feat: Add vector visualization pane with multi-select document types
- Add /app/vector-viz endpoint for interactive search testing - Implement server-side PCA dimensionality reduction (768-dim → 2D) - Support multi-select document type filter for cross-app search - Support all search algorithms: semantic, keyword, fuzzy, hybrid - Display 2D scatter plot of vector embeddings using Plotly - Show search results with scores and document types - Register viz routes in app.py
This commit is contained in:
Chris Coutinho
@@ -1477,6 +1477,10 @@ def get_app(transport: str = "sse", enabled_apps: list[str] | None = None):
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user_info_html,
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vector_sync_status_fragment,
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)
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from nextcloud_mcp_server.auth.viz_routes import (
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vector_visualization_html,
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vector_visualization_search,
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)
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from nextcloud_mcp_server.auth.webhook_routes import (
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disable_webhook_preset,
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enable_webhook_preset,
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@@ -1496,6 +1500,15 @@ def get_app(transport: str = "sse", enabled_apps: list[str] | None = None):
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vector_sync_status_fragment,
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methods=["GET"],
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), # /app/vector-sync/status
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# Vector visualization routes
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Route(
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"/vector-viz", vector_visualization_html, methods=["GET"]
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), # /app/vector-viz
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Route(
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"/vector-viz/search",
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vector_visualization_search,
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methods=["GET"],
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), # /app/vector-viz/search
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# Webhook management routes (admin-only)
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Route("/webhooks", webhook_management_pane, methods=["GET"]), # /app/webhooks
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Route(
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@@ -183,6 +183,21 @@ async def vector_visualization_html(request: Request) -> HTMLResponse:
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</select>
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</div>
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<div class="control-group">
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<label>Document Types (multi-select)</label>
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<select x-model="docTypes" multiple size="4" style="height: auto;">
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<option value="">All Types (cross-app search)</option>
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<option value="note">Notes</option>
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<option value="file">Files</option>
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<option value="calendar">Calendar Events</option>
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<option value="contact">Contacts</option>
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<option value="deck">Deck Cards</option>
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</select>
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<small style="color: #666; display: block; margin-top: 4px;">
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Hold Ctrl/Cmd to select multiple. Select "All Types" for cross-app search.
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</small>
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</div>
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<div class="control-group weight-controls" :class="{{ active: algorithm === 'hybrid' }}">
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<label>Hybrid Weights</label>
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<div style="margin-bottom: 8px;">
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@@ -249,6 +264,7 @@ async def vector_visualization_html(request: Request) -> HTMLResponse:
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return {{
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query: '',
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algorithm: 'hybrid',
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docTypes: [''], // Default to "All Types"
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limit: 50,
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scoreThreshold: 0.7,
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semanticWeight: 0.5,
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@@ -276,6 +292,12 @@ async def vector_visualization_html(request: Request) -> HTMLResponse:
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fuzzy_weight: this.fuzzyWeight,
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}});
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// Add doc_types parameter (filter out empty string for "All Types")
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const selectedTypes = this.docTypes.filter(t => t !== '');
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if (selectedTypes.length > 0) {{
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params.append('doc_types', selectedTypes.join(','));
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}}
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const response = await fetch(`/app/vector-viz/search?${{params}}`);
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const data = await response.json();
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@@ -371,9 +393,13 @@ async def vector_visualization_search(request: Request) -> JSONResponse:
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keyword_weight = float(request.query_params.get("keyword_weight", "0.3"))
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fuzzy_weight = float(request.query_params.get("fuzzy_weight", "0.2"))
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# Parse doc_types (comma-separated list, None = all types)
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doc_types_param = request.query_params.get("doc_types", "")
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doc_types = doc_types_param.split(",") if doc_types_param else None
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logger.info(
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f"Viz search: user={username}, query='{query}', "
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f"algorithm={algorithm}, limit={limit}"
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f"algorithm={algorithm}, limit={limit}, doc_types={doc_types}"
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)
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try:
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@@ -445,15 +471,44 @@ async def vector_visualization_search(request: Request) -> JSONResponse:
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status_code=400,
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)
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# Execute search
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search_results = await search_algo.search(
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query=query,
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user_id=username,
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limit=limit,
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doc_type="note",
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nextcloud_client=nextcloud_client,
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score_threshold=score_threshold,
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)
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# Execute search (supports cross-app when doc_types=None)
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if doc_types is None or len(doc_types) == 0:
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# Cross-app search - search all indexed types
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search_results = await search_algo.search(
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query=query,
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user_id=username,
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limit=limit,
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doc_type=None, # Search all types
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nextcloud_client=nextcloud_client,
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score_threshold=score_threshold,
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)
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elif len(doc_types) == 1:
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# Single document type
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search_results = await search_algo.search(
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query=query,
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user_id=username,
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limit=limit,
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doc_type=doc_types[0],
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nextcloud_client=nextcloud_client,
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score_threshold=score_threshold,
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)
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else:
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# Multiple document types - search each and combine
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all_results = []
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for doc_type in doc_types:
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results = await search_algo.search(
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query=query,
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user_id=username,
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limit=limit * 2, # Get extra per type
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doc_type=doc_type,
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nextcloud_client=nextcloud_client,
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score_threshold=score_threshold,
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)
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all_results.extend(results)
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# Sort by score and limit
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all_results.sort(key=lambda r: r.score, reverse=True)
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search_results = all_results[:limit]
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if not search_results:
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return JSONResponse(
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