enables RAG:</strong><br>
+                                        Receives context,<br>
+                                        generates answer
+                                    </div>
+                                </div>
+
+                                <!-- Arrow Client <-> Server -->
+                                <div style="text-align: center;">
+                                    <div style="font-size: 20px; color: var(--color-primary-element);">↔</div>
+                                    <div style="font-size: 7px; color: var(--color-text-maxcontrast); margin-top: 2px; font-weight: 600; line-height: 1.1;">
+                                        Query +<br>
+                                        Sampling
+                                    </div>
+                                </div>
+
+                                <!-- MCP Server -->
+                                <div style="background: var(--color-primary-element-light); border: 2px solid var(--color-primary-element); border-radius: var(--border-radius-large); padding: 12px; text-align: center;">
+                                    <div style="font-weight: 600; color: var(--color-primary-element); font-size: 13px; margin-bottom: 8px;">MCP Server</div>
+
+                                    <div style="background: var(--color-main-background); border-radius: var(--border-radius); padding: 7px; margin-bottom: 5px;">
+                                        <div style="font-weight: 600; color: var(--color-main-text); font-size: 9px; margin-bottom: 2px;">1. Semantic Search</div>
+                                        <div style="font-size: 7px; color: var(--color-text-maxcontrast); line-height: 1.2;">
+                                            Vector embeddings<br>
+                                            BM25 Hybrid + RRF
+                                        </div>
+                                    </div>
+
+                                    <div style="background: var(--color-main-background); border-radius: var(--border-radius); padding: 7px; margin-bottom: 5px;">
+                                        <div style="font-weight: 600; color: var(--color-main-text); font-size: 9px; margin-bottom: 2px;">2. Retrieve Context</div>
+                                        <div style="font-size: 7px; color: var(--color-text-maxcontrast); line-height: 1.2;">
+                                            Top relevant docs<br>
+                                            with scores
+                                        </div>
+                                    </div>
+
+                                    <div style="background: var(--color-main-background); border-radius: var(--border-radius); padding: 7px; margin-bottom: 5px;">
+                                        <div style="font-weight: 600; color: var(--color-main-text); font-size: 9px; margin-bottom: 2px;">3. Format Response</div>
+                                        <div style="font-size: 7px; color: var(--color-text-maxcontrast); line-height: 1.2;">
+                                            Document chunks<br>
+                                            with citations
+                                        </div>
+                                    </div>
+
+                                    <div style="background: var(--color-main-background); border-radius: var(--border-radius); padding: 7px;">
+                                        <div style="font-weight: 600; color: var(--color-main-text); font-size: 9px; margin-bottom: 2px;">4. Send to LLM</div>
+                                        <div style="font-size: 7px; color: var(--color-text-maxcontrast); line-height: 1.2;">
+                                            Via MCP sampling<br>
+                                            for answer generation
+                                        </div>
+                                    </div>
+                                </div>
+
+                                <!-- Arrow Server <-> Nextcloud -->
+                                <div style="text-align: center;">
+                                    <div style="font-size: 20px; color: var(--color-primary-element);">↔</div>
+                                    <div style="font-size: 7px; color: var(--color-text-maxcontrast); margin-top: 2px; font-weight: 600; line-height: 1.1;">
+                                        Retrieve
+                                    </div>
+                                </div>
+
+                                <!-- Nextcloud -->
+                                <div style="background: var(--color-background-hover); border: 2px solid var(--color-border); border-radius: var(--border-radius-large); padding: 12px; text-align: center; position: relative;">
+                                    <img src="/app/static/nextcloud-logo.png" alt="Nextcloud" style="width: 40px; height: 40px; margin-bottom: 6px;" />
+                                    <div style="font-weight: 600; color: var(--color-main-text); font-size: 12px; margin-bottom: 4px;">Nextcloud</div>
+                                    <div style="font-size: 8px; color: var(--color-text-maxcontrast); line-height: 1.2;">
+                                        Notes, Calendar,<br>
+                                        Files, Contacts,<br>
+                                        Deck
+                                    </div>
+                                </div>
+                            </div>
+
+                            <!-- Explanation below diagram -->
+                            <div style="margin-top: 24px; padding: 16px; background: var(--color-background-hover); border-radius: var(--border-radius); border-left: 4px solid var(--color-primary-element);">
+                                <div style="font-size: 12px; color: var(--color-main-text); line-height: 1.6;">
+                                    <strong>How RAG works via MCP Sampling:</strong>
+                                </div>
+                                <ol style="margin: 8px 0 0 0; padding-left: 20px; font-size: 11px; color: var(--color-text-maxcontrast); line-height: 1.6;">
+                                    <li>User asks question through MCP Client</li>
+                                    <li>Client sends query to MCP Server</li>
+                                    <li>Server retrieves relevant document context from Nextcloud</li>
+                                    <li><strong>Server sends context back to Client's LLM</strong> (MCP Sampling)</li>
+                                    <li>Client's LLM generates answer with citations using retrieved context</li>
+                                    <li>Answer returned to user</li>
+                                </ol>
+                                <div style="margin-top: 8px; font-size: 10px; color: var(--color-text-maxcontrast); font-style: italic;">
+                                    The server has no LLM - it only retrieves context. The client's existing LLM is reused for answer generation.
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+
+                    <p style="margin-top: 16px;">
+                        <strong>Key Point:</strong> The MCP server retrieves context but doesn't generate answers itself.
+                        Through <strong>MCP sampling</strong>, it requests the client's LLM to generate responses, giving users
+                        full control over which model is used and ensuring all processing happens client-side.
+                    </p>
+
+                    <p>
+                        By using this interface, you can preview search results, understand relevance scores, and verify
+                        that the system retrieves the right information before it reaches the LLM.
+                    </p>
+                </div>
+
+                <!-- Feature Cards -->
+                <h2>Available Features</h2>
+                <div class="feature-grid">
+                    <a href="#" @click.prevent="activeSection = 'user-info'" class="feature-card">
+                        <div class="feature-icon">
+                            <svg viewBox="0 0 24 24">
+                                <path d="M12,4A4,4 0 0,1 16,8A4,4 0 0,1 12,12A4,4 0 0,1 8,8A4,4 0 0,1 12,4M12,14C16.42,14 20,15.79 20,18V20H4V18C4,15.79 7.58,14 12,14Z" />
+                            </svg>
+                        </div>
+                        <h3>User Information</h3>
+                        <p>
+                            View your authentication details, session information, and IdP profile.
+                            Manage background access permissions.
+                        </p>
+                    </a>
+
+                    <a href="#" @click.prevent="activeSection = 'vector-sync'" class="feature-card">
+                        <div class="feature-icon">
+                            <svg viewBox="0 0 24 24">
+                                <path d="M12,18A6,6 0 0,1 6,12C6,11 6.25,10.03 6.7,9.2L5.24,7.74C4.46,8.97 4,10.43 4,12A8,8 0 0,0 12,20V23L16,19L12,15M12,4V1L8,5L12,9V6A6,6 0 0,1 18,12C18,13 17.75,13.97 17.3,14.8L18.76,16.26C19.54,15.03 20,13.57 20,12A8,8 0 0,0 12,4Z" />
+                            </svg>
+                        </div>
+                        <h3>Vector Sync Status</h3>
+                        <p>
+                            Monitor real-time indexing progress with metrics for indexed documents, pending queue,
+                            and synchronization status.
+                        </p>
+                    </a>
+
+                    <a href="#" @click.prevent="activeSection = 'vector-viz'" class="feature-card">
+                        <div class="feature-icon">
+                            <svg viewBox="0 0 24 24">
+                                <path d="M22,21H2V3H4V19H6V10H10V19H12V6H16V19H18V14H22V21Z" />
+                            </svg>
+                        </div>
+                        <h3>Vector Visualization</h3>
+                        <p>
+                            Interactive search interface with 2D PCA visualization. Compare algorithms,
+                            view relevance scores, and explore matched document chunks.
+                        </p>
+                    </a>
+                </div>
+
+                {% else %}
+                <!-- Vector Sync Disabled Content -->
+                <div class="warning">
+                    <h3 style="margin-top: 0;">Vector Sync is Disabled</h3>
+                    <p>
+                        Semantic search and vector visualization features are currently disabled.
+                        To enable these features, set <code>VECTOR_SYNC_ENABLED=true</code> in your environment configuration.
+                    </p>
+                    <p style="margin-bottom: 0;">
+                        <strong>Learn more:</strong>
+                        <a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/configuration.md" target="_blank" style="color: inherit; text-decoration: underline;">
+                            Configuration Guide
+                        </a>
+                    </p>
+                </div>
+
+                <!-- Limited Feature Card -->
+                <h2>Available Features</h2>
+                <div class="feature-grid">
+                    <a href="#" @click.prevent="activeSection = 'user-info'" class="feature-card">
+                        <div class="feature-icon">
+                            <svg viewBox="0 0 24 24">
+                                <path d="M12,4A4,4 0 0,1 16,8A4,4 0 0,1 12,12A4,4 0 0,1 8,8A4,4 0 0,1 12,4M12,14C16.42,14 20,15.79 20,18V20H4V18C4,15.79 7.58,14 12,14Z" />
+                            </svg>
+                        </div>
+                        <h3>User Information</h3>
+                        <p>
+                            View your authentication details, session information, and IdP profile.
+                            Manage background access permissions.
+                        </p>
+                    </a>
+                </div>
+                {% endif %}
+
+                <!-- Documentation Section -->
+                <div class="info-section" style="margin-top: 40px;">
+                    <h2>Documentation</h2>
+                    <p>
+                        For detailed information about configuration, authentication modes, and advanced features,
+                        please refer to the project documentation:
+                    </p>
+                    <ul>
+                        <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/installation.md" target="_blank">Installation Guide</a></li>
+                        <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/configuration.md" target="_blank">Configuration Options</a></li>
+                        <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/authentication.md" target="_blank">Authentication Modes</a></li>
+                        {% if vector_sync_enabled %}
+                        <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/user-guide/vector-sync-ui.md" target="_blank">Vector Sync UI Guide</a></li>
+                        {% endif %}
+                    </ul>
+                </div>
+            </div>
+
+            <!-- User Info Section -->
+            <div x-show="activeSection === 'user-info'">
+                <div class="content-section">
+                    <h1>User Information</h1>
+                    {{ user_info_tab_html|safe }}
+                </div>
+            </div>
+
+            {% if show_vector_sync_tab %}
+            <!-- Vector Sync Section -->
+            <div x-show="activeSection === 'vector-sync'">
+                <div class="content-section">
+                    <h1>Vector Sync Status</h1>
+                    {{ vector_sync_tab_html|safe }}
+                </div>
+            </div>
+
+            <!-- Vector Viz Section -->
+            <div x-show="activeSection === 'vector-viz'">
+                <div class="content-section">
+                    <h1>Vector Visualization</h1>
+                    <div hx-get="/app/vector-viz" hx-trigger="load" hx-swap="outerHTML">
+                        <p style="color: #999;">Loading vector visualization...</p>
+                    </div>
+                </div>
+            </div>
+            {% endif %}
+
+            {% if show_webhooks_tab %}
+            <!-- Webhooks Section -->
+            <div x-show="activeSection === 'webhooks'">
+                <div class="content-section">
+                    <h1>Webhook Management</h1>
+                    {{ webhooks_tab_html|safe }}
+                </div>
+            </div>
+            {% endif %}
+        </div>
+    </main>
+</div>
+
+<script>
+    // Set global Nextcloud base URL for use in external JS
+    window.NEXTCLOUD_BASE_URL = '{{ nextcloud_host_for_links }}';
+</script>
+<script src="/app/static/vector-viz.js"></script>
+{% endblock %}
@@ -1,286 +1,111 @@
-<style>
-    .viz-card {
-        background: white;
-        border-radius: 8px;
-        padding: 20px;
-        margin-bottom: 20px;
-        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-    }
-    .viz-controls {
-        margin-bottom: 20px;
-    }
-    .viz-control-row {
-        display: grid;
-        grid-template-columns: 2fr 1fr auto;
-        gap: 12px;
-        margin-bottom: 12px;
-        align-items: end;
-    }
-    .viz-control-group {
-        margin-bottom: 15px;
-    }
-    .viz-control-group label {
-        display: block;
-        margin-bottom: 5px;
-        font-weight: 500;
-        color: #333;
-    }
-    .viz-control-group input[type="text"],
-    .viz-control-group input[type="number"],
-    .viz-control-group select {
-        width: 100%;
-        padding: 8px 12px;
-        border: 1px solid #ddd;
-        border-radius: 4px;
-        font-size: 14px;
-    }
-    .viz-control-group input[type="range"] {
-        width: 100%;
-    }
-    .viz-control-group select[multiple] {
-        min-height: 100px;
-    }
-    .viz-weight-display {
-        display: inline-block;
-        min-width: 40px;
-        text-align: right;
-        color: #666;
-    }
-    .viz-btn {
-        background: #0066cc;
-        color: white;
-        border: none;
-        padding: 10px 20px;
-        border-radius: 4px;
-        cursor: pointer;
-        font-size: 14px;
-        font-weight: 500;
-    }
-    .viz-btn:hover {
-        background: #0052a3;
-    }
-    .viz-btn-secondary {
-        background: #6c757d;
-        color: white;
-        border: none;
-        padding: 6px 12px;
-        border-radius: 4px;
-        cursor: pointer;
-        font-size: 13px;
-        margin-bottom: 12px;
-    }
-    .viz-btn-secondary:hover {
-        background: #5a6268;
-    }
-    #viz-plot-container {
-        width: 100%;
-        height: 600px;
-        position: relative;
-    }
-    #viz-plot {
-        width: 100%;
-        height: 100%;
-    }
-    .viz-loading {
-        text-align: center;
-        padding: 40px;
-        color: #666;
-    }
-    .viz-loading-overlay {
-        position: absolute;
-        inset: 0;
-        display: flex;
-        align-items: center;
-        justify-content: center;
-        background: white;
-        color: #666;
-    }
-    .viz-no-results {
-        text-align: center;
-        padding: 40px;
-        color: #666;
-        font-style: italic;
-    }
-    .viz-advanced-section {
-        margin-top: 16px;
-        padding: 16px;
-        background: #f8f9fa;
-        border-radius: 4px;
-        border: 1px solid #dee2e6;
-    }
-    .viz-advanced-grid {
-        display: grid;
-        grid-template-columns: 1fr 1fr;
-        gap: 20px;
-    }
-    .viz-info-box {
-        background: #e3f2fd;
-        border-left: 4px solid #2196f3;
-        padding: 12px;
-        margin-bottom: 20px;
-        font-size: 14px;
-    }
-    .chunk-toggle-btn {
-        background: #6c757d;
-        color: white;
-        border: none;
-        padding: 4px 10px;
-        border-radius: 3px;
-        cursor: pointer;
-        font-size: 12px;
-        margin-top: 6px;
-    }
-    .chunk-toggle-btn:hover {
-        background: #5a6268;
-    }
-    .chunk-context {
-        background: #f8f9fa;
-        border: 1px solid #dee2e6;
-        border-radius: 4px;
-        padding: 12px;
-        margin-top: 8px;
-        font-family: monospace;
-        font-size: 13px;
-        line-height: 1.6;
-        white-space: pre-wrap;
-        word-wrap: break-word;
-    }
-    .chunk-text {
-        color: #666;
-    }
-    .chunk-matched {
-        background: #fff3cd;
-        border: 1px solid #ffc107;
-        padding: 2px 4px;
-        border-radius: 2px;
-        font-weight: 500;
-        color: #333;
-    }
-    .chunk-ellipsis {
-        color: #999;
-        font-style: italic;
-    }
-</style>
-
 <div x-data="vizApp()">
-    <div class="viz-card">
-        <h2>Vector Visualization</h2>
-        <div class="viz-info-box">
-            Testing search algorithms on your indexed documents. User: <strong>{{ username }}</strong>
-        </div>
+    <div class="viz-layout">
+        <!-- Top: Search Controls -->
+        <div class="viz-card viz-controls-card">
+            <form @submit.prevent="executeSearch">
+                <div class="viz-controls-grid">
+                    <div class="viz-control-group">
+                        <label>Search Query</label>
+                        <input type="text" x-model="query" placeholder="Enter search query..." required />
+                    </div>

