A single global "Ignored" person row, marked is_ignored=true, that the
frontend lazily creates on first use to hold strangers, false
detections, and faces the user doesn't want bound to a real person.
Schema (new migration 2026-04-29-000200_add_is_ignored):
- persons.is_ignored BOOLEAN NOT NULL DEFAULT 0
- Partial index on (is_ignored) WHERE is_ignored = 1; small WHERE
set means a tiny index that only ever services the bucket lookup.
Why a real persons row instead of a separate table or status enum:
- face_detections.person_id stays a clean foreign key — no special
code paths for "ignored faces" anywhere else in the schema.
- The cluster-suggester already filters by `person_id IS NULL`, so
bound-to-ignored faces are naturally excluded from re-clustering
without any change.
- merge / rename / delete all work on it with the existing routes
(the management UI just hides it from default views).
DAO additions / changes:
- get_or_create_ignored_person (idempotent; race-safe via the
UNIQUE COLLATE NOCASE on persons.name + retry-on-409 fallback).
- list_persons gains an include_ignored parameter; default false
so the management screen hides the bucket unless asked.
- find_persons_by_names_ci filters is_ignored=0 in SQL so the
auto-bind path can NEVER target the bucket — even if the user
happens to tag photos as "Ignored", the heuristic look-up skips
it. Bucket assignment is always an explicit operator action.
- update_person accepts is_ignored: Option<bool> so a person can
be moved into / out of the bucket without a delete + recreate.
Routes:
- POST /persons/ignore-bucket — returns the bucket, creating it on
first call. Frontend uses this lazily right before binding.
- GET /persons gains ?include_ignored=true; default behavior
unchanged.
- PATCH /persons/{id} now accepts is_ignored.
Tests: ignore_bucket_idempotent_and_filters_auto_bind covers the
contract: bucket is idempotent across calls, find_persons_by_names_ci
skips it (even on exact name match), default list_persons hides it,
include_ignored=true surfaces it. All other tests updated to pass
the new is_ignored: false / Option<bool> fields explicitly.
cargo test --lib: 181/0; fmt + clippy clean for new code.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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>
- Few-shot injection on /insights/generate/agentic: compresses prior
training_messages into trajectory blocks (tool calls + result summaries)
and injects into the system prompt. Hardcoded default ids with optional
request override.
- New fewshot_source_ids column on photo_insights (+ migration) to track
which exemplars influenced a given row, for downstream training-set
filtering. Chat amend rows stamp None with a lineage note.
- Ollama client now remembers which server (primary/fallback) most
recently succeeded and tries it first on the next call, via a shared
Arc<AtomicBool>. Avoids re-404ing the primary on every agent iteration
when the chosen model only lives on the fallback.
- Demote noisy logs: daily_summary "Summary match" lines to debug;
inner chat_with_tools non-2xx body log from error to warn (outer
layer owns the terminal-error signal).
- Drift-guard tests for summarize_tool_result covering the success /
empty / error / unknown shape for every tool.
- Tidy: three pre-existing clippy warnings cleaned up.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds a `backend` column to photo_insights (default 'local', migration
2026-04-20-000000) and a corresponding optional `backend` field on the
agentic request. When a request sets backend=hybrid:
- The local Ollama vision model is called once via describe_image to
produce a text description.
- The description is inlined into the first user message as text —
no base64 image is ever sent to the chat model.
- The agentic tool-calling loop and title generation route through an
OpenRouterClient (dispatched via &dyn LlmClient), letting the user
pick any tool-capable model from OpenRouter per request.
- describe_photo is removed from the offered tools since the description
is already present.
Embeddings and vision stay on local Ollama regardless of backend.
Hybrid mode requires OPENROUTER_API_KEY; handlers return a clear error
when hybrid is requested without it, and also when the selected
OpenRouter model lacks tool-calling support.
AppState gains an optional openrouter client built from
OPENROUTER_API_KEY / OPENROUTER_BASE_URL / OPENROUTER_DEFAULT_MODEL /
OPENROUTER_EMBEDDING_MODEL / attribution headers. Default model is
anthropic/claude-sonnet-4.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds blake3 content hashing as the basis for derivative dedup
(thumbnails, HLS) across libraries. Computed inline by the watcher on
ingest and by a new `backfill_hashes` binary for historical rows.
Key changes:
- `content_hash` and `size_bytes` are now populated on new image_exif
rows; a new ExifDao surface (`get_rows_missing_hash`,
`backfill_content_hash`, `find_by_content_hash`) supports backfill and
future hash-keyed lookups.
- The watcher now registers every image/video in image_exif, not just
files with parseable EXIF. EXIF becomes optional enrichment; videos
and other non-EXIF files still get a hashed row. This also makes
DB-indexed sort/filter cover the full library.
