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/models/semantic.py

@@ -35,6 +35,29 @@ class SemanticSearchResult(BaseModel):
     chunk_end_offset: Optional[int] = Field(
         default=None, description="Character position where chunk ends in document"
     )
+    page_number: Optional[int] = Field(
+        default=None, description="Page number for PDF documents"
+    )
+    # Context expansion fields (optional, populated when include_context=True)
+    has_context_expansion: bool = Field(
+        default=False, description="Whether context expansion was performed"
+    )
+    marked_text: Optional[str] = Field(
+        default=None,
+        description="Full text with position markers around matched chunk",
+    )
+    before_context: Optional[str] = Field(
+        default=None, description="Text before the matched chunk"
+    )
+    after_context: Optional[str] = Field(
+        default=None, description="Text after the matched chunk"
+    )
+    has_before_truncation: Optional[bool] = Field(
+        default=None, description="Whether before_context was truncated"
+    )
+    has_after_truncation: Optional[bool] = Field(
+        default=None, description="Whether after_context was truncated"
+    )
 
 
 class SemanticSearchResponse(BaseResponse):