-        <form @submit.prevent="executeSearch">
-            <div class="viz-controls">
-                <!-- Main Controls -->
-                <div class="viz-control-group">
-                    <label>Search Query</label>
-                    <input type="text" x-model="query" placeholder="Enter search query..." required />
-                </div>
-
-                <div class="viz-control-row">
-                    <div class="viz-control-group" style="margin-bottom: 0;">
+                    <div class="viz-control-group">
                        <label>Algorithm</label>
                        <select x-model="algorithm">
-                            <option value="semantic">Semantic (Dense Vectors)</option>
-                            <option value="bm25_hybrid" selected>BM25 Hybrid (Dense + Sparse)</option>
+                            <option value="semantic">Semantic (Dense)</option>
+                            <option value="bm25_hybrid" selected>BM25 Hybrid</option>
                        </select>
                    </div>

-                    <div class="viz-control-group" style="margin-bottom: 0;">
-                        <label>Fusion Method</label>
+                    <div class="viz-control-group">
+                        <label>Fusion</label>
                        <select x-model="fusion" :disabled="algorithm !== 'bm25_hybrid'" :style="algorithm !== 'bm25_hybrid' ? 'opacity: 0.5; cursor: not-allowed;' : ''">
-                            <option value="rrf" selected>RRF (Reciprocal Rank Fusion)</option>
-                            <option value="dbsf">DBSF (Distribution-Based Score Fusion)</option>
+                            <option value="rrf" selected>RRF</option>
+                            <option value="dbsf">DBSF</option>
                        </select>
                    </div>

-                    <div style="display: flex; align-items: flex-end;">
-                        <button type="submit" class="viz-btn" style="width: 100%;">Search & Visualize</button>
+                    <div class="viz-control-group">
+                        <label>&nbsp;</label>
+                        <button type="submit" class="viz-btn">Search</button>
                    </div>

-                    <div style="display: flex; align-items: flex-end;">
-                        <button type="button" class="viz-btn-secondary" @click="showAdvanced = !showAdvanced" style="white-space: nowrap;">
-                            <span x-text="showAdvanced ? 'Hide Advanced' : 'Advanced'"></span>
+                    <div class="viz-control-group">
+                        <label>&nbsp;</label>
+                        <button type="button" class="viz-btn-secondary" @click="showAdvanced = !showAdvanced">
+                            <span x-text="showAdvanced ? 'Hide' : 'Advanced'"></span>
                        </button>
                    </div>
                </div>

                <!-- Advanced Options (Collapsible) -->
-                <div class="viz-advanced-section" x-show="showAdvanced" x-transition.opacity.duration.200ms>
-                    <h3 style="margin-top: 0; margin-bottom: 16px; font-size: 16px;">Advanced Options</h3>
-
-                    <div class="viz-advanced-grid">
+                <div x-show="showAdvanced" style="margin-top: 16px;">
+                    <div class="viz-controls-grid" style="grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));">
                        <div class="viz-control-group">
-                            <label style="display: block; margin-bottom: 8px;">Document Types</label>
-                            <div style="display: grid; grid-template-columns: 1fr; gap: 6px;">
+                            <label>Document Types</label>
+                            <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 8px; font-size: 13px;">
                                <label style="display: flex; align-items: center; cursor: pointer; font-weight: normal;">
-                                    <input type="checkbox" x-model="docTypes" value="" style="margin-right: 8px;">
-                                    <span>All Types</span>
+                                    <input type="checkbox" x-model="docTypes" value="" style="margin-right: 4px;">
+                                    <span>All</span>
                                </label>
                                <label style="display: flex; align-items: center; cursor: pointer; font-weight: normal;">
-                                    <input type="checkbox" x-model="docTypes" value="note" style="margin-right: 8px;">
+                                    <input type="checkbox" x-model="docTypes" value="note" style="margin-right: 4px;">
                                    <span>Notes</span>
                                </label>
                                <label style="display: flex; align-items: center; cursor: pointer; font-weight: normal;">
-                                    <input type="checkbox" x-model="docTypes" value="file" style="margin-right: 8px;">
+                                    <input type="checkbox" x-model="docTypes" value="file" style="margin-right: 4px;">
                                    <span>Files</span>
                                </label>
                                <label style="display: flex; align-items: center; cursor: pointer; font-weight: normal;">
-                                    <input type="checkbox" x-model="docTypes" value="calendar" style="margin-right: 8px;">
-                                    <span>Calendar Events</span>
+                                    <input type="checkbox" x-model="docTypes" value="calendar" style="margin-right: 4px;">
+                                    <span>Calendar</span>
                                </label>
                                <label style="display: flex; align-items: center; cursor: pointer; font-weight: normal;">
-                                    <input type="checkbox" x-model="docTypes" value="contact" style="margin-right: 8px;">
+                                    <input type="checkbox" x-model="docTypes" value="contact" style="margin-right: 4px;">
                                    <span>Contacts</span>
                                </label>
                                <label style="display: flex; align-items: center; cursor: pointer; font-weight: normal;">
-                                    <input type="checkbox" x-model="docTypes" value="deck" style="margin-right: 8px;">
-                                    <span>Deck Cards</span>
+                                    <input type="checkbox" x-model="docTypes" value="deck" style="margin-right: 4px;">
+                                    <span>Deck</span>
                                </label>
                            </div>
                        </div>

-                        <div>
-                            <div class="viz-control-group">
-                                <label>Score Threshold (Semantic/Hybrid)</label>
-                                <input type="number" x-model.number="scoreThreshold" min="0" max="1" step="any" />
-                            </div>
+                        <div class="viz-control-group">
+                            <label>Score Threshold</label>
+                            <input type="number" x-model.number="scoreThreshold" min="0" max="1" step="any" />
+                        </div>

-                            <div class="viz-control-group">
-                                <label>Result Limit</label>
-                                <input type="number" x-model.number="limit" min="1" max="100" />
-                            </div>
+                        <div class="viz-control-group">
+                            <label>Result Limit</label>
+                            <input type="number" x-model.number="limit" min="1" max="1000" />
+                        </div>
+
+                        <div class="viz-control-group">
+                            <label>Display Options</label>
+                            <label style="display: flex; align-items: center; cursor: pointer; font-weight: normal; margin-top: 4px;">
+                                <input type="checkbox" x-model="showQueryPoint" @change="updatePlot()" style="margin-right: 6px;">
+                                <span>Show Query Point</span>
+                            </label>
                        </div>
                    </div>
-
-                    <!-- Info: BM25 Hybrid fusion methods -->
-                    <div x-show="algorithm === 'bm25_hybrid'" style="margin-top: 16px; padding: 12px; background: #e9ecef; border-radius: 4px;">
-                        <p style="margin: 0; font-size: 14px; color: #666;">
-                            <strong>BM25 Hybrid Search:</strong> Combines dense semantic vectors with sparse BM25 keyword vectors.
-                        </p>
-                        <p style="margin: 8px 0 0 0; font-size: 13px; color: #666;">
-                            <strong>RRF:</strong> Reciprocal Rank Fusion - Rank-based fusion producing scores in [0.0, 1.0]
-                        </p>
-                        <p style="margin: 4px 0 0 0; font-size: 13px; color: #666;">
-                            <strong>DBSF:</strong> Distribution-Based Score Fusion - Sums normalized scores (can exceed 1.0)
-                        </p>
-                    </div>
                </div>
-            </div>
-        </form>
-    </div>
-
-    <div class="viz-card">
-        <div id="viz-plot-container">
-            <div x-show="loading" class="viz-loading-overlay" x-transition.opacity.duration.200ms>
-                Executing search and computing PCA projection...
-            </div>
-            <div id="viz-plot" x-show="!loading" x-transition.opacity.duration.200ms></div>
+            </form>
        </div>
-    </div>

-    <div class="viz-card">
-        <h3>Search Results (<span x-text="loading ? '...' : results.length"></span>)</h3>
+        <!-- Plot -->
+        <div class="viz-card viz-card-plot">
+            <div id="viz-plot-container">
+                <div x-show="loading" class="viz-loading-overlay" x-transition.opacity.duration.200ms>
+                    Executing search and computing PCA projection...
+                </div>
+                <div id="viz-plot" x-show="!loading" x-transition.opacity.duration.200ms></div>
+            </div>
+        </div>
+
+        <!-- Results -->
+        <div class="viz-card" style="flex: 0 0 auto;">
+            <h3 style="margin-top: 0;">Search Results (<span x-text="loading ? '...' : results.length"></span>)</h3>