- `/image` thumbnail serve dual-looks up hash-keyed path first, then
falls back to the legacy mirrored layout.
- Upload flow accepts `?library=` query param + hashes uploaded files.
- Store_exif logs the underlying Diesel error on insert failure so
constraint violations surface instead of hiding behind a generic
InsertError.
- New migration normalizes rel_path separators to forward slash across
all tables, deduplicating any rows that collide after normalization.
Fixes spurious UNIQUE violations from mixed backslash/forward-slash
paths on Windows ingest.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Adds a `libraries` registry table and threads library_id through
per-instance metadata tables (image_exif, photo_insights,
entity_photo_links, video_preview_clips). File-path columns renamed to
rel_path to make the relative-to-root semantics explicit. Adds
content_hash + size_bytes on image_exif to support future hash-keyed
thumbnail/HLS dedup. Tags and favorites stay library-agnostic so they
share across libraries by rel_path.
Behavior is unchanged: a single primary library (id=1) is seeded from
BASE_PATH on first boot; all handlers and DAOs route through it as a
transitional shim until the API gains a library query param.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Implements persistent cross-photo knowledge memory so the agentic
insight loop can learn and recall facts about people, places, and
events across the photo collection.
Changes:
- photo_insights: drop UNIQUE(file_path) + INSERT OR REPLACE, replace
with append-only rows + is_current flag for insight history retention
- New tables: entities, entity_facts, entity_photo_links with FK
constraints and confidence scoring
- KnowledgeDao trait + SqliteKnowledgeDao with upsert, merge, and
corroboration (confidence +0.1 on duplicate fact detection)
- Four new agent tools: recall_entities, recall_facts_for_photo,
store_entity, store_fact (with object_entity_id FK support)
- Cameron entity auto-seeded with stable ID injected into system prompt
- Pre-run photo link clearing + post-loop source_insight_id backfill
- Audit REST API: GET/PATCH/DELETE /knowledge/entities/{id},
POST /knowledge/entities/merge, GET/PATCH/DELETE /knowledge/facts/{id},
GET /knowledge/recent
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Backend (Rust/Actix-web):
- Add video_preview_clips table and PreviewDao for tracking preview generation
- Add ffmpeg preview clip generator: 10 equally-spaced 1s segments at 480p with CUDA NVENC auto-detection
- Add PreviewClipGenerator actor with semaphore-limited concurrent processing
- Add GET /video/preview and POST /video/preview/status endpoints
- Extend file watcher to detect and queue previews for new videos
- Use relative paths consistently for DB storage (matching EXIF convention)
Frontend (React Native/Expo):
- Add VideoWall grid view with 2-3 column layout of looping preview clips
- Add VideoWallItem component with ActiveVideoPlayer sub-component for lifecycle management
- Add useVideoWall hook for batch status polling with 5s refresh
- Add navigation button in grid header (visible when videos exist)
- Use TextureView surface type to fix Android z-ordering issues
- Optimize memory: players only mount while visible via FlatList windowSize
- Configure ExoPlayer buffer options and caching for short clips
- Tap to toggle audio focus, long press to open in full viewer
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Implement database-level sorting with composite indexes for efficient date and tag queries. Add pagination metadata support and optimize tag count queries using batch processing.
Implements Phase 1 & 2 of Google Takeout RAG integration:
- Database migrations for calendar_events, location_history, search_history
- DAO implementations with hybrid time + semantic search
- Parsers for .ics, JSON, and HTML Google Takeout formats
- Import utilities with batch insert optimization
Features:
- CalendarEventDao: Hybrid time-range + semantic search for events
- LocationHistoryDao: GPS proximity with Haversine distance calculation
- SearchHistoryDao: Semantic-first search (queries are embedding-rich)
- Batch inserts for performance (1M+ records in minutes vs hours)
- OpenTelemetry tracing for all database operations
Import utilities:
- import_calendar: Parse .ics with optional embedding generation
- import_location_history: High-volume GPS data with batch inserts
- import_search_history: Always generates embeddings for semantic search
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Implements foundation for EXIF-based photo search capabilities:
- Add geo.rs module with GPS distance calculations (Haversine + bounding box)
- Extend FilesRequest with EXIF search parameters (camera, GPS, date, media type)
- Add MediaType enum and DateTakenAsc/DateTakenDesc sort options
- Create date_taken index migration for efficient date queries
- Implement ExifDao methods: get_exif_batch, query_by_exif, get_camera_makes
- Add FileWithMetadata struct for date-aware sorting
- Implement date sorting with filename extraction fallback
- Make extract_date_from_filename public for reuse
Next: Integrate EXIF filtering into list_photos() and enhance get_all_tags()
