feat(astrolabe): use proper icons and thumbnails in unified search
Improve search result display to match Nextcloud's native search providers by using mimetype-specific icons and preview thumbnails. **File Results:** - Use preview thumbnails for images/PDFs (core.Preview API) - Use mimetype-specific icon classes (icon-pdf, icon-text, icon-image, etc.) - Detect folders and use icon-folder appropriately **Other Document Types:** - Notes: icon-notes - Deck Cards: icon-deck - Calendar: icon-calendar - News: icon-rss - Contacts: icon-contacts **API Changes:** - Management API now includes mime_type in search results - SemanticSearchProvider uses IMimeTypeDetector and IPreview services This makes Astroglobe search results visually consistent with Files, Notes, and other native providers. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
Chris Coutinho
@@ -393,6 +393,231 @@ async def revoke_user_access(request: Request) -> JSONResponse:
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)
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async def unified_search(request: Request) -> JSONResponse:
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"""POST /api/v1/search - Search endpoint for Nextcloud Unified Search.
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Optimized search endpoint for the Nextcloud Unified Search provider
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and other PHP app integrations. Returns results with metadata needed
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for navigation to source documents.
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Request body:
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{
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"query": "search query",
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"algorithm": "semantic|bm25|hybrid", // default: hybrid
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"limit": 20, // max: 100
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"offset": 0, // pagination offset
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"include_pca": false, // optional PCA coordinates
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"include_chunks": true // include text snippets
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}
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Response:
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{
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"results": [{
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"id": "doc123",
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"doc_type": "note",
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"title": "Document Title",
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"excerpt": "Matching text snippet...",
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"score": 0.85,
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"path": "/path/to/file.txt", // for files
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"board_id": 1, // for deck cards
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"card_id": 42
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}],
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"total_found": 150,
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"algorithm_used": "hybrid"
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}
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Requires OAuth bearer token for user filtering.
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"""
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from nextcloud_mcp_server.config import get_settings
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settings = get_settings()
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if not settings.vector_sync_enabled:
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return JSONResponse(
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{"error": "Vector sync is disabled on this server"},
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status_code=404,
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)
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# Validate OAuth token and extract user
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try:
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user_id, _validated = await validate_token_and_get_user(request)
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except Exception as e:
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logger.warning(f"Unauthorized access to /api/v1/search: {e}")
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return JSONResponse(
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{"error": "Unauthorized", "message": str(e)},
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status_code=401,
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)
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try:
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# Parse request body
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body = await request.json()
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query = body.get("query", "")
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algorithm = body.get("algorithm", "hybrid")
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fusion = body.get("fusion", "rrf")
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score_threshold = body.get("score_threshold", 0.0)
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limit = min(body.get("limit", 20), 100) # Enforce max limit
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offset = body.get("offset", 0)
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include_pca = body.get("include_pca", False)
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include_chunks = body.get("include_chunks", True)
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doc_types = body.get("doc_types") # Optional filter
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if not query:
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return JSONResponse({"results": [], "total_found": 0})
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# Validate algorithm
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valid_algorithms = {"semantic", "bm25", "hybrid"}
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if algorithm not in valid_algorithms:
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algorithm = "hybrid"
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# Validate fusion method
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valid_fusions = {"rrf", "dbsf"}
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if fusion not in valid_fusions:
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fusion = "rrf"
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# Validate score threshold
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score_threshold = max(0.0, min(1.0, float(score_threshold)))
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# Execute search using the appropriate algorithm
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from nextcloud_mcp_server.search import (
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BM25HybridSearchAlgorithm,
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SemanticSearchAlgorithm,
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)
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# Select search algorithm
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if algorithm == "semantic":
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search_algo = SemanticSearchAlgorithm(score_threshold=score_threshold)
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else:
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search_algo = BM25HybridSearchAlgorithm(
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score_threshold=score_threshold, fusion=fusion
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)
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# Request extra results to handle offset
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search_limit = limit + offset
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# Execute search
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all_results = []
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if doc_types and isinstance(doc_types, list):
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for doc_type in doc_types:
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if doc_type:
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results = await search_algo.search(
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query=query,