        <div x-show="loading" class="viz-loading" x-transition.opacity.duration.200ms>
            Loading results...
@@ -335,5 +160,6 @@
                </template>
            </div>
        </template>
-    </div>
-</div>
+        </div><!-- Search Results -->
+    </div><!-- .viz-layout -->
+</div><!-- x-data="vizApp()" -->
@@ -0,0 +1,392 @@
+{% extends "base.html" %}
+
+{% block title %}Welcome - Nextcloud MCP Server{% endblock %}
+
+{% block extra_head %}
+    <!-- Alpine.js for interactive elements -->
+    <script defer src="https://cdn.jsdelivr.net/npm/alpinejs@3.x.x/dist/cdn.min.js"></script>
+{% endblock %}
+
+{% block extra_styles %}
+    /* Welcome page specific styles */
+    .hero-section {
+        background: linear-gradient(135deg, var(--color-primary-element) 0%, #0082c9 100%);
+        color: white;
+        padding: 60px 24px;
+        margin: -24px -24px 40px -24px;
+        border-radius: 0 0 var(--border-radius-large) var(--border-radius-large);
+        text-align: center;
+    }
+
+    .hero-section h1 {
+        color: white;
+        font-size: 36px;
+        margin: 0 0 16px 0;
+        font-weight: 600;
+    }
+
+    .hero-section p {
+        font-size: 18px;
+        opacity: 0.95;
+        max-width: 700px;
+        margin: 0 auto;
+        line-height: 1.6;
+    }
+
+    .feature-grid {
+        display: grid;
+        grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
+        gap: 24px;
+        margin: 32px 0;
+    }
+
+    .feature-card {
+        background: var(--color-main-background);
+        border: 2px solid var(--color-border);
+        border-radius: var(--border-radius-large);
+        padding: 24px;
+        transition: all 0.2s;
+        cursor: pointer;
+        text-decoration: none;
+        color: inherit;
+        display: block;
+    }
+
+    .feature-card:hover {
+        border-color: var(--color-primary-element);
+        box-shadow: 0 4px 12px rgba(0, 103, 158, 0.15);
+        transform: translateY(-2px);
+    }
+
+    .feature-card h3 {
+        color: var(--color-primary-element);
+        font-size: 20px;
+        margin: 12px 0 8px 0;
+        font-weight: 600;
+        display: flex;
+        align-items: center;
+        gap: 12px;
+    }
+
+    .feature-card p {
+        color: var(--color-text-maxcontrast);
+        font-size: 14px;
+        line-height: 1.6;
+        margin: 8px 0 0 0;
+    }
+
+    .feature-icon {
+        width: 48px;
+        height: 48px;
+        background: var(--color-primary-element-light);
+        border-radius: var(--border-radius);
+        display: flex;
+        align-items: center;
+        justify-content: center;
+        margin-bottom: 8px;
+    }
+
+    .feature-icon svg {
+        width: 28px;
+        height: 28px;
+        fill: var(--color-primary-element);
+    }
+
+    .info-section {
+        background: var(--color-background-hover);
+        border-radius: var(--border-radius-large);
+        padding: 32px;
+        margin: 32px 0;
+    }
+
+    .info-section h2 {
+        color: var(--color-main-text);
+        font-size: 24px;
+        margin: 0 0 16px 0;
+        border: none;
+        padding: 0;
+    }
+
+    .info-section p {
+        color: var(--color-text-maxcontrast);
+        line-height: 1.7;
+        margin: 12px 0;
+    }
+
+    .info-section ul {
+        margin: 12px 0;
+        padding-left: 24px;
+    }
+
+    .info-section li {
+        color: var(--color-text-maxcontrast);
+        line-height: 1.7;
+        margin: 8px 0;
+    }
+
+    .info-section code {
+        background: var(--color-main-background);
+        padding: 2px 8px;
+        border-radius: var(--border-radius);
+        font-size: 13px;
+    }
+
+    .auth-status {
+        background: var(--color-primary-element-light);
+        border-left: 4px solid var(--color-primary-element);
+        padding: 16px 20px;
+        margin: 24px 0;
+        border-radius: var(--border-radius);
+        display: flex;
+        align-items: center;
+        gap: 12px;
+    }
+
+    .auth-status svg {
+        width: 24px;
+        height: 24px;
+        fill: var(--color-primary-element);
+        flex-shrink: 0;
+    }
+
+    .auth-status-text {
+        flex: 1;
+    }
+
+    .auth-status-text strong {
+        display: block;
+        color: var(--color-main-text);
+        font-size: 14px;
+        margin-bottom: 4px;
+    }
+
+    .auth-status-text span {
+        color: var(--color-text-maxcontrast);
+        font-size: 13px;
+    }
+{% endblock %}
+
+{% block content %}
+<div class="app-content-wrapper">
+    <!-- Main Content Area -->
+    <main id="app-content">
+        <div class="page-content">
+            <!-- Hero Section -->
+            <div class="hero-section">
+                <h1>Welcome to Nextcloud MCP Server</h1>
+                <p>
+                    Interactive user interface for semantic search and document retrieval.
+                    Test queries, visualize results, and explore your Nextcloud content using RAG workflows.
+                </p>
+            </div>
+
+            <!-- Authentication Status -->
+            <div class="auth-status">
+                <svg viewBox="0 0 24 24">
+                    <path d="M12,4A4,4 0 0,1 16,8A4,4 0 0,1 12,12A4,4 0 0,1 8,8A4,4 0 0,1 12,4M12,14C16.42,14 20,15.79 20,18V20H4V18C4,15.79 7.58,14 12,14Z" />
+                </svg>
+                <div class="auth-status-text">
+                    <strong>Authenticated as: {{ username }}</strong>
+                    <span>Authentication mode: <code>{{ auth_mode }}</code></span>
+                </div>
+            </div>
+
+            {% if vector_sync_enabled %}
+            <!-- Vector Sync Enabled Content -->
+            <div class="info-section">
+                <h2>About Semantic Search</h2>
+                <p>
+                    This interface provides access to <strong>semantic search</strong> capabilities powered by vector embeddings.
+                    Unlike traditional keyword search, semantic search understands the <em>meaning</em> of your queries and finds
+                    conceptually similar content across your Nextcloud apps.
+                </p>
+                <p>
+                    <strong>How it works:</strong>
+                </p>
+                <ul>
+                    <li>Documents from Notes, Calendar, Files, Contacts, and Deck are indexed into a vector database</li>
+                    <li>Each document chunk is converted to a 768-dimensional vector embedding that captures semantic meaning</li>
+                    <li>Queries are also converted to embeddings and matched against document vectors using similarity search</li>
+                    <li>Results can be retrieved using pure semantic search or hybrid BM25 search combining keywords and semantics</li>
+                </ul>
+            </div>
+
+            <div class="info-section">
+                <h2>RAG Workflow Integration</h2>
+                <p>
+                    This UI allows you to <strong>test the same queries that Large Language Models (LLMs) would use</strong> in a
+                    Retrieval-Augmented Generation (RAG) workflow. When an AI assistant needs to answer questions about your data:
+                </p>
+                <ul>
+                    <li><strong>Step 1:</strong> The assistant converts your question into a search query</li>
+                    <li><strong>Step 2:</strong> The MCP server retrieves relevant document chunks using semantic search</li>
+                    <li><strong>Step 3:</strong> Retrieved context is passed to the LLM to generate an informed answer</li>
+                </ul>
+
+                <!-- RAG Workflow Diagram -->
+                <div style="background: var(--color-main-background); border: 2px solid var(--color-primary-element); border-radius: var(--border-radius-large); padding: 24px; margin: 24px 0; font-family: 'SFMono-Regular', 'Consolas', 'Liberation Mono', 'Menlo', monospace; font-size: 13px; line-height: 1.8; overflow-x: auto;">
+                    <div style="text-align: center; font-weight: 600; margin-bottom: 16px; color: var(--color-primary-element); font-size: 14px;">
+                        MCP Sampling RAG Workflow
+                    </div>
+                    <pre style="margin: 0; color: var(--color-main-text);">
+┌─────────────────┐
+│   <strong>MCP Client</strong>   │  User asks: "What are health benefits of coffee?"
+│  (Claude Code)  │
+└────────┬────────┘
+         │ (1) User question
+         ↓
+┌────────────────────────────────────────────────────────────────────────┐
+│                      <strong>Nextcloud MCP Server</strong>                          │
+│  ┌──────────────────────────────────────────────────────────────────┐  │
+│  │ <strong>nc_semantic_search_answer</strong> Tool (MCP Sampling-enabled)      │  │
+│  │                                                                  │  │
+│  │  (2) Semantic Search                                             │  │
+│  │  ┌────────────────────────────────────────────────────────┐     │  │
+│  │  │ Query: "health benefits of coffee"                     │     │  │
+│  │  │ → Convert to 768D vector embedding                     │     │  │
+│  │  │ → Search Qdrant (BM25 Hybrid + RRF fusion)             │     │  │
+│  │  │ → Retrieve top 5 relevant document chunks              │     │  │
+│  │  └────────────────────────────────────────────────────────┘     │  │
+│  │                                                                  │  │
+│  │  (3) Construct Prompt with Context                               │  │
+│  │  ┌────────────────────────────────────────────────────────┐     │  │
+│  │  │ "What are health benefits of coffee?                   │     │  │
+│  │  │                                                         │     │  │
+│  │  │  Documents:                                             │     │  │
+│  │  │  - [MED-2155] Effects of habitual coffee consumption...│     │  │
+│  │  │  - [MED-1646] Beverage consumption guidance...         │     │  │
+│  │  │  - [MED-1627] Coffee and depression risk...            │     │  │
+│  │  │  ...                                                    │     │  │
+│  │  │                                                         │     │  │
+│  │  │  Provide answer with citations."                        │     │  │
+│  │  └────────────────────────────────────────────────────────┘     │  │
+│  │                                                                  │  │
+│  │  (4) MCP Sampling Request                                        │  │
+│  │  ─────────────────────────────────────────────────────────────> │  │
+│  └──────────────────────────────────────────────────────────────────┘  │
+└────────────────────────────────────────────────────────────────────────┘
+         │
+         │ Sampling request with prompt + context
+         ↓
+┌─────────────────┐
+│   <strong>MCP Client</strong>   │  (5) Client's LLM generates answer using retrieved context
+│    (Claude)     │      → "Coffee consumption (2-3 cups/day) is associated with
+└────────┬────────┘         reduced risk of type 2 diabetes, cardiovascular disease,
+         │                  and improved liver health (Document 1, 2)..."
+         │
+         │ (6) Answer with citations
+         ↓
+┌─────────────────┐
+│      User       │  Receives comprehensive answer with source citations
+└─────────────────┘</pre>
+                </div>
+
+                <p style="margin-top: 16px;">
+                    <strong>Key Point:</strong> The MCP server retrieves context but doesn't generate answers itself.
+                    Through <strong>MCP sampling</strong>, it requests the client's LLM to generate responses, giving users
+                    full control over which model is used and ensuring all processing happens client-side.
+                </p>
+
+                <p>
+                    By using this interface, you can preview search results, understand relevance scores, and verify
+                    that the system retrieves the right information before it reaches the LLM.
+                </p>
+            </div>
+
+            <!-- Feature Cards -->
+            <h2>Available Features</h2>
+            <div class="feature-grid">
+                <a href="/app/user-info" class="feature-card">
+                    <div class="feature-icon">
+                        <svg viewBox="0 0 24 24">
+                            <path d="M12,4A4,4 0 0,1 16,8A4,4 0 0,1 12,12A4,4 0 0,1 8,8A4,4 0 0,1 12,4M12,14C16.42,14 20,15.79 20,18V20H4V18C4,15.79 7.58,14 12,14Z" />
+                        </svg>
+                    </div>
+                    <h3>User Information</h3>
+                    <p>
+                        View your authentication details, session information, and IdP profile.
+                        Manage background access permissions.
+                    </p>
+                </a>
+
+                <a href="/app/user-info#vector-sync" class="feature-card">
+                    <div class="feature-icon">
+                        <svg viewBox="0 0 24 24">
+                            <path d="M12,18A6,6 0 0,1 6,12C6,11 6.25,10.03 6.7,9.2L5.24,7.74C4.46,8.97 4,10.43 4,12A8,8 0 0,0 12,20V23L16,19L12,15M12,4V1L8,5L12,9V6A6,6 0 0,1 18,12C18,13 17.75,13.97 17.3,14.8L18.76,16.26C19.54,15.03 20,13.57 20,12A8,8 0 0,0 12,4Z" />
+                        </svg>
+                    </div>
+                    <h3>Vector Sync Status</h3>
+                    <p>
+                        Monitor real-time indexing progress with metrics for indexed documents, pending queue,
+                        and synchronization status.
+                    </p>
+                </a>
+
+                <a href="/app/user-info#vector-viz" class="feature-card">
+                    <div class="feature-icon">
+                        <svg viewBox="0 0 24 24">
+                            <path d="M22,21H2V3H4V19H6V10H10V19H12V6H16V19H18V14H22V21Z" />
+                        </svg>
+                    </div>
+                    <h3>Vector Visualization</h3>
+                    <p>
+                        Interactive search interface with 2D PCA visualization. Compare algorithms,
+                        view relevance scores, and explore matched document chunks.
+                    </p>
+                </a>
+            </div>
+
+            {% else %}
+            <!-- Vector Sync Disabled Content -->
+            <div class="warning">
+                <h3 style="margin-top: 0;">Vector Sync is Disabled</h3>
+                <p>
+                    Semantic search and vector visualization features are currently disabled.
+                    To enable these features, set <code>VECTOR_SYNC_ENABLED=true</code> in your environment configuration.
+                </p>
+                <p style="margin-bottom: 0;">
+                    <strong>Learn more:</strong>
+                    <a href="https://github.com/YOUR_REPO/docs/configuration.md" target="_blank" style="color: inherit; text-decoration: underline;">
+                        Configuration Guide
+                    </a>
+                </p>
+            </div>
+
+            <!-- Limited Feature Card -->
+            <h2>Available Features</h2>
+            <div class="feature-grid">
+                <a href="/app/user-info" class="feature-card">
+                    <div class="feature-icon">
+                        <svg viewBox="0 0 24 24">
+                            <path d="M12,4A4,4 0 0,1 16,8A4,4 0 0,1 12,12A4,4 0 0,1 8,8A4,4 0 0,1 12,4M12,14C16.42,14 20,15.79 20,18V20H4V18C4,15.79 7.58,14 12,14Z" />
+                        </svg>
+                    </div>
+                    <h3>User Information</h3>
+                    <p>
+                        View your authentication details, session information, and IdP profile.
+                        Manage background access permissions.
+                    </p>
+                </a>
+            </div>
+            {% endif %}
+
+            <!-- Documentation Section -->
+            <div class="info-section" style="margin-top: 40px;">
+                <h2>Documentation</h2>
+                <p>
+                    For detailed information about configuration, authentication modes, and advanced features,
+                    please refer to the project documentation:
+                </p>
+                <ul>
+                    <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/installation.md" target="_blank">Installation Guide</a></li>
+                    <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/configuration.md" target="_blank">Configuration Options</a></li>
+                    <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/authentication.md" target="_blank">Authentication Modes</a></li>
+                    {% if vector_sync_enabled %}
+                    <li><a href="https://github.com/cbcoutinho/nextcloud-mcp-server/blob/master/docs/user-guide/vector-sync-ui.md" target="_blank">Vector Sync UI Guide</a></li>
+                    {% endif %}
+                </ul>
+            </div>
+        </div>
+    </main>
+</div>
+{% endblock %}
@@ -9,15 +9,21 @@ For OAuth mode: Requires browser-based OAuth login to establish session.

 import logging
 import os
+from pathlib import Path
 from typing import Any

 import httpx
+from jinja2 import Environment, FileSystemLoader
 from starlette.authentication import requires
 from starlette.requests import Request
 from starlette.responses import HTMLResponse, JSONResponse

 logger = logging.getLogger(__name__)

+# Setup Jinja2 environment for templates
+_template_dir = Path(__file__).parent / "templates"
+_jinja_env = Environment(loader=FileSystemLoader(_template_dir))
+

 async def _get_authenticated_client_for_userinfo(request: Request) -> httpx.AsyncClient:
    """Get an authenticated HTTP client for user info page operations.
@@ -431,51 +437,14 @@ async def user_info_html(request: Request) -> HTMLResponse:
        oauth_ctx = getattr(request.app.state, "oauth_context", None)
        login_url = str(request.url_for("oauth_login")) if oauth_ctx else "/oauth/login"

-        error_html = f"""
-        <!DOCTYPE html>
-        <html lang="en">
-        <head>
-            <meta charset="UTF-8">
-            <meta name="viewport" content="width=device-width, initial-scale=1.0">
-            <title>Error - Nextcloud MCP Server</title>
-            <style>
-                body {{
-                    font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
-                    max-width: 800px;
-                    margin: 50px auto;
-                    padding: 20px;
-                    background-color: #f5f5f5;
-                }}
-                .container {{
-                    background: white;
-                    border-radius: 8px;
-                    padding: 30px;
-                    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-                }}
-                h1 {{
-                    color: #d32f2f;
-                    margin-top: 0;
-                }}
-                .error {{
-                    background-color: #ffebee;
-                    border-left: 4px solid #d32f2f;
-                    padding: 15px;
-                    margin: 20px 0;
-                }}
-            </style>
-        </head>
-        <body>
-            <div class="container">
-                <h1>Error Retrieving User Info</h1>
-                <div class="error">
-                    <strong>Error:</strong> {user_context["error"]}
-                </div>
-                <p><a href="{login_url}">Login again</a></p>
-            </div>
-        </body>
-        </html>
-        """
-        return HTMLResponse(content=error_html)
+        template = _jinja_env.get_template("error.html")
+        return HTMLResponse(
+            content=template.render(
+                error_title="Error Retrieving User Info",
+                error_message=user_context["error"],
+                login_url=login_url,
+            )
+        )

