Introduces a one-shot `init` service in docker-compose that runs Postgres
migrations, Neo4j index setup, and library-type seeding on every `up`.
Long-running services (`app`, `mcp`, `worker`) now depend on its
successful completion via `service_completed_successfully`, blocking the
stack on configuration errors (missing embedding model, dimension
mismatch, unreachable DB) rather than serving silent zero-result
searches.
Also standardizes reranker test fixtures to use the `/v1` OpenAI-style
base URL convention used across other service clients.
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