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user_id=user_id,
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limit=search_limit,
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doc_type=doc_type,
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)
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all_results.extend(results)
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all_results.sort(key=lambda r: r.score, reverse=True)
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else:
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all_results = await search_algo.search(
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query=query,
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user_id=user_id,
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limit=search_limit,
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)
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# Deduplicate results by document (multiple chunks may come from same doc)
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# Keep highest-scoring chunk per document
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doc_map: dict[str, Any] = {} # key: "doc_type:id" -> best result
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for result in all_results:
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# Build document key from type and ID
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doc_id = result.id
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if result.metadata:
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# Use note_id if present (for notes), otherwise use result.id
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doc_id = result.metadata.get("note_id", result.id)
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doc_key = f"{result.doc_type}:{doc_id}"
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# Keep only the highest-scoring chunk per document
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if doc_key not in doc_map or result.score > doc_map[doc_key].score:
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doc_map[doc_key] = result
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# Convert back to list and sort by score
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deduplicated_results = sorted(
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doc_map.values(), key=lambda r: r.score, reverse=True
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)
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# Calculate total and apply pagination (on deduplicated results)
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total_found = len(deduplicated_results)
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paginated_results = deduplicated_results[offset : offset + limit]
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# Format results for Unified Search
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formatted_results = []
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for result in paginated_results:
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# Get document ID (prefer note_id for notes)
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doc_id = result.id
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if result.metadata and "note_id" in result.metadata:
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doc_id = result.metadata["note_id"]
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result_data: dict[str, Any] = {
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"id": doc_id,
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"doc_type": result.doc_type,
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"title": result.title,
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"score": result.score,
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}
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# Include excerpt/chunk if requested (full content, no truncation)
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if include_chunks and result.excerpt:
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result_data["excerpt"] = result.excerpt
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# Include navigation metadata from result.metadata
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if result.metadata:
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# File path and mimetype for files
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if "path" in result.metadata:
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result_data["path"] = result.metadata["path"]
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if "mime_type" in result.metadata:
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result_data["mime_type"] = result.metadata["mime_type"]
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# Deck card navigation
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if "board_id" in result.metadata:
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result_data["board_id"] = result.metadata["board_id"]
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if "card_id" in result.metadata:
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result_data["card_id"] = result.metadata["card_id"]
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# Calendar event metadata
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if "calendar_id" in result.metadata:
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result_data["calendar_id"] = result.metadata["calendar_id"]
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if "event_uid" in result.metadata:
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result_data["event_uid"] = result.metadata["event_uid"]
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formatted_results.append(result_data)
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response_data: dict[str, Any] = {
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"results": formatted_results,
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"total_found": total_found,
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"algorithm_used": algorithm,
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}
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# Optional PCA coordinates
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if include_pca and len(paginated_results) >= 2:
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try:
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from nextcloud_mcp_server.vector.visualization import (
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compute_pca_coordinates,
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)
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if search_algo.query_embedding is not None:
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query_embedding = search_algo.query_embedding
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else:
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from nextcloud_mcp_server.embedding.service import (
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get_embedding_service,
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)
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embedding_service = get_embedding_service()
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query_embedding = await embedding_service.embed(query)
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pca_data = await compute_pca_coordinates(
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paginated_results, query_embedding
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)
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response_data["pca_data"] = pca_data
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except Exception as e:
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logger.warning(f"Failed to compute PCA for unified search: {e}")
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return JSONResponse(response_data)
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except Exception as e:
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logger.error(f"Error in unified search: {e}")
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return JSONResponse(
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{"error": "Internal error", "message": str(e)},
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status_code=500,
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)
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async def vector_search(request: Request) -> JSONResponse:
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"""POST /api/v1/vector-viz/search - Vector search for visualization.