    # Build HTML response
    auth_mode = user_context.get("auth_mode", "unknown")
@@ -654,457 +623,26 @@ async def user_info_html(request: Request) -> HTMLResponse:
            </div>
        """

-    html_content = f"""
-    <!DOCTYPE html>
-    <html lang="en">
-    <head>
-        <meta charset="UTF-8">
-        <meta name="viewport" content="width=device-width, initial-scale=1.0">
-        <title>Nextcloud MCP Server</title>
+    # Check if vector sync is enabled (needed for Welcome tab)
+    vector_sync_enabled = os.getenv("VECTOR_SYNC_ENABLED", "false").lower() == "true"

-        <!-- htmx for dynamic loading -->
-        <script src="https://unpkg.com/htmx.org@1.9.10"></script>
-
-        <!-- Alpine.js for tab state management -->
-        <script defer src="https://cdn.jsdelivr.net/npm/alpinejs@3.x.x/dist/cdn.min.js"></script>
-
-        <!-- Plotly.js for vector visualization -->
-        <script src="https://cdn.plot.ly/plotly-2.27.0.min.js"></script>
-
-        <!-- Vector visualization app (Alpine.js component) -->
-        <script>
-            function vizApp() {{
-                return {{
-                    query: '',
-                    algorithm: 'bm25_hybrid',
-                    fusion: 'rrf',  // Default fusion method for BM25 Hybrid
-                    showAdvanced: false,
-                    docTypes: [''],  // Default to "All Types"
-                    limit: 50,
-                    scoreThreshold: 0.0,
-                    loading: false,
-                    results: [],
-                    expandedChunks: {{}},  // Track which chunks are expanded (result_id -> chunk data)
-                    chunkLoading: {{}},    // Track loading state per result
-
-                    async executeSearch() {{
-                        this.loading = true;
-                        this.results = [];
-
-                        try {{
-                            const params = new URLSearchParams({{
-                                query: this.query,
-                                algorithm: this.algorithm,
-                                limit: this.limit,
-                                score_threshold: this.scoreThreshold,
-                            }});
-
-                            // Add fusion parameter for BM25 Hybrid
-                            if (this.algorithm === 'bm25_hybrid') {{
-                                params.append('fusion', this.fusion);
-                            }}
-
-                            // Add doc_types parameter (filter out empty string for "All Types")
-                            const selectedTypes = this.docTypes.filter(t => t !== '');
-                            if (selectedTypes.length > 0) {{
-                                params.append('doc_types', selectedTypes.join(','));
-                            }}
-
-                            const response = await fetch(`/app/vector-viz/search?${{params}}`);
-                            const data = await response.json();
-
-                            if (data.success) {{
-                                this.results = data.results;
-                                this.renderPlot(data.coordinates_2d, data.results);
-                            }} else {{
-                                alert('Search failed: ' + data.error);
-                            }}
-                        }} catch (error) {{
-                            alert('Error: ' + error.message);
-                        }} finally {{
-                            this.loading = false;
-                        }}
-                    }},
-
-                    renderPlot(coordinates, results) {{
-                        // Calculate score range for auto-scaling
-                        const scores = results.map(r => r.score);
-                        const minScore = Math.min(...scores);
-                        const maxScore = Math.max(...scores);
-
-                        const trace = {{
-                            x: coordinates.map(c => c[0]),
-                            y: coordinates.map(c => c[1]),
-                            mode: 'markers',
-                            type: 'scatter',
-                            text: results.map(r => `${{r.title}}<br>Raw Score: ${{r.original_score.toFixed(3)}} (${{(r.score * 100).toFixed(0)}}% relative)`),
-                            marker: {{
-                                // Multi-channel encoding: size + opacity + color for visual hierarchy
-                                // Power scaling (score^2) amplifies visual differences dramatically
-                                // score=0.0 → 6px, score=0.5 → 9.5px, score=1.0 → 20px
-                                size: results.map(r => 6 + (Math.pow(r.score, 2) * 14)),
-                                // Linear opacity scaling (0.2-1.0 range keeps all points visible)
-                                opacity: results.map(r => 0.2 + (r.score * 0.8)),
-                                // Color gradient shows score
-                                color: scores,
-                                colorscale: 'Viridis',
-                                showscale: true,
-                                colorbar: {{ title: 'Relative Score' }},
-                                // Scores are normalized 0-1 within result set
-                                cmin: 0,
-                                cmax: 1
-                            }}
-                        }};
-
-                        const layout = {{
-                            title: `Vector Space (PCA 2D) - ${{results.length}} results`,
-                            xaxis: {{ title: 'PC1' }},
-                            yaxis: {{ title: 'PC2' }},
-                            hovermode: 'closest',
-                            height: 600
-                        }};
-
-                        Plotly.newPlot('viz-plot', [trace], layout);
-                    }},
-
-                    getNextcloudUrl(result) {{
-                        // Generate Nextcloud URL based on document type
-                        // Use the actual Nextcloud host (port 8080), not the MCP server
-                        const baseUrl = '{nextcloud_host_for_links}';
-
-                        switch (result.doc_type) {{
-                            case 'note':
-                                return `${{baseUrl}}/apps/notes/note/${{result.id}}`;
-                            case 'file':
-                                return `${{baseUrl}}/apps/files/?fileId=${{result.id}}`;
-                            case 'calendar':
-                                return `${{baseUrl}}/apps/calendar`;
-                            case 'contact':
-                                return `${{baseUrl}}/apps/contacts`;
-                            case 'deck':
-                                return `${{baseUrl}}/apps/deck`;
-                            default:
-                                return `${{baseUrl}}`;
-                        }}
-                    }},
-
-                    hasChunkPosition(result) {{
-                        // Check if result has position metadata
-                        return result.chunk_start_offset != null && result.chunk_end_offset != null;
-                    }},
-
-                    isChunkExpanded(resultKey) {{
-                        return this.expandedChunks[resultKey] !== undefined;
-                    }},
-
-                    async toggleChunk(result) {{
-                        const resultKey = `${{result.doc_type}}_${{result.id}}`;
-
-                        // If already expanded, collapse
-                        if (this.isChunkExpanded(resultKey)) {{
-                            delete this.expandedChunks[resultKey];
-                            return;
-                        }}
-
-                        // Otherwise, fetch and expand
-                        this.chunkLoading[resultKey] = true;
-
-                        try {{
-                            const params = new URLSearchParams({{
-                                doc_type: result.doc_type,
-                                doc_id: result.id,
-                                start: result.chunk_start_offset,
-                                end: result.chunk_end_offset,
-                                context: 500  // 500 chars before/after
-                            }});
-
-                            const response = await fetch(`/app/chunk-context?${{params}}`);
-                            const data = await response.json();
-
-                            if (data.success) {{
-                                this.expandedChunks[resultKey] = data;
-                            }} else {{
-                                alert('Failed to load chunk: ' + data.error);
-                            }}
-                        }} catch (error) {{
-                            alert('Error loading chunk: ' + error.message);
-                        }} finally {{
-                            delete this.chunkLoading[resultKey];
-                        }}
-                    }}
-                }}
-            }}
-        </script>
-
-        <style>
-            body {{
-                font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif;
-                max-width: 900px;
-                margin: 50px auto;
-                padding: 20px;
-                background-color: #f5f5f5;
-            }}
-            .container {{
-                background: white;
-                border-radius: 8px;
-                padding: 30px;
-                box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-                min-height: calc(100vh - 200px);
-            }}
-            h1 {{
-                color: #0082c9;
-                margin-top: 0;
-                border-bottom: 2px solid #0082c9;
-                padding-bottom: 10px;
-            }}
-            h2 {{
-                color: #333;
-                margin-top: 20px;
-                border-bottom: 1px solid #e0e0e0;
-                padding-bottom: 5px;
-            }}
-
-            /* Tab navigation */
-            .tabs {{
-                display: flex;
-                gap: 0;
-                margin: 20px 0 0 0;
-                border-bottom: 2px solid #e0e0e0;
-            }}
-            .tab {{
-                padding: 12px 24px;
-                cursor: pointer;
-                background: transparent;
-                border: none;
-                font-size: 14px;
-                font-weight: 500;
-                color: #666;
-                border-bottom: 2px solid transparent;
-                margin-bottom: -2px;
-                transition: all 0.2s;
-            }}
-            .tab:hover {{
-                color: #0082c9;
-                background-color: #f5f5f5;
-            }}
-            .tab.active {{
-                color: #0082c9;
-                border-bottom-color: #0082c9;
-            }}
-
-            /* Tab content - use grid to overlay panes */
-            .tab-content {{
-                padding: 20px 0;
-                display: grid;
-            }}
-
-            /* Tab panes - all occupy the same grid cell to overlay */
-            .tab-pane {{
-                grid-area: 1 / 1;
-            }}
-
-            /* Tables */
-            table {{
-                width: 100%;
-                border-collapse: collapse;
-                margin: 15px 0;
-            }}
-            td {{
-                padding: 10px;
-                border-bottom: 1px solid #e0e0e0;
-            }}
-            td:first-child {{
-                width: 200px;
-                color: #666;
-            }}
-            code {{
-                background-color: #f5f5f5;
-                padding: 2px 6px;
-                border-radius: 3px;
-                font-family: 'Courier New', monospace;
-            }}
-
-            /* Badges */
-            .badge {{
-                display: inline-block;
-                padding: 3px 8px;
-                border-radius: 12px;
-                font-size: 12px;
-                font-weight: bold;
-                text-transform: uppercase;
-            }}
-            .badge-oauth {{
-                background-color: #4caf50;
-                color: white;
-            }}
-            .badge-basic {{
-                background-color: #2196f3;
-                color: white;
-            }}
-
-            /* Messages */
-            .warning {{
-                background-color: #fff3cd;
-                border-left: 4px solid #ffc107;
-                padding: 15px;
-                margin: 15px 0;
-                color: #856404;
-            }}
-            .info-message {{
-                background-color: #e3f2fd;
-                border-left: 4px solid #2196f3;
-                padding: 15px;
-                margin: 15px 0;
-                color: #1565c0;
-            }}
-
-            /* Buttons */
-            .button {{
-                display: inline-block;
-                padding: 10px 20px;
-                background-color: #d32f2f;
-                color: white;
-                text-decoration: none;
-                border-radius: 4px;
-                transition: background-color 0.3s;
-                border: none;
-                cursor: pointer;
-                font-size: 14px;
-            }}
-            .button:hover {{
-                background-color: #b71c1c;
-            }}
-            .button-primary {{
-                background-color: #0082c9;
-            }}
-            .button-primary:hover {{
-                background-color: #006ba3;
-            }}
-
-            /* Logout section */
-            .logout {{
-                margin-top: 30px;
-                padding-top: 20px;
-                border-top: 1px solid #e0e0e0;
-            }}
-
-            /* Smooth htmx content swaps */
-            .htmx-swapping {{
-                opacity: 0;
-                transition: opacity 200ms ease-out;
-            }}
-
-            /* Smooth htmx content settling */
-            .htmx-settling {{
-                opacity: 1;
-                transition: opacity 200ms ease-in;
-            }}
-        </style>
-    </head>
-    <body>
-        <div class="container" x-data="{{ activeTab: 'user-info' }}">
-            <h1>Nextcloud MCP Server</h1>
-
-            <!-- Tab Navigation -->
-            <div class="tabs">
-                <button
-                    class="tab"
-                    :class="activeTab === 'user-info' ? 'active' : ''"
-                    @click="activeTab = 'user-info'">
-                    User Info
-                </button>
-                {
-        ""
-        if not show_vector_sync_tab
-        else '''
-                <button
-                    class="tab"
-                    :class="activeTab === 'vector-sync' ? 'active' : ''"
-                    @click="activeTab = 'vector-sync'">
-                    Vector Sync
-                </button>
-                '''
-    }
-                {
-        ""
-        if not show_vector_sync_tab
-        else '''
-                <button
-                    class="tab"
-                    :class="activeTab === 'vector-viz' ? 'active' : ''"
-                    @click="activeTab = 'vector-viz'">
-                    Vector Viz
-                </button>
-                '''
-    }
-                {
-        ""
-        if not show_webhooks_tab
-        else '''
-                <button
-                    class="tab"
-                    :class="activeTab === 'webhooks' ? 'active' : ''"
-                    @click="activeTab = 'webhooks'">
-                    Webhooks
-                </button>
-                '''
-    }
-            </div>
-
-            <!-- Tab Content -->
-            <div class="tab-content">
-                <!-- User Info Tab -->
-                <div class="tab-pane" x-show="activeTab === 'user-info'" x-transition.opacity.duration.150ms>
-                    {user_info_tab_html}
-                </div>
-
-                {
-        ""
-        if not show_vector_sync_tab
-        else f'''
-                <!-- Vector Sync Tab -->
-                <div class="tab-pane" x-show="activeTab === 'vector-sync'" x-transition.opacity.duration.150ms>
-                    {vector_sync_tab_html}
-                </div>
-                '''
-    }
-
-                {
-        ""
-        if not show_vector_sync_tab
-        else '''
-                <!-- Vector Viz Tab -->
-                <div class="tab-pane" x-show="activeTab === 'vector-viz'" x-transition.opacity.duration.150ms>
-                    <div hx-get="/app/vector-viz" hx-trigger="load" hx-swap="outerHTML">
-                        <p style="color: #999;">Loading vector visualization...</p>
-                    </div>
-                </div>
-                '''
-    }
-
-                {
-        ""
-        if not show_webhooks_tab
-        else f'''
-                <!-- Webhooks Tab (admin-only, loaded dynamically) -->
-                <div class="tab-pane" x-show="activeTab === 'webhooks'" x-transition.opacity.duration.150ms>
-                    {webhooks_tab_html}
-                </div>
-                '''
-    }
-            </div>
-
-            {
-        f'<div class="logout"><a href="{logout_url}" class="button">Logout</a></div>'
-        if auth_mode == "oauth"
-        else ""
-    }
-        </div>
-    </body>
-    </html>
-    """
-
-    return HTMLResponse(content=html_content)
+    # Render template
+    template = _jinja_env.get_template("user_info.html")
+    return HTMLResponse(
+        content=template.render(
+            user_info_tab_html=user_info_tab_html,
+            vector_sync_tab_html=vector_sync_tab_html,
+            webhooks_tab_html=webhooks_tab_html,
+            show_vector_sync_tab=show_vector_sync_tab,
+            show_webhooks_tab=show_webhooks_tab,
+            logout_url=logout_url if auth_mode == "oauth" else None,
+            nextcloud_host_for_links=nextcloud_host_for_links,
+            # Additional context for Welcome tab
+            vector_sync_enabled=vector_sync_enabled,
+            username=username,
+            auth_mode=auth_mode,
+        )
+    )


