faces: phase 2 — schema + manual face/person CRUD

Land the persistence model and HTTP surface for local face recognition.
Inference still lives in Apollo (Phase 1); this side adds the data home
plus every endpoint Apollo's UI and FileViewer-React will consume.

Schema (new migration 2026-04-29-000000_add_faces):
  - persons: visual identities. Optional entity_id bridges to the
    existing knowledge-graph entities table; auto-bridging is left to
    the management UI (we don't muddy LLM provenance from face rows).
    UNIQUE(name COLLATE NOCASE) so 'alice' / 'Alice' fold to one row.
  - face_detections: keyed on content_hash (cross-library dedup), with
    status='detected' carrying bbox + 512-d embedding BLOB, and
    'no_faces' / 'failed' marker rows that tell Phase 3's file watcher
    not to re-scan. Marker invariant enforced via CHECK; partial UNIQUE
    on content_hash WHERE status='no_faces' guards against double-marks.

Schema regenerated with `diesel print-schema` against a clean migration
run; joinables added for face_detections → libraries / persons and
persons → entities.

face_client.rs (sibling of apollo_client.rs):
  - reqwest multipart, 60 s timeout (CPU inference on a backlog can be
    slow; bounded threadpool on Apollo serializes calls anyway).
  - FaceDetectError::{Permanent, Transient, Disabled} — Phase 3 keys
    its marker-row decision on this. 422 → mark failed, 5xx → defer.
  - APOLLO_FACE_API_BASE_URL falls back to APOLLO_API_BASE_URL when
    unset; both unset = is_enabled() false, callers no-op.

faces.rs (DAO + handlers):
  - SqliteFaceDao implements the full FaceDao trait; person face counts
    go through sql_query because diesel's BoxedSelectStatement +
    group_by trips trait-resolver recursion.
  - merge_persons re-points face rows in a transaction, copies notes
    when target's are empty, deletes src.
  - manual POST /image/faces resolves content_hash through image_exif,
    crops the user-drawn bbox with 10% padding (detector wants context
    around ears/jaw), POSTs the crop to face_client.embed for a real
    ArcFace vector, then inserts source='manual'.
  - Cluster-suggest (Phase 6) gets its data from
    GET /faces/embeddings — base64-encoded paged BLOBs so Apollo's
    DBSCAN can stream them without ImageApi pre-aggregating.

Endpoints registered alongside add_*_services in main.rs:
  GET    /faces/stats?library=
  GET    /faces/embeddings?library=&unassigned=&limit=&offset=
  GET    /image/faces?path=&library=
  POST   /image/faces                        (manual create via embed)
  PATCH  /image/faces/{id}
  DELETE /image/faces/{id}
  GET    /persons?library=
  POST   /persons
  GET    /persons/{id}
  PATCH  /persons/{id}
  DELETE /persons/{id}?cascade=set_null|delete   (set_null default)
  POST   /persons/{id}/merge
  GET    /persons/{id}/faces?library=

The file-watch hook (Phase 3) and the rerun-on-one-photo handler
(Phase 6) live behind the FaceDao methods marked dead_code today —
they're called only when those phases land. Same shape for the trait
methods that aren't reached by Phase 2 routes.

Tests: 3 DAO unit tests cover person CRUD + case-insensitive uniqueness,
marker-row idempotency (mark_status is a no-op when any row exists),
and merge re-pointing faces.

Cargo.toml: reqwest gains the `multipart` feature.

cargo build / cargo test --lib / cargo fmt / cargo clippy --all-targets
all clean for the new code; the two pre-existing test_path_excluder
failures and the pre-existing sort_by clippy warnings are unrelated and
present on master.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Cameron Cordes
2026-04-29 18:03:42 +00:00
parent 6642db3c8b
commit 860169032b
13 changed files with 2344 additions and 1 deletions

View File

@@ -49,7 +49,7 @@ opentelemetry-appender-log = "0.31.0"
tempfile = "3.20.0"
regex = "1.11.1"
exif = { package = "kamadak-exif", version = "0.6.1" }
reqwest = { version = "0.12", features = ["json", "stream"] }
reqwest = { version = "0.12", features = ["json", "stream", "multipart"] }
async-stream = "0.3"
tokio-util = { version = "0.7", features = ["io"] }
bytes = "1"