Refine the phase-2 integration spec to reflect implementation details:
- Change `resolved_libraries` from `set[str]` to ordered `list[str]`
- Document `MCPToken.allowed_libraries` as JSONField (not M2M) since
Library lives in Neo4j, not Django's ORM
- Clarify that `Library.workspace_id` is a content-routing attribute,
not an authorization axis
- Describe retirement of the three-branch `_WORKSPACE_SCOPE_CLAUSE` in
favor of a single `lib.uid IN $resolved_libraries` check
- Specify team JWT resolution via `TeamWorkspaceAssignment` DB join
- Note admin UI materializes full Library UID list explicitly
Implement hybrid search pipeline combining vector, fulltext, and graph
search across Neo4j, with cross-attention reranking via Synesis
(Qwen3-VL-Reranker-2B) `/v1/rerank` endpoint.
- Add SearchService with vector, fulltext, and graph search strategies
- Add SynesisRerankerClient for multimodal reranking via HTTP API
- Add search API endpoint (POST /search/) with filtering by library,
collection, and library_type
- Add SearchRequest/Response serializers and image search results
- Add "nonfiction" to library_type choices
- Consolidate reranker stack from two models to single Synesis service
- Handle image analysis_status as "skipped" when analysis is unavailable
- Add comprehensive tests for search pipeline and reranker client
- Introduced a new vision analysis service to classify, describe, and extract text from images.
- Enhanced the Image model with fields for OCR text, vision model name, and analysis status.
- Added a new "nonfiction" library type with specific chunking and embedding configurations.
- Updated content types to include vision prompts for various library types.
- Integrated vision analysis into the embedding pipeline, allowing for image analysis during document processing.
- Implemented metrics to track vision analysis performance and usage.
- Updated UI components to display vision analysis results and statuses in item details and the embedding dashboard.
- Added migration for new vision model fields and usage tracking.
- Implemented custom form widgets for date, time, and datetime fields with DaisyUI styling.
- Created utility functions for formatting dates, times, and numbers according to user preferences.
- Developed views for profile settings, API key management, and notifications, including health check endpoints.
- Added URL configurations for Themis tests and main application routes.
- Established test cases for custom widgets to ensure proper functionality and integration.
- Defined project metadata and dependencies in pyproject.toml for package management.