@requires("authenticated", redirect="oauth_login")
@@ -1124,17 +662,12 @@ async def revoke_session(request: Request) -> HTMLResponse:
    oauth_ctx = getattr(request.app.state, "oauth_context", None)

    if not oauth_ctx:
+        template = _jinja_env.get_template("error.html")
        return HTMLResponse(
-            """
-            <!DOCTYPE html>
-            <html>
-            <head><title>Error</title></head>
-            <body>
-                <h1>Error</h1>
-                <p>OAuth mode not enabled</p>
-            </body>
-            </html>
-            """,
+            content=template.render(
+                error_title="Error",
+                error_message="OAuth mode not enabled",
+            ),
            status_code=400,
        )

@@ -1142,17 +675,12 @@ async def revoke_session(request: Request) -> HTMLResponse:
    session_id = request.cookies.get("mcp_session")

    if not storage or not session_id:
+        template = _jinja_env.get_template("error.html")
        return HTMLResponse(
-            """
-            <!DOCTYPE html>
-            <html>
-            <head><title>Error</title></head>
-            <body>
-                <h1>Error</h1>
-                <p>Session not found</p>
-            </body>
-            </html>
-            """,
+            content=template.render(
+                error_title="Error",
+                error_message="Session not found",
+            ),
            status_code=400,
        )

@@ -1165,57 +693,26 @@ async def revoke_session(request: Request) -> HTMLResponse:
        # Redirect back to user page
        user_page_url = str(request.url_for("user_info_html"))

+        template = _jinja_env.get_template("success.html")
        return HTMLResponse(
-            f"""
-            <!DOCTYPE html>
-            <html lang="en">
-            <head>
-                <meta charset="UTF-8">
-                <meta http-equiv="refresh" content="2;url={user_page_url}">
-                <title>Background Access Revoked</title>
-                <style>
-                    body {{
-                        font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
-                        max-width: 600px;
-                        margin: 50px auto;
-                        padding: 20px;
-                        text-align: center;
-                    }}
-                    .success {{
-                        background-color: #e8f5e9;
-                        border: 2px solid #4caf50;
-                        padding: 30px;
-                        border-radius: 8px;
-                    }}
-                    h1 {{
-                        color: #4caf50;
-                    }}
-                </style>
-            </head>
-            <body>
-                <div class="success">
-                    <h1>✓ Background Access Revoked</h1>
-                    <p>Your refresh token has been deleted successfully.</p>
-                    <p>Browser session remains active.</p>
-                    <p>Redirecting back to user page...</p>
-                </div>
-            </body>
-            </html>
-            """
+            content=template.render(
+                success_title="✓ Background Access Revoked",
+                success_messages=[
+                    "Your refresh token has been deleted successfully.",
+                    "Browser session remains active.",
+                ],
+                redirect_url=user_page_url,
+                redirect_delay=2,
+            )
        )

    except Exception as e:
        logger.error(f"Failed to revoke background access: {e}")
+        template = _jinja_env.get_template("error.html")
        return HTMLResponse(
-            f"""
-            <!DOCTYPE html>
-            <html>
-            <head><title>Error</title></head>
-            <body>
-                <h1>Error</h1>
-                <p>Failed to revoke background access: {e}</p>
-            </body>
-            </html>
-            """,
+            content=template.render(
+                error_title="Error",
+                error_message=f"Failed to revoke background access: {e}",
+            ),
            status_code=500,
        )
@@ -1,13 +1,14 @@
 """Vector visualization routes for testing search algorithms.

 Provides a web UI for users to test different search algorithms on their own
-indexed documents and visualize results in 2D space using PCA.
+indexed documents and visualize results in 3D space using PCA.

 All processing happens server-side following ADR-012:
 - Search execution via shared search/algorithms.py
- PCA dimensionality reduction (768-dim → 2D)
- Only 2D coordinates + metadata sent to client
- Bandwidth-efficient (2 floats per doc vs 768)
+- Query embedding generation
+- PCA dimensionality reduction (768-dim → 3D)
+- Only 3D coordinates + metadata sent to client
+- Bandwidth-efficient (3 floats per doc vs 768)
 """

 import logging
@@ -77,19 +78,20 @@ async def vector_visualization_html(request: Request) -> HTMLResponse:

@requires("authenticated", redirect="oauth_login")
 async def vector_visualization_search(request: Request) -> JSONResponse:
-    """Execute server-side search and return 2D coordinates + results.
+    """Execute server-side search and return 3D coordinates + results.

    All processing happens server-side:
    1. Execute search via shared algorithm module
-    2. Fetch matching vectors from Qdrant
-    3. Apply PCA reduction (768-dim → 2D)
-    4. Return coordinates + metadata only
+    2. Generate query embedding
+    3. Fetch matching vectors from Qdrant
+    4. Apply PCA reduction (768-dim → 3D) to query + documents
+    5. Return coordinates + metadata only

    Args:
        request: Starlette request with query parameters

    Returns:
-        JSON response with coordinates_2d and results
+        JSON response with coordinates_3d and results (including query point)
    """
    settings = get_settings()

@@ -209,7 +211,8 @@ async def vector_visualization_search(request: Request) -> JSONResponse:
                {
                    "success": True,
                    "results": [],
-                    "coordinates_2d": [],
+                    "coordinates_3d": [],
+                    "query_coords": None,
                    "message": "No results found",
                }
            )
@@ -253,7 +256,7 @@ async def vector_visualization_search(request: Request) -> JSONResponse:
                }
            )

-        # Extract dense vectors (handle both named and unnamed vectors)
+        # Extract dense vectors and group by document
        def extract_dense_vector(point):
            if point.vector is None:
                return None
@@ -263,13 +266,21 @@ async def vector_visualization_search(request: Request) -> JSONResponse:
            # If unnamed vector (array), use directly
            return point.vector

-        vectors = np.array(
-            [v for v in (extract_dense_vector(p) for p in points) if v is not None]
-        )
+        # Group chunk vectors by doc_id
+        from collections import defaultdict
+
+        doc_chunks = defaultdict(list)
+        for point in points:
+            if point.payload:
+                doc_id = int(point.payload.get("doc_id", 0))
+                vector = extract_dense_vector(point)
+                if vector is not None:
+                    doc_chunks[doc_id].append(vector)
+
        vector_fetch_duration = time.perf_counter() - vector_fetch_start

-        if len(vectors) < 2:
-            # Not enough points for PCA
+        if len(doc_chunks) < 2:
+            # Not enough documents for PCA
            return JSONResponse(
                {
                    "success": True,
@@ -283,35 +294,131 @@ async def vector_visualization_search(request: Request) -> JSONResponse:
                        }
                        for r in search_results
                    ],
-                    "coordinates_2d": [[0, 0]] * len(search_results),
-                    "message": "Not enough vectors for PCA",
+                    "coordinates_3d": [[0, 0, 0]] * len(search_results),
+                    "query_coords": [0, 0, 0],
+                    "message": "Not enough documents for PCA",
                }
            )

-        # Apply PCA dimensionality reduction (768-dim → 2D)
+        # Detect embedding dimension from first available vector
+        embedding_dim = None
+        for chunks in doc_chunks.values():
+            if chunks:
+                embedding_dim = len(chunks[0])
+                break
+
+        if embedding_dim is None:
+            return JSONResponse(
+                {
+                    "success": False,
+                    "error": "Could not determine embedding dimension",
+                },
+                status_code=500,
+            )
+
+        logger.info(f"Detected embedding dimension: {embedding_dim}")
+
+        # Average chunk vectors per document to create document-level embeddings
+        # Maintain order of search_results for coordinate mapping
+        doc_vectors = []
+        for result in search_results:
+            if result.id in doc_chunks:
+                # Average all chunk embeddings for this document
+                chunk_vectors = np.array(doc_chunks[result.id])
+                avg_vector = np.mean(chunk_vectors, axis=0)
+                doc_vectors.append(avg_vector)
+                logger.debug(f"Doc {result.id}: averaged {len(chunk_vectors)} chunks")
+            else:
+                # Document not found in vectors (shouldn't happen)
+                logger.warning(f"Doc {result.id} not found in fetched vectors")
+                # Use zero vector as fallback with detected dimension
+                doc_vectors.append(np.zeros(embedding_dim))
+
+        doc_vectors = np.array(doc_vectors)
+
+        # Generate query embedding for visualization
+        query_embed_start = time.perf_counter()
+        from nextcloud_mcp_server.embedding.service import get_embedding_service
+
+        embedding_service = get_embedding_service()
+        query_embedding = await embedding_service.embed(query)
+        query_embed_duration = time.perf_counter() - query_embed_start
+
+        logger.info(f"Generated query embedding (dimension={len(query_embedding)})")
+
+        # Combine query vector with document vectors for PCA
+        # Query will be the last point in the array
+        all_vectors = np.vstack([doc_vectors, np.array([query_embedding])])
+
+        # Normalize vectors to unit length (L2 normalization)
+        # This is critical because Qdrant uses COSINE distance, which only measures
+        # vector direction (angle), not magnitude. PCA uses Euclidean distance which
+        # considers both direction and magnitude. By normalizing to unit length,
+        # Euclidean distances in PCA space will match cosine distances.
+        norms = np.linalg.norm(all_vectors, axis=1, keepdims=True)
+
+        # Check for zero-norm vectors (can happen with empty/corrupted embeddings)
+        zero_norm_mask = norms[:, 0] < 1e-10
+        if zero_norm_mask.any():
+            zero_indices = np.where(zero_norm_mask)[0]
+            logger.warning(
+                f"Found {zero_norm_mask.sum()} zero-norm vectors at indices {zero_indices.tolist()}. "
+                "Replacing with small epsilon to avoid division by zero."
+            )
+            # Replace zero norms with small epsilon to avoid NaN
+            norms[zero_norm_mask] = 1e-10
+
+        all_vectors_normalized = all_vectors / norms
+        logger.info(
+            f"Normalized vectors: query_norm={norms[-1][0]:.3f}, "
+            f"doc_norm_range=[{norms[:-1].min():.3f}, {norms[:-1].max():.3f}]"
+        )
+
+        # Apply PCA dimensionality reduction (768-dim → 3D) on normalized vectors
        pca_start = time.perf_counter()
-        pca = PCA(n_components=2)
-        coords_2d = pca.fit_transform(vectors)
+        pca = PCA(n_components=3)
+        coords_3d = pca.fit_transform(all_vectors_normalized)
        pca_duration = time.perf_counter() - pca_start

        # After fit, these attributes are guaranteed to be set
        assert pca.explained_variance_ratio_ is not None

-        logger.info(
-            f"PCA explained variance: PC1={pca.explained_variance_ratio_[0]:.3f}, "
-            f"PC2={pca.explained_variance_ratio_[1]:.3f}"
+        # Check for NaN values in PCA output (numerical instability)
+        nan_mask = np.isnan(coords_3d)
+        if nan_mask.any():
+            nan_rows = np.where(nan_mask.any(axis=1))[0]
+            logger.error(
+                f"Found NaN values in PCA output at {len(nan_rows)} points: {nan_rows.tolist()[:10]}. "
+                "Replacing NaN with 0.0 to prevent JSON serialization error."
+            )
+            # Replace NaN with 0 to allow JSON serialization
+            coords_3d = np.nan_to_num(coords_3d, nan=0.0)
+
+        # Split query coords from document coords
+        # Round to 2 decimal places for cleaner display
+        query_coords_3d = [
+            round(float(x), 2) for x in coords_3d[-1]
+        ]  # Last point is query
+        doc_coords_3d = coords_3d[:-1]  # All but last are documents
+
+        total_chunks = sum(len(chunks) for chunks in doc_chunks.values())
+        avg_chunks_per_doc = (
+            total_chunks / len(doc_vectors) if doc_vectors.size > 0 else 0
        )

-        # Map results to coordinates (use first chunk per document)
-        result_coords = []
-        seen_doc_ids = set()
+        logger.info(
+            f"PCA explained variance: PC1={pca.explained_variance_ratio_[0]:.3f}, "
+            f"PC2={pca.explained_variance_ratio_[1]:.3f}, "
+            f"PC3={pca.explained_variance_ratio_[2]:.3f}"
+        )
+        logger.info(
+            f"Embedding stats: documents={len(doc_vectors)}, "
+            f"total_chunks={total_chunks}, avg_chunks_per_doc={avg_chunks_per_doc:.1f}, "
+            f"query_dim={len(query_embedding)}, doc_vector_dim={doc_vectors.shape[1] if doc_vectors.size > 0 else 0}"
+        )

-        for point, coord in zip(points, coords_2d):
-            if point.payload:
-                doc_id = int(point.payload.get("doc_id", 0))
-                if doc_id not in seen_doc_ids and doc_id in doc_ids:
-                    seen_doc_ids.add(doc_id)
-                    result_coords.append(coord.tolist())
+        # Coordinates already match search_results order (1:1 mapping)
+        result_coords = [[round(float(x), 2) for x in coord] for coord in doc_coords_3d]

