feat: Implement per-chunk vector visualization with context expansion

Major improvements to vector visualization page:
- Refactor PCA to display individual chunks instead of averaged documents
- Add context expansion module for fetching surrounding text from notes and PDFs
- Update deduplication to use (doc_id, doc_type, chunk_start, chunk_end) keys
- Fix Alpine.js rendering with chunk-specific keys including offsets
- Refactor authentication helper to return NextcloudClient for better reuse
- Add async context manager support to NextcloudClient

Technical details:
- viz_routes.py: Fetch specific chunk vectors instead of averaging per document
- context.py: New module supporting both notes and PDF text extraction via PyMuPDF
- search algorithms: Extract page_number, chunk_index, total_chunks from Qdrant
- vector-viz.js/html: Use chunk positions in expansion tracking keys

This enables users to see which specific chunks match their query
and view them with surrounding context in the PCA visualization.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

nextcloud_mcp_server/search/algorithms.py

@@ -133,6 +133,9 @@ class SearchResult:
         metadata: Additional algorithm-specific metadata
         chunk_start_offset: Character position where chunk starts (None if not available)
         chunk_end_offset: Character position where chunk ends (None if not available)
+        page_number: Page number for PDF documents (None for other doc types)
+        chunk_index: Zero-based index of this chunk in the document
+        total_chunks: Total number of chunks in the document
     """
 
     id: int
@@ -143,6 +146,9 @@ class SearchResult:
     metadata: dict[str, Any] | None = None
     chunk_start_offset: int | None = None
     chunk_end_offset: int | None = None
+    page_number: int | None = None
+    chunk_index: int = 0
+    total_chunks: int = 1
 
     def __post_init__(self):
         """Validate score is non-negative.