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+46
-14
@@ -8,8 +8,11 @@ use OCA\Astroglobe\AppInfo\Application;
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use OCA\Astroglobe\Service\McpServerClient;
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use OCA\Astroglobe\Service\McpTokenStorage;
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use OCA\Astroglobe\Settings\Admin as AdminSettings;
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use OCP\Files\FileInfo;
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use OCP\Files\IMimeTypeDetector;
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use OCP\IConfig;
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use OCP\IL10N;
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use OCP\IPreview;
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use OCP\IURLGenerator;
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use OCP\IUser;
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use OCP\Search\IProvider;
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@@ -35,6 +38,8 @@ class SemanticSearchProvider implements IProvider {
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private IConfig $config,
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private IL10N $l10n,
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private IURLGenerator $urlGenerator,
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private IMimeTypeDetector $mimeTypeDetector,
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private IPreview $previewManager,
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private LoggerInterface $logger,
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) {
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}
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@@ -174,12 +179,14 @@ class SemanticSearchProvider implements IProvider {
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$title = $result['title'] ?? $this->l10n->t('Untitled');
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$excerpt = $result['excerpt'] ?? '';
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$score = $result['score'] ?? 0;
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$id = $result['id'] ?? null;
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$mimeType = $result['mime_type'] ?? null;
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// Build resource URL based on document type
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$resourceUrl = $this->buildResourceUrl($result);
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// Build thumbnail URL based on document type
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$thumbnailUrl = $this->buildThumbnailUrl($docType);
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// Get icon and thumbnail based on document type
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[$thumbnailUrl, $iconClass] = $this->getIconAndThumbnail($docType, $id, $mimeType);
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// Subline shows full excerpt if available, otherwise document type and score
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if (!empty($excerpt)) {
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@@ -199,7 +206,7 @@ class SemanticSearchProvider implements IProvider {
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$title,
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$subline,
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$resourceUrl,
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'', // icon class (empty, using thumbnail)
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$iconClass,
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false // not rounded
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);
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}
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@@ -239,19 +246,44 @@ class SemanticSearchProvider implements IProvider {
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}
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/**
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* Get thumbnail URL for document type.
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* Get icon and thumbnail for document type.
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*
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* Returns [thumbnailUrl, iconClass] tuple.
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* For files, uses mimetype-specific icons and preview thumbnails when available.
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* For other document types, uses appropriate icon classes.
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*
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* @return array{string, string} [thumbnailUrl, iconClass]
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*/
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private function buildThumbnailUrl(string $docType): string {
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// Use app icons for different document types
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return match ($docType) {
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'note' => $this->urlGenerator->imagePath('notes', 'app.svg'),
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'file' => $this->urlGenerator->imagePath('files', 'app.svg'),
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'deck_card' => $this->urlGenerator->imagePath('deck', 'app.svg'),
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'calendar', 'calendar_event' => $this->urlGenerator->imagePath('calendar', 'app.svg'),
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'news_item' => $this->urlGenerator->imagePath('news', 'app.svg'),
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'contact' => $this->urlGenerator->imagePath('contacts', 'app.svg'),
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default => $this->urlGenerator->imagePath(Application::APP_ID, 'app.svg'),
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private function getIconAndThumbnail(string $docType, ?string $id, ?string $mimeType): array {
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if ($docType === 'file' && $id !== null && $mimeType !== null) {
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// For files, check if preview is supported
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$thumbnailUrl = '';
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if ($this->previewManager->isMimeSupported($mimeType)) {
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$thumbnailUrl = $this->urlGenerator->linkToRouteAbsolute(
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'core.Preview.getPreviewByFileId',
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['x' => 32, 'y' => 32, 'fileId' => $id]
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);
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}
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// Get mimetype-specific icon class
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$iconClass = $mimeType === FileInfo::MIMETYPE_FOLDER
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? 'icon-folder'
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: $this->mimeTypeDetector->mimeTypeIcon($mimeType);
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return [$thumbnailUrl, $iconClass];
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}
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// For non-file document types, use icon classes
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$iconClass = match ($docType) {
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'note' => 'icon-notes',
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'deck_card' => 'icon-deck',
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'calendar', 'calendar_event' => 'icon-calendar',
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'news_item' => 'icon-rss',
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'contact' => 'icon-contacts',
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default => 'icon-file',
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};
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return ['', $iconClass];
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}
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/**
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