        # Build response
        response_results = [
@@ -338,26 +445,30 @@ async def vector_visualization_search(request: Request) -> JSONResponse:
            f"Viz search timing: total={total_duration * 1000:.1f}ms, "
            f"search={search_duration * 1000:.1f}ms ({search_duration / total_duration * 100:.1f}%), "
            f"vector_fetch={vector_fetch_duration * 1000:.1f}ms ({vector_fetch_duration / total_duration * 100:.1f}%), "
+            f"query_embed={query_embed_duration * 1000:.1f}ms ({query_embed_duration / total_duration * 100:.1f}%), "
            f"pca={pca_duration * 1000:.1f}ms ({pca_duration / total_duration * 100:.1f}%), "
-            f"results={len(search_results)}, vectors={len(vectors)}"
+            f"results={len(search_results)}, doc_vectors={len(doc_vectors)}"
        )

        return JSONResponse(
            {
                "success": True,
                "results": response_results,
-                "coordinates_2d": result_coords[: len(search_results)],
+                "coordinates_3d": result_coords[: len(search_results)],
+                "query_coords": query_coords_3d,
                "pca_variance": {
                    "pc1": float(pca.explained_variance_ratio_[0]),
                    "pc2": float(pca.explained_variance_ratio_[1]),
+                    "pc3": float(pca.explained_variance_ratio_[2]),
                },
                "timing": {
                    "total_ms": round(total_duration * 1000, 2),
                    "search_ms": round(search_duration * 1000, 2),
                    "vector_fetch_ms": round(vector_fetch_duration * 1000, 2),
+                    "query_embed_ms": round(query_embed_duration * 1000, 2),
                    "pca_ms": round(pca_duration * 1000, 2),
                    "num_results": len(search_results),
-                    "num_vectors": len(vectors),
+                    "num_doc_vectors": len(doc_vectors),
                },
            }
        )
@@ -181,8 +181,8 @@ class Settings:
    ollama_verify_ssl: bool = True

    # Document chunking settings (for vector embeddings)
-    document_chunk_size: int = 512  # Words per chunk
-    document_chunk_overlap: int = 50  # Overlapping words between chunks
+    document_chunk_size: int = 2048  # Characters per chunk
+    document_chunk_overlap: int = 200  # Overlapping characters between chunks

    # Observability settings
    metrics_enabled: bool = True
@@ -227,10 +227,10 @@ class Settings:
                f"Overlap should be 10-20% of chunk size for optimal results."
            )

-        if self.document_chunk_size < 100:
+        if self.document_chunk_size < 512:
            logger.warning(
-                f"DOCUMENT_CHUNK_SIZE is set to {self.document_chunk_size} words, which is quite small. "
-                f"Smaller chunks may lose context. Consider using at least 256 words."
+                f"DOCUMENT_CHUNK_SIZE is set to {self.document_chunk_size} characters, which is quite small. "
+                f"Smaller chunks may lose context. Consider using at least 1024 characters."
            )

        if self.document_chunk_overlap < 0:
@@ -335,8 +335,8 @@ def get_settings() -> Settings:
        ollama_embedding_model=os.getenv("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text"),
        ollama_verify_ssl=os.getenv("OLLAMA_VERIFY_SSL", "true").lower() == "true",
        # Document chunking settings
-        document_chunk_size=int(os.getenv("DOCUMENT_CHUNK_SIZE", "512")),
-        document_chunk_overlap=int(os.getenv("DOCUMENT_CHUNK_OVERLAP", "50")),
+        document_chunk_size=int(os.getenv("DOCUMENT_CHUNK_SIZE", "2048")),
+        document_chunk_overlap=int(os.getenv("DOCUMENT_CHUNK_OVERLAP", "200")),
        # Observability settings
        metrics_enabled=os.getenv("METRICS_ENABLED", "true").lower() == "true",
        metrics_port=int(os.getenv("METRICS_PORT", "9090")),
@@ -1,9 +1,10 @@
-"""Document chunking for large texts."""
+"""Document chunking for large texts using LangChain text splitters."""

 import logging
-import re
 from dataclasses import dataclass

+from langchain_text_splitters import RecursiveCharacterTextSplitter
+
 logger = logging.getLogger(__name__)


@@ -17,25 +18,47 @@ class ChunkWithPosition:


 class DocumentChunker:
-    """Chunk large documents for optimal embedding."""
+    """Chunk large documents for optimal embedding using LangChain text splitters.

-    def __init__(self, chunk_size: int = 512, overlap: int = 50):
+    Uses RecursiveCharacterTextSplitter which preserves semantic boundaries
+    by splitting on sentence and paragraph boundaries before resorting to
+    character-level splitting.
+    """
+
+    def __init__(self, chunk_size: int = 2048, overlap: int = 200):
        """
        Initialize document chunker.

        Args:
-            chunk_size: Number of words per chunk (default: 512)
-            overlap: Number of overlapping words between chunks (default: 50)
+            chunk_size: Number of characters per chunk (default: 2048)
+            overlap: Number of overlapping characters between chunks (default: 200)
        """
        self.chunk_size = chunk_size
        self.overlap = overlap

+        # Initialize LangChain RecursiveCharacterTextSplitter
+        # Uses hierarchical splitting to preserve semantic boundaries:
+        # - Paragraphs (\n\n)
+        # - Sentences (. ! ?)
+        # - Words (spaces)
+        # - Characters (last resort)
+        # This prevents mid-sentence splitting while maintaining semantic coherence
+        self.splitter = RecursiveCharacterTextSplitter(
+            chunk_size=chunk_size,
+            chunk_overlap=overlap,
+            add_start_index=True,  # Enable position tracking
+            strip_whitespace=True,
+        )
+
    def chunk_text(self, content: str) -> list[ChunkWithPosition]:
        """
        Split text into overlapping chunks with position tracking.

-        Uses simple word-based chunking with configurable overlap to preserve
-        context across chunk boundaries. Tracks character positions for each chunk.
+        Uses LangChain's RecursiveCharacterTextSplitter to create chunks that
+        preserve semantic boundaries by splitting at paragraphs and sentences
+        before resorting to word or character-level splitting. This ensures
+        sentences are kept intact. Preserves character positions for each chunk
+        to enable precise document retrieval.

        Args:
            content: Text content to chunk
@@ -43,53 +66,25 @@ class DocumentChunker:
        Returns:
            List of chunks with their character positions in the original content
        """
-        # Use regex to find all words and their positions
-        # This preserves the original spacing and allows accurate position tracking
-        word_pattern = re.compile(r"\S+")
-        word_matches = list(word_pattern.finditer(content))
+        # Handle empty content - return single empty chunk for backward compatibility
+        if not content:
+            return [ChunkWithPosition(text="", start_offset=0, end_offset=0)]

-        if len(word_matches) <= self.chunk_size:
-            # Single chunk - use entire content
-            return [
-                ChunkWithPosition(text=content, start_offset=0, end_offset=len(content))
-            ]
+        # Use LangChain to create documents with position tracking
+        docs = self.splitter.create_documents([content])

-        chunks = []
-        start_idx = 0
-
-        while start_idx < len(word_matches):
-            end_idx = min(start_idx + self.chunk_size, len(word_matches))
-
-            # Get the first and last word positions
-            first_word = word_matches[start_idx]
-            last_word = word_matches[end_idx - 1]
-
-            # Extract chunk using character positions
-            start_offset = first_word.start()
-            end_offset = last_word.end()
-            chunk_text = content[start_offset:end_offset]
-
-            chunks.append(
-                ChunkWithPosition(
-                    text=chunk_text, start_offset=start_offset, end_offset=end_offset
-                )
+        # Convert LangChain Documents to ChunkWithPosition objects
+        chunks = [
+            ChunkWithPosition(
+                text=doc.page_content,
+                start_offset=doc.metadata.get("start_index", 0),
+                end_offset=doc.metadata.get("start_index", 0) + len(doc.page_content),
            )
-
-            # If we've reached the end, break
-            if end_idx >= len(word_matches):
-                break
-
-            # Move to next chunk with overlap
-            next_start_idx = end_idx - self.overlap
-
-            # Safety check: ensure we're making forward progress
-            # If we're not advancing (overlap >= chunk processed), break to prevent infinite loop
-            if next_start_idx <= start_idx:
-                break
-
-            start_idx = next_start_idx
+            for doc in docs
+        ]

        logger.debug(
-            f"Chunked document into {len(chunks)} chunks ({len(word_matches)} words)"
+            f"Chunked document into {len(chunks)} chunks "
+            f"(chunk_size={self.chunk_size}, overlap={self.overlap})"
        )
        return chunks
@@ -1,6 +1,6 @@
 [project]
 name = "nextcloud-mcp-server"
-version = "0.40.0"
+version = "0.44.0"
 description = "Model Context Protocol (MCP) server for Nextcloud integration - enables AI assistants to interact with Nextcloud data"
 authors = [
    {name = "Chris Coutinho", email = "chris@coutinho.io"}
@@ -22,7 +22,7 @@ dependencies = [
    "aiosqlite>=0.20.0", # Async SQLite for refresh token storage
    "authlib>=1.6.5",
    "qdrant-client>=1.7.0",
-    "fastembed>=0.4.2", # BM25 sparse vector embeddings for hybrid search
+    "fastembed>=0.7.3", # BM25 sparse vector embeddings for hybrid search
    "anthropic>=0.42.0", # For RAG evaluation with Anthropic LLMs
    "boto3>=1.35.0", # For Amazon Bedrock provider (optional)
    # Observability dependencies
@@ -35,6 +35,7 @@ dependencies = [
    "opentelemetry-exporter-otlp-proto-grpc>=1.28.2", # OTLP gRPC exporter
    "python-json-logger>=3.2.0", # Structured JSON logging
    "jinja2>=3.1.6",
+    "langchain-text-splitters>=1.0.0",
 ]
 classifiers = [
    "Development Status :: 4 - Beta",
@@ -107,7 +108,7 @@ module-root = ""
 [dependency-groups]
 dev = [
    "commitizen>=4.8.2",
-    "datasets>=3.3.0",  # For BeIR nfcorpus dataset loading
+    "datasets>=3.3.0", # For BeIR nfcorpus dataset loading
    "ipython>=9.2.0",
    "playwright>=1.49.1",
    "pytest>=8.3.5",
@@ -159,8 +159,8 @@ class TestChunkConfigValidation:
    def test_default_chunk_settings(self):
        """Test default chunk size and overlap values."""
        settings = Settings()
-        assert settings.document_chunk_size == 512
-        assert settings.document_chunk_overlap == 50
+        assert settings.document_chunk_size == 2048
+        assert settings.document_chunk_overlap == 200

    def test_valid_chunk_settings(self):
        """Test valid chunk size and overlap configuration."""
@@ -205,7 +205,7 @@ class TestChunkConfigValidation:
            )

    def test_small_chunk_size_warning(self, caplog):
-        """Test that chunk size < 100 triggers warning."""
+        """Test that chunk size < 512 triggers warning."""
        import logging

        caplog.set_level(logging.WARNING, logger="nextcloud_mcp_server.config")
@@ -214,19 +214,19 @@ class TestChunkConfigValidation:
            document_chunk_overlap=10,
        )
        assert (
-            "DOCUMENT_CHUNK_SIZE is set to 64 words, which is quite small"
+            "DOCUMENT_CHUNK_SIZE is set to 64 characters, which is quite small"
            in caplog.text
        )
-        assert "Consider using at least 256 words" in caplog.text
+        assert "Consider using at least 1024 characters" in caplog.text

    def test_reasonable_chunk_size_no_warning(self, caplog):
-        """Test that chunk size >= 100 doesn't trigger warning."""
+        """Test that chunk size >= 512 doesn't trigger warning."""
        import logging

        caplog.set_level(logging.WARNING, logger="nextcloud_mcp_server.config")
        Settings(
-            document_chunk_size=256,
-            document_chunk_overlap=25,
+            document_chunk_size=1024,
+            document_chunk_overlap=100,
        )
        assert "DOCUMENT_CHUNK_SIZE" not in caplog.text

@@ -1,4 +1,4 @@
-"""Unit tests for DocumentChunker with position tracking."""
+"""Unit tests for DocumentChunker with LangChain text splitters."""

 from nextcloud_mcp_server.vector.document_chunker import (
    ChunkWithPosition,
@@ -11,7 +11,7 @@ class TestDocumentChunkerPositions:

    def test_single_chunk_simple_text(self):
        """Test that single-chunk documents return correct positions."""
-        chunker = DocumentChunker(chunk_size=512, overlap=50)
+        chunker = DocumentChunker(chunk_size=2048, overlap=200)
        content = "This is a short document."

        chunks = chunker.chunk_text(content)
@@ -24,15 +24,20 @@ class TestDocumentChunkerPositions:

    def test_multiple_chunks_positions(self):
        """Test that multi-chunk documents have correct positions."""
-        chunker = DocumentChunker(chunk_size=10, overlap=2)  # Small chunks for testing
-        # Create content with exactly 30 words
-        words = [f"word{i:02d}" for i in range(30)]
-        content = " ".join(words)
+        # Use small chunk size to force multiple chunks
+        chunker = DocumentChunker(chunk_size=50, overlap=10)
+        # Create content longer than chunk size
+        content = (
+            "This is the first sentence with some important content. "
+            "This is the second sentence with more details. "
+            "This is the third sentence continuing the discussion. "
+            "This is the fourth sentence adding more context."
+        )

        chunks = chunker.chunk_text(content)

-        # Verify we got multiple chunks (30 words, 10 per chunk, 2 overlap = 4 chunks)
-        assert len(chunks) == 4
+        # Verify we got multiple chunks
+        assert len(chunks) > 1

        # Verify all chunks are ChunkWithPosition
        for chunk in chunks:
@@ -44,10 +49,12 @@ class TestDocumentChunkerPositions:
        # Verify last chunk ends at content length
        assert chunks[-1].end_offset == len(content)

-        # Verify chunks are contiguous or overlap (no gaps)
+        # Verify chunks are contiguous or overlap (minimal gaps allowed)
        for i in range(len(chunks) - 1):
-            # Next chunk should start at or before current chunk ends
-            assert chunks[i + 1].start_offset <= chunks[i].end_offset
+            # Next chunk should start at or near current chunk end
+            # Allow small gaps (1-2 chars) for whitespace/punctuation at boundaries
+            gap = chunks[i + 1].start_offset - chunks[i].end_offset
+            assert gap <= 2, f"Gap too large between chunks: {gap} characters"

        # Verify we can reconstruct the content using positions
        for chunk in chunks:
@@ -56,8 +63,8 @@ class TestDocumentChunkerPositions:

    def test_chunk_positions_with_whitespace(self):
        """Test position tracking with various whitespace."""
-        chunker = DocumentChunker(chunk_size=5, overlap=1)
-        content = "word1  word2\n\nword3\tword4    word5 word6"
+        chunker = DocumentChunker(chunk_size=30, overlap=5)
+        content = "First sentence here.  Second sentence.\n\nThird sentence.\tFourth sentence."

        chunks = chunker.chunk_text(content)

@@ -65,14 +72,12 @@ class TestDocumentChunkerPositions:
        for chunk in chunks:
            extracted = content[chunk.start_offset : chunk.end_offset]
            assert extracted == chunk.text
-            # Verify no leading/trailing whitespace unless in original
-            if chunk != chunks[0] and chunk != chunks[-1]:
-                # Middle chunks should be extracted correctly
-                assert len(chunk.text.strip()) > 0
+            # LangChain strips whitespace by default
+            assert len(chunk.text.strip()) > 0

    def test_empty_content(self):
        """Test that empty content returns empty chunk."""
-        chunker = DocumentChunker(chunk_size=512, overlap=50)
+        chunker = DocumentChunker(chunk_size=2048, overlap=200)
        content = ""

        chunks = chunker.chunk_text(content)
@@ -84,27 +89,35 @@ class TestDocumentChunkerPositions:

    def test_chunk_overlap_positions(self):
        """Test that overlapping chunks have correct positions."""
-        chunker = DocumentChunker(chunk_size=10, overlap=3)
-        words = [f"word{i:02d}" for i in range(25)]
-        content = " ".join(words)
+        chunker = DocumentChunker(chunk_size=50, overlap=15)
+        content = (
+            "This is sentence one with content. "
+            "This is sentence two with more. "
+            "This is sentence three continuing. "
+            "This is sentence four adding details."
+        )

        chunks = chunker.chunk_text(content)

-        # Verify overlap exists
-        for i in range(len(chunks) - 1):
-            current_chunk = chunks[i]
-            next_chunk = chunks[i + 1]
+        # Verify overlap exists if we have multiple chunks
+        if len(chunks) > 1:
+            for i in range(len(chunks) - 1):
+                current_chunk = chunks[i]
+                next_chunk = chunks[i + 1]

-            # Next chunk should start before current ends (overlap)
-            # This happens because we move back by overlap words
-            # The actual character overlap depends on word lengths
-            assert next_chunk.start_offset >= 0
-            assert current_chunk.end_offset <= len(content)
+                # Verify positions are valid
+                assert next_chunk.start_offset >= 0
+                assert current_chunk.end_offset <= len(content)
+
+                # With overlap, next chunk may start before current ends
+                assert next_chunk.start_offset <= current_chunk.end_offset

    def test_unicode_content_positions(self):
        """Test position tracking with Unicode characters."""
-        chunker = DocumentChunker(chunk_size=10, overlap=2)
-        content = "Hello 世界 こんにちは мир Привет שלום مرحبا 你好"
+        chunker = DocumentChunker(chunk_size=50, overlap=10)
+        content = (
+            "Hello 世界. こんにちは there. мир Привет world. שלום مرحبا 你好 friend."
+        )

        chunks = chunker.chunk_text(content)

@@ -118,26 +131,9 @@ class TestDocumentChunkerPositions:
            assert chunks[0].start_offset == 0
            assert chunks[0].end_offset == len(content)

-    def test_single_word_chunks(self):
-        """Test position tracking with single-word chunks."""
-        chunker = DocumentChunker(chunk_size=1, overlap=0)
-        content = "one two three"
-
-        chunks = chunker.chunk_text(content)
-
-        assert len(chunks) == 3
-        assert chunks[0].text == "one"
-        assert chunks[1].text == "two"
-        assert chunks[2].text == "three"
-
-        # Verify positions
-        assert content[chunks[0].start_offset : chunks[0].end_offset] == "one"
-        assert content[chunks[1].start_offset : chunks[1].end_offset] == "two"
-        assert content[chunks[2].start_offset : chunks[2].end_offset] == "three"
-
    def test_realistic_note_content(self):
        """Test with realistic note content similar to Nextcloud Notes."""
-        chunker = DocumentChunker(chunk_size=50, overlap=10)
+        chunker = DocumentChunker(chunk_size=200, overlap=50)
        content = """My Project Notes

 This is a note about my project. It contains several paragraphs of text
@@ -172,19 +168,121 @@ which builds trust in the RAG system."""
            assert chunk.end_offset <= len(content)
            assert chunk.start_offset < chunk.end_offset

-    def test_chunk_boundaries(self):
-        """Test that chunk boundaries are word-aligned."""
-        chunker = DocumentChunker(chunk_size=10, overlap=2)
-        words = [f"word{i:02d}" for i in range(30)]
-        content = " ".join(words)
+    def test_semantic_boundary_preservation(self):
+        """Test that LangChain creates semantically coherent chunks."""
+        chunker = DocumentChunker(chunk_size=100, overlap=20)
+        content = (
+            "First sentence is here. "
+            "Second sentence follows. "
+            "Third sentence continues. "
+            "Fourth sentence ends."
+        )

        chunks = chunker.chunk_text(content)

+        # Verify all chunks are extractable using their positions
        for chunk in chunks:
-            # Verify chunk text starts and ends with word characters (no split words)
-            # Unless it's the full content
-            if len(chunks) > 1:
-                # Each chunk should start with a word (not whitespace)
-                assert chunk.text[0].strip() != ""
-                # Each chunk should end with a word (not whitespace)
-                assert chunk.text[-1].strip() != ""
+            extracted = content[chunk.start_offset : chunk.end_offset]
+            assert extracted == chunk.text
+
+            # Verify chunk text is meaningful (not empty or just whitespace)
+            assert len(chunk.text.strip()) > 0
+
+            # Verify positions are valid
+            assert chunk.start_offset >= 0
+            assert chunk.end_offset <= len(content)
+            assert chunk.start_offset < chunk.end_offset
+
+    def test_paragraph_boundary_preservation(self):
+        """Test that LangChain preserves paragraph boundaries."""
+        chunker = DocumentChunker(chunk_size=80, overlap=15)
+        content = """First paragraph here.
+
+Second paragraph here.
+
+Third paragraph here.
+
+Fourth paragraph here."""
+
+        chunks = chunker.chunk_text(content)
+
+        # LangChain should prefer splitting at paragraph boundaries (\n\n)
+        # Verify we got multiple chunks
+        assert len(chunks) >= 1
+
+        # Verify all positions work correctly
+        for chunk in chunks:
+            extracted = content[chunk.start_offset : chunk.end_offset]
+            assert extracted == chunk.text
+
+    def test_default_parameters(self):
+        """Test that default parameters work correctly."""
+        chunker = DocumentChunker()  # Use defaults: 2048 chars, 200 overlap
+
+        # Create content that's smaller than default chunk size
+        content = (
+            "This is a short note with a few sentences. It should fit in one chunk."
+        )
+
+        chunks = chunker.chunk_text(content)
+
+        assert len(chunks) == 1
+        assert chunks[0].text == content
+        assert chunks[0].start_offset == 0
+        assert chunks[0].end_offset == len(content)
+
+    def test_large_document_chunking(self):
+        """Test chunking of a large document."""
+        chunker = DocumentChunker(chunk_size=100, overlap=20)
+
+        # Create a large document with multiple paragraphs
+        paragraphs = [
+            f"This is paragraph {i} with some meaningful content about topic {i}. "
+            f"It contains multiple sentences to make it realistic. "
+            f"The content should be properly chunked."
+            for i in range(10)
+        ]
+        content = "\n\n".join(paragraphs)
+
+        chunks = chunker.chunk_text(content)
+
+        # Should create multiple chunks
+        assert len(chunks) > 1
+
+        # Verify all chunks are valid
+        for chunk in chunks:
+            assert isinstance(chunk, ChunkWithPosition)
+            assert len(chunk.text) > 0
+            # Verify extraction
+            extracted = content[chunk.start_offset : chunk.end_offset]
+            assert extracted == chunk.text
+
+        # Verify first and last positions
+        assert chunks[0].start_offset == 0
+        assert chunks[-1].end_offset == len(content)
+
+    def test_position_tracking_with_overlap(self):
+        """Test that position tracking works correctly with overlap."""
+        chunker = DocumentChunker(chunk_size=50, overlap=15)
+        content = "A" * 25 + ". " + "B" * 25 + ". " + "C" * 25 + ". " + "D" * 25 + "."
+
+        chunks = chunker.chunk_text(content)
+
+        if len(chunks) > 1:
+            # Verify overlap creates correct positions
+            for i in range(len(chunks) - 1):
+                # Each chunk should be extractable
+                assert (
+                    content[chunks[i].start_offset : chunks[i].end_offset]
+                    == chunks[i].text
+                )
+
+                # Next chunk should overlap with current
+                # (start before current ends)
+                if chunks[i + 1].start_offset < chunks[i].end_offset:
+                    # There is overlap - verify content matches
+                    overlap_start = chunks[i + 1].start_offset
+                    overlap_end = chunks[i].end_offset
+                    overlap_text = content[overlap_start:overlap_end]
+                    assert overlap_text in chunks[i].text
+                    assert overlap_text in chunks[i + 1].text
@@ -2,7 +2,8 @@ version = 1
 revision = 3
 requires-python = ">=3.11"
 resolution-markers = [
-    "python_full_version >= '3.13'",
+    "python_full_version >= '3.14'",
+    "python_full_version == '3.13.*'",
    "python_full_version == '3.12.*'",
    "python_full_version < '3.12'",
 ]
@@ -1333,6 +1334,27 @@ wheels = [
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 ]

+[[package]]
+name = "jsonpatch"
+version = "1.33"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jsonpointer" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/42/78/18813351fe5d63acad16aec57f94ec2b70a09e53ca98145589e185423873/jsonpatch-1.33.tar.gz", hash = "sha256:9fcd4009c41e6d12348b4a0ff2563ba56a2923a7dfee731d004e212e1ee5030c", size = 21699, upload-time = "2023-06-26T12:07:29.144Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/73/07/02e16ed01e04a374e644b575638ec7987ae846d25ad97bcc9945a3ee4b0e/jsonpatch-1.33-py2.py3-none-any.whl", hash = "sha256:0ae28c0cd062bbd8b8ecc26d7d164fbbea9652a1a3693f3b956c1eae5145dade", size = 12898, upload-time = "2023-06-16T21:01:28.466Z" },
+]
+
+[[package]]
+name = "jsonpointer"
+version = "3.0.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/6a/0a/eebeb1fa92507ea94016a2a790b93c2ae41a7e18778f85471dc54475ed25/jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef", size = 9114, upload-time = "2024-06-10T19:24:42.462Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942", size = 7595, upload-time = "2024-06-10T19:24:40.698Z" },
+]
+
 [[package]]
 name = "jsonschema"
 version = "4.25.1"
@@ -1360,6 +1382,54 @@ wheels = [
    { url = "https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl", hash = "sha256:98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe", size = 18437, upload-time = "2025-09-08T01:34:57.871Z" },
 ]

+[[package]]
+name = "langchain-core"
+version = "1.0.5"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jsonpatch" },
+    { name = "langsmith" },
+    { name = "packaging" },
+    { name = "pydantic" },
+    { name = "pyyaml" },
+    { name = "tenacity" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/d9/61/c356e19525a210baf960968dbfb03ee38a05e05ddb41efeb32abfcb4e360/langchain_core-1.0.5.tar.gz", hash = "sha256:7ecbad9a60dde626252733a9c18c7377f4468cfe00465ffa99f5e9c6cb9b82d2", size = 778259, upload-time = "2025-11-14T16:59:27.277Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/6e/ee/aaf2343a35080154c82ceb110e03dd00f15459bc72e518df51724cbc41a9/langchain_core-1.0.5-py3-none-any.whl", hash = "sha256:d24c0cf12cfcd96dd4bd479aa91425f3a6652226cd824228ae422a195067b74e", size = 471506, upload-time = "2025-11-14T16:59:25.629Z" },
+]
+
+[[package]]
+name = "langchain-text-splitters"
+version = "1.0.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "langchain-core" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/fa/2e/c833dcc379c1c086453708ef5eef7d4d1f808559ca4458bd6569d5d83ad7/langchain_text_splitters-1.0.0.tar.gz", hash = "sha256:d8580a20ad7ed10b432feb273e5758b2cc0902d094919629cec0e1ad691a6744", size = 264257, upload-time = "2025-10-17T14:33:41.743Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/1e/97/d362353ab04f865af6f81d4d46e7aa428734aa032de0017934b771fc34b7/langchain_text_splitters-1.0.0-py3-none-any.whl", hash = "sha256:f00c8219d3468f2c5bd951b708b6a7dd9bc3c62d0cfb83124c377f7170f33b2e", size = 33851, upload-time = "2025-10-17T14:33:40.46Z" },
+]
+
+[[package]]
+name = "langsmith"
+version = "0.4.43"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "httpx" },
+    { name = "orjson", marker = "platform_python_implementation != 'PyPy'" },
+    { name = "packaging" },
+    { name = "pydantic" },
+    { name = "requests" },
+    { name = "requests-toolbelt" },
+    { name = "zstandard" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/ad/b4/073e3fd494f7853fd4e59f5ae56c49f672e081e65f17ef363224e60530ab/langsmith-0.4.43.tar.gz", hash = "sha256:75c2468ab740438adfb32af8595ad8837c3af2bd1cdaf057d534182c5a07407a", size = 984142, upload-time = "2025-11-15T00:32:12.454Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/f1/5c/521a3d8295e2e7caea67032e65554866293b6dc8e934bd86be8cc1f7b955/langsmith-0.4.43-py3-none-any.whl", hash = "sha256:c97846a0b15061bc15844aac32fd1ce4a8e50983905f80a0d6079bb41b112ae3", size = 410232, upload-time = "2025-11-15T00:32:10.557Z" },
+]
+
 [[package]]
 name = "loguru"
 version = "0.7.3"
@@ -1857,7 +1927,7 @@ wheels = [

 [[package]]
 name = "nextcloud-mcp-server"
-version = "0.40.0"
+version = "0.44.0"
 source = { editable = "." }
 dependencies = [
    { name = "aiosqlite" },
@@ -1870,6 +1940,7 @@ dependencies = [
    { name = "httpx" },
    { name = "icalendar" },
    { name = "jinja2" },
+    { name = "langchain-text-splitters" },
    { name = "mcp", extra = ["cli"] },
    { name = "opentelemetry-api" },
    { name = "opentelemetry-exporter-otlp-proto-grpc" },
@@ -1910,10 +1981,11 @@ requires-dist = [
    { name = "boto3", specifier = ">=1.35.0" },
    { name = "caldav", git = "https://github.com/cbcoutinho/caldav?branch=feature%2Fhttpx" },
    { name = "click", specifier = ">=8.1.8" },
-    { name = "fastembed", specifier = ">=0.4.2" },
+    { name = "fastembed", specifier = ">=0.7.3" },
    { name = "httpx", specifier = ">=0.28.1,<0.29.0" },
    { name = "icalendar", specifier = ">=6.0.0,<7.0.0" },
    { name = "jinja2", specifier = ">=3.1.6" },
+    { name = "langchain-text-splitters", specifier = ">=1.0.0" },
    { name = "mcp", extras = ["cli"], specifier = ">=1.21,<1.22" },
    { name = "opentelemetry-api", specifier = ">=1.28.2" },
    { name = "opentelemetry-exporter-otlp-proto-grpc", specifier = ">=1.28.2" },
@@ -2210,6 +2282,74 @@ wheels = [
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 ]

+[[package]]
+name = "orjson"
+version = "3.11.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/c6/fe/ed708782d6709cc60eb4c2d8a361a440661f74134675c72990f2c48c785f/orjson-3.11.4.tar.gz", hash = "sha256:39485f4ab4c9b30a3943cfe99e1a213c4776fb69e8abd68f66b83d5a0b0fdc6d", size = 5945188, upload-time = "2025-10-24T15:50:38.027Z" }
+wheels = [
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Author	SHA1	Message	Date
github-actions[bot]	bf11f16e2f	bump: version 0.43.0 → 0.44.0	2025-11-19 22:43:03 +00:00
Chris Coutinho	bf05ff8d6e	Merge pull request #329 from cbcoutinho/feature/nextcloud-ui-improvements feat: Redesign UI and improve vector visualization	2025-11-19 23:42:32 +01:00
Chris Coutinho	c4ce28f05d	fix: Improve 3D plot rendering with explicit dimensions and window resize support - Get container dimensions before creating Plotly layout to render at correct size immediately - Add init() method with window resize listener for responsive plot sizing - Remove post-render resize call (no longer needed with explicit dimensions) - Improve colorbar positioning and scene domain configuration This eliminates the visual "jump" during initial render and ensures the plot resizes smoothly when the browser window changes size. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>	2025-11-19 19:43:20 +01:00
Chris Coutinho	9b2a06964b	Merge pull request #331 from cbcoutinho/renovate/commitizen-tools-commitizen-action-0.x chore(deps): update commitizen-tools/commitizen-action action to v0.26.0	2025-11-19 14:42:06 +01:00
Chris Coutinho	c126c3ec03	fix: Preserve 3D plot camera and improve documentation This commit addresses PR feedback and fixes plot camera behavior. ## JavaScript Fix - Camera Preservation - Changed plot update strategy from recreating layout to using Plotly.restyle() - Query point visibility now toggles via restyle() which only modifies trace visibility - Camera position/zoom naturally preserved since layout remains untouched - Resolves jumpy plot behavior when toggling "Show Query Point" checkbox Related: nextcloud_mcp_server/auth/static/vector-viz.js:58-73 ## Documentation Improvements - Condensed vector-sync-ui.md from 316 to 94 lines (~70% reduction) - Removed redundant FAQ section (content merged into main sections) - Simplified use cases from 4 detailed sections to 3 focused paragraphs - Streamlined troubleshooting to 3 common issues - Merged technical details into overview section - Retained all essential information while improving readability ## Screenshot Updates Removed old/outdated images (5 files): - rag-workflow-bidirectional-final.png - rag-workflow-prominent-llm.png - rag-workflow-simple-final.png - vector-viz-interface.png - welcome-page.png Replaced with current screenshots (3 files): - vector-viz-document-types-2col.png - Now shows plot + results - vector-viz-chunk-context.png - Centered content view - vector-viz-results.png - Updated results list 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>	2025-11-19 14:10:53 +01:00
Chris Coutinho	9bd02d7ef7	fix: Preserve 3D plot camera position and fix CSS loading Two fixes for the vector visualization page: 1. CSS Loading Fix: Moved CSS <link> from vector_viz.html fragment to user_info.html <head> block. HTMX fragments don't process <link> tags in <head>, causing unstyled page. Now CSS loads correctly. 2. Camera Preservation: Modified renderPlot() to preserve camera position when toggling query point visibility. Previously, toggling the "Show Query Point" checkbox would reset zoom/rotation to default. Now reads existing camera settings from plot before updating. Related: nextcloud_mcp_server/auth/static/vector-viz.js:123-130 Related: nextcloud_mcp_server/auth/templates/user_info.html:12 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>	2025-11-19 13:51:08 +01:00
renovate-bot-cbcoutinho[bot]	e38a830f02	chore(deps): update commitizen-tools/commitizen-action action to v0.26.0	2025-11-19 11:07:37 +00:00
Chris Coutinho	18b753c3c7	Merge pull request #330 from cbcoutinho/renovate/docker.io-library-nextcloud-32.0.1 chore(deps): update docker.io/library/nextcloud:32.0.1 docker digest to d572839	2025-11-19 09:57:27 +01:00
renovate-bot-cbcoutinho[bot]	b0735bae85	chore(deps): update docker.io/library/nextcloud:32.0.1 docker digest to d572839	2025-11-19 05:08:00 +00:00
Chris Coutinho	53689d076b	feat: Improve vector visualization with static assets and fixes - Extract CSS and JavaScript into separate static files - Created nextcloud_mcp_server/auth/static/vector-viz.css - Created nextcloud_mcp_server/auth/static/vector-viz.js - Updated templates to reference external assets - Fix vector visualization issues: - Normalize vectors before PCA to match Qdrant's cosine distance - Add zero-norm and NaN detection/handling for large datasets - Enable responsive Plotly sizing (autosize + responsive config) - Widen plot area to full viewport width with minimized margins - Improve visualization accuracy: - Query point now positioned correctly relative to documents - Handles 200+ points without JSON serialization errors - Full-width plot maximizes screen space utilization 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>	2025-11-19 04:10:44 +01:00
Chris Coutinho	0f7d6c0e33	Merge pull request #327 from cbcoutinho/renovate/docker.io-library-python-3.12-slim-trixie chore(deps): update docker.io/library/python:3.12-slim-trixie docker digest to 2e683fc	2025-11-19 01:53:05 +01:00
Chris Coutinho	16701fdb72	Merge pull request #328 from cbcoutinho/renovate/docker.io-library-redis-alpine chore(deps): update docker.io/library/redis:alpine docker digest to 5013e94	2025-11-19 01:52:57 +01:00
Chris Coutinho	9db20a4d01	feat: Redesign UI to match Nextcloud ecosystem aesthetic This commit updates the web interface to better align with Nextcloud's design system and improve the Vector Viz layout. Changes: - Replace emoji icons with Material Design SVG icons for better consistency with Nextcloud apps - Simplify navigation styling with minimal padding and subtle active states (250px width) - Update CSS variables to match Nextcloud design system - Restructure Vector Viz from two-column to single-column vertical layout for better plot visibility - Move search controls to compact horizontal grid at top - Make navigation toggle always visible (not just on mobile) - Fix plot container sizing with overflow:visible to prevent colorbar clipping - Remove heavy shadows and custom card styling for cleaner aesthetic - Add error and success page templates with consistent styling Technical details: - Preserve Alpine.js for reactive functionality - Use CSS Grid for responsive horizontal controls layout - Add smooth transitions for navigation collapse/expand - Maintain HTMX for dynamic content loading 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>	2025-11-19 00:45:19 +01:00
renovate-bot-cbcoutinho[bot]	7ddf8370e6	chore(deps): update docker.io/library/redis:alpine docker digest to 5013e94	2025-11-18 23:10:41 +00:00
renovate-bot-cbcoutinho[bot]	98dff98e9c	chore(deps): update docker.io/library/python:3.12-slim-trixie docker digest to 2e683fc	2025-11-18 23:10:36 +00:00
Chris Coutinho	73e8012707	Merge pull request #325 from cbcoutinho/renovate/docker.io-library-python-3.12-slim-trixie chore(deps): update docker.io/library/python:3.12-slim-trixie docker digest to 2bbc83f	2025-11-18 14:06:14 +01:00
Chris Coutinho	c2fd87a5d3	Merge pull request #324 from cbcoutinho/renovate/docker.io-library-nextcloud-32.0.1 chore(deps): update docker.io/library/nextcloud:32.0.1 docker digest to f6232ea	2025-11-18 14:03:38 +01:00
github-actions[bot]	441d94301e	bump: version 0.42.0 → 0.43.0	2025-11-18 12:56:15 +00:00
Chris Coutinho	b488d69939	Merge pull request #326 from cbcoutinho/feature/notes2 feat: Replace custom document chunker with LangChain MarkdownTextSplitter	2025-11-18 13:55:34 +01:00
Chris Coutinho	eec923eff5	feat: Replace custom document chunker with LangChain MarkdownTextSplitter Migrates from custom word-based chunking to LangChain's MarkdownTextSplitter for better semantic search quality. This implements the chunking portion of ADR-011. Changes: - Replace custom regex word chunker with MarkdownTextSplitter - Optimized for Markdown content (headers, code blocks, lists) - Convert from word-based (512 words) to character-based (2048 chars) chunking - Maintain backward-compatible ChunkWithPosition interface - Update configuration defaults and validation - Update all unit tests (12/12 passing) Benefits: - Respects markdown structure boundaries - Never breaks code blocks or headers mid-chunk - Preserves semantic coherence within chunks - Expected 20-30% improvement in recall quality - Industry-standard approach (used by production RAG systems) Note: Full reindex required to apply new chunking to existing documents. Current vector database still contains old word-based chunks. Related: ADR-011 (Improving Semantic Search Quality) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>	2025-11-18 12:17:23 +01:00
renovate-bot-cbcoutinho[bot]	3642faf32c	chore(deps): update docker.io/library/python:3.12-slim-trixie docker digest to 2bbc83f	2025-11-18 11:08:08 +00:00
renovate-bot-cbcoutinho[bot]	3b1cd96722	chore(deps): update docker.io/library/nextcloud:32.0.1 docker digest to f6232ea	2025-11-18 11:08:03 +00:00
Chris Coutinho	219d064459	Merge pull request #321 from cbcoutinho/renovate/pin-dependencies chore(deps): pin ghcr.io/astral-sh/uv docker tag to 29bd450	2025-11-18 00:15:32 +01:00
Chris Coutinho	d0ab8d071a	Merge pull request #322 from cbcoutinho/renovate/actions-checkout-digest chore(deps): update actions/checkout digest to 93cb6ef	2025-11-18 00:15:20 +01:00
Chris Coutinho	b792e9d9a3	Merge pull request #323 from cbcoutinho/renovate/docker.io-library-mariadb-lts chore(deps): update docker.io/library/mariadb:lts docker digest to 1cac849	2025-11-18 00:14:46 +01:00
renovate-bot-cbcoutinho[bot]	4288814ff4	chore(deps): update docker.io/library/mariadb:lts docker digest to 1cac849	2025-11-17 23:11:14 +00:00
renovate-bot-cbcoutinho[bot]	f34a1c5677	chore(deps): update actions/checkout digest to 93cb6ef	2025-11-17 23:11:10 +00:00
renovate-bot-cbcoutinho[bot]	6d48f90112	chore(deps): pin ghcr.io/astral-sh/uv docker tag to 29bd450	2025-11-17 23:11:04 +00:00
Chris Coutinho	b72aeca55f	test: Add custom notes app	2025-11-17 22:14:01 +01:00
Chris Coutinho	c1ae818b75	Merge pull request #317 from cbcoutinho/renovate/ghcr.io-astral-sh-uv-latest chore(deps): update ghcr.io/astral-sh/uv:latest docker digest to 29bd450	2025-11-17 19:40:24 +01:00
Chris Coutinho	ebca2bfc70	build: pin uv to 0.9.10, use --no-cache	2025-11-17 19:33:15 +01:00
Chris Coutinho	6dcd0bae48	Merge pull request #318 from cbcoutinho/renovate/actions-checkout-5.x chore(deps): update actions/checkout action to v5.0.1	2025-11-17 19:23:32 +01:00
Chris Coutinho	818f643dca	Merge pull request #319 from cbcoutinho/renovate/qdrant-1.x chore(deps): update helm release qdrant to v1.16.0	2025-11-17 19:23:25 +01:00
Chris Coutinho	d31b490f13	Merge pull request #320 from cbcoutinho/renovate/qdrant-qdrant-1.x chore(deps): update qdrant/qdrant docker tag to v1.16.0	2025-11-17 19:23:16 +01:00
renovate-bot-cbcoutinho[bot]	839cf159b8	chore(deps): update qdrant/qdrant docker tag to v1.16.0	2025-11-17 17:09:02 +00:00
renovate-bot-cbcoutinho[bot]	cefb438017	chore(deps): update helm release qdrant to v1.16.0	2025-11-17 17:08:54 +00:00
renovate-bot-cbcoutinho[bot]	efc78a835e	chore(deps): update actions/checkout action to v5.0.1	2025-11-17 17:08:34 +00:00
renovate-bot-cbcoutinho[bot]	fa25a1b4df	chore(deps): update ghcr.io/astral-sh/uv:latest docker digest to 29bd450	2025-11-17 17:08:28 +00:00
github-actions[bot]	8367208a03	bump: version 0.41.0 → 0.42.0	2025-11-17 07:25:33 +00:00
Chris Coutinho	52acc4bc07	Merge pull request #316 from cbcoutinho/feature/cleanup feat(viz): Add dual-score display and improve UI controls	2025-11-17 08:25:04 +01:00
github-actions[bot]	b1f7b1d30b	bump: version 0.40.0 → 0.41.0	2025-11-17 05:57:12 +00:00
Chris Coutinho	b8bdbb499f	Merge pull request #315 from cbcoutinho/feature/cleanup Feature/cleanup	2025-11-17 06:56:43 +